Model Predictive Control for the Operation of Building Cooling Systems

被引：0

作者：

Ma, Yudong ^{[1
]}

Borrelli, Francesco ^{[1
]}

Hencey, Brandon ^{[2
]}

Coffey, Brian ^{[3
]}

Bengea, Sorin ^{[4
]}

Haves, Philip ^{[5
]}

机构：

[1] Univ Calif Berkeley, Dept Mech Engn, Berkeley, CA 94720 USA

[2] Cornell Univ, Sch Mech & Aerosp Engn, Ithaca, NY 14853 USA

[3] Univ Calif Berkeley, Dept Architecture, Berkeley, CA 94720 USA

[4] United Technol Res Ctr, E Hartford, CT 06108 USA

[5] Lawrence Berkeley Natl Lab, Berkeley, CA 94720 USA

来源：

2010 AMERICAN CONTROL CONFERENCE | 2010年

基金：

美国国家科学基金会;

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A model-based predictive control (MPC) is designed for optimal thermal energy storage in building cooling systems. We focus on buildings equipped with a water tank used for actively storing cold water produced by a series of chillers. Typically the chillers are operated at night to recharge the storage tank in order to meet the building demands on the following day. In this paper, we build on our previous work, improve the building load model, and present experimental results. The experiments show that MPC can achieve reduction in the central plant electricity cost and improvement of its efficiency.

引用

页码：5106 / 5111

页数：6

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