Two-Stage Multi-Objective Meta-Heuristics for Environmental and Cost-Optimal Energy Refurbishment at District Level
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2019
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Abstract
Energy efficiency and environmental performance optimization at the district level are following an upward trend mostly triggered by minimizing the Global Warming Potential (GWP) to 20% by 2020 and 40% by 2030 settled by the European Union (EU) compared with 1990 levels. This paper advances over the state of the art by proposing two novel multi-objective algorithms, named Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multi-Objective Harmony Search (MOHS), aimed at achieving cost-effective energy refurbishment scenarios and allowing at district level the decision-making procedure. This challenge is not trivial since the optimisation process must provide feasible solutions for a simultaneous environmental and economic assessment at district scale taking into consideration highly demanding real-based constraints regarding district and buildings’ specific requirements. Consequently, in this paper, a two-stage optimization methodology is proposed in order to reduce the energy demand and fossil fuel consumption with an affordable investment cost at building level and minimize the total payback time while minimizing the GWP at district level. Aimed at demonstrating the effectiveness of the proposed two-stage multi-objective approaches, this work presents simulation results at two real district case studies in Donostia-San Sebastian (Spain) for which up to a 30% of reduction of GWP at district level is obtained for a Payback Time (PT) of 2–3 years.
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Publisher Copyright: © 2019 by the authors.
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Energy , Environmental , Global warming potential , District refurbishment , Multi-objective , Optimization , Energy , Environmental , Global warming potential , District refurbishment , Multi-objective , Optimization , Geography, Planning and Development , Renewable Energy, Sustainability and the Environment , Environmental Science (miscellaneous) , Energy Engineering and Power Technology , Management, Monitoring, Policy and Law , SDG 7 - Affordable and Clean Energy , SDG 8 - Decent Work and Economic Growth , SDG 13 - Climate Action , Project ID , info:eu-repo/grantAgreement/EC/H2020/680676/EU/Optimised Energy Efficient Design Platform for Refurbishment at District Level/OptEEmAL , info:eu-repo/grantAgreement/EC/H2020/680676/EU/Optimised Energy Efficient Design Platform for Refurbishment at District Level/OptEEmAL , Funding Info , Part of this work has been developed from results obtained during the H2020 “Optimised Energy_x000D_ Efficient Design Platform for Refurbishment at District Level” (OptEEmAL) project, Grant No. 680676. , Part of this work has been developed from results obtained during the H2020 “Optimised Energy_x000D_ Efficient Design Platform for Refurbishment at District Level” (OptEEmAL) project, Grant No. 680676.
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Manjarres , D , Mabe , L , Oregi , X & Landa-Torres , I 2019 , ' Two-Stage Multi-Objective Meta-Heuristics for Environmental and Cost-Optimal Energy Refurbishment at District Level ' , Sustainability , vol. 11 , no. 5 , 1495 , pp. 1495 . https://doi.org/10.3390/su11051495