A Markov Process Approach to Ensemble Control of Smart Buildings
A Markov Process Approach to Ensemble Control of Smart Buildings
复制标题
智能建筑集成控制的马尔可夫过程方法
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Y. Dvorkin
中科院分区：
文献类型：
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作者：
R. Pop;Ali Hassan;K. Bruninx;M. Chertkov;Y. Dvorkin
本文介绍了一个循序渐进的过程，将建筑物的物理模型转换为马尔可夫过程，该过程表征了该建筑物的能耗。相对于现有的基于热物理的建筑模型，所提出的方法降低了模型的复杂性，并依赖于更少的参数，同时还保持了足够的准确性和可行性，以进行系统级分析。此外，所提出的马尔可夫过程方法可以利用智能建筑数据采集系统提供的实时数据流，这些数据流在智能建筑中很容易获得，并将其与基于物理和统计的模型合并。马尔可夫过程的构建自然会导致马尔可夫决策过程公式化，该公式描述了相似建筑物集合的最优概率控制。该方法说明了使用验证的建筑数据从比利时。
This paper describes a step-by-step procedure that converts a physical model of a building into a Markov Process that characterizes energy consumption of this building. Relative to existing thermo-physics-based building models, the proposed procedure reduces model complexity and depends on fewer parameters, while also maintaining accuracy and feasibility sufficient for system-level analyses. Furthermore, the proposed Markov Process approach makes it possible to leverage real-time data streams available from intelligent building data acquisition systems, which are readily available in smart buildings, and merge it with physics-based and statistical models. Construction of the Markov Process naturally leads to a Markov Decision Process formulation, which describes optimal probabilistic control of a collection of similar buildings. The approach is illustrated using validated building data from Belgium.
机会约束最优潮流中的最优负荷集合控制
影响因子：
9.6
作者：
Hassan, Ali;Mieth, Robert;Chertkov, Michael;Deka, Deepjyoti;Dvorkin, Yury
通讯作者：
Dvorkin, Yury