IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v311y2022ics0306261922000745.html
   My bibliography  Save this article

A low-carbon planning method for joint regional-district multi-energy systems: From the perspective of privacy protection

Author

Listed:
  • Gan, Wei
  • Yan, Mingyu
  • Wen, Jianfeng
  • Yao, Wei
  • Zhang, Jing

Abstract

The construction of the multi-energy system (MES) is regarded as one of the silver bullets that help construct a low-carbon and high-efficiency energy system. In addition to the synergy of multiple energy systems, the coordination of regional and district energy systems can further improve flexibility. However, current studies rarely focus on the joint planning of regional-district MES. Additionally, privacy protection has not been considered in multi-energy system planning yet. This paper proposes a novel low-carbon planning method for joint regional-district MES which ensures the privacy of regional and district energy systems based on the enhanced Benders decomposition. A new Benders cut generation method with refined iteration and improved convergence is designed for the planning model where the subproblem itself is the mixed-integer linear programming. To ensure convergence and optimality, supplementary Benders cuts for convergence restoration are also generated. Numerical results tested on a real-world MES in North China and a modified IEEE RTS-79 40-node MES show the effectiveness of the proposed planning method and solution technique. The simulation results validate that the proposed joint planning method can enhance the economic benefit of planning and reduce carbon emission, and the computational performance of the enhanced Benders decomposition is also validated from the perspectives of both computational accuracy and time. In the real-world MES, the joint planning method saves 8.8% of the total cost and reduces carbon emission by 11.1 % compared to the separate planning method.

