IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v216y2021ics0360544220322787.html

A data-driven distributionally robust optimization model for multi-energy coupled system considering the temporal-spatial correlation and distribution uncertainty of renewable energy sources

Author

Listed:
  • Zhang, Yachao
  • Liu, Yan
  • Shu, Shengwen
  • Zheng, Feng
  • Huang, Zhanghao

Abstract

The increasing expansion of wind and gas turbine installation has intensified the interdependency between power system and natural gas network, which poses great challenges to the coordination scheduling of the multi-energy coupled system (MECS). The data-driven robust optimization (DDRO) model is proposed for the energy coupled system. In this model, the temporal-spatial correlation of wind power can be considered based on the minimum volume enclosing convex hull uncertainty set, and the confidence set about the probability distribution for wind power scenarios with the form of the norm-1 and norm-inf constraints is constructed to handle wind power uncertainty. Moreover, to describe natural gas transient characteristics, the hydrodynamic model for gas flow represented as a series of partial differential equations is transformed by the Wendroff difference scheme and linearization technique. And then the master-subproblem framework and tri-level duality-free decomposition method is developed to solve the above model. Finally, the proposed model and solving method are carried out on two test systems with different scale, and the robust optimization models and distributionally optimization models in the existing literatures are implemented for comparison. Simulation results demonstrate the effectiveness and superiority of the proposed model for solving the coordination scheduling problem of MECS.

