Planning Strategy for an Electric Vehicle Fast Charging Service Provider in a Competitive Environment

Duan, Xiaoyu; Hu, Zechun; Song, Yonghua; Strunz, Kai; Cui, Yan; Liu, Likai

doi:10.1109/tte.2022.3152387

Cited by 35 publications

(3 citation statements)

References 30 publications

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“…There is a user interface that allows users to enter trip parameters, access real-time route planning, and receive energy efficient routes. Electric vehicle ownership can 269 only be accurately simulated with this wide-ranging sequential approach which builds each step on previous ones [15][16][17][18].…”

Section: Loss Function and Optimizationmentioning

confidence: 99%

Electric Vehicle Health Monitoring with Electric Vehicle Range Prediction and Route Planning

Jayaram,

Chetan,

Nayak

2024

JIWE

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The automotive industry is experiencing a revolutionary wave due to the rapid spread of electric vehicles (EVs), which is paving the way for a fundamental and long-lasting revolution in the way we approach transportation. The global movement to reduce greenhouse gas emissions and lessen the environmental impact of traditional internal combustion engine vehicles has seen a significant boost in the popularity of electric vehicles as people come together to support environmentally conscious and sustainable mobility solutions. But the ecology surrounding electric vehicles must continue to flourish if the particular problems that EVs present are to be successfully addressed. Chief among these are the formidable foes of range anxiety and battery health management. Range anxiety is a real issue felt by many potential EV owners worry about becoming stuck because their battery has run out before reaching their destination. This psychological barrier is very noticeable and makes present and future EV owners doubtful. In addition, the longevity and health of EV batteries are essential to their continued effectiveness and affordability. The driving range and operating efficiency of the vehicle are directly affected by the gradual degradation of the battery due to several factors like aging, charging patterns, and temperature. This research presents an integrative and holistic approach to address these pressing issues, enhancing and elevating the whole EV ownership experience by combining Electric Vehicle Health Monitoring (EVHM) with Electric Vehicle Range Prediction (EVRP) and Route Planning (EVRP). Combining these three essential elements creates an all-encompassing plan created to not only lessen these enormous obstacles but also accelerate the switch to electric vehicles by giving consumers the knowledge and assurance they require for a smooth, eco-friendly, and sustainable mobility in the future.

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Section: Loss Function and Optimizationmentioning

confidence: 99%

Electric Vehicle Health Monitoring with Electric Vehicle Range Prediction and Route Planning

Jayaram,

Chetan,

Nayak

2024

JIWE

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“…The driving time on each trip can be obtained according to the U.S. Bureau of Public Roads (BPR) function [43] as ().

\begin{equation}{t}_a = {t}_{0a}\left[ {1 + 0.15{{\left( {\frac{{{x}_a}}{{{c}_a}}} \right)}}^{0.14}} \right]\end{equation}

where t 0 a is the EV driving time with zero traffic flow, x a is the real‐time traffic flow, and c a is the road capacity.…”

Section: Modelling Restoration Capacity Of Bssmentioning

confidence: 99%

“…The driving time on each trip can be obtained according to the U.S. Bureau of Public Roads (BPR) function [43] as (2).…”

Section: Ev Battery Swapping Demandmentioning

confidence: 99%

Service restoration for resilient distribution system with coordination of battery swapping stations and distributed generations

Guo

Liao

Yang

et al. 2022

IET Renewable Power Gen

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Due to sufficient energy storage resources and central dispatch, the battery swapping station (BSS) offers a promising solution for the service restoration and resilience enhancement of the distribution system (DS). This paper proposes a joint service restoration strategy for the DS by coordinating BSSs and distributed generations (DGs) with distribution network reconfiguration. Firstly, the spatio-temporal distribution of battery swapping demand for electric vehicles (EVs) is analyzed. On this basis, the participation of the BSS in the DS service restoration is investigated, and the model of restoration capacity for the BSS is established, which can describe the power supply ability of the BSS to support the DS restoration. Secondly, a mathematical model for the resilient DS restoration with coordination between BSSs and DGs is established, aiming to minimize the total system cost by optimally allocating BSSs and DGs during the restoration stage. The second-order cone programming (SOCP) relaxation is also adopted to transform the proposed restoration model into a mixed-integer convex formulation, which can be tractably solved. Finally, numerical simulations are conducted based on the modified IEEE 33-bus distribution test system. The results demonstrate the effectiveness of the proposed strategy for the service restoration and resilience enhancement of the DS.

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Blockchain‐based electric vehicle charging reservation scheme for optimum pricing

Tanwar

Kakkar

Gupta

et al. 2022

Intl J of Energy Research

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Summary The adaptation of intelligent transportation system has evolved the quality of life of people with the huge demand for electric vehicles. Moreover, it becomes essential to schedule an electric vehicle for charging optimally. Therefore, this paper proposes a blockchain‐based electric vehicle charging reservation scheme for optimum pricing. It primarily aims to secure data transactions between electric vehicles and charging stations. It uses the communication channel as 5G to ensure ultra‐low latency and extremely high reliability. Furthermore, the proposed scheme uses a double‐auction mechanism to optimize the payoff for both electric vehicles and charging stations. The performance of the proposed scheme is evaluated by distinguishing it from the conventional networks such as 4G and LTE‐A. The performance parameters are considered profit and loss for electric vehicles, scalability, cost overhead for data storage, communication overhead for data transactions, and data storage cost. Results show that the proposed scheme is secure and achieves the optimized payoff for electric vehicles and charging stations compared with traditional approaches.

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Planning Strategy for an Electric Vehicle Fast Charging Service Provider in a Competitive Environment

Cited by 35 publications

References 30 publications

Electric Vehicle Health Monitoring with Electric Vehicle Range Prediction and Route Planning

Electric Vehicle Health Monitoring with Electric Vehicle Range Prediction and Route Planning

Service restoration for resilient distribution system with coordination of battery swapping stations and distributed generations

Blockchain‐based electric vehicle charging reservation scheme for optimum pricing

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