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Global sensitivity analysis for key parameters identification of net-zero energy buildings for grid interaction optimization

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  • Zhang, Yelin
  • Zhang, Xingxing
  • Huang, Pei
  • Sun, Yongjun

Abstract

Utilizing renewable energy to meet the energy demand, net-zero energy building (NZEB) is considered a promising solution to the worsening energy and environmental problems. Due to the intermittent and unstable characteristics of renewable energy (e.g. solar energy), NZEB needs to frequently exchange energy with the power grid. Such frequent energy interactions can impose negative impacts on the grid in terms of power balance and voltage stability. Existing studies demonstrated that there exist many influential parameters to NZEB grid interaction. However, the impacts of influential parameters have not been systematically compared and the key parameters with critical impacts are still unknown. Without knowing the key parameters, researchers may mistakenly optimize non-critical parameters, thereby leading to limited performance improvements; or they have to take parameters more than necessary into consideration, thereby causing unnecessarily high computation loads. Therefore, this study proposes a novel method to identify the key parameters affecting NZEB grid interactions. In the method, global sensitivity analysis is adopted to quantitatively compare the impacts of 24 influential parameters in three major performance aspects including over/under voltage, grid dependence and energy loss. Meanwhile, Monte-Carlo method is used to simulate the parameter uncertainties. The identified key parameters have been verified through comparing their performance improvements and computation loads. Providing an effective way to identify key parameters out of numerous ones, the study results can substantially reduce the unnecessary considerations of non-critical parameters in design optimizations. Also, the identified key parameters can be used for improving NZEB grid interaction with limited computing power requirement.

Suggested Citation

  • Zhang, Yelin & Zhang, Xingxing & Huang, Pei & Sun, Yongjun, 2020. "Global sensitivity analysis for key parameters identification of net-zero energy buildings for grid interaction optimization," Applied Energy, Elsevier, vol. 279(C).
  • Handle: RePEc:eee:appene:v:279:y:2020:i:c:s030626192031299x
    DOI: 10.1016/j.apenergy.2020.115820
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    References listed on IDEAS

    as
    1. Roos, Aleksandra & Bolkesjø, Torjus Folsland, 2018. "Value of demand flexibility on spot and reserve electricity markets in future power system with increased shares of variable renewable energy," Energy, Elsevier, vol. 144(C), pages 207-217.
    2. Jamil, Majid & Anees, Ahmed Sharique, 2016. "Optimal sizing and location of SPV (solar photovoltaic) based MLDG (multiple location distributed generator) in distribution system for loss reduction, voltage profile improvement with economical bene," Energy, Elsevier, vol. 103(C), pages 231-239.
    3. Storti, Bruno A. & Dorella, Jonathan J. & Roman, Nadia D. & Peralta, Ignacio & Albanesi, Alejandro E., 2019. "Improving the efficiency of a Savonius wind turbine by designing a set of deflector plates with a metamodel-based optimization approach," Energy, Elsevier, vol. 186(C).
    4. Huang, Pei & Fan, Cheng & Zhang, Xingxing & Wang, Jiayuan, 2019. "A hierarchical coordinated demand response control for buildings with improved performances at building group," Applied Energy, Elsevier, vol. 242(C), pages 684-694.
    5. 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.
    6. Baetens, R. & De Coninck, R. & Van Roy, J. & Verbruggen, B. & Driesen, J. & Helsen, L. & Saelens, D., 2012. "Assessing electrical bottlenecks at feeder level for residential net zero-energy buildings by integrated system simulation," Applied Energy, Elsevier, vol. 96(C), pages 74-83.
    7. Guarino, Francesco & Cassarà, Pietro & Longo, Sonia & Cellura, Maurizio & Ferro, Erina, 2015. "Load match optimisation of a residential building case study: A cross-entropy based electricity storage sizing algorithm," Applied Energy, Elsevier, vol. 154(C), pages 380-391.
    8. Huang, Pei & Wu, Hunjun & Huang, Gongsheng & Sun, Yongjun, 2018. "A top-down control method of nZEBs for performance optimization at nZEB-cluster-level," Energy, Elsevier, vol. 159(C), pages 891-904.
    9. Zhang, Sheng & Huang, Pei & Sun, Yongjun, 2016. "A multi-criterion renewable energy system design optimization for net zero energy buildings under uncertainties," Energy, Elsevier, vol. 94(C), pages 654-665.
    10. Wu, Wei & Skye, Harrison M. & Domanski, Piotr A., 2018. "Selecting HVAC systems to achieve comfortable and cost-effective residential net-zero energy buildings," Applied Energy, Elsevier, vol. 212(C), pages 577-591.
    11. Tian, Wei, 2013. "A review of sensitivity analysis methods in building energy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 411-419.
    12. 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.
    13. Sharma, Vanika & Haque, Mohammed H. & Aziz, Syed Mahfuzul, 2019. "Energy cost minimization for net zero energy homes through optimal sizing of battery storage system," Renewable Energy, Elsevier, vol. 141(C), pages 278-286.
    14. Yildiz, Yusuf & Korkmaz, Koray & Göksal Özbalta, Türkan & Durmus Arsan, Zeynep, 2012. "An approach for developing sensitive design parameter guidelines to reduce the energy requirements of low-rise apartment buildings," Applied Energy, Elsevier, vol. 93(C), pages 337-347.
    15. Huang, Pei & Huang, Gongsheng & Sun, Yongjun, 2018. "Uncertainty-based life-cycle analysis of near-zero energy buildings for performance improvements," Applied Energy, Elsevier, vol. 213(C), pages 486-498.
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