Analysis of Electrical Load Forecasting by Using Matlab Tool Box through Artificial Neural Network

Load forecasting is a central integral process in the planning and operation of electric utilities. Load forecasting has become in recent years one of the major areas of research in electrical engineering. The main problem for the planning is the determination of load demand in the future. Because electrical energy cannot be stored appropriately, correct load forecasting is very essential for the correct investments. Effective forecasting, however, is difficult in view of the complicated effects on load by a variety of factors such as temperature, humidity. In this paper a threelayered feed forward neural network are trained by the Levenberg-Marquardt algorithm and a radial basis function using matlab programming and matlab tool-box. The Proposed neural network based model is used for forecasting next-week electricity prices. We evaluate the accuracy of the price forecasting attained with the proposed neural network approach, reporting the results from the electricity markets of India.