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Distributionally robust operation for integrated rural energy systems with broiler houses

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  • Tan, Hong
  • Yan, Wei
  • Ren, Zhouyang
  • Wang, Qiujie
  • Mohamed, Mohamed A.

Abstract

The integrated energy system (IES) can improve energy efficiency by unified planning and operation of multiple heterogeneous energy sources. However, the existing research mainly focuses on the IES in urban areas. This paper introduces the broiler house and biogas digester into the IES and proposes a distributionally robust dispatch model for the integrated rural energy system with broiler houses (IRES-BH). The heat demand model of the broiler house is first built according to the thermal equivalent circuit of the broiler house and the heat radiation of the broiler flock. Then, the electricity demand model of the broiler house is derived based on the ventilation requirements of the broiler flock and the performance parameters of the fans. Furthermore, the gas production rate model of the biogas digester is suggested according to the relationship between the biogas production rate and the fermentation temperature. Finally, a day-ahead dispatch model of the IRES-BH is formulated based on the Kullback-Leibler divergence constrained distributionally robust optimization and the solution methodology of the dispatch model is proposed. Two cases of different scales verify the effectiveness of the proposed model.

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  • Tan, Hong & Yan, Wei & Ren, Zhouyang & Wang, Qiujie & Mohamed, Mohamed A., 2022. "Distributionally robust operation for integrated rural energy systems with broiler houses," Energy, Elsevier, vol. 254(PC).
    • Handle: RePEc:eee:energy:v:254:y:2022:i:pc:s0360544222013019
    DOI: 10.1016/j.energy.2022.124398
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    Cited by:

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    3. Wang, Yongli & Guo, Lu & Wang, Yanan & Zhang, Yunfei & Zhang, Siwen & Liu, Zeqiang & Xing, Juntai & Liu, Ximei, 2024. "Bi-level programming optimization method of rural integrated energy system based on coupling coordination degree of energy equipment," Energy, Elsevier, vol. 298(C).
    4. Abdulaziz Almalaq & Saleh Albadran & Amer Alghadhban & Tao Jin & Mohamed A. Mohamed, 2022. "An Effective Hybrid-Energy Framework for Grid Vulnerability Alleviation under Cyber-Stealthy Intrusions," Mathematics, MDPI, vol. 10(14), pages 1-20, July.
    5. Han, Fengwu & Zhao, Yunlong & Zeng, Jianfeng & Zhang, Shengnan & Wu, Tianyu, 2024. "Uncertain parameters adjustable two-stage robust optimization of a rural housing integrated energy system considering biomass on-site utilization," Energy, Elsevier, vol. 296(C).
    6. Zhang, Rongquan & Bu, Siqi & Li, Gangqiang, 2024. "Multi-market P2P trading of cooling–heating-power-hydrogen integrated energy systems: An equilibrium-heuristic online prediction optimization approach," Applied Energy, Elsevier, vol. 367(C).
    7. Zhou, Yizhou & Ge, Jingyu & Li, Xiang & Zang, Haixiang & Chen, Sheng & Sun, Guoqiang & Wei, Zhinong, 2024. "Bi-level distributionally robust optimization model for low-carbon planning of integrated electricity and heat systems," Energy, Elsevier, vol. 302(C).
    8. Tan, Hong & Li, Zhenxing & Wang, Qiujie & Mohamed, Mohamed A., 2023. "A novel forecast scenario-based robust energy management method for integrated rural energy systems with greenhouses," Applied Energy, Elsevier, vol. 330(PB).
    9. Liang, Weikun & Lin, Shunjiang & Liu, Mingbo & Sheng, Xuan & Pan, Yue & Liu, Yun, 2023. "Risk assessment for cascading failures in regional integrated energy system considering the pipeline dynamics," Energy, Elsevier, vol. 270(C).

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