Electric‐bus charging stations multi‐objective optimization planning on coupled power and traffic networks
Abstract The electrification of public transportation is one significant step towards the sustainability of modern society. Both power networks and traffic networks are influenced by the optimal allocation of electric‐bus (e‐bus) charging stations. In this paper, the optimal operation cost of e‐bus...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-04-01
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| Series: | IET Intelligent Transport Systems |
| Online Access: | https://doi.org/10.1049/itr2.12215 |
| Summary: | Abstract The electrification of public transportation is one significant step towards the sustainability of modern society. Both power networks and traffic networks are influenced by the optimal allocation of electric‐bus (e‐bus) charging stations. In this paper, the optimal operation cost of e‐bus charging stations is first designed based on the charging price and congestion toll. Charging price and congestion toll are used to guide charging behavior to reduce total traveling and waiting time. Second, the e‐bus charging station allocation method is proposed. The planning costs are optimized to locate e‐bus charging stations on coupled power and traffic networks. Third, a non‐dominated sorting genetic algorithm‐II (NSGA‐II) is adopted to solve the multi‐objective optimization problem, which maximizes the captured traffic flow and minimizes infrastructure investment at the same time. The effectiveness of NSGA‐II is proved compared with the enumeration method. Finally, based on a 33‐node power distribution network and a 77‐node traffic network, simulation results demonstrate the feasibility of the e‐bus charging station allocation method. |
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| ISSN: | 1751-956X 1751-9578 |