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ARIMA models to predict next-day electricity prices

IEEE Transactions on Power Systems · 2003 · Vol. 18(3) · pp. 1014–1020
Javier ContrerasRosa EspínolaFrancisco J. NogalesAntonio J. Conejo

Abstract

Price forecasting is becoming increasingly relevant to producers and consumers in the new competitive electric power markets. Both for spot markets and long-term contracts, price forecasts are necessary to develop bidding strategies or negotiation skills in order to maximize benefit. This paper provides a method to predict next-day electricity prices based on the ARIMA methodology. ARIMA techniques are used to analyze time series and, in the past, have been mainly used for load forecasting, due to their accuracy and mathematical soundness. A detailed explanation of the aforementioned ARIMA models and results from mainland Spain and Californian markets are presented.

Energy Load and Power ForecastingElectric Power System OptimizationStock Market Forecasting MethodsAutoregressive integrated moving averageElectricity price forecastingBiddingElectricitySpot contractEconometricsTime seriesComputer scienceEconomicsElectric power system
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References
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Neural networks for short-term load forecasting: a review and evaluation
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