Open AccessA distributed EV charging strategy in an integrated energy system
Author(s) -
Tao Zhu,
Xiaoying Shi,
Ronghua Duan,
Yizhen Wang,
Yinliang Xu
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/424/1/012004
Subject(s) - range (aeronautics) , computer science , electricity , wireless , electric vehicle , purchasing , driving range , charging station , energy (signal processing) , real time computing , simulation , automotive engineering , electrical engineering , power (physics) , telecommunications , engineering , operations management , physics , quantum mechanics , statistics , mathematics , aerospace engineering
Electric vehicles (EV) are viewed as an environmental-friendly travel device but bring the driver with range anxiety. One of the solutions to tackle this issue is to recharge at the fast charging station (FCS). Since the traffic flow of the transportation network and the operation condition of the fast charging station varies from time to time, it is important to implement real-time charging guiding for the EV drivers. In this paper, we propose a distributed guiding method to search for the best FCS with minimum sum of time cost and electricity purchasing cost. The EVs are viewed as a distribution of spatial and temporal electrical loads, which would affect the locational marginal price (LMP) of the FCS. The varied LMPs would also react upon the EV driver’s choice. The proposed guiding method utilizes the wireless communication technologies. Simulation test demonstrates the effectiveness of the proposed EV guiding method in an integrated energy system.