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1,{value:"2 commercial SaaS products"}]}},{id:"649c1c667df15a13847d77da",slug:ak,title:"Skills Section",content:b,bucket:d,created_at:s,created_by:c,modified_at:s,created:s,status:e,thumbnail:b,published_at:s,modified_by:c,type:ak,metadata:{title:"Our core skills",skills:[{id:"649c1c5f7df15a13847d77b9",slug:"energy",title:"Renewable Energy",content:b,bucket:d,created_at:al,created_by:c,modified_at:"2023-09-26T14:10:12.653Z",created:al,status:"draft",thumbnail:b,published_at:"2023-03-29T15:03:47.472Z",modified_by:c,publish_at:a,unpublish_at:a,type:k,metadata:{skill:[],content:"\u003Cp\u003EWe have a growing portfolio of work applying forecasting and optimisation techniques to energy sector challenges. Project examples include the evaluation of forecast accuracy and weather regimes on the economic dispatch and spinning reserve requirements of fossil fuel generators, analysis of factors driving unscheduled downtime for a wind farm and the optimisation of production to minimise energy costs and CO2 emissions.\u003C\u002Fp\u003E",icon:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F69b1d7d0-9a40-11ec-852b-ab884ffd8c85-Energy.png",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F69b1d7d0-9a40-11ec-852b-ab884ffd8c85-Energy.png"}}},{id:"649c1c5f7df15a13847d77b8",slug:"weather",title:am,content:b,bucket:d,created_at:an,created_by:c,modified_at:ao,created:an,status:e,thumbnail:b,published_at:ao,modified_by:c,publish_at:a,unpublish_at:a,type:k,metadata:{skill:[],content:ap,icon:{url:aq,imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F69b38580-9a40-11ec-852b-ab884ffd8c85-Weather.png"}}},{id:"649c1c607df15a13847d77be",slug:"data-visualisation",title:ar,content:b,bucket:d,created_at:as,created_by:c,modified_at:at,created:as,status:e,thumbnail:b,published_at:at,modified_by:c,publish_at:a,unpublish_at:a,type:k,metadata:{skill:[],content:au,icon:{url:av,imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F699723e0-9a40-11ec-852b-ab884ffd8c85-DataVis.png"}}},{id:"649c1c5f7df15a13847d77bb",slug:"data-science-kzebxpxq",title:aw,content:b,bucket:d,created_at:ax,created_by:c,modified_at:ay,created:ax,status:e,thumbnail:b,published_at:ay,modified_by:c,publish_at:a,unpublish_at:a,type:k,metadata:{skill:[],content:az,icon:{url:aA,imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F69963980-9a40-11ec-852b-ab884ffd8c85-DataScience.png"}}},{id:"649c1c607df15a13847d77bd",slug:"full-stack-system-engineering",title:aB,content:b,bucket:d,created_at:aC,created_by:c,modified_at:aD,created:aC,status:e,thumbnail:b,published_at:aD,modified_by:c,publish_at:a,unpublish_at:a,type:k,metadata:{skill:[],content:aE,icon:{url:aF,imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F69b2c230-9a40-11ec-852b-ab884ffd8c85-FSEng.png"}}},{id:"649c1c607df15a13847d77bc",slug:"earth-observation-eo",title:aG,content:b,bucket:d,created_at:aH,created_by:c,modified_at:aI,created:aH,status:e,thumbnail:b,published_at:aI,modified_by:c,publish_at:a,unpublish_at:a,type:k,metadata:{skill:[],content:aJ,icon:{url:aK,imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F6997c020-9a40-11ec-852b-ab884ffd8c85-EO.png"}}}]}},{id:"649c1c637df15a13847d77d0",slug:"about-us-content-banner-w-image",title:"About Us Content Banner W\u002F Image",content:b,bucket:d,created_at:t,created_by:c,modified_at:t,created:t,status:e,thumbnail:b,published_at:t,modified_by:c,type:l,metadata:{background_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fb314ff80-9f84-11ec-a634-2f1716dd45af-Renewable-Energy-and-Farmland.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fb314ff80-9f84-11ec-a634-2f1716dd45af-Renewable-Energy-and-Farmland.jpg"},text:a,cta_text:a,background_color:a}},{id:"649c1c657df15a13847d77d9",slug:aL,title:"Leadership Team Section",content:b,bucket:d,created_at:u,created_by:c,modified_at:u,created:u,status:e,thumbnail:b,published_at:u,modified_by:c,type:aL,metadata:{title:"Our leadership team",leadership:[{id:"649c1c5d7df15a13847d77b1",slug:"colin-mckinnon",title:J,content:b,bucket:d,created_at:aM,created_by:c,modified_at:"2023-09-26T14:07:36.92Z",created:aM,status:e,thumbnail:b,modified_by:c,publish_at:a,published_at:"2023-01-12T12:13:04.084Z",unpublish_at:a,type:v,metadata:{name:J,role:aN,bio:aO,photo:{url:aP,imgix_url:aQ},email:aR,linkedin:aS}

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Direct CLR arises from the risk of legal or regulatory action against the FI itself due to climate-related activities. Indirect CLR stems from the exposure to portfolio companies or other entities that may face climate-related legal challenges\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EMDY Legal and Cariad Climate have jointly developed a methodology to enable FIs to assess climate liability risk (CLR). This approach would empower FIs to proactively identify, evaluate, and manage - or mitigate - CLR while also ensuring transparency in climate-related matters.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003ERecognising the limitations of their spreadsheet-based methodology, MDY Legal and Cariad Climate sought to create a more accessible online tool to streamline the assessment process for FIs, thereby making it easier to apply the developed methodology. We were contracted to initiate the process of converting this existing risk-based methodology into a user-friendly and visually engaging online tool.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E",image:{url:S,imgix_url:T},image_attribution:a,process:"\u003Cp id=\"isPasted\"\u003EThe project was funded by Innovate UK through its Business Growth initiative and involved several strands of work:\u003C\u002Fp\u003E\u003Cp\u003E&bull; &nbsp; &nbsp;\u003Cstrong\u003EExisting methodology review\u003C\u002Fstrong\u003E: Our consultants analysed the client&rsquo;s spreadsheet approach and evaluated the current set of climate indictors and the CLR scoring mechanism.\u003C\u002Fp\u003E\u003Cp\u003E&bull; &nbsp; \u003Cstrong\u003E&nbsp;Visualisation:\u003C\u002Fstrong\u003E Based on this review, and in conversation with the clients, we developed a variety of data visualisations to demonstrate different ways the assessment results could be displayed.\u003C\u002Fp\u003E\u003Cp\u003E&bull; &nbsp; &nbsp;\u003Cstrong\u003EUser experience \u002F User interface\u003C\u002Fstrong\u003E: Our UX designers defined detailed &ldquo;activities&rdquo; and produced wireframes to describe the user interface and experience.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E&bull; &nbsp; \u003Cstrong\u003E&nbsp;System requirements and architecture\u003C\u002Fstrong\u003E: In collaboration with the client, our software developers established a comprehensive set of system requirements, including a detailed system architecture, to guide the development of the prototype CLR online tool.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E",solution:"\u003Cp\u003EBy the end of the project, we successfully delivered the essential components for the development of the online CLR tool, tailored to the client&rsquo;s needs:&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E1) intuitive visualisations to effectively communicate assessment results;&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E2) a clear definition of user roles and how each role would interact with the tool (user interface\u002F user experience);&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E3) a comprehensive framework for the tool&rsquo;s development (system requirements and architecture).\u003C\u002Fp\u003E",solution_list_items:[],solution_image:a,solution_image_attribution:a,impact:"\u003Cp id=\"isPasted\"\u003EAlthough it was beyond the scope of the project to develop the final tool, our technical contributions provided a solid foundation for future development efforts ensuring the tool aligns with end-user expectations. The deliverables from this project offered significant value to our clients, including:\u003C\u002Fp\u003E\u003Cp id=\"isPasted\"\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003E&bull; &nbsp; &nbsp;Clarifying scope: Providing a clear understanding of the requirements and scope for the online tool.\u003C\u002Fp\u003E\u003Cp\u003E&bull; &nbsp; &nbsp;Informing development: Establishing a strong foundation for future development efforts.\u003C\u002Fp\u003E\u003Cp\u003E&bull; &nbsp; &nbsp;Identifying gaps: Offering inspiration and thought-provoking insights to build on the methodology.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp id=\"isPasted\"\u003ERachel Child, Cariad - &ldquo;I was very impressed by how quickly the IEA team understood our requirements for the tool and translated our methodology into a user-friendly and accessible online tool design.&rdquo; &nbsp;\u003C\u002Fp\u003E\u003Cp\u003E&nbsp;\u003C\u002Fp\u003E\u003Cp\u003EDiane Harris, \u003Ca href=\"https:\u002F\u002Fwww.mdy.co.uk\u002F\"\u003EMDY Legal\u003C\u002Fa\u003E - &ldquo;The IEA team were great to work with and very patient with us as we went up the on-line tool learning curve - they clearly understood what we were trying to achieve and have provided us with a very user-friendly tool design.&rdquo;\u003C\u002Fp\u003E",testimonial:"\u003Cp id=\"isPasted\"\u003ERachel Child, Cariad - &ldquo;I was very impressed by how quickly the IEA team understood our requirements for the tool and translated our methodology into a user-friendly and accessible online tool design.&rdquo; &nbsp;\u003C\u002Fp\u003E\u003Cp\u003E&nbsp;\u003C\u002Fp\u003E\u003Cp\u003EDiane Harris, MDY Legal - &ldquo;The IEA team were great to work with and very patient with us as we went up the on-line tool learning curve - they clearly understood what we were trying to achieve and have provided us with a very user-friendly tool design.&rdquo;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E",project_metadata:{title:bD,description:"Financial institutions (FIs) are increasingly exposed to climate liability risk (CLR), both directly and indirectly. Direct

1CLR arises from the risk of legal or regulatory action against the FI itself due to climate-related activities. Indirect CLR stems from the exposure to portfolio companies or other entities that may face climate-related legal challenges",meta_image:{url:S,imgix_url:T}}},{slug:"machine-learning-for-energy-consumption-forecasting",title:"Machine learning for energy consumption forecasting ",top_intro__challenge_old:a,top_intro__challenge:"\u003Cp id=\"isPasted\"\u003E\u003Ca class=\"action--text\" href=\"https:\u002F\u002Fenergysavingbear.com\u002F\"\u003EEnergy Saving Bear Limited\u003C\u002Fa\u003E (ESB) is a company that provides energy monitoring services to buildings: they install sensors, collect energy consumption data and display information in dashboard reports to inform customers. Their monitors not only offer a way to track building energy usage, but also to understand it - ultimately leading to targeted and quantifiable savings for building owners.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EESB was seeking to enhance its energy saving monitoring service by introducing a machine learning component, with the aim of forecasting hourly sensor consumption and triggering alerts if actual usage deviated from agreed thresholds. ESB felt that manually reviewing and commenting on the monitoring reports was time-consuming and expensive. They wanted to explore if machine learning could enhance analysis speed, improve appraisals, enhance alert accuracy and discover more energy-saving opportunities.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EWe were contracted to help develop the predictive machine learning model and review ESB&rsquo;s current dashboard monitoring reports to improve usability.\u003C\u002Fp\u003E",image:{url:bE,imgix_url:bF},image_attribution:a,process:"\u003Cp id=\"isPasted\"\u003EThe project was funded by Innovate UK through its Business Growth initiative. As part of our brief we:\u003C\u002Fp\u003E\u003Cp\u003E- Conducted a literature review to advise ESB on the machine learning methods to deploy.\u003C\u002Fp\u003E\u003Cp\u003E- Undertook a thorough review of the dashboard reports generated by ESB to provide feedback on how these could be improved. Specifically, the client was interested to focus on &ldquo;exception reporting&rdquo;, so relevant changes in consumption could be reported promptly to clients for their quick response.\u003C\u002Fp\u003E\u003Cp\u003E- Performed an analysis of the historical electricity consumption data from a collection of buildings. This data was then used to develop a machine learning model to predict energy consumption in the future.\u003C\u002Fp\u003E",solution:"\u003Cp id=\"isPasted\"\u003EThe proposed solution involved constructing individual XGBoost models for each building using one month of historical data and retraining monthly. This approach balances model accuracy and system complexity while capturing intra-building correlations.\u003C\u002Fp\u003E\u003Cp\u003EKey features of the model included:\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cstrong\u003E- Model level:\u003C\u002Fstrong\u003E One model per building.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cstrong\u003E- Training data:\u003C\u002Fstrong\u003E One month of historical data.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cstrong\u003E- Retraining:\u003C\u002Fstrong\u003E Monthly updates for improved accuracy.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cstrong\u003E- Feature importance:\u003C\u002Fstrong\u003E Lagged consumption data was a key predictor.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EThis approach provided a solid foundation for predicting energy consumption at the building level.\u003C\u002Fp\u003E",solution_list_items:[],solution_image:a,solution_image_attribution:a,impact:"\u003Cp\u003EBy leveraging a supervised learning approach, our model was trained on historical energy consumption data with known outcomes. This enabled the model to establish a robust understanding of the relationship between input factors, such as time of day and past consumption, and the target variable: energy consumption. This learning process empowers the model to predict energy usage for new, unseen data, delivering valuable insights and supporting informed decision-making.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp id=\"isPasted\"\u003E\u003Ca href=\"http:\u002F\[email protected]\"\u003EJamie Greig\u003C\u002Fa\u003E, CEO, \u

1003Ca href=\"https:\u002F\u002Fwww.linkedin.com\u002Fcompany\u002Fenergysavingbear\u002F\"\u003EEnergy Saving Bear Ltd\u003C\u002Fa\u003E\u003C\u002Fp\u003E\u003Cp\u003E&ldquo;This project provided us with the information required to start building a production Machine Learning model. Using a third party research facility for this work has been very valuable in creating a tried and tested specification for commercial tenders. The IEA team were great to work with, knowledgeable, helpful and completed on time.&rdquo;\u003C\u002Fp\u003E",testimonial:"\u003Cp id=\"isPasted\"\u003E\u003Ca href=\"http:\u002F\[email protected]\"\u003EJamie Greig\u003C\u002Fa\u003E, CEO, \u003Ca href=\"https:\u002F\u002Fwww.linkedin.com\u002Fcompany\u002Fenergysavingbear\u002F\"\u003EEnergy Saving Bear Ltd\u003C\u002Fa\u003E\u003C\u002Fp\u003E\u003Cp\u003E&ldquo;This project provided us with the information required to start building a production Machine Learning model. Using a third party research facility for this work has been very valuable in creating a tried and tested specification for commercial tenders. The IEA team were great to work with, knowledgeable, helpful and completed on time.&rdquo;\u003C\u002Fp\u003E",project_metadata:{title:"Machine learning for energy consumption forecasting",description:"The IEA team were contracted to help develop the predictive machine learning model and review ESBâs current dashboard monitoring reports to improve usability.",meta_image:{url:bE,imgix_url:bF}}},{slug:"sustainable-transport-reducing-scope-3-travel-to-work-emissions",title:"Sustainable transport - reducing Scope 3 travel-to-work emissions ",top_intro__challenge_old:a,top_intro__challenge:"\u003Cp id=\"isPasted\"\u003E\u003Ca class=\"action--text\" href=\"http:\u002F\u002Fwww.calcommuter.com\u002F\"\u003ECalCommuter\u003C\u002Fa\u003E, an online web application developed by David Smith Consulting Limited (DSC), aims to assist organisations in understanding and acting on Scope 3 travel-to-work emissions. The application creates personalised commute travel plans for employees based on employees&rsquo; responses to a survey regarding their commute and work patterns.\u003C\u002Fp\u003E\u003Cp\u003EThe tool works out the cost, duration and emissions of home working days and every viable commute from home to their worksite. The goal is for organisations to take action on their workforce&rsquo;s commute emissions to support sustainable workplace travel plans. It is currently being tested with East Lothian Council in Scotland.\u003C\u002Fp\u003E\u003Cp\u003EDavid Smith Consulting wanted to expand the functionality of their existing CalCommuter application to provide data-driven insights on the greatest opportunities for commute emissions reduction in an organisation.\u003C\u002Fp\u003E\u003Cp\u003EThe IEA was contracted to help develop the &lsquo;LERO module&rsquo; (Latent Emission Reduction Opportunity module) for this additional functionality.\u003C\u002Fp\u003E",image:{url:bG,imgix_url:bH},image_attribution:a,process:"\u003Cp id=\"isPasted\"\u003EThe project to develop the LERO module was funded by Innovate UK through its Business Growth initiative and involved several key tasks:\u003C\u002Fp\u003E\u003Cul\u003E\u003Cli class=\"white--text\"\u003EData preparation: Our data team ingested, cleaned and sorted CalCommuter survey and results data for analysis. Tests of their API feed were also performed, which identified some edge cases and improvements.\u003C\u002Fli\u003E\u003Cli class=\"white--text\"\u003ECar sharing opportunities: We conducted modelling to identify potential car sharing opportunities among employees.\u003C\u002Fli\u003E\u003Cli class=\"white--text\"\u003EEmission-reduction opportunities: We developed a comprehensive modelling exercise to identify &lsquo;latent&rsquo; commute emission reduction opportunities by worksite and mode of transport.\u003C\u002Fli\u003E\u003C\u002Ful\u003E",solution:"\u003Cp\u003EBy the end of the project we provided DSC with a Python library containing the core logic required to support the initial requirements of the Latent Emission Reduction Opportunity (LERO) module. This library serves as a foundation for integrating the new functionality into the CalCommuter application. The Python library was delivered to the client via GitHub.\u003C\u002Fp\u003E",solution_list_items:[],solution_image:a,solution_image_attribution:a,impact:"\u003Cp\u003EThe library code developed represents a significant milestone towards deploying the Latent Emission Reduction Opportunity (LERO) module within the CalCommuter application. It provides a solid foundation for future development and will offer organisations valuable insights into optimising commute emissions.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp id=\"isPasted\"\u003EDavid Smith, \u003Ca href=\"http:\u002F\u002Fwww.davidsmithconsulting.co.uk\u002F\"\u003EDavid Smith Consulting Limited\u003C\u002Fa\u003E\u003C\u002Fp\u003E\u003Cp\u003E&ldquo;Working with the team on the development of the LERO module for CalCommuter has been an absolute pleasure. Their expertise and dedication were evident throughout the project and their regular progress updates kept us well-informed every step of the way.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003EThe team&rsquo;s friendly and professional approach made the collaboration seamless, and the work delivered has provided a strong foundation for expanding CalCommuter&rsquo;s functionality. We&rsquo;re excited to offer the insights generated by the LERO module to our clients, helping them unlock opportunities to reduce commute emissions. &rdquo;\u003C\u002Fp\u003E",testimonial:"\u003Cp id=\"isPasted\"\u003EDavid Smith, \u003Ca href=\"http:\u002F\u002Fwww.davidsmithconsulting.co.uk\u002F\"\u003EDavid Smith Consulting Limited\u003C\u002Fa\u003E\u003C\u002Fp\u003E\u003Cp\u003E&ldquo;Working with the team on the development of the LERO module for CalCommuter has been an absolute pleasure. Their expertise and dedication were evident throughout the project, and their regular progress updates kept us well-informed every step of the way. The team&rsquo;s friendly and professional approach made the collaboration seamless, and the work delivered has provided a strong foundation for expanding CalCommuter&rsquo;s functionality. We&rsquo;re excited to offer the insights generated by the LERO module to our clients, helping them unlock opportunities to reduce commute emissions. &rdquo;\u003C\u002Fp\u003E",project_metadata:{title:"Sustainable transport ",description:"Reducing Scope 3 travel-to-work emissions ",meta_image:{url:bG,imgix_url:bH}}},{slug:"strategic-planning-for-an-energy-broker",title:"Strategic planning for an energy trading company",top_intro__challenge_old:"South Africaâs ongoing energy crisis is driving rapid and meaningful regulatory change which in turn is stimulating development of renewables, particularly for the Commercial and Industrial (C&I) sector. But wind and s

