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Reference Number | NIA_NGET0110 | |
Title | Electricity Demand Archetype Model 2 | |
Status | Completed | |
Energy Categories | Other Power and Storage Technologies(Electricity transmission and distribution) 100%; | |
Research Types | Applied Research and Development 100% | |
Science and Technology Fields | ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 100% | |
UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
Principal Investigator |
Project Contact No email address given National Grid Electricity Transmission |
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Award Type | Network Innovation Allowance | |
Funding Source | Ofgem | |
Start Date | 01 November 2013 | |
End Date | 01 November 2014 | |
Duration | 12 months | |
Total Grant Value | £299,000 | |
Industrial Sectors | Power | |
Region | London | |
Programme | Network Innovation Allowance | |
Investigators | Principal Investigator | Project Contact , National Grid Electricity Transmission (100.000%) |
Web Site | http://www.smarternetworks.org/project/NIA_NGET0110 |
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Objectives | The key objective is to develop a model that will enable the GB System Operator to produce more realistic demand forecasts in the future (up to 2020). In addition to use this information to stress test our business processes and to assess their viability for future operation by having a better understanding of the rate of change of demand during the day at key moments A model which can be shown to replicate current demand profiles (i.e. with zero new technology uptake) at National level. Future demand profiles with fully understood assumptions that can be traced to the final results generated. A tool that allows data to be easily extracted and used in other areas. | |
Abstract | The GB Electricity System Operator must continually match generation to demand. To do this, National Grid needs accurate forecasts of both electricity demand, and the rate of change of that demand, during the course of a day. Current processes make use of historic records. To predict the demand for the following day the System Operator will refer to records for a similar day from the past held in a database containing several years of data. This will then be used as a starting point for the forecast but will have added to it special events (such as TV pick-ups etc.). It is widely expected that that the behaviour of electricity demand in 2020 will be very different from the past. The adoption of electric vehicles, solar panels, heat pumps etc will change the shape of the demand profile. The Energy Savings Trust (EST) has developed a model of domestic demand (EDAM1) which allows users to apply different levels of technology adoption and to generate a new demand profile. EDAM2 will extend this model to include industrial and commercial demand to obtain a total daily profile. Modelling and research to mirror the EDAM1 project within an industrial and commercial context.Note : Project Documents may be available via the ENA Smarter Networks Portal using the Website link above | |
Publications | (none) |
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Final Report | (none) |
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Added to Database | 14/08/18 |