Identification and modification of improper load data used in short-term load forecasting

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. Data used for STLF is mostly historical hourly load and weather parameters. Hourly load data is subject to errors made by instruments and/or operators and also unwanted or unplanned changes in the power system. In this paper, an approach to identification and modification of improper load data used in STLF is proposed. The results for Bakhtar regional electric company (Bakhtar REC), a part of Iran national power system (INPS), shows that the idea of modifying improper input load data used for STLF can improve greatly the performance of the STLF itself.