User-Friendly Demand Side Management for Smart Grid Network

Abstract

Diverse methods for demand side management (DSM) have been proposed for residential areas. These techniques are effectual in reducing electricity cost by scheduling the customer loads. However, waiting time of user appliances is increased. In this research work a user-friendly technique is developed by using heuristic algorithm to overcome user inconvenience. Genetic algorithm is used for scheduling a residential load in smart grid (SG) network. By using Genetic algorithm in real time pricing (RTP) environment, our main purpose is to minimize both peak to average ratio (PAR), cost of electricity and maximize comfort level in sense of user priority and preferences. To attain our purpose, we categorize appliances according to their duty cycle. We used renewable energy source (RES) to meet peak hours and better scheduling of loads. Simulation work shows that our user-friendly algorithm plays a vital role in load scheduling and reduction in PAR values.