Comparative Analysis of Medium Term Load Forecasting using Genetic Algorithm and Particle Swarm Optimization

Abstract

The forecasting of electrical energy provides the required information about future conditions
of the network to the system engineers and helps to predict essential improving actions such
as putting power plants at their maximum production, electricity purchasing, switching etc. It
is essential for the booking of fuel supply and maintenance activities and making
arrangements for utility power exchange. With the ongoing advancement of new numerical,
mining and man-made reasoning devices, it is potentially feasible to enhance the result.