IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i9p2448-d169961.html
   My bibliography  Save this article

Linearized Stochastic Scheduling of Interconnected Energy Hubs Considering Integrated Demand Response and Wind Uncertainty

Author

Listed:
  • Yining Zhang

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Yubin He

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Mingyu Yan

    (Electrical and Computer Engineering Department, Illinois Institute of Technology, Chicago, IL 60616, USA)

  • Chuangxin Guo

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Yi Ding

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

Abstract

In the context of the Energy Internet, customers are supplied by energy hubs (EH), while the EHs are interconnected through an upper-level transmission system. In this paper, a stochastic scheduling model is proposed for the interconnected EHs considering integrated demand response (DR) and wind variation. The whole integrated energy system (IES) is linearly modeled for the first time. The output-input relationship within the energy hub is denoted as a linearized matrix, while the upper-level power and natural gas transmission systems are analyzed through piecewise linearization method. A novel sequential linearization method is further proposed to balance computational efficiency and approximation accuracy. Integrated demand response is introduced to smooth out demand curve, considering both internal DR achieved by the optimal energy conversion strategy within energy hubs, and external DR achieved by demand adjustment on the customer’s side. Distributed energy storage like natural gas and heat storage are considered to provide buffer for system operation. The proposed stochastic model is solved by scenario-based optimization with a backward scenario reduction strategy. Numerical tests on a three-hub and seventeen-hub interconnected system that validates the effectiveness of the proposed scheduling model and solution methodology.

Suggested Citation

  • Yining Zhang & Yubin He & Mingyu Yan & Chuangxin Guo & Yi Ding, 2018. "Linearized Stochastic Scheduling of Interconnected Energy Hubs Considering Integrated Demand Response and Wind Uncertainty," Energies, MDPI, vol. 11(9), pages 1-23, September.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2448-:d:169961
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/9/2448/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/9/2448/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xianzheng Zhou & Chuangxin Guo & Yifei Wang & Wanqi Li, 2017. "Optimal Expansion Co-Planning of Reconfigurable Electricity and Natural Gas Distribution Systems Incorporating Energy Hubs," Energies, MDPI, vol. 10(1), pages 1-22, January.
    2. Feng Qi & Fushuan Wen & Xunyuan Liu & Md. Abdus Salam, 2017. "A Residential Energy Hub Model with a Concentrating Solar Power Plant and Electric Vehicles," Energies, MDPI, vol. 10(8), pages 1-17, August.
    3. Wang, Yi & Zhang, Ning & Zhuo, Zhenyu & Kang, Chongqing & Kirschen, Daniel, 2018. "Mixed-integer linear programming-based optimal configuration planning for energy hub: Starting from scratch," Applied Energy, Elsevier, vol. 210(C), pages 1141-1150.
