Peak Load Chopping Applying Fuzzy Bayesian Technique For Regional Load Management-Performance Evaluation

Abstract

In this paper Fuzzy Bayesian Synthetic algorithm based methodology has been evaluated for its performance using real time data for chopping off peak load demand. This is achieved by judiciously scheduling load from the regional load under a new load management technique. This technique validates the timely decision making capacity of the system to reduce peak demand hence giving us a chance to reduce the peak demand and hence reduce the stress of generating excess power during the peak period. This method uses data of a previous day and then predicts for the next day. Thus by evaluating this process it was found that the new peak demand has a reduced value as compared to the actual peak demand. It is evident that this method can not only reduce peak demand by chopping of the regional loads by following the proposed algorithm but also helps in generating indirect revenue by saving energy. This method authenticates the proposed method and saves peak demand or otherwise energy by about ten to fifty megawatts on daily basis depending on the service condition of the network and solar day light hour availability over span of a day.