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Optimizing energy efficiency and thermal comfort in building green retrofit

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  • Li, Qing
  • Zhang, Lianying
  • Zhang, Limao
  • Wu, Xianguo

Abstract

Building green retrofit offers significant opportunities for enhancing energy efficiency and achieving green development goals. However, a conflicting criterion exists between energy conservation and thermal comfort improvement when making optimal design solutions for building retrofit. This study presents a simulation-based energy-comfort optimization model to facilitate evaluating various design alternatives and balancing multiple objectives in building green retrofit. A building simulation model is first established to measure energy consumption and comfort level. Then, a multi-objective optimization method (response surface method) is employed to identify critical building parameters and generates a set of alternative plans for building retrofit based on green building standards. After that, optimal design solutions with trade-offs between thermal comfort and energy demand are obtained. A school building in Wuhan city of China is chosen as a case to validate the developed model, and ten building parameters pertaining to energy demand and environmental comfort are considered in the optimization process. The results show that four parameters are significantly sensitive to energy efficiency and thermal comfort, including insulation thickness of the external wall, the heat transmission coefficient of the roof, solar heat gain coefficient of the external window, and window to wall ratio. The optimal combination of four parameters approximately produces 4 % of energy savings, as well as an improving level of environmental comfort. The study benefits designers and construction managers to determine optimal solutions for building retrofit to achieve better energy efficiency and comfort in green building development.

Suggested Citation

  • Li, Qing & Zhang, Lianying & Zhang, Limao & Wu, Xianguo, 2021. "Optimizing energy efficiency and thermal comfort in building green retrofit," Energy, Elsevier, vol. 237(C).
    • Handle: RePEc:eee:energy:v:237:y:2021:i:c:s0360544221017576
    DOI: 10.1016/j.energy.2021.121509
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    References listed on IDEAS

