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Distributionally robust day-ahead scheduling of park-level integrated energy system considering generalized energy storages

Author

Listed:
  • Chen, Changming
  • Wu, Xueyan
  • Li, Yan
  • Zhu, Xiaojun
  • Li, Zesen
  • Ma, Jien
  • Qiu, Weiqiang
  • Liu, Chang
  • Lin, Zhenzhi
  • Yang, Li
  • Wang, Qin
  • Ding, Yi

Abstract

The optimal scheduling of park-level integrated energy system can improve the efficiency of energy utilization and promote the consumption level of renewable energy. However, the uncertainty of renewable energy sources’ output power may lead to negative impacts on the scheduling of park-level integrated energy system. Therefore, a distributionally robust day-ahead scheduling model of PIES considering generalized energy storages is proposed in this paper, aiming to reduce the operating cost, renewable energy curtailment, and carbon emission of park-level integrated energy system. In the proposed model, the actual multi-energy storage devices, integrated demand response and pipeline energy storages are synergistically modeled as generalized energy storages to improve the operating flexibility of park-level integrated energy system; the Wasserstein metric-based distributionally robust optimization method is utilized to handle the uncertainty problems in the scheduling of park-level integrated energy system, which can obtain the expected operating costs of park-level integrated energy system under the worst-case probability distribution restricted in an ambiguity set; the strong duality theory and reformulation–linearization technique are utilized to linearize the proposed non-convex model and make it easier to be solved by the commercial solver. Case studies are performed on a park-level integrated energy system that consists of an IEEE 33-bus distribution network, a 44-node district heating network and a 20-node natural gas network for verifying the effectiveness and advantages of the proposed model.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:appene:v:302:y:2021:i:c:s0306261921008795
    DOI: 10.1016/j.apenergy.2021.117493
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    as
    1. Guevara, Esnil & Babonneau, Fréderic & Homem-de-Mello, Tito & Moret, Stefano, 2020. "A machine learning and distributionally robust optimization framework for strategic energy planning under uncertainty," Applied Energy, Elsevier, vol. 271(C).
    2. Li, Xiaozhu & Wang, Weiqing & Wang, Haiyun, 2021. "Hybrid time-scale energy optimal scheduling strategy for integrated energy system with bilateral interaction with supply and demand," Applied Energy, Elsevier, vol. 285(C).
    3. Jin, Ming & Feng, Wei & Marnay, Chris & Spanos, Costas, 2018. "Microgrid to enable optimal distributed energy retail and end-user demand response," Applied Energy, Elsevier, vol. 210(C), pages 1321-1335.
    4. 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).
    5. Mu, Yunfei & Chen, Wanqing & Yu, Xiaodan & Jia, Hongjie & Hou, Kai & Wang, Congshan & Meng, Xianjun, 2020. "A double-layer planning method for integrated community energy systems with varying energy conversion efficiencies," Applied Energy, Elsevier, vol. 279(C).
    6. Xie, Shiwei & Hu, Zhijian & Wang, Jueying, 2020. "Two-stage robust optimization for expansion planning of active distribution systems coupled with urban transportation networks," Applied Energy, Elsevier, vol. 261(C).
    7. Zheng, Shunlin & Sun, Yi & Li, Bin & Qi, Bing & Zhang, Xudong & Li, Fei, 2021. "Incentive-based integrated demand response for multiple energy carriers under complex uncertainties and double coupling effects," Applied Energy, Elsevier, vol. 283(C).
    8. Fang, Xin & Cui, Hantao & Yuan, Haoyu & Tan, Jin & Jiang, Tao, 2019. "Distributionally-robust chance constrained and interval optimization for integrated electricity and natural gas systems optimal power flow with wind uncertainties," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    9. Xie, Shiwei & Zheng, Jieyun & Hu, Zhijian & Wang, Jueying & Chen, Yuwei, 2020. "Urban multi-energy network optimization: An enhanced model using a two-stage bound-tightening approach," Applied Energy, Elsevier, vol. 277(C).
    10. Lei, Yang & Wang, Dan & Jia, Hongjie & Li, Jiaxi & Chen, Jingcheng & Li, Jingru & Yang, Zhihong, 2021. "Multi-stage stochastic planning of regional integrated energy system based on scenario tree path optimization under long-term multiple uncertainties," Applied Energy, Elsevier, vol. 300(C).
    11. Farrokhifar, Meisam & Nie, Yinghui & Pozo, David, 2020. "Energy systems planning: A survey on models for integrated power and natural gas networks coordination," Applied Energy, Elsevier, vol. 262(C).
    12. Su, Yongxin & Zhou, Yao & Tan, Mao, 2020. "An interval optimization strategy of household multi-energy system considering tolerance degree and integrated demand response," Applied Energy, Elsevier, vol. 260(C).
    13. Wang, Yongli & Ma, Yuze & Song, Fuhao & Ma, Yang & Qi, Chengyuan & Huang, Feifei & Xing, Juntai & Zhang, Fuwei, 2020. "Economic and efficient multi-objective operation optimization of integrated energy system considering electro-thermal demand response," Energy, Elsevier, vol. 205(C).
    14. Dutton, Spencer & Marnay, Chris & Feng, Wei & Robinson, Matthew & Mammoli, Andrea, 2019. "Moore vs. Murphy: Tradeoffs between complexity and reliability in distributed energy system scheduling using software-as-a-service," Applied Energy, Elsevier, vol. 238(C), pages 1126-1137.
    15. Liu, Wenxia & Huang, Yuchen & Li, Zhengzhou & Yang, Yue & Yi, Fang, 2020. "Optimal allocation for coupling device in an integrated energy system considering complex uncertainties of demand response," Energy, Elsevier, vol. 198(C).
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