IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v224y2024ics0960148124001678.html
   My bibliography  Save this article

Optimal scheduling of integrated energy system using decoupled distributed CSO with opposition-based learning and neighborhood re-dispatch strategy

Author

Listed:
  • Meng, Anbo
  • Wu, Zhenbo
  • Zhang, Zhan
  • Xu, Xuancong
  • Tang, Yanshu
  • Xie, Zhifeng
  • Xian, Zikang
  • Zhang, Haitao
  • Luo, Jianqiang
  • Wang, Yu
  • Yan, Baiping
  • Yin, Hao

Abstract

Integrated energy optimization scheduling (IEOS) is a complex problem aiming to minimize the total cost while the requirements of load balance is met. Due to the non-convex, non-differentiable and high-dimensional characteristics, there are many difficulties in solving the problem. Based on a regional integrated energy system (RIES), a decoupled distributed crisscross optimization with opposition-based learning and neighborhood re-dispatch strategy (DDCSO-OBL-NR) is proposed to solve IEOS problem by distributed method with different energy types as the scale. Initially, the CSO with excellent global search ability is firstly used to solve the complicated IEOS problem. Then, based on the distributed structure, distributed parallel computing can be achieved by DDCSO, which contributes to 1) protect the privacy of different energy data, 2) reduce the solving dimensions and 3) relieve the heavy communication burden. The total optimal cost is achieved by minimizing the cost of each portion without centralized controller. Furthermore, the opposition-based learning (OBL) strategy and the neighborhood re-dispatch (NR) strategy are combined into DDCSO aiming to optimize initial population location and enhance local search ability. Eventually, the DDCSO-OBL-NR is realized, and the effectiveness of which in solving the distributed IEOS problems is verified by the experimental results of three cases.

