HVAC system optimization - In-building section

被引：0

作者：

Lu, L ^{[1
]}

Cai, WJ ^{[1
]}

Soh, YC ^{[1
]}

Li, SY ^{[1
]}

机构：

[1] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore

来源：

PROCEEDINGS OF THE 4TH INTERNATIONAL SYMPOSIUM ON HEATING, VENTILATING AND AIR CONDITIONING, VOLS 1 AND 2 | 2003年

关键词：

optimization; ANFIS; genetic algorithm; indoor air loop; chilled water loop;

D O I：

暂无

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

This paper presents a practical method to optimize in-building section of centralized Heating, Ventilation and Air-conditioning (HVAC) systems which consist of indoor air loops and chilled water loops. First, through component characteristic analysis, mathematical models associated with cooling loads and energy consumption for heat exchangers and energy consuming devices are established. By considering variation of cooling load of each end user, adaptive neuro-fuzzy inference system (ANFIS) is employed to model duct and pipe networks and obtain optimal differential pressure (DP) set points based on limited sensor information. A mix-integer nonlinear constraint optimization of system energy is formulated and solved by a modified genetic algorithm. The main feature of our paper is a systematic approach in optimizing the overall system energy consumption rather than that of individual component. A simulation study for a typical centralized HVAC system is provided to compare the proposed optimization method with traditional ones. The results show that the proposed method indeed improves the system performance significantly.

引用

页码：622 / 631

页数：10

共 26 条

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