Joint planning of multi-data driven electric vehicle charging facilities including distributed energy

In response to the traditional planning methods' over-reliance on centralized power grid supply and neglect of the spatial dispatch potential of distributed energy sources and electric vehicles, this paper proposes a joint planning method for distributed energy and electric vehicle charging facilities that takes into account the dispatch characteristics of charging loads. By dynamically guiding charging loads to upstream nodes in feeder lines or areas with abundant distributed energy resources, the method optimizes the location and capacity determination of charging facilities and the differentiated configuration of distributed energy. The model aims to minimize the annual social total cost, considering power flow safety, user dispatch distance, and the uncertainty of distributed energy output, achieving coordinated optimization of charging demand spatiotemporal distribution and energy supply. Case studies show that the proposed method can increase photovoltaic capacity by 10.2%, reduce the annual social total cost by 4.3%, and mitigate voltage limit risks by 15.8%, providing an efficient and low-carbon solution for distribution network planning under high renewable energy integration.