Provision of an Optimal Strategy to Forecast the Prices Set by the Electricity Market in the Competitive Iranian Energy Market in Fall

Given the complexities of electricity market, various factors, such as uncertainties, ways upon which markets are set, how debts settled, market structure and regulations, production prices, constraints governing units networks, etc. influential in determining optimal pricing strategies. Various methods models have been presented to resolve issue competitive industry. The most prominent include based on prediction competitors’ behavior; also forecasts price, game theory lastly, intelligent algorithms. Therefore, this study was conducted provide an strategy order forecast price set Iranian (based data collected). In paper, proposed method uses a compound network neural networks. analyzed amount consumed energy well temperature (if applicable) for past days weeks. self-organizing map (SOM) used input clustering similar days. A number multilayer perceptron (MLP) networks were combine extracted consisting levels, possible). results showed improvements performance smart systems predicting prices.