Artificial Neural Network based Short Term Load Forecasting

Accurate Short Term Load Forecasting (STLF) is essential to the operating and planning for electricity supply industry. For increase accuracy of the STLF, we analyzed load patterns which are categorized by the weather-load relationship and the time-load relationship. The time-load relationship has typical patterns which show the concentrated load consumption shape under the specific time period. The weather-load relationship is identified by correlation between weather factors and load demand and used to adjust the weather weight for the load forecasting accuracy. This paper describes the analyzing of the relationships which are concern with load demand and proposed the improved an Artificial Neural Network (ANN) based non-linear model for 24-hour-ahead load forecasting