Suggested Citation

  • Gan, Wei & Yan, Mingyu & Wen, Jianfeng & Yao, Wei & Zhang, Jing, 2022. "A low-carbon planning method for joint regional-district multi-energy systems: From the perspective of privacy protection," Applied Energy, Elsevier, vol. 311(C).
    • Handle: RePEc:eee:appene:v:311:y:2022:i:c:s0306261922000745
    DOI: 10.1016/j.apenergy.2022.118595
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922000745
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.118595?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. Chaudry, Modassar & Jenkins, Nick & Qadrdan, Meysam & Wu, Jianzhong, 2014. "Combined gas and electricity network expansion planning," Applied Energy, Elsevier, vol. 113(C), pages 1171-1187.
    2. 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.
    3. Qadrdan, Meysam & Cheng, Meng & Wu, Jianzhong & Jenkins, Nick, 2017. "Benefits of demand-side response in combined gas and electricity networks," Applied Energy, Elsevier, vol. 192(C), pages 360-369.
    4. 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.
    5. Zhang, Ning & Lu, Xi & McElroy, Michael B. & Nielsen, Chris P. & Chen, Xinyu & Deng, Yu & Kang, Chongqing, 2016. "Reducing curtailment of wind electricity in China by employing electric boilers for heat and pumped hydro for energy storage," Applied Energy, Elsevier, vol. 184(C), pages 987-994.
    6. 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.
    7. Wang, Qin & Yao, Wei & Fang, Jiakun & Ai, Xiaomeng & Wen, Jinyu & Yang, Xiaobo & Xie, Hailian & Huang, Xing, 2020. "Dynamic modeling and small signal stability analysis of distributed photovoltaic grid-connected system with large scale of panel level DC optimizers," Applied Energy, Elsevier, vol. 259(C).
    8. Gan, Wei & Ai, Xiaomeng & Fang, Jiakun & Yan, Mingyu & Yao, Wei & Zuo, Wenping & Wen, Jinyu, 2019. "Security constrained co-planning of transmission expansion and energy storage," Applied Energy, Elsevier, vol. 239(C), pages 383-394.
    9. Gan, Wei & Yan, Mingyu & Yao, Wei & Wen, Jinyu, 2021. "Peer to peer transactive energy for multiple energy hub with the penetration of high-level renewable energy," Applied Energy, Elsevier, vol. 295(C).
    10. Chen, Jian & Yao, Wei & Zhang, Chuan-Ke & Ren, Yaxing & Jiang, Lin, 2019. "Design of robust MPPT controller for grid-connected PMSG-Based wind turbine via perturbation observation based nonlinear adaptive control," Renewable Energy, Elsevier, vol. 134(C), pages 478-495.
    11. 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).
    12. Cui, Hantao & Li, Fangxing & Hu, Qinran & Bai, Linquan & Fang, Xin, 2016. "Day-ahead coordinated operation of utility-scale electricity and natural gas networks considering demand response based virtual power plants," Applied Energy, Elsevier, vol. 176(C), pages 183-195.
    13. Li, Chengzhou & Wang, Ningling & Wang, Zhuo & Dou, Xiaoxiao & Zhang, Yumeng & Yang, Zhiping & Maréchal, François & Wang, Ligang & Yang, Yongping, 2022. "Energy hub-based optimal planning framework for user-level integrated energy systems: Considering synergistic effects under multiple uncertainties," Applied Energy, Elsevier, vol. 307(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. Yan, Mingyu & Teng, Fei & Gan, Wei & Yao, Wei & Wen, Jinyu, 2023. "Blockchain for secure decentralized energy management of multi-energy system using state machine replication," Applied Energy, Elsevier, vol. 337(C).
    2. Marcel Antal & Vlad Mihailescu & Tudor Cioara & Ionut Anghel, 2022. "Blockchain-Based Distributed Federated Learning in Smart Grid," Mathematics, MDPI, vol. 10(23), pages 1-19, November.
    3. Qiu, Dawei & Xue, Juxing & Zhang, Tingqi & Wang, Jianhong & Sun, Mingyang, 2023. "Federated reinforcement learning for smart building joint peer-to-peer energy and carbon allowance trading," Applied Energy, Elsevier, vol. 333(C).
    4. Zhu, Yilin & Xu, Yujie & Chen, Haisheng & Guo, Huan & Zhang, Hualiang & Zhou, Xuezhi & Shen, Haotian, 2023. "Optimal dispatch of a novel integrated energy system combined with multi-output organic Rankine cycle and hybrid energy storage," Applied Energy, Elsevier, vol. 343(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. Zhang, Menglin & Wu, Qiuwei & Wen, Jinyu & Pan, Bo & Qi, Shiqiang, 2020. "Two-stage stochastic optimal operation of integrated electricity and heat system considering reserve of flexible devices and spatial-temporal correlation of wind power," Applied Energy, Elsevier, vol. 275(C).
    2. Gan, Wei & Yan, Mingyu & Yao, Wei & Guo, Jianbo & Ai, Xiaomeng & Fang, Jiakun & Wen, Jinyu, 2021. "Decentralized computation method for robust operation of multi-area joint regional-district integrated energy systems with uncertain wind power," Applied Energy, Elsevier, vol. 298(C).
    3. Qiu, Dawei & Dong, Zihang & Zhang, Xi & Wang, Yi & Strbac, Goran, 2022. "Safe reinforcement learning for real-time automatic control in a smart energy-hub," Applied Energy, Elsevier, vol. 309(C).
    4. 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).
    5. Zheng, Jinfu & Zhou, Zhigang & Zhao, Jianing & Wang, Jinda, 2018. "Effects of the operation regulation modes of district heating system on an integrated heat and power dispatch system for wind power integration," Applied Energy, Elsevier, vol. 230(C), pages 1126-1139.
    6. Zheng, Jinfu & Zhou, Zhigang & Zhao, Jianing & Hu, Songtao & Wang, Jinda, 2021. "Effects of intermittent heating on an integrated heat and power dispatch system for wind power integration and corresponding operation regulation," Applied Energy, Elsevier, vol. 287(C).
    7. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    8. Zhang, Yang & Campana, Pietro Elia & Yang, Ying & Stridh, Bengt & Lundblad, Anders & Yan, Jinyue, 2018. "Energy flexibility from the consumer: Integrating local electricity and heat supplies in a building," Applied Energy, Elsevier, vol. 223(C), pages 430-442.
    9. Wang, Wenting & Yang, Dazhi & Huang, Nantian & Lyu, Chao & Zhang, Gang & Han, Xueying, 2022. "Irradiance-to-power conversion based on physical model chain: An application on the optimal configuration of multi-energy microgrid in cold climate," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    10. Yang, Bo & Zeng, Chunyuan & Li, Danyang & Guo, Zhengxun & Chen, Yijun & Shu, Hongchun & Cao, Pulin & Li, Zilin, 2022. "Improved immune genetic algorithm based TEG system reconfiguration under non-uniform temperature distribution," Applied Energy, Elsevier, vol. 325(C).
    11. 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).
    12. Kang Qian & Tong Lv & Yue Yuan, 2021. "Integrated Energy System Planning Optimization Method and Case Analysis Based on Multiple Factors and A Three-Level Process," Sustainability, MDPI, vol. 13(13), pages 1-22, July.
    13. Yang, Bo & Wang, Junting & Zhang, Xiaoshun & Yu, Lei & Shu, Hongchun & Yu, Tao & Sun, Liming, 2020. "Control of SMES systems in distribution networks with renewable energy integration: A perturbation estimation approach," Energy, Elsevier, vol. 202(C).
    14. Shi, Huaizhou & Blaauwbroek, Niels & Nguyen, Phuong H. & Kamphuis, René (I.G.), 2016. "Energy management in Multi-Commodity Smart Energy Systems with a greedy approach," Applied Energy, Elsevier, vol. 167(C), pages 385-396.
    15. Liao, Shiwu & Yao, Wei & Han, Xingning & Fang, Jiakun & Ai, Xiaomeng & Wen, Jinyu & He, Haibo, 2019. "An improved two-stage optimization for network and load recovery during power system restoration," Applied Energy, Elsevier, vol. 249(C), pages 265-275.
    16. Zhong, Xiaoqing & Zhong, Weifeng & Liu, Yi & Yang, Chao & Xie, Shengli, 2023. "A communication-efficient coalition graph game-based framework for electricity and carbon trading in networked energy hubs," Applied Energy, Elsevier, vol. 329(C).
    17. Pan, Zhaoguang & Guo, Qinglai & Sun, Hongbin, 2016. "Interactions of district electricity and heating systems considering time-scale characteristics based on quasi-steady multi-energy flow," Applied Energy, Elsevier, vol. 167(C), pages 230-243.
    18. Tan, Jin & Wu, Qiuwei & Hu, Qinran & Wei, Wei & Liu, Feng, 2020. "Adaptive robust energy and reserve co-optimization of integrated electricity and heating system considering wind uncertainty," Applied Energy, Elsevier, vol. 260(C).
    19. 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).
    20. 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).

    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:appene:v:311:y:2022:i:c:s0306261922000745. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.