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Factored MDPs for optimal prosumer decision-making in continuous state spaces

Angelidakis Angelos, Chalkiadakis Georgios

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URIhttp://purl.tuc.gr/dl/dias/E1E8608D-4126-4834-AC8D-7EF0DDCE59C4-
Identifierhttps://link.springer.com/chapter/10.1007%2F978-3-319-33509-4_8-
Identifierhttps://doi.org/10.1007/978-3-319-33509-4_8-
Languageen-
Extent17 pagesen
TitleFactored MDPs for optimal prosumer decision-making in continuous state spacesen
CreatorAngelidakis Angelosen
CreatorΑγγελιδακης Αγγελοςel
CreatorChalkiadakis Georgiosen
CreatorΧαλκιαδακης Γεωργιοςel
PublisherSpringer Verlagen
Content SummaryThe economic profitability of Smart Grid prosumers (i.e., producers that are simultaneously consumers) depends on their tackling of the decision-making problem they face when selling and buying energy. In previous work, we had modelled this problem compactly as a factored Markov Decision Process, capturing the main aspects of the business decisions of a prosumer corresponding to a community microgrid of any size. Though that work had employed an exact value iteration algorithm to obtain a near-optimal solution over discrete state spaces, it could not tackle problems defined over continuous state spaces. By contrast, in this paper we show how to use approximate MDP solution methods for taking decisions in this domain without the need of discretizing the state space. Specifically, we employ fitted value iteration, a sampling-based approximation method that is known to be well behaved. By so doing, we generalize our factored MDP solution method to continuous state spaces. We evaluate our approach using a variety of basis functions over different state sample sizes, and compare its performance to that of our original “exact” value iteration algorithm. Our generic approximation method is shown to exhibit stable performance in terms of accumulated reward, which for certain basis functions reaches 98% of that gathered by the exact algorithm.en
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2018-10-30-
Date of Publication2016-
SubjectApproximation methodsen
SubjectContinuous state spacesen
SubjectDecision-makingen
SubjectEnergyen
SubjectFactored MDPsen
SubjectSmart Griden
Bibliographic CitationA. Angelidakis and G. Chalkiadakis, "Factored MDPs for optimal prosumer decision-making in continuous state spaces," in 13th European Conference on Multi-Agent Systems, EUMAS 2015 and 3rd International Conference on Agreement Technologies, 2016, pp. 91-107. doi: 10.1007/978-3-319-33509-4_8en

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