Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/150547
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dc.contributor.authorJing, Gangen_US
dc.contributor.authorCai, Wenjianen_US
dc.contributor.authorZhang, Xinen_US
dc.contributor.authorCui, Canen_US
dc.contributor.authorYin, Xiaohongen_US
dc.contributor.authorXian, Huacaien_US
dc.date.accessioned2021-06-07T02:48:59Z-
dc.date.available2021-06-07T02:48:59Z-
dc.date.issued2019-
dc.identifier.citationJing, G., Cai, W., Zhang, X., Cui, C., Yin, X. & Xian, H. (2019). Modeling, air balancing and optimal pressure set-point selection for the ventilation system with minimized energy consumption. Applied Energy, 236, 574-589. https://dx.doi.org/10.1016/j.apenergy.2018.12.026en_US
dc.identifier.issn0306-2619en_US
dc.identifier.urihttps://hdl.handle.net/10356/150547-
dc.description.abstractTraditional static pressure reset control strategies commonly use a feedback indicator to reset the static pressure; this results in under-ventilation in certain zones and over-ventilation in others. Based on this issue, the objective of this study was to develop a model-based, improved, static pressure reset control strategy, providing a well-balanced system to eliminate under-ventilation and over-ventilation, while consuming minimal energy. In the study reported here, a comprehensive mathematical model was established to simulate the non-linear behavior of the ventilation system, and a supervised machine learning algorithm for a support vector machine was used to obtain values for unknown parameters in the model. The resulting model was then used as the basis for development of a damper position control method and to determine the damper position, given a desired airflow rate. An optimal, static pressure set-point selection method was also proposed using the developed model to calculate the minimum static pressure set-point in a closed-form. As a result, the revised system consumed less energy owing to the better-balanced system and optimized pressure set-point selection. Moreover, through the application of the damper position control method, the ventilation system was well-balanced and eliminated both under-ventilation and over-ventilation. Experimental tests were carried out to validate the performance of the proposed method in comparison with the conventional static pressure reset strategy, data from which were collected to train the proposed model.en_US
dc.description.sponsorshipNational Research Foundation (NRF)en_US
dc.language.isoenen_US
dc.relationNRF2014EWT-EIRP003-014en_US
dc.relationNRF2013EWT-EIRP004-019en_US
dc.relationNRF2011 NRF-CRP001-090en_US
dc.relation.ispartofApplied Energyen_US
dc.rights© 2018 Elsevier Ltd. All rights reserved.en_US
dc.subjectEngineering::Electrical and electronic engineeringen_US
dc.titleModeling, air balancing and optimal pressure set-point selection for the ventilation system with minimized energy consumptionen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.identifier.doi10.1016/j.apenergy.2018.12.026-
dc.identifier.scopus2-s2.0-85058026174-
dc.identifier.volume236en_US
dc.identifier.spage574en_US
dc.identifier.epage589en_US
dc.subject.keywordsVentilationen_US
dc.subject.keywordsAir Balancingen_US
dc.description.acknowledgementThis work was partially funded by National Research Foundation of Singapore under the grant NRF2014EWT-EIRP003-014, NRF2013EWT-EIRP004-019, NRF2011 NRF-CRP001-090, the scholarship from China Scholarship Council (CSC) (No. 201704000002) and the Science and Technology Plan project of Shandong higher education institutions (No. J16LN26, No. J17KA210).en_US
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