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    1. Li, Hong Xian & Li, Yan & Jiang, Boya & Zhang, Limao & Wu, Xianguo & Lin, Jingyi, 2020. "Energy performance optimisation of building envelope retrofit through integrated orthogonal arrays with data envelopment analysis," Renewable Energy, Elsevier, vol. 149(C), pages 1414-1423.
    2. Chong, Daokun & Zhu, Neng & Luo, Wei & Zhang, Zhiyu, 2019. "Broadening human thermal comfort range based on short-term heat acclimation," Energy, Elsevier, vol. 176(C), pages 418-428.
    3. Pan, Yue & Zhang, Limao, 2020. "Data-driven estimation of building energy consumption with multi-source heterogeneous data," Applied Energy, Elsevier, vol. 268(C).
    4. Moazzen, Nazanin & Ashrafian, Touraj & Yilmaz, Zerrin & Karagüler, Mustafa Erkan, 2020. "A multi-criteria approach to affordable energy-efficient retrofit of primary school buildings," Applied Energy, Elsevier, vol. 268(C).
    5. Hall, Samantha, 2014. "Development and initial trial of a tool to enable improved energy & human performance in existing commercial buildings," Renewable Energy, Elsevier, vol. 67(C), pages 109-118.
    6. Zhang, Sheng & Sun, Yongjun & Cheng, Yong & Huang, Pei & Oladokun, Majeed Olaide & Lin, Zhang, 2018. "Response-surface-model-based system sizing for Nearly/Net zero energy buildings under uncertainty," Applied Energy, Elsevier, vol. 228(C), pages 1020-1031.
    7. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
    8. Seal, Sayani & Boulet, Benoit & Dehkordi, Vahid R., 2020. "Centralized model predictive control strategy for thermal comfort and residential energy management," Energy, Elsevier, vol. 212(C).
    9. Pao-Hung Lin & Chin-Chuan Chang & Yu-Hui Lin & Wei-Liang Lin, 2019. "Green BIM Assessment Applying for Energy Consumption and Comfort in the Traditional Public Market: A Case Study," Sustainability, MDPI, vol. 11(17), pages 1-26, August.
    10. Ruparathna, Rajeev & Hewage, Kasun & Sadiq, Rehan, 2016. "Improving the energy efficiency of the existing building stock: A critical review of commercial and institutional buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1032-1045.
    11. Yang, Zheng & Becerik-Gerber, Burcin, 2015. "A model calibration framework for simultaneous multi-level building energy simulation," Applied Energy, Elsevier, vol. 149(C), pages 415-431.
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    2. Konstantinos Sofias & Zoe Kanetaki & Constantinos Stergiou & Sébastien Jacques, 2023. "Combining CAD Modeling and Simulation of Energy Performance Data for the Retrofit of Public Buildings," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    3. Ozarisoy, B. & Altan, H., 2022. "Significance of occupancy patterns and habitual household adaptive behaviour on home-energy performance of post-war social-housing estate in the South-eastern Mediterranean climate: Energy policy desi," Energy, Elsevier, vol. 244(PB).
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    5. Chadly, Assia & Azar, Elie & Maalouf, Maher & Mayyas, Ahmad, 2022. "Techno-economic analysis of energy storage systems using reversible fuel cells and rechargeable batteries in green buildings," Energy, Elsevier, vol. 247(C).
    6. Lee, Minjung & Ham, Jeonggyun & Lee, Jeong-Won & Cho, Honghyun, 2023. "Analysis of thermal comfort, energy consumption, and CO2 reduction of indoor space according to the type of local heating under winter rest conditions," Energy, Elsevier, vol. 268(C).
    7. Renata Rapisarda & Francesco Nocera & Vincenzo Costanzo & Gaetano Sciuto & Rosa Caponetto, 2022. "Hydroponic Green Roof Systems as an Alternative to Traditional Pond and Green Roofs: A Literature Review," Energies, MDPI, vol. 15(6), pages 1-27, March.
    8. Simone Forastiere & Cristina Piselli & Benedetta Pioppi & Carla Balocco & Fabio Sciurpi & Anna Laura Pisello, 2023. "Towards Achieving Zero Carbon Targets in Building Retrofits: A Multi-Parameter Building Information Modeling (BIM) Approach Applied to a Case Study of a Thermal Bath," Energies, MDPI, vol. 16(12), pages 1-23, June.
    9. Xiaomiao Liao & Wanjiang Wang & Yihuan Zhou, 2023. "Investigating the Energy-Saving Effectiveness of Envelope Retrofits and Photovoltaic Systems: A Case Study of a Hotel in Urumqi," Sustainability, MDPI, vol. 15(13), pages 1-22, June.
    10. Silvia Erba & Alessandra Barbieri, 2022. "Measured Indoor Environmental Data in a Retrofitted Multiapartment Building to Assess Energy Flexibility and Thermal Safety during Winter Power Outages," Data, MDPI, vol. 7(7), pages 1-14, July.
    11. Margherita Mastellone & Silvia Ruggiero & Dimitra Papadaki & Nikolaos Barmparesos & Anastasia Fotopoulou & Annarita Ferrante & Margarita Niki Assimakopoulos, 2022. "Energy, Environmental Impact and Indoor Environmental Quality of Add-Ons in Buildings," Sustainability, MDPI, vol. 14(13), pages 1-29, June.
    12. Domenico Curto & Vincenzo Franzitta & Andrea Guercio & Domenico Panno, 2021. "Energy Retrofit. A Case Study—Santi Romano Dormitory on the Palermo University," Sustainability, MDPI, vol. 13(24), pages 1-13, December.
    13. Søndergaard, Henrik Alexander Nissen & Shaker, Hamid Reza & Jørgensen, Bo Nørregaard, 2024. "Contextual operational energy performance indexing of district heating consumers," Energy, Elsevier, vol. 302(C).
    14. Chen, Hongyu & Shen, Geoffrey Qiping & Feng, Zongbao & Liu, Yang, 2024. "Optimization of energy-saving retrofit solutions for existing buildings: A multidimensional data fusion approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 201(C).
    15. Yanfei Ji & Guangchen Li & Fanghan Su & Yixing Chen & Rongpeng Zhang, 2023. "Retrofit Analysis of City-Scale Residential Buildings in the Hot Summer and Cold Winter Climate Zone," Energies, MDPI, vol. 16(17), pages 1-19, August.

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