Electric vehicle charging station placement: Formulation, complexity, and solutions
Open accessAbstract
To enhance environmental sustainability, many countries will electrify their transportation systems in their future smart city plans, so the number of electric vehicles (EVs) running in a city will grow significantly. There are many ways to recharge EVs' batteries and charging stations will be considered as the main source of energy. The locations of charging stations are critical; they should not only be pervasive enough such that an EV anywhere can easily access a charging station within its driving range, but also widely spread so that EVs can cruise around the whole city upon being recharged. Based on these new perspectives, we formulate the EV charging station placement problem (EVCSPP) in this paper. We prove that the problem is nondeterministic polynomial-time hard. We also propose four solution methods to tackle EVCSPP, and evaluate their performance on various artificial and practical cases. As verified by the simulation results, the methods have their own characteristics and they are suitable for different situations depending on the requirements for solution quality, algorithmic efficiency, problem size, nature of the algorithm, and existence of system prerequisite.
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The optimal location of EVCSs and the impact of EV load on the distribution system have become more prominent research topics in the last decade.
“In addition, the optimal location of EVCSs and the impact of EVs load on the distribution system have become more prominent research topics (Lam et al., 2014) in the last decade.”
From Optimal location of electric vehicle charging station and its impact on distribution network: A review (2022) · cites this paper as Lam et al., 2014
The Introduction says EVs have been studied actively since the boom of the smart grid, and Related Work discusses both charging-station placement and the effects of EV charging on distribution networks (page numbers unavailable). The paper supports these as research topics, but does not establish that both became more prominent over the claimed decade. (LLM, conf=0.82)
Experimental — accuracy not yet measuredLam et al. (2014) considered construction cost.
“Construction cost (Lam et al., 2014) | 2014 | CRO | N | Y | N | N | N | N | N | L3 | N |”
From Optimal location of electric vehicle charging station and its impact on distribution network: A review (2022) · cites this paper as Lam et al., 2014
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- Authors
- Lam, A. Y. S., Leung, Y.-W., & Chu, X.
- Affiliations
- Hong Kong Baptist University (HK)
- Venue
- IEEE Transactions on Smart Grid
- Published
- 2014-11
- Volume
- 5
- Issue
- 6
- Pages
- 2846-2856
- ISSN
- 1949-3053 (ISSN-L)
- 1949-3061
- OpenAlex
- W2141503184
- Cited by
- 436
- References
- 23
- Citations by year
- 2026: 25 · 2025: 45 · 2024: 38 · 2023: 53 · 2022: 37 · 2021: 45 · 2020: 42 · 2019: 48 · 2018: 38 · 2017: 34 · 2016: 23 · 2015: 7 · 2014: 1
- FWCI
- 11.51
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- IEEE Transactions on Smart Grid (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Faculty Research Grant of Hong Kong Baptist University (FRG2/13-14/045)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Vehicle Routing Optimization Methods
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Facility Location and Emergency Management
- Keywords
- electric vehicle charging stations, charging station location, electric vehicles, NP-hardness, combinatorial optimization, smart cities, electric mobility, solution methods
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