Abstract: In order to reduce the cost of household electricity consumption and improve the local consumption rate of residential photovoltaic power generation, a home load scheduling strategy is proposed based on real-time control of energy storage charging and discharging behavior. Firstly, the household loads are classified and a scheduling model is established with the objectives of lowest electricity cost, smallest carbon emission and largest comfort; secondly, based on the real-time photovoltaic output and peak-valley time-of-use electricity price, a scheduling strategy is proposed to meet the household load electricity demand through controlling the charging and discharging of energy storage; finally, the proposed model is simulated and solved using the scenario analysis method and hierarchical multi-strategy learning improved binary particle swarm optimization algorithm (HLSBPSO). The results show that the proposed strategy and algorithm can reduce the user's electricity bill by 49.2% and increase the comfort by 67.9%, which can provide a new theoretical support for the safe and economical operation of household photovoltaic power generation.