On energy-efficient HVAC operation with Model Predictive Control: A multiple climate zone study
On energy-efficient HVAC operation with Model Predictive Control: A multiple climate zone study
复制标题
DOI：
10.1016/j.apenergy.2022.119752
复制
发表时间：
2022-10
期刊：
影响因子：
11.2
通讯作者：
N. Raman;Bo Chen;P. Barooah
中科院分区：
文献类型：
--
作者：
N. Raman;Bo Chen;P. Barooah
本文旨在量化模型预测控制（MPC）的性能为一个典型的商业建筑供暖，通风和空调（HVAC）系统在广泛的气候和天气条件。这项研究的动机来自于这样一个事实，即尽管有大量关于HVAC系统MPC的工作，但缺乏研究MPC的可能性能范围，即节能和保持室内气候（温度和湿度）作为室外天气的函数。进行这样的研究的一个挑战是开发一种可以在各种天气中使用的MPC控制器。这一挑战的根本原因是需要一个可以由MPC控制器使用的易处理的冷却和冷却盘管模型，因为盘管可以根据天气以非常不同的模式运行。我们提出了这样一个MPC控制器，然后利用它进行广泛的模拟活动，在美国的14个气候区和四个气候条件（冬季，春季，夏季和秋季）在每个气候区。所提出的控制器的性能进行比较，不仅基于规则的基线控制器，但也与一个简单的MPC控制器，忽略湿度和潜热的考虑。从这项比较研究中得出了几个结果。一个这样的结果是，MPC在基线上的能源节省可能会因气候和季节而变化很大。另一个原因是，在MPC公式中忽略湿度的影响可能导致在温和天气而不是炎热天气中更差的室内湿度控制。本研究的结果可以帮助从业者和研究人员评估用于HVAC控制的拟议MPC配方的成本和效益。
This paper aims to quantify the performance of Model Predictive Control (MPC) for a typical commercial building heating, ventilation and air conditioning (HVAC) system across a wide range of climate and weather conditions. The motivation of the study comes from the fact that although there is a large body of work on MPC for HVAC systems, there is a lack of studies that examine the range of possible performance of MPC, in terms of both energy savings and maintaining indoor climate (temperature and humidity) as a function of outdoor weather. A challenge in conducting such a study is developing an MPC controller that can be used in a wide range of weather. The root cause of this challenge is the need for a tractable cooling and dehumidification coil model that can be used by the MPC controller, since the coil may operate in quite distinct modes depending on weather. We present such an MPC controller, and then leverage it to conduct an extensive simulation campaign for fourteen climate zones in the United States and four weather conditions (winter, spring, summer, and fall) in each climate zone. The performance of the proposed controller is compared with not only a rule-based baseline controller but also with a simpler MPC controller that ignores humidity and latent heat considerations. There are several results the arise from this comparative study. One such result is that energy savings from MPC over baseline can vary dramatically based on climate and season. Another is that the effect of ignoring humidity in the MPC formulation can lead to poor indoor humidity control more in milder weather rather than in hot weather. The results from this study can help practitioners and researchers assess costs and benefits of proposed MPC formulations for HVAC control.