Enhanced-efficiency operating variables selection for vapor compression refrigeration cycle system

被引：5
|
作者：
Yin, Xiaohong [1 ,2 ]
Li, Shaoyuan [1 ,2 ]
Cai, Wenjian [3 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China
[2] Minist Educ China, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China
[3] Nanyang Technol Univ, Sch Elect & Elect Engn, Ctr E City, EXQUISITUS, Singapore 639798, Singapore
来源：
COMPUTERS & CHEMICAL ENGINEERING | 2015年 / 80卷
基金：
新加坡国家研究基金会;
关键词：
Vapor compression refrigeration cycle; Operating variables; Self-optimizing control; Model predictive control; Energy efficiency; MODEL-PREDICTIVE CONTROL; PART I;
D O I：
10.1016/j.compchemeng.2015.05.005
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper, a novel enhanced-efficiency selection of operating variables based on self-optimizing control (SOC) method for the vapor compression refrigeration cycle (VCC) system is proposed. An objective function is proposed to maximize the energy efficiency of the VCC system while meeting with the demand of indoor thermal comfort. With the detailed analysis of operating variables, three unconstrained degrees of freedom are selected among all the candidate operating variables. Then two SOC methods are applied to determine the optimal individual controlled variables (CVs) and measurement combinations as CVs. The model predictive control (MPC) method based controllers and PID controllers are designed for different sets of CVs, and the experimental results indicate that the proposed selection of CVs can achieve a good trade-off between optimal (or near optimal) stable operation and enhanced-efficiency of the synthesized control structure. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1 / 14
页数：14
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