Distribution network planning integrating charging stations of electric vehicle with V2G |
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| Affiliation: | 1. State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;2. Guangxi University, Nanning, Guangxi Province, China;3. China Three Gorges University, Yichang, Hubei Province, China;1. Department of Management and Management Science, Pace University, New York, NY 10038, United States;2. Department of Industrial and Systems Engineering, Auburn University, Auburn, AL 36849, United States;3. Department of Electrical and Computer Engineering, New York University, New York, NY 11201, United States;1. Academy of Engineering Sciences of Serbia, Belgrade, Serbia;2. Tech. School of Professional Studies, Požarevac, Serbia;1. Department of Electrical and Information Engineering, Politecnico di Bari, Bari, Italy;2. Terna S.p.A., Rome, Italy;1. INESC TEC and University of Porto, Porto, Portugal;2. UFABC – Federal University of ABC, Santo André, SP, Brazil;3. INESC TEC, Porto, Portugal;4. UNESP – São Paulo State University, Ilha Solteira, SP, Brazil;1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China;2. Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen 518000, China |
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| Abstract: | Accompanied by the popularization of EVs, the planning of electric vehicle (EV) charging stations becomes an important concern of distribution network planning. In this paper, the load density method is introduced to determine the optimal capacity of the EV charging stations in the areas to be planned, and the difference between 1 and the weight coefficients obtained by the analytic hierarchy process (AHP) method is used to calculate the cost coefficients of the charging station. The objective function of the optimal distribution network planning model should be the minimal cost of the fixed investments, the operational costs and the maintenance costs including the substations, charging stations and feeders. In this model, the effect of vehicle-to-grid (V2G) is considered, i.e., the EV is respectively treated as both the load and the source. Moreover, the electricity price volatility has been taken into consideration. In this case, EV owners can be guided to charge and discharge EV orderly. The ordinal optimization approach is applied to get the best solution. The results of the case study based on IEEE 54 nodes model show the feasibility and effectiveness of the proposed model. |
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| Keywords: | Electric vehicle charging station V2G Distribution network planning Load density method AHP Ordinal optimization approach |
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