Suggested Citation

  • Zhang, Yachao & Liu, Yan & Shu, Shengwen & Zheng, Feng & Huang, Zhanghao, 2021. "A data-driven distributionally robust optimization model for multi-energy coupled system considering the temporal-spatial correlation and distribution uncertainty of renewable energy sources," Energy, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:energy:v:216:y:2021:i:c:s0360544220322787
    DOI: 10.1016/j.energy.2020.119171
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544220322787
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2020.119171?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Kuriqi, Alban & Pinheiro, António N. & Sordo-Ward, Alvaro & Garrote, Luis, 2019. "Flow regime aspects in determining environmental flows and maximising energy production at run-of-river hydropower plants," Applied Energy, Elsevier, vol. 256(C).
    2. He, Chuan & Wu, Lei & Liu, Tianqi & Wei, Wei & Wang, Cheng, 2018. "Co-optimization scheduling of interdependent power and gas systems with electricity and gas uncertainties," Energy, Elsevier, vol. 159(C), pages 1003-1015.
    3. Pantoš, Miloš, 2011. "Market-based congestion management in electric power systems with increased share of natural gas dependent power plants," Energy, Elsevier, vol. 36(7), pages 4244-4255.
    4. Zhang, Yachao & Huang, Zhanghao & Zheng, Feng & Zhou, Rongyu & Le, Jian & An, Xueli, 2020. "Cooperative optimization scheduling of the electricity-gas coupled system considering wind power uncertainty via a decomposition-coordination framework," Energy, Elsevier, vol. 194(C).
    5. Zhang, Yachao & Le, Jian & Zheng, Feng & Zhang, Yi & Liu, Kaipei, 2019. "Two-stage distributionally robust coordinated scheduling for gas-electricity integrated energy system considering wind power uncertainty and reserve capacity configuration," Renewable Energy, Elsevier, vol. 135(C), pages 122-135.
    6. Ding, Tao & Lv, Jiajun & Bo, Rui & Bie, Zhaohong & Li, Fangxing, 2016. "Lift-and-project MVEE based convex hull for robust SCED with wind power integration using historical data-driven modeling approach," Renewable Energy, Elsevier, vol. 92(C), pages 415-427.
    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. Zhang, Yachao & Liu, Wei & Huang, Zhanghao & Zheng, Feng & Le, Jian & Zhu, Shu, 2021. "Distributionally robust coordination optimization scheduling for electricity-gas-transportation coupled system considering multiple uncertainties," Renewable Energy, Elsevier, vol. 163(C), pages 2037-2052.
    2. Hosseini, Seyed Hamid Reza & Allahham, Adib & Walker, Sara Louise & Taylor, Phil, 2021. "Uncertainty analysis of the impact of increasing levels of gas and electricity network integration and storage on Techno-Economic-Environmental performance," Energy, Elsevier, vol. 222(C).
    3. Zhang, Yachao & Huang, Zhanghao & Zheng, Feng & Zhou, Rongyu & Le, Jian & An, Xueli, 2020. "Cooperative optimization scheduling of the electricity-gas coupled system considering wind power uncertainty via a decomposition-coordination framework," Energy, Elsevier, vol. 194(C).
    4. Faridpak, Behdad & Farrokhifar, Meisam & Murzakhanov, Ilgiz & Safari, Amin, 2020. "A series multi-step approach for operation Co-optimization of integrated power and natural gas systems," Energy, Elsevier, vol. 204(C).
    5. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Gao, Chong & Ma, Zeyang, 2023. "A novel two-layer nested optimization method for a zero-carbon island integrated energy system, incorporating tidal current power generation," Renewable Energy, Elsevier, vol. 218(C).
    6. Sayed, Ahmed Rabee & Wang, Cheng & Chen, Sheng & Shang, Ce & Bi, Tianshu, 2021. "Distributionally robust day-ahead operation of power systems with two-stage gas contracting," Energy, Elsevier, vol. 231(C).
    7. 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).
    8. 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).
    9. Wang, Yang & Zhang, Shanhong & Chow, David & Kuckelkorn, Jens M., 2021. "Evaluation and optimization of district energy network performance: Present and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    10. Zhou, Dengji & Yan, Siyun & Huang, Dawen & Shao, Tiemin & Xiao, Wang & Hao, Jiarui & Wang, Chen & Yu, Tianqi, 2022. "Modeling and simulation of the hydrogen blended gas-electricity integrated energy system and influence analysis of hydrogen blending modes," Energy, Elsevier, vol. 239(PA).
    11. Zhai, Yijie & Ma, Xiaotian & Gao, Feng & Zhang, Tianzuo & Hong, Jinglan & Zhang, Xu & Yuan, Xueliang & Li, Xiangzhi, 2020. "Is energy the key to pursuing clean air and water at the city level? A case study of Jinan City, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    12. Jiang, Hou & Lu, Ning & Huang, Guanghui & Yao, Ling & Qin, Jun & Liu, Hengzi, 2020. "Spatial scale effects on retrieval accuracy of surface solar radiation using satellite data," Applied Energy, Elsevier, vol. 270(C).
    13. Feng, Qianqian & Sun, Xiaolei & Hao, Jun & Li, Jianping, 2021. "Predictability dynamics of multifactor-influenced installed capacity: A perspective of country clustering," Energy, Elsevier, vol. 214(C).
    14. Bao, Minglei & Hui, Hengyu & Ding, Yi & Sun, Xiaocong & Zheng, Chenghang & Gao, Xiang, 2023. "An efficient framework for exploiting operational flexibility of load energy hubs in risk management of integrated electricity-gas systems," Applied Energy, Elsevier, vol. 338(C).
    15. Guo, Liang-Liang & Zhang, Yong-Bo & Wang, Zhi-Chao & Zeng, Jian & Zhang, Yan-Jun & Zhang, Zhi-Xiang, 2020. "Parameter sensitivity analysis and optimization strategy research of enhanced geothermal system: A case study in Guide Basin, Northwestern China," Renewable Energy, Elsevier, vol. 153(C), pages 813-831.
    16. Jiang, Aihua & Yuan, Huihong & Li, Delong, 2021. "Energy management for a community-level integrated energy system with photovoltaic prosumers based on bargaining theory," Energy, Elsevier, vol. 225(C).
    17. Li, Yanbin & Zhang, Feng & Li, Yun & Wang, Yuwei, 2021. "An improved two-stage robust optimization model for CCHP-P2G microgrid system considering multi-energy operation under wind power outputs uncertainties," Energy, Elsevier, vol. 223(C).
    18. Zhou, Liangsong & Wei, Xiaolong & Suvorov, Anton & Safaraliev, Murodbek, 2024. "Operation of coupled power-gas networks with hydrogen refueling stations, responsive demands and storage systems: A novel stochastic framework," Energy, Elsevier, vol. 309(C).
    19. Golpîra, Hêriş, 2020. "Smart Energy-Aware Manufacturing Plant Scheduling under Uncertainty: A Risk-Based Multi-Objective Robust Optimization Approach," Energy, Elsevier, vol. 209(C).
    20. Ninad Bhagwat & Xiaobing Zhou, 2023. "Locating Potential Run-of-River Hydropower Sites by Developing Novel Parsimonious Multi-Dimensional Moving Window (PMMW) Algorithm with Digital Elevation Models," Energies, MDPI, vol. 16(19), pages 1-20, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:216:y:2021:i:c:s0360544220322787. 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.