Construction of a framework for real-time evaluation of regulation effect of distributed photovoltaic users based on multi-source data fusion

Distributed photovoltaic (PV) power generation is one of the new quality productive forces to promote the application of green energy and realize high-quality development. In order to improve the regulation effect in the process of PV power generation, multiple sources of data such as economic factors, electricity consumption habits, and indoor temperature are included in the calculation, and a real-time evaluation framework of the regulation effect of electricity users is constructed, and the particle swarm algorithm is used to solve the efficient regulation of energy. The case study shows that different electricity consumption habits and behaviors have an impact on the load dispatch situation. After using this paper’s scheme for regulation, the in-situ consumption increases by 77.2% and 89.4% in two scenarios, where the adjustable load consists of electric water heaters and washing machines (Scenario 1) and where the adjustable load consists of electric cars, electric water heaters and washing machines (Scenario 2), respectively. This paper’s scenario is able to better cope with the scheduling demand under different weather conditions, and the economic returns during the experimental cycle totaled 113.215 yuan, with gains of 8.180%, 10.186%, and 12.593%, respectively, over the remaining three alternative scenarios.