A New Hybrid Method for Short-Term Price Forecasting in Iran Electricity Market

Author

Moghadam, Mohammad Reza Vedady ; Afshar, Karim ; Bigdeli, Nooshin

Author_Institution

Electr. Eng., Imam Khomeini Int. Univ., Qazvin, Iran

fYear

2011

fDate

12-14 Aug. 2011

Firstpage

1

Lastpage

4

Abstract

In this paper, a new hybrid method for prediction of the weighted average price (WAP) of Iran electricity market is introduced. The proposed model has a linear structure which its components are selected based on correlation analysis of WAP time series with its past values and the total required load as the most effective variable in this market as well as the critiques of Iran electricity market. The model coefficients are tuned by Genetic algorithm (GA) as an optimization algorithm based on available data from electricity market of Iran. The simulation results based on experimental data from Iran electricity market are representative of good performance of developed model in forecasting the market behavior.

Keywords

genetic algorithms; power markets; pricing; Iran; correlation analysis; electricity market; genetic algorithm; hybrid method; model coefficients; short-term price forecasting; weighted average price; Correlation; Electricity; Electricity supply industry; Forecasting; Genetic algorithms; Predictive models; Wireless application protocol;

fLanguage

English

Publisher

ieee

Conference_Titel

Management and Service Science (MASS), 2011 International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-6579-8

Type

conf

DOI

10.1109/ICMSS.2011.5998135

Filename

5998135