1olar resources are distributed by nature making co-location of generation with demand challenging. To address this, ESKOM, the national system operator, provides a âwheelingâ service enabling solar and wind generators to move power over the transmission system to where it is needed.",top_intro__challenge:"\u003Cp id=\"isPasted\"\u003ESouth Africa&rsquo;s ongoing energy crisis is driving rapid and meaningful regulatory change which in turn is stimulating development of renewables, particularly for the Commercial and Industrial (C&amp;I) sector. But wind and solar resources are distributed by nature making co-location of generation with demand challenging. To address this, ESKOM, the national system operator, provides a &lsquo;wheeling&rsquo; service enabling solar and wind generators to move power over the transmission system to where it is needed.\u003C\u002Fp\u003E\u003Cp\u003EA market opportunity has emerged for organisations to match generation capacity with off-taker demand and to enable the required transmission through management of the wheeling arrangements. These energy brokers aim to match a portfolio of generation capacity on the supply side with a portfolio of off-take load on the demand side. This means that they must manage volume and shape risk on the supply side and demand for baseload power on the consumption side.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003EOur energy experts recently worked with a South African based power trading company to provide deep dive solar and wind yield analysis and strategic modelling support to help balance demand and supply risk.\u003C\u002Fp\u003E",image:{url:bI,imgix_url:bJ},image_attribution:a,process:"\u003Cp id=\"isPasted\"\u003EOur client already had an industry standard yield assessment for a large solar facility providing supply capacity. Our work focused initially on demonstrating the potential to supplement industry standard yield analysis with deeper, commercially relevant insights into the expected production and how well it fits with complex demand.\u003C\u002Fp\u003E\u003Cp\u003EWe used a 10-year weather simulation, downscaled to a spatial resolution of 1km and a temporal resolution of 10 minutes as input to our proprietary modelling applicaton, EnergyMetric. EnergyMetric converts weather to power for any combination of solar and\u002For wind installations.&nbsp;\u003C\u002Fp\u003E\u003Cp id=\"isPasted\"\u003EBy basing our production analysis on a longer time series of weather data (the industry standard approach provides a 12-month simulation) we unlock the potential to explore variability in a lot more detail.\u003C\u002Fp\u003E\u003Cp\u003EWe exposed inter-annual variability and trends in seasonality. We were also able to show what low production, high production and average production look like within each month, considering the full 10-year weather simulation. EnergyMetric also quantifies uncertainty, providing exceedance probabilities on production metrics across all timescales and statistical uncertainties on all graphical outputs. Our client now had access to:\u003C\u002Fp\u003E\u003Cul\u003E\u003Cli style=\"color: rgb(255, 255, 255);\"\u003EDeeper understanding of the potential for production to vary from year to year,\u003C\u002Fli\u003E\u003Cli style=\"color: rgb(255, 255, 255);\"\u003Emore detailed understanding of trends in within-year seasonality,\u003C\u002Fli\u003E\u003Cli style=\"color: rgb(255, 255, 255);\"\u003Equantitative insights into what good, bad and average production looks like, and\u003C\u002Fli\u003E\u003Cli style=\"color: rgb(255, 255, 255);\"\u003Ethe ability to understand and exploit exceedance probabilities.\u003C\u002Fli\u003E\u003C\u002Ful\u003E\u003Cp id=\"isPasted\"\u003EWith EnergyMetric we can also provide demand comparisons. By integrating an aggregaged demand profile into the analysis we can show how well the production profile fits with the consumption requirements from multiple off-takers, exposing and quantifying periods of residual or excess generation.\u003C\u002Fp\u003E\u003Cp\u003ETo improve things further we extended our initial yield-focused analysis to include a demonstration of potential to inform decisions about how best to grow the supply side portfolio. We did this using EnergyMetric to explore production potential from a range of solar and wind locations, in different c

1ombinations and considering different off-take requirements.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E",solution:a,solution_list_items:[],solution_image:a,solution_image_attribution:a,impact:"\u003Cp\u003EThe additional insights improved on industry standard yield analysis, enabling our client to increase the sophistication with which they manage volume and shape and increasing their confidence in implementing mechanisms to improve returns.\u003C\u002Fp\u003E\u003Cp\u003EOur correlation analysis into building out the supply side portfolio provided quantitative evidence to clarify questions like:\u003C\u002Fp\u003E\u003Cul id=\"isPasted\"\u003E\u003Cli\u003EHow well does solar combine with wind?\u003C\u002Fli\u003E\u003Cli\u003EAre 2 large installations better than 1 large and 2 small?\u003C\u002Fli\u003E\u003Cli\u003EWhich combination of technologies and locations maximises diversity?\u003C\u002Fli\u003E\u003C\u002Ful\u003E\u003Cp\u003EBy the end of the initiative our client had a detailed understanding of how industry standard yield analysis could be enhanced and how EnergyMetric could inform strategic decisions on the best way to grow their business.\u003C\u002Fp\u003E",testimonial:a,project_metadata:{title:bK,description:bK,meta_image:{url:bI,imgix_url:bJ}}},{slug:"optimising-long-duration-storage-technology",title:U,top_intro__challenge_old:a,top_intro__challenge:"\u003Cp id=\"isPasted\"\u003EThe energy modelling team worked with a South African energy venture developing a new technology for reliable and cost-effective long-duration storage of energy from intermittent solar and wind.&nbsp;\u003C\u002Fp\u003E\u003Cp id=\"isPasted\"\u003EThe proposed solution is a gravity storage system that uses power from renewable sources to raise and lower weights, in the process storing and releasing energy over longer cycles than can be achieved with chemical battery technologies. Not only does the &lsquo;gravity battery&rsquo; offer the potential to store energy over longer time periods, but it does so far more cost efficiently than would be possible with alternatives.\u003C\u002Fp\u003E\u003Cp\u003EThe technology is being trialled in the South African market in collaboration with the mining industry, where high energy consumption and an ongoing energy crisis provide an ideal opportunity to test the potential savings.\u003C\u002Fp\u003E",image:{url:bL,imgix_url:bM},image_attribution:a,process:"\u003Cp id=\"isPasted\"\u003ETo support our client with effective market engagement we worked closely to develop the investment case for this new technology. Critical for this was an ability to model the performance of a storage installation and establish the attractiveness of the associated economics.\u003C\u002Fp\u003E\u003Cp\u003EThe study focused on assessing the value of the storage technology when integrated into pre-defined renewable energy development plans (carbon neutral goals).\u003C\u002Fp\u003E\u003Cp\u003EOur analysis involved modelling the renewable production potential from several candidate mixes of solar and wind facilities and then simulating how the available energy could best be used to contribute directly to load and charge the gravity battery system. The objective was to identify optimal charging and discharging strategies when taking account of other commercial factors such as:\u003C\u002Fp\u003E\u003Cul\u003E\u003Cli style=\"color: rgb(255, 255, 255);\"\u003EPPA pricing for the solar and wind procurement\u003C\u002Fli\u003E\u003Cli style=\"color: rgb(255, 255, 255);\"\u003Evariable tariffs for any remaining grid inputs, and\u003C\u002Fli\u003E\u003Cli style=\"color: rgb(255, 255, 255);\"\u003Eall other charges associated with utilisation of the grid infrastructure.\u003C\u002Fli\u003E\u003C\u002Ful\u003E\u003Cp\u003EA further key factor to consider was the existing and planned renewable developments, which defined the modelled scenarios, and significantly influenced the techno-economic feasibility of the proposed storage systems.\u003C\u002Fp\u003E",solution:"\u003Cp id=\"isPasted\"\u003E\u003Cstrong\u003EModelled use case\u003C\u002Fstrong\u003E\u003C\u002Fp\u003E\u003Cp\u003EWhilst there are multiple commercial use cases for the new storage technology, our work focused on quantifying the potential for reducing energy costs. To do this, our consultants modelled real-world scenarios characterised by:\u003C\u002Fp\u003E\u003Cul\u003E\u003Cli\u003EAn off-taker with a known energy consumption profile.\u003C\u002Fli\u003E\u003Cli\u003EPotential to co-locate utility-scale solar at the off-taker&rsquo;s mining facilities.\u003C\u002Fli\u003E\u003Cli\u003EPotential to source additional wind generation from off-site locations, and\u003C\u002Fli\u003E\u003Cli\u003EInstallation of a properly specified gravity storage system.\u003C\u002Fli\u003E\u003C\u002Ful\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cimg alt=\"Energy-Cubes-Solution.jpg\" src=\"https:\u002F\u002Fimgix.cosmicjs.com\u002F7973dfa0-0952-11ef-b837-75832108e4e1-Energy-Cubes-Solution.jpg\" class=\"fr-fil fr-dib\" style=\"width: 1200px;\"\u003E\u003Cbr\u003E\u003C\u002Fp\u003E",solution_list_items:[],solution_image:a,solution_image_attribution:"\u003Cp\u003EGra

1phs\u003C\u002Fp\u003E",impact:"\u003Cp id=\"isPasted\"\u003EBy the end of the initiative our client had detailed, quantitative evidence supporting a positive investment case for the new storage technology, complete with a high impact visual story telling aid to further enable effective market engagement.\u003C\u002Fp\u003E",testimonial:a,project_metadata:{title:U,description:U,meta_image:{url:bL,imgix_url:bM}}},{slug:"campus-energy-decarbonisation",title:bN,top_intro__challenge_old:"\n",top_intro__challenge:"\u003Cp id=\"isPasted\"\u003EThere is a desire to decarbonise current and future energy needs with ambitious targets being set for developing capacity to produce and consume clean energy.\u003C\u002Fp\u003E\u003Cp\u003EIn this project we worked with a large R&amp;D organisation to help them strategically plan their energy transition journey across a series of landholdings and research sites with mixed-use building stock. The client was keen to understand the potential for integrating solar, wind and BESS into their existing energy infrastructure.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E",image:{url:bO,imgix_url:bP},image_attribution:"\u003Cp\u003EAn illustration of possible solar panel placement\u003C\u002Fp\u003E",process:"\u003Cp\u003EOur energy analysts provided comprehensive site and yield assessment of the potential for developing solar and wind capacity, detailed analysis of the associated economics of different options and strategic insights into how best to manage the utilisation of a portfolio of intermittent generation assets.\u003C\u002Fp\u003E\u003Cp\u003EThe work draws on several of our key competencies and tools, including the use of our generation modelling software &ndash; EnergyMetric &ndash; to plan different scenarios with varying cost implications and the potential to offset electricity demand and deliver reductions in carbon emissions.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cimg alt=\"UoR_added-image.jpg\" src=\"https:\u002F\u002Fimgix.cosmicjs.com\u002F152e22f0-0955-11ef-b837-75832108e4e1-UoR_added-image.jpg\" class=\"fr-fil fr-dib\"\u003E\u003C\u002Fp\u003E",solution:"\u003Cp\u003EThe analysis is enabled through integration of a 10- year high resolution weather simulation. The on-site generation analysis is complemented with a further assessment into the potential for battery storage considering a number of use cases: peak shaving, load shifting and energy arbitrage.\u003C\u002Fp\u003E",solution_list_items:[],solution_image:a,solution_image_attribution:a,impact:"\u003Cp id=\"isPasted\"\u003EBy the end of the project the client had a thorough understanding of the generation potential from existing assets and extent to which the additional capacity could contribute to existing and future demand whilst reducing CO2 emissions. The client also benefitted from much greater awareness of the potential from renewables leading to a further phase of analysis to explore more ambitious strategies including storage and the detailed quantification of additional revenue opportunities.\u003C\u002Fp\u003E",testimonial:a,project_metadata:{title:bN,description:"In this project we worked with a large R&D organisation to help them strategically plan their energy transition journey across a series of landholdings and research sites with mixed-use building stock. The client was keen to understand the potential for integrating solar, wind and BESS into their existing energy infrastructure.",meta_image:{url:bO,imgix_url:bP}}},{slug:"monitoring-weather-and-climate-risks-to-electricity-networks",title:"Monitoring weather and climate risks to electricity networks ",top_intro__challenge_old:a,top_intro__challenge:"\u003Cp\u003EExtreme weather events are causing greater uncertainty to infrastructure owners and operators. Physical damage to assets as well as disruption to services and field operations lead to higher O&amp;M costs and potential penalties for regulated utilities. On top of this, climate change makes it more uncertain how weather patterns will impact networks over the longer term.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003ETo help manage this challenge, the IEA worked with a range of transmission and distribution grid operators to develop a proof-of-concept software platform to provide a new, enhanced capability for operators to more effectively understand, monitor and mitigate weather-related risks to their networks. The project also demonstrated the benefit of integrating climate projections into the assessment by showing how risk profiles may evolve in the face of ongoing climate change.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EThe project ran over 9 months with funding provided by the UK Space Agency. The partners were Barbados Light&amp;Power, ISA Group, Grupo EPM, Northern Power Grid, Western Power Distribution and the Energy Systems Catapult.\u003C\u002Fp\u003E",image:{url:bQ,imgix_url:bR},image_attribution:a,process:"\u003Cp\u003EThrough a series of workshops, the data team analysed the current challenges faced by the partners and undertook a data mining exercise to look for patterns between faults and weather disruption across the different networks. Part of this exercise was to understand the &lsquo;fragilities&rsquo; for different asset classes &ndash; a key concept to ensure that the system can be tuned to monitor the right weather variables.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EAt the same time, the modelling team analysed a range of climate projection models to develop an initial understanding how different scenarios might impact on the frequency and potential durations of specific weather events compared to the present day. This informed thinking around planning for future O&amp;M activity as well as shaping the recommended mitigation actions that could be built into a future operational system.\u003C\u002Fp\u003E",solution:"\u003Cp\u003EThe final output of the project was a proof-of-concept software platform demonstrating the potential for the system, highlighting how real time alerts could sit alongside network data and risk maps.\u003C\u002Fp\u003E",solution_list_items:[],solution_image:a,solution_image_attribution:a,impact:"\u003Cp\u003EThe proof-of-concept and data insight coming out of the project successfully demonstrated the potential benefits for the system to improve O&amp;

1M operations as well as providing greater infrastructure resilience through enhanced long-term climate planning.\u003C\u002Fp\u003E",testimonial:a,project_metadata:{title:"Proof of concept to highlight network risks",description:"The IEA explores patterns between faults and weather disruption across the electricity networks",meta_image:{url:bQ,imgix_url:bR}}},{slug:"reducing-energy-costs-in-cement-manufacturing",title:"Reducing energy costs in cement manufacture",top_intro__challenge_old:a,top_intro__challenge:"This project was undertaken for Hanson UK to examine the potential for dynamic load shifting in order to minimise electricity costs and\u002For CO2 emissions. The overall objective was to identify when energy-intensive processes (such as cement milling) could be shifted to off-peak times in order to reduce energy costs via leveraging the availability of cheaper off-peak electricity as well as potentially increasing the use of renewable energy sources.",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F0374f6d0-b1d9-11ed-a13d-c3e6887fd23f-Reducing-energy-costs-in-cement-manufacture.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F0374f6d0-b1d9-11ed-a13d-c3e6887fd23f-Reducing-energy-costs-in-cement-manufacture.jpg"},image_attribution:a,process:"\u003Cp\u003EThrough initial workshops and user needs analysis with management and production staff, we developed an operational model to simulate the cement production process. This was brought together with energy consumption data to provide a proof-of-concept software tool to allow cement operators and plant management the ability to model the impact of load shifting on energy consumption and production output. A key aspect in the early stages of the project was confirmation of the objectives and measures of success (considering cost reduction, optimising CO2 emissions and key operational usability requirements) for the client.\u003C\u002Fp\u003E",solution:"\u003Cp\u003EFollowing an iterative development cycle and on-going presentations to Hanson staff, the IEA team developed a proof-of-concept software tool which let operators and management (i) explore scenarios to optimise cement production given operational targets, practical constraints (e.g. planned plant downtime) and trade-offs between objectives (e.g. cost versus CO2 emission saving) and (ii) run simulations against historic price data to compare actual with optimal schedules and quantify potential cost savings and benefits over weekly or monthly schedule optimisation.\u003C\u002Fp\u003E",solution_list_items:[],solution_image:a,solution_image_attribution:a,impact:"\u003Cp\u003EThe proof-of-concept software tool was used to explore a typical year using historic data on cement mill operations in 2018. Overall the likely cost saving between &lsquo;business as usual&rsquo; and an optimised schedule was estimated to be a six figure &pound; sum in comparison to the actual costs incurred for that year, thereby justifying future work to explore how to operationalise load shifting technology.\u003C\u002Fp\u003E",testimonial:"\u003Cp\u003E\u003Cem\u003EThe IEA team worked in a collaborative way to develop a model that optimised power costs and hence reduced Scope 2 CO2 emissions. The analysis IEA provided on historic data helped to identify power cost savings through changes to operations over a weekly production planning period and changes to within day operations by utilising existing equipment differently to the normal accepted practice.\u003C\u002Fem\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cem\u003EIain Walpole, Hanson UK\u003C\u002Fem\u003E\u003C\u002Fp\u003E",project_metadata:{title:"The IEA aid reduction of energy consumption in the cement industry",description:"The IEA work with Hanson to reduce costs and increase the use of renewable energy sources",meta_image:{url:g,imgix_url:h}}},{slug:"analysing-climate-impacts-on-infrastructure",title:"Analysing climate impacts on infrastructure",top_intro__challenge_old:a,top_intro__challenge:"A drive towards sustainable and future-proofing infrastru

1cture means that climate change is beginning to be embedded into the standards that drive the design and maintenance of industries such as transport, buildings and power distribution networks. \n\nAlongside this drive for sustainability, the world of climate data is developing at a rapid pace. Computer models simulating possible future climate and weather events are being created and improved upon in an on-going cycle of world-class scientific research. The options are seemingly endless. Do you want a model that captures the entire world, such as one from the CMIP5 family (Coupled Model Intercomparison Project)? Or one for a specific region, such as the CORDEX (Coordinated Regional Climate Downscaling Experiment) models? Maybe maximum detail for a specific country is required, like the UKCP18 for the UK. For most businesses, this all means confusion. Where do you obtain trusted climate data? How do you use it? What are its strengths and weaknesses? What do the numbers mean?  The questions are never-ending and not many of them have a simple yes\u002Fno answer.\n",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F03798ab0-b1d9-11ed-a13d-c3e6887fd23f-Analysing-climate-impacts-on-infrastructure.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F03798ab0-b1d9-11ed-a13d-c3e6887fd23f-Analysing-climate-impacts-on-infrastructure.jpg"},image_attribution:"\u003Cp\u003EImages Copyright Copernicus Climate Change Service\u003C\u002Fp\u003E",process:"\u003Cp\u003EA recent project commissioned by the European climate data supplier - \u003Ca href=\"https:\u002F\u002Fclimate.copernicus.eu\u002F\"\u003ECopernicus Climate Change Service (C3S)\u003C\u002Fa\u003E - saw the IEA and several European partners using the C3S Climate Data Store, an online repository of climate data, to try to address these questions using five use cases where infrastru

