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Ιδρυματικό Αποθετήριο [SANDBOX]
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| URI | http://purl.tuc.gr/dl/dias/AC6E8DD9-AA80-4D27-9562-298AF8E712A3 | - |
| Αναγνωριστικό | https://dl.acm.org/citation.cfm?id=3061228 | - |
| Γλώσσα | en | - |
| Μέγεθος | 5 pages | en |
| Τίτλος | Optimal prosumer decision-making using factored MDPs | en |
| Δημιουργός | Angelidakis Angelos | en |
| Δημιουργός | Αγγελιδακης Αγγελος | el |
| Δημιουργός | Chalkiadakis Georgios | en |
| Δημιουργός | Χαλκιαδακης Γεωργιος | el |
| Εκδότης | International Joint Conferences on Artificial Intelligence | en |
| Περίληψη | Tackling the decision-making problem faced by a prosumer (i.e., a producer that is simultaneously a consumer) when selling and buying energy in the emerging smart electricity grid, is of utmost importance for the economic profitability of such a business entity. In this work, we model, for the first time, this problem as a factored Markov Decision Process. By so doing, we are able to represent the problem compactly, and provide an exact optimal solution via dynamic programming- notwithstanding its large size. Our model successfully captures the main aspects of the business decisions of a prosumer corresponding to a community microgrid of any size. Moreover, it includes appropriate sub-models for prosumer production and consumption prediction. Experimental simulations verify the effectiveness of our approach; and show that our exact value iteration solution matches that of a state-of-the-art method for stochastic planning in very large environments, while outperforming it in terms of computation time. | en |
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Τύπος | Conference Full Paper | en |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2018-10-30 | - |
| Ημερομηνία Δημοσίευσης | 2016 | - |
| Θεματική Κατηγορία | MDPs | en |
| Θεματική Κατηγορία | Λήψη αποφάσεων | el |
| Θεματική Κατηγορία | Decision making | en |
| Βιβλιογραφική Αναφορά | A. Angelidakis and G. Chalkiadakis, "Optimal prosumer decision-making using factored MDPs," in 25th International Joint Conference on Artificial Intelligence, 2016, pp. 4110-4114. | en |
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