An Artificial Intelligence Based Day Lag Technique for Day Ahead Short Term Load Forecasting

Abstract

Load forecasting is an indispensable part of power system operation and maintenance. A reliable forecasting results in economically viable dispatch, unit commitment and energy security. Smart power management in generation, transmission and distribution network and corresponding need of energy can be realized with accurate forecasting methods. There are mainly two types of forecasting techniques i.e. statistical and intelligence method. It is not easy to find a suitable forecasting model for a particular power network. As a matter of fact, many developed forecasting methods cannot be fitted in all load demand sequences. In this paper, a short-term load forecasting (STLF) technique based on Artificial Intelligence for power network of Bangladesh has been applied and effect of changing a certain parameter called day lag of data processing is presented.