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A multi-time-space scale optimal operation strategy for a distributed integrated energy system

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  • Li, Peng
  • Wang, Zixuan
  • Wang, Jiahao
  • Guo, Tianyu
  • Yin, Yunxing

Abstract

Integrated energy system (IES) has become a popular topic in the field of energy research, and a considerable part of this research has paid attention to IES operation. However, regarding a distributed integrated energy system (DIES) with multiple communities, the coordination of multiple operation measures on different time and space scales has not been fully considered. Based on these considerations, a multi-time-space scale optimal operation strategy based on multi-dimensional energy supply and demand balance is proposed for a DIES. First, from the perspective of energy supply and demand, various types of energy equipment are modelled and analysed to propose a multi-dimensional energy supply and demand balance model. Moreover, a collaborative optimization framework and a multi-time-space scale operation model of DIES that comprises upper, middle and lower levels are further established. While the upper-level model optimizes the whole DIES in the day-ahead stage, the middle-level model performs a rolling optimization for each single community during the intraday, and the lower-level model achieves an adjustment of the electric part of each community in the real-time stage. Finally, a case study is carried out based on a practical town area, and simulation results show that the proposed strategy can utilize the complementary advantages of multiple energy sources and promote the energy supply and demand balance at multiple time and space scales, while exhibiting better performances in terms of objectives, constraints, operation measures and economics.

Suggested Citation

  • Li, Peng & Wang, Zixuan & Wang, Jiahao & Guo, Tianyu & Yin, Yunxing, 2021. "A multi-time-space scale optimal operation strategy for a distributed integrated energy system," Applied Energy, Elsevier, vol. 289(C).
  • Handle: RePEc:eee:appene:v:289:y:2021:i:c:s0306261921002233
    DOI: 10.1016/j.apenergy.2021.116698
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    Cited by:

