UKERC Energy Data Centre: Projects

Projects: Projects for Investigator
UKERC Home >> UKERC Energy Data Centre >> Projects >> Choose Investigator >> All Projects involving >> NIA2_NGESO019
 
Reference Number NIA2_NGESO019
Title Peak Demand Forecasting
Status Started
Energy Categories OTHER CROSS-CUTTING TECHNOLOGIES or RESEARCH(Energy Models) 50%;
OTHER POWER and STORAGE TECHNOLOGIES(Electricity transmission and distribution) 25%;
OTHER CROSS-CUTTING TECHNOLOGIES or RESEARCH(Energy system analysis) 25%;
Research Types Applied Research and Development 100%
Science and Technology Fields ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 100%
UKERC Cross Cutting Characterisation Systems Analysis related to energy R&D (Other Systems Analysis) 50%;
Systems Analysis related to energy R&D (Energy modelling) 50%;
Principal Investigator Project Contact
No email address given
National Grid ESO
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 August 2022
End Date 31 January 2023
Duration ENA months
Total Grant Value £250,000
Industrial Sectors Power
Region London
Programme Network Innovation Allowance
 
Investigators Principal Investigator Project Contact , National Grid ESO (100.000%)
  Industrial Collaborator Project Contact , National Grid plc (0.000%)
Web Site https://smarter.energynetworks.org/projects/NIA2_NGESO019
Objectives Working with Aurora Energy, the proposed approach is as follows: Work package 1: Literature review of approaches to demand forecasting, focusing on peak demand periods.Work package 2: Analysis of historical data on peak demand patterns and correlation to efficiencies, economic activity, weather events and uptake of new technologies.The approach to each of these work packages is described in more detail below.Work package 1: Literature review of approaches to demand forecasting, focusing on peak demand periodsIn the first stage of the project, a literature review will be carried out, studying current methodologies that are being used to develop electricity demand forecasts, both in GB and in select regions globally. This will include an assessment of the current methodology used by NGESO to forecast demand and peak demand. This phase will commence by collating material from a range of academic and industry sources, as well as data from NGESO, reviewing:Main drivers of changes to historical electricity demand,Methodologies that have been developed for forecasting future electricity demand.Considering GB and other comparable markets, the project will first examine how changes in population growth, economic activity, weather events, improvements to energy efficiencies, and technological developments have impacted historical electricity demand. This research will also highlight any other key drivers identified. In particular, the project will focus on how average cold spell (ACS) periods have impacted historical demand patterns.Following this, the project will review current methodologies that are being used to forecast future electricity demand in GB and comparable markets, also focusing on average cold spell (ACS) periods. This review will highlight how:Continuing energy efficiency improvements are expected to push down demand,Increasing electrification of heating and transport will increase demand,Time-shifting of demand could change the relationship between average and peak demand.This research will also highlight key uncertainties in forecasting methodologies, challenge areas where they feel there is a risk to assumptions being made and suggest areas which should be studied in more depth.The deliverables for this work package will be a written report.Work package 2: Analysis of historical data on peak demand patterns and correlation to efficiencies, economic activity, weather events and uptake of new technologiesIn work package 2, we will quantitatively assess the drivers of peak electricity demand. The analysis will test three hypothesis NGESO has laid out:1. Core contributing factors that make up an annual peak demand are:underlying consumer behaviour & behaviour synchronisation,seasonal factors (weather),economic & socio-economic factors,incentives & restrictions.2. Driving factors of change in short[s
Abstract Peak demand is subject to a range of uncertainties, such as population growth, calendar effects, changing technology, economic conditions, prevailing weather conditions (and their timing), as well as the general randomness inherent in individual usage. To improve peak forecasting, the relationship between peak demand and its driving factors must be understood across the short, medium, and long-term ranges (5yr, 10yr, 30yr). The project will study the latest advancements in peak demand forecasting, both in GB and select regions globally, comparing against National Grid ESOSs (NGESO) current methodology. The second phase will focus on quantitatively assessing the drivers of peak electricity demand.
Publications (none)
Final Report (none)
Added to Database 14/10/22