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
相关论文
共 50 条
  • [1] Optimal chiller loading for energy conservation using a new differential cuckoo search approach
    Coelho, Leandro dos Santos
    Klein, Carlos Eduardo
    Sabat, Samrat L.
    Mariani, Viviana Cocco
    ENERGY, 2014, 75 : 237 - 243
  • [2] A novel energy conservation method - optimal chiller loading
    Chang, YC
    ELECTRIC POWER SYSTEMS RESEARCH, 2004, 69 (2-3) : 221 - 226
  • [3] Genetic algorithm based optimal chiller loading for energy conservation
    Chang, YC
    APPLIED THERMAL ENGINEERING, 2005, 25 (17-18) : 2800 - 2815
  • [4] Optimal chiller loading by particle swarm algorithm for reducing energy consumption
    Lee, Wen-Shing
    Lin, Lung-Chieh
    APPLIED THERMAL ENGINEERING, 2009, 29 (8-9) : 1730 - 1734
  • [5] A novel approach for optimal chiller loading using particle swarm optimization
    Ardakani, A. Jahanbani
    Ardakani, F. Fattahi
    Hosseinian, S. H.
    ENERGY AND BUILDINGS, 2008, 40 (12) : 2177 - 2187
  • [6] Optimal chiller loading by improved artificial fish swarm algorithm for energy saving
    Zheng, Zhi-Xin
    Li, Jun-qing
    Duan, Pei-yong
    MATHEMATICS AND COMPUTERS IN SIMULATION, 2019, 155 : 227 - 243
  • [7] Optimal Chiller Loading by Team Particle Swarm Algorithm for Reducing Energy Consumption
    Lee, Wen-Shing
    Lin, Wen-Hsin
    Cheng, Chin-Chi
    Lin, Chien-Yu
    ENERGIES, 2021, 14 (21)
  • [8] Improved firefly algorithm approach applied to chiller loading for energy conservation
    Coelho, Leandro dos Santos
    Mariani, Viviana Cocco
    ENERGY AND BUILDINGS, 2013, 59 : 273 - 278
  • [9] Optimal Chiller Loading Using Improved Particle Swarm Optimization
    Nallagownden, Perumal
    Abdalla, Elnazeer Ali Hamid
    Nor, Nursyarizal Mohd
    Romlie, Mohd Fakhizan
    9TH INTERNATIONAL CONFERENCE ON ROBOTIC, VISION, SIGNAL PROCESSING AND POWER APPLICATIONS: EMPOWERING RESEARCH AND INNOVATION, 2017, 398 : 103 - 113
  • [10] Optimal chiller loading solution for energy conservation using Barnacles Mating Optimizer algorithm
    Sulaiman, Mohd Herwan
    Mustaffa, Zuriani
    RESULTS IN CONTROL AND OPTIMIZATION, 2022, 7
12345