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Patrick E. McSharry, Sonja Bouwman and Gabriël Bloemhof (2005) Probabilistic forecasts of the magnitude and timing of peak electricity demand IEEE Transactions on Power Systems, 20(2): 1166-1172

Abstract

Adequate capacity planning requires accurate forecasts of the future magnitude and timing of peak electricity demand. Electricity demand is affected by the day of the week, seasonal variations, holiday periods, feast days and temperature. A model that provides probabilistic forecasts of both magnitude and timing over short, medium and long term is presented. This model is capable of capturing the main sources of variation in demand and also facilitates the use of simulated temperature time series for producing probabilistic forecasts of future peak demands. Having access to probabilistic forecasts provides a means of assessing the uncertainty in the predictions and can lead to improved decision-making and better risk management.

Keywords

Power demand, Power generation peaking capacity, Power system planning, Time series, Load forecasting, Temperature, Simulation, Load management, Management decision-making.