A Hybrid Bat-Crow Search Algorithm Based Home Energy Management in Smart Grid
In smart grid (SG), demand side management (DSM) is a set or group of programs, allow consumers to play a vital role in transferring of their own load demand during peak time periods and minimizing their hourly based power consumption and total monetary cost of the electricity consumed and it also helps the electric utility in reducing higher power demand in the time of high energy demanded time slots. Where, this consequently results in reduction of the total electricity cost, maximization of power grid sustainability and reduction in carbon dioxide emissions which ultimately results in a pollution free environment. Nowadays, most of the DSM strategies available in existing literature concentrate on house hold appliances scheduling to decrease consumer delay time and peak to average ratio (PAR). However, they ignore the total electricity cost. In this paper, we employ load shifting strategy, to decrease total electricity payment. To gain above objective, we propose a hybrid of bat algorithm (BA) and crow search algorithm (CSA) i.e., bat-crow search algorithm (BCSA) and the results are compared with the existing BA and CSA. Simulations were conducted for a single home with 15 appliances, uses critical peak pricing (CPP) scheme for the computation of consumer’s electricity bill. The results show that load is successfully shifted to lower price time slots using our proposed BCSA technique, which ultimately leads to 31.191% reduction in total electricity payment.
KeywordsBat Algorithm Crow Search Algorithm Metaheuristic techniques Heuristic techniques Appliances scheduling Home Energy Management Demand Side Management Smart Grid
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