A New Swarm Intelligence Approach for Optimal Chiller Loading for Energy Conservation

被引：22
|
作者：
Sulaiman, Mohd Herwan [1 ]
Ibrahim, Hassan [2 ]
Daniyal, Hamdan [1 ]
Mohamed, Mohd Rusllim [1 ]
机构：
[1] Univ Malaysia Pahang, Fac Elect & Elect Engn, Pekan Pahang 26600, Malaysia
[2] Univ Malaysia Pahang, Fac Mech Engn, Pekan Pahang 26600, Malaysia
来源：
2ND INTERNATIONAL CONFERENCE ON INNOVATION, MANAGEMENT AND TECHNOLOGY RESEARCH | 2014年 / 129卷
关键词：
Differential Search Algorithm; Heating; Ventilation and Air-Conditioning (HVAC) System; Optimal Chiller Loading (OCL); Partial Load Ratio (PLR); Swarm Intelligence; ALGORITHM;
D O I：
10.1016/j.sbspro.2014.03.704
中图分类号：
C93 [管理学];
学科分类号：
12 ; 1201 ; 1202 ; 120202 ;
摘要：
This paper employs a recent swarm intelligence technique to solve optimal chiller loading (OCL) problem, namely differential search (DS) algorithm. In general, significant energy savings can be obtained by optimizing chiller operation and design in heating, ventilation and air-conditioning (HVAC) systems. In this paper, partial load ratio (PLR) of the chiller is used as parameters to be optimized where the power consumption in kW is used as objective function to be minimized. In order to show the effectiveness of the proposed technique, the comparison with other techniques has been done and analyzed. (C) 2014 The Authors. Published by Elsevier Ltd.
引用
收藏
页码：483 / 488
页数：6
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