    1. Wu, Long & Yin, Xunyuan & Pan, Lei & Liu, Jinfeng, 2023. "Distributed economic predictive control of integrated energy systems for enhanced synergy and grid response: A decomposition and cooperation strategy," Applied Energy, Elsevier, vol. 349(C).
    2. Guo, Jiacheng & Wu, Di & Wang, Yuanyuan & Wang, Liming & Guo, Hanyuan, 2023. "Co-optimization method research and comprehensive benefits analysis of regional integrated energy system," Applied Energy, Elsevier, vol. 340(C).
    3. Ma, Xin & Peng, Bo & Ma, Xiangxue & Tian, Changbin & Yan, Yi, 2023. "Multi-timescale optimization scheduling of regional integrated energy system based on source-load joint forecasting," Energy, Elsevier, vol. 283(C).
    4. Fan, Wei & Tan, Zhongfu & Li, Fanqi & Zhang, Amin & Ju, Liwei & Wang, Yuwei & De, Gejirifu, 2023. "A two-stage optimal scheduling model of integrated energy system based on CVaR theory implementing integrated demand response," Energy, Elsevier, vol. 263(PC).
    5. Zhou, Yuan & Wang, Jiangjiang & Wei, Changqi & Li, Yuxin, 2024. "A novel two-stage multi-objective dispatch model for a distributed hybrid CCHP system considering source-load fluctuations mitigation," Energy, Elsevier, vol. 300(C).
    6. Dong, Xing & Zhang, Chenghui & Sun, Bo, 2022. "Optimization strategy based on robust model predictive control for RES-CCHP system under multiple uncertainties," Applied Energy, Elsevier, vol. 325(C).
    7. Qinqin Xia & Yao Zou & Qianggang Wang, 2024. "Optimal Capacity Planning of Green Electricity-Based Industrial Electricity-Hydrogen Multi-Energy System Considering Variable Unit Cost Sequence," Sustainability, MDPI, vol. 16(9), pages 1-20, April.
    8. Wang, Xiaojing & Han, Li & Wang, Chong & Yu, Hongbo & Yu, Xiaojiao, 2023. "A time-scale adaptive dispatching strategy considering the matching of time characteristics and dispatching periods of the integrated energy system," Energy, Elsevier, vol. 267(C).
    9. Yang, Xiaohui & Wang, Xiaopeng & Deng, Yeheng & Mei, Linghao & Deng, Fuwei & Zhang, Zhonglian, 2023. "Integrated energy system scheduling model based on non-complete interval multi-objective fuzzy optimization," Renewable Energy, Elsevier, vol. 218(C).
    10. Saletti, Costanza & Morini, Mirko & Gambarotta, Agostino, 2022. "Smart management of integrated energy systems through co-optimization with long and short horizons," Energy, Elsevier, vol. 250(C).
    11. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Zhao, Yunlong & Gao, Chong, 2023. "A stochastic hierarchical optimization and revenue allocation approach for multi-regional integrated energy systems based on cooperative games," Applied Energy, Elsevier, vol. 350(C).
    12. Li, Peng & Wang, Zixuan & Liu, Haitao & Wang, Jiahao & Guo, Tianyu & Yin, Yunxing, 2021. "Bi-level optimal configuration strategy of community integrated energy system with coordinated planning and operation," Energy, Elsevier, vol. 236(C).
    13. Fang, Xiaolun & Dong, Wei & Wang, Yubin & Yang, Qiang, 2024. "Multi-stage and multi-timescale optimal energy management for hydrogen-based integrated energy systems," Energy, Elsevier, vol. 286(C).
    14. Wang, L.L. & Xian, R.C. & Jiao, P.H. & Chen, J.J. & Chen, Y. & Liu, H.G., 2024. "Multi-timescale optimization of integrated energy system with diversified utilization of hydrogen energy under the coupling of green certificate and carbon trading," Renewable Energy, Elsevier, vol. 228(C).
    15. Wang, Liying & Lin, Jialin & Dong, Houqi & Wang, Yuqing & Zeng, Ming, 2023. "Demand response comprehensive incentive mechanism-based multi-time scale optimization scheduling for park integrated energy system," Energy, Elsevier, vol. 270(C).
    16. Li, Na & Okur, Özge, 2023. "Economic analysis of energy communities: Investment options and cost allocation," Applied Energy, Elsevier, vol. 336(C).
    17. Xi, Yufei & Zhang, Zhengfa & Zhang, Jiansheng, 2024. "Multi-objective optimization strategy for regional multi-energy systems integrated with medium-high temperature solar thermal technology," Energy, Elsevier, vol. 300(C).
    18. Zhou, Yuan & Wang, Jiangjiang & Yang, Mingxu & Xu, Hangwei, 2023. "Hybrid active and passive strategies for chance-constrained bilevel scheduling of community multi-energy system considering demand-side management and consumer psychology," Applied Energy, Elsevier, vol. 349(C).
    19. Chen, Changming & Wu, Xueyan & Li, Yan & Zhu, Xiaojun & Li, Zesen & Ma, Jien & Qiu, Weiqiang & Liu, Chang & Lin, Zhenzhi & Yang, Li & Wang, Qin & Ding, Yi, 2021. "Distributionally robust day-ahead scheduling of park-level integrated energy system considering generalized energy storages," Applied Energy, Elsevier, vol. 302(C).
    20. Lin, Xiaojie & Lin, Xueru & Zhong, Wei & Zhou, Yi, 2024. "Multi-time scale dynamic operation optimization method for industrial park electricity-heat-gas integrated energy system considering demand elasticity," Energy, Elsevier, vol. 293(C).
    21. Wu, Long & Yin, Xunyuan & Pan, Lei & Liu, Jinfeng, 2022. "Economic model predictive control of integrated energy systems: A multi-time-scale framework," Applied Energy, Elsevier, vol. 328(C).
    22. Ghilardi, Lavinia Marina Paola & Castelli, Alessandro Francesco & Moretti, Luca & Morini, Mirko & Martelli, Emanuele, 2021. "Co-optimization of multi-energy system operation, district heating/cooling network and thermal comfort management for buildings," Applied Energy, Elsevier, vol. 302(C).
    23. Fang, Xiaolun & Dong, Wei & Wang, Yubin & Yang, Qiang, 2022. "Multiple time-scale energy management strategy for a hydrogen-based multi-energy microgrid," Applied Energy, Elsevier, vol. 328(C).
    24. Du, Sipeng & Wu, Di & Dai, Zhong & Li, Guiqiang & Lahaxibai, Shala, 2023. "Regional collaborative planning equipped with shared energy storage under multi-time scale rolling optimisation method," Energy, Elsevier, vol. 277(C).

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