Heuristic Algorithm Based Energy Management System in Smart Grid

Abstract

Smart grid is one of the most advanced technologies which plays a key role in maintaining balance between demand and supply by implementing demand response (DR). Residential users basically effect the overall performance of traditional grid due to maximum requirement of their energy demand. Home energy management (HEM) benefit the end user by monitoring, managing and controlling their energy consumption. Appliance scheduling is integral part of HEM as it manages energy demand according to supply by automatically controlling the appliances or by shifting the load from peak to off peak hours. Recently different techniques based on artificial intelligence (AI) are used to meet these objectives. In this research work, we evaluate the performance of HEM which is designed on the basis of heuristic algorithms, wind driven optimization (WDO), ganetic algorithm (GA) and binary particle swarm optimisation (BPSO). Finally, simulations are conducted in MATLAB to validate the performance of scheduling techniques in terms of cost, reduced peak to average ratio (PAR) and equally distributed energy consumption pattern. The simulation results prove that WDO algorithm based HEM proves to perform efficiently than BPSO and GA.