دانلود مقاله انگلیسی رایگان:یادگیری تقویتی برای کنترل ساخت : فرصت ها و چالش ها - 2020
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  • Reinforcement learning for building controls:  The opportunities and challenges Reinforcement learning for building controls: The opportunities and challenges
    Reinforcement learning for building controls:  The opportunities and challenges

    سال انتشار:

    2020


    عنوان انگلیسی مقاله:

    Reinforcement learning for building controls: The opportunities and challenges


    ترجمه فارسی عنوان مقاله:

    یادگیری تقویتی برای کنترل ساخت : فرصت ها و چالش ها


    منبع:

    Sciencedirect - Elsevier - Applied Energy, 269 (2020) 115036. doi:10.1016/j.apenergy.2020.115036


    نویسنده:

    Zhe Wang, Tianzhen Hong⁎


    چکیده انگلیسی:

    Building controls are becoming more important and complicated due to the dynamic and stochastic energy demand, on-site intermittent energy supply, as well as energy storage, making it difficult for them to be optimized by conventional control techniques. Reinforcement Learning (RL), as an emerging control technique, has attracted growing research interest and demonstrated its potential to enhance building performance while addressing some limitations of other advanced control techniques, such as model predictive control. This study conducted a comprehensive review of existing studies that applied RL for building controls. It provided a detailed breakdown of the existing RL studies that use a specific variation of each major component of the Reinforcement Learning: algorithm, state, action, reward, and environment. We found RL for building controls is still in the research stage with limited applications (11%) in real buildings. Three significant barriers prevent the adoption of RL controllers in actual building controls: (1) the training process is time consuming and data demanding, (2) the control security and robustness need to be enhanced, and (3) the generalization capabilities of RL controllers need to be improved using approaches such as transfer learning. Future research may focus on developing RL controllers that could be used in real buildings, addressing current RL challenges, such as accelerating training and enhancing control robustness, as well as developing an open-source testbed and dataset for performance benchmarking of RL controllers.
    Keywords: Building controls | Reinforcement learning | Machine learning | Optimization | Building performance


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 18
    حجم فایل: 2932 کیلوبایت

    قیمت: رایگان


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