1cture design might be impacted by climate change: (i) long term design and planning of roads in Spain (ii) climate change adaptation in railway infrastructure planning in the Netherlands\u002FUK (iii) a climate stress-test for urban infrastructures in the city of Amersfoort, the Netherlands and Basque municipalities, Spain (iv) design of power station and district heating in Vitoria, Spain and (v) water and sewage infrastructure management in Rome.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EDuring the project, feedback from industry partners regarding data presentation, structure and areas of uncertainty were taken into account and used to improve documentation around datasets. For example, while daily data can be provided, it was made clear that the output of the model for a certain date in the future is not a forecast for that day.\u003C\u002Fp\u003E",solution:"\u003Cp\u003EOur analysis found that the large uncertainty that exists in the future projections of extreme events, the inherent limitations and inadequacies of climate models and the need for very high-resolution data (due to the local features of a site being of utmost importance) often limit the possibility to feed climate model data directly into standards. This means there is currently an absence of simple, practical examples of climate projections being used to design and operate infrastructure. The project tackled this by highlighting a number of case studies and by providing improved documentation to guide activity.\u003C\u002Fp\u003E",solution_list_items:[],solution_image:a,solution_image_attribution:"\u003Cp\u003Etesting the next image&nbsp;\u003C\u002Fp\u003E",impact:"\u003Cp\u003EThe project aimed to provide a realistic, traceable and robust methodology for dealing with climate models of all types, signposting users to sources of climate data that are well referenced. Whilst the project focused on Europe, the lessons and outcomes are equally applicable to other regions. Work was also undertaken to communicate with standards bodies such as the European standards organisations (CEN-CENLEC) to highlight the complexities of using climate data and how to start renewing it into standards.&nbsp;\u003C\u002Fp\u003E",testimonial:a,project_metadata:{title:"The IEA and partners address climate impact on infrastructure",description:"Using the C3S climate data to store to address climate change impacts on infrastructure.",meta_image:{url:g,imgix_url:h}}},{slug:"modelling-methane-gas-emissions-using-machine-learning",title:"Modelling methane gas emissions using machine learning",top_intro__challenge_old:a,top_intro__challenge:"The re-development of former landfill sites requires a careful risk assessment of the ground gases that are released to ensure they do not form a hazard to later occupants. Our client deploys sensors that monitor emissions of landfill gases including methane, carbon monoxide, carbon dioxide and hydrogen sulphide, alongside other parameters such as borehole temperature, pressure and humidity. The purpose of this project was to develop a data-driven approach to interpret the information coming from the sensors, in order to understand more about the gas flows and the conditions that can lead to hazardous levels of emissions.",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F0378ee70-b1d9-11ed-a13d-c3e6887fd23f-Modelling-methane-gas-emissions-using-machine-learning.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F0378ee70-b1d9-11ed-a13d-c3e6887fd23f-Modelling-methane-gas-emissions-using-machine-learning.jpg"},image_attribution:a,process:"\u003Cp\u003EWe worked closely with the client to understand their requirements, the risk assessment process and the role that data analytics can play in informing decisions. A set of case study locations was selected and the data from this location were gathered. Environmental data including ambient temperature and pressure were also sourced from third party weather data archives to form part of the analysis.\u003C\u002Fp\u003E",solution:"\u003Cp\u003EThe goal of this work was to develop tools and methodologies to help the expert sift through the large amounts of available data and alert them to the factors that appear to be most important in terms of affecting the emission of dangerous gases such as methane. We chose to apply a machine learning method based on the random forest algorithm to model relationships between the various variables in the system. This algorithm is capable of modelling relationships that are complex and non-linear, unlike a traditional linear regression approach. The importance of each variable to the system can be assessed, enabling the analyst to discard irrelevant variables and simplify the interpretation.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EThe results of the process differed between the case study locations, which is itself an important result. The relationships between variables were found to be highly complex, reflecting the complexity and variability of flow within the landfill sites. In some locations, the ambient conditions were found to be the primary control on emissions of methane and other gases, which matches the intuition and expectations of the expert consultants. However, in other locations this was not found to be the case, which highlights the importance of having case-specific information to inform the risk assessment process.\u003C\u002Fp\u003E",solution_list_items:[],solution_image:a,solution_image_attribution:a,impact:"\u003Cp\u003EThe client was able to build on the project outcomes to develop a commercial version of the softw

1are to enhance their service offering.\u003C\u002Fp\u003E",testimonial:a,project_metadata:{title:"Understanding methane gas flows and how conditions affect hazardous emissions.",description:"The IEA develop tools and methodologies to help experts understand the risk factors that appear to be most important in terms of affecting the emission of dangerous gases",meta_image:{url:g,imgix_url:h}}},{slug:"forecasting-fog-using-data-analytics",title:"Forecasting fog using data analytics",top_intro__challenge_old:a,top_intro__challenge:"Fog poses a life-threatening challenge to the travelling public. To help address this problem, we investigated the feasibility of developing fog prediction software to provide early warning alerts to Highwayâs England to help improve road safety and save the capital costs involved in installing a widespread roadside sensor network.",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F03734920-b1d9-11ed-a13d-c3e6887fd23f-Forecasting-fog-using-data-analytics.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F03734920-b1d9-11ed-a13d-c3e6887fd23f-Forecasting-fog-using-data-analytics.jpg"},image_attribution:a,process:"\u003Cp\u003EThrough workshops with Highway&rsquo;s England staff and visits to the regional network control centre, we developed the technical scope for the feasibility study. This was followed by an extensive data gathering exercise to bring together the different forms of data pertaining to the M40 motorway network area which formed the basis for the analysis.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EData included network road sensors, CCTV camera, satellite data and relevant meteorological information. On top of this we spent time reviewing technical literature on previous attempts to predict fog using different data sources and how appropriate they were given the spatial and temporal specifications needed for a solution to be utilised by Highway&rsquo;s England.\u003C\u002Fp\u003E",solution:"\u003Cp\u003EModelling work was undertaken using a combination of different analytical techniques. A comparison of COBS fog messages with weather station data, CCTV and traffic flow data suggest that these data provide a promising basis for the development an improved fog prediction system. In particular, it was discovered that a potential &lsquo;fog signature&rsquo; in the data could form the basis of a future machine learning system (see image below). Visibility measurements also showed potential for alerting drivers to the risk of fog several hours before it can be reported by officers on the road.\u003C\u002Fp\u003E",solution_list_items:[],solution_image:a,solution_image_attribution:a,impact:"\u003Cp\u003EThe project demonstrated that advances in data fusion provide a ready-made framework for the development of a data intensive &lsquo;intelligent&rsquo; fog prediction system using machine learning to provide early warning alerts well in advance of likely reporting times provided by traffic officers on the network. This intelligent system for fog prediction implemented &lsquo;by software&rsquo; as opposed to installing roadside equipment would be universally deployable and would offer the potential for improving safety and reducing the operational costs required to maintain and service new roadside hardware.\u003C\u002Fp\u003E",testimonial:"\u003Cp\u003E\u003Cem\u003EIt was a great pleasure to work with the IEA, both in terms of the intellectual depth of the conversations, and the positive business spirit of &lsquo;making it happen&rsquo;.&nbsp;\u003C\u002Fem\u003E\u003Cem\u003EThroughout the project we met numerous times, including in Highways England control rooms, which really helped foster a partnership and mutual understanding. As the analysis progressed, it became clear that the idea would work, as traffic flow patterns became very different when it was foggy, leading to a &lsquo;fog signature&rsquo; which could be used to proactively activate fog warning signs and action plans.&nbsp;\u003C\u002Fem\u003E\u003Cem\u003EI would like to thank everyone at IEA for their great enthusiasm and dedication, without which nothing would have happened.&nbsp;\u003C\u002Fem\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EPeter Richards, Highways England&nbsp;\u003C\u002Fp\u003E",project_metadata:{title:"The IEA undertake data modelling to re

1cognise fog indicators",description:"The IEA utilise multiple data sources to model a warning system for imminent fog",meta_image:{url:g,imgix_url:h}}},{slug:"improving-environmental-impact-assessments-using-knowledge-graphs",title:"Improving environmental impact assessments using knowledge graphs",top_intro__challenge_old:a,top_intro__challenge:"Environmental, Social and Health Impact Assessments (ESHIAs) are required by investors and regulatory authorities for large scale engineering and infrastructure projects. The early identification of the impact of such projects on habitats and species can avoid significant financial penalties and costs in later stages. This project demonstrated the use of âknowledge graphsâ in linking together all the relevant information needed to produce an ESHIA, thereby increasing the efficiency of producing ESHIAs and increasing knowledge sharing between projects within the clientâs organisation and with their customers.",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F03759310-b1d9-11ed-a13d-c3e6887fd23f-Improving-environmental-impact-assessments.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F03759310-b1d9-11ed-a13d-c3e6887fd23f-Improving-environmental-impact-assessments.jpg"},image_attribution:a,process:"\u003Cp\u003EThrough a series of consultation meetings with the client, we gained an understanding of the ESHIA process, the datasets that are involved and the challenges faced by environmental consultants in drawing all the relevant information together. The knowledge graph - and a custom-built user interface, - were built in an iterative fashion, gaining feedback from the client at each stage.\u003C\u002Fp\u003E",solution:"\u003Cp\u003EWe developed an online software tool, consisting of a graph database, query tool and a web-based graphical user interface for searching and visualising the data. The knowledge graph approach is a highly flexible means of storing data, representing information as a set of objects that are linked together by relationships, forming a rich network (or \u003Cem\u003Egraph\u003C\u002Fem\u003E) of information. For example, information about a species can be linked to information about its vulnerabilities, habitats and protected status, which can in turn be linked to other information, such as scientific publications and biodiversity surveys.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EThis approach allows the graph database to grow organically with time and permits powerful and rapid searching and querying. Using reference data provided by the client, and accessing a number of third party biodiversity and habitat datasets, a trial database was created storing 897 species and 4125 protected or key biodiversity areas. We also automatically extracted information from a set of publications and reports and linked these into the knowledge graph.\u003C\u002Fp\u003E",solution_list_items:[],solution_image:a,solution_image_attribution:a,impact:"\u003Cp\u003EA key result of the project was to show that complex queries across multiple data sources can be made much easier. For example, the analyst may wish to find all species that are vulnerable to oil and are also on threatened species lists. Answering this question involves cross-referencing multiple data sources (both in-house and third-party) and can be time-consuming with traditional tools, but is made significantly more efficient using a knowledge graph approach.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EIn addition to the creation of a knowledge base and query tool, it was demonstrated how an open satellite data - such as optical imagery from the Sentinel 2 satellites - could potentially be used to detect changes in habitats (for example, that have occurred since other reference sources have been issued). &nbsp;This could allow analysts to stay informed on relevant habitat changes at minimal cost.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"color: rgb(0, 0, 0);\"\u003E\u003C!--[if !supportFootnotes]--\u003E\u003C!--[endif]--\u003E&nbsp;\u003C\u002Fspan\u003E\u003C\u002Fp\u003E",testimonial:a,project_metadata:{title:"Visualising environmental impact of large infrastru

1cture",description:"The IEA have developed an online software tool to visualise the effect large infrastructure projects can have on species and their habitats",meta_image:{url:g,imgix_url:h}}},{slug:"making-climate-science-accessible-viewpoint-brazil",title:bS,top_intro__challenge_old:a,top_intro__challenge:"\u003Cp\u003EThe  WCSSP brings together weather and climate expertise from the UK and partner countries to focus on the global challenges\nof climate and extreme weather events. It is funded in the UK by the Newton Fund and delivered by the UK Met Office.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003ESince 2014 more than 90 research projects have advanced knowledge of weather and climate science, created new or improved weather and climate services and strengthened the weather and climate resilience of vulnerable communities around the world.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003ETo promote this activity to a wider audience of non-specialist policymakers and businesses, the IEA was commissioned by the Met Office in 2021 to develop a range of technical and promotional materials to showcase some of the key findings and opportunities\nfor climate action from the linked Brazilian CSSP Programme across the key thematic areas of (i) carbon cycle, net zero budgets, ecosystem analysis and land-use (ii) climate modelling, especially of rainfall predictability and processes and (iii) climate\nimpacts modelling for disaster risk reduction and alerting\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EOur design and communications team developed a range of bespoke resources highlighting key findings and data in language accessible to policymakers and NGOs, as well as making business and industry aware of potential new climate services such as fire\nforecasting, drought and flood monitoring. The work also included the development of 2 bespoke software tools for visualising and interrogating specific climate analysis datasets.\u003C\u002Fp\u003E",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F037b5f70-b1d9-11ed-a13d-c3e6887fd23f-Making-climate-science-accessible.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F037b5f70-b1d9-11ed-a13d-c3e6887fd23f-Making-climate-science-accessible.jpg"},image_attribution:a,process:"\u003Cp\u003EThe project lasted 9 months and involved an intensive series of meetings with key researchers, the Met Office and the CSSP Brazil programme partners. These included the Brazilian National Institute for Space Research (INPE), the National Institute of Amazonian Research (INPA), Brazil&#39;s National Centre for Monitoring and Early Warning of Natural Disasters (CEMADEN) as well as British Embassy staff in Brazil.\u003C\u002Fp\u003E",solution:"\u003Cp\u003EThe final outputs of the project included a series of briefing papers and videos on a range of climate topics, a programme handbook with feature articles and interviews, a series of infographics and 2 software visualisations on river level forecasting and extra-tropical rainfall.&nbsp;\u003C\u002Fp\u003E",solution_list_items:[],solution_image:a,solution_image_attribution:a,impact:"\u003Cp\u003EThe material produced during the project was all were brought together on a new website designed and built by the IEA team \u003Ca href=\"https:\u002F\u002Fwww.viewpoint-brazil.org\u002F\"\u003E\u003C\u002Fa\u003E\u003Ca href=\"https:\u002F\u002Fwww.viewpoint-brazil.org\u002F\"\u003Ehttps:\u002F\u002Fwww.viewpoint-brazil.org\u002F\u003C\u002Fa\u003E and launched at a virtual event hosted by the British Embassy in Sao Paulo.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003E&quot;We are excited to launch VIEWPoint Brazil, a resource that shares the world-class scientific research from CSSP Brazil in an accessible and creative way...[and] as a reference to build understanding and inform decision-making.&rdquo;&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EPeter Wilson Her Majesty&rsquo;s Ambassador to the Federal Republic of Brazil\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E",testimonial:a,project_metadata:{title:bS,description:"Showcasing key findings and opportunities for climate action from the Brazilian CSSP Programme",meta_image:{url:V,imgix_url:W}}},{slug:"visualising-wind-and-flood-hazards-in-europe",title:"Visualising wind and flood hazards in Europe",top_intro__challenge_old:a,top_intro__challenge:"\u003Cp\u003EThe UK Centre for Greening Finance &amp; Investment (CGFI) is a national centre established to accelerate the adoption and use of climate and environmental data and analytics by financial institutions.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EThe IEA is part of CGFI and leads on ensuring the outputs from CGFI have a real impact on these institutions through the development of software tools and data visualisations to help explore weather and climate impacts.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EThe Wind and Flood Correlation Explorer is an example of the work we are co-developing with researchers and financial services companies.\u003C\u002Fp\u003E",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F5d796e40-c700-11ed-a451-7f625299de0a-image.png",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F5d796e40-c700-11ed-a451-7f625299de0a-image.png"},image_attribution:"\u003Cp\u003EScreenshot of visualising wind app\u003C\u002Fp\u003E",process:"\u003Cp\u003E\u003Cstrong\u003EWind and Flood Correlation Explorer\u003C\u002Fstrong\u003E\u003C\u002Fp\u003E\u003Cp\u003EFinancial institutions need to take into account property risk for insurance, reinsurance, mortgages, and credit risk. Properties are at risk from wind and flood hazards, and there is evidence to suggest that these covary; storms can bring wind and flooding simultaneously, amplifying risk. Wind and flood hazards are currently analysed separately by insurers and catastrophe modellers. This could put capital at risk of correlated windstorm and flood events.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003ECGFI researchers have investigated the correlations between extremes relating to wind and flooding at all timescales from daily to seasonal for Europe. The results are detailed in \u003Ca href=\"https:\u002F\u002Fwww.sciencedirect.com\u002Fscience\u002Farticle\u002Fpii\u002FS2212094723000038\" rel=\"noopener noreferrer\"\u003E\u003Cspan style=\"color: rgb(84, 172, 210);\"\u003EHannah et al (2023)\u003C\u002Fspan\u003E\u003C\u002Fa\u003E and this visualisation tool showcased these results as an extension to the paper.\u003C\u002Fp\u003E",solution:"\u003Cp\u003EThe tool enables users to explore the correlations between historical hydro-meteorological variables (wind gust, river flow and precipitation) and correlations between metrics to estimate impacts (Storm Severity Index and Flood Severity Index). The user can visualise these correlations on a map for selected timescales (day, week, month and season). There is also a way to display correlations across all timescales for each country in graphical form.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Ca href=\"https:\u002F\u002Fthe-iea.github.io\u002Fcgfi-wind-flood\u002F\"\u003E\u003C\u002Fa\u003E\u003Cspan style=\"color: rgb(84, 172, 210);\"\u003E\u003Ca href=\"https:\u002F\u002Fthe-iea.github.io\u002Fcgfi-wind-flood\u002F\" rel=\"noopener noreferrer\" target=\"_blank\"\u003Ehttps:\u002F\u002Fthe-iea.github.io\u002Fcgfi-wind-flood\u002F\u003C\u002Fa\u003E\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EIt also includes a new a new Flood Severity Index (FSI), which can be used to help insurers understand compounding risks and hghlights multiple correlations between wind and flood hazards in Europe across multiple timescales.\u003C\u002Fp\u003E",solution_list_items:[],solution_image:a,solution_image_attribution:a,impact:"\u003Cp align=\"center\"\u003E\u003Cstrong\u003E&ldquo;\u003Cem\u003EI think it&rsquo;s a really good tool for the industry to quickly visualise the correlation between wind and flood over Europe. The ability to change the correlation length is extremely useful in the current market, and how that correlation varies between the different c

