Home energy management in smart households: Optimal appliance scheduling model with photovoltaic energy storage system

Abstract At present, with the applying of distributed energy resource (DER) in the demand side, the difficulty of demand-side management (DSM) is increasing. Improving the consumption rate of DER is currently one of the important research contents of the home energy management system (HEMS). How to better coordinate household appliances to participate in the HEMS, so as to improve the situation is the focus of this paper. Due to the development of artificial intelligence and communication technology, we establish a household appliance optimization scheduling system. According to the household electricity-using habits, most household appliances are divided into three categories. Based on this, we propose a HEMS model, which aims to minimize the peak load and electricity cost of a smart home, and achieve single-objective and multi-objective optimization. In order to better implement the research of DER, the solar radiation data of one day in summer in Shanghai is used to compare with different capacities of photovoltaic energy storage system (PESS). Because the variables in the model are mostly binary or decimal integers, it is essentially a mixed integer programming (MIP). Therefore, a simulator has been implemented in the MATLAB software environment to facilitate the solution of proposed HEMS. The results show that the configuration of PESS is beneficial to the optimal scheduling of household appliances. In the single objective optimization, the peak load and electricity cost of scheme 4 is decreased by 61.51% and 71.39% compared with scheme 1, respectively. Besides, Pareto front is the most ideal in multi-objective optimization under scheme 4, and Pareto solutions distribution are more uniform, which can provide more scheduling choices for residential users. In addition, by comparing the different photovoltaic (PV) subsidy policies in 2013 and 2018, it is reasonable for China to gradually realize PV subsidy-free.