IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v254y2022ipcs0360544222013019.html
   My bibliography  Save this article

Distributionally robust operation for integrated rural energy systems with broiler houses

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222013019
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2022.124398?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Narimani, Mohammad Rasoul, 2012. "An efficient scenario-based stochastic programming framework for multi-objective optimal micro-grid operation," Applied Energy, Elsevier, vol. 99(C), pages 455-470.
    2. Michalak, Piotr, 2014. "The simple hourly method of EN ISO 13790 standard in Matlab/Simulink: A comparative study for the climatic conditions of Poland," Energy, Elsevier, vol. 75(C), pages 568-578.
    3. Liu, Xuezhi & Wu, Jianzhong & Jenkins, Nick & Bagdanavicius, Audrius, 2016. "Combined analysis of electricity and heat networks," Applied Energy, Elsevier, vol. 162(C), pages 1238-1250.
    4. Wang, Yongli & Wang, Yudong & Huang, Yujing & Yang, Jiale & Ma, Yuze & Yu, Haiyang & Zeng, Ming & Zhang, Fuwei & Zhang, Yanfu, 2019. "Operation optimization of regional integrated energy system based on the modeling of electricity-thermal-natural gas network," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    5. Mohamed, Mohamed A., 2022. "A relaxed consensus plus innovation based effective negotiation approach for energy cooperation between smart grid and microgrid," Energy, Elsevier, vol. 252(C).
    6. Zhang, Menglin & Wu, Qiuwei & Wen, Jinyu & Lin, Zhongwei & Fang, Fang & Chen, Qun, 2021. "Optimal operation of integrated electricity and heat system: A review of modeling and solution methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    7. Tan, Hong & Yan, Wei & Ren, Zhouyang & Wang, Qiujie & Mohamed, Mohamed A., 2022. "A robust dispatch model for integrated electricity and heat networks considering price-based integrated demand response," Energy, Elsevier, vol. 239(PA).
    8. Skalyga, Mikhail & Wu, Qiuwei & Zhang, Menglin, 2021. "Uncertainty-fully-aware coordinated dispatch of integrated electricity and heat system," Energy, Elsevier, vol. 224(C).
    9. Raya-Armenta, Jose Maurilio & Bazmohammadi, Najmeh & Avina-Cervantes, Juan Gabriel & Sáez, Doris & Vasquez, Juan C. & Guerrero, Josep M., 2021. "Energy management system optimization in islanded microgrids: An overview and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    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. 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.
    2. 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).
    3. 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).

