Study on load distribution and economic benefit of electric taxi charging station

Yu-ying, Shen; Peng, Pai; Ming-xi, Chen; Bing, Wang

doi:10.1049/icp.2021.0349

Cited by 2 publications

(2 citation statements)

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“…Since the load-level scheduling optimization has the same logical framework as in Chapter 2, the optimization is performed using the Monte Carlo method, which is used to simulate the wind turbine, PV output, and EV load for the load tier scheduling optimization strategy (Yuying et al, 2021).…”

Section: Ev Hierarchical Scheduling Optimization Strategy Solving And...mentioning

confidence: 99%

Research on EV Scheduling Optimization Strategy Based on Monte Carlo and AntLion Optimizer

Peng

Zhao

et al. 2022

Front. Energy Res.

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As environmental problems become more serious, the trend of “carbon peaking and carbon neutral” has become necessary. However, the disorderly entry of large-scale EVs into the grid has threatened the security of the grid. The purpose of this paper is to study the optimization strategy of EVs to improve the economy and stability of distributed energy. Firstly, the EV user behavior model is constructed to study the charging and discharging behavior influencing factors, and the EV charging and discharging loads are simulated using Monte Carlo simulation. Secondly, we build a hierarchical scheduling optimization strategy based on EV user satisfaction using an improved AntLion optimizer, finally, the load peaks of the distributed energy system are suppressed and the satisfaction of EV customers is significantly improved; in the process of EV scheduling optimization at the source storage layer, EVs fully consume renewable energy output and the comprehensive operating costs of the distributed energy system are reduced. The conclusions are verified and the system is optimized, resulting in improved user satisfaction and optimized system economy and stability.

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Section: Ev Hierarchical Scheduling Optimization Strategy Solving And...mentioning

confidence: 99%

Research on EV Scheduling Optimization Strategy Based on Monte Carlo and AntLion Optimizer

Peng

Zhao

et al. 2022

Front. Energy Res.

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“…From the infrastructure point of view, the charging station takes the vast majority of EU funding [20,21]. Is it worth noticing that many cities, including Shanghai and Shenzhen, have vigorously promoted the development of electric taxis by introducing electric vehicles into public transportation service systems [22]. Furthermore all taxis in Beijing are planned to be replaced with EVs [23].…”

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confidence: 99%

Electrifying Urban Transportation: A Comparative Study of Battery Swap Stations and Charging Infrastructure for Taxis in Chicago

Borgosano,

Martini,

Longo

et al. 2024

IEEE Access

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In recent years, the Electric Vehicles (EVs) industry has experienced rapid growth, driven by advancements in battery technology, environmental awareness, and government incentives. However, traditional charging infrastructure's limited availability and long charging times pose significant challenges, especially for long-distance travel and public service vehicles like taxis, buses, and law enforcement vehicles. This work explores the innovative concept of Battery Swap Stations (BSSs), an emerging technology poised to transform the EV charging landscape. It specifically focuses on electric taxis operating in Chicago's urban environment, highlighting the substantial benefits this technology can offer. BSSs demonstrated to dramatically reduce charging times, improving taxi service efficiency and increasing revenue potential. Instead, conductive charging impacts the working time of taxis across all case studies (as observed in the Level 2 charger scenario) While BSS technology has its drawbacks, such as optimal location challenges and battery management complexities, it has the potential to significantly enhance service quality. Additionally, these stations hold the promise of not only increasing urban transportation system efficiency but also contributing to their sustainability.

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Study on load distribution and economic benefit of electric taxi charging station

Cited by 2 publications

References 0 publications

Research on EV Scheduling Optimization Strategy Based on Monte Carlo and AntLion Optimizer

Research on EV Scheduling Optimization Strategy Based on Monte Carlo and AntLion Optimizer

Electrifying Urban Transportation: A Comparative Study of Battery Swap Stations and Charging Infrastructure for Taxis in Chicago

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