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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.