Utilization of Demand Side Management for Stability Improvement in Renewable Energy Resources in United Kingdom

This research deals with the Particle Swarm Optimization (PSO) algorithm for a meagre load shifting in demand side management focusing on scheduling the residential, commercial, and industrial load in United Kingdom. Irregular and unscheduled load consumption causes sparsity in renewable energy sources, which on the other sides causes customers discomfort in their utility bills. Nash equilibrium, which smartly minimizes energy utility cost and peak-to-average ratio, is still an intense problem. Therefore, a bidirectional framework is developed to monitor both the demand and supply side and provide solutions to solve customer’s problems. The PSO algorithm is employed to achieve super liner convergence rate and minimize to average ratio. The suitable selection for the inertia weight creates an equilibrium between global and local exploration abilities. The detailed analysis and results of the two cases of the PSO algorithm have been drawn to illustrate the reduction in peak-to-average ratio and utility cost.