Long Term Load Forecasting Using SA-ANN Model: a Comparative Analysis on Real Case Khorasan Regional Load

long term electric power system load forecasting (LTLF) plays an important role in Energy Management System (EMS), which has remarkable influence on planning, control system, generation expansion and economic issues on power systems. While several promising techniques have been done in the short-term load forecasting, no trustworthy methods have been contemplated for long-term predictions. The intent of this paper is to introduce two approaches based on the regression method and Artificial Neural Network (ANN) with considering on input data for prediction of real case Khorasan regional load. Furthermore, we apply combination of Simulated Annealing and Artificial Neural Network (SA-ANN) in order to increasing accuracy in LTLF. Comparison of the results illustrate that proposed method have a reliable solution for long term load forecasting of Khorasan, Iran and in more than 95% of test result, SA-ANN give better solutions than ANN and AR methods

کلیدواژه ها:

Power System Planning ، Long Term Load Forecasting (LTLF) ، Regression Methods ، Artificial Neural Network (ANN) ، Simulated Annealing ANN