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Multistage Optimization toward a Nearly Net Zero Energy Building Due to Climate Change

Author

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  • Kimiya Aram

    (Department of Civil Engineering, Faculty of Technical and Engineering, Imam Khomeini International University (IKIU), Qazvin 34148-96818, Iran)

  • Roohollah Taherkhani

    (Department of Civil Engineering, Faculty of Technical and Engineering, Imam Khomeini International University (IKIU), Qazvin 34148-96818, Iran)

  • Agnė Šimelytė

    (Department of Economics Engineering, Faculty of Business Management, Vilnius Gediminas Technical University, 10221 Vilnius, Lithuania)

Abstract

Climate change is one of the major problems of the planet. The atmosphere is overloaded with carbon dioxide caused by fossil fuels that are burned for energy. Almost 40 percent of the total energy worldwide is used by the building sector, which comes from non-renewable sources and contributes up to 30% of annual greenhouse gas emissions globally. The building sector in Iran accounts for 33.8% of Iran’s total energy usage. Within the building sector, the energy consumption of Iranian educational buildings is 2.5 times higher than educational buildings in developed countries. One of the most effective ways of reducing global energy consumption and greenhouse gas emissions is retrofitting existing buildings. This study aims to investigate whether a particular energy-optimized design under the present climate conditions would respond effectively to future climate change. This can help designers make a better decision on an optimal model, which can remain optimal over the years based on climate change. For methodological purposes, multistage optimization was used to retrofit an existing educational building. Specifically, the non-dominated sorting genetic algorithm (NSGA-II) was chosen to minimize the cooling and heating load, as well as consider investment costs for present and future weather files, using the jEPlus tool. Furthermore, the TOPSIS method was used to identify the best set of retrofit measures. For this purpose, a four-story educational building in Tehran was modeled on Design Builder software v7.0.0.116 as a case study to provide a better understanding for researchers of how to effectively retrofit a building to achieve a nearly zero energy building considering climate change. The results show that the optimized solution for the present weather file does not remain the optimized solution in 2080. Moreover, it is shown that to have an optimized building in regard to future weather files, the model should be designed for the future weather conditions. This study shows that if the building becomes optimized using the present weather file the total energy consumption will be reduced by 65.14% and 86.18% if using the future weather file. These two figures are obtained by implementing active and passive measures and show the priority of using the future weather file for designers. Using PV panels also, this building is capable of becoming a nearly net zero building, which would produce about 90% of its own energy demands.

Suggested Citation

  • Kimiya Aram & Roohollah Taherkhani & Agnė Šimelytė, 2022. "Multistage Optimization toward a Nearly Net Zero Energy Building Due to Climate Change," Energies, MDPI, vol. 15(3), pages 1-21, January.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:3:p:983-:d:737147
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    References listed on IDEAS

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    1. Wan, Kevin K.W. & Li, Danny H.W. & Pan, Wenyan & Lam, Joseph C., 2012. "Impact of climate change on building energy use in different climate zones and mitigation and adaptation implications," Applied Energy, Elsevier, vol. 97(C), pages 274-282.
    2. Chai, Jiale & Huang, Pei & Sun, Yongjun, 2019. "Investigations of climate change impacts on net-zero energy building lifecycle performance in typical Chinese climate regions," Energy, Elsevier, vol. 185(C), pages 176-189.
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    2. Hoda Ramezani & Ehsan Reza, 2022. "The Consequence of Combining Indigenous Techniques with a Flexible Design to Reduce Energy Consumption in Residential Buildings for Future Architecture," Sustainability, MDPI, vol. 14(21), pages 1-15, October.
    3. Hao Wang & Quan Liu & Hongyang Zhang & Yinlong Jin & Wenzhen Yu, 2022. "A Two-Stage Decision-Making Method Based on WebGIS for Bulk Material Transportation of Hydropower Construction," Energies, MDPI, vol. 15(5), pages 1-21, February.
    4. Zihan Zhang & Wanjiang Wang & Junkang Song & Zhe Wang & Weiyi Wang, 2022. "Multi-Objective Optimization of Ultra-Low Energy Consumption Buildings in Severely Cold Regions Considering Life Cycle Performance," Sustainability, MDPI, vol. 14(24), pages 1-17, December.

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