Demand-side Management of Residential Service Area Under Price-based Demand Response Program in Smart Grid

Abstract

Grid extension and construction of additional power plants based on conventional fuels are becoming a challenge to meet ramping-up load demand. This becomes more pressing especially in cost and time constraints. In order to alleviate these issues and bridge the gap of demand with supply, demand-side management (DSM) in the smart grid (SG) is considered as an effective solution. In this paper, DSM is performed through residential load-scheduling with the help of an energy management controller (EMC). The EMC introduced for residential load-scheduling is based on heuristic algorithms like; binary particle swarm optimization (BPSO), genetic algorithm (GA), and hybrid genetic BPSO (HGBPSO). The proposed heuristic-based EMC performs DSM by scheduling residential load under day-ahead price-based demand response (DR) program. The proposed scheme optimally performs DSM and results in an acceptable reduction of electricity cost, peak to average ratio (PAR), CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emission, and user-discomfort all at once. Simulation results validate that HGBPSO-based EMC outperforms BPSO and GA-based EMC in the matter of management. The proposed scheme is highly suitable for real-life management of residential service in SG.