Distributed Coordination of Electric Vehicles providing V2G Regulation Services

Karfopoulos, Evangelos; Panourgias, Kostas A.; Hatziargyriou, Nikos D.

doi:10.1109/tpwrs.2015.2472957

Cited by 115 publications

(60 citation statements)

References 23 publications

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“…e) Minimize battery degradation: In certain distributed charge-discharge schemes, as in [34], [51], [84], the minimum and maximum SoC are specified to protect the battery from early degradation. In several other schemes such as [18], [34], [55], [71], [85], [86], the cost of battery degradation is included in the objective function of the OP.…”

Section: ) Ev User's Perspective: A) Provision Of Ancillary Servicesmentioning

confidence: 99%

A Survey of Algorithms for Distributed Charging Control of Electric Vehicles in Smart Grid

Nimalsiri

Mediwaththe

Ratnam

et al. 2020

IEEE Trans. Intell. Transport. Syst.

163

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Electric vehicles (EVs) are an eco-friendly alternative to vehicles with internal combustion engines. Despite their environmental benefits, the massive electricity demand imposed by the anticipated proliferation of EVs could jeopardize the secure and economic operation of the power grid. Hence, proper strategies for charging coordination will be indispensable to the future power grid. Coordinated EV charging schemes can be implemented as centralized, decentralized, and hierarchical systems, with the last two, referred to as distributed charging control systems. This paper reviews the recent literature of distributed charging control schemes, where the computations are distributed across multiple EVs and/or aggregators. First, we categorize optimization problems for EV charging in terms of operational aspects and cost aspects. Then under each category, we provide a comprehensive discussion on algorithms for distributed EV charge scheduling, considering the perspectives of the grid operator, the aggregator, and the EV user. We also discuss how certain algorithms proposed in the literature cope with various uncertainties inherent to distributed EV charging control problems. Finally, we outline several research directions that require further attention.

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Section: ) Ev User's Perspective: A) Provision Of Ancillary Servicesmentioning

confidence: 99%

A Survey of Algorithms for Distributed Charging Control of Electric Vehicles in Smart Grid

Nimalsiri

Mediwaththe

Ratnam

et al. 2020

IEEE Trans. Intell. Transport. Syst.

163

View full text Add to dashboard Cite

show abstract

“…In other cases, EVs provide frequency regulation service stimulated by high service price. Hence, a hierarchical game framework is a common approach [210], [211]: both AGs and EVs aim to maximize their revenue while accomplishing the regulation task with price as the control signal in-between. The game framework is usually solved by iterative best response algorithm, and achieve the equilibrium optimality depending on the payoff function formulation.…”

Section: Centralized Controlmentioning

confidence: 99%

Energy and Information Management of Electric Vehicular Network: A Survey

Chen

Wang

Zhang

et al. 2020

IEEE Commun. Surv. Tutorials

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The connected vehicle paradigm empowers vehicles with the capability to communicate with neighboring vehicles and infrastructure, shifting the role of vehicles from a transportation tool to an intelligent service platform. Meanwhile, the transportation electrification pushes forward the electric vehicle (EV) commercialization to reduce the greenhouse gas emission by petroleum combustion. The unstoppable trends of connected vehicle and EVs transform the traditional vehicular system to an electric vehicular network (EVN), a clean, mobile, and safe system. However, due to the mobility and heterogeneity of the EVN, improper management of the network could result in charging overload and data congestion. Thus, energy and information management of the EVN should be carefully studied. In this paper, we provide a comprehensive survey on the deployment and management of EVN considering all three aspects of energy flow, data communication, and computation. We first introduce the management framework of EVN. Then, research works on the EV aggregator (AG) deployment are reviewed to provide energy and information infrastructure for the EVN. Based on the deployed AGs, we present the research work review on EV scheduling that includes both charging and vehicle-to-grid (V2G) scheduling. Moreover, related works on information communication and computing are surveyed under each scenario. Finally, we discuss open research issues in the EVN.

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“…Design of charging facility microgrids [64] Scheduling of distributed generation (DG) units in a charging facility microgrid [71] Control of the ESS in a charging facility microgrid [72] Expremental implementation of a charging facility microgrid [6] Control of the microgrid interaction with V2G technology [73] Schedulling PEVs charging/discharging to minimize the load variance [74] Within the distribution system Design of charging facilities to regulate voltage in distribution system with high PV penetration [75] Design of a smart energy microhub [5] Sizing and sitting of DG units in the distribution system with integrated charging facilities [19,76] PEVs coordination to acheive valley filling concept via V2G technology [77] Investigating the cababilty of V2G enabled PEVs in reactive power compansation [78] The first scheme is to design charging facilities with an on-roof PV system and/or an ESS. The main research problem is to size the PV system and determine the capacity of ESS, which minimize the grid dependency and maximize the utilization of the on-roof PV system.…”

Section: Integration Scheme Research Workmentioning

confidence: 99%

“…PEV users can then sell (discharge) energy to the distribution system with higher prices. A price based coordination mechanism can be used to allocate the PEV charging demand on the valley hours and enabling V2G capability on the peak hours to minimize the load variance [77]. To enable such PEV management structure, a communication system is needed for information exchange between PEV users and the system operator.…”

Section: Integration Scheme Research Workmentioning

confidence: 99%

A Survey on PEV Charging Infrastructure: Impact Assessment and Planning

Abdalrahman

Zhuang

2017

Energies

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Plug-in electric vehicles (PEVs) represent a huge step forward in a green transportation system, contribute in reduction of greenhouse gas emission, and reduce the dependence on fossil fuel. Integration of PEVs into the electric power system will result in a considerable addition to electricity demand. Due to PEV mobility, this demand has a random distribution in space and time among distribution system nodes. Therefore, short term forecast of PEV charging demand is more challenging than that for conventional loads. Assessment of PEV impacts on the power system is essential to mitigate the impairments from PEV loads. Optimal planning of PEV charging infrastructure will promote the penetration rate of PEVs and minimize the negative impacts of PEVs on the electric power distribution system and transportation road network. Design of charging facilities with integrated distributed energy resources (DER) is considered a solution to alleviate strain on the grid, reduce the integration cost with the distribution network and the charging cost. In this paper, we present a comprehensive literature survey on modelling of PEV charging demand, impact assessment approaches and tools, and charging infrastructure planning. Moreover, an overview on charging facility design with integrated DER is given. Some future research directions are identified.

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Distributed Coordination of Electric Vehicles providing V2G Regulation Services

Cited by 115 publications

References 23 publications

A Survey of Algorithms for Distributed Charging Control of Electric Vehicles in Smart Grid

A Survey of Algorithms for Distributed Charging Control of Electric Vehicles in Smart Grid

Energy and Information Management of Electric Vehicular Network: A Survey

A Survey on PEV Charging Infrastructure: Impact Assessment and Planning

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