1ountries\u003C\u002Fem\u003E.&rdquo; &nbsp;\u003C\u002Fstrong\u003E\u003Cstrong\u003EAdrian Champion, Aon\u003C\u002Fstrong\u003E\u003C\u002Fp\u003E\u003Cp align=\"center\"\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp align=\"center\"\u003E\u003Cstrong\u003E\u003Cimg class=\"fr-fic fr-dib\" style=\"width: 158px;\" src=\"https:\u002F\u002Fcdn.cosmicjs.com\u002Ffd830940-c7d8-11ed-a451-7f625299de0a-LogoAonCorporation.svg.png\"\u003E\u003C\u002Fstrong\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp align=\"center\"\u003E\u003Cstrong\u003E\u003Cstrong\u003E\u003Ca href=\"https:\u002F\u002Fcdn.cosmicjs.com\u002Fec6ebdd0-c7d7-11ed-a451-7f625299de0a-LogoAonCorporation.svg.png\"\u003E\u003C\u002Fa\u003E\u003C\u002Fstrong\u003E\u003C\u002Fstrong\u003E\u003C\u002Fp\u003E",testimonial:a,project_metadata:{title:"Visualising wind and flood risk correlation",description:"The tool enables users to explore the correlations between historical hydro-meteorological variables (wind gust, river flow and precipitation) and correlations between metrics to estimate impacts (Storm Severity Index and Flood Severity Index). ",meta_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fb83c9960-c700-11ed-a451-7f625299de0a-Visualising-Wind.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fb83c9960-c700-11ed-a451-7f625299de0a-Visualising-Wind.jpg"}}},{slug:"predictive-maintenance-for-wind-turbines",title:bT,top_intro__challenge_old:a,top_intro__challenge:"\u003Cp\u003EIn this project, our analysts worked with a wind farm operator to investigate the likely reasons for observed operational reductions in turbine availability and production output during operational wind windows (wind speeds &gt;3ms-1 and &lt;25ms-1) and to explore the potential for developing an AI-based predictive maintenance programme to help:\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003E&ndash; reduce maintenance-related downtime disruption,\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003E&ndash; minimise maintenance costs,\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003E&ndash; providing enhanced lead times to enable timely ordering of parts.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EA rich set of operational wind turbine performance data was made available from the operator&rsquo;s SCADA system. This included\u003Cstrong\u003E&nbsp;\u003C\u002Fstrong\u003Eerror information such as timestamps, duration and severity.&nbsp;\u003C\u002Fp\u003E",image:{url:bU,imgix_url:bV},image_attribution:"\u003Cp\u003EWind Turbines\u003C\u002Fp\u003E",process:"\u003Cp\u003EThe data allowed the team to investigate the changes in the frequency of the errors over time using the 10-minute window dataset and to evaluate the most common types of errors. This was then compared to 5 years of meteorological data at the same temporal resolution to look for any correlations with factors such as wind speed, wind direction, temperature, and rainfall.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003ESimilarly, power curves for each turbine were analysed for any sign of output loss correlated with the error information. All the data was brought together and visualised through a series of plots and charts, two of which can be seen in the examples below.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cimg src=\"https:\u002F\u002Fcdn.cosmicjs.com\u002F12266220-ccac-11ed-a451-7f625299de0a-Case-Study-10-figs.jpg\" style=\"width: 1200px;\" class=\"fr-fic fr-dii\"\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E",solution:"\u003Cp\u003EOur analysis demonstrated that the frequency of errors that lead to downtime of the wind turbines had increased from 2015 to 2019, both in total count as well as for all levels of severity. While these errors affect the availability of the turbines, they did not affect the power production to a large extent, with the exception of one turbine. While weather variables were seen to act on all turbines equally, the fact that all turbines present different patterns for the occurrence of errors showed that the errors were independent for each turbine.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E&nbsp;\u003C\u002Fp\u003E\u003Cp\u003EOur data scientists also investigated the feasibility of developing a system of two complimentary predictive models to help optimise maintenance scheduling and minimise maintenance costs. One model would focus on the prediction of component-specific failures (given suitable error data to train the model on) whilst the other would predict indiscriminate failures in the turbines based on recent operating performance, faults, and maintenance programmes.\u003C\u002Fp\u003E\u003Cp\u003E&nbsp;\u003C\u002Fp\u003E\u003Cp\u003EBy the end of the project, the team built a successful proof-of-concept which was able to predict significant failures for selected lead times. We also identified how best to improve the outputs by fine-tuning parameters, using different lead times and timeframes for training data, and developing specific models for each turbine or component system.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cstrong\u003E&nbsp;\u003C\u002Fstrong\u003E\u003C\u002Fp\u003E",solution_list_items:[],solution_image:a,solution_image_attribution:a,impact:"\u003Cp\u003EOur analysis demonstrated that the frequency of errors that lead to downtime of the wind turbines had increased from 2015 to 2019, both in total count as well as for all levels of severity. While these errors affect the availability of the turbines, they did not affect the power production to a large extent, with the exception of one turbine. While weather variables were seen to act on all turbines equally, the fact that all turbines present different patterns for the occurrence of errors showed that the errors were independent for each turbine.&nbsp;\u003C\u002Fp\u003E\u003Cp\u003E&nbsp;\u003C\u002Fp\u003E\u003Cp\u003EOur data scientists also investigated the feasibility of developing a system of two complimentary predictive models to help optimise maintenance scheduling and minimise maintenance costs. One model would focus on the prediction of component-specific failures (given suitable error data to train the model on) whilst the other would predict indiscriminate failures in the turbines based on recent operating performance, faults, and maintenance programmes.\u003C\u002Fp\u003E\u003Cp\u003E&nbsp;\u003C\u002Fp\u003E\u003Cp\u003EBy the end of the project, the team built a we built a successful proof-of-concept that was able to predict significant failures for selected lead times. We also identified how best to improve the outputs by fine-tuning parameters, using different lead times and timeframes for training data, and developing specific models for each turbine or component system.\u003C\u002Fp\u003E\u003Cp\u003E\u003Cstrong\u003E&nbsp;\u003C\u002Fstrong\u003E\u003C\u002Fp\u003E",testimonial:a,project_metadata:{title:bT,description:"Investigating the likely reasons for observed operational reductions in turbine availability and production output during operational wind windows (wind speeds \u003E3ms-1 and \u003C25ms-1) and to explore the potential for developing an AI-based predictive maintenance programme ",meta_image:{url:bU,imgix_url:bV}}}]},contact:{contact:{}},cookie:{showCookieBar:f},events:{events:[{title:"All Energy",date:"2024-05-15",event_dates:"15-16 May, Glasgow, UK",description:a,event_link:a},{title:"Renewables Revenue Summit",date:"2024-05-22",event_dates:"22-23 May, London, UK",description:a,event_link:a},{title:"Global Offshore Wind",date:"2024-06-18",event_dates:"18-19 June, Manchester, UK",description:a,event_link:a},{title:"World Utilities Congress 2024",date:"2024-09-16",event_dates:"16-18 September, Abu Dhabi, UAE",description:a,event_link:a},{title:"Wind Energy",date:"2024-09-24",event_dates:"24-27 September, Hamburg, Germany",de

1scription:a,event_link:a},{title:"ENA Innovation Summit 2024",date:"2024-10-29",event_dates:"29-30 October 2024, Liverpool, UK",description:a,event_link:a}]},homePage:{homeBanner:{id:"649c1c627df15a13847d77ca",slug:"home-page-banner",title:"Home page banner",content:b,bucket:d,created_at:bW,created_by:c,modified_at:bX,created:bW,status:e,thumbnail:b,published_at:bX,modified_by:c,publish_at:a,unpublish_at:a,type:n,metadata:{banner_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fa206cd60-f7ff-11ee-b8e9-b1c350f53f6e-Wind-and-Solar-home-page-banner.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fa206cd60-f7ff-11ee-b8e9-b1c350f53f6e-Wind-and-Solar-home-page-banner.jpg"},title:"Data science for the environment",subtitle:"Providing cutting-edge data science to help organisations meet Net Zero and climate change targets"}},homeComponents:[{id:"649c1c647df15a13847d77d2",slug:bY,title:"Our offerings Section",content:b,bucket:d,created_at:bZ,created_by:c,modified_at:b_,created:bZ,status:e,thumbnail:b,published_at:b_,modified_by:c,publish_at:a,unpublish_at:a,type:bY,metadata:{offerings:[{icon:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fd6f9d900-76e5-11ed-bac9-7fe1734a16aa-Scale.png",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fd6f9d900-76e5-11ed-bac9-7fe1734a16aa-Scale.png"},icon_alt_text:b$,title:b$,information:"Our modelling activities are focussed on solving strategic challenges requiring innovative thinking and novel approaches. With expertise spanning data science, operational research, physics and engineering, we provide highly specialised data handling and analysis services to ensure that no data problem is too difficult to solve. \n\n"},{icon:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fd6f2d420-76e5-11ed-bac9-7fe1734a16aa-Analysis.png",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fd6f2d420-76e5-11ed-bac9-7fe1734a16aa-Analysis.png"},icon_alt_text:ca,title:ca,information:"With access to global meteorological and climate data, satellite-based observations and in-house numerical weather modelling capability, we can provide independent technical support in areas such as solar and wind resource assessments, meteorological verification studies, weather risk assessment and climate scale impact studies.  "},{icon:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fd6f6f2d0-76e5-11ed-bac9-7fe1734a16aa-Framework.png",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fd6f6f2d0-76e5-11ed-bac9-7fe1734a16aa-Framework.png"},icon_alt_text:cb,title:cb,information:"Advances in digitalisation and remote sensing provide huge potential for enhancing operational performance through data mining and analysis. We are experts in developing custom software tools that transform large, complex data streams into valuable and accessible insights to gain efficiencies, reduce risks, improve asset performance and inform strategic thinking. "}]}},{id:y,slug:z,title:A,content:b,bucket:d,created_at:i,created_by:c,modified_at:j,created:i,status:e,thumbnail:b,published_at:j,modified_by:c,publish_at:a,unpublish_at:a,type:l,metadata:{background_image:a,text:B,cta_text:C,background_color:D}},{id:"649c1c657df15a13847d77d7",slug:cc,title:"Product section",content:b,bucket:d,created_at:cd,created_by:c,modified_at:ce,created:cd,status:e,thumbnail:b,published_at:ce,modified_by:c,publish_at:a,unpublish_at:a,type:cc,metadata:{title:cf,subtitle:cg,products:[{id:ch,slug:"energymetric-lbf89xs8",title:"EnergyMetric",content:b,bucket:d,created_at:ci,created_by:c,modified_at:cj,created:ci,status:e,thumbnail:b,published_at:cj,modified_by:c,publish_at:a,unpublish_at:a,type:"products",metadata:{logo:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F5630e690-7714-11ed-bac9-7fe1734a16aa-EnergyMetric---Main.png",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F5630e690-7714-11ed-bac9-7fe1734a16aa-EnergyMetric---Main.png"},description:"EnergyMetric is cutting-edge SaaS software to support the energy transition. From utility-scale solar and wind projects through to complex hybrid portfolios and national roadmaps, EnergyMetric supports accurate generation planning and assessment of renewable energy developments.",link_text:"Visit EnergyMetric",link_url:"https:\u002F\u002Fenergy-metric.com"}}]}},{id:"649c1c657df15a13847d77d8",slug:ck,title:"Project Stories Section",content:b,bucket:

1d,created_at:"2022-12-09T10:15:53.637Z",created_by:c,modified_at:X,created:X,status:e,thumbnail:b,published_at:X,modified_by:c,type:ck,metadata:{title:Y,case_studies_count:6}},{id:"649c1c667df15a13847d77db",slug:cl,title:"News Section",content:b,bucket:d,created_at:E,created_by:c,modified_at:E,created:E,status:e,thumbnail:b,published_at:E,modified_by:c,type:cl,metadata:{title:Z}},{id:"662f7cfd110003f9e3bf6149",slug:cm,title:"Partners section",content:b,bucket:d,created_at:"2024-04-29T10:57:01.814Z",modified_at:cn,status:e,published_at:cn,modified_by:c,created_by:c,publish_at:a,thumbnail:b,type:cm,metadata:{mobile_xs:{url:F,imgix_url:G},mobile:{url:F,imgix_url:G},tablet:{url:co,imgix_url:cp},desktop:a,desktop_xl:{url:cq,imgix_url:cr},text:cs,cta_text:ct,background_colour:cu}}],pageMetadata:{title:R,description:"We apply advanced data science techniques and software engineering to develop the tools, insight and advice to help you better understand the risks and opportunities",image:{url:g,imgix_url:h}}},knowledgeHub:{khItems:[{slug:"electricity-market-modelling-2",page_link:_,always_first:f,title:"Electricity market modelling 2",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F2bc198e0-9086-11ef-a1ab-839814478987-Electricity-market-modelling-2.png",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F2bc198e0-9086-11ef-a1ab-839814478987-Electricity-market-modelling-2.png"},use_image_in_banner:f,introduction:"Exploring weather-driven changes in price formation in the GB market",content:"\u003Cp\u003E\u003Cspan class=\"fr-video fr-deletable fr-fvc fr-dvb fr-draggable\" draggable=\"true\"\u003E\u003Ciframe src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002F3CMKN795468?&wmode=opaque&rel=0\" height=\"360\" width=\"640\" class=\"fr-draggable\"\u003E\u003C\u002Fiframe\u003E\u003C\u002Fspan\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EThis is an unedited recording of our webinar held on 01 October 2024. It is not possible to interact with polling or to raise questions.\u003C\u002Fp\u003E",download:a,published:"2024-10-01",author:a},{slug:"electricity-market-modelling",page_link:_,always_first:f,title:"Electricity market modelling 1",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Faa8e7820-49d5-11ef-bbaa-af49ecc8228f-Electricty-Market-Modelling-opening-slide.png",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Faa8e7820-49d5-11ef-bbaa-af49ecc8228f-Electricty-Market-Modelling-opening-slide.png"},use_image_in_banner:f,introduction:"How will climate change impact renewable investments?",content:"\u003Cp style=\"position: relative;overflow: hidden;width: 100%;padding-top: 56.25%;\"\u003E\u003Ciframe style=\"position: absolute;top: 0;left: 0;bottom: 0;right: 0;width: 100%;height: 100%;\" width=\"560\" height=\"315\" src=\"https:\u002F\u002Fwww.youtube.com\u002Fembed\u002FkSnw7KPTNA4?si=ewaY8abW75RnqmKl&start=240&autoplay=1&fs=0&playlist=kSnw7KPTNA4&loop=1\" title=\"YouTube video player\"\u003E\u003Cspan class=\"fr-mk\" style=\"display: none;\"\u003E&nbsp;\u003C\u002Fspan\u003E\u003Cspan class=\"fr-mk\" style=\"display: none;\"\u003E&nbsp;\u003C\u002Fspan\u003E\u003Cspan class=\"fr-mk\" style=\"display: none;\"\u003E&nbsp;\u003C\u002Fspan\u003E\u003Cspan class=\"fr-mk\" style=\"display: none;\"\u003E&nbsp;\u003C\u002Fspan\u003E\u003Cspan class=\"fr-mk\" style=\"display: none;\"\u003E&nbsp;\u003C\u002Fspan\u003E\u003Cspan class=\"fr-mk\" style=\"display: none;\"\u003E&nbsp;\u003C\u002Fspan\u003E\u003Cspan class=\"fr-mk\" style=\"display: none;\"\u003E&nbsp;\u003C\u002Fspan\u003E\u003C\u002Fiframe\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cbr\u003E\u003C\u002Fp\u003E\u003Cp\u003EThis is an unedited recording of our webinar held on 16 July 2024. It is not possible to interact with polling or to raise questions.\u003C\u002Fp\u003E",download:a,published:"2024-07-16",author:a},{slug:"modelling-power-outputs-from-wind-turbines-from-normal-wind-speed-to-non-normal-power-distributions",page_link:$,always_first:f,title:"Modelling power outputs from wind turbines â from normal wind speed to non-normal power distributions",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F6272d210-5d46-11ee-bdcf-b7795530a864-Insights-Images-Turbines.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F6272d210-5d46-11ee-bdcf-b7795530a864-Insights-Images-Turbines.jpg"},use_image_in_banner:f,introduction:"The estimated energy production from wind is a key consideration in determining bankability. To secure project finance, a thorough evaluation of the uncertainty in the wind resource is needed.  Within our weather analytics team, we are always interested in how wind simulation errors propagate through our power modelling software, EnergyMetric. ",content:"\u003Cp id=\"isPasted\"\u003E\u003Cspan style=\"font-size: 18px;\"\u003EThe estimated energy production from wind is a key consideration in determining bankability. To secure project finance, a thorough evaluation of the uncertainty in the wind resource is needed.\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003EWithin our weather analytics team, we are always interested in how wind simulation errors propagate through our power modelling software, EnergyMetric. Errors on weather forecasts of wind speed typically follow a normal distribution (the &lsquo;bell curve&rsquo;).\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003EHowever, the non-linear nature of the power curves used to estimate the resulting wind energy produced have the effect of transforming the wind speed errors into a family of non-normal distributions for the power estimates. This can be seen in the following 4 examples:\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Col id=\"isPasted\"\u003E\u003Cli style=\"font-size: 18px;\"\u003E\u003Cstrong\u003ELow wind speeds\u003C\u002Fstrong\u003E - At low wind speeds, the distribution of wind power estimates is truncated to the right as the turbine fails to cut in for the lowest wind speed samples.\u003Cbr\u003E\u003Cbr\u003E\u003Cimg class=\"fr-fil fr-dib\" alt=\"1-Diagram.png\" src=\"https:\u002F\u002Fimgix.cosmicjs.com\u002F7f73e620-5de5-11ee-bdcf-b7795530a864-1-Diagram.png\"\u003E\u003Cbr\u003E\u003Cbr\u003E\u003C\u002Fli\u003E\u003Cli id=\"isPasted\" style=\"font-size: 18px;\"\u003E\u003Cstrong\u003EMid wind speeds\u003C\u002Fstrong\u003E - As the wind speed increases and enters the &lsquo;ramping&rsquo; part of the power curve, the gradient acts to amplify the uncertainty in the wind and the standard deviation of the power estimates increases.\u003Cbr\u003E\u003Cbr\u003E\u003Cimg class=\"fr-fil fr-dib\" alt=\"2-Diagram.png\" src=\"https:\u002F\u002Fimgix.cosmicjs.com\u002F7f7a9ce0-5de5-11ee-bdcf-b7795530a864-2-Diagram.png\"\u003E\u003Cbr\u003E\u003Cbr\u003E\u003C\u002Fli\u003E\u003Cli id=\"isPasted\" style=\"font-size: 18px;\"\u003E\u003Cstrong\u003EHigh wind speeds\u003C\u002Fstrong\u003E - At higher wind speeds toward the top of the ramp, the distribution of wind power estimates is truncated to the left as the turbine maxes out for the highest wind speed samples.\u003Cbr\u003E\u003Cbr\u003E\u003Cimg class=\"fr-fil fr-dib\" alt=\"3-Diagram.png\" src=\"https:\u002F\u002Fimgix.cosmicjs.com\u002F7f76a540-5de5-11ee-bdcf-b7795530a864-3-Diagram.png\"\u003E\u003Cbr\u003E\u003Cbr\u003E\u003C\u002Fli\u003E\u003Cli id=\"isPasted\" style=\"font-size: 18px;\"\u003E\u003Cstrong\u003EVery high wind speeds\u003C\u002Fstrong\u003E - Finally, for very high wind speeds close to the turbine limit, the distribution of wind power estimates becomes pathologically bimodal as some samples max and other cut out. Taking the mean of the power estimates as representative here would be very misleading.\u003Cbr\u003E\u003Cbr\u003E\u003Cimg class=\"fr-fil fr-dib\" alt=\"4-Diagram.png\" src=\"https:\u002F\u002Fimgix.cosmicjs.com\u002F7f7c71a0-5de5-11ee-bdcf-b7795530a864-4-Diagram.png\"\u003E\u003Cbr\u003E\u003Cbr\u003E\u003C\u002Fli\u003E\u003C\u002Fol\u003E\u003Cp\u003E\u003Cstrong\u003E\u003Cspan style=\"font-size: 18px;\"\u003EConclusions\u003C\u002Fspan\u003E\u003C\u002Fstrong\u003E\u003Cbr\u003E\u003Cspan style=\"font-size: 18px;\"\u003EThe analysis above assumes that the power curve is known and can be represented by a nice clean line. In reality, this isn&rsquo;t the case and a probabilistic model is required. Overlapping Mixtures of Gaussian Processes (OMGP) provide such a model and this will be discussed in a subsequent post.\u003C\u002Fspan\u003E\u003C\u002Fp\u003E",download:a,published:"2023-08-21",author:{id:"6504554d20fb860008a68212",slug:"ben",title:"Ben",content:b,bucket:

