Demand Side Management in Smart Grid using Optimization Technique for Residential, Commercial and Industrial Load

Abstract

Objective: To minimize the Peak to Average load Ratio (PAR) per day of end users so that the smart grids(SG) efficiency is increased. Set of appliances differentiated as elastic and fixed are considered for optimal scheduling at the user end. Methods: Demand side management (DSM) in smart grid is one which permits customers to reach determinations affecting their energy consumption, and reduces the peak hour demand of the energy providers and reshapes the load profile. Genetic algorithm (GA) is a powerful technique to obtain near optimal solution. Hence GA is used for this load rescheduling problem for a sample test system to minimize the cost of end user. Findings: Economical and environmental advantages can be obtained by time based pricing model compared to currently existing scenario. Especially, the electricity expenditures of the end user can be reduced by responding to pricing which changes with different hours of a day in SG. Improvement: In this work rescheduling of the load curve of a consumer from the existing load curve is performed. The former is done based on time based pricing method that would reduce the PAR of end-user. This scheduling is also based on categorizing the devices used by the user as shiftable and non-shiftable loads.