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The Power of Weather: Some Empirical Evidence on Predicting Day-ahead Power Prices through Day-ahead Weather Forecasts

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Author Info
Christian Huurman (Financial Engineering Associates)
Francesco Ravazzolo () (Erasmus Universiteit Rotterdam)
Chen Zhou () (Erasmus Universiteit Rotterdam)

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Abstract

In the literature the effects of weather on electricity sales are well-documented. However, studies that have investigated the impact of weather on electricity prices are still scarce (e.g. Knittel and Roberts, 2005), partly because the wholesale power markets have only recently been deregulated. We introduce the weather factor into well-known forecasting models to study its impact. We find that weather has explanatory power for the day-ahead power spot price. Using weather forecasts improves the forecast accuracy, and in particular new models with power transformations of weather forecast variables are significantly better in term of out-of-sample statistics than popular mean reverting models. For different power markets, such as Norway, Eastern Denmark and the Netherlands, we build specific models. The dissimilarity among these models indicates that weather forecasts influence not only the demand of electricity but also the supply side according to different electricity producing methods.

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Publisher Info
Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 07-036/4.

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Date of creation: 25 Apr 2007
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Handle: RePEc:dgr:uvatin:20070036

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Related research
Keywords: Electricity prices; forecasting; GARCH models; weather forecasts;

Find related papers by JEL classification:
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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  1. Rafal Weron & Adam Misiorek, 2005. "Forecasting Spot Electricity Prices With Time Series Models," Econometrics 0504001, EconWPA. [Downloadable!]
  2. Siem Jan Koopman & Marius Ooms & M. Angeles Carnero, 2005. "Periodic Seasonal Reg-ARFIMA-GARCH Models for Daily Electricity Spot Prices," Tinbergen Institute Discussion Papers 05-091/4, Tinbergen Institute. [Downloadable!]
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  3. Knittel, Christopher R. & Roberts, Michael R., 2005. "An empirical examination of restructured electricity prices," Energy Economics, Elsevier, vol. 27(5), pages 791-817, September. [Downloadable!] (restricted)
  4. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April. [Downloadable!] (restricted)
  5. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
    Other versions:
  6. Granger, Clive W. J. & Engle, Robert & Ramanathan, Ramu & Andersen, Allan, 1979. "Residential load curves and time-of-day pricing : An econometric analysis," Journal of Econometrics, Elsevier, vol. 9(1-2), pages 13-32, January. [Downloadable!] (restricted)
  7. Álvaro Escribano & Juan Ignacio Peña & Pablo Villaplana, 2002. "Modeling Electricity Prices: International Evidence," Economics Working Papers we022708, Universidad Carlos III, Departamento de Economía. [Downloadable!]
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