Generation of synthetic sequences of electricity demand: Application in South Australia

L. Magnano and J.W. Boland

Energy, 2007, vol. 32, issue 11, 2230-2243

Abstract: We have developed a model to generate synthetic sequences of half-hourly electricity demand. The generated sequences represent possible realisations of electricity load that could have occurred. Each of the components included in the model has a physical interpretation. These components are yearly and daily seasonality which were modelled using Fourier series, weekly seasonality modelled with dummy variables, and the relationship with current temperature described by polynomial functions of temperature. Finally the stochastic component was modelled with autoregressive moving average (ARMA) processes. These synthetic sequences were developed for two purposes. The first one is to use them as input data in market simulation software. The second one is to build probability distributions of the outputs to calculate probabilistic forecasts. As an application several summers of half-hourly electricity demand were generated and from them the value of demand that is not expected to be exceeded more than once in 10 years was calculated.

Keywords: Half-hourly electricity demand; Fourier series; Multiple regression; ARMA; Probabilistic; Forecasting (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:32:y:2007:i:11:p:2230-2243

DOI: 10.1016/j.energy.2007.04.001

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