Suggested Citation

  • Meng, Anbo & Wu, Zhenbo & Zhang, Zhan & Xu, Xuancong & Tang, Yanshu & Xie, Zhifeng & Xian, Zikang & Zhang, Haitao & Luo, Jianqiang & Wang, Yu & Yan, Baiping & Yin, Hao, 2024. "Optimal scheduling of integrated energy system using decoupled distributed CSO with opposition-based learning and neighborhood re-dispatch strategy," Renewable Energy, Elsevier, vol. 224(C).
  • Handle: RePEc:eee:renene:v:224:y:2024:i:c:s0960148124001678
    DOI: 10.1016/j.renene.2024.120102
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124001678
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2024.120102?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. Meng, Anbo & Zeng, Cong & Wang, Peng & Chen, De & Zhou, Tianmin & Zheng, Xiaoying & Yin, Hao, 2021. "A high-performance crisscross search based grey wolf optimizer for solving optimal power flow problem," Energy, Elsevier, vol. 225(C).
    2. 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.
    3. Yin, Hao & Wu, Fei & Meng, Xin & Lin, Yicheng & Fan, Jingmin & Meng, Anbo, 2020. "Crisscross optimization based short-term hydrothermal generation scheduling with cascaded reservoirs," Energy, Elsevier, vol. 203(C).
    4. Elattar, Ehab E., 2018. "Modified harmony search algorithm for combined economic emission dispatch of microgrid incorporating renewable sources," Energy, Elsevier, vol. 159(C), pages 496-507.
    5. 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).
    6. Mu, Yunfei & Chen, Wanqing & Yu, Xiaodan & Jia, Hongjie & Hou, Kai & Wang, Congshan & Meng, Xianjun, 2020. "A double-layer planning method for integrated community energy systems with varying energy conversion efficiencies," Applied Energy, Elsevier, vol. 279(C).
    7. Qi Zhu & Zhengming Li & Jinxing Liu & Zizhu Fan & Lei Yu & Yan Chen, 2013. "Improved Minimum Squared Error Algorithm with Applications to Face Recognition," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-5, August.
    8. Li, Xiaozhu & Wang, Weiqing & Wang, Haiyun, 2021. "A novel bi-level robust game model to optimize a regionally integrated energy system with large-scale centralized renewable-energy sources in Western China," Energy, Elsevier, vol. 228(C).
    9. Nami, Hossein & Anvari-Moghaddam, Amjad, 2020. "Geothermal driven micro-CCHP for domestic application – Exergy, economic and sustainability analysis," Energy, Elsevier, vol. 207(C).
    10. Li, Fan & Sun, Bo & Zhang, Chenghui & Liu, Che, 2019. "A hybrid optimization-based scheduling strategy for combined cooling, heating, and power system with thermal energy storage," Energy, Elsevier, vol. 188(C).
    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. Li, Xiaozhu & Wang, Weiqing & Wang, Haiyun, 2021. "A novel bi-level robust game model to optimize a regionally integrated energy system with large-scale centralized renewable-energy sources in Western China," Energy, Elsevier, vol. 228(C).
    2. Li, Xiaozhu & Wang, Weiqing & Wang, Haiyun, 2021. "Hybrid time-scale energy optimal scheduling strategy for integrated energy system with bilateral interaction with supply and demand," Applied Energy, Elsevier, vol. 285(C).
    3. 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).
    4. 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.
    5. 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).
    6. Lyu, Jiawei & Zhang, Shenxi & Cheng, Haozhong & Yuan, Kai & Song, Yi, 2022. "A graph theory-based optimal configuration method of energy hub considering the integration of electric vehicles," Energy, Elsevier, vol. 243(C).
    7. Ahmadisedigh, Hossein & Gosselin, Louis, 2022. "Combined heating and cooling networks with part-load efficiency curves: Optimization based on energy hub concept," Applied Energy, Elsevier, vol. 307(C).
    8. Wu, Min & Xu, Jiazhu & Zeng, Linjun & Li, Chang & Liu, Yuxing & Yi, Yuqin & Wen, Ming & Jiang, Zhuohan, 2022. "Two-stage robust optimization model for park integrated energy system based on dynamic programming," Applied Energy, Elsevier, vol. 308(C).
    9. Lasemi, Mohammad Ali & Arabkoohsar, Ahmad & Hajizadeh, Amin & Mohammadi-ivatloo, Behnam, 2022. "A comprehensive review on optimization challenges of smart energy hubs under uncertainty factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    10. Ahmadisedigh, Hossein & Gosselin, Louis, 2022. "How can combined heating and cooling networks benefit from thermal energy storage? Minimizing lifetime cost for different scenarios," Energy, Elsevier, vol. 243(C).
    11. 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).
    12. Jiang, Qian & Jia, Hongjie & Mu, Yunfei & Yu, Xiaodan & Wang, Zibo, 2024. "Bilateral planning and operation for integrated energy service provider and prosumers - A Nash bargaining-based method," Applied Energy, Elsevier, vol. 368(C).
    13. Qiao, Yiyang & Hu, Fan & Xiong, Wen & Guo, Zihao & Zhou, Xiaoguang & Li, Yajun, 2023. "Multi-objective optimization of integrated energy system considering installation configuration," Energy, Elsevier, vol. 263(PC).
    14. Zhou, Yuan & Wang, Jiangjiang & Dong, Fuxiang & Qin, Yanbo & Ma, Zherui & Ma, Yanpeng & Li, Jianqiang, 2021. "Novel flexibility evaluation of hybrid combined cooling, heating and power system with an improved operation strategy," Applied Energy, Elsevier, vol. 300(C).
    15. 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).
    16. Xiang, Yue & Guo, Yongtao & Wu, Gang & Liu, Junyong & Sun, Wei & Lei, Yutian & Zeng, Pingliang, 2022. "Low-carbon economic planning of integrated electricity-gas energy systems," Energy, Elsevier, vol. 249(C).
    17. Mengzhu Xiao & Manuel Wetzel & Thomas Pregger & Sonja Simon & Yvonne Scholz, 2020. "Modeling the Supply of Renewable Electricity to Metropolitan Regions in China," Energies, MDPI, vol. 13(12), pages 1-31, June.
    18. Sakthivel, V.P. & Thirumal, K. & Sathya, P.D., 2022. "Short term scheduling of hydrothermal power systems with photovoltaic and pumped storage plants using quasi-oppositional turbulent water flow optimization," Renewable Energy, Elsevier, vol. 191(C), pages 459-492.
    19. Feng Dong & Yuling Pan, 2020. "Evolution of Renewable Energy in BRI Countries: A Combined Econometric and Decomposition Approach," IJERPH, MDPI, vol. 17(22), pages 1-18, November.
    20. Mahmoudan, Alireza & Samadof, Parviz & Hosseinzadeh, Siamak & Garcia, Davide Astiaso, 2021. "A multigeneration cascade system using ground-source energy with cold recovery: 3E analyses and multi-objective optimization," Energy, Elsevier, vol. 233(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:renene:v:224:y:2024:i:c:s0960148124001678. 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/renewable-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.