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Modeling and forecasting electricity loads: A comparison

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Author Info
Rafal Weron (Hugo Steinhaus Center)
Adam Misiorek (Institute of Power Systems Automation)

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Abstract

In this paper we study two statistical approaches to load forecasting. Both of them model electricity load as a sum of two components – a deterministic (representing seasonalities) and a stochastic (representing noise). They differ in the choice of the seasonality reduction method. Model A utilizes differencing, while Model B uses a recently developed seasonal volatility technique. In both models the stochastic component is described by an ARMA time series. Models are tested on a time series of system-wide loads from the California power market and compared with the official forecast of the California System Operator (CAISO).

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File URL: http://129.3.20.41/eps/em/papers/0502/0502004.pdf
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Publisher Info
Paper provided by EconWPA in its series Econometrics with number 0502004.

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Length: 8 pages
Date of creation: 07 Feb 2005
Date of revision:
Handle: RePEc:wpa:wuwpem:0502004

Note: Type of Document - pdf; pages: 8. ”The European Electricity Market EEM-04”, Proceedings Volume, pp. 135-142
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Web page: http://129.3.20.41

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Related research
Keywords: Electricity; load forecasting; ARMA model; seasonal component;

Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Smith, Michael, 2000. "Modeling and Short-term Forecasting of New South Wales Electricity System Load," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(4), pages 465-78, October.
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  1. repec:mop:credwp:08.09.77 is not listed on IDEAS
  2. Sandro Sapio, 2008. "Volatility-price relationships in power exchanges: A demand-supply analysis," LEM Papers Series 2008/07, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy. [Downloadable!]
  3. Weron, Rafal & Misiorek, Adam, 2007. "Heavy tails and electricity prices: Do time series models with non-Gaussian noise forecast better than their Gaussian counterparts?," MPRA Paper 2292, University Library of Munich, Germany, revised Oct 2007. [Downloadable!]
  4. Borak, Szymon & Weron, Rafal, 2008. "A semiparametric factor model for electricity forward curve dynamics," MPRA Paper 10421, University Library of Munich, Germany. [Downloadable!]
    Other versions:
  5. Rafal Weron & Adam Misiorek, 2005. "Forecasting Spot Electricity Prices With Time Series Models," Econometrics 0504001, EconWPA. [Downloadable!]
  6. Weron, Rafal & Misiorek, Adam, 2006. "Point and interval forecasting of wholesale electricity prices: Evidence from the Nord Pool market," MPRA Paper 1363, University Library of Munich, Germany. [Downloadable!]
  7. Trueck, Stefan & Weron, Rafal & Wolff, Rodney, 2007. "Outlier Treatment and Robust Approaches for Modeling Electricity Spot Prices," MPRA Paper 4711, University Library of Munich, Germany. [Downloadable!]
  8. Weron, Rafal & Misiorek, Adam, 2008. "Forecasting spot electricity prices: A comparison of parametric and semiparametric time series models," MPRA Paper 10428, University Library of Munich, Germany. [Downloadable!]
    Other versions:
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