Distributed photovoltaic power generation as a renewable resource plays an important role in people’s lives, but the instability of photovoltaic power generation at the same time also brings difficulties in scheduling optimization of user power. In this paper, from the perspective of optimizing distributed PV scheduling to enhance the benefits, we constructed a distributed PV user power scheduling model, and proposed the scheduling based on the electrical appliances and energy storage system, under the real-time tariff mechanism, based on the charging and discharging cycle of the energy storage system BESS to effectively utilize the PV power generation and to reduce the cost of electricity consumption. In model solving, the non-dominated sorting genetic algorithm NSGA-II has been improved, and the combined crossover operator, combined mutation operator, and dynamic congestion strategy have been introduced to improve the global search capability. In the application practice, the model in this paper enables instant prediction tracking in the face of different weather changes, such as cloudy days and sunny days. Regardless of the fixed strategy or economic scheduling strategy, the model in this paper can complete the corresponding power optimization and control in accordance with the strategy, to meet the user to improve the effectiveness of economic efficiency, to mobilize the user’s distributed photovoltaic use of enthusiasm.