期刊
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
卷 66, 期 4, 页码 2915-2926出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2016.2593712
关键词
Charging station; deployment; electric vehicle (EV); power network; traffic network
资金
- National High-Tech Research and Development Plan of China [2011AA010102]
The lack of charging facilities has been a main obstacle to the widespread use of electric vehicles (EVs). What is worse is that existing chargers are still underutilized. Meanwhile, the grid instability caused by EV charging is becoming muchmore significant with increasing EV penetration. This paper studies how to size and locate charging stations in traffic networks considering grid constraints to balance the charging demand and power network stability. First, a spatiotemporal model of charging demand is proposed, and a 1 - (1/e) approximation algorithm to maximize the charging demand is designed. We analytically prove that 1 - (1/e) is the best bound that can be obtained in polynomial time. Then, a linearized power network model (LPNM) is proposed. Based on LPNM, a heuristic algorithm involving the grid constraints (HAG) is designed. Finally, the proposed models and algorithms are evaluated on real-world traffic networks and power networks. The relative error of the voltage deviation estimated by LPNM is about 4%. Compared with the plain demand model, adopting the spatiotemporal charging demandmodel improves the utilization of chargers by 5% at least. Compared with the greedy algorithm with grid constraints (GAG), HAG improves the carrying capacity of the power network by 20.7%, reduces the voltage deviation by 25%, and increases the EVs charged by 18.07%.
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