Abstract

The information of electricity demand forecasting is a base for energy generation enterprise to develop electricity supply system. The purpose of this study is to develop a monthly electricity forecasting model in order to predict electricity demand for energy management. The proposed approach to monthly electricity demand time series forecasting model, describes the trend of the electricity demand series and is solved by a proposed GANN which is integrated by a neural network algorithm with optimal parameters obtained from a genetic algorithm. Electricity demand data in United States is applied.

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