IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i21p7302-d1269066.html
   My bibliography  Save this article

Robust Bilevel Optimal Dispatch of Park Integrated Energy System Considering Renewable Energy Uncertainty

Author

Listed:
  • Puming Wang

    (Guangxi Key Laboratory of Power System Optimization and Energy Technology, School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Liqin Zheng

    (State Grid Xiamen Electric Power Supply Company, Xiamen 361004, China)

  • Tianyi Diao

    (State Grid Liaocheng Power Supply Company, Liaocheng 252000, China)

  • Shengquan Huang

    (Guangxi Key Laboratory of Power System Optimization and Energy Technology, School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Xiaoqing Bai

    (Guangxi Key Laboratory of Power System Optimization and Energy Technology, School of Electrical Engineering, Guangxi University, Nanning 530004, China)

Abstract

This paper focuses on optimizing the park integrated energy system (PIES) operation, and a robust bilevel optimal dispatch is proposed. Firstly, the robust uncertainty set is constructed based on the K-means++ algorithm to solve the uncertainty of renewable energy sources output in PIES. Then, the bi-level dispatch model is proposed, with the operator as the leader and consumers as the follower. The upper model establishes an electricity-heat-gas integrated energy network, and the lower model considers the demand response of consumers. Optimizing the pricing strategies of energy sources to determine the output of each energy conversion equipment and the demand response plan. Moreover, analyzing the decision-making process of the robust bi-level model and the solution method is given. Finally, case studies show that the proposed dispatch model can increase operator profits and reduce consumers’ energy costs. The in-sample and out-of-sample simulations demonstrate that the proposed ellipsoid uncertainty set possesses high compactness, good robustness, and low conservatism.

Suggested Citation

  • Puming Wang & Liqin Zheng & Tianyi Diao & Shengquan Huang & Xiaoqing Bai, 2023. "Robust Bilevel Optimal Dispatch of Park Integrated Energy System Considering Renewable Energy Uncertainty," Energies, MDPI, vol. 16(21), pages 1-23, October.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:21:p:7302-:d:1269066
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/21/7302/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/21/7302/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zifa Liu & Chengchen Li, 2023. "Low-Carbon Economic Optimization of Integrated Energy System Considering Refined Utilization of Hydrogen Energy and Generalized Energy Storage," Energies, MDPI, vol. 16(15), pages 1-23, July.
    2. Beck, Yasmine & Ljubić, Ivana & Schmidt, Martin, 2023. "A survey on bilevel optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 311(2), pages 401-426.
    3. 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.
    4. Burak Kocuk & Santanu S. Dey & X. Andy Sun, 2016. "Strong SOCP Relaxations for the Optimal Power Flow Problem," Operations Research, INFORMS, vol. 64(6), pages 1177-1196, December.
    5. Johanna Burtscheidt & Matthias Claus, 2020. "Bilevel Linear Optimization Under Uncertainty," Springer Optimization and Its Applications, in: Stephan Dempe & Alain Zemkoho (ed.), Bilevel Optimization, chapter 0, pages 485-511, Springer.
    6. Fan Li & Jingxi Su & Bo Sun, 2023. "An Optimal Scheduling Method for an Integrated Energy System Based on an Improved k-Means Clustering Algorithm," Energies, MDPI, vol. 16(9), pages 1-22, April.
    7. Qin, Xin & Sun, Hongbin & Shen, Xinwei & Guo, Ye & Guo, Qinglai & Xia, Tian, 2019. "A generalized quasi-dynamic model for electric-heat coupling integrated energy system with distributed energy resources," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    8. Jiang, Sheng-Long & Peng, Gongzhuang & Bogle, I. David L. & Zheng, Zhong, 2022. "Two-stage robust optimization approach for flexible oxygen distribution under uncertainty in integrated iron and steel plants," Applied Energy, Elsevier, vol. 306(PB).
    Full references (including those not matched with items on IDEAS)

