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

Show simple item record Mossolly M. Ghali K. Ghaddar N.
dc.contributor.editor 2009 2017-10-04T11:16:08Z 2017-10-04T11:16:08Z 2009
dc.identifier 10.1016/
dc.identifier.issn 03605442
dc.description.abstract This paper examines optimal control strategies of variable air volume air conditioning system. The control strategies included a base control strategy of fixed temperature set point and two advanced strategies for insuring comfort and indoor air quality (IAQ). The first advanced control adjusts the fresh air supply rate and the supply air temperature to maintain the temperature set point in each zone while assuring indoor air quality. The second strategy controls the fresh air rate and the supply air temperature to maintain an acceptable thermal comfort and IAQ in each zone. The optimization problem for each control strategy is formulated based on the cost of energy consumption and constrained by system and thermal space transient models. The optimization problem is solved using genetic algorithm. The optimization scheme-model is applied to a case study for a building floor in Beirut weather. The thermal space and system component models were validated for the base strategy using Visual DOE 4.0 software [Architectural Energy Cooperation, San Francisco, USA; 2005 〈〉]. Energy savings up to 30.4percent were achieved during the summer season of four months with the optimized advanced strategies when compared with the conventional base strategy while comfort and IAQ were satisfied. © 2008 Elsevier Ltd. All rights reserved.
dc.format.extent Pages: (58-66)
dc.language English
dc.publisher OXFORD
dc.relation.ispartof Publication Name: Energy; Publication Year: 2009; Volume: 34; no. 1; Pages: (58-66);
dc.source Scopus
dc.title Optimal control strategy for a multi-zone air conditioning system using a genetic algorithm
dc.type Article
dc.contributor.affiliation Mossolly, M., Department of Mechanical Engineering, Faculty of Engineering and Architecture, American University of Beirut, P.O. Box 11-236, Riad El Solh, Beirut 11072020, Lebanon
dc.contributor.affiliation Ghali, K., Beirut Arab University, New Road, Beirut, Lebanon
dc.contributor.affiliation Ghaddar, N., Department of Mechanical Engineering, Faculty of Engineering and Architecture, American University of Beirut, P.O. Box 11-236, Riad El Solh, Beirut 11072020, Lebanon
dc.contributor.authorAddress Ghaddar, N.; Department of Mechanical Engineering, Faculty of Engineering and Architecture, American University of Beirut, P.O. Box 11-236, Riad El Solh, Beirut 11072020, Lebanon; email:
dc.contributor.authorCorporate University: American University of Beirut; Faculty: Faculty of Engineering and Architecture; Department: Mechanical Engineering;
dc.contributor.authorDepartment Mechanical Engineering
dc.contributor.authorFaculty Faculty of Engineering and Architecture
dc.contributor.authorInitials Mossolly, M
dc.contributor.authorInitials Ghali, K
dc.contributor.authorInitials Ghaddar, N
dc.contributor.authorReprintAddress Ghaddar, N (reprint author), Amer Univ Beirut, Fac Engn and Architecture, Dept Mech Engn, POB 11-236,Riad El Solh, Beirut 11072020, Lebanon.
dc.contributor.authorUniversity American University of Beirut
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dc.description.citedCount 72
dc.description.citedTotWOSCount 61
dc.description.citedWOSCount 60
dc.format.extentCount 9
dc.identifier.coden ENEYD
dc.identifier.scopusID 57449101464
dc.relation.ispartOfISOAbbr Energy
dc.relation.ispartOfIssue 1
dc.relation.ispartofPubTitle Energy
dc.relation.ispartofPubTitleAbbr Energy
dc.relation.ispartOfVolume 34
dc.source.ID WOS:000262658200008
dc.type.publication Journal
dc.subject.otherAuthKeyword Control of HVAC system
dc.subject.otherAuthKeyword Energy saving
dc.subject.otherAuthKeyword Genetic algorithm
dc.subject.otherAuthKeyword Model based optimization
dc.subject.otherAuthKeyword Optimal control strategy
dc.subject.otherIndex Air conditioning
dc.subject.otherIndex Air quality
dc.subject.otherIndex Atmospheric temperature
dc.subject.otherIndex Constrained optimization
dc.subject.otherIndex Control systems
dc.subject.otherIndex Electric fault location
dc.subject.otherIndex Electric load forecasting
dc.subject.otherIndex Flow of gases
dc.subject.otherIndex Genetic algorithms
dc.subject.otherIndex Genetic engineering
dc.subject.otherIndex Indoor air pollution
dc.subject.otherIndex Intersections
dc.subject.otherIndex Optimal control systems
dc.subject.otherIndex Optimization
dc.subject.otherIndex Advanced controls
dc.subject.otherIndex Air-conditioning systems
dc.subject.otherIndex Building floors
dc.subject.otherIndex Case studies
dc.subject.otherIndex Control strategies
dc.subject.otherIndex Energy consumptions
dc.subject.otherIndex Energy cooperations
dc.subject.otherIndex Energy saving
dc.subject.otherIndex Energy savings
dc.subject.otherIndex Fixed temperatures
dc.subject.otherIndex Fresh airs
dc.subject.otherIndex Indoor Air qualities
dc.subject.otherIndex Model based optimization
dc.subject.otherIndex Optimal control strategies
dc.subject.otherIndex Optimal control strategy
dc.subject.otherIndex Optimization problems
dc.subject.otherIndex San Francisco
dc.subject.otherIndex Set points
dc.subject.otherIndex Software architectural
dc.subject.otherIndex Strategy using
dc.subject.otherIndex Summer seasons
dc.subject.otherIndex Supply air temperatures
dc.subject.otherIndex System components
dc.subject.otherIndex Transient models
dc.subject.otherIndex Variable air volume air conditioning systems
dc.subject.otherIndex Quality control
dc.subject.otherIndex air conditioning
dc.subject.otherIndex air quality
dc.subject.otherIndex energy conservation
dc.subject.otherIndex genetic algorithm
dc.subject.otherIndex optimization
dc.subject.otherKeywordPlus HVAC SYSTEMS
dc.subject.otherKeywordPlus OPTIMIZATION
dc.subject.otherKeywordPlus DESIGN
dc.subject.otherKeywordPlus MODEL
dc.subject.otherWOS Thermodynamics
dc.subject.otherWOS Energy and Fuels

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