A New Approach for Short Term Load Forecasting Based on Finding Similar Days

Short term load forecasting (STLF) plays an important role for the power system operational planners and also most of the participants in the nowadays power markets. With the importance of the STLF in power system operation and power markets, many methods for arriving careful results, are represented. In this paper, an approach for STLF is proposed. The proposed approach is based on finding similar days. This approach is much simple than intelligent methods such as artificial neural networks (ANN) and fuzzy expert system (FES). The results of this method for Iran National Power System (INPS) is compared with ANN and FES results for STLF. The results shows that the idea of finding similar days used for STLF, can improve greatly the performance of the STLF.