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AuthorRaoofat, M.
AuthorRaoofat, M.
AuthorSaad, M.
AuthorLefebvre, S.
AuthorAsber, D.
AuthorMehrjedri, H.
AuthorLenoir, L.
Available date2019-09-11T11:08:31Z
Publication Date2018-07-01
Publication NameInternational Journal of Electrical Power and Energy Systemsen_US
CitationRaoofat, M., Saad, M., Lefebvre, S., Asber, D., Mehrjedri, H., & Lenoir, L. (2018). Wind power smoothing using demand response of electric vehicles. International Journal of Electrical Power & Energy Systems, 99, 164-174.‏
Abstract© 2018 Elsevier Ltd Large penetrations of wind power is prevented in most power systems, mainly because it is highly stochastic. One important aspect of this uncertainty is the large power gradients that wind farms may impose to the grid. To mitigate such undesirable fluctuations, this paper proposes a power smoothing service using the demand response of electric vehicles connected to the adjacent networks. A hierarchical controller is proposed, in which the top layer calculates the ramp rate and sends a request signal to all participant vehicles. In the second layer, a fuzzy controller is developed introducing two fuzzy indices that measure how ready each vehicle is to participate in mitigating large positive and negative fluctuations. These indices are inferred from the state-of-charge and time-to-departure of the vehicle, and are used as the participation factors of the vehicle to provide this service. As much as possible, the proposed controller tries to supply the required service by controlling the vehicles charging load instead of using V2G, which wears out their expensive batteries. Numerical studies on microgrids with high penetrations of wind power corroborate the success of the proposed algorithm in limiting the power fluctuations as well as charging the vehicles in proper time.
PublisherElsevier Ltd
SubjectDemand Response (DR)
SubjectElectric Vehicle (EV)
SubjectFuzzy control
SubjectRamp rate limit
SubjectRamp rate limiting service
SubjectWind power smoothing
TitleWind power smoothing using demand response of electric vehicles
Volume Number99
elsevier.identifier.scopusid SCOPUS_ID:85041474540

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