Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.enbuild.2012.04.021
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dc.titleA preference driven multi-criteria optimization tool for HVAC design and operation
dc.contributor.authorPantelic, J.
dc.contributor.authorRaphael, B.
dc.contributor.authorTham, K.W.
dc.date.accessioned2013-10-14T04:45:26Z
dc.date.available2013-10-14T04:45:26Z
dc.date.issued2012
dc.identifier.citationPantelic, J., Raphael, B., Tham, K.W. (2012). A preference driven multi-criteria optimization tool for HVAC design and operation. Energy and Buildings 55 : 118-126. ScholarBank@NUS Repository. https://doi.org/10.1016/j.enbuild.2012.04.021
dc.identifier.issn03787788
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/45988
dc.description.abstractThis paper discusses the issue of selecting the design solution that best accords with an articulated preference of multiple criteria with an acceptable performance band. The application of a newly developed multi-criteria decision-making tool called RR-PARETO2 is presented. An example of HVAC design is used to illustrate how solutions could be selected within a multi-criteria optimization framework. In this example, five criteria have been selected, namely, power consumption, thermal comfort, risk of airborne infection of influenza and tuberculosis and effective differential temperature (Δt eq) of body parts. The goal is to select the optimal air exchange rate that makes reasonable trade-offs among all the objectives. Two scenarios have been studied. In the first scenario, there is an influenza outbreak and the important objective is to prevent the spread of infection. In the second scenario, energy prices are high and the primary objective is to reduce energy. In both scenarios, RR-PARETO2 algorithm selects solutions that make reasonable trade-offs among conflicting objectives. The example illustrates how objectives such as reduction of airborne disease transmission and maximizing thermal comfort can be incorporated in the design of a practical, full-scale HVAC system. © 2012 Elsevier B.V. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.enbuild.2012.04.021
dc.sourceScopus
dc.subjectAirborne infection risk
dc.subjectEnergy
dc.subjectMixing ventilation
dc.subjectMulti-criteria optimization
dc.subjectPersonalized ventilation
dc.subjectThermal comfort
dc.typeReview
dc.contributor.departmentBUILDING
dc.description.doi10.1016/j.enbuild.2012.04.021
dc.description.sourcetitleEnergy and Buildings
dc.description.volume55
dc.description.page118-126
dc.description.codenENEBD
dc.identifier.isiut000313152400015
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