A Novel Approach of Input Variable Selection for ANN Based Load Forecasting

Abstract

The forecasting of electricity demand has become one of the major research fields in electrical engineering. The supply industry requires forecasts with lead times, which range from the short term (a few minutes, hours, or days ahead) to the long term (up to 20 years ahead). The major priority for an electrical power utility is to provide uninterrupted power supply to its customers. Long term peak load forecasting plays an important role in electrical power systems in terms of policy planning and budget allocation. This paper presents a peak load forecasting model using Artificial Neural Networks (ANN). The approach in the paper is based on multi-layered back-propagation feed forward neural network. A case study is performed using the proposed method of peak load data of the Grid Corporation of Orrissa (GRIDCO), India which maintain high quality, reliable, historical data.