Improved Demand Response with Particle Swarm Optimization - Dey, Suparna; Dasgupta, Monalisa; Chatterjee, Soumesh; Deb, Gagari (International Journal of Computer Sciences and Engineering, 2025)
Among all the power management strategies in smart grid, demand response is quiet popular because of its significance impact on saving in peak demand and reduced energy consumption. Electricity price revealed by utility companyis mainly accountable for the demand response to lead the consumer in electricity scheduling.The mutual benefits for both customer and supply side are ensured with the use of price conferring mechanism through demand response.This paper proposes anapproach to minimize the elastic load through price weight given by the utility company. Three types of consumers are designed as residential, industrial and commercial. The ‘per day electricity use’ for these consumers has been reducedby scheduling elastic loads using Particle Swarm Optimization(PSO) technique. The outcome of simulation results show that the recommended algorithm reduces the cost while balancing the peak demand.