Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/108502
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dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorMehmood, A-
dc.creatorZhang, L-
dc.creatorRen, J-
dc.date.accessioned2024-08-19T01:58:47Z-
dc.date.available2024-08-19T01:58:47Z-
dc.identifier.urihttp://hdl.handle.net/10397/108502-
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.rights© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-NDlicense (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.rightsThe following publication Mehmood, A., Zhang, L., & Ren, J. (2023). A multi-stage optimisation-based decision-making framework for sustainable hybrid energy system in the residential sector. Sustainable Futures, 6, 100122 is available at https://doi.org/10.1016/j.sftr.2023.100122.en_US
dc.subjectEnergy sustainabilityen_US
dc.subjectGenetic algorithmen_US
dc.subjectHybrid energy systemen_US
dc.subjectMulti-criteria decision-makingen_US
dc.subjectSystem thinking approachen_US
dc.titleA multi-stage optimisation-based decision-making framework for sustainable hybrid energy system in the residential sectoren_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume6-
dc.identifier.doi10.1016/j.sftr.2023.100122-
dcterms.abstractIntegrating renewables into existing energy infrastructure to construct hybrid energy systems (HES) plays a vital role for advancing energy sustainability. While various approaches, such as energy systems analysis and linear or non-linear optimisation, have been employed to achieve energy sustainability mainly at the national or city level, there has been a lack of focus on achieving energy sustainability in the residential sector through a holistic optimal decision-making approach for efficient HES design. This study focuses on developing a multi-stage optimisation-based decision-making framework that models, quantifies, and optimises the performance indicators of HES, allowing for an assessment of the trade-off between benefits and systems costs under various design scenarios. The initial step involves designing the HES model and constructing scenarios that cater to the electrification requirements of water, energy, and food elements in the residential sector by using a systematic thinking approach. Then, a preliminary evaluation of the modelled scenarios is conducted to assess energy sustainability in terms of technical and economic aspects. Afterwards, an optimal decision-making setup is established by integrating a multi-objective HES model into the NSGA-II algorithm, which approximates the Pareto optimal solutions. These solutions are then ranked by using a multi-criteria decision-making method. According to the findings, the Quetta region in Pakistan contains the best optimal solution. The results underscore the utility of the developed framework in facilitating the optimal design of renewables-integrated HES for the residential sector. Furthermore, intergovernmental organizations can leverage this framework to formulate effective policies aimed at encouraging residents to invest in HES installation.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationSustainable futures, Dec. 2023, v. 6, 100122-
dcterms.isPartOfSustainable futures-
dcterms.issued2023-12-
dc.identifier.scopus2-s2.0-85169802526-
dc.identifier.eissn2666-1888-
dc.identifier.artn100122-
dc.description.validate202408 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextResearch Committee of The Hong Kong Polytechnic University; Research Institute for Advanced Manufacturing (RIAM), The Hong Kong Polytechnic University; Departmental General Research Fund, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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