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Aiming for half gets you to the top: winning PowerTAC 2020

Orfanoudakis Stavros, Kontos Stefanos, Akasiadis Charilaos, Chalkiadakis Georgios

Απλή Εγγραφή


URIhttp://purl.tuc.gr/dl/dias/17A26F7A-A3AC-4EF7-9AA2-3BDB1411EA9C-
Αναγνωριστικόhttps://doi.org/10.1007/978-3-030-82254-5_9-
Αναγνωριστικόhttps://link.springer.com/chapter/10.1007/978-3-030-82254-5_9-
Γλώσσαen-
Μέγεθος16 pagesen
ΤίτλοςAiming for half gets you to the top: winning PowerTAC 2020en
ΔημιουργόςOrfanoudakis Stavrosen
ΔημιουργόςΟρφανουδακης Σταυροςel
ΔημιουργόςKontos Stefanosen
ΔημιουργόςΚοντος Στεφανοςel
ΔημιουργόςAkasiadis Charilaosen
ΔημιουργόςΑκασιαδης Χαριλαοςel
ΔημιουργόςChalkiadakis Georgiosen
ΔημιουργόςΧαλκιαδακης Γεωργιοςel
ΕκδότηςSpringeren
ΠερίληψηThe PowerTAC competition provides a multi-agent simulation platform for electricity markets, in which intelligent agents acting as electricity brokers compete with each other aiming to maximize their profits. Typically, the gains of agents increase as the number of their customers rises, but in parallel, costs also increase as a result of higher transmission fees that need to be paid by the electricity broker. Thus, agents that aim to take over a disproportionately high share of the market, often end up with losses due to being obliged to pay huge transmission capacity fees. In this paper, we present a novel trading strategy that, based on this observation, aims to balance gains against costs; and was utilized by the champion of the PowerTAC-2020 tournament, TUC-TAC. The approach also incorporates a wholesale market strategy that employs Monte Carlo Tree Search to determine TUC-TAC’s best course of action when participating in the market’s double auctions. The strategy is improved by making effective use of a forecasting module that seeks to predict upcoming peaks in demand, since in such intervals incurred costs significantly increase. A post-tournament analysis is also included in this paper, to help draw important lessons regarding the strengths and weaknesses of the various strategies used in the PowerTAC-2020 competition.en
ΤύποςΔημοσίευση σε Συνέδριοel
ΤύποςConference Publicationen
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2023-07-06-
Ημερομηνία Δημοσίευσης2021-
Θεματική ΚατηγορίαElectricity brokersen
Θεματική ΚατηγορίαTrading agentsen
Θεματική ΚατηγορίαBidding strategiesen
Βιβλιογραφική ΑναφοράS. Orfanoudakis, S. Kontos, C. Akasiadis and G. Chalkiadakis, “Aiming for half gets you to the top: winning PowerTAC 2020,” in Multi-Agent Systems, Lecture Notes in Computer Science, A. Rosenfeld, N. Talmon, Eds., Cham, Switzerland: Springer, 2021, pp. 144–159, doi: 10.1007/978-3-030-82254-5_9.en

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