    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. 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).
    2. Fahad Alsokhiry & Pierluigi Siano & Andres Annuk & Mohamed A. Mohamed, 2022. "A Novel Time-of-Use Pricing Based Energy Management System for Smart Home Appliances: Cost-Effective Method," Sustainability, MDPI, vol. 14(21), pages 1-20, November.
    3. Luo, Xi & Liu, Yanfeng & Feng, Pingan & Gao, Yuan & Guo, Zhenxiang, 2021. "Optimization of a solar-based integrated energy system considering interaction between generation, network, and demand side," Applied Energy, Elsevier, vol. 294(C).
    4. Jona Maurer & Jochen Illerhaus & Pol Jané Soneira & Sören Hohmann, 2022. "Distributed Optimization of District Heating Networks Using Optimality Condition Decomposition," Energies, MDPI, vol. 15(18), pages 1-21, September.
    5. Alabi, Tobi Michael & Aghimien, Emmanuel I. & Agbajor, Favour D. & Yang, Zaiyue & Lu, Lin & Adeoye, Adebusola R. & Gopaluni, Bhushan, 2022. "A review on the integrated optimization techniques and machine learning approaches for modeling, prediction, and decision making on integrated energy systems," Renewable Energy, Elsevier, vol. 194(C), pages 822-849.
    6. Tan, Hong & Yan, Wei & Ren, Zhouyang & Wang, Qiujie & Mohamed, Mohamed A., 2022. "A robust dispatch model for integrated electricity and heat networks considering price-based integrated demand response," Energy, Elsevier, vol. 239(PA).
    7. Fahad Alsokhiry & Andres Annuk & Toivo Kabanen & Mohamed A. Mohamed, 2022. "A Malware Attack Enabled an Online Energy Strategy for Dynamic Wireless EVs within Transportation Systems," Mathematics, MDPI, vol. 10(24), pages 1-20, December.
    8. Liu, Xinrui & Hou, Min & Sun, Siluo & Wang, Jiawei & Sun, Qiuye & Dong, Chaoyu, 2022. "Multi-time scale optimal scheduling of integrated electricity and district heating systems considering thermal comfort of users: An enhanced-interval optimization method," Energy, Elsevier, vol. 254(PB).
    9. Li, Hang & Hou, Kai & Xu, Xiandong & Jia, Hongjie & Zhu, Lewei & Mu, Yunfei, 2022. "Probabilistic energy flow calculation for regional integrated energy system considering cross-system failures," Applied Energy, Elsevier, vol. 308(C).
    10. Hosseini, Seyed Hamid Reza & Allahham, Adib & Walker, Sara Louise & Taylor, Phil, 2020. "Optimal planning and operation of multi-vector energy networks: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    11. Wang, Jiangjiang & Deng, Hongda & Qi, Xiaoling, 2022. "Cost-based site and capacity optimization of multi-energy storage system in the regional integrated energy networks," Energy, Elsevier, vol. 261(PA).
    12. 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).
    13. Adrian Grimm & Patrik Schönfeldt & Herena Torio & Peter Klement & Benedikt Hanke & Karsten von Maydell & Carsten Agert, 2021. "Deduction of Optimal Control Strategies for a Sector-Coupled District Energy System," Energies, MDPI, vol. 14(21), pages 1-13, November.
    14. Chi, Lixun & Su, Huai & Zio, Enrico & Zhang, Jinjun & Li, Xueyi & Zhang, Li & Fan, Lin & Zhou, Jing & Bai, Hua, 2020. "Integrated Deterministic and Probabilistic Safety Analysis of Integrated Energy Systems with bi-directional conversion," Energy, Elsevier, vol. 212(C).
    15. Fu, Xueqian & Guo, Qinglai & Sun, Hongbin & Pan, Zhaoguang & Xiong, Wen & Wang, Li, 2017. "Typical scenario set generation algorithm for an integrated energy system based on the Wasserstein distance metric," Energy, Elsevier, vol. 135(C), pages 153-170.
    16. Kandpal, Bakul & Pareek, Parikshit & Verma, Ashu, 2022. "A robust day-ahead scheduling strategy for EV charging stations in unbalanced distribution grid," Energy, Elsevier, vol. 249(C).
    17. Zhang, Xi & Geng, Yong & Shao, Shuai & Wilson, Jeffrey & Song, Xiaoqian & You, Wei, 2020. "China’s non-fossil energy development and its 2030 CO2 reduction targets: The role of urbanization," Applied Energy, Elsevier, vol. 261(C).
    18. Chunyi Wang & Fengzhang Luo & Zheng Jiao & Xiaolei Zhang & Zhipeng Lu & Yanshuo Wang & Ren Zhao & Yang Yang, 2022. "An Enhanced Second-Order Cone Programming-Based Evaluation Method on Maximum Hosting Capacity of Solar Energy in Distribution Systems with Integrated Energy," Energies, MDPI, vol. 15(23), pages 1-19, November.
    19. Lan, Puzhe & Han, Dong & Xu, Xiaoyuan & Yan, Zheng & Ren, Xijun & Xia, Shiwei, 2022. "Data-driven state estimation of integrated electric-gas energy system," Energy, Elsevier, vol. 252(C).
    20. Li, Weiwei & Qian, Tong & Zhao, Wei & Huang, Wenwei & Zhang, Yin & Xie, Xuehua & Tang, Wenhu, 2023. "Decentralized optimization for integrated electricity–heat systems with data center based energy hub considering communication packet loss," Applied Energy, Elsevier, vol. 350(C).

    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:eee:energy:v:254:y:2022:i:pc:s0360544222013019. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.