dc.contributor.authorWang, Xinli
dc.contributor.authorCai, Wenjian
dc.contributor.authorYin, Xiaohong
dc.date.accessioned2017-02-03T08:41:53Z
dc.date.available2017-02-03T08:41:53Z
dc.date.issued2017
dc.identifier.citationWang, X., Cai, W., & Yin, X. (2017). A global optimized operation strategy for energy savings in liquid desiccant air conditioning using self-adaptive differential evolutionary algorithm. Applied Energy, 187, 410-423.en_US
dc.identifier.issn0306-2619en_US
dc.identifier.urihttp://hdl.handle.net/10220/42070
dc.description.abstractThis study proposes a global optimized operation strategy to reduce energy consumption of a liquid desiccant air conditioning (LDAC) driven by chiller and electric heater. Energy models of chiller, electric heater, pumps and fans are developed to predict their energy consumptions under different operating conditions with different control settings. Heat transfer models of cooling heat exchanger, heating heat exchanger and recovery heat exchanger are established to analyze the heat transfer processes in these components. An optimization problem considering system constraints and interactions between components is built to optimize the energy usage of the whole liquid desiccant air conditioning and simultaneously maintaining the required indoor air quality (IAQ) level. Nine controllable variables related to the performance and energy usage of LDAC are selected as control settings. Self-adaptive differential evolutionary (SADE) algorithm with fast convergence rate is employed to solve the optimization problem to obtain optimal control settings and to develop optimal operation strategies. Compare study is carried out on a fabricated testing facility to show the energy saving performance of the proposed global optimized operation strategy. Compared with the conventional strategy, 18.5% energy saving can be achieved by using the proposed global optimized operation strategy. The proposed global optimized operation strategy is a valid operation strategy that is suitable for application in energy reduction of the existing LDAC system in building.en_US
dc.description.sponsorshipNRF (Natl Research Foundation, S’pore)en_US
dc.format.extent40 p.en_US
dc.language.isoenen_US
dc.relation.ispartofseriesApplied Energyen_US
dc.rights© 2016 Elsevier Ltd. This is the author created version of a work that has been peer reviewed and accepted for publication by Applied Energy, Elsevier Ltd. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.apenergy.2016.11.073].en_US
dc.subjectLiquid desiccant air conditioneren_US
dc.subjectEnergy conservationen_US
dc.titleA global optimized operation strategy for energy savings in liquid desiccant air conditioning using self-adaptive differential evolutionary algorithmen_US
dc.typeJournal Article
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.apenergy.2016.11.073
dc.description.versionAccepted versionen_US


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