Pricing for Electric Vehicle Charging Stations Based on the Responsiveness of Demand

排队论 动态定价 电动汽车 利润(经济学) 需求响应 波动性(金融) 温室气体 汽车工程 计算机科学 环境经济学 业务 微观经济学 经济 工程类 功率(物理) 电气工程 计算机网络 计量经济学 生态学 量子力学 物理 生物
作者
Shuying Lai,Jing Qiu,Yuechuan Tao,Junhua Zhao
出处
期刊:IEEE Transactions on Smart Grid [Institute of Electrical and Electronics Engineers]
卷期号:14 (1): 530-544 被引量:27
标识
DOI:10.1109/tsg.2022.3188832
摘要

Electric vehicles (EVs) have the promising potential to be effective in mitigating greenhouse gas emissions in the transportation sector. Hence, the penetration of EVs in some countries experiences steady growth. However, the proliferation of EVs can cause negative impacts on the power distribution network (PDN) and the transportation network (TN). Thus, in this paper, a dynamic pricing strategy for electric vehicle charging stations (EVCSs) is proposed to facilitate EVCSs to earn higher profits while alleviating the potential negative impacts on both PDN and TN. First, a pricing strategy, considering the competition effect established based on the TN, is formulated to facilitate the EVCS to attract the defined competitive charging demand. Second, a two-step approach is proposed to mathematically formulate the responsiveness of demand towards the charging price. Third, EV user behaviors are incorporated based on both an admission control scheme and a queueing model to further adjust the charging demand. We have conducted simulations to verify the effectiveness of the pricing strategy in a PDN and TN coupled system, which contains approximately 2000 EVs. Results show that the proposed pricing strategy can facilitate the EVCS to gain 14.2% more net charging profit on average compared with the other three cases. Moreover, the operational stability of the EVCS can be ensured because the proposed pricing strategy can result in the least queueing length volatility with moderate profit variance compared with the other three cases. Furthermore, the proposed pricing strategy can achieve spatial load shifting by incentivizing EVs to alter their station-selection decisions to avoid possible power congestion in the electricity network.
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