INTELLIGENT SYSTEM FOR LONG TERM LOAD FORECASTING

Long term load forecasting plays an important role in the economic optimization and secured operation of electric power systems. The plans of the electric power sector have been done and developed with the aid of statistical prediction methods. Electric utilities companies need monthly peak and yearly load forecasting for budget planning, maintenance scheduling and fuel management. The present work presents a comparative study between the approach based on neural network and a hybrid fuzzy neural technique for long term load forecasting of Haryana State. A large number of influencing factors have been examined and tested. This paper presents a system developed for the prediction of maximum electric demand and consumption of electricity. The strength of this technique lies in its ability to reduce appreciable computational time and its comparable accuracy with other modeling techniques.