A hybrid robust-stochastic approach for the day-ahead scheduling of an EV aggregator

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

Uittreksel

Electric Vehicles (EVs) are emerging among the Distributed Energy Resources (DERs) as a promising flexibility source. The small-scale of DERs still constitutes a barrier to their direct participation in electricity markets. Aggregators can exploit EV smart charging to lower the energy procurement cost in the day-ahead (DA) scheduling phase. This cost minimization should consider the uncertainty stemming from the availability of EVs, the DA and the imbalance market prices. To catch all these uncertainties, a novel approach combining robust optimization and stochastic programming is proposed to define the DA charging schedule for an EV fleet, considering the DA market prices and the possible imbalance realizations in real-time. This method is compared with a two-stage stochastic (TSS) programming approach and with the EV uncontrolled charging. Two weeks of data from the DA spot market in the Netherlands have been used for comparing the methods with different fleet sizes: 100, 200 and 400 EVs. The results show that the hybrid robust-stochastic method, while keeping approximately the same average DA energy cost, can estimate better than the TSS method the actual daily energy cost with reduced computational time.

TaalEngels
Titel2019 IEEE Milan PowerTech, PowerTech 2019
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Aantal pagina's6
ISBN van elektronische versie978-1-5386-4722-6
DOI's
StatusGepubliceerd - 1 jun 2019
Evenement2019 IEEE Milan PowerTech, PowerTech 2019 - Milan, Italië
Duur: 23 jun 201927 jun 2019

Congres

Congres2019 IEEE Milan PowerTech, PowerTech 2019
LandItalië
StadMilan
Periode23/06/1927/06/19

Vingerafdruk

Electric vehicles
Scheduling
Stochastic programming
Energy resources
Costs
Availability

Trefwoorden

    Citeer dit

    Minniti, S., Haque, A. N. M. M., Paterakis, N. G., & Nguyen, P. H. (2019). A hybrid robust-stochastic approach for the day-ahead scheduling of an EV aggregator. In 2019 IEEE Milan PowerTech, PowerTech 2019 [8810412] Piscataway: Institute of Electrical and Electronics Engineers. DOI: 10.1109/PTC.2019.8810412
    Minniti, Simone ; Haque, A.N.M.M. ; Paterakis, N.G. ; Nguyen, P.H./ A hybrid robust-stochastic approach for the day-ahead scheduling of an EV aggregator. 2019 IEEE Milan PowerTech, PowerTech 2019. Piscataway : Institute of Electrical and Electronics Engineers, 2019.
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    title = "A hybrid robust-stochastic approach for the day-ahead scheduling of an EV aggregator",
    abstract = "Electric Vehicles (EVs) are emerging among the Distributed Energy Resources (DERs) as a promising flexibility source. The small-scale of DERs still constitutes a barrier to their direct participation in electricity markets. Aggregators can exploit EV smart charging to lower the energy procurement cost in the day-ahead (DA) scheduling phase. This cost minimization should consider the uncertainty stemming from the availability of EVs, the DA and the imbalance market prices. To catch all these uncertainties, a novel approach combining robust optimization and stochastic programming is proposed to define the DA charging schedule for an EV fleet, considering the DA market prices and the possible imbalance realizations in real-time. This method is compared with a two-stage stochastic (TSS) programming approach and with the EV uncontrolled charging. Two weeks of data from the DA spot market in the Netherlands have been used for comparing the methods with different fleet sizes: 100, 200 and 400 EVs. The results show that the hybrid robust-stochastic method, while keeping approximately the same average DA energy cost, can estimate better than the TSS method the actual daily energy cost with reduced computational time.",
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    Minniti, S, Haque, ANMM, Paterakis, NG & Nguyen, PH 2019, A hybrid robust-stochastic approach for the day-ahead scheduling of an EV aggregator. in 2019 IEEE Milan PowerTech, PowerTech 2019., 8810412, Institute of Electrical and Electronics Engineers, Piscataway, Milan, Italië, 23/06/19. DOI: 10.1109/PTC.2019.8810412

    A hybrid robust-stochastic approach for the day-ahead scheduling of an EV aggregator. / Minniti, Simone; Haque, A.N.M.M.; Paterakis, N.G.; Nguyen, P.H.

    2019 IEEE Milan PowerTech, PowerTech 2019. Piscataway : Institute of Electrical and Electronics Engineers, 2019. 8810412.

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

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    AU - Paterakis,N.G.

    AU - Nguyen,P.H.

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    N2 - Electric Vehicles (EVs) are emerging among the Distributed Energy Resources (DERs) as a promising flexibility source. The small-scale of DERs still constitutes a barrier to their direct participation in electricity markets. Aggregators can exploit EV smart charging to lower the energy procurement cost in the day-ahead (DA) scheduling phase. This cost minimization should consider the uncertainty stemming from the availability of EVs, the DA and the imbalance market prices. To catch all these uncertainties, a novel approach combining robust optimization and stochastic programming is proposed to define the DA charging schedule for an EV fleet, considering the DA market prices and the possible imbalance realizations in real-time. This method is compared with a two-stage stochastic (TSS) programming approach and with the EV uncontrolled charging. Two weeks of data from the DA spot market in the Netherlands have been used for comparing the methods with different fleet sizes: 100, 200 and 400 EVs. The results show that the hybrid robust-stochastic method, while keeping approximately the same average DA energy cost, can estimate better than the TSS method the actual daily energy cost with reduced computational time.

    AB - Electric Vehicles (EVs) are emerging among the Distributed Energy Resources (DERs) as a promising flexibility source. The small-scale of DERs still constitutes a barrier to their direct participation in electricity markets. Aggregators can exploit EV smart charging to lower the energy procurement cost in the day-ahead (DA) scheduling phase. This cost minimization should consider the uncertainty stemming from the availability of EVs, the DA and the imbalance market prices. To catch all these uncertainties, a novel approach combining robust optimization and stochastic programming is proposed to define the DA charging schedule for an EV fleet, considering the DA market prices and the possible imbalance realizations in real-time. This method is compared with a two-stage stochastic (TSS) programming approach and with the EV uncontrolled charging. Two weeks of data from the DA spot market in the Netherlands have been used for comparing the methods with different fleet sizes: 100, 200 and 400 EVs. The results show that the hybrid robust-stochastic method, while keeping approximately the same average DA energy cost, can estimate better than the TSS method the actual daily energy cost with reduced computational time.

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    Minniti S, Haque ANMM, Paterakis NG, Nguyen PH. A hybrid robust-stochastic approach for the day-ahead scheduling of an EV aggregator. In 2019 IEEE Milan PowerTech, PowerTech 2019. Piscataway: Institute of Electrical and Electronics Engineers. 2019. 8810412. Beschikbaar vanaf, DOI: 10.1109/PTC.2019.8810412