Optimal Short Term Power Load Forecasting Algorithm by Using Improved Artificial Intelligence Technique

Abstract

Electrical load forecasting plays a significant impact in terms of future power generation systems such as smart grid, power demand approximation, and better energy management system. Therefore, high accuracy is needed for different time horizons related to regulating, dispatch and scheduling of power system grid. However, it is difficult to do energy prediction with high precision because of influencing factors such as climate, social and seasonal factors. Artificial Intelligence (AI) and Support Vector Machine (SVM) are proved to be capable of handle complex systems and deployed worldwide in many applications due to its superiority on other techniques. The improved short term load forecasting algorithm has been introduced in this research to analyze, discuss and deal with the enhanced electrical power system. The related constraints, influential factors are given and the experimental results can be validated by the effective outcome.