Title :
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
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;
Conference_Titel :
Management and Service Science (MASS), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6579-8
DOI :
10.1109/ICMSS.2011.5998135
