Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm

Mossolly, Mounir Kassem; Ghali, Kamel; Ghaddar, Nesreen

doi:10.1016/j.energy.2008.10.001

Cited by 236 publications

(96 citation statements)

References 19 publications

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“…Weimin Wang, Radu Zmeureanu, Hugues Rivard have published green building optimization concept with multi-objective genetic algorithms [10]. M. Mossolly, K. Ghali, N. Ghaddar have used Matlab to optimize control strategy for an air-conditioning system [11]. HVAC system optimization results were published by Lu Lu, Wenjian Cai, Lihua Xie, Shujiang Li, Yeng Chai Soh [12].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Office Building Façades in a Warm Summer Continental Climate

Hani¹,

Koiv²

2012

SGRE

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A typical office building model with conventional use and contemporary building systems was developed for façade optimization in continental climate. Wall, glazing area and window parameters were taken as the main variables. The objective function of optimization task described in this article is the minimization of cooling and heating energy consumption. The office building façades optimization was carried out using a combination of IDA Indoor Climate and Energy 4.5 and GenOpt. The process is described in detail so that the approach may be emulated. A hybrid multidimensional optimization algorithm GPSPSOCCHJ was used in calculation process. The optimization results are presented in four quick selection charts to assist architects, designers and real estate developers make suitable early stage façade selection decisions.

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Section: Introductionmentioning

confidence: 99%

Optimization of Office Building Façades in a Warm Summer Continental Climate

Hani¹,

Koiv²

2012

SGRE

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“…As the consumption of air treatment system accounts for about 35% of total consumption of air conditioning [1] , the research on energy saving of central air conditioning system has attracted more and more attention. M·Mossolly, K·Ghali, and N·Ghaddar, by applying genetic algorithm, proposed a strategy to achieve optimum control of multi-partition air conditioning system-using two improved control strategy to replace the basic control strategy of indoor air quality [2] . Maria Jos é Gacto, Rafael Alcal á and Francisco Herrera, by applying multi-objective evolutionary Supported by project of Shenyang Municipal Science and Technology Bureau algorithm, optimized the fuzzy logic controller for HVAC.…”

Section: Introductionmentioning

confidence: 99%

Optimized Research of Energy-saving of the wind system in HVAC based on Improved Ant Colony Algorithm

Li¹,

Jingliang²,

Wang³

2014

2014 International Conference on Automatic Control Theory and Application

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Abstract-According to the nonlinear, time-varying variable, large lag and other properties of air handle system, the improved ant colony algorithm is adopted to optimize the air handle system energy consumption. First, mathematical model of wind system of central air conditioning energy consumption is established for improved ant colony algorithm to optimize the model of energy consumption minimization.The improved ant colony algorithm solves the defect of directly deal with continuous optimization problem using ant colony algorithm by discretizing the solution space of continuous function. The experimental results show that, the improved ant colony algorithm can be successfully used in air handle system of HVAC, and has achieved an execellent effect of energy-saving.

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“…A genetic algorithm is used to solve the optimization problem. The GA, as a heuristic approach, is suit for solving complex problems with large search spaces (Goldberg, 1989;Deb, 2001;Mossolly et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Developing and Testing Dynamic Models for HVAC Systems Using System Identification Approach

Nassif¹,

Buford²,

Abu-Lebdeh³

2017

American Journal of Engineering and Applied Sciences

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This paper proposes integrated modeling and optimization methods for a chilled water HVAC system using a system identification approach. Two multiple input-single output models are developed to find the supply air temperature and fan power of the investigated chilled water air handling unit AHU. To test the proposed models, actual data are collected from existing HVAC systems. Different fan and cooling coil model structures with various time delays and orders are tested to find the optimal model structure in term of normalized root-mean-square deviation or Coefficient Of Variances (COV). The paper also proposes an optimization procedure integrated into system identification model to automate the process of finding optimal fan and cooling coil model structures yielding the best accurate predictions. The testing results show that the proposed methods can provide accurate predictions that can used for several applications such as control optimization, energy assessment and fault detection and diagnosis.

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Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm

Cited by 236 publications

References 19 publications

Optimization of Office Building Façades in a Warm Summer Continental Climate

Optimization of Office Building Façades in a Warm Summer Continental Climate

Optimized Research of Energy-saving of the wind system in HVAC based on Improved Ant Colony Algorithm

Developing and Testing Dynamic Models for HVAC Systems Using System Identification Approach

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Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm

Cited by 236 publications

References 19 publications

Optimization of Office Building Fa&#231;ades in a Warm Summer Continental Climate

Optimization of Office Building Fa&#231;ades in a Warm Summer Continental Climate

Optimized Research of Energy-saving of the wind system in HVAC based on Improved Ant Colony Algorithm

Developing and Testing Dynamic Models for HVAC Systems Using System Identification Approach

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Product

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Optimization of Office Building Façades in a Warm Summer Continental Climate

Optimization of Office Building Façades in a Warm Summer Continental Climate