Short term load forecasting using fuzzy logic

Load forecasting is essential for planning and operation in energy management. It enhances the Energy efficient and reliable operation of a power system. The energy supplied by utilities meets the load plus the energy lost in the system is ensured by this tool. Since in power system the next day’s power generation must be scheduled every day. The dayahead short term load forecasting (STLF) is a necessary daily task for power dispatch. Short term load forecasting is essential for unit commitment, economic allocation of generation, maintenance schedules. This paper presents a solution methodology using fuzzy logic for short term load forecasting. Fuzzy logic approach is implemented on weather sensitive data and historical load data for forecasting the load. The proposed methodology uses fuzzy reasoning decision rules that capture the nonlinear relationships between inputs and outputs. The input data include historical load and hourly data like temperature, humidity and windspeed. Jaipur Vidyut Nigam hourly load data is used for training and testing which is collected from State Load Dispatch and Communication Centre, Rajasthan Vidyut Parasaran Nigam. The forecasted load results are obtained from fuzzy logic model using triangular membership function. Keywords--Short term load forecasting, fuzzy logic, membership function, Absolute percentage error