Abstract / Description of output
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
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 language | English |
|---|---|
| Number of pages | 6 |
| Publication status | Submitted - 2022 |
| Event | Probability Methods Applied to Power Systems - Manchester, United Kingdom Duration: 12 Jun 2022 → 15 Jun 2022 https://www.pmaps2022.org/ |
Conference
| Conference | Probability Methods Applied to Power Systems |
|---|---|
| Country/Territory | United Kingdom |
| City | Manchester |
| Period | 12/06/22 → 15/06/22 |
| Internet address |