Online Energy Management Method Of PV-assisted Charging Station For Electric Vehicle

Developing renewable energy resources and Electric Vehicles (EVs) has been seen as an effective way to reduce carbon emission in development and ensure energy security by many countries. The Photovoltaic-assisted Charging Station (PVCS) is gradually growing up, and is having more attenetion. Owing to the uncertainty of EV charging demand, a enengy management method should be studied to decide the charging power of EVs, and meanwhile promote the operation profit of charging station. In order to maximize the operation profit and simultaneously guarantee the service quality, the energy management is an important issue for the PVCS. With the development of PVCS, a network will be gradualy formed. There is a difference betwwen PV power and charging demand of each PVCS, and some charging demand is adjustable. It provides a basis of energy flow among different PVCS. In some cases, exchanging energy through the grid can optimize the operation of these PVCS, and promote the operation profit. This operation mode is an effective way to optimize the operation in the present market environment. However, some information of PVCS is private, and can not be shared. For these purpose, an Online Energy Management Method of PV-assisted Charging Station for Electric Vehicle is proposed in this paper.For single PVCS, an online energy management method leveraging both offline optimization and online decision under independent mode is proposed. In order to maximize the self-consumption of PV energy, and decide the power supplied from the power grid with Time-of-Use (TOU) pricing, online learning is cooperated with rule-based decision to form a real-time online decision algorithm. The knowledge base for online learning are derived and updated from the results of offline optimization after every operation day. The PVCS located at workplace parking lots is taken as an instance to test the method. The simulation results show that the method can be operated without future information of PV power and charging demand. The online decision results are close to the optimal results of offline optimization.For the network of PVCS, Therefore, an online energy management method under cooperation mode is proposed. The operation way of PVCS and energy dispatch strategy can be decided using the method with partial information shared. Firstly, according to the feature of energy flow in PVCS, the traditional ADMM algorithm is modified, and the distributed optimization model is established. The model make the charging power and exchange energy as optimal variable. The only required information, whitch is exchanged among PVCS, is the information of exchange energy. Then, the centralized optimization model is introduced for contrast, which need some other information besides exchange energy. Making the operation profit as the objective, and the enengy balance etc. as constrains, the model is established and solved. At last, the accuracy and practicality of the distributed optimization model is verified, through contrast of distributed and centralized optimization model in the case study.