IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i5p1269-d330398.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/5/1269/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/5/1269/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. 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.
    5. 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.
    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. 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.

    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. Chen, Long Xiang & Xie, Mei Na & Zhao, Pan Pan & Wang, Feng Xiang & Hu, Peng & Wang, Dong Xiang, 2018. "A novel isobaric adiabatic compressed air energy storage (IA-CAES) system on the base of volatile fluid," Applied Energy, Elsevier, vol. 210(C), pages 198-210.
    2. Qian, Jiaxin & Wu, Jiahui & Yao, Lei & Mahmut, Saniye & Zhang, Qiang, 2021. "Comprehensive performance evaluation of Wind-Solar-CCHP system based on emergy analysis and multi-objective decision method," Energy, Elsevier, vol. 230(C).
    3. Yang, Dechang & Wang, Ming & Yang, Ruiqi & Zheng, Yingying & Pandzic, Hrvoje, 2021. "Optimal dispatching of an energy system with integrated compressed air energy storage and demand response," Energy, Elsevier, vol. 234(C).
    4. Houssainy, Sammy & Janbozorgi, Mohammad & Ip, Peggy & Kavehpour, Pirouz, 2018. "Thermodynamic analysis of a high temperature hybrid compressed air energy storage (HTH-CAES) system," Renewable Energy, Elsevier, vol. 115(C), pages 1043-1054.
    5. Fan, Jinyang & Liu, Wei & Jiang, Deyi & Chen, Junchao & Ngaha Tiedeu, William & Chen, Jie & JJK, Deaman, 2018. "Thermodynamic and applicability analysis of a hybrid CAES system using abandoned coal mine in China," Energy, Elsevier, vol. 157(C), pages 31-44.
    6. Cheayb, Mohamad & Marin Gallego, Mylène & Tazerout, Mohand & Poncet, Sébastien, 2022. "A techno-economic analysis of small-scale trigenerative compressed air energy storage system," Energy, Elsevier, vol. 239(PA).
    7. Zhang, Wanshi & Wu, Yunlei & Li, Xiuwei & Cheng, Feng & Zhang, Xiaosong, 2021. "Performance investigation of the wood-based heat localization regenerator in liquid desiccant cooling system," Renewable Energy, Elsevier, vol. 179(C), pages 133-149.
    8. Liu, Jin-Long & Wang, Jian-Hua, 2015. "Thermodynamic analysis of a novel tri-generation system based on compressed air energy storage and pneumatic motor," Energy, Elsevier, vol. 91(C), pages 420-429.
    9. Guelpa, Elisa & Bischi, Aldo & Verda, Vittorio & Chertkov, Michael & Lund, Henrik, 2019. "Towards future infrastructures for sustainable multi-energy systems: A review," Energy, Elsevier, vol. 184(C), pages 2-21.
    10. Bai, Jiayu & Wei, Wei & Chen, Laijun & Mei, Shengwei, 2020. "Modeling and dispatch of advanced adiabatic compressed air energy storage under wide operating range in distribution systems with renewable generation," Energy, Elsevier, vol. 206(C).
    11. Dib, Ghady & Haberschill, Philippe & Rullière, Romuald & Revellin, Rémi, 2021. "Modelling small-scale trigenerative advanced adiabatic compressed air energy storage for building application," Energy, Elsevier, vol. 237(C).
    12. Guo, Cong & Xu, Yujie & Zhang, Xinjing & Guo, Huan & Zhou, Xuezhi & Liu, Chang & Qin, Wei & Li, Wen & Dou, Binlin & Chen, Haisheng, 2017. "Performance analysis of compressed air energy storage systems considering dynamic characteristics of compressed air storage," Energy, Elsevier, vol. 135(C), pages 876-888.
    13. Stinner, Sebastian & Schlösser, Tim & Huchtemann, Kristian & Müller, Dirk & Monti, Antonello, 2017. "Primary energy evaluation of heat pumps considering dynamic boundary conditions in the energy system," Energy, Elsevier, vol. 138(C), pages 60-78.
    14. Muhsin Kılıç, 2022. "Evaluation of Combined Thermal–Mechanical Compression Systems: A Review for Energy Efficient Sustainable Cooling," Sustainability, MDPI, vol. 14(21), pages 1-38, October.
    15. Fachrizal, Reza & Shepero, Mahmoud & Åberg, Magnus & Munkhammar, Joakim, 2022. "Optimal PV-EV sizing at solar powered workplace charging stations with smart charging schemes considering self-consumption and self-sufficiency balance," Applied Energy, Elsevier, vol. 307(C).
    16. Juan Pablo Fernández Goycoolea & Gabriela Zapata-Lancaster & Christopher Whitman, 2022. "Operational Emissions in Prosuming Dwellings: A Study Comparing Different Sources of Grid CO 2 Intensity Values in South Wales, UK," Energies, MDPI, vol. 15(7), pages 1-24, March.
    17. Dzido, Aleksandra & Krawczyk, Piotr & Wołowicz, Marcin & Badyda, Krzysztof, 2022. "Comparison of advanced air liquefaction systems in Liquid Air Energy Storage applications," Renewable Energy, Elsevier, vol. 184(C), pages 727-739.
    18. Meng, Hui & Wang, Meihong & Olumayegun, Olumide & Luo, Xiaobo & Liu, Xiaoyan, 2019. "Process design, operation and economic evaluation of compressed air energy storage (CAES) for wind power through modelling and simulation," Renewable Energy, Elsevier, vol. 136(C), pages 923-936.
    19. Wenting Zhang & Minxing Yue, 2021. "The application of building energy management system based on IoT technology in smart city," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(4), pages 617-628, August.
    20. Prasanna, Ashreeta & Dorer, Viktor & Vetterli, Nadège, 2017. "Optimisation of a district energy system with a low temperature network," Energy, Elsevier, vol. 137(C), pages 632-648.

    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:gam:jeners:v:13:y:2020:i:5:p:1269-:d:330398. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.