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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/13078
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dc.contributor.authorParameshwaran, R.-
dc.date.accessioned2023-11-15T05:28:17Z-
dc.date.available2023-11-15T05:28:17Z-
dc.date.issued2008-
dc.identifier.urihttps://zenodo.org/records/1085235-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/13078-
dc.description.abstractThe objective of this study is to present the test results of variable air volume (VAV) air conditioning system optimized by two objective genetic algorithm (GA). The objective functions are energy savings and thermal comfort. The optimal set points for fuzzy logic controller (FLC) are the supply air temperature (T s ), the supply duct static pressure (P s ), the chilled water temperature (T w ), and zone temperature (T z ) that is taken as the problem variables. Supply airflow rate and chilled water flow rate are considered to be the constraints. The optimal set point values are obtained from GA process and assigned into fuzzy logic controller (FLC) in order to conserve energy and maintain thermal comfort in real time VAV air conditioning system. A VAV air conditioning system with FLC installed in a software laboratory has been taken for the purpose of energy analysis. The total energy saving obtained in VAV GA optimization system with FLC compared with constant air volume (CAV) system is expected to achieve 31.5%. The optimal duct static pressure obtained through Genetic fuzzy methodology attributes to better air distribution by delivering the optimal quantity of supply air to the conditioned space. This combination enhanced the advantages of uniform air distribution, thermal comfort and improved energy savings potentialen_US
dc.language.isoenen_US
dc.publisherWorld Academy of Science, Engineering and Technologyen_US
dc.subjectMechanical Engineeringen_US
dc.subjectEnergy savingsen_US
dc.subjectFuzzy logicen_US
dc.subjectGenetic algorithmen_US
dc.subjectThermal Comforten_US
dc.titleOptimization of energy conservation potential for VAV air conditioning system using fuzzy based genetic algorithmen_US
dc.typeArticleen_US
Appears in Collections:Department of Mechanical engineering

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