A domestic microgrid with optimized home energy management system

Abstract

Microgrid is a community-based power generation and distribution system that interconnects smart homes with renewable energy sources (RESs). Microgrid efficiently and economically generates power for electricity consumers and operates in both islanded and grid-connected modes. In this study, we proposed optimization schemes for reducing electricity cost and minimizing peak to average ratio (PAR) with maximum user comfort (UC) in a smart home. We considered a grid-connected microgrid for electricity generation which consists of wind turbine and photovoltaic (PV) panel. First, the problem was mathematically formulated through multiple knapsack problem (MKP) then solved by existing heuristic techniques: grey Wolf optimization (GWO), binary particle swarmoptimization (BPSO), genetic algorithm (GA) and wind-driven optimization (WDO). Furthermore, we also proposed three hybrid schemes for electric cost and PAR reduction: (1) hybrid of GA andWDO namedWDGA; (2) hybrid of WDO and GWO namedWDGWO; and (3)WBPSO, which is the hybrid of BPSO andWDO. In addition, a battery bank system (BBS) was also integrated to make our proposed schemes more cost-efficient and reliable, and to ensure stable grid operation. Finally, simulations were performed to verify our proposed schemes. Results show that our proposed scheme efficiently minimizes the electricity cost and PAR.Moreover, our proposed techniques,WDGA,WDGWO andWBPSO, outperform the existing heuristic techniques.