IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v261y2022ipas0360544222019338.html
   My bibliography  Save this article

Optimal plan for energy conservation and CO2 emissions reduction of public buildings considering users' behavior: Case of China

Author

Listed:
  • Huang, He
  • Wang, Honglei
  • Hu, Yu-Jie
  • Li, Chengjiang
  • Wang, Xiaolin

Abstract

Public buildings play a significant role in carbon emissions reduction and building energy conservation. This study establishes a simulation model for an existing public building in China's hot summer and cold winter areas. It applies the global sensitivity analysis model to obtain the optimally combined strategy of energy-saving renovation, including users' behavior and other parameters' changes. Finally, this study implements a time-of-use (TOU) pricing strategy through the demand response function, and obtains an optimization plan for energy conservation and CO2 emission reduction. Results show that in the combined strategy, on a typical day in summer, energy consumption, carbon emissions and energy expenditure of users are reduced by 24.5%. Moreover, in the TOU pricing strategy, the energy consumption and carbon emissions are reduced by 26.4%, and the energy expenditure of users is reduced by 26.1%. In summary, considering users' comfort, energy consumption, and economy, adopting the TOU pricing strategy is beneficial to load response and adjusting power supply volatility. Moreover, it reduces the electricity cost of users and the maintenance cost of the power supply bureau. This study provides new ideas for energy conservation and CO2 emissions reduction in existing public buildings.

