عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Due to the independence of distribution companies and their require presence in the electricity market and according to the restructuring in electricity market from the monopoly to a competitive market, finding an appropriate method for prediction of load is necessary. For the simulation and forecasting of this problem, some characteristics of this problem should be considered such as seasonal demand. If this model provides the minimum error in forecasting based on the previous data, will be effective and applicable. In this paper, a hybrid Artificial Neural Network (ANN) and Improved Gravitational Search Algorithm (IGSA) is presented for prediction of load in electricity market. Where, the weight and bias of ANN will be optimized by IGSA to provide the minimum mean square error. To demonstrate the efficiency of proposed method, this method is compared with other methods over New York power system. Obtained results demonstrate the validity of proposed method.