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dc.contributor.authorTeymoori H., Fatemeh
dc.contributor.authorSafari, Amir
dc.contributor.authorKamalinasab, Mostafa
dc.date.accessioned2024-05-07T12:48:47Z
dc.date.available2024-05-07T12:48:47Z
dc.date.created2022-08-25T12:02:38Z
dc.date.issued2022
dc.identifier.citationTeymoori H, F., Safari, A., & Kamalinasab, M. (2022). Augmented ε-Constraint Algorithm Applied to Multi-objective Optimization Programs of Residential Micro-CHP Systems. Process Integration and Optimization for Sustainability, 6(4), 1143-1161.en_US
dc.identifier.issn2509-4238
dc.identifier.urihttps://hdl.handle.net/11250/3129513
dc.description.abstractMicro-combined heat and power systems (Micro-CHP) are expected to play a major role in reducing carbon dioxide emission, increasing the primary energy and economic saving in the future. In this paper, the optimal planning of a residential Micro-CHP system for a single-family house situated in Iran is investigated. In order to achieve this target, a new mixed-integer linear programming model is developed. Mathematical modeling and optimization were carried out for the Micro-CHP system using natural gas, at the residential building level and for three different operating strategies, cost-driven, primary energy driven, and carbon emission driven. Three competing objective functions are simultaneously minimized using an augmented ε-constraint optimization algorithm. This work has multiple novelties, containing the consideration of some economic and technical constraints previously neglected, such as the energy, economic, and environmental effects of replacing conventional energy systems with a residential Micro-CHP system and the effects of integrating an electrical heating element for storing thermal energy (electrical heating element can act as a power sink when required). A detailed case study on a residential building situated in Tabriz city, Iran, was carried out by applying the developed model and the optimum strategies and optimal sizes for Micro-CHP, axillary boiler, and other equipment are obtained. Results have shown that the optimal values of CSR, PESR, and ERR, in the augmented ε-constraint method, were 12.46%, 1.19%, and 88.38%, respectively. In this case, the obtained result for a nominal capacity of Micro-CHP and boiler was 3.6 kW and 1.05 kW, respectively. Finally, the payback period was obtained for 2 years. Furthermore, to understand the influence of key parameters on the planning of the Micro-CHP system, the sensitivity analysis has been performed on energy prices. Sensitivity analysis of electricity price indicated that, by increasing the electricity price, the overall annual cost-saving value clearly increases, while increasing gas prices significantly reduces the profitability index.en_US
dc.language.isoengen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleAugmented ε-Constraint Algorithm Applied to Multi-objective Optimization Programs of Residential Micro-CHP Systemsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© The Author(s) 2022.en_US
dc.source.pagenumber1143-1161en_US
dc.source.volume6en_US
dc.source.journalProcess Integration and Optimization for Sustainabilityen_US
dc.source.issue4en_US
dc.identifier.doihttps://doi.org/10.1007/s41660-022-00254-2
dc.identifier.cristin2045972
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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