Optimum day-ahead bidding profiles of electrical vehicle charging stations in FCR markets
Year of publication
2021
Authors
Astero, Poria; Evens, Corentin
Abstract
This research developed an application for electrical vehicles charging stations (EVCS) to estimate the optimum day-ahead bidding profiles in frequency containment reserves (FCR) markets and this paper presents the stochastic methodology behind this application. To achieve this, first, deterministic models are developed to calculate the maximum FCR that could be provided by each charging event (cycle) of an electric vehicle (EV). These models are established based on the technical requirements of FCR in the Nordic flexibility market, namely the frequency containment reserve for normal operation (FCR-N) and frequency containment reserve for disturbances (FCR-D). In the next step, these deterministic models will be combined with historical data of charging records in EVCS to calculate the probability density functions of the FCR profiles. Finally, the proposed application estimates the optimum FCR profiles, which maximise the expected profit of EVCS from participating in the day-ahead flexibility market, by performing a stochastic optimisation. The performance of the proposed application is evaluated by using empirical charging data of public EVCS in Helsinki area.
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Publication type
Publication format
Article
Parent publication type
Journal
Article type
Original article
Audience
ScientificPeer-reviewed
Peer-ReviewedMINEDU's publication type classification code
A1 Journal article (refereed), original researchPublication channel information
Journal
Volume
190
Article number
106667
ISSN
Publication forum
Publication forum level
2
Open access
Open access in the publisher’s service
Yes
Open access of publication channel
Partially open publication channel
License of the publisher’s version
CC BY
Self-archived
No
Article processing fee (EUR)
1080
Year of payment for the open publication fee
2021
Other information
Fields of science
Electronic, automation and communications engineering, electronics; Environmental engineering
Keywords
[object Object],[object Object],[object Object],[object Object]
Language
English
International co-publication
No
Co-publication with a company
No
DOI
10.1016/j.epsr.2020.106667
The publication is included in the Ministry of Education and Culture’s Publication data collection
Yes