Demand-Side Load Management Using Grey Wolf Optimization

Demand-Side Management (DSM) is one of the methods that tries to understand customer behaviour and put it into a strategy that maintains network stability. Recently, a large number of load scheduling algorithms were developed by various experts, however these methods were not providing accurate results because of their high complexity and utilization of static datasets. To overcome these issues, an improved load scheduling method is proposed in this paper, in which loads are optimized by using the meta-heuristic Grey Wolf Optimization (GWO) algorithm. In addition to this, a real-time dataset is used that is collected from the Chandigarh Region. The information about the total demand felt and met initially is extracted from the available dataset. In addition to this, the minimum hour of electricity that must be provided to the six sectors (AP, PAT, RDS, MGJG, urban and industrial) is also defined. The loads are optimized by the proposed GWO model and later on its performance is evaluated in the MATLAB software. The performance outcomes were delineated by observing the total demand felt by the providers for the month of May, June and July and the total demand met by the proposed scheme. The results proved the efficiency of the proposed GWO model as it was able to provide electricity to every sector as per the demand.