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    Autonomous Demand-Side Management system based on Monte Carlo Tree Search

    Galvan, Edgar and Harris, Colin and Trujillo, Leonardo and Rodriguez-Vazquez, Katya and Clarke, Siobhan and Cahill, Vinny (2014) Autonomous Demand-Side Management system based on Monte Carlo Tree Search. 2014 IEEE International Energy Conference (ENERGYCON). pp. 1263-1270.

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    Smart Grid (SG) technologies are becoming increasingly dynamic, motivating the use of computational intelligence to support the SG by predicting and intelligently responding to certain requests (e.g, reducing electricity costs given fluctuating prices). The presented work intends to do precisely this, to make intelligent decisions to switch on electric devices at times when the electricity price (prices that change over time) is the lowest while at the same time attempting to balance energy usage by avoiding turning on multiple devices at the same time, whenever possible. To this end, we use Monte Carlo Tree Search (MCTS), a real-time decision algorithm. MCTS takes into consideration what might happen in the future by approximating what other entities/agents (electric devices) might do via Monte Carlo simulations. We propose two variants of this method: (a) max n MCTS approach where the competition for resources (e.g, lowest electricity price) happens in one single decision tree and where all the devices are considered, and (b) two-agent MCTS approach, where the competition for resources is distributed among various decision trees. To validate our results, we used two scenarios, a rather simple one where there are no constraints associated to the problem, and another more complex, and realistic scenario with equality and inequality constraints associated to the problem. The results achieved by this real-time decision tree algorithm are very promising, specially those achieved by the max n MCTS approach.

    Item Type: Article
    Keywords: Demand-Side Management Systems; Monte Carlo Tree Search;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 15366
    Identification Number:
    Depositing User: Laura Gallagher
    Date Deposited: 31 Jan 2022 15:24
    Journal or Publication Title: 2014 IEEE International Energy Conference (ENERGYCON)
    Publisher: IEEE
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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