V2G for Reliable Microgrid Operations: Voltage/Frequency Regulation with Virtual Inertia Emulation

Dinkhah, Saleh; Negri, Cesar A.; He, Miao; Bayne, Stephen

doi:10.1109/itec.2019.8790615

Cited by 24 publications

(32 citation statements)

References 11 publications

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“…Wang et al [20] introduced a rewarding scheme based on blockchain, which could encourage the willingness for V2G adoption. Increased percentage penetrations of wind and solar will underpin a greater need for V2G to both optimise the integration of these resources and to balance frequency disturbances created from their variability in a generation [21][22][23]. According to Navigant Research, frequency regulation revenue will reach $190.7 million by 2022 [24].…”

Section: Introductionmentioning

confidence: 99%

Cloud-Based Big Data Platform for Vehicle-to-Grid (V2G)

Grée¹,

Laznikova²,

Kim³

et al. 2020

WEVJ

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Battery Electric Vehicles (BEVs) have increasingly become prevalent over the past years. BEVs can be regarded as a grid load and as a way to support the grid (energy buffering), provided this extensive battery usage does not affect the BEV’s performance. Data from both the vehicle and the grid are required for effective Vehicle-to-Grid (V2G) implementation. As such, a cloud-based big data platform is proposed in this paper to exploit these data. Additionally, this study aims to develop smart algorithms, which optimise different factors, including BEV cost of ownership and battery degradation. Dashboards are developed to provide key information to different V2G stakeholders.

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Section: Introductionmentioning

confidence: 99%

Cloud-Based Big Data Platform for Vehicle-to-Grid (V2G)

Grée¹,

Laznikova²,

Kim³

et al. 2020

WEVJ

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“…Accordingly, V2G technology has been proposed as a cost‐effective solution, wherein PEVs can play a role of distributed energy storage system to improve the supply‐demand balance by feeding the electricity back to power grids 9‐13 . In addition, the utilization of V2G technology can also provide ancillary services such as load curve flatting, voltage regulation and frequency regulation 14‐17 …”

Section: Introductionmentioning

confidence: 99%

“…[9][10][11][12][13] In addition, the utilization of V2G technology can also provide ancillary services such as load curve flatting, voltage regulation and frequency regulation. [14][15][16][17]…”

mentioning

confidence: 99%

A centralized vehicle‐to‐grid scheme with distributed computing capacity engaging internet of smart charging points: Case study

et al. 2020

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In order to accommodate additional plug-in electric vehicle (PEV) charging loads for existing distribution power grids, the vehicle-to-grid (V2G) technology has been regarded as a cost-effective solution. Nevertheless, it can hardly scale up to large PEVs fleet coordination due to the computational complexity issue. In this paper, a centralized V2G scheme with distributed computing capability engaging internet of smart charging points (ISCP) is proposed. Within ISCP, each smart charging point equips a computing unit and does not upload PEV sensitive information to the energy coordinator, to protect PEV users' privacy. Particularly, the computational complexity can be decreased dramatically by employing distributed computing, viz., by decomposing the overall scheduling problem into many manageable sub-problems. Moreover, six typical V2G scenarios are analyzed deliberately, and based on that, a load peak-shaving and valley-filling scheduling algorithm is built up. The proposed algorithm can be conducted in real-time to mitigate the uncertainties in arrival time, departure time, and energy demand. Finally, the proposed scheme and its algorithm are verified under the distribution grid of the SUSTech campus (China). Compared with uncoordinated charging, the proposed scheme realizes load peak-shaving and valley-filling by 11.98% and 12.68%, respectively. The voltage values are ensured within the limitation range by engaging power flow calculation, in which the minimum voltage values are increasing and the maximum voltage values are decreasing with the expansion of PEV penetration. What is more, the computational complexity of peak-shaving and valley-filling strategy is near-linear, which verifies the proposed scheme can be carried out very efficiently. K E Y W O R D S distributed computing, internet of smart charging points (ISCP), load peak-shaving and valleyfilling, plug-in electric vehicle, vehicle-to-grid

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“…However, due to serious contradictions between limited charging stations and enormous EVs, uncoordinated charging schedules can lead to huge damages to the existing electric grid systems, and make EV drivers suffer from worse QoE (quality of experience) with respect to travelling time, waiting time at CSs (charging stations), charging expense and so forth. In order to solve the above chal-lenges and achieve spatio-temporal accommodated charging services in smart grids [3], [4], for example, choosing the most suitable CSs and charging time for mobile EVs with charging demands, it is indispensable and necessary to establish efficient communications between mobile EVs and distributed CSs, to complete a large number of charging information exchanges, such as current locations of CSs and EVs with low energy levels, required energy amount of EVs, busy situations of CSs, charging decisions and all. The existing centralized cloud-based communication framework [5] is widely utilized in the optimal charging management for EVs, but this solution may lead to the common concerns of privacy and security, and the costs of communication and computation rise exponentially with the increase of EVs.…”

Section: Introductionmentioning

confidence: 99%

An Effective MEC Sustained Charging Data Transmission Algorithm in VANET-Based Smart Grids

Sun

et al. 2020

IEEE Access

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Available charging information exchanges between mobile electric vehicles (EVs) and charging stations are significantly critical in spatio-temporal coordinated charging services introduced by smart girds. In this paper, we propose an efficient information transmission strategy for intelligent charging navigations of enormous moving EVs in large-scale urban environments. Specifically, we firstly design a heterogeneous VANET-based (vehicular ad hoc network) communication framework by means of mobile edge computing concept. In addition, based on the established multi-objective communication optimization problem, we propose an effective charging information dissemination algorithm between mobile edge computing servers and moving EVs. Moreover, in order to further increase charging information delivery efficiency and reduce redundant overheads, an improved local relaying scheme for charging information is designed on the basis of the formulated waiting time model. Finally, a series of simulation experiments are implemented to demonstrate the excellence and feasibility of our charging information transmission strategy. INDEX TERMS Charging information transmission, electric vehicles, VANETs.

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V2G for Reliable Microgrid Operations: Voltage/Frequency Regulation with Virtual Inertia Emulation

Cited by 24 publications

References 11 publications

Cloud-Based Big Data Platform for Vehicle-to-Grid (V2G)

Cloud-Based Big Data Platform for Vehicle-to-Grid (V2G)

A centralized vehicle‐to‐grid scheme with distributed computing capacity engaging internet of smart charging points: Case study

An Effective MEC Sustained Charging Data Transmission Algorithm in VANET-Based Smart Grids

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