부산대학교 도서관

In light of contemporary societal emphasis on low-carbon development and the exponential growth of electric vehicles, the optimization of EVs within low-carbon energy networks has garnered heightened attention. In pursuit of achieving more profound emissions reductions and the substantial integration of renewable energy sources, this study delves into a collaborative planning approach encompassing public charging station and distributed renewable energy sources. Aiming at improving renewable energy consumption of electric vehicles and integration of distributed renewable energy sources on distributed networks, a mixed integer model is proposed to determine the sizing and size of charging station, PV generation, and other renewable energy sources. Meanwhile, several significant factors such as electric vehicle charging demand, the operation conditions of the power distribution network are considered. The proposed model is solved by neural networks to make sure the accuracy of solutions and solving speed. he effectiveness of this method is verified by simulation. To make sure of the feasibility and practicality of the methodology, numerical experiments are conducted. The results show that this method can well optimize the location and size of the charging stations, PV generators and utilization of renewable energy as much as possible.