Research on Distributed Photovoltaic Based on Clustering sub to Enhance the Carrying Capacity of Electric Vehicles under Orderly Charging

Enhancing the carrying capacity of electric vehicles through distributed photovoltaic is important to achieve the carbon peaking and carbon neutrality goals. In this paper, based on Monte Carlo simulation, a multi-time tariff model is established to guide the orderly charging of electric vehicles and obtain a probabilistic model of electric vehicle charging load. The maximum load capacity and node voltage deviation are selected as the operating constraints. Using source-load power balance as the index, the distribution network is divided into clusters to determine the siting of distributed photovoltaic. The impact of distributed photovoltaic access scale on electric vehicle carrying capacity is simulated using typical photovoltaic power output data. The algorithm results show that under orderly charging, the access to distributed photovoltaic helps to alleviate the voltage dip problem, improve the electric vehicle carrying capacity, and promote the safe and stable operation of the system.