1d,created_at:aa,modified_at:aa,status:e,published_at:aa,modified_by:c,created_by:c,type:ab,metadata:{name:"Ben Lloyd-Hughes",mugshot:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Faaa898f0-53c6-11ee-8d99-6566412c38cc-Bensmall.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Faaa898f0-53c6-11ee-8d99-6566412c38cc-Bensmall.jpg"},position:"Principal Data Scientist",email:"[email protected]",linkedin:"https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fbenjamin-lloyd-hughes-b41556112\u002F"}}},{slug:"viewpoint-magazine",page_link:o,always_first:f,title:"Viewpoint CSSP Brazil",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F42fc8d20-5d48-11ee-bdcf-b7795530a864-Viewpoint-CSSP.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F42fc8d20-5d48-11ee-bdcf-b7795530a864-Viewpoint-CSSP.jpg"},use_image_in_banner:f,introduction:"Understanding the impacts of climate change in Brazil",content:a,download:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F68b5d6c0-5d48-11ee-bdcf-b7795530a864-IEA_VIEWpoint-Brazil-CSSP-2022_Final-090522_Eng.pdf",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F68b5d6c0-5d48-11ee-bdcf-b7795530a864-IEA_VIEWpoint-Brazil-CSSP-2022_Final-090522_Eng.pdf"},published:"2022-03-16",author:a},{slug:"iea-brochure",page_link:o,always_first:ac,title:"IEA Brochure",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F9a51bb00-53ce-11ee-8d99-6566412c38cc-IEA-Corporate-Brochure-2023TH.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F9a51bb00-53ce-11ee-8d99-6566412c38cc-IEA-Corporate-Brochure-2023TH.jpg"},use_image_in_banner:f,introduction:"Introducing the Institute for Environmental Analytics",content:a,download:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fce058260-53ce-11ee-8d99-6566412c38cc-IEA-Corporate-Brochure-2023.pdf",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fce058260-53ce-11ee-8d99-6566412c38cc-IEA-Corporate-Brochure-2023.pdf"},published:cv,author:a},{slug:"energymetric-brochure-2023",page_link:o,always_first:f,title:"EnergyMetric brochure 2023",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F1a1ca0c0-53d4-11ee-8d99-6566412c38cc-Energy-Metric-Flyer-4ppFInal-0722TH.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F1a1ca0c0-53d4-11ee-8d99-6566412c38cc-Energy-Metric-Flyer-4ppFInal-0722TH.jpg"},use_image_in_banner:f,introduction:"Introducing EnergyMetric",content:a,download:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fbf129ae0-53ce-11ee-8d99-6566412c38cc-Energy-Metric-Flyer-4ppFInal-0722.pdf",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fbf129ae0-53ce-11ee-8d99-6566412c38cc-Energy-Metric-Flyer-4ppFInal-0722.pdf"},published:cv,author:a},{slug:"a-glimpse-into-atmospheric-data-driven-applicability",page_link:$,always_first:f,title:"Assessing technical advances in Numerical Weather Prediction (NWP)",image:{url:S,imgix_url:T},use_image_in_banner:f,introduction:"Understanding the weather is crucial is an energy-driven world. The rapid increase in energy consumption, along with the desire to transition away from fossil fuels on a global scale, has accelerated the need for solutions to an ever-lasting problem: how do we accurately represent the weather in an applicable manner? This article looks at advances in NWP techniques and how these might improve modelling capability.",content:"\u003Cp id=\"isPasted\"\u003E\u003Cspan style=\"font-size: 18px;\"\u003EUnderstanding the weather is crucial for understanding the changing nature of energy systems. The rapid increase in energy consumption, along with the desire to achieve net-zero systems in future, has accelerated the need for solutions to an on-going problem: how do we accurately model the weather to support better system analysis?\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003EOur weather modelling team use the state-of-the-art Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model to generate accurate global weather hindcasts and short-term forecasts at high spatial and temporal resolution using AWS&rsquo;s cloud platform. Not only does WRF allow us full-flexibility and control of our weather simulations, but scaling the simulations on AWS&rsquo;s cloud platform allows us to constantly push the boundaries of running WRF in an efficie

1nt manner, both for data quality and the time-taken to produce data. However, WRF is not the only NWP model. Both academia and industry use a variety of different NWP models, with many tailored for a specific region or climate type.\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003EOne advantage of regionally configured NWP models is that they can be used \u003Cem\u003Ealongside&nbsp;\u003C\u002Fem\u003Eother NWP models, like WRF, allowing for the generation of diverse weather production from a multi-model perspective. This gives us the opportunity to explore the confidence and uncertainties of our simulations, helping improve our understanding of atmospheric processes and diagnosing model biases and limitations.\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003EIndeed, one possibility is using multiple NWP models to generate an ensemble of past weather data. Although ensemble approaches are typically used for regional, continental and global forecasting (e.g., ECMWF, UKMO, DWD), the application of ensembles to hindcasting is a general unknown. Yet understanding the past (particularly with respect to how NWP models capture the weather) is of critical importance to understanding how we can predict the future.\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003EFurthermore, not only are regional-specific NWP models now becoming more available, but so are \u003Cem\u003Eregionally tailored&nbsp;\u003C\u002Fem\u003Eweather reanalysis datasets. These datasets take global, coarse resolution reanalysis datasets (e.g., ECMWF&rsquo;s ERA5) and downscale them using novel machine or deep learning techniques to return a much higher-resolution dataset for a given region. Such datasets avoid many of the bottlenecks of using NWP models, including requiring immense computational power.\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003ERegional weather reanalysis datasets can be useful for various sectors, including energy production, agriculture, water resource management and infrastructure planning. Accurate and high-resolution information about past weather conditions allows for better understanding of the local climate characteristics, such as the frequency and intensity of extreme events like storms, heatwaves, or heavy rainfall. This information can guide decision-makers in an energy-driven world, designing efficient and resilient infrastru

1cture to help maximise energy production and reduce OPEX costs over a typical operating lifespan.\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003EEnhancements of both regional NWP models and reanalysis datasets have only been made possible due to recent implementations of better data assimilation techniques. Data assimilation combines recent observations with a previous weather forecast to obtain the best estimate of the current state of the atmosphere. Although such techniques are typically performed when constructing global reanalysis datasets, the intricacies of local effects are often lost owing to the coarse resolution of the final product. Indeed, being able to produce higher resolution regional weather reanalysis datasets allows for a more accurate representation of weather events: either in real-time, or by glimpsing into the past.\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003EMost of the applications of enhanced data assimilation techniques are being applied to nowcasting, with a particular focus on accurately nowcasting severe weather events (e.g., DWD&rsquo;s SINFONY project, UKMO&rsquo;s Coupled Data Assimilation team) or solar production. However, combined with machine and deep learning techniques, the recent advancements of data assimilation techniques may lead to a better understanding of past weather events and, as such, allow for more accurate forecasts.\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003EMany recent enhancements of data assimilation techniques have been made possible by EUMETSAT&rsquo;s latest geostationary satellite: Meteosat Third generation Imager 1 (MTG-I1). MTG-I1 returns ultra-high resolution spatial and temporal data of unprecedented detail, spanning a range of wavelength channels.\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003EOne current application of such data is the integration into the German Meteorological Service&#39;s SINFONY framework, combining NWP models with the ultra-high resolution satellite imagery, allowing for more accurate near-future forecasting and nowcasting.&nbsp;\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003EAccurate nowcasting can now be performed for up to three hours in advance over Continental Europe, a critical advancement for understanding the real-time evolution of weather risks. The open-source data is made available using EUMETSAT&rsquo;s SIFT application, with more wavelength channels becoming available as MTG-I1 continues to be calibrated. As more data comes online, the advancements of data assimilation techniques using satellite data will only increase.\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003E\u003Cstrong\u003EConclusions\u003C\u002Fstrong\u003E\u003C\u002Fspan\u003E\u003Cbr\u003E\u003Cspan style=\"font-size: 18px;\"\u003EIn summary, several innovations in weather modelling are coming together to help improve the accuracy of hindcast and forecast data:\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cul\u003E\u003Cli style=\"font-size: 18px;\"\u003Eadvancements in regionally-configured, highly-specialised NWP models allow for regional ensemble-like analyses, pathing the way for a better understanding of NWP model strengths and weaknesses.\u003C\u002Fli\u003E\u003Cli style=\"font-size: 18px;\"\u003Eregionally-tailored weather reanalysis datasets allow us to bypass many of the limitations of running NWP models, including requiring immense computational resources.\u003C\u002Fli\u003E\u003Cli style=\"font-size: 18px;\"\u003Eenhancements in data assimilation techniques, especially the introduction of new satellite products, have increased nowcasting and short-term forecasting accuracy and capabilities drastically.\u003C\u002Fli\u003E\u003C\u002Ful\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003EIt&rsquo;s an exciting time to be in the atmospheric modelling industry. Not only are rapid technological improvements allowing for faster, more efficient NWP modelling, but additional reanalysis datasets and external data sources allow for the continuous refinement of produced data, leading the way for a better understanding of energy production from a hindcasting, nowcasting and forecasting perspective.\u003C\u002Fspan\u003E\u003C\u002Fp\u003E\u003Cp\u003E\u003Cspan style=\"font-size: 18px;\"\u003EHere at the Institute for Environmental Analytics, we are at the forefront of adapting to and integrating the latest advancements in NWP modelling and beyond into our

1commercial products and technical consulting projects.\u003C\u002Fspan\u003E\u003C\u002Fp\u003E",download:a,published:"2023-05-19",author:{id:"6515508dadfd710008f9698a",slug:"ty-buckingham",title:cw,content:b,bucket:d,created_at:"2023-09-28T10:08:13.191Z",modified_at:cx,status:e,published_at:cx,modified_by:c,created_by:c,publish_at:a,thumbnail:b,type:ab,metadata:{name:cw,mugshot:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F3dcba990-5de7-11ee-bdcf-b7795530a864-Ty_small.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F3dcba990-5de7-11ee-bdcf-b7795530a864-Ty_small.jpg"},position:"Applied Meteorologist and Data Analyst",email:a,linkedin:a}}},{slug:"the-role-of-data-in-africas-energy-transition",page_link:o,always_first:ac,title:"White Paper",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F3b8e94b0-f65f-11ee-b8e9-b1c350f53f6e-White-Paper_Generic_TH.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F3b8e94b0-f65f-11ee-b8e9-b1c350f53f6e-White-Paper_Generic_TH.jpg"},use_image_in_banner:f,introduction:"This white paper looks at how high-resolution, high-quality weather data and complex data analysis and visualisation tools enable users to confidently evaluate the generation potential and financial performance of renewable projects. Informing and supporting strategic planning and operational decision-making for the\ntransition to clean energy across Africa.",content:"\u003Cp\u003EThe International Renewable Energy Agency (IRENA) estimates that clean renewable energy sources could provide nearly a quarter of Africa&rsquo;s energy needs by 2030, and up to two-thirds by 2050.\u003C\u002Fp\u003E\u003Cp\u003EWhile there is great potential for renewables, a BP study of Africa&rsquo;s electricity generation in 2020 showed that it was heavily dependent on natural gas (46%) and coal (35%). For many African countries, fossil fuels are both a

1source of power and revenue. Making the transition to renewable energy sources will have a major impact across the continent and will require compelling arguments.\u003C\u002Fp\u003E\u003Cp\u003EEvery stage along the energy transition involves important, complex decisions. When it comes to integrating renewables in the generation mix, those decisions are invariably influenced by the weather. Understanding how weather behaviour will impact energy generation plays an enormous role in any and every decision about renewable energy.\u003C\u002Fp\u003E\u003Cp\u003EAs organisations across Africa look to development finance institutions, governments, NGOs and private sector investors to secure financing at scale, the need to de-risk climate investments and incentivise funding from institutional investors, demands informed insight and persuasive scenario modelling.\u003C\u002Fp\u003E",download:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F9538cb30-f65e-11ee-b8e9-b1c350f53f6e-IEA-White-Paper_Impacts-of-weather-on-Renewable-transition_WR.pdf",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F9538cb30-f65e-11ee-b8e9-b1c350f53f6e-IEA-White-Paper_Impacts-of-weather-on-Renewable-transition_WR.pdf"},published:"2023-02-23",author:{id:"64c121205ab154000835cdfe",slug:aT,title:"Alan",content:b,bucket:d,created_at:"2023-07-26T13:35:28.536Z",modified_at:cy,status:e,published_at:cy,modified_by:c,created_by:c,publish_at:a,thumbnail:b,type:ab,metadata:{name:K,mugshot:{url:M,imgix_url:N},position:L,email:O,linkedin:P}}}],khBanner:{id:"64c11345af120500082bdb8d",slug:"knowledge-hub-banner",title:"Knowledge Hub banner",content:b,bucket:d,created_at:cz,modified_at:"2023-07-26T12:36:46.746Z",status:e,published_at:cz,modified_by:c,created_by:c,type:n,metadata:{banner_image:{url:cA,imgix_url:cB},title:cC,subtitle:a}},khComponents:[{id:y,slug:z,title:A,content:b,bucket:d,created_at:i,created_by:c,modified_at:j,created:i,status:e,thumbnail:b,published_at:j,modified_by:c,publish_at:a,unpublish_at:a,type:l,metadata:{background_image:a,text:B,cta_text:C,background_color:D}}],pageMetadata:{title:"Knowledge Hub | The IEA",description:"Access the resources produced by the IEA.",image:{url:cA,imgix_url:cB}}},menu:{menu:[{title:"Home",page_link:cD},{title:"About Us",page_link:"about"},{title:Y,page_link:"project_stories"},{title:cC,page_link:"knowledge-hub",submenu:[{title:"Insights",page_link:$,number_wide:3,index_format:cE},{title:"Literature",page_link:o,number_wide:4,index_format:"COMPACT"},{title:"Webinars",page_link:_,number_wide:2,index_format:cE}]},{title:Z,page_link:"news"}],downloadBanner:a,showContactForm:f,showSubscribeForm:f,showDownloadForm:{type:b,url:b,id:b},showCampaignForm:a,campaignContact:f,acceptedCookie:f,showConsentWindow:f,showMobileMenu:f,showWeatherAssetWarning:f},news:{news:[{slug:"webinar-manage-the-impact-of-variable-weather-on-price-distribution-in-an-evolving-gb-electricity-system",title:cF,content:b,created_at:"2024-09-30T09:37:03.075Z",metadata:{headline:"Upcoming webinar: The impact of variable weather on price distribution in an evolving GB electricity system",main_image:{url:cG,imgix_url:cH},main_image_attribution:a,story_excerpt:"The GB energy market is going through fundamental change. Ever higher proportions of renewables and storage, increasing flexibility and uncertain weather patterns all affect price formation and the financial performance of solar, wind and storage assets.",content:"Current market modelling assessments used for financial modelling and risk management, rely on typical meteorological years or limited sampling to capture weather-related variability. Is this sufficient to understand how weather patterns affect price formation?\u003Cbr\u003E\n \nIn this webinar we will explore how to create proper weather and climate conditioned price distributions and how this can be used to enhance market modelling for investment decisions.\u003Cbr\u003E\n\n\u003Cb\u003EWhen:\u003C\u002Fb\u003E Oct 1, 2024 1PM (BST)\n\nPlease click the link below to join the webinar: \u003Ca href=\"https:\u002F\u002Fus02web.zoom.us\u002Fj\u002F86396663924\" target=\"_blank\"\u003Ehttps:\u002F\u002Fus02web.zoom.us\u002Fj\u002F86396663924\u003C\u002Fa\u003E\n",news_metadata:{title:cF,description:"In this webinar we will explore how to create proper weather and climate conditioned price distributions and how this can be used to enhance market modelling for investment decisions.",image:{url:cG,imgix_url:cH}}}},{slug:"helping-smes-boost-growth-through-data-and-software-innovation",title:ad,content:b,created_at:"2024-09-24T09:29:07.228Z",metadata:{headline:ad,main_image:{url:cI,imgix_url:cJ},main_image_attribution:a,story_excerpt:"Over the spring and summer, weâve been busy providing data analysis and software support to several SMEs to help turbo-charge their growth and product development ambitions.",content:"\u003Cp\u003EOver the spring and summer, weâve been busy providing data analysis and software support to several SMEs to help turbo-charge their growth and product development ambitions.\u003C\u002Fp\u003E\u003Cbr\u003E\n\n\u003Cp\u003EUtilising Innovate UK funding, the clients all picked the IEA team due to our ability to turn projects round quickly and find innovative technical solutions to problems that their in-house teams lacked the bandwidth or capability to deal with.\u003C\u002Fp\u003E\u003Cbr\u003E\n\n\u003Cp\u003EThe projects included:\u003C\u002Fp\u003E\n\n\u003Cul\u003E\u003Cli\u003E\u003Cstrong\u003E- Energy Saving Bear Ltd\u003C\u002Fstrong\u003E â developing a machine learning model to provide real time alerts of energy consumption anomalies in buildings.\u003C\u002Fli\u003E\u003Cbr\u003E\n\n\u003Cli\u003E\u003Cstrong\u003E- CalCommuter\u003C\u002Fstrong\u003E â undertaking a comprehensive data modelling exercise to identify âlatentâ Scope 3 emission reduction opportunities for employees by worksite and mode of transport as part of the development of a new sustainable transport tool by David Smith Consulting Ltd.\u003C\u002Fli\u003E\u003Cbr\u003E\n\n\u003Cli\u003E\u003Cstrong\u003E- MDY Legal\u003C\u002Fstrong\u003E â developing a proof-of-concept data analysis dashboard for a London-based law firm developing a new service helping large financial sector companies identify climate legal r

