Potential of vehicle-to-grid ancillary services considering the uncertainties in plug-in electric vehicle availability and service/localization limitations in distribution grids

Sarabi, Siyamak; Davigny, Arnaud; Courtecuisse, V.; Riffonneau, Yann; Robyns, Benoît

doi:10.1016/j.apenergy.2016.03.064

Cited by 85 publications

(46 citation statements)

References 45 publications

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“…Information gap decision theory (IGDT) is applied to handle the uncertainties of microgrid and solved by MILP framework. Many other type of uncertainty handling method such as robust, fuzzy, scenario based, linearization based, unscented transform, probabilistic, possibilistic Monte Carlo, Gaussian mixture model, estimation distribution, and stochastic inventory theory are also proposed by researchers to model uncertainties in an EMS. Selection of appropriate method to handle uncertainty is required in the power system to avoid a large gap between supply and demand.…”

Section: Factors To Be Considered For Ems Implementationmentioning

confidence: 99%

Energy management system for smart grid: An overview and key issues

2020

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Summary Energy crisis and the global impetus to “go green” have encouraged the integration of renewable energy resources, plug‐in electric vehicles, and energy storage systems to the grid. The presence of more than one energy source in the grid necessitates the need for an efficient energy management system to guide the flow of energy. Moreover, the variability and volatile nature of renewable energy sources, uncertainties associated with plug‐in electric vehicles, the electricity price, and the time‐varying load bring new challenges to the power engineers to achieve demand‐supply balance for stable operation of the power system. The energy management system can effectively coordinate the energy sharing/trading among all available energy resources, and supply loads economically in all the conditions for the reliable, secure, and efficient operation of the power system. This paper reviews the framework, objectives, architecture, benefits, and challenges of the energy management system with a comprehensive analysis of different stakeholders and participants involved in it. The review paper gives a critical analysis of the distributed energy resources behavior and different programs such as demand response, demand‐side management, and power quality management implemented in the energy management system. Different uncertainty quantification methods are also summarized. This review paper also presents a comparative and critical analysis of the main optimization techniques used to achieve different energy management system objectives while satisfying multiple constraints. Thus, the review offers numerous recommendations for research and development of the cutting‐edge optimized energy management system applicable for homes, buildings, industries, electric vehicles, and the whole community.

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Section: Factors To Be Considered For Ems Implementationmentioning

confidence: 99%

Energy management system for smart grid: An overview and key issues

2020

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“…The authors develop a classification of different methods for the smart charging of EVs without focusing on EV-DSS. In [19], the feasibilities of certain services are evaluated for EVs in an aggregated mode, enabling DSOs to provide ancillary services for TSOs. In [20] and [21], the authors assess the framework, benefits, and challenges of vehicle-to-grid (V2G) technology and conduct a review of optimization techniques.…”

Section: Distribution System Services Provided By Electric Vehicles: mentioning

confidence: 99%

“…Similarly, in [18], peak load reduction and power loss services are considered in the congestion prevention category. The authors in [19] classify peak power shaving and voltage regulation for both medium and low voltage networks. The authors also propose an ancillary service called balancing mechanism, which is also found in the literature as a tertiary reserve [32].…”

Section: Overview Of Traditional Classifications Of Ev Services Imentioning

confidence: 99%

Distribution System Services Provided by Electric Vehicles: Recent Status, Challenges, and Future Prospects

Arias

Hashemi

Andersen

et al. 2019

IEEE Trans. Intell. Transport. Syst.

128

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Trend-setting countries have promoted or even employed an increased number of electric vehicles (EVs) and other distributed energy resources (DERs) in their power systems. This development has triggered new and increasing challenges in the distribution system planning and operation, whereby distribution systems must adapt to the increased share of DERs. However, EVs may also offer new opportunities and can be used to support the grid by providing several local and global powerand energy-based services. This paper presents a review and classification of the services potentially available from EVs for distribution systems, referred to as EV distribution system services (EV-DSS). A detailed description of recent services and approaches is given, and an assessment of the maturity of EV-DSS is provided. Moreover, challenges and prospects for future research are identified, considering key topics, such as the design of the market framework, economic assessment, battery degradation, and the impacts of the transmission system operator service provision by EVs on distribution networks. Thus, this work offers a tool for stakeholders concerning services available from EVs and provides a broad literature framework that can be used as a base for further investigations. It is aligned with the current requirements to move toward realistic implementations of EV-DSS.

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“…The resulting data is listed in Table II. The (statistical) relative frequency of the initial SOC is estimated on the base of the traveling distance, as in [17]. We assume an autonomy of 280km with full charge and that each v-th PEV charges only at the DCS, up to e min v .…”

Section: A Test Casementioning

confidence: 99%

Reliable Dispatch of Renewable Generation via Charging of Time-Varying PEV Populations

Appino

Munoz-Ortiz

Ordiano

et al. 2019

IEEE Trans. Power Syst.

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The inherent storage of plug-in electric vehicles is likely to foster the integration of intermittent generation from renewable energy sources into existing power systems. In the present paper, we propose a three-stage scheme to the end of achieving dispatchability of a system composed of plug-in electric vehicles and intermittent generation. The main difficulties in dispatching such a system are the uncertainties inherent to intermittent generation and the time-varying aggregation of vehicles. We propose to address the former by means of probabilistic forecasts and we approach the latter with separate stagespecific models. Specifically, we first compute a dispatch schedule, using probabilistic forecasts together with an aggregated dynamic model of the system. The power output of the single devices are set subsequently, using deterministic forecasts and device-specific models. We draw upon a simulation study based on real data of generation and vehicle traffic to validate our findings.Index Terms-dispatch schedule, plug-in electric vehicle, probabilistic forecasting, renewable energy, stochastic programming, dynamic aggregation of energy storage All authors are with the

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Potential of vehicle-to-grid ancillary services considering the uncertainties in plug-in electric vehicle availability and service/localization limitations in distribution grids

Cited by 85 publications

References 45 publications

Energy management system for smart grid: An overview and key issues

Energy management system for smart grid: An overview and key issues

Distribution System Services Provided by Electric Vehicles: Recent Status, Challenges, and Future Prospects

Reliable Dispatch of Renewable Generation via Charging of Time-Varying PEV Populations

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