Suggested Citation

  • Huang, He & Wang, Honglei & Hu, Yu-Jie & Li, Chengjiang & Wang, Xiaolin, 2022. "Optimal plan for energy conservation and CO2 emissions reduction of public buildings considering users' behavior: Case of China," Energy, Elsevier, vol. 261(PA).
    • Handle: RePEc:eee:energy:v:261:y:2022:i:pa:s0360544222019338
    DOI: 10.1016/j.energy.2022.125037
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222019338
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.125037?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Turhan, Cihan & Simani, Silvio & Gokcen Akkurt, Gulden, 2021. "Development of a personalized thermal comfort driven controller for HVAC systems," Energy, Elsevier, vol. 237(C).
    2. Dai, Baolian & Tong, Yan & Hu, Qi & Chen, Zheng, 2022. "Characteristics of thermal stratification and its effects on HVAC energy consumption for an atrium building in south China," Energy, Elsevier, vol. 249(C).
    3. Kiguchi, Y. & Weeks, M. & Arakawa, R., 2021. "Predicting winners and losers under time-of-use tariffs using smart meter data," Energy, Elsevier, vol. 236(C).
    4. A.M. Fogheri, 2015. "Energy Efficiency in Public Buildings," Rivista economica del Mezzogiorno, Società editrice il Mulino, issue 3-4, pages 763-784.
    5. Heiselberg, Per & Brohus, Henrik & Hesselholt, Allan & Rasmussen, Henrik & Seinre, Erkki & Thomas, Sara, 2009. "Application of sensitivity analysis in design of sustainable buildings," Renewable Energy, Elsevier, vol. 34(9), pages 2030-2036.
    6. Song, Kwonsik & Jang, Youjin & Park, Moonseo & Lee, Hyun-Soo & Ahn, Joseph, 2020. "Energy efficiency of end-user groups for personalized HVAC control in multi-zone buildings," Energy, Elsevier, vol. 206(C).
    7. Luerssen, Christoph & Verbois, Hadrien & Gandhi, Oktoviano & Reindl, Thomas & Sekhar, Chandra & Cheong, David, 2021. "Global sensitivity and uncertainty analysis of the levelised cost of storage (LCOS) for solar-PV-powered cooling," Applied Energy, Elsevier, vol. 286(C).
    8. Hu, Maomao & Xiao, Fu, 2018. "Price-responsive model-based optimal demand response control of inverter air conditioners using genetic algorithm," Applied Energy, Elsevier, vol. 219(C), pages 151-164.
    9. Dababneh, Fadwa & Li, Lin & Sun, Zeyi, 2016. "Peak power demand reduction for combined manufacturing and HVAC system considering heat transfer characteristics," International Journal of Production Economics, Elsevier, vol. 177(C), pages 44-52.
    10. Kishore, Ravi Anant & Bianchi, Marcus V.A. & Booten, Chuck & Vidal, Judith & Jackson, Roderick, 2021. "Enhancing building energy performance by effectively using phase change material and dynamic insulation in walls," Applied Energy, Elsevier, vol. 283(C).
    11. Huo, Tengfei & Xu, Linbo & Feng, Wei & Cai, Weiguang & Liu, Bingsheng, 2021. "Dynamic scenario simulations of carbon emission peak in China's city-scale urban residential building sector through 2050," Energy Policy, Elsevier, vol. 159(C).
    12. Naji, Sareh & Aye, Lu & Noguchi, Masa, 2021. "Sensitivity analysis on energy performance, thermal and visual discomfort of a prefabricated house in six climate zones in Australia," Applied Energy, Elsevier, vol. 298(C).
    13. Yuang Guo & Dewancker Bart, 2020. "Optimization of Design Parameters for Office Buildings with Climatic Adaptability Based on Energy Demand and Thermal Comfort," Sustainability, MDPI, vol. 12(9), pages 1-23, April.
    14. 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).
    15. Amasyali, Kadir & El-Gohary, Nora, 2021. "Machine learning for occupant-behavior-sensitive cooling energy consumption prediction in office buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
    16. Li, Hangxin & Wang, Shengwei & Cheung, Howard, 2018. "Sensitivity analysis of design parameters and optimal design for zero/low energy buildings in subtropical regions," Applied Energy, Elsevier, vol. 228(C), pages 1280-1291.
    17. Yang, Liu & Dong, Ciwei & Wan, C.L. Johnny & Ng, Chi To, 2013. "Electricity time-of-use tariff with consumer behavior consideration," International Journal of Production Economics, Elsevier, vol. 146(2), pages 402-410.
    18. Yang, Shu-Xia & Nie, Tian-qi & Li, Cheng-Cheng, 2022. "Research on the contribution of regional Energy Internet emission reduction considering time-of-use tariff," Energy, Elsevier, vol. 239(PB).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liobikienė, Genovaitė & Matiiuk, Yuliia & Krikštolaitis, Ričardas, 2023. "The concern about main crises such as the Covid-19 pandemic, the war in Ukraine, and climate change's impact on energy-saving behavior," Energy Policy, Elsevier, vol. 180(C).
    2. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhao, Zeming & Li, Hangxin & Wang, Shengwei, 2022. "Identification of the key design parameters of Zero/low energy buildings and the impacts of climate and building morphology," Applied Energy, Elsevier, vol. 328(C).
