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dc.contributor.authorFong, Kwong Fai
dc.contributor.authorHanby, V. I. (Victor Ian), 1942-
dc.contributor.authorChow, Tin-Tai
dc.date.accessioned2007-12-14T11:25:57Z
dc.date.available2007-12-14T11:25:57Z
dc.date.issued2003
dc.identifier.citationFong, Kwong-Fai, Hanby, Victor Ian and Chow, Tin-Tai (2003) Optimization of MVAC systems for energy management by evolutionary algorithm. Facilities, 21 (10), pp. 223-232.en
dc.identifier.issn0263-2772
dc.identifier.otherIR/2007/2
dc.identifier.urihttp://hdl.handle.net/2086/73
dc.description.abstractEnergy management in existing building services installations is an essential focus of contemporary facilities management. The subway company that is one of the major utilities services in Hong Kong Special Administrative Region (HKSAR) has considered better energy management schemes in its subway stations to reduce the running cost. In the past few years, in order to achieve energy saving in the stations, some feasible measures in the Mechanical Ventilation and Air Conditioning (MVAC) systems were implemented, however the engineering decisions were supported by the trial-and-error or imprecise estimation. Improvement to this process would be possible if numerical optimization methods were to be used. Evolutionary algorithm coupled with external plant simulation programme was applied to determine the optimum conditions of the essential parameters of the MVAC systems, in order to provide a holistic energy management approach. For the centralized MVAC systems of the 5 subway stations under studies, the developed optimization and simulation model was found useful to appraise the energy management opportunities for effective design and facilities management.en
dc.language.isoenen
dc.publisherEmeralden
dc.subjectair diffusionen
dc.subjectoptimization techniquesen
dc.subjectenergy managementen
dc.subjectHong Kongen
dc.subjectevolutionary algorithmen
dc.subjectoptimizationen
dc.subjectMVAC systemsen
dc.titleOptimization of MVAC systems for energy management by evolutionary algorithmen
dc.typePreprinten
dc.identifier.doihttps://doi.org/10.1108/02632770310493599
dc.researchgroupInstitute of Energy and Sustainable Development


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