Abstract
To tackle the challenges introduced by the fast-growing charging demand of electric vehicles (EVs), the power distribution systems (PDSs) and fast charging stations (FCSs) of EVs should be planned and operated in a more coordinated fashion. However, existing planning approaches generally aim to minimize investment costs in PDSs while ignoring the risk of worsening traffic conditions. To overcome this research gap, this article integrates the interests of traffic networks into PDS and FCS joint planning model to mitigate negative impacts on traffic conditions caused by installing FCSs. First, a novel microscopic method that is different from traditional assignment methods is proposed to simulate the influences of FCSs on traffic flows and EV charging loads. Then, a multiobjective joint planning model is developed to minimize both the planning costs and unbalanced traffic flows. A new bilayer Benders decomposition algorithm is designed to solve the proposed joint planning model. Numerical results on two practical systems in China validate the feasibility of our microscopic method by comparing the simulated results with real data. Compared with existing approaches, it is also demonstrated that the proposed joint planning approach helps to balance traffic flow assignments and relieve traffic congestion.
Original language | American English |
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Article number | 9096550 |
Pages (from-to) | 1795-1809 |
Number of pages | 15 |
Journal | IEEE Transactions on Industrial Informatics |
Volume | 17 |
Issue number | 3 |
DOIs | |
State | Published - Mar 2021 |
Bibliographical note
Publisher Copyright:© 2005-2012 IEEE.
NREL Publication Number
- NREL/JA-5D00-78879
Keywords
- Bilayer expanded Benders decomposition
- electric vehicle (EV)
- joint planning
- multiagent-based microscopic traffic assignment model (MMTAM)
- traffic flow assignment