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Bilevel Optimal Dispatch Strategy for a Multi-Energy System of Industrial Parks by Considering Integrated Demand Response

Author

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  • Yuehao Zhao

    (School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, Shandong, China)

  • Ke Peng

    (School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, Shandong, China)

  • Bingyin Xu

    (School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, Shandong, China)

  • Huimin Li

    (School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, Shandong, China)

  • Yuquan Liu

    (Guangzhou Power Supply Bureau Co. Ltd., Guangzhou 510620, Guangdong, China)

  • Xinhui Zhang

    (School of Electrical and Electronic Engineering, Shandong University of Technology, Zibo 255000, Shandong, China)

Abstract

To combat energy shortage, the multi-energy system has gained increasing interest in contemporary society. In order to fully utilize adjustable multi-energy resources on the demand side and reduce interactive compensation, this paper presents an integrated demand response (IDR) model in consideration of conventional load-shedding and novel resource-shifting, due to the fact that participants in IDR can use more abundant resources to reduce the consumption of energy. In the proposed IDR, cooling, heating, electricity, gas and so forth are considered, which takes the connection between compensation and load reductions into consideration. Furthermore, a bilevel optimal dispatch strategy is proposed to decrease the difficulty in coordinated control and interaction between lower-level factories and upper-level multi-energy operators in industrial parks. In this strategy, resources in both multi-energy operator and user sides are optimally controlled and scheduled to maximize the benefits under peak shifting constraint. In the normal operation mode, this strategy can maximize the benefits to users and multi-energy operators. Particularly in heavy load conditions, compared to the conventional electricity demand response, there are more types of adjustable resources, more flexibility, and lower interactive compensations in IDR. The results indicate that optimal operation for factories and multi-energy operators can be achieved under peak shifting constraint and the overall peak power value in industrial park is reduced.

Suggested Citation

  • Yuehao Zhao & Ke Peng & Bingyin Xu & Huimin Li & Yuquan Liu & Xinhui Zhang, 2018. "Bilevel Optimal Dispatch Strategy for a Multi-Energy System of Industrial Parks by Considering Integrated Demand Response," Energies, MDPI, vol. 11(8), pages 1-21, July.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:1942-:d:160106
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    References listed on IDEAS

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    1. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    2. Jin, Xiaolong & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Jiang, Tao & Yu, Xiaodan, 2017. "Dynamic economic dispatch of a hybrid energy microgrid considering building based virtual energy storage system," Applied Energy, Elsevier, vol. 194(C), pages 386-398.
    3. Marzband, Mousa & Azarinejadian, Fatemeh & Savaghebi, Mehdi & Pouresmaeil, Edris & Guerrero, Josep M. & Lightbody, Gordon, 2018. "Smart transactive energy framework in grid-connected multiple home microgrids under independent and coalition operations," Renewable Energy, Elsevier, vol. 126(C), pages 95-106.
    4. Wang, Jianxiao & Zhong, Haiwang & Ma, Ziming & Xia, Qing & Kang, Chongqing, 2017. "Review and prospect of integrated demand response in the multi-energy system," Applied Energy, Elsevier, vol. 202(C), pages 772-782.
    5. Graus, W.H.J. & Voogt, M. & Worrell, E., 2007. "International comparison of energy efficiency of fossil power generation," Energy Policy, Elsevier, vol. 35(7), pages 3936-3951, July.
    6. Li, Yajun & Xia, Yan, 2013. "DES/CCHP: The best utilization mode of natural gas for China’s low carbon economy," Energy Policy, Elsevier, vol. 53(C), pages 477-483.
    7. Sheikhi, Aras & Bahrami, Shahab & Ranjbar, Ali Mohammad, 2015. "An autonomous demand response program for electricity and natural gas networks in smart energy hubs," Energy, Elsevier, vol. 89(C), pages 490-499.
    8. Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.
    9. Baker, John, 2008. "New technology and possible advances in energy storage," Energy Policy, Elsevier, vol. 36(12), pages 4368-4373, December.
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    Cited by:

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    2. Morteza Vahid-Ghavidel & Mohammad Sadegh Javadi & Matthew Gough & Sérgio F. Santos & Miadreza Shafie-khah & João P.S. Catalão, 2020. "Demand Response Programs in Multi-Energy Systems: A Review," Energies, MDPI, vol. 13(17), pages 1-17, August.
    3. Changrong Liu & Hanqing Wang & Zhiqiang Liu & Zhiyong Wang & Sheng Yang, 2021. "Research on a Bi-Level Collaborative Optimization Method for Planning and Operation of Multi-Energy Complementary Systems," Energies, MDPI, vol. 14(23), pages 1-20, November.
    4. Tostado-Véliz, Marcos & Rezaee Jordehi, Ahmad & Mansouri, Seyed Amir & Zhou, Yuekuan & Jurado, Francisco, 2024. "A local electricity-hydrogen market model for industrial parks," Applied Energy, Elsevier, vol. 360(C).
    5. Dezhou Kong & Jianru Jing & Tingyue Gu & Xuanyue Wei & Xingning Sa & Yimin Yang & Zhiang Zhang, 2023. "Theoretical Analysis of Integrated Community Energy Systems (ICES) Considering Integrated Demand Response (IDR): A Review of the System Modelling and Optimization," Energies, MDPI, vol. 16(10), pages 1-22, May.
    6. Gu, Haifei & Li, Yang & Yu, Jie & Wu, Chen & Song, Tianli & Xu, Jinzhou, 2020. "Bi-level optimal low-carbon economic dispatch for an industrial park with consideration of multi-energy price incentives," Applied Energy, Elsevier, vol. 262(C).
    7. Turdybek, Balgynbek & Tostado-Véliz, Marcos & Mansouri, Seyed Amir & Rezaee Jordehi, Ahmad & Jurado, Francisco, 2024. "A local electricity market mechanism for flexibility provision in industrial parks involving Heterogenous flexible loads," Applied Energy, Elsevier, vol. 359(C).

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