IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i24p9262-d995632.html
   My bibliography  Save this article

Research on Maintenance Strategies for Different Transmission Sections to Improve the Consumption Rate Based on a Renewable Energy Production Simulation

Author

Listed:
  • Xiaojing Hu

    (Power System Automation Institute, China Electric Power Research Institute, Beijing 100192, China)

  • Haoling Min

    (School of Renewable Energy, North China Electric Power University, Beijing 102206, China)

  • Sai Dai

    (Power System Automation Institute, China Electric Power Research Institute, Beijing 100192, China)

  • Zhi Cai

    (Power System Automation Institute, China Electric Power Research Institute, Beijing 100192, China)

  • Xiaonan Yang

    (Power System Automation Institute, China Electric Power Research Institute, Beijing 100192, China)

  • Qiang Ding

    (Power System Automation Institute, China Electric Power Research Institute, Beijing 100192, China)

  • Zhanyong Yang

    (Power System Automation Institute, China Electric Power Research Institute, Beijing 100192, China)

  • Feng Xiao

    (School of Renewable Energy, North China Electric Power University, Beijing 102206, China)

Abstract

Renewable energy consumption is one of the most important factors in meeting the goal of “30 and 60” in China. However, the maintenance of the transmission section affects the amount of generation transfer, further affecting the consumption of renewable energy. Hence, in this study, a time-series renewable energy production simulation (REPS) is proposed in order to accurately predict the power generation in a simulated situation. According to the results of the REPS, the sensitivity of the different sections’ maintenance can be calculated and determined. The appropriate maintenance strategies can be selected for different situations by comparing the consumption rate; as an example, we conducted a case study. The results show that the quota in the transmission section has higher sensitivity; a larger quota indicates a greater sensitivity to the consumption rate. The results also show that a larger quota is more suitable for maintenance in February or November, since the consumption rate is higher regardless of if it is in a single-transmission-section maintenance strategy or in a two-section simultaneous maintenance strategy.

Suggested Citation

  • Xiaojing Hu & Haoling Min & Sai Dai & Zhi Cai & Xiaonan Yang & Qiang Ding & Zhanyong Yang & Feng Xiao, 2022. "Research on Maintenance Strategies for Different Transmission Sections to Improve the Consumption Rate Based on a Renewable Energy Production Simulation," Energies, MDPI, vol. 15(24), pages 1-11, