Analysis and design of a Taguchi–Grey based electricity demand predictor for energy management systems

In order to use electricity efficiently, a demand control management system is one of the effective ways to reduce energy consumption and electric bills. An electricity demand control system is used as a means to monitor and manage the usage of electricity effectively. Moreover, it is a useful tool for avoiding penalties beyond the contracted demand value of electricity with the electric power company. In this project, we developed a Taguchi–Grey based predictor to forecast the demand value of electricity on line. In a Grey prediction, the parameter settings are highly relevant to the accuracy of forecasting. A Taguchi method was employed to optimize the parameter settings for the Grey based electricity demand value predictor. Our experimental results show that the optimal parameter settings of the Grey prediction are α=0.4, five point modeling and three minute sampling time of the data acquisition system. The improved Taguchi–Grey based electricity demand predictor in conjunction with the PC based electricity demand control system is a cost effective and efficient means to manage the usage of electricity.