    2. Sun, Hongchang & Niu, Yanlei & Li, Chengdong & Zhou, Changgeng & Zhai, Wenwen & Chen, Zhe & Wu, Hao & Niu, Lanqiang, 2022. "Energy consumption optimization of building air conditioning system via combining the parallel temporal convolutional neural network and adaptive opposition-learning chimp algorithm," Energy, Elsevier, vol. 259(C).
    3. Su, Ziyi & Li, Xiaofeng, 2022. "Extraction of key parameters and simplification of sub-system energy models using sensitivity analysis in subway stations," Energy, Elsevier, vol. 261(PA).
    4. Meiyan Wang & Chen Chen & Bingxin Fan & Zilu Yin & Wenxuan Li & Huifang Wang & Fang’ai Chi, 2023. "Multi-Objective Optimization of Envelope Design of Rural Tourism Buildings in Southeastern Coastal Areas of China Based on NSGA-II Algorithm and Entropy-Based TOPSIS Method," Sustainability, MDPI, vol. 15(9), pages 1-27, April.
    5. Abdo Abdullah Ahmed Gassar & Choongwan Koo & Tae Wan Kim & Seung Hyun Cha, 2021. "Performance Optimization Studies on Heating, Cooling and Lighting Energy Systems of Buildings during the Design Stage: A Review," Sustainability, MDPI, vol. 13(17), pages 1-47, September.
    6. Perwez, Usama & Yamaguchi, Yohei & Ma, Tao & Dai, Yanjun & Shimoda, Yoshiyuki, 2022. "Multi-scale GIS-synthetic hybrid approach for the development of commercial building stock energy model," Applied Energy, Elsevier, vol. 323(C).
    7. Østergård, Torben & Jensen, Rasmus L. & Maagaard, Steffen E., 2016. "Building simulations supporting decision making in early design – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 187-201.
    8. Shilei Lu & Zichen Wang & Tianshuai Zhang, 2020. "Quantitative Analysis and Multi-Index Evaluation of the Green Building Envelope Performance in the Cold Area of China," Sustainability, MDPI, vol. 12(1), pages 1-38, January.
    9. Choi, Dong Gu & Murali, Karthik, 2022. "The impact of heterogeneity in consumer characteristics on the design of optimal time-of-use tariffs," Energy, Elsevier, vol. 254(PB).
    10. Zakula, Tea & Badun, Nikola & Ferdelji, Nenad & Ugrina, Ivo, 2021. "Framework for the ISO 52016 standard accuracy prediction based on the in-depth sensitivity analysis," Applied Energy, Elsevier, vol. 298(C).
    11. Yibing Xue & Wenhan Liu, 2022. "A Study on Parametric Design Method for Optimization of Daylight in Commercial Building’s Atrium in Cold Regions," Sustainability, MDPI, vol. 14(13), pages 1-22, June.
    12. Hua Zhang & Junya Ye & Kunming Li & Shujie Niu & Xiao Liu, 2024. "Multi-Stage Sensitivity Analysis of the Energy Demand for the Cooling of Grain Warehouses in Cold Regions of China," Agriculture, MDPI, vol. 14(2), pages 1-15, January.
    13. Xiaojing Meng & Beibei Wei & Yingni Zhai, 2020. "Sensitivity Analysis of Envelope Design Parameters of Industrial Buildings with Natural Ventilation," Sustainability, MDPI, vol. 12(24), pages 1-12, December.
    14. Hu, Maomao & Xiao, Fu, 2020. "Quantifying uncertainty in the aggregate energy flexibility of high-rise residential building clusters considering stochastic occupancy and occupant behavior," Energy, Elsevier, vol. 194(C).
    15. Jordehi, A. Rezaee, 2019. "Optimisation of demand response in electric power systems, a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 308-319.
    16. Chen, Huadun & Du, Qianxi & Huo, Tengfei & Liu, Peiran & Cai, Weiguang & Liu, Bingsheng, 2023. "Spatiotemporal patterns and driving mechanism of carbon emissions in China's urban residential building sector," Energy, Elsevier, vol. 263(PE).
    17. Yu Dong & Tongyu Qin & Siyuan Zhou & Lu Huang & Rui Bo & Haibo Guo & Xunzhi Yin, 2020. "Comparative Whole Building Life Cycle Assessment of Energy Saving and Carbon Reduction Performance of Reinforced Concrete and Timber Stadiums—A Case Study in China," Sustainability, MDPI, vol. 12(4), pages 1-24, February.
    18. Liu, Xinglei & Liu, Jun & Ren, Kezheng & Liu, Xiaoming & Liu, Jiacheng, 2022. "An integrated fuzzy multi-energy transaction evaluation approach for energy internet markets considering judgement credibility and variable rough precision," Energy, Elsevier, vol. 261(PB).
    19. Zhong, Fangliang & Calautit, John Kaiser & Wu, Yupeng, 2022. "Assessment of HVAC system operational fault impacts and multiple faults interactions under climate change," Energy, Elsevier, vol. 258(C).
    20. Karanafti, Aikaterina & Theodosiou, Theodoros & Tsikaloudaki, Katerina, 2022. "Assessment of buildings’ dynamic thermal insulation technologies-A review," Applied Energy, Elsevier, vol. 326(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:261:y:2022:i:pa:s0360544222019338. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.