4.7 Article

Model-based predictive control optimization of chiller plants with water-side economizer system

期刊

ENERGY AND BUILDINGS
卷 278, 期 -, 页码 -

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2022.112633

关键词

Chiller plants; Water-side economizer; Model predictive control; Optimization; Free cooling

向作者/读者索取更多资源

This study proposes a model-based predictive control (MPC) method to optimize multiple parameters of the water-side economizer (WSE) system for energy saving. The results show that the hourly optimization strategy can achieve a maximum energy saving potential of around 14.3%, followed by the daily optimization with 12% energy savings. The difference in energy consumption between the other three optimization frequencies was small. Although multi-parameter optimization can save more energy, it requires significant time and computational resources.
A chiller plant with a water-side economizer (WSE) system is an environmental technology that utilizes the low-grade natural cooling source to optimize the cooling supply and reduce the energy consumption. Many studies focused on the real-time optimization of conventional chiller plants, but few researchers aimed at optimizing chiller plants with a WSE system. There is also a lack of optimization platforms that can provide a systematic evaluation of the energy saving potential of WSE under different optimization scenarios. Therefore, this study proposes a model-based predictive control (MPC) method to optimize multiple parameters of the WSE system. First, WSE system models and an optimization platform were developed using the equation-based Modelica modeling method. An actual real-world chiller plant sys-tem was considered to validate the chiller plant models. Then, the energy saving potential was demon-strated by considering 15 simulation cases, implementing three optimization strategies and five optimization frequencies. The obtained results indicated that the hourly optimization strategy can achieve the maximum energy saving potential of around 14.3% compared to the baseline model, followed by the daily optimization, with a reported 12% energy savings. The difference in energy consumption between the other three optimization frequencies was found to be small. The largest chiller plants' energy efficiency ratio was 7.04 when performing hourly optimization for multiple parameters, which is 16.7% higher than that obtained by running annually optimization for a single parameter. Although multi-parameter optimization can save more energy than single-parameter optimization, it is time-consuming and requires extensive computational resources. The proposed MPC optimization method can provide a reference for engineers to select appropriate optimization parameters and frequency to be used for applications in practice.(c) 2022 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据