    4. Yinuo Huang & Chuangxin Guo & Yi Ding & Licheng Wang & Bingquan Zhu & Lizhong Xu, 2016. "A Multi-Period Framework for Coordinated Dispatch of Plug-in Electric Vehicles," Energies, MDPI, vol. 9(5), pages 1-16, May.
    5. 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.
    6. Conrado Borraz-Sánchez & Russell Bent & Scott Backhaus & Hassan Hijazi & Pascal Van Hentenryck, 2016. "Convex Relaxations for Gas Expansion Planning," INFORMS Journal on Computing, INFORMS, vol. 28(4), pages 645-656, November.
    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. 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.
    2. Li, Peng & Wang, Zixuan & Liu, Haitao & Wang, Jiahao & Guo, Tianyu & Yin, Yunxing, 2021. "Bi-level optimal configuration strategy of community integrated energy system with coordinated planning and operation," Energy, Elsevier, vol. 236(C).
    3. Coelho, António & Iria, José & Soares, Filipe, 2021. "Network-secure bidding optimization of aggregators of multi-energy systems in electricity, gas, and carbon markets," Applied Energy, Elsevier, vol. 301(C).
    4. Guoqiang Sun & Wenxue Wang & Yi Wu & Wei Hu & Zijun Yang & Zhinong Wei & Haixiang Zang & Sheng Chen, 2019. "A Nonlinear Analytical Algorithm for Predicting the Probabilistic Mass Flow of a Radial District Heating Network," Energies, MDPI, vol. 12(7), pages 1-20, March.
    5. Xinyu Sun & Hao Wu & Siqi Guo & Lingwei Zheng, 2022. "Day-Ahead Optimal Scheduling of Integrated Energy System Based on Type-II Fuzzy Interval Chance-Constrained Programming," Energies, MDPI, vol. 15(18), pages 1-17, September.
    6. Mohammad Jooshaki & Ali Abbaspour & Mahmud Fotuhi-Firuzabad & Moein Moeini-Aghtaie & Matti Lehtonen, 2019. "Multistage Expansion Co-Planning of Integrated Natural Gas and Electricity Distribution Systems," Energies, MDPI, vol. 12(6), pages 1-16, March.
    7. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N., 2022. "Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    8. Li, Peng & Wang, Zixuan & Wang, Jiahao & Yang, Weihong & Guo, Tianyu & Yin, Yunxing, 2021. "Two-stage optimal operation of integrated energy system considering multiple uncertainties and integrated demand response," Energy, Elsevier, vol. 225(C).
    9. Wang, Zixuan & Li, Peng & Zhou, Yue & Wu, Jianzhong & Zhang, Chunyan & Zeng, Pingliang & Wang, Jiahao & Pan, Youpeng & Yin, Yunxing, 2023. "Coordinated configuration strategy of multi-energy systems based on capacity-energy-information sharing," Energy, Elsevier, vol. 277(C).
    10. Chengyu Zeng & Yuechun Jiang & Yuqing Liu & Zuoyun Tan & Zhongnan He & Shuhong Wu, 2019. "Optimal Dispatch of Integrated Energy System Considering Energy Hub Technology and Multi-Agent Interest Balance," Energies, MDPI, vol. 12(16), pages 1-17, August.
    11. Yizhi Cheng & Peichao Zhang & Xuezhi Liu, 2019. "Collaborative Autonomous Optimization of Interconnected Multi-Energy Systems with Two-Stage Transactive Control Framework," Energies, MDPI, vol. 13(1), pages 1-21, December.