    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. Yasmine Beck & Daniel Bienstock & Martin Schmidt & Johannes Thürauf, 2023. "On a Computationally Ill-Behaved Bilevel Problem with a Continuous and Nonconvex Lower Level," Journal of Optimization Theory and Applications, Springer, vol. 198(1), pages 428-447, July.
    2. Wang, Yongli & Li, Jiapu & Wang, Shuo & Yang, Jiale & Qi, Chengyuan & Guo, Hongzhen & Liu, Ximei & Zhang, Hongqing, 2020. "Operational optimization of wastewater reuse integrated energy system," Energy, Elsevier, vol. 200(C).
    3. Che, Gelegen & Zhang, Yanyan & Tang, Lixin & Zhao, Shengnan, 2023. "A deep reinforcement learning based multi-objective optimization for the scheduling of oxygen production system in integrated iron and steel plants," Applied Energy, Elsevier, vol. 345(C).
    4. Beck, Yasmine & Ljubić, Ivana & Schmidt, Martin, 2023. "A survey on bilevel optimization under uncertainty," European Journal of Operational Research, Elsevier, vol. 311(2), pages 401-426.
    5. Jiang, Sheng-Long & Wang, Meihong & Bogle, I. David L., 2023. "Plant-wide byproduct gas distribution under uncertainty in iron and steel industry via quantile forecasting and robust optimization," Applied Energy, Elsevier, vol. 350(C).
    6. Savelli, Iacopo & Morstyn, Thomas, 2021. "Electricity prices and tariffs to keep everyone happy: A framework for fixed and nodal prices coexistence in distribution grids with optimal tariffs for investment cost recovery," Omega, Elsevier, vol. 103(C).
    7. Zhang, Suhan & Gu, Wei & Lu, Hai & Qiu, Haifeng & Lu, Shuai & Wang, Dada & Liang, Junyu & Li, Wenyun, 2021. "Superposition-principle based decoupling method for energy flow calculation in district heating networks," Applied Energy, Elsevier, vol. 295(C).
    8. Le Cadre, Hélène & Mezghani, Ilyès & Papavasiliou, Anthony, 2019. "A game-theoretic analysis of transmission-distribution system operator coordination," European Journal of Operational Research, Elsevier, vol. 274(1), pages 317-339.
    9. Zhang, Suhan & Gu, Wei & Qiu, Haifeng & Yao, Shuai & Pan, Guangsheng & Chen, Xiaogang, 2021. "State estimation models of district heating networks for integrated energy system considering incomplete measurements," Applied Energy, Elsevier, vol. 282(PA).
    10. Haoxiang Yang & David P. Morton & Chaithanya Bandi & Krishnamurthy Dvijotham, 2021. "Robust Optimization for Electricity Generation," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 336-351, January.
    11. Jay, Devika & Swarup, K.S., 2021. "A comprehensive survey on reactive power ancillary service markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    12. Pan, Zhenning & Yu, Tao & Li, Jie & Qu, Kaiping & Yang, Bo, 2020. "Risk-averse real-time dispatch of integrated electricity and heat system using a modified approximate dynamic programming approach," Energy, Elsevier, vol. 198(C).
    13. Blom, Danny & Smeulders, Bart & Spieksma, Frits, 2024. "Rejection-proof mechanisms for multi-agent kidney exchange," Games and Economic Behavior, Elsevier, vol. 143(C), pages 25-50.
    14. Subramanian, Vignesh & Feijoo, Felipe & Sankaranarayanan, Sriram & Melendez, Kevin & Das, Tapas K., 2022. "A bilevel conic optimization model for routing and charging of EV fleets serving long distance delivery networks," Energy, Elsevier, vol. 251(C).
    15. Tian, Hang & Zhao, Haoran & Liu, Chunyang & Chen, Jian & Wu, Qiuwei & Terzija, Vladimir, 2022. "A dual-driven linear modeling approach for multiple energy flow calculation in electricity–heat system," Applied Energy, Elsevier, vol. 314(C).
    16. Wogrin, S. & Tejada-Arango, D. & Delikaraoglou, S. & Botterud, A., 2020. "Assessing the impact of inertia and reactive power constraints in generation expansion planning," Applied Energy, Elsevier, vol. 280(C).
    17. Tian, Xingtao & Lin, Xiaojie & Zhong, Wei & Zhou, Yi, 2022. "Security assessment of electricity-gas-heat integrated energy systems based on the vulnerability index," Energy, Elsevier, vol. 249(C).
    18. 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).
    19. Zhang, Hanxin & Sun, Wenqiang & Li, Weidong & Ma, Guangyu, 2022. "A carbon flow tracing and carbon accounting method for exploring CO2 emissions of the iron and steel industry: An integrated material–energy–carbon hub," Applied Energy, Elsevier, vol. 309(C).
    20. Massimiliano Caramia, 2024. "An algorithm to find stable solutions in linear–linear bilevel problems," OPSEARCH, Springer;Operational Research Society of India, vol. 61(2), pages 972-988, June.

    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:gam:jeners:v:16:y:2023:i:21:p:7302-:d:1269066. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.