IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i4p1011-d324616.html
   My bibliography  Save this article

Optimization Model of Key Equipment Maintenance Scheduling for an AC/DC Hybrid Transmission Network Based on Mixed Integer Linear Programming

Author

Listed:
  • Jie Cai

    (State Grid Hubei Electric Power Company Limited Economic Research Institute, Wuhan 430062, China)

  • Shuyu Guo

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Shuang Liao

    (State Grid Hubei Electric Power Company Limited Economic Research Institute, Wuhan 430062, China)

  • Xing Chen

    (State Grid Xinjiang Electric Power Company Limited Urumqi Power Supply Company, Urumqi 830001, China)

  • Shihong Miao

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yaowang Li

    (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

The unbalanced distribution of resource and consuming centers in China has prompted the AC/DC hybrid transmission technology. The maintenance scheduling of an AC/DC hybrid transmission network is the key technology to ensure its safety and reliability. In this study, the mutual influence mechanism of an AC/DC system in a maintenance period was analyzed in detail. The overhead transmission line and transformer are key equipment within an AC/DC hybrid transmission network, and an optimization model of the key equipment maintenance scheduling was established. The objective of the model was to improve the system reliability during the maintenance scheduling. By considering the constraints of maintenance cost, maintenance resources, and maintenance workload, the maintenance scheduling of overhead transmission lines and transformer branches was obtained. The over-limit situation of power flow and the weakness of the system during the maintenance period was evaluated. The “double-layer substitution method” was adopted to convert the nonlinear constraints into its bilinear formulation such that it could then be solved. The random number sampling method was used to quantify the system reliability, and the commercial optimization software was used to solve the optimized scheduling. Based on the improved IEEE RTS-79 system and the Hubei Province electrical system, the simulation results showed the effectiveness of the proposed method.

Suggested Citation

  • Jie Cai & Shuyu Guo & Shuang Liao & Xing Chen & Shihong Miao & Yaowang Li, 2020. "Optimization Model of Key Equipment Maintenance Scheduling for an AC/DC Hybrid Transmission Network Based on Mixed Integer Linear Programming," Energies, MDPI, vol. 13(4), pages 1-26, February.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:4:p:1011-:d:324616
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/4/1011/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/4/1011/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zelan Li & Yijia Cao & Le Van Dai & Xiaoliang Yang & Thang Trung Nguyen, 2019. "Optimal Power Flow for Transmission Power Networks Using a Novel Metaheuristic Algorithm," Energies, MDPI, vol. 12(22), pages 1-36, 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. Pavel Y. Gubin & Vladislav P. Oboskalov & Anatolijs Mahnitko & Roman Petrichenko, 2020. "Simulated Annealing, Differential Evolution and Directed Search Methods for Generator Maintenance Scheduling," Energies, MDPI, vol. 13(20), pages 1-26, October.

    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. Po-Chou Shih & Chui-Yu Chiu & Chi-Hsun Chou, 2019. "Using Dynamic Adjusting NGHS-ANN for Predicting the Recidivism Rate of Commuted Prisoners," Mathematics, MDPI, vol. 7(12), pages 1-25, December.
    2. Francisco Quinteros & Diego Carrión & Manuel Jaramillo, 2022. "Optimal Power Systems Restoration Based on Energy Quality and Stability Criteria," Energies, MDPI, vol. 15(6), pages 1-23, March.
    3. Shahenda Sarhan & Ragab El-Sehiemy & Amlak Abaza & Mona Gafar, 2022. "Turbulent Flow of Water-Based Optimization for Solving Multi-Objective Technical and Economic Aspects of Optimal Power Flow Problems," Mathematics, MDPI, vol. 10(12), pages 1-22, June.
    4. Matheus Henrique Dal Molin Ribeiro & Stéfano Frizzo Stefenon & José Donizetti de Lima & Ademir Nied & Viviana Cocco Mariani & Leandro dos Santos Coelho, 2020. "Electricity Price Forecasting Based on Self-Adaptive Decomposition and Heterogeneous Ensemble Learning," Energies, MDPI, vol. 13(19), pages 1-22, October.

    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:13:y:2020:i:4:p:1011-:d:324616. 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.