Dynamic Modeling and Real-time Management of a System of EV Fast-charging Stations Article Swipe
Dingtong Yang
,
Navjyoth J.S. Sarma
,
Michael Hyland
,
R. Jayakrishnan
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2012.09349
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2012.09349
Demand for electric vehicles (EVs), and thus EV charging, has steadily increased over the last decade. However, there is limited fast-charging infrastructure in most parts of the world to support EV travel, especially long-distance trips. The goal of this study is to develop a stochastic dynamic simulation modeling framework of a regional system of EV fast-charging stations for real-time management and strategic planning (i.e., capacity allocation) purposes. To model EV user behavior, specifically fast-charging station choices, the framework incorporates a multinomial logit station choice model that considers charging prices, expected wait times, and detour distances. To capture the dynamics of supply and demand at each fast-charging station, the framework incorporates a multi-server queueing model in the simulation. The study assumes that multiple fast-charging stations are managed by a single entity and that the demand for these stations are interrelated. To manage the system of stations, the study proposes and tests dynamic demand-responsive price adjustment (DDRPA) schemes based on station queue lengths. The study applies the modeling framework to a system of EV fast-charging stations in Southern California. The results indicate that DDRPA strategies are an effective mechanism to balance charging demand across fast-charging stations. Specifically, compared to the no DDRPA scheme case, the quadratic DDRPA scheme reduces average wait time by 26%, increases charging station revenue (and user costs) by 5.8%, while, most importantly, increasing social welfare by 2.7% in the base scenario. Moreover, the study also illustrates that the modeling framework can evaluate the allocation of EV fast-charging station capacity, to identify stations that require additional chargers and areas that would benefit from additional fast-charging stations.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2012.09349
- https://arxiv.org/pdf/2012.09349
- OA Status
- green
- Cited By
- 5
- References
- 47
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3111544536
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3111544536Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2012.09349Digital Object Identifier
- Title
-
Dynamic Modeling and Real-time Management of a System of EV Fast-charging StationsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-12-17Full publication date if available
- Authors
-
Dingtong Yang, Navjyoth J.S. Sarma, Michael Hyland, R. JayakrishnanList of authors in order
- Landing page
-
https://arxiv.org/abs/2012.09349Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2012.09349Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2012.09349Direct OA link when available
- Concepts
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Charging station, Queueing theory, Computer science, Revenue, Queue, Operations research, Dynamic pricing, Electric vehicle, Simulation, Real-time computing, Engineering, Computer network, Economics, Microeconomics, Power (physics), Quantum mechanics, Physics, AccountingTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 2, 2023: 2, 2022: 1Per-year citation counts (last 5 years)
- References (count)
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47Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| publication_date | 2020-12-17 |
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| referenced_works_count | 47 |
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| abstract_inverted_index.(EVs), | 4 |
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| abstract_inverted_index.prices, | 88 |
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| abstract_inverted_index.revenue | 215 |
| abstract_inverted_index.schemes | 155 |
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| abstract_inverted_index.Moreover, | 233 |
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| abstract_inverted_index.Specifically, | 194 |
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| abstract_inverted_index.interrelated. | 138 |
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