    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. Patrick Sunday Onen & Geev Mokryani & Rana H. A. Zubo, 2022. "Planning of Multi-Vector Energy Systems with High Penetration of Renewable Energy Source: A Comprehensive Review," Energies, MDPI, vol. 15(15), pages 1-25, August.
    2. Mittelviefhaus, Moritz & Pareschi, Giacomo & Allan, James & Georges, Gil & Boulouchos, Konstantinos, 2021. "Optimal investment and scheduling of residential multi-energy systems including electric mobility: A cost-effective approach to climate change mitigation," Applied Energy, Elsevier, vol. 301(C).
    3. 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).
    4. Ramos-Teodoro, Jerónimo & Rodríguez, Francisco & Berenguel, Manuel & Torres, José Luis, 2018. "Heterogeneous resource management in energy hubs with self-consumption: Contributions and application example," Applied Energy, Elsevier, vol. 229(C), pages 537-550.
    5. Heendeniya, Charitha Buddhika & Sumper, Andreas & Eicker, Ursula, 2020. "The multi-energy system co-planning of nearly zero-energy districts – Status-quo and future research potential," Applied Energy, Elsevier, vol. 267(C).
    6. Lin, Haiyang & Liu, Yiling & Sun, Qie & Xiong, Rui & Li, Hailong & Wennersten, Ronald, 2018. "The impact of electric vehicle penetration and charging patterns on the management of energy hub – A multi-agent system simulation," Applied Energy, Elsevier, vol. 230(C), pages 189-206.
    7. Pierpaolo Garavaso & Fabio Bignucolo & Jacopo Vivian & Giulia Alessio & Michele De Carli, 2021. "Optimal Planning and Operation of a Residential Energy Community under Shared Electricity Incentives," Energies, MDPI, vol. 14(8), pages 1-24, April.
    8. Alaa Farah & Hamdy Hassan & Alaaeldin M. Abdelshafy & Abdelfatah M. Mohamed, 2020. "Optimal Scheduling of Hybrid Multi-Carrier System Feeding Electrical/Thermal Load Based on Particle Swarm Algorithm," Sustainability, MDPI, vol. 12(11), pages 1-21, June.
    9. Liu, Tianhao & Tian, Jun & Zhu, Hongyu & Goh, Hui Hwang & Liu, Hui & Wu, Thomas & Zhang, Dongdong, 2023. "Key technologies and developments of multi-energy system: Three-layer framework, modelling and optimisation," Energy, Elsevier, vol. 277(C).
    10. Xu, Xiao & Hu, Weihao & Liu, Wen & Du, Yuefang & Huang, Rui & Huang, Qi & Chen, Zhe, 2021. "Look-ahead risk-constrained scheduling for an energy hub integrated with renewable energy," Applied Energy, Elsevier, vol. 297(C).
    11. Yi, Ji Hyun & Ko, Woong & Park, Jong-Keun & Park, Hyeongon, 2018. "Impact of carbon emission constraint on design of small scale multi-energy system," Energy, Elsevier, vol. 161(C), pages 792-808.
    12. Cheng, Yaohua & Zhang, Ning & Kirschen, Daniel S. & Huang, Wujing & Kang, Chongqing, 2020. "Planning multiple energy systems for low-carbon districts with high penetration of renewable energy: An empirical study in China," Applied Energy, Elsevier, vol. 261(C).
    13. Tsoumalis, Georgios I. & Bampos, Zafeirios N. & Biskas, Pandelis N. & Keranidis, Stratos D. & Symeonidis, Polychronis A. & Voulgarakis, Dimitrios K., 2022. "A novel system for providing explicit demand response from domestic natural gas boilers," Applied Energy, Elsevier, vol. 317(C).
    14. Wang, Yi & Qiu, Dawei & Sun, Mingyang & Strbac, Goran & Gao, Zhiwei, 2023. "Secure energy management of multi-energy microgrid: A physical-informed safe reinforcement learning approach," Applied Energy, Elsevier, vol. 335(C).
    15. Beatrice Castellani & Alberto Maria Gambelli & Elena Morini & Benedetto Nastasi & Andrea Presciutti & Mirko Filipponi & Andrea Nicolini & Federico Rossi, 2017. "Experimental Investigation on CO 2 Methanation Process for Solar Energy Storage Compared to CO 2 -Based Methanol Synthesis," Energies, MDPI, vol. 10(7), pages 1-13, June.
    16. Fambri, Gabriele & Diaz-Londono, Cesar & Mazza, Andrea & Badami, Marco & Sihvonen, Teemu & Weiss, Robert, 2022. "Techno-economic analysis of Power-to-Gas plants in a gas and electricity distribution network system with high renewable energy penetration," Applied Energy, Elsevier, vol. 312(C).
    17. 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).
    18. Mengying Xue & Tianhu Deng & Zuo‐Jun Max Shen, 2019. "Optimizing natural gas pipeline transmission with nonuniform elevation: A new initialization approach," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(7), pages 547-564, October.
    19. Ma, Huan & Sun, Qinghan & Chen, Qun & Zhao, Tian & He, Kelun, 2023. "Exergy-based flexibility cost indicator and spatio-temporal coordination principle of distributed multi-energy systems," Energy, Elsevier, vol. 267(C).
    20. Li, Yang & Wang, Bin & Yang, Zhen & Li, Jiazheng & Chen, Chen, 2022. "Hierarchical stochastic scheduling of multi-community integrated energy systems in uncertain environments via Stackelberg game," Applied Energy, Elsevier, vol. 308(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:gam:jeners:v:11:y:2018:i:9:p:2448-:d:169961. 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.