An Adaptive Model Predictive Control Scheme for Energy-Efficient Control of Building HVAC Systems

An Adaptive Model Predictive Control Scheme for Energy-Efficient Control of Building HVAC Systems
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建筑暖通空调系统节能控制的自适应模型预测控制方案

DOI:
10.1115/1.4051482
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发表时间:
2021
期刊:
ASME Journal of Engineering for Sustainable Buildings and Cities
影响因子:
--
通讯作者:
Barooah, Prabir
Barooah, Prabir
中科院分区:
--
文献类型:
--
作者:
Zeng, Tingting;Barooah, Prabir

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提出了一种用于控制供暖、通风和空调(HVAC)系统的自主自适应模型预测控制(MPC)架构,以在减少能量使用的同时保持室内温度。尽管设备使用和占用者随时间变化,但现有MPC方法不能够在没有人类专家干预的情况下自动重新学习模型并可靠地计算控制决策。我们力求解决这一弱点。在所提出的架构中嵌入了两个主要功能以实现自主性:(i)来自我们先前工作的系统识别算法,该算法定期从数据中重新学习建筑动态和未测量的内部热负荷,而无需专家重新调整。估计的模型是保证是稳定的,并具有理想的物理性质,无论数据;(ii)一个MPC计划与凸近似的原始非凸问题。规划器使用下降和收敛方法,底层优化问题是可行的和凸的。一个现实的工厂为期一年的模拟表明,这两个功能的建议架构的周期性模型和扰动更新和凸化的规划问题是必不可少的,以获得性能的改善比常用的基线控制器。如果没有这些功能,MPC的长期节能可能很小,而有了这些功能,MPC的节能将变得非常可观。
An autonomous adaptive model predictive control (MPC) architecture is presented for control of heating, ventilation, and air condition (HVAC) systems to maintain indoor temperature while reducing energy use. Although equipment use and occupant changes with time, existing MPC methods are not capable of automatically relearning models and computing control decisions reliably for extended periods without intervention from a human expert. We seek to address this weakness. Two major features are embedded in the proposed architecture to enable autonomy: (i) a system identification algorithm from our prior work that periodically re-learns building dynamics and unmeasured internal heat loads from data without requiring re-tuning by experts. The estimated model is guaranteed to be stable and has desirable physical properties irrespective of the data; (ii) an MPC planner with a convex approximation of the original nonconvex problem. The planner uses a descent and convergent method, with the underlying optimization problem being feasible and convex. A yearlong simulation with a realistic plant shows that both of the features of the proposed architecture—periodic model and disturbance update and convexification of the planning problem—are essential to get performance improvement over a commonly used baseline controller. Without these features, long-term energy savings from MPC can be small while with them, the savings from MPC become substantial.
DOI: 10.1109/tcst.2019.2949546
发表时间: 2020-09
影响因子: 4.8
作者:
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用于建筑 HVAC 系统节能控制的自主 MPC 方案
DOI: 10.23919/acc45564.2020.9147753
发表时间: 2020
期刊: 2020 American Control Conference (ACC
影响因子: --
作者:
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DOI: 10.1115/1.4048895
发表时间: 2021
期刊: ASME Journal of Engineering for Sustainable Buildings and Cities
影响因子: --
作者:
Kircher, Kevin J.;Schaefer, Walter;Max Zhang, K.
通讯作者: Max Zhang, K.
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DOI: --
发表时间: 2015
期刊:
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作者:
E. Atam;L. Helsen
通讯作者: L. Helsen
通过显式 MPC 和“修剪和响应”方法进行建筑温度分布式控制
DOI: 10.23919/ecc.2013.6669781
发表时间: 2013
期刊: 2013 European Control Conference (ECC)
影响因子: --
作者:
S. Koehler;F. Borrelli
通讯作者: F. Borrelli