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Projects: Projects for Investigator
Reference Number NIA2_NGESO055
Status Completed
Energy Categories Other Cross-Cutting Technologies or Research(Energy Models) 40%;
Other Power and Storage Technologies(Electricity transmission and distribution) 60%;
Research Types Applied Research and Development 100%
Science and Technology Fields PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics) 30%;
PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 30%;
ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 40%;
UKERC Cross Cutting Characterisation Systems Analysis related to energy R&D (Energy modelling) 100%
Principal Investigator Project Contact
No email address given
National Grid plc
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 September 2023
End Date 29 February 2024
Duration ENA months
Total Grant Value £125,000
Industrial Sectors Power
Region London
Programme Network Innovation Allowance
Investigators Principal Investigator Project Contact , National Grid plc (100.000%)
  Industrial Collaborator Project Contact , National Grid plc (0.000%)
Web Site https://smarter.energynetworks.org/projects/NIA2_NGESO055
Objectives "This is a technical research project to develop a WDF calculation method. The project will be structured around a series of workshops. Estimated at five over the six-month project. These workshops will cover: Kick off, project plan, definitionsMethod development, literature review, data benchmarkingAnalysis plan, interim review of results and tools developed, interim reportDiscussion of results and sensitivity analysisFinal report, handover of outputs and tools Historic data will be gathered on the variability of inflexible demand and inflexible generation and on average and extreme weather years. This historic data will be analysed to develop metrics that characterise the variability and can be used to project future variability. These metrics will be combined with scenarios of the future electricity system (FES) to quantify the future need for WDF, as the main zero carbon tool to manage the variability. Tools will be developed in Python and Excel to make this a repeatable and adjustable process.Project Partner, TNEIs approach will, wherever possible, rely on high-quality data sets gathered from credible public sources, or, where necessary, internal experts within the ESO. All statistical modelling will be evaluated according to best practice, including visual diagnostics (e.g., calibration plots), and quantification of appropriate metrics. All work will be quality assured prior to completion, in accordance with TNEIs ISO 9001 accredited quality management processes. Determining appropriate sources of data and developing methods to cleanse and process them is a core part of this project. Part of determining which data sources to use will be understanding the errors they contain and their significance for the analysis. The proposals for future work at the end of the project will include an assessment of the errors and uncertainties in the method developed and how they could be improved by further work. It is an explicit intention of the project that the method developed can be understood and reused by our stakeholders and it will be designed with possible future improvements in mind. It is expected that most of the data used will come from public sources. Examples include: Elexon – historic demand and BMU generation data – accessed through a data portal and saved as CSV filesSheffield Solar – live and historic solar PV output with locational information – accessed through an API and saved as JSON filesEuropean Centre for Medium-Range Weather Forecasts – long time series of estimated weather data from historic reanalysis processes – accessed through an API and saved as netCDF or GRIB filesESO Future Energy Scenarios – scenarios of future generation capacity and demand – accessed from the ESO website as Excel filesUK Data Service – heat pump demand profiles from the Renewable Heat Premium Payment Scheme and the Electrification of Heat Demonstration Project, both raw and cleaned versions are available – accessed as CSV filesNational Grid Electricity Distribution – the EV charging behaviour dataset from the Electric Nation innovation project – accessed as Excel files All data gathered to conduct this project will require prior pre-processing, through developed code, to standardise and cleanse any bad and missing data. The consultants will use their expertise alongside scripts previously produced to identify and handle such data. Further processing may involve resampling, adjusting structures, and converting units.The project will mitigate any issues with all these data sources, for example: Historic demand data will reflect trends in behavioural patterns in time. Appropriate statistical modelling techniques will be used to detrend this data. Historic demand data will probably also net-off the effect of embedded generation. Some of these effects can be approximately controlled for (e.g., by applying the PV Live data), but this will still be imperfect. Historic wind production data will also have trends (e.g., due to changing technology), which will need to be controlled for. Corrections may also be necessary to remove the presence of constraints within that data. In addition, the available data may be relatively short compared to the long-term variation in wind conditions year-on-year. This can be addressed with weather reanalysis data to enhance these historic observations.Historic demand and generation data is typically lacking information on unique events which may have had a significant impact on the profile at any given time. Efforts will be made to mitigate this, and their impact will be minimised by the aggregation of data to national level.Projected LCT data used within the FES may only consider expected or typical profiles (e.g., associated with Average Cold Spell conditions), which may mask the true range of possible WDF requirements under different future scenarios. In line with the ENAs ENIP document, the risk rating is scored Low. TRL Steps = 2 Cost = 1(£125k) Suppliers = 1 (1 Supplier) Data Assumptions = 1 " "The scope of the project is: Flexibility for balancing inflexible demand and inflexible generation across the whole of the electricity system (transmission and distribution)Flexibility for energy balancing only, excluding any locational component and therefore any network management componentFlexibility for energy balancing only between 0.5 and 24 hours (energy balancing within 0.5 is considered frequency management and energy balancing over more than 24 house is considered adequacy)The need for flexibility only (not how much flexibility will be provided, how it will be provided, the benefits, the barriers, the business models etc.) " "The project is expected to: Provide a clearly defined method for calculating the need for WDFProvide an explanation of why this is the best method to useUse the selected method to calculate the system need for WDF. Provide and discuss the resultsProvide all of the tools required to repeat the calculation using the chosen methodPropose possible future work to build on this project "
Abstract "Operating a future energy system with high levels of renewables will require significantly more flexible, zero carbon capacity than currently available. Large amounts of short-duration flexibility will be needed to match supply and demand within the same day. During periods of high or low renewable generation, greater amounts of within-day flexibility (WDF) will be needed. There is no widely agreed method for quantifying the need for WDF. Unless this method is developed, inconsistent and flawed methods may be used, leading to inefficiencies. The project will seek to develop a rigorous, repeatable, transparent method for quantifying the need for WDF. The method will include identifying relevant data sources and how to process them, assumptions, treatments of averages and extremes, calculations and interpretation of results. "
Publications (none)
Final Report (none)
Added to Database 01/11/23