Sigma-Modified Power Control and Parametric Adaptation in a Grid-Integrated PV for EV Charging Architecture

Mishra, Debasish; Singh, Birender; Panigrahi, Bijaya Ketan

doi:10.1109/tec.2022.3145884

Cited by 21 publications

(6 citation statements)

References 24 publications

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“…The optimal operational model is not specific to any particular hardware or software. In fact, there are multiple hardware and software alternatives available in literature, for instance, vehicle recognition [36], routing [37], automatic plugin [38], communication [39], charging control [40], etc. Note the operational model focuses on the energy management level.…”

Section: Discussionmentioning

confidence: 99%

Robo-Chargers: Optimal Operation and Planning of a Robotic Charging System to Alleviate Overstay

Zeng

Allybokus

et al. 2024

IEEE Trans. Smart Grid

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Charging infrastructure availability is a major concern for plug-in electric vehicle users. Nowadays, the limited public chargers are commonly occupied by vehicles which have already been fully charged. Such phenomenon, known as overstay, hinders other vehicles' accessibility to charging resources. In this paper, we analyze a charging facility innovation to tackle the challenge of overstay, leveraging the idea of Robo-chargers -automated chargers that can rotate in a charging station and proactively plug or unplug plug-in electric vehicles. We formalize an operation model for stations incorporating Fixedchargers and Robo-chargers. Optimal scheduling can be solved with the recognition of the combinatorial nature of vehiclecharger assignments, charging dynamics, and customer waiting behaviors. Then, with operation model nested, we develop a planning model to guide economical investment on both types of chargers so that the total cost of ownership is minimized. In the planning phase, it further considers charging demand variances and service capacity requirements. In this paper, we provide systematic techno-economical methods to evaluate if introducing Robo-chargers is beneficial given a specific application scenario. Comprehensive sensitivity analysis based on real-world data highlights the advantages of Robo-chargers, especially in a scenario where overstay is severe. Validations also suggest the tractability of operation model and robustness of planning results for real-time application under reasonable model mismatches, uncertainties and disturbances.

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Section: Discussionmentioning

confidence: 99%

Robo-Chargers: Optimal Operation and Planning of a Robotic Charging System to Alleviate Overstay

Zeng

Allybokus

et al. 2024

IEEE Trans. Smart Grid

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“…Solar PV panels have been installed rapidly, are more affordable at low cost, and EV batteries can be used to store energy for solar PV as they can consume a large amount of Solar PV energy [122], [123]. Many researchers have discovered that coordinate operation of PVs and EVs can decrease impacts encountered by individual PV and EV integration on the power grid [124]. However, the integration of EVs and RESs into the grid is a challenge due to the additional planning stages, converters, and control strategies needed to be considered in this type of charging station.…”

Section: Renewable Energy Integrated Charging Stationmentioning

confidence: 99%

Review of Electric Vehicle Charging Technologies, Standards, Architectures, and Converter Configurations

et al. 2023

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Electric Vehicles (EVs) are projected to be one of the major contributors to energy transition in global transportation due to their rapid expansion. High-level of EVs integration into the electricity grid will introduce many challenges for the power grid planning, operation, stability, standards, and safety. Therefore, the wide-scale adoption of EVs imposes research and development of charging systems and EV supply equipment (EVSE) to achieve expected charging solutions for EV batteries as well as to improve ancillary services. Analysis of the status of EV charging technologies is important to accelerate EV adoption with advanced control strategies to discover a remedial solution for negative impacts and to enhance desired charging efficiency and grid support. This paper presents a comprehensive review of EV charging technologies, international standards, the architecture of EV charging stations, and the power converter configurations of EV charging systems. The charging systems require a dedicated converter topology, a control strategy, compatibility with standards, and grid codes for charging and discharging to ensure optimum operation and enhance grid support. An overview of different charging systems in terms of onboard and offboard chargers, AC-DC and DC-DC converter configuration, and AC and DC-based charging station architectures are evaluated. In addition, recent charging systems which are integrated with renewable energy sources are presented to identify the power train of modern charging stations. Finally, future trends and challenges in EV charging and grid integration issues are summarized as the future direction of the research.INDEX TERMS Electric vehicle, charging configuration, grid integration, international standards, onboard and offboard charger, power converters.

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“…In Ref. [8], PV and grid jointly supplied EVs' charging demand, meanwhile EV scheduling was set as a benefit maximization problem. With the support of PV and ESS, Ref.…”

Section: Introductionmentioning

confidence: 99%

Multi-Agent System for Electric Vehicle Charging Scheduling in Parking Lots

Tan

Zhang

Ren

et al. 2023

Complex Syst. Model. Simul.

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As the number of electric vehicles (EVs) increases, massive numbers of EVs have started to gather in commercial parking lots to charge and discharge, which may significantly impact the operation of the grid.There may also be a deviation in the departure time of charged and discharged EVs in commercial parking lots.This deviation can lead to insufficient battery energy when the EVs leave the parking lot. This study uses the simulation software AnyLogic to build a commercial parking lot multi-agent simulation model, and the agentbased model can fully reflect the autonomy of individual EVs. Based on this simulation model, we propose an EV scheduling algorithm. The algorithm contains two main agents. The first is the power distribution center agent (PDCA), which is used to coordinate the energy output of photovoltaic (PV), energy storage system (ESS), and distribution station (DS) to solve the problem of grid overload. The second is the scheduling center agent (SCA), which is used to solve the insufficient battery energy problem due to EVs' random departures.The SCA includes two stages. In the first stage, a priority scheduling algorithm is proposed to emphasize the fairness of EV charging. In the second stage, a genetic algorithm is used to accurately determine the time interval between charging and discharging to ensure the maximum benefit of EV owner. Finally, simulation experiments are conducted in AnyLogic, and the results demonstrate the superiority of the algorithm over the classical algorithm.

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Sigma-Modified Power Control and Parametric Adaptation in a Grid-Integrated PV for EV Charging Architecture

Cited by 21 publications

References 24 publications

Robo-Chargers: Optimal Operation and Planning of a Robotic Charging System to Alleviate Overstay

Robo-Chargers: Optimal Operation and Planning of a Robotic Charging System to Alleviate Overstay

Review of Electric Vehicle Charging Technologies, Standards, Architectures, and Converter Configurations

Multi-Agent System for Electric Vehicle Charging Scheduling in Parking Lots

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