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Optimal prosumer decision-making using factored MDPs

Angelidakis Angelos, Chalkiadakis Georgios

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URI: http://purl.tuc.gr/dl/dias/AC6E8DD9-AA80-4D27-9562-298AF8E712A3
Year 2016
Type of Item Conference Full Paper
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Bibliographic Citation A. Angelidakis and G. Chalkiadakis, "Optimal prosumer decision-making using factored MDPs," in 25th International Joint Conference on Artificial Intelligence, 2016, pp. 4110-4114.
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Summary

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.

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