TY - JOUR
T1 - Stochastic bidding strategy for electrical vehicle charging stations to participate in frequency containment reserves markets
AU - Astero, Poria
AU - Evens, Corentin
PY - 2020/7/3
Y1 - 2020/7/3
N2 - This study presents a stochastic bidding strategy for electrical vehicle charging stations (EVCSs) to participate in frequency containment reserves (FCRs) markets. To achieve this, the study starts by developing deterministic models to calculate the maximum FCR that could be provided by each charging event (cycle) of an electric vehicle. These models are established based on the technical requirements of FCR in the Nordic flexibility market, namely the frequency containment reserve for normal operation and frequency containment reserve for disturbances. These deterministic models will be combined with historical data of charging records in EVCS to develop a methodology to calculate the probability density functions of the FCR profiles. Finally, the optimum FCR profiles, which maximise the expected profit of EVCS from participating in the dayahead flexibility market, are estimated by performing a stochastic optimisation. The proposed methodology is evaluated by using empirical charging data of public EVCS in the Helsinki area.
AB - This study presents a stochastic bidding strategy for electrical vehicle charging stations (EVCSs) to participate in frequency containment reserves (FCRs) markets. To achieve this, the study starts by developing deterministic models to calculate the maximum FCR that could be provided by each charging event (cycle) of an electric vehicle. These models are established based on the technical requirements of FCR in the Nordic flexibility market, namely the frequency containment reserve for normal operation and frequency containment reserve for disturbances. These deterministic models will be combined with historical data of charging records in EVCS to develop a methodology to calculate the probability density functions of the FCR profiles. Finally, the optimum FCR profiles, which maximise the expected profit of EVCS from participating in the dayahead flexibility market, are estimated by performing a stochastic optimisation. The proposed methodology is evaluated by using empirical charging data of public EVCS in the Helsinki area.
UR - http://www.scopus.com/inward/record.url?scp=85086425638&partnerID=8YFLogxK
U2 - 10.1049/iet-gtd.2019.0906
DO - 10.1049/iet-gtd.2019.0906
M3 - Article
AN - SCOPUS:85086425638
SN - 1751-8687
VL - 14
SP - 2566
EP - 2572
JO - IET Generation, Transmission and Distribution
JF - IET Generation, Transmission and Distribution
IS - 13
ER -