Multi-Objective Decision Making Optimization of a Residential Net Zero Energy Building in Cold Climate

Abstract : The challenge in Zero energy building (ZEB) design is to find the best combination of design strategies that would face the energy performance problems of a particular building. This paper outlines the methodology and the cost-effectiveness potential for optimizing the design of net-zero energy building (NZEB) in a cold climate region in Lebanon; Cedars. Specifically, the non-sorting genetic algorithm (NSGA-II) is chosen in order to minimize thermal, electrical demands and life cycle cost (LCC) while reaching the net zero energy balance; and thus getting the Pareto-front. A ranking decision making technique (ELECTRE III) is applied to the Pareto-front so as to obtain one optimal solution. A wide range of energy efficiency measures are investigated, besides solar energy systems are employed to produce required electricity and hot water for domestic purposes. The results clearly indicate that, for designing a residential NZEB in cold climate, it is essential to minimize the space thermal load through a building envelope with high thermal performance. Envelop high level of insulation is an essential step to decrease the high heating demand. Building thermal loads are decreased by 33.19%. Moreover the LCC is decreased by 31.09%.
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Communication dans un congrès
SENSET 2017 - First International Conference on Sensors, Networks, Smart and Emerging Technologies, Sep 2017, Beyrouth, Lebanon. IEEE Proceedings 2017 Sensors Networks Smart and Emerging Technologies (SENSET), pp.ISBN 978-150906011-5, 2017, 〈10.1109/SENSET.2017.8125044〉
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Soumis le : lundi 11 décembre 2017 - 15:39:18
Dernière modification le : jeudi 3 mai 2018 - 13:32:58

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Fatima Harkouss, Farouk Fardoun, Pascal Henry Biwole. Multi-Objective Decision Making Optimization of a Residential Net Zero Energy Building in Cold Climate. SENSET 2017 - First International Conference on Sensors, Networks, Smart and Emerging Technologies, Sep 2017, Beyrouth, Lebanon. IEEE Proceedings 2017 Sensors Networks Smart and Emerging Technologies (SENSET), pp.ISBN 978-150906011-5, 2017, 〈10.1109/SENSET.2017.8125044〉. 〈hal-01660981〉

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