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Co-optimization of a novel distributed energy system integrated with hybrid energy storage in different nearly zero energy community scenarios

Author

Listed:
  • Liu, Zhijian
  • Li, Ying
  • Fan, Guangyao
  • Wu, Di
  • Guo, Jiacheng
  • Jin, Guangya
  • Zhang, Shicong
  • Yang, Xinyan

Abstract

Many countries have proposed plans on distributed energy systems. However, distributed energy systems still can be improved in system optimization design methods, new-type load, and application scenarios. Therefore, a novel distributed energy system is developed combining solar energy utilization with hybrid energy storage technology, i.e., heat storage and electricity storage. Secondly, with primary energy saving rate, carbon dioxide equivalent emission reduction rate, and annual cost per unit supply area as objectives, an integration optimization method considering equipment configuration and operation strategy is adopted. Then, considering different community types and scales, 12 nearly zero energy community scenarios with electric vehicles as a new-type load are designed. Comparative analysis is conducted on the proposed system, comparing with separated production system and in different scenarios. The results show the scenario with 50% public buildings possesses considerable energy saving (53.1%), environmentally protection (56.4%), and economy (50.1 CNY/m2). The proportion of public buildings mainly influences primary energy saving rate (21.0%), followed by annual cost per unit supply area 17.7 (CNY/m2), finally carbon emission reduction (9.1%). The residential community with 196800 m2 building scale perform brilliantly. These findings worth popularization and application in the developing nearly zero energy communities.

Suggested Citation

  • Liu, Zhijian & Li, Ying & Fan, Guangyao & Wu, Di & Guo, Jiacheng & Jin, Guangya & Zhang, Shicong & Yang, Xinyan, 2022. "Co-optimization of a novel distributed energy system integrated with hybrid energy storage in different nearly zero energy community scenarios," Energy, Elsevier, vol. 247(C).
    • Handle: RePEc:eee:energy:v:247:y:2022:i:c:s036054422200456x
    DOI: 10.1016/j.energy.2022.123553
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    Cited by:

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    4. Tostado-Véliz, Marcos & Rezaee Jordehi, Ahmad & Amir Mansouri, Seyed & Jurado, Francisco, 2022. "Day-ahead scheduling of 100% isolated communities under uncertainties through a novel stochastic-robust model," Applied Energy, Elsevier, vol. 328(C).
    5. Tostado-Véliz, Marcos & Jordehi, Ahmad Rezaee & Mansouri, Seyed Amir & Jurado, Francisco, 2023. "A two-stage IGDT-stochastic model for optimal scheduling of energy communities with intelligent parking lots," Energy, Elsevier, vol. 263(PD).
    6. Aruta, Giuseppe & Ascione, Fabrizio & Bianco, Nicola & Mauro, Gerardo Maria, 2023. "Sustainability and energy communities: Assessing the potential of building energy retrofit and renewables to lead the local energy transition," Energy, Elsevier, vol. 282(C).
    7. Li, Ye & Liu, Zihan & Sang, Yufeng & Hu, Jingfan & Li, Bojia & Zhang, Xinyu & Jurasz, Jakub & Zheng, Wandong, 2023. "Optimization of integrated energy system for low-carbon community considering the feasibility and application limitation," Applied Energy, Elsevier, vol. 348(C).

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