A Stochastic Model Based on Markov Chain to Support Vehicle-to-Grid (V2G) Operation in Smart Distribution Network

Hampannavar, Santoshkumar; Yaragatti, Udaykumar R.; Chavhan, Suresh

doi:10.1515/ijeeps-2018-0347

Cited by 3 publications

(1 citation statement)

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“…Also, the mass adoption of EVs mandates a robust charging infrastructure, communication infrastructure between EVs [3]- [5] and charging stations [3]- [5], and highlights the necessity to build a communication infrastructure between a dedicated aggregator and grid [6], [7]. Managing power transaction processes of EVs because of the varying demands and highly intermittent renewable energy sources penetration at different periods will be a major challenge [22], [25].…”

Section: Introductionmentioning

confidence: 99%

Next-Generation Smart Electric Vehicles Cyber Physical System for Charging Slots Booking in Charging Stations

Chavhan

Dubey²,

Lal³

et al. 2020

IEEE Access

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Owing to the increased worldwide awareness regarding pollution caused by the consumption of fossil fuels, Battery-powered vehicles are bound to take over the conventional Internal Combustion Engine. Keeping the difficulties faced by the economy of the city and the populace of adapting to an entirely grid-run charging infrastructure in mind, a framework incorporating electric vehicles to everything (EV2X) communication and Charge Slot booking based on data got from a survey conducted has been developed in this literature. The conclusions drawn from the survey develop key insights into developing statisticorating the use of LTE to support the conventional OCPP and promote user controlal models that are further explored in this context. Algorithms and strategies to implement next-generation efficient EV2X communications have been implemented and developed for the city. Further, we have established a priority order for slot booking and incorp over charge-cycles. Introducing IPMUs using an LTE connection to act as a supplement to the conventional OCPP is explored in this context. Besides that, we have built the M/M/m queuing model of EVs in the charging station and its optimisation. We have done the exhaustive evaluation of the robustness of the proposed system in a fairly large-scale network in a discrete-time event simulator. The proposed system's results (simulation, analytical, and comparison) show the reduction of waiting time, good accuracy, and saving of charging time and costs. These performances measures improve shows the real-time applicability of the proposed system.

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