@inproceedings{6afd675ab26c42e98735531076c8d710,
title = "Pricing Strategy of Fast Charging Stations in Coupled Power-Transportation System Considering Responsive Traffic Demand",
abstract = "The price of fast charging stations (FCSs) can dramatically impact the behavior of electric vehicle (EV) users on choosing paths or charging stations, which will further influence the operation of both power distribution network (PDN) and transportation network (TN). This paper proposes a unique framework to get an optimal pricing strategy for FCSs considering the responsive traffic demand of EV users. The responsive traffic demand correlates closely with the current charging price and traffic condition. The optimal pricing problem of FCSs considered coupled operation of PDN and TN is first formulated as a bi-level optimization model to maximize the profit of the distribution power system operator (DSO). Then a deep reinforcement learning method is adopted to approximately solve the hard bi-level problem. Numerical experiments demonstrate that the proposed strategy can redistribute charging loads and enhance the operation of PDN.",
keywords = "Electric vehicle, Fast charging station, Power distribution network, Pricing strategy, Transportation network",
author = "Guo Chen and Xiuli Wang and Ziqiang Wang",
note = "Publisher Copyright: {\textcopyright} 2023, State Grid Electric Power.; 37th Annual Conference on Power System and Automation in Chinese Universities, CUS-EPSA 2022 ; Conference date: 23-10-2022 Through 25-10-2022",
year = "2023",
doi = "10.1007/978-981-99-1439-5\_43",
language = "英语",
isbn = "9789819914388",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "460--469",
editor = "Pingliang Zeng and Xiao-Ping Zhang and Vladimir Terzija and Yi Ding and Yunxia Luo",
booktitle = "The 37th Annual Conference on Power System and Automation in Chinese Universities, CUS-EPSA 2022",
}