ACN-Sim: An Open-Source Simulator for Data-Driven Electric Vehicle Charging Research

Lee, Zachary J.; Sharma, Sunash; Johansson, Daniel; Low, Steven H.

doi:10.1109/tsg.2021.3103156

Cited by 17 publications

(5 citation statements)

References 27 publications

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“…The prestage rectifier corrects the power factor, and the post-stage DC/DC converter controls the charging power and voltage isolation. Therefore, the working efficiency of the post-stage DC/DC converter determines the overall performance of the DC/DC charger [31], [32], [33], [34], [35]. The DC/DC converter controlled by the traditional pulse width modulation method belongs to the hard switching type, that is, the voltage and current at both ends of the switch tube are not zero during the conduction and shutdown, and there is a cross between the two [36], [37], [38], [39].…”

Section: Design and Loss Analysis Of Fast Charging Optimization Circu...mentioning

confidence: 99%

DC Charger Circuit Optimization Design and Fast Charging and Discharging Mechanism Research

Shen,

Yan,

Zhou

et al. 2023

IEEE Access

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With the advent of the era of new energy vehicles, the layout of charging piles is slightly lagging behind, and the charging efficiency of chargers is uneven, which leads to the problems of difficult charging and long charging time of electric vehicles. Therefore, market users put forward higher requirements for the charging efficiency of chargers. This paper first analyzes the circuit design principle and loss of the traditional charger, then designs a zero voltage switch(ZVS) half-bridge three-level DC/DC converter with high charging efficiency, and proposes a multi-stage constant current limiting charging strategy. Finally, through simulation and experimental verification, it is proved that the proposed strategy can strengthen the voltage regulation ability of the charger, and can achieve a stable current sharing state when charging.INDEX TERMS Circuit design, charging strategy, DC/DC charger, working loss.

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Section: Design and Loss Analysis Of Fast Charging Optimization Circu...mentioning

confidence: 99%

DC Charger Circuit Optimization Design and Fast Charging and Discharging Mechanism Research

Shen,

Yan,

Zhou

et al. 2023

IEEE Access

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“…Remark 1. Metrics used in industry for imbalance can be found in the IEEE standard [1]; a first proposal is precisely the left-hand side of (7). A different metric attributed to ANSI is to consider deviations of each magnitude with respect to the average; this is connected to the approach above because one can readily show that 𝑃𝑔 = 𝑔 − ḡ1, where ḡ = (𝜌 𝑎 + 𝜌 𝑎 + 𝜌 𝑎 )/3 is the average of the load magnitudes.…”

Section: Quantifying Imbalancementioning

confidence: 99%

“…Then in Section 3 we explain the analytical basis for the imbalance cost to include. An online optimization strategy that incorporates this metric is described in Section 4 and tested using the ACN simulation platform [7]. Conclusions are given in Section 5.…”

mentioning

confidence: 99%

Symmetrical components analysis for managing phase imbalance in EV charge scheduling

Acuña

Ferragut

Paganini

et al. 2022

Proceedings of the Thirteenth ACM International Conference on Future Energy Systems

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This paper studies the scenario of an EV charging facility in which scheduling is used to manage the overall power consumption profile. We address the concern of a possible imbalance in the resulting 3-phase load, due to an uneven EV loading of the different phases. We apply symmetrical component analysis to develop metrics that capture this imbalance in a convex fashion in the natural problem variables, namely individual EV charging rates. We incorporate this metric into an online optimization for EV scheduling, and test in a scenario from the Caltech Adaptive Charging Network; simulations demonstrate this method is able to improve phase balance with a minimal impact on the service provided to the EV customers. CCS CONCEPTS• Networks → Network performance analysis; • Applied computing → Mathematics and statistics; Engineering.

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“…It employed deep neural networks to analyze and predict EV charging behavior, which was also described in [43]. In [44], a data-driven simulator was designed to help with the implementation of online scheduling algorithms for EV charging. This tool significantly reduces the software programming burden on researchers and exposes them to practical EV charging issues.…”

Section: Introductionmentioning

confidence: 99%

Optimum Scenarios of EV Charging Infrastructure: A Case Study for the Saudi Arabia Market

Azab

2023

Energies

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The lack of an EV charging infrastructure is of the top five barriers preventing the adoption of EVs on a large scale. A long charging time is also one of the five barriers, according to the latest survey published by the IEA in 2021. The estimated increase in demand for EVs is a big challenge in many countries all around the world. This challenge exists in many EU and Middle East countries. The main reason for this problem is the requirement of huge funds to install enough public charging points that result in satisfactory charging services. Hence, the phase-out plans of internal combustion engine (ICE) vehicles can be carried out successfully and smoothly. Unfortunately, there is a trade-off between the cost of installing charging points and EV charging time. Therefore, it is important to optimize both factors simultaneously. This way, the charging services can be provided at the minimum possible cost and at a satisfactory level of quality. This study determines the optimum ratio of the number of chargers to the number of EVs in a certain province. The optimal number of chargers that are necessary to optimally serve a certain number of EVs has been determined. Two well-known evolutionary search techniques have solved the optimization problem: particle swarm optimization (PSO) and genetic algorithms (GA). Both algorithms have succeeded in providing many optimal charging infrastructure scenarios. Hence, the decision maker can select the most convenient scenario from several alternatives based on the available budgets and the most convenient charging time.

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ACN-Sim: An Open-Source Simulator for Data-Driven Electric Vehicle Charging Research

Cited by 17 publications

References 27 publications

DC Charger Circuit Optimization Design and Fast Charging and Discharging Mechanism Research

DC Charger Circuit Optimization Design and Fast Charging and Discharging Mechanism Research

Symmetrical components analysis for managing phase imbalance in EV charge scheduling

Optimum Scenarios of EV Charging Infrastructure: A Case Study for the Saudi Arabia Market

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