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    Submitted manuscript, 2 MB, PDF-document

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DOI

In power systems, demand and supply always have to be balanced. This is becoming more challenging due to the sustained penetration of renewable energy sources. Because of the increasing amount of electrical vehicles (EVs), and the high capacity and flexibility of their charging process, EVs are a good candidate for providing balancing services to electric systems. We propose a stochastic optimization method for an EV aggregator that models the uncertainty of the imbalance price, the reserve prices and the probability of acceptance and deployment of reserves. The model results in an optimal charging and discharging strategy considering day-ahead purchase, imbalance trading and reserve bids. Unlike previous studies, the reserve bids consists of both a quantity and an optimal price. Experimental evaluation shows that the proposed stochastic optimization method results in lower costs than deterministic and quantity-only bid solutions.
Original languageEnglish
Title of host publicationProceedings of the 15th International Conference on the European Energy Market, EEM 2018
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages1-5
Number of pages5
ISBN (Electronic)978-1-5386-1488-4
DOIs
Publication statusPublished - 2018
EventEEM 2018: 15th International Conference on the European Energy Market - Łódź, Poland
Duration: 27 Jun 201829 Jun 2018
Conference number: 15
http://www.eem18.eu/

Conference

ConferenceEEM 2018
Abbreviated titleEEM 18
CountryPoland
City Łódź
Period27/06/1829/06/18
Internet address

    Research areas

  • Electrical vehicles, stochastic opti-mization, reserve markets, day-ahead markets, mixed integer programming

ID: 45434700