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Rapid multi-objective optimization with multi-year future weather condition and decision-making support for building retrofit

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  • Shen, Pengyuan
  • Braham, William
  • Yi, Yunkyu
  • Eaton, Eric

Abstract

A method of fast multi-objective optimization and decision-making support for building retrofit planning is developed, and lifecycle cost analysis method taking into account of future climate condition is used in evaluating the retrofit performance. In order to resolve the optimization problem in a fast manner with recourse to non-dominate sorting differential evolution algorithm, the simplified hourly dynamic simulation modeling tool SimBldPy is used as the simulator for objective function evaluation. Moreover, the generated non-dominated solutions are treated and rendered by a layered scheme using agglomerative hierarchical clustering technique to make it more intuitive and sense making during the decision-making process as well as to be better presented.

Suggested Citation

  • Shen, Pengyuan & Braham, William & Yi, Yunkyu & Eaton, Eric, 2019. "Rapid multi-objective optimization with multi-year future weather condition and decision-making support for building retrofit," Energy, Elsevier, vol. 172(C), pages 892-912.
    • Handle: RePEc:eee:energy:v:172:y:2019:i:c:p:892-912
    DOI: 10.1016/j.energy.2019.01.164
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    1. Chantrelle, Fanny Pernodet & Lahmidi, Hicham & Keilholz, Werner & Mankibi, Mohamed El & Michel, Pierre, 2011. "Development of a multicriteria tool for optimizing the renovation of buildings," Applied Energy, Elsevier, vol. 88(4), pages 1386-1394, April.
    2. Shen, Pengyuan & Braham, William & Yi, Yunkyu, 2018. "Development of a lightweight building simulation tool using simplified zone thermal coupling for fast parametric study," Applied Energy, Elsevier, vol. 223(C), pages 188-214.
    3. Giuliano, Genevieve & Small, Kenneth A., 1991. "Subcenters in the Los Angeles region," Regional Science and Urban Economics, Elsevier, vol. 21(2), pages 163-182, July.
    4. Shen, Pengyuan & Lior, Noam, 2016. "Vulnerability to climate change impacts of present renewable energy systems designed for achieving net-zero energy buildings," Energy, Elsevier, vol. 114(C), pages 1288-1305.
    5. Xu, Peng & Huang, Yu Joe & Miller, Norman & Schlegel, Nicole & Shen, Pengyuan, 2012. "Impacts of climate change on building heating and cooling energy patterns in California," Energy, Elsevier, vol. 44(1), pages 792-804.
    6. Stephen Johnson, 1967. "Hierarchical clustering schemes," Psychometrika, Springer;The Psychometric Society, vol. 32(3), pages 241-254, September.
    7. Robert Thorndike, 1953. "Who belongs in the family?," Psychometrika, Springer;The Psychometric Society, vol. 18(4), pages 267-276, December.
    8. Wu, Raphael & Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2017. "Multiobjective optimisation of energy systems and building envelope retrofit in a residential community," Applied Energy, Elsevier, vol. 190(C), pages 634-649.
    9. Shen, Pengyuan & Braham, William & Yi, Yunkyu, 2019. "The feasibility and importance of considering climate change impacts in building retrofit analysis," Applied Energy, Elsevier, vol. 233, pages 254-270.
    10. Tadesse, Mahlet G. & Sha, Naijun & Vannucci, Marina, 2005. "Bayesian Variable Selection in Clustering High-Dimensional Data," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 602-617, June.
    11. Yoza, Akihiro & Yona, Atsushi & Senjyu, Tomonobu & Funabashi, Toshihisa, 2014. "Optimal capacity and expansion planning methodology of PV and battery in smart house," Renewable Energy, Elsevier, vol. 69(C), pages 25-33.
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    3. Wang, Yuhao & Qu, Ke & Chen, Xiangjie & Zhang, Xingxing & Riffat, Saffa, 2022. "Holistic electrification vs deep energy retrofits for optimal decarbonisation pathways of UK dwellings: A case study of the 1940s’ British post-war masonry house," Energy, Elsevier, vol. 241(C).
    4. Pengying Wang & Shuo Zhang, 2022. "Retrofitting Strategies Based on Orthogonal Array Testing to Develop Nearly Zero Energy Buildings," Sustainability, MDPI, vol. 14(8), pages 1-18, April.
    5. Ma, Dingyuan & Li, Xiaodong & Lin, Borong & Zhu, Yimin, 2023. "An intelligent retrofit decision-making model for building program planning considering tacit knowledge and multiple objectives," Energy, Elsevier, vol. 263(PB).
    6. Petkov, Ivalin & Mavromatidis, Georgios & Knoeri, Christof & Allan, James & Hoffmann, Volker H., 2022. "MANGOret: An optimization framework for the long-term investment planning of building multi-energy system and envelope retrofits," Applied Energy, Elsevier, vol. 314(C).
    7. Richarz, Jan & Henn, Sarah & Osterhage, Tanja & Müller, Dirk, 2022. "Optimal scheduling of modernization measures for typical non-residential buildings," Energy, Elsevier, vol. 238(PA).
    8. Shen, Pengyuan & Yang, Biao, 2020. "Projecting Texas energy use for residential sector under future climate and urbanization scenarios: A bottom-up method based on twenty-year regional energy use data," Energy, Elsevier, vol. 193(C).
    9. Ascione, Fabrizio & Bianco, Nicola & Maria Mauro, Gerardo & Napolitano, Davide Ferdinando, 2019. "Building envelope design: Multi-objective optimization to minimize energy consumption, global cost and thermal discomfort. Application to different Italian climatic zones," Energy, Elsevier, vol. 174(C), pages 359-374.
    10. Luo, Xiaojun & Oyedele, Lukumon O., 2022. "Integrated life-cycle optimisation and supply-side management for building retrofitting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    11. Qu, Ke & Chen, Xiangjie & Wang, Yixin & Calautit, John & Riffat, Saffa & Cui, Xin, 2021. "Comprehensive energy, economic and thermal comfort assessments for the passive energy retrofit of historical buildings - A case study of a late nineteenth-century Victorian house renovation in the UK," Energy, Elsevier, vol. 220(C).
    12. Davidson, Eleni & Schwartz, Yair & Williams, Joe & Mumovic, Dejan, 2024. "Resilience of the higher education sector to future climates: A systematic review of predicted building energy performance and modelling approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).

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