Optimal Capacity Planning Method for Distributed Photovoltaics Considering the User Grid Connection Locations

To address the conflicts between high-penetration distributed photovoltaics (PV) integration causing voltage limit violations, reverse power flow issues, and the grid connection needs of industrial and commercial users, this paper proposes an optimal capacity planning method for distributed PV considering the user’s grid connection locations. This method effectively increases the acceptance capacity of the distribution transformer network for distributed PV while ensuring the safe and stable operation of the distribution network. First, the source–load uncertainty is considered, and the k-means clustering algorithm is used to select multiple typical daily probability scenarios. Then, the PV optimal connection node range is obtained through a PV site selection and sizing model. For the planning of nodes within the optimal range, an optimal capacity planning model focusing on the economic benefits of users is established. This model aims to optimize the improvement of wheeling cost and maximize the economic benefits of grid-connected users by determining the optimal PV access capacity for each node. Finally, for PV users outside this range, after determining the maximum allowable capacity for each node, the capacity margin and static voltage stability are comprehensively considered to evaluate the network access scheme. Simulation examples are used to verify the effectiveness of the proposed method, and the simulation results show that the proposed method can effectively increase the acceptance capacity of the distribution network for photovoltaic systems. By fully considering the wheeling cost collection strategy, the distributed PV acceptance capacity is increased by 20.14%, while both user benefits and the operational safety and economic performance of the distribution network are significantly improved, ultimately resulting in a 27.77% increase in total revenue.