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A collaborative control optimization of grid-connected net zero energy buildings for performance improvements at building group level

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  • Fan, Cheng
  • Huang, Gongsheng
  • Sun, Yongjun

Abstract

Due to inherent differences in building usage and system configuration, NZEBs frequently show different sufficiency of renewable energy at same moments, thereby providing chances of renewable-energy-sharing among NZEBs. Conventional controls are developed for NZEB performance improvements at single building level while potential collaborations (renewable energy sharing) between NZEBs are rarely considered. For this reason, they are unable to achieve optimized results at building group level. This study thus proposes a new collaborative control in which renewable energy sharing are realized among NZEBs. Adopting different objective functions, case studies have been conducted to compare the proposed control with a conventional one in two aspects, i.e. operation cost and grid friendliness. The study results have shown that the proposed collaborative control is able to achieve performance improvements through renewable energy sharing among NZEBs. The proposed collaborative control can be implemented in practice to realize renewable energy sharing among NZEBs and thus improve the cost effectiveness and grid friendliness at building group level.

Suggested Citation

  • Fan, Cheng & Huang, Gongsheng & Sun, Yongjun, 2018. "A collaborative control optimization of grid-connected net zero energy buildings for performance improvements at building group level," Energy, Elsevier, vol. 164(C), pages 536-549.
    • Handle: RePEc:eee:energy:v:164:y:2018:i:c:p:536-549
    DOI: 10.1016/j.energy.2018.09.018
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    Cited by:

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    3. Huang, Pei & Han, Mengjie & Zhang, Xingxing & Hussain, Syed Asad & Jayprakash Bhagat, Rohit & Hogarehalli Kumar, Deepu, 2022. "Characterization and optimization of energy sharing performances in energy-sharing communities in Sweden, Canada and Germany," Applied Energy, Elsevier, vol. 326(C).
    4. Tao Lv & Yuehong Lu & Yijie Zhou & Xuemei Liu & Changlong Wang & Yang Zhang & Zhijia Huang & Yanhong Sun, 2022. "Optimal Control of Energy Systems in Net-Zero Energy Buildings Considering Dynamic Costs: A Case Study of Zero Carbon Building in Hong Kong," Sustainability, MDPI, vol. 14(6), pages 1-25, March.
    5. Zhang, Guiqing & Tian, Chenlu & Li, Chengdong & Zhang, Jun Jason & Zuo, Wangda, 2020. "Accurate forecasting of building energy consumption via a novel ensembled deep learning method considering the cyclic feature," Energy, Elsevier, vol. 201(C).
    6. Zheng, Siqian & Jin, Xin & Huang, Gongsheng & Lai, Alvin CK., 2022. "Coordination of commercial prosumers with distributed demand-side flexibility in energy sharing and management system," Energy, Elsevier, vol. 248(C).
    7. Zheng, Siqian & Huang, Gongsheng & Lai, Alvin CK., 2021. "Techno-economic performance analysis of synergistic energy sharing strategies for grid-connected prosumers with distributed battery storages," Renewable Energy, Elsevier, vol. 178(C), pages 1261-1278.
    8. Ziyu Duan & Seiyong Kim, 2023. "Progress in Research on Net-Zero-Carbon Cities: A Literature Review and Knowledge Framework," Energies, MDPI, vol. 16(17), pages 1-27, August.
    9. Huang, Pei & Sun, Yongjun & Lovati, Marco & Zhang, Xingxing, 2021. "Solar-photovoltaic-power-sharing-based design optimization of distributed energy storage systems for performance improvements," Energy, Elsevier, vol. 222(C).

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