1isk from investments and operations. \u003C\u002Fli\u003E\u003C\u002Ful\u003E\n\n\u003Cp\u003EFor more information on these and other projects, check out our \u003Ca href=\".\u002Fproject_stories\" class=\"action--text\"\u003EProject Stories page\u003C\u002Fa\u003E.\u003C\u002Fp\u003E",news_metadata:{title:ad,description:"Utilising Innovate UK funding, the clients all picked the IEA team due to our ability to turn projects round quickly and find innovative technical solutions to problems that their in-house teams lacked the bandwidth or capability to deal with.",image:{url:cI,imgix_url:cJ}}}},{slug:"modelling-the-economics-of-long-duration-energy-storage",title:p,content:b,created_at:"2024-03-21T12:14:33.866Z",metadata:{headline:p,main_image:{url:cK,imgix_url:cL},main_image_attribution:p,story_excerpt:"Our energy modelling team recently worked with a South African energy company to support the analysis for their novel gravity storage system. ",content:"\u003Cp\u003EOur energy modelling team recently worked with a South African energy company to support the analysis for their novel gravity storage system. \u

1003C\u002Fp\u003E\u003Cbr\u003E\n\n\u003Cp\u003EThe proposed solution uses power from renewable sources to raise and lower weights, in the process storing and releasing energy over longer cycles than can be achieved with chemical battery technologies. Not only does the âgravity batteryâ offer the potential to store energy over longer time periods, but to do so far more cost efficiently than would be possible with alternatives. \u003C\u002FP\u003E\n\n\u003Cp\u003EThe technology is being trialled in the South African market in collaboration with the mining industry, where high energy consumption and ready access to mine shafts provide an ideal opportunity to test the potential savings. \u003C\u002Fp\u003E\u003Cbr\u003E\n\n\u003Cp\u003EOur analysis involved us modelling the production profiles and variability from both the solar and wind facilities, the demand profile for the off-taker and the optimal economic charging and discharging strategy when taking account of the other commercial factors such as: \u003C\u002Fp\u003E\u003Cbr\u003E\n\n\u003Cp\u003E- PPA pricing for the solar and wind procurement\u003C\u002Fp\u003E\u003Cbr\u003E\n\n\u003Cp\u003E- variable tariffs for any remaining grid inputs and\u003C\u002Fp\u003E\u003Cbr\u003E\n\n\u003Cp\u003E- all other charges associated with utilisation of the grid infrastructure.\u003C\u002Fp\u003E\u003Cbr\u003E",news_metadata:{title:p,description:p,image:{url:cK,imgix_url:cL}}}},{slug:"integrating-solar-wind-and-bess-onto-a-large-research-campus",title:"Integrating solar, wind and BESS onto a research campus",content:b,created_at:"2024-03-21T12:09:25.268Z",metadata:{headline:"Integrating solar, wind and BESS onto a large research campus",main_image:{url:cM,imgix_url:cN},main_image_attribution:"Solar panels",story_excerpt:"Our energy analysts recently worked with a large organisation to understand the potential for integrating solar, wind and BESS into their existing energy infrastructure. ",content:"\u003Cp\u003EOur energy analysts recently worked with a large R&D organisation to understand the potential for integrating solar, wind and BESS into their existing energy infrastructure. \u003C\u002Fp\u003E \u003Cbr\u003E\n\n\u003Cp\u003EWe provided comprehensive site and yield assessment of the potential for developing solar and wind capacity, detailed analysis of the associated economics of different options and strategic insights into how best to manage the utilisation of a portfolio of intermittent generation assets. The study covered several campuses and regional landholdings.\u003C\u002Fp\u003E \u003Cbr\u003E\n \n\u003Cp\u003EThe work draws on several of our key competencies and tools, including the use of our generation modelling software â EnergyMetric â to plan different scenarios with varying cost implications and the potential to offset electricity demand and deliver reductions in carbon emissions.  The on-site generation analysis was complemented with a further assessment of the potential for battery storage considering a number of use cases: peak shaving, load shifting and energy arbitrage. \u003C\u002Fp\u003E \u003Cbr\u003E",news_metadata:{title:"Integrating solar, wind and BESS to decarbonise a University Estate",description:"Integrating solar, wind and BESS onto a large University Estate",image:{url:cM,imgix_url:cN}}}},{slug:"analysing-solar-and-wind-generation-for-energy-trading",title:H,content:b,created_at:"2024-03-21T12:03:21.849Z",metadata:{headline:H,main_image:{url:cO,imgix_url:cP},main_image_attribution:"Wind and Solar",story_excerpt:"Our data scientists are working with an innovative energy business in South Africa to explore the potential for optimising their trading activity.",content:"\u003Cp\u003EOur data scientists are working with an innovative energy business in South Africa to explore the potential for optimising their trading activity.\u003C\u002Fp\u003E \u003Cbr\u003E\n\n\u003Cp\u003EAccessing a portfolio of clean energy providers is often beyond the remit of an individual corporate client, sourcing clean energy through a third-party energy trader can unlock this opportunity. However, energy traders need to manage this intermittency, which is often described as shape, or volume risk. Traders must also determine how best to use discreet blocks of energy from multiple generators on the supply side to meet demand from multiple off-takers on the demand side. \u003C\u002Fp\u003E \u003Cbr\u003E\n\n\u003Cp\u003EUsing our in-house software, EnergyMetric, our team will be modelling generation profiles from solar and wind facilities and then comparing these against likely energy demand from different customers across the country. If successful, this will enable our client to build out the supply side of the business and meet the variable demand requirements of multiple energy customers within specific regional areas.\u003C\u002Fp\u003E \u003Cbr\u003E",news_metadata:{title:H,description:H,image:{url:cO,imgix_url:cP}}}},{slug:"providing-meteorological-data-for-novel-wind-turbine-analysis",title:ae,content:b,created_at:"2023-09-26T14:56:22.516Z",metadata:{headline:ae,main_image:{url:cQ,imgix_url:cR},main_image_attribution:"Ilosta Logo",story_excerpt:"Working with clean tech start-up Ilosta to provide bespoke meteorological data and weather consultancy in support of the testing of their new wind turbine blade analysis software, âCrack Mapâ. ",content:"\u003Cp\u003EWe recently partnered with clean tech start-up Ilosta to provide bespoke meteorological data and weather consultancy in support of the testing of their new wind turbine blade analysis software, âCrack Mapâ.  \nThe innovative software leverages a range of data sources and utilises a novel physics-based AI algorithm to predict blade defects, thereby improving the reliability and increasing the lifespan of turbines. \u003C\u002Fp\u003E\u003Cbr\u003E\n\n\u003Cp\u003EAs part of a test project, the IEA weather modelling team provided Ilosta with a 10-year weather time series for a

1wind development zone in Scotland. The data was supplied at a 1km spatial resolution with 10-minute time steps and relevant weather variables (such as wind speed, hail and rain) at 50, 100, 150 and 200m heights. The data provided a rich characterisation of weather history in support of Ilostaâs technical analysis of blade defects.\u003C\u002Fp\u003E\u003Cbr\u003E\n\n\u003Cp\u003EWe look forward to supporting the Ilosta team as they develop their technology within the renewables industry.",news_metadata:{title:ae,description:"Working with Ilosta to provide bespoke meteorological data and weather consultancy in support of the testing of their new wind turbine blade analysis software, âCrack Mapâ. ",image:{url:cQ,imgix_url:cR}}}},{slug:"developing-an-iac-solution-for-new-remote-monitoring-platform",title:cS,content:b,created_at:"2023-09-20T12:48:27.318Z",metadata:{headline:cS,main_image:{url:cT,imgix_url:cU},main_image_attribution:cV,story_excerpt:cW,content:"\u003Cp\u003ESoftware engineers at the IEA recently provided technical consultancy to UK-based Dyna-mo Instruments to develop an Infrastructure as Code (IaC) solution to deploy their new SaaS-based remote monitoring software into AWS. \u003C\u002Fp\u003E\u003Cbr\u003E\n\u003Cp\u003EThe innovative new platform will enable customers to manage multiple projects via a single login covering a wide variety of remote monitoring applications. Key to the development of the platform is the wide array of sensor types and data that the platform can visualise in intuitive and relevant graphics.\u003C\u002Fp\u003E\u003Cbr\u003E\n\n\u003Cp\u003EThe IEA consultants utilised the IaC DevOps methodology to provision the clientâs cloud infrastructure using code rather than defining infrastructure components manually. This can help speed up the development of solutions and ensure a consistent deployment for different environments.\u003C\u002Fp\u003E\u003Cbr\u003E\n\n\u003Cp\u003EUtilising tools such as S3, Kinesis Firehose, Lambda, Amazon Glue and Amazon Athena, our DevOps engineers designed the system to be flexible enough to handle sensor data adhering to multiple schemas and ensured there was data alignment and transformation allowing data to be viewed easily in customer-facing dashboards. In addition, the solution was designed to be future-proof in terms of scalability and cost-effectiveness.\u003C\u002Fp\u003E \u003Cbr\u003E\n\n\u003Cem\u003EâWorking with IEA has been of enourmous value to this project. The team at IEA took time to ensure they had fully understood our requirements and provided great flexibility to support both our immediate needs and future ambitions for the platform.â \u003Cbr\u003E\u003C\u002Fem\u003E\u003Cb\u003EToby Cottam â Managing Direction, Dyna-mo Instruments.\u003C\u002Fb\u003E\n",news_metadata:{title:cV,description:cW,image:{url:cT,imgix_url:cU}}}},{slug:"oman-workshop-on-results-of-rainfall-modelling-project",title:af,content:b,created_at:"2023-09-20T10:11:47.37Z",metadata:{headline:af,main_image:{url:cX,imgix_url:cY},main_image_attribution:"Dr. Maria Noguer and Dr. Ben Lloyd-Hughes in Oman",story_excerpt:"IEA weather and climate experts - Dr. Maria Noguer and Dr. Ben Lloyd-Hughes - were recently in Muscat, Oman to present the results of a statistical analysis project examining the outcome of Omanâs national rainfall enhancement programme between 2019-2022 at a workshop organised by the National Rainfall Enhancement Centre.",content:"\u003Cp\u003EIEA weather and climate experts, Dr. Maria Noguer and Dr. Ben Lloyd-Hughes, were recently in Muscat, Oman to present the results of a statistical analysis project examining the outcome of Omanâs national rainfall enhancement programme between 2019-2022 at a workshop organised by the National Rainfall Enhancement Centre. \u003C\u002Fp\u003E\u003Cbr\u003E\n\u003Cp\u003EThe workshop was the culmination of a successful project undertaken on behalf of the Ministry of Agriculture, Fisheries Wealth and Water Resources, Sultanate of Oman. \u003C\u002Fp\u003E\u003Cbr\u003E\n\u003Cp\u003EThe analysis looked at different regions of the country where rainfall enhancement stations (RES) have been installed. The IEA team employed a two-step regression-based procedure to estimate the amount of rainfall attributed to RES operations, using a comprehensive dataset derived from raw meteorological observations and operational schedules, including RES and rainfall gauge networks, radiosonde profiles, DGMAN weather stations, and records of the operational status of the RES. \u003C\u002Fp\u003E\u003Cbr\u003E\n\u003Cp\u003EBy analysing rainfall frequency, intensity, and distribution in both regions, we were able to provide valuable insights into the effectiveness of RES and their impact on precipitation levels in Oman. The investigation examined the implications of weather anomalies on the rainfall enhancement analysis and modelling, highlighting the challenges in determining the actual impact of RES on precipitation levels and discussing potential biases in the statistical models.\u003C\u002Fp\u003E\u003Cbr\u003E\n\u003Cp\u003EThe findings of the investigation have the potential to contribute to the development of more effective rainfall enhancement strategies, inform decision-making regarding water resource management in arid and semi-arid regions and promote a better understanding of the complex interactions between meteorological factors and rainfall enhancement technologies.\u003C\u002Fp\u003E",news_metadata:{title:af,description:"IEA weather and climate experts - Maria Noguer and Dr. Ben Lloyd-Hughes - were recently in Muscat, Oman to present the results of a statistical analysis project examining the outcome of Omanâs national rainfall enhancement programme between 2019-2022 at a workshop organised by the National Rainfall Enhancement Centre.\n\nThe workshop w

1as the culmination of a successful project undertaken on behalf of the Ministry of Agriculture, Fisheries Wealth and Water Resources, Sultanate of Oman. ",image:{url:cX,imgix_url:cY}}}},{slug:"preparing-geospatial-data-to-support-climate-action-in-the-uk",title:cZ,content:b,created_at:"2023-09-20T10:00:49.884Z",metadata:{headline:cZ,main_image:{url:c_,imgix_url:c$},main_image_attribution:a,story_excerpt:"The IEA has been awarded a contract from the National Centre for Earth Observation to enable the effective translation of climate data\n",content:"\u003Cp\u003EWe are pleased to have been awarded a contract from the National Centre for Earth Observation to develop category-based geospatial data files for the UK to enable the effective translation of climate data into new forms of actionable information. \u003C\u002Fp\u003E\u003Cbr\u003E\n\u003Cp\u003EThis activity is part of the UK Earth Observation Climate Information Service (EOCIS) programme which provides contextual data to support climate analysis. \u003C\u002Fp\u003E\u003Cbr\u003E\nThe datasets will provide underpinning spatial and land classification information such as the NHS and Fire service administration boundaries, postcode sectors, parish, community, roads, railways, transmission lines, etc. These datasets will support the creation of climate information at high resolution and will provide underpinning data in support of national policy actions on climate change.",news_metadata:{title:"Geospatial data supporting climate action in the UK",description:"Translating Geospatial data, UK climate change action",image:{url:c_,imgix_url:c$}}}},{slug:"partnering-with-uk-power-networks-on-new-ofgem-sif-innovation-project",title:da,content:b,created_at:"2023-04-13T13:57:26.744Z",metadata:{headline:da,main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fdaff4600-dcfe-11ed-b6eb-0fc980522195-UKPN-Project2.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fdaff4600-dcfe-11ed-b6eb-0fc980522195-UKPN-Project2.jpg"},main_image_attribution:a,story_excerpt:"The Institute for Environmental Analytics has been awarded an initial 2-month Discovery Phase project to investigate the potential for developing a weather and climate monitoring platform for UK Power Networks, one of the UKâs leading DNOs (Distribution Network Operators).",content:"\u003Cstrong\u003EWe are pleased to announce that we have been awarded an initial 2-month Discovery Phase project to investigate the potential for developing a weather and climate monitoring platform for UK Power Networks, one of the UKâs leading DNOs (Distribution Network Operators). \u003C\u002Fstrong\u003E \n\u003Cbr\u003E\n\u003Cbr\u003E\nThe WARN project aims to improve the resilience and robustness of the power network during extreme weather events. The project will assess the feasibility of developing an integrated digital solution that monitors weather and climate-related asset vulnerabilities across three relevant time horizons:\n\u003Cbr\u003E\n\u003Cbr\u003E\n\na.\tShort-term (up to seven day-ahead forecasting)\u003Cbr\u003E\u003Cbr\u003E\nb.\tSeasonal (three-six month ahead outlooks) \u003Cbr\u003E\u003Cbr\u003E\nc.\tLong-term (10-50 year ahead climate projections)\n\u003Cbr\u003E\n\u003Cbr\u003E\nIf implemented, the platform will enable UK Power Networks to make decisions that will reduce the scope and scale of weather-related disruptions as well as improve longer-term network resilience planning, keeping the lights on for the 20 million customers across the network. \n\u003Cbr\u003E\n\u003Cbr\u003E\nThe WARN project is funded through the Ofgem Strategic Innovation Fund, managed by UKRI.\n",news_metadata:{title:db,description:db,image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F17625230-da03-11ed-b6eb-0fc980522195-UKPN-Project.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F17625230-da03-11ed-b6eb-0fc980522195-UKPN-Project.jpg"}}}},{slug:"iea-secures-ukri-round-2-funding-for-novel-energy-market-modelling-initiative",title:ag,content:b,created_at:"2023-03-17T09:49:23.006Z",metadata:{headline:ag,main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F8d3e3ed0-c4a8-11ed-a451-7f625299de0a-believe.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F8d3e3ed0-c4a8-11ed-a451-7f625299de0a-believe.jpg"},main_image_attribution:"energy market modelling initiative",story_excerpt:"After a successful 3-month discovery activity, we are pleased to announce that we have been awarded a 12-month follow-on project from UKRI (UK Research & Innovation) to further develop our innovative economic dispatch modeling technology.",content:"\u003Cp\u003E\u003Cstrong\u003EAfter a successful 3-month discovery activity, we are pleased to announce that we have been awarded a 12-month follow-on project from UKRI (UK Research & Innovation) to further develop our innovative economic dispatch modeling technology. \u003C\u002Fstrong\u003E\u003C\u002Fp\u003E\n\u003Cp\u003E\u003Cbr\u003EThe project â BELIEVE â is one of 10 successful Round 2 SBRI (Small Business Research Initiative) projects exploring new commercial products and services for green finance. \u003C\u002Fp\u003E\n\u003Cbr\u003E\n\u003Cp\u003EThe project will focus primarily on the UK energy market and allow us to further assess the impact of long-term weather and climate patterns on energy production and demand. The goals are to provide enhanced insight into expected volatility in future electricity prices and to help understand and mitigate volatility-related risks, in markets that will be increasingly exposed to weather-related variability â key determinants for the financial sector when considering new investments in the renewable energy sector. \u003C\u002Fp\u003E\n\u003Cbr\u003E\n\u003Cp\u003EThe BELIEVE project is led by the Institute for Environmental Analytics in collaboration with a range of leading industry collaborators including Copenhagen Infrastru

1cture Partners, Danske Commodities, Ãrsted, and The Crown Estate.\u003C\u002Fp\u003E\n\n\u003Cbr\u003E\n\u003Cbr\u003E\n\u003Cdiv class=\"iea-text-center\"\u003E\n\u003Cimg class=\"iea-width-100-m iea-width-2-3\" src=\"https:\u002F\u002Fcdn.cosmicjs.com\u002F9a126200-c73a-11ed-a451-7f625299de0a-Belive-Partner-Logos.jpg\" alt=\"energy market modelling innitiative partners\"\u003E\n\u003C\u002Fdiv\u003E\n",news_metadata:{title:"Energy market modelling initiative",description:ag,image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Ff52f9700-c4a8-11ed-a451-7f625299de0a-believe.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Ff52f9700-c4a8-11ed-a451-7f625299de0a-believe.jpg"}}}},{slug:"white-paper-released",title:"White paper released",content:b,created_at:"2023-01-25T13:51:34.456Z",metadata:{headline:"The IEA publish white paper exploring the role of weather data in Africa's energy transition",main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F6d4bab90-9cb6-11ed-aca2-37db769eb59f-IEASupporting-Africas-Energy-Transition.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F6d4bab90-9cb6-11ed-aca2-37db769eb59f-IEASupporting-Africas-Energy-Transition.jpg"},main_image_attribution:"IEA_Supporting Africas Energy Transition",story_excerpt:"The Institute for Environmental Analytics is pleased to announce the release of our white paper which looks at how weather variability can affect solar and wind production. ",content:"\u003Cp\u003EThe Institute for Environmental Analytics is pleased to announce the release of our white paper which looks at how weather variability can affect solar and wind production. \u003C\u002FP\u003E \u003Cbr\u003E\nWritten by Alan Yates, our Head of Energy Applications, the paper explores the role of weather data in Africa's energy transition and is available to download now on the \u003Ca href=\"https:\u002F\u002Fwww.esi-africa.com\u002Findustry-sectors\u002Fsmart-technologies\u002Fwhite-paper-analyse-the-impact-of-weather-on-your-energy-planning\u002F\"target=â_blankâ\u003E\u003Cstrong\u003EESI Africa website\u003C\u002Fsrong\u003E\u003C\u002Fa\u003E.",news_metadata:{title:"The role of weather data in Africas energy transition",description:"A white paper by Alan Yates, Head of Energy Applications at the Institute of Environmental Analytics, exploring the role of weather data in Africa's energy transition",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F08bd10f0-9cb7-11ed-aca2-37db769eb59f-IEASupporting-Africas-Energy-Transition.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F08bd10f0-9cb7-11ed-aca2-37db769eb59f-IEASupporting-Africas-Energy-Transition.jpg"}}}},{slug:"providing-software-engineering-support-for-new-sustainability-platform",title:dc,content:b,created_at:"2023-01-16T13:46:23.120Z",metadata:{headline:dc,main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F37e6adb0-9653-11ed-aca2-37db769eb59f-Inforecast-Logo.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F37e6adb0-9653-11ed-aca2-37db769eb59f-Inforecast-Logo.jpg"},main_image_attribution:"Innovate UK logo, Inforecast logo",story_excerpt:"Supporting UK-based start-up InForecast Limited.",content:"We have recently started a new technology development project with UK-based start-up - InForecast Limited. The IEA team will be providing software engineering services to support the early-stage development of a prototype commercial software platform. \n\nThe Sustainability Initiative (SI) product is aimed at helping companies in the construction sector define, capture and demonstrate measurable sustainability performance faster through an easy-to-use cloud-based KPI management platform. \n\nThe collaboration combines the experience of both organisations in software development, AI and domain expertise and is the result of a successful bid to Innovate UK.",news_metadata:{title:"Supporting UK-based start-up - InForecast Limited",description:"The IEA team will be providing software engineering services to support the early-stage development of a prototype commercial software platform. ",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F15d996b0-95a4-11ed-aca2-37db769eb59f-Inforecast-Image.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F15d996b0-95a4-11ed-aca2-37db769eb59f-Inforecast-Image.jpg"}}}},{slug:"analysing-cloud-seeding-in-oman",title:dd,content:b,created_at:"2023-01-16T13:32:19.283Z",metadata:{headline:

1dd,main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F517cff10-b136-11ed-a13d-c3e6887fd23f-Oman.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F517cff10-b136-11ed-a13d-c3e6887fd23f-Oman.jpg"},main_image_attribution:a,story_excerpt:"We are pleased to have been awarded a contract from the Ministry of Agriculture, Fisheries Wealth and Water Resources, Sultanate of Oman to undertake a statistical analysis of the results of the rainfall enhancement programme between 2019-2022. This innovative national initiative has been running for a number of years and uses cloud seeding technology to enhance rainfall levels.",content:"We are pleased to have been awarded a contract from the Ministry of Agriculture, Fisheries Wealth and Water Resources, Sultanate of Oman to undertake a statistical analysis of the results of the national rainfall enhancement programme between 2019-2021.\n\nThe national rainfall enhancement project has the aim of enhancing the amount of rainfall in order to increase the groundwater level and reduce the water deficit. The project uses ions emitter stations. These spread negatively charged ions which are transported by dust atoms and rising air to the clouds to stimulate precipitation. In order for these stations to operate with high efficiency, certain climatic conditions such as high humidity and rising air currents are required. \n\nTwelve rainfall enhancement stations have installed since 2013, including ten stations distributed on the eastern and western Hajar Mountains and two stations on the mountains of Dhofar Governorate.\n\nThe results of this report will indicate if the rainfall enhancement project has had positive effects on rainfall and water resources.\n",news_metadata:{title:"Rainfall modelling in Oman",description:"The Institute of Environmental Analytics is working with the Sultanate of Oman to undertake a statistical analysis of the results of the national rainfall enhancement programme between 2019-2022.",image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F0299d530-95a2-11ed-aca2-37db769eb59f-thunderclouds-in-the-desert-2021-08-26-19-00-20-utc.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F0299d530-95a2-11ed-aca2-37db769eb59f-thunderclouds-in-the-desert-2021-08-26-19-00-20-utc.jpg"}}}},{slug:"assessing-climate-impacts-on-horticulture",title:ah,content:b,created_at:"2022-09-15T11:49:30.056Z",metadata:{headline:ah,main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fbbe8bc30-9652-11ed-aca2-37db769eb59f-Halls.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fbbe8bc30-9652-11ed-aca2-37db769eb59f-Halls.jpg"},main_image_attribution:a,story_excerpt:"Modelling the impact of climate change on crops",content:"We are pleased to have recently completed a project looking at the potential impact of climate change on fresh produce growing regions in South Africa. The work was undertaken for Halls, a large multinational farming business with over 125 years of growing experience on the African continent. During the project, the IEA analysed data from 37 climate models for 2 emission pathways in order to assess likely changes to temperature, hail, drought rainfall and humidity, The final report will help provide context for Halls as they plan future investment decisions and technical strategies to adapt to climate change.",news_metadata:{title:ah,description:"Discover how The IEA analysed climate models to inform future investment decisions at Halls",image:{url:V,imgix_url:W}}}},{slug:"innovate-uk-bid-win-for-energy-market-modelling",title:"Innovate UK bid win for energy market modelling ",content:b,created_at:"2022-07-04T09:31:52.987Z",metadata:{headline:de,main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F1775df00-fb7c-11ec-bc5f-a7b22e2a7bc8-s300UKRIIUK-LogoOCT2019.jpeg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F1775df00-fb7c-11ec-bc5f-a7b22e2a7bc8-s300UKRIIUK-LogoOCT2019.jpeg"},main_image_attribution:a,story_excerpt:"Modelling the impact of weather and climate change in future energy markets.",content:"Asset performance in electricity markets is dependent on the performance of all agents in the marketplace and is complex to model. In future, it will become increasingly dependent on weather-driven intermittent generation as the proportion of solar and wind power increases. To address this, investors and owners of energy asset portfolios need to properly assess the strategic risk of weather and climate variability in future markets. \n\n\nThe BELIEVE project - led by the IEA - will combine novel methods for modelling weather-driven generation with economic dispatch in order to optimise asset value in long term strategic portfolio planning. It is funded by Innovate UK as part of a portfolio of projects aimed at commercialising climate data within the financial services market.",news_metadata:{title:de,description:"Optimising asset value by combining weather-driven generation with economic dispatch.",image:{url:V,imgix_url:W}}}},{slug:"assessing-weather-impacts-on-electricity-networks",title:df,content:b,created_at:"2022-06-23T16:00:26.263Z",metadata:{headline:

1df,main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fec3f4590-f3c1-11ec-a2eb-c1653f3f9199-pexels-photo-371838.webp",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fec3f4590-f3c1-11ec-a2eb-c1653f3f9199-pexels-photo-371838.webp"},main_image_attribution:a,story_excerpt:"The IEA team has recently completed Phase 1 of a project to assess the impact of weather and climate on electricity networks. ",content:"The IEA team has recently completed a technology development project to assess the impact of weather and climate on electricity networks. The 9 month project was funded by the UK Space Agency and involved transmission operators and DSOs from Latin America, the UK and Caribbean. The project has developed a proof-of-concept software platform to provide real time weather alerts alongside longer-term climatic analysis to support planning.",news_metadata:{title:"Assessing the impact of weather and climate on electricity networks. ",description:"UK Space Agency fund The IEA to develop software to provide real time weather alerts alongside longer-term climatic analysis to support planning.",image:{url:g,imgix_url:h}}}},{slug:"suriname-pilots-energymetric-to-further-energy-transition",title:"Suriname pilots EnergyMetric to further energy transition",content:b,created_at:"2022-06-23T15:45:50.839Z",metadata:{headline:"Suriname pilots EnergyMetric to further energy transition ",main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F2ad90240-f3c3-11ec-a2eb-c1653f3f9199-Suriname-photo.jpeg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F2ad90240-f3c3-11ec-a2eb-c1653f3f9199-Suriname-photo.jpeg"},main_image_attribution:a,story_excerpt:"The IEA is delighted to have signed an MOU with the Suriname Energy Chamber for a pilot initiative to demonstrate the potential for EnergyMetric to inform renewable energy transition options in the country. ",content:"The IEA is delighted to have signed an MOU with the Suriname Energy Chamber for a pilot initiative to demonstrate the potential for EnergyMetric to inform renewable energy transition options in the country. \n\nThe pilot will focus on the main grid network surrounding the capital Paramaribo and will involve the Ministry of Energy and Natural Resources, Suriname Public Utility, Suriname Energy Authority and Anton de Kom University.\n\nSpecial thanks to the Caribbean Climate Smart Accelerator for their excellent work in helping to set up the project.\n",news_metadata:{title:"Suriname use EnergyMetric to inform renewable energy transition options",description:"Suriname have undertaken a pilot to use EnergyMetric to understand the demand of their main electricity grid and learn how future renewable energy infrastructure can be used to meet that demand.",image:{url:g,imgix_url:h}}}},{slug:"energymetric-launches-in-africa",title:dg,content:b,created_at:"2022-06-23T15:25:24.657Z",metadata:{headline:dg,main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fd30a3130-b1de-11ed-a13d-c3e6887fd23f-EM-Launch-Africa.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fd30a3130-b1de-11ed-a13d-c3e6887fd23f-EM-Launch-Africa.jpg"},main_image_attribution:a,story_excerpt:"The IEA was in Cape Town from 7-9 June to launch EnergyMetric at Enlit Africa. ",content:"The IEA was in Cape Town from 7-9 June to launch EnergyMetric at Enlit Africa. The trade show is one of the premier events for the energy industry and a hotspot of activity for planning new solar and wind capacity on the continent. Visitors to the EnergyMetric stand were able to view live demos of the software and chat to the team about how we are using our weather and climate modelling expertise to improve renewable energy project planning.",news_metadata:{title:"The IEA attend Enlit Africa to show off the benefits EnergyMetric can offer",description:"The IEA demonstrate the benefits of EnergyMetric and chat to leaders in the energy industry about how we are using our weather and climate modelling expertise to improve renewable energy project planning.",image:{url:g,imgix_url:h}}}},{slug:"new-funding-announced-at-cref-2022",title:dh,content:b,created_at:"2022-04-26T14:52:49.897Z",metadata:{headline:

1dh,main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F6cda75d0-c573-11ec-bf80-e74645a81647-CREF2022-600x600A-600x450.jpeg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F6cda75d0-c573-11ec-bf80-e74645a81647-CREF2022-600x600A-600x450.jpeg"},main_image_attribution:a,story_excerpt:"Weâre proud to announce the roll out of EnergyMetric across six small island states, thanks to further funding from the UK Space Agency. ",content:"We're proud to announce the roll out of EnergyMetric across six small island states, thanks to further funding from the UK Space Agency. With access to EnergyMetric's multi-year weather data, intuitive software and experienced climate analysts, users across Mauritius, Montserrat, Saint Lucia, Seychelles, Tonga and Vanuatu can explore the generation potential and bankability of renewable energy projects. Our technology will be game-changing for supporting strategic energy planning and building resilience in some of the world's most climate-sensitive areas. This news comes as we join the 2022 CREF conference in Miami, where we look forward to sharing how EnergyMetric is supporting the energy transitions of islands in the Caribbean.",news_metadata:{title:"EnergyMetric rolled out to 6 small island states",description:"The IEA is proud to announce that EnergyMetric has been rolled out across 6 small island states with funding from the UK Space Agency",image:{url:g,imgix_url:h}}}},{slug:"insight-3",title:di,content:b,created_at:"2022-03-30T13:30:15.293Z",metadata:{headline:di,main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F68119c70-9653-11ed-aca2-37db769eb59f-Birkbeck.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F68119c70-9653-11ed-aca2-37db769eb59f-Birkbeck.jpg"},main_image_attribution:a,story_excerpt:"During March, the IEA will be delivering a special workshop on energy modelling to students on the Energy and Climate Change course at Birkbeck College, London.",content:"During March, the IEA will be delivering a special workshop on energy modelling to students on the Energy and Climate Change course at Birkbeck College, London. The session is being led by Alan Yates, Principal Consultant and will focus on the challenges of achieving high penetrations of intermittent renewable energy. As part of the workshop, students will get to use EnergyMetric software as a tool for resource assessment and renewable generation modelling.\n\n",news_metadata:{title:"The IEA delivers an energy and climate changes workshop",description:"The IEA visits Birkbeck College to deliver an energy and climate change workshop to students",image:{url:g,imgix_url:h}}}},{slug:"weatherasset-exhibiting-at-fruit-logistica",title:dj,content:b,created_at:"2022-01-10T15:42:27.076Z",metadata:{headline:dj,main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fea7cc930-9650-11ed-aca2-37db769eb59f-Fruit-Logistika.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fea7cc930-9650-11ed-aca2-37db769eb59f-Fruit-Logistika.jpg"},main_image_attribution:a,story_excerpt:"We will be showcasing our suite of weather modelling software, data and consultancy services at Fruit Logistica 2022 in Berlin between 5th-7th April.",content:"We will be showcasing our suite of weather modelling software, data and consultancy services at Fruit Logistica 2022 in Berlin between 5th-7th April. It's been 2 years since the last in-person event and we're excited at being able to reconnect with customers and partners once more. With over 77,000 visitors attending in 2020, we're expecting to have a busy time. Come and visit us on Stand A-16, Hall 5.1.",news_metadata:{title:"IEA attends Fruit Logistica",description:"The IEA shows off Weather Asset at Fruit Logistica",image:{url:g,imgix_url:h}}}},{slug:"energymetric-at-solar-finance-and-investment-europe",title:"Solar Finance and Investment Europe 2022",content:b,created_at:"2022-01-10T15:40:52.036Z",metadata:{headline:"EnergyMetric at Solar Finance and Investment Europe",main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F73031ff0-9653-11ed-aca2-37db769eb59f-Solar-Finance-Investment.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F73031ff0-9653-11ed-aca2-37db769eb59f-Solar-Finance-Investment.jpg"},main_image_attribution:a,story_excerpt:"Solar Media Events will host the 9th edition of Solar Finance and Investment Europe in London on 8-9 March 2022. ",content:"Solar Media Events will host the 9th edition of Solar Finance and Investment Europe in London on 8-9 March 2022. \n\nAs the global energy transition gathers momentum, solar is a key driving technology. The event will bring together Europe's leading investors and lenders with the region's top solar developers with a focus on business and growth.\n\nEnergyMetric is proud to participate and we look forward to sharing how EnergyMetric can de-risk strategic planning for solar projects around the world.",news_metadata:{title:"EnergyMetric and its solar applications",description:"The IEA demonstrates how EnergyMetric can de-risk strategic planning for solar projects around the world.",image:{url:g,imgix_url:h}}}},{slug:"launch-of-energymetric",title:dk,content:b,created_at:"2022-01-10T15:39:58.460Z",metadata:{headline:

1dk,main_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fa8e511f0-9653-11ed-aca2-37db769eb59f-Energy-Metric-Launch.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fa8e511f0-9653-11ed-aca2-37db769eb59f-Energy-Metric-Launch.jpg"},main_image_attribution:a,story_excerpt:"After 5 years of R&D effort funded by the UK Space Agencyâs International Partnership Programme (IPP), we are pleased to announce the commercial launch of EnergyMetric.",content:"After 5 years of R&D effort funded by the UK Space Agencyâs International Partnership Programme (IPP), we are pleased to announce the commercial launch of EnergyMetric.The cloud-based modelling software has been the result of intensive development in partnership with government energy departments and national power companies in 7 developing countries. Initially designed to support complex national energy transition planning, the software is now also being released to the private sector to enhance project and portfolio scale analysis.\n\nThe IEA team would like to thank the UK Space Agency for supporting the development of the technology.",news_metadata:{title:"The IEA launches EnergyMetric",description:"The IEA launches its cloud-based modelling software named EnergyMetric",image:{url:g,imgix_url:h}}}}],newsBanner:{id:"649c1c637df15a13847d77cd",slug:"news-page-banner",title:"News Page Banner",content:b,bucket:d,created_at:dl,created_by:c,modified_at:dm,created:dl,status:e,thumbnail:b,published_at:dm,modified_by:c,publish_at:a,unpublish_at:a,type:n,metadata:{banner_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fcacf6b80-964e-11ed-aca2-37db769eb59f-solar-energy-2022-09-15-23-02-09-utc-copy.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fcacf6b80-964e-11ed-aca2-37db769eb59f-solar-energy-2022-09-15-23-02-09-utc-copy.jpg"},title:Z,subtitle:a}},newsComponents:[{id:y,slug:z,title:A,content:b,bucket:d,created_at:i,created_by:c,modified_at:j,created:i,status:e,thumbnail:b,published_at:j,modified_by:c,publish_at:a,unpublish_at:a,type:l,metadata:{background_image:a,text:B,cta_text:C,background_color:D}}],pageMetadata:{title:"News | The IEA",description:"The IEA in the news. See how we have an impact on the world with our bespoke applications and expertise.",image:{url:g,imgix_url:h}}},partners:{partners:{mobile_xs:{url:F,imgix_url:G},mobile:{url:F,imgix_url:G},tablet:{url:co,imgix_url:cp},desktop:dn,desktop_xl:dn,text:cs,cta_text:ct,background_colour:cu}},products:{products:{},productSectionContent:{title:cf,subtitle:cg,products:[ch]}},projectStories:{projectStoriesBanner:{id:"649c1c637df15a13847d77cc",slug:"project-stories-banner",title:"Project Stories Banner",content:b,bucket:d,created_at:do0,created_by:c,modified_at:dp,created:do0,status:e,thumbnail:b,published_at:dp,modified_by:c,publish_at:a,unpublish_at:a,type:n,metadata:{banner_image:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002F8c8a0940-95b1-11ed-aca2-37db769eb59f-aerial-view-on-the-solar-panel-technologies-of-re-2021-08-29-03-54-08-utc-copy.jpg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002F8c8a0940-95b1-11ed-aca2-37db769eb59f-aerial-view-on-the-solar-panel-technologies-of-re-2021-08-29-03-54-08-utc-copy.jpg"},title:Y,subtitle:a}},projectStoriesComponents:[{id:y,slug:z,title:A,content:b,bucket:d,created_at:i,created_by:c,modified_at:j,created:i,status:e,thumbnail:b,published_at:j,modified_by:c,publish_at:a,unpublish_at:a,type:l,metadata:{background_image:a,text:B,cta_text:C,background_color:D}}],pageMetadata:{title:"Projects | The IEA",description:"See the projects and case studies that The IEA have undertaken to reduce costs d environmental impact across the energy sector.",image:{url:g,imgix_url:h}}},skills:{skills:[{title:am,content:ap,icon:aq},{title:aw,content:az,icon:aA},{title:aG,content:aJ,icon:aK},{title:aB,content:aE,icon:aF},{title:ar,content:au,icon:av}]},teamMembers:{teamMembers:[{name:J,role:aN,bio:aO,photo:{url:aP,imgix_url:aQ},email:aR,linkedin:aS},{name:bd,role:be,bio:bf,photo:{url:bg,imgix_url:bh},email:bi,linkedin:bj},{name:aW,role:aX,bio:aY,photo:{url:aZ,imgix_url:a_},email:a$,linkedin:ba},{name:K,role:L,bio:aU,photo:{url:M,imgix_url:N},email:O,linkedin:P}

1,{name:"Dr Samuel Doolin",role:"Head of Software Engineering",bio:"Sam obtained a first-class MPhys and DPhil (Astrophysics) from the University of Oxford. He then completed a technical postdoc at an international network of telescopes, building the hardware infrastructure, operational software, and scientific data analysis pipeline. Samuel is a versatile and experienced software developer with a passion for building data-driven solutions to solve real-world problems. He brings strong quantitative and analytical expertise.",photo:{url:"https:\u002F\u002Fcdn.cosmicjs.com\u002Fec14a1d0-0c8a-11ef-b837-75832108e4e1-Sam.jpeg",imgix_url:"https:\u002F\u002Fimgix.cosmicjs.com\u002Fec14a1d0-0c8a-11ef-b837-75832108e4e1-Sam.jpeg"},email:"[email protected]",linkedin:a}]}},serverRendered:ac,routePath:"\u002Fabout",config:{_app:{basePath:cD,assetsPath:"\u002F_nuxt\u002F",cdnURL:a}}}}(null,"","649c1935593c4d0008e4a858","649c1c089edc180008872849","published",false,"https:\u002F\u002Fcdn.cosmicjs.com\u002Fb89e3980-7a21-11ed-bac9-7fe1734a16aa-aboutuspagebanner.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002Fb89e3980-7a21-11ed-bac9-7fe1734a16aa-aboutuspagebanner.jpg","2022-12-08T13:37:06.587Z","2024-04-25T13:47:05.979Z","skills","content-banners","Contact us","page-banners","literature","Modelling the economics of long-duration energy storage","2023-01-12T10:07:53.825Z","2022-12-12T13:34:59.799Z","2022-12-16T12:28:23.082Z","2022-12-12T13:53:39.041Z","2022-12-12T14:08:28.919Z","leadership","2023-10-06T16:39:40.855Z","2023-10-06T16:40:41.935Z","649c1c637df15a13847d77ce","home-cta-banner-1","Home CTA Banner 1","How can we support you?","Schedule a call","dark-red","2022-12-20T14:35:39.068Z","https:\u002F\u002Fcdn.cosmicjs.com\u002F1e22a200-0865-11ef-b837-75832108e4e1-Partners-Mobile.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F1e22a200-0865-11ef-b837-75832108e4e1-Partners-Mobile.jpg","Analysing solar and wind generation for energy trading","metadata","Colin McKinnon","Alan Yates","Head of Energy Applications","https:\u002F\u002Fcdn.cosmicjs.com\u002F6a985a90-9272-11ed-aca2-37db769eb59f-alan.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F6a985a90-9272-11ed-aca2-37db769eb59f-alan.jpg","[email protected]","https:\u002F\u002Fuk.linkedin.com\u002Fin\u002Falan-yates-31691825","campaign-sections","The Institute for Environmental Analytics","https:\u002F\u002Fcdn.cosmicjs.com\u002Ffcabd3f0-5d45-11ee-bdcf-b7795530a864-Insights-Images-Weather-Modelling.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002Ffcabd3f0-5d45-11ee-bdcf-b7795530a864-Insights-Images-Weather-Modelling.jpg","Optimising long-duration storage technology","https:\u002F\u002Fcdn.cosmicjs.com\u002Fa47391f0-76e1-11ed-bac9-7fe1734a16aa-home-page-banner.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002Fa47391f0-76e1-11ed-bac9-7fe1734a16aa-home-page-banner.jpg","2022-12-09T10:15:53.638Z","Project Stories","News","webinars","insights","2023-09-15T12:59:57.464Z","authors",true,"Helping SMEs boost growth through data and software innovation","Providing meteorological data for novel wind turbine analysis","Oman workshop on results of rainfall modelling project","IEA secures UKRI Round 2 funding for novel energy market modelling initiative","Assessing climate impacts on horticulture",{},"2024-04-30T14:44:24.921Z","skills-section","2022-02-08T16:19:43.430Z","Weather and Climate","2022-02-08T16:19:01.462Z","2023-01-17T09:50:40.454Z","\u003Cp\u003EOur applied meteorologists work operationally with data from global forecast providers and run our own in-house WRF meso-scale weather model. We are experts in sourcing and manipulating observational data, forecast verification and performance benchmarking. We have practical experience working with climate reanalysis data and climate model outputs and have developed several applications for ECMWF&rsquo;s Climate Change Service and Data Store.\u003C\u002Fp\u003E","https:\u002F\u002Fcdn.cosmicjs.com\u002F69b38580-9a40-11ec-852b-ab884ffd8c85-Weather.png","Data visualisation","2022-02-08T16:21:58.942Z","2022-03-24T12:49:27.961Z","\u003Cp\u003EWe have many years of experience in data visualisation, with a particular focus on integrating geospatial data with other information sources, including scientific and socio-economic data. We combine a deep knowledge of the scientific principles behind the data with an appreciation of the need to present data in an engaging and meaningful manner that c

1ommunicates a clear message or enables better decision-making.\u003C\u002Fp\u003E","https:\u002F\u002Fcdn.cosmicjs.com\u002F699723e0-9a40-11ec-852b-ab884ffd8c85-DataVis.png","Modelling and analysis","2022-02-08T16:20:39.181Z","2022-03-16T11:33:57.736Z","\u003Cp\u003EWe have a wealth of expertise in the development and deployment of data-driven models of virtually every conceivable type. Specific methodological expertise includes deep neural networks, support vector machines, generalised linear models and Bayesian belief networks. We also frequently employ optimisation techniques such as mixed integer programming to identify optimum decision thresholds.\u003C\u002Fp\u003E","https:\u002F\u002Fcdn.cosmicjs.com\u002F69963980-9a40-11ec-852b-ab884ffd8c85-DataScience.png","Full stack software engineering","2022-02-08T16:21:29.395Z","2022-03-24T12:50:07.162Z","\u003Cp\u003EWe have many years of experience across all areas of software development, ranging from small stand-alone apps to full-scale commercial SaaS products. Our front-end team writes modern, single page applications which enable intuitive data exploration leveraging our in-house UX design skills. Our back-end team develops GIS-enabled services exploiting the latest containerisation technology and cloud services to deliver secure and resilient performance.\u003C\u002Fp\u003E","https:\u002F\u002Fcdn.cosmicjs.com\u002F69b2c230-9a40-11ec-852b-ab884ffd8c85-FSEng.png","Earth observation ","2022-03-04T15:52:29.678Z","2022-03-24T12:51:02.693Z","\u003Cp\u003EWe have significant experience in processing many kinds of satellite imagery (optical, radar, thermal and others) using image analysis and machine learning algorithms. Our projects have included studies of land cover classification, urban change detection, atmospheric composition (e.g. air quality and pollutant analysis) and surface temperature using Earth observation data from both free and commercial sources.\u003C\u002Fp\u003E","https:\u002F\u002Fcdn.cosmicjs.com\u002F6997c020-9a40-11ec-852b-ab884ffd8c85-EO.png","leadership-team-section","2022-01-28T11:55:58.175Z","CEO","Colin has overall responsibility for the IEA. He has a background in general management with BP and has spent the last 25 years turning scientific R&D into commercial opportunities through the development of new products, services and start-up ventures. His experience covers data and software, environmental science and engineering. He has worked for early stage companies through to major corporations across a wide range of sectors including energy, infrastructure, oil\u002Fgas and the space sector.  ","https:\u002F\u002Fcdn.cosmicjs.com\u002F6a9d8ab0-9272-11ed-aca2-37db769eb59f-colin.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F6a9d8ab0-9272-11ed-aca2-37db769eb59f-colin.jpg","[email protected]","https:\u002F\u002Fuk.linkedin.com\u002Fin\u002Fcolin-mckinnon-34673119?trk=people-guest_people_search-card","alan-yates","Alan is the principal energy consultant at the IEA  with over 35 years commercial experience in applied decision support.  He oversees the technical development of EnergyMetric, our renewable generation software and is an expert in renewable energy resource assessment. He recently led a project to quantify potential emission reductions for a large-scale industrial electricity consumer. Alan is a Fellow of the Operational Research Society, has an engineering degree and an MSc in Environmental Informatics. ","2022-01-19T17:31:55.762Z","Dr Maria Noguer","Head of Data and Modelling","Maria is an experienced programme manager and is responsible for implementing and directing major projects at the IEA. A Meteorologist by training, she has over 25 yearsâ experience in climate science research and management, having worked for the UK Met Office as a climate scientist, for the UK Government as a climate adviser and for the Intergovernmental Panel on Climate Change as deputy head of the technical support unit. ","https:\u002F\u002Fcdn.cosmicjs.com\u002F6a9c0410-9272-11ed-aca2-37db769eb59f-maria.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F6a9c0410-9272-11ed-aca2-37db769eb59f-maria.jpg","[email protected]","https:\u002F\u002Fwww.linkedin.com\u002Fin\u002Fmaria-noguer-59a59135\u002F","2022-01-19T17:58:02.475Z","2023-01-12T12:13:18.619Z","Andrew Groom ","Business Development Director ","Andrew leads on developing our commercial strategy and related opportunities. Andrew has science qualifications and a background in technical, analytical and leadership roles. His early career includes over 10 years working in the finance sector for multi-national retail and investment banks. Prior to joining the IEA Andrew spent over 12 years in the UKâs space sector, working as an analyst, consultant, and business development manager at Airbus before 4 years of Director-level roles at CGI.","https:\u002F\u002Fcdn.cosmicjs.com\u002F6a9cc760-9272-11ed-aca2-37db769eb59f-andrew.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F6a9cc760-9272-11ed-aca2-37db769eb59f-andrew.jpg","[email protected]","https:\u002F\u002Fuk.linkedin.com\u002Fin\u002Fandrew-groom-92a731149","2022-12-16T14:43:46.356Z","2023-01-13T16:00:32.057Z","Contact us today","2023-11-23T16:20:31.2Z","USP","2023-11-21T10:37:42.546Z","2023-11-27T10:50:05.176Z","https:\u002F\u002Fcdn.cosmicjs.com\u002F3ebbeb00-8d10-11ee-b62d-5b90a0a1bade-Partners-group-anim-X-10.gif","https:\u002F\u002Fimgix.cosmicjs.com\u002F3ebbeb00-8d10-11ee-b62d-5b90a0a1bade-Partners-group-anim-X-10.gif","2023-11-24T11:28:07.449Z","6520384cc05d4a000813c7de","home-page-metadata-f23c8b80-6466-11ee-a748-8bb51ad4c8c3","Test campaign page metadata","Data-driven decision making for effective climate risk management","https:\u002F\u002Fcdn.cosmicjs.com\u002F77fd2f40-637c-11ee-bdcf-b7795530a864-Winding-rOAD.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F77fd2f40-637c-11ee-bdcf-b7795530a864-Winding-rOAD.jpg","Find out how","2023-10-06T12:02:44.648Z","2023-10-06T12:03:21.993Z","Developing a climate liability risk tool for financial institutions","https:\u002F\u002Fcdn.cosmicjs.com\u002F090380e0-7b1c-11ef-beb8-f3894cda4d77-building-4885295_1280.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F090380e0-7b1c-11ef-beb8-f3894cda4d77-building-4885295_1280.jpg","https:\u002F\u002Fcdn.cosmicjs.com\u002F098a12e0-7a54-11ef-beb8-f3894cda4d77-Traffic.png","https:\u002F\u002Fimgix.cosmicjs.com\u002F098a12e0-7a54-11ef-beb8-f3894cda4d77-Traffic.png","https:\u002F\u002Fcdn.cosmicjs.com\u002F0de67b10-0c6a-11ef-b837-75832108e4e1-Optimising-storage.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F0de67b10-0c6a-11ef-b837-75832108e4e1-Optimising-storage.jpg","Strategic planning for energy broker","https:\u002F\u002Fcdn.cosmicjs.com\u002F93f7a9d0-0950-11ef-b837-75832108e4e1-Optimising-long-duration-storage-technology.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F93f7a9d0-0950-11ef-b837-75832108e4e1-Optimising-long-duration-storage-technology.jpg","Campus energy decarbonisation","https:\u002F\u002Fcdn.cosmicjs.com\u002F80f60d50-094f-11ef-b837-75832108e4e1-UoR.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F80f60d50-094f-11ef-b837-75832108e4e1-UoR.jpg","https:\u002F\u002Fcdn.cosmicjs.com\u002F0374a8b0-b1d9-11ed-a13d-c3e6887fd23f-Monitoring-weather-and-climate-risks.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F0374a8b0-b1d9-11ed-a13d-c3e6887fd23f-Monitoring-weather-and-climate-risks.jpg","Making climate science accessible - VIEWpoint Brazil ","Predictive Maintenance for Wind Turbines","https:\u002F\u002Fcdn.cosmicjs.com\u002F203acd50-cca8-11ed-a451-7f625299de0a-Predictive-Maintenance-for-Wind-Turbines.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F203acd50-cca8-11ed-a451-7f625299de0a-Predictive-Maintenance-for-Wind-Turbines.jpg","2022-12-08T10:19:59.911Z","2024-05-03T14:45:05.491Z","our-offerings","2022-12-08T14:05:48.041Z","2024-04-25T14:03:31.794Z","Data Science","Weather and Climate ","Software","product-section","2022-12-08T14:17:10.900Z","2024-04-25T16:03:16.331Z","Products","Our commercial product, EnergyMetric, combines precision meteorological data with powerful analytics for assessing variable energy production from solar and wind projects. From single projects to national transition plans, EnergyMetric helps you model complex scenarios or pick the best combinations of solar and wind sites through the provision of geospatial analysis, resource data, long-term weather variability and yield analysis.  ","649c1c577df15a13847d7791","2022-12-08T15:22:24.968Z","2022-12-08T16:21:30.886Z","project-stories-section","news-section","partners-section","2024-05-02T09:20:03.892Z","https:\u002F\u002Fcdn.cosmicjs.com\u002F85005cc0-0864-11ef-b837-75832108e4e1-Partners-Mobile.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F85005cc0-0864-11ef-b837-75832108e4e1-Partners-Mobile.jpg","https:\u002F\u002Fcdn.cosmicjs.com\u002F637ac880-06f5-11ef-b837-75832108e4e1-Partners-Logos-3-stack.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F637ac880-06f5-11ef-b837-75832108e4e1-Partners-Logos-3-stack.jpg","Some of the leading organisations we've worked with","Join the list","white","2023-09-15","Ty Buckingham","2023-09-28T10:10:29.329Z","2023-07-27T11:23:49.494Z","2023-07-26T12:36:21.162Z","https:\u002F\u002Fcdn.cosmicjs.com\u002Fcb6cdb60-9df5-11ec-b20b-ad2fdaf5e1bc-pexels-pixabay-209831.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002Fcb6cdb60-9df5-11ec-b20b-ad2fdaf5e1bc-pexels-pixabay-209831.jpg","Knowledge Hub","\u002F","WIDE","Webinar:  Manage the impact of variable weather on price distribution in an evolving GB electricity system","https:\u002F\u002Fcdn.cosmicjs.com\u002Fcc09aab0-7f0e-11ef-beb8-f3894cda4d77-aerial-view-on-the-solar-panel-technologies-of-re-2021-08-29-03-54-08-utc.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002Fcc09aab0-7f0e-11ef-beb8-f3894cda4d77-aerial-view-on-the-solar-panel-technologies-of-re-2021-08-29-03-54-08-utc.jpg","https:\u002F\u002Fcdn.cosmicjs.com\u002F05c9cf30-7a57-11ef-beb8-f3894cda4d77-Innovation-finger.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F05c9cf30-7a57-11ef-beb8-f3894cda4d77-Innovation-finger.jpg","https:\u002F\u002Fcdn.cosmicjs.com\u002F7938a360-e77c-11ee-a01e-c56f185aea7b-Modelling-the-economics-of-long-duration-energy-storage.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F7938a360-e77c-11ee-a01e-c56f185aea7b-Modelling-the-economics-of-long-duration-energy-storage.jpg","https:\u002F\u002Fcdn.cosmicjs.com\u002Fc84c95c0-e77b-11ee-a01e-c56f185aea7b-integrating-solar-wind-and-bess-onto-a-large-campus.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002Fc84c95c0-e77b-11ee-a01e-c56f185aea7b-integrating-solar-wind-and-bess-onto-a-large-campus.jpg","https:\u002F\u002Fcdn.cosmicjs.com\u002Fd8d52de0-e77

1a-11ee-a01e-c56f185aea7b-Analysing-solar-and-wind-generation-for-energy-trading.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002Fd8d52de0-e77a-11ee-a01e-c56f185aea7b-Analysing-solar-and-wind-generation-for-energy-trading.jpg","https:\u002F\u002Fcdn.cosmicjs.com\u002F6c309f50-5c7c-11ee-8d99-6566412c38cc-Ilosta.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F6c309f50-5c7c-11ee-8d99-6566412c38cc-Ilosta.jpg","Developing an IaC solution for new remote monitoring platform","https:\u002F\u002Fcdn.cosmicjs.com\u002F7ab02230-57b3-11ee-8d99-6566412c38cc-IaC.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F7ab02230-57b3-11ee-8d99-6566412c38cc-IaC.jpg","Dyna-mo Instruments","Software engineers at the IEA recently provided technical consultancy to UK-based Dyna-mo Instruments to develop an Infrastructure as Code (IaC) solution to deploy their new SaaS-based remote monitoring software into AWS. ","https:\u002F\u002Fcdn.cosmicjs.com\u002F82123f60-579d-11ee-8d99-6566412c38cc-Rainfall-Modelling.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F82123f60-579d-11ee-8d99-6566412c38cc-Rainfall-Modelling.jpg","Preparing geospatial data to support climate action in the UK","https:\u002F\u002Fcdn.cosmicjs.com\u002F0f7b7d50-579c-11ee-8d99-6566412c38cc-EOCIS.jpg","https:\u002F\u002Fimgix.cosmicjs.com\u002F0f7b7d50-579c-11ee-8d99-6566412c38cc-EOCIS.jpg","Partnering with UK Power Networks on new Ofgem-SIF Innovation Project ","Investigating the potential for developing a weather and climate monitoring platform for UK Power Networks, ","Providing software engineering support for new Sustainability platform","Analysing cloud seeding programme in Oman","Innovate UK bid win for energy market modelling","Assessing weather impacts on electricity networks","EnergyMetric launches in Africa","New funding announced at CREF 2022","Energy workshop for Birkbeck students","WeatherAsset exhibiting at Fruit Logistica","Launch of EnergyMetric","2022-12-19T11:56:08.238Z","2023-01-17T10:07:53.446Z",{},"2022-12-19T11:24:59.933Z","2023-07-26T12:47:36.343Z"));

Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.