AREA BASED EFFICIENT AND FLEXIBLE DEMAND SIDE MANAGEMENT TO REDUCE POWER AND ENERGY USING EVOLUTIONARY ALGORITHMS

Abstract

Evolutionary algorithms are stochastic that reflects the biological evolution to reach optimal solutions to optimization problems where mathematical techniques may fail. Demand Side Management (DSM) are designed to reduce electricity consumption or to shift the consumption from peak to off – peak hours depending on consumers’ lifestyle and behaviour. DSM is a flexible consumer driven activity in which the consumer has voluntarily changed his energy usage pattern during peak demand so to maintain the reliability and stability of power system and the performance of an electrical grid. In this aspect we have explored the impact of an efficient and flexible DSM which can reduce the power demand and energy in different areas like rural, urban and villa there by utilizing the device power rating and its activation time. The defined problem was solved with evolutionary based – genetic (GA), particle swarm (PSO) and differential evolution (DE) optimization algorithms. Simulation results show the better outcome in terms of power demand and energy reduction and the results are compared to know the better performing algorithm as on applied to DSM.