COMMUNITY BASED HOME ENERGY MANAGEMENT SYSTEM

Abstract

In a Smart Grid (SG) scenario, domestic consumers can gain cost reduction benefit by scheduling their Appliance Activation Time (AAT) towards the slots of low charge. Minimization in cost is essential in Home Energy Management Systems (HEMS) to induce consumers acceptance for power scheduling to accommodate for a Demand Response (DR) at peak hours. Despite the fact that many algorithms address the power scheduling for HEMS, community based optimization has not been the focus. This paper presents an algorithm that targets the minimization of energy costs of whole community while keeping a low Peak to Average Ratio (PAR) and smooth Power Usage Pattern (PUP). Objective of cost reduction is accomplished by finding most favorable AAT by Particle Swarm Optimization (PSO) in conjunction with Inclined Block Rate (IBR) approach and Circular Price Shift (CPS). Simulated numerical results demonstrate the effectiveness of CPS to assist the merger of PSO & IBR to enhance the reduction/stability of PAR and cost reduction.