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Matching Characteristic Research of Building Renewable Energy System Based on Virtual Energy Storage of Air Conditioning Load

Author

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  • Yongzhen Wang

    (Department of Electrical Engineering, Energy Internet Research Institute, Tsinghua University, Beijing 100085, China
    Key Laboratory of Efficient Utilization of Low and Medium Grade Energy, Tianjin University, Tianjin 300350, China)

  • Congchuan Hu

    (Luneng Group Co., Ltd., Beijing 100020, China)

  • Boyuan Wu

    (School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney 2052, Australia)

  • Jing Zhang

    (Department of Electrical Engineering, Energy Internet Research Institute, Tsinghua University, Beijing 100085, China)

  • Zhenning Zi

    (Department of Electrical Engineering, Energy Internet Research Institute, Tsinghua University, Beijing 100085, China)

  • Ligai Kang

    (School of Civil Engineering, Hebei University of Science & Technology, Shijiazhuang 050018, China)

Abstract

Considering the huge power consumption, rapid response and the short-term heat reserving capacity of the air conditioning load in the building’s energy system, the air conditioning load and its system can be equivalent to the virtual energy storage device for the power grid. Therefore, to obtain a high matching building renewable energy system, a virtual energy storage system of the air conditioning load, accompanied by a storage battery, was built in the paper. Then, operating strategies for the virtual energy storage of the air conditioning load and storage battery were designed. Further, to quantize the contribution of the virtual energy storage to the improvement of matching characteristics, two indicators of the demand side and supply side in the energy system were adopted, including on-site energy fraction (OEF r ) and on-site energy matching (OEM r ). Lastly, matching characteristic research of the building’s renewable energy system based on virtual energy storage of the air conditioning load was established and analyzed by TRNSYS and MATLAB in Tianjin, China. The results revealed that a better matching characteristic performance of the building’s renewable energy systems driven by virtual energy storage was obtained. In the condition set out in the paper, compared with that without virtual energy storage, the average values of OEF r and OEM r after virtual energy storage were 0.66 and 0.77, which increased by 8.19% and 8.45% respectively. Simultaneously, the battery operation performance in the building renewable system was improved when the virtual energy storage was working. The times of charge and discharge cycles decreased after virtual energy storage, and the depth of discharge of the battery reduced by 23.37% on a specific day.

Suggested Citation

  • Yongzhen Wang & Congchuan Hu & Boyuan Wu & Jing Zhang & Zhenning Zi & Ligai Kang, 2020. "Matching Characteristic Research of Building Renewable Energy System Based on Virtual Energy Storage of Air Conditioning Load," Energies, MDPI, vol. 13(5), pages 1-15, March.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1269-:d:330398
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    References listed on IDEAS

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    1. Altun, A.F. & Kilic, M., 2020. "Economic feasibility analysis with the parametric dynamic simulation of a single effect solar absorption cooling system for various climatic regions in Turkey," Renewable Energy, Elsevier, vol. 152(C), pages 75-93.
    2. Lyu, Weihua & Li, Xianting & Yan, Shuai & Jiang, Sihang, 2020. "Utilizing shallow geothermal energy to develop an energy efficient HVAC system," Renewable Energy, Elsevier, vol. 147(P1), pages 672-682.
    3. Haisheng Chen & Xinjing Zhang & Jinchao Liu & Chunqing Tan, 2013. "Compressed Air Energy Storage," Chapters, in: Ahmed F. Zobaa (ed.), Energy Storage - Technologies and Applications, IntechOpen.
    4. Salom, Jaume & Marszal, Anna Joanna & Widén, Joakim & Candanedo, José & Lindberg, Karen Byskov, 2014. "Analysis of load match and grid interaction indicators in net zero energy buildings with simulated and monitored data," Applied Energy, Elsevier, vol. 136(C), pages 119-131.
    5. Cabeza, Luisa F. & Urge-Vorsatz, Diana & McNeil, Michael A. & Barreneche, Camila & Serrano, Susana, 2014. "Investigating greenhouse challenge from growing trends of electricity consumption through home appliances in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 36(C), pages 188-193.
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    Cited by:

    1. Wang, Yongzhen & Zhang, Lanlan & Song, Yi & Han, Kai & Zhang, Yan & Zhu, Yilin & Kang, Ligai, 2024. "State-of-the-art review on evaluation indicators of integrated intelligent energy from different perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    2. Ran Lv & Enqi Wu & Li Lan & Chen Fu & Mingxing Guo & Feier Chen & Min Wang & Jie Zou, 2024. "Research on Virtual Energy Storage Scheduling Strategy for Air Conditioning Based on Adaptive Thermal Comfort Model," Energies, MDPI, vol. 17(11), pages 1-19, May.

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