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Modeling and Forecasting the Electricity Price in Iran Using Wavelet-Based GARCH Model

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  • Pourghorban, Mojtaba
  • Mamipour, Siab

Abstract

The restructuring of Iranian electricity industry allowed electricity price to be determined through market forces in 2005. The main purpose of this paper is to present a method for modeling and forecasting the electricity prices based on complex features such as instability, nonlinear conditions, and high fluctuations in Iran during the spring 2013 and winter 2018. For this purpose, time series data of the daily average electricity price was decomposed into one approximation series (low frequency) and four details series (high frequency) utilizing the wavelet transform technique. The approximation and details series are estimated and predicted by ARIMA and GARCH models, respectively. Then, the electricity price is predicted by reconstructing and composing the forecasted values of different frequencies as a proposed method (Wavelet-ARMA-GARCH). The results demonstrated that the proposed method has higher predictive power and can forecast volatility of electricity prices more accurately by taking into consideration different domains of the time-frequency; although, more errors are produced if the wavelet transform process is not used. The mean absolute percentage error values of the proposed method during spring 2017 to winter 2018 are significantly less than that of the alternative method, and the proposed method can better and more accurately capture the complex features of electricity prices.

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  • Pourghorban, Mojtaba & Mamipour, Siab, 2020. "Modeling and Forecasting the Electricity Price in Iran Using Wavelet-Based GARCH Model," MPRA Paper 115042, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:115042
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    References listed on IDEAS

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    More about this item

    Keywords

    Electricity Price Forecasting Volatility Wavelet Transform ARMA-GARCH Model;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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