Rescaling of Historic Electricity Demand Series for Forward-Looking Risk Calculations

Edward Wheatcroft, Chris J. Dent, Amy L Wilson

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper presents a forecasting approach for national
annual peak electricity demand. Forecasting is performed
by rescaling observed historic demand. The rescaled peaks are
then used to produce probabilistic forecasts of peak demand for
a target year. Both the rescaling approach and the probabilistic
forecasting methodology are carefully validated and shown to
provide a good fit to the data. Comparisons are made with the
National Grid’s Average Cold Spell (ACS) Methodology which
aims to estimate the level of electricity demand in Great Britain
for which there is a 50 percent probability of exceedance in a
given year.
Index Terms—Demand Forecasting, Power Demand, Risk
Analysis, Uncertainty
Original languageEnglish
Number of pages6
Publication statusSubmitted - 2022
EventProbability Methods Applied to Power Systems - Manchester, United Kingdom
Duration: 12 Jun 202215 Jun 2022
https://www.pmaps2022.org/

Conference

ConferenceProbability Methods Applied to Power Systems
Country/TerritoryUnited Kingdom
CityManchester
Period12/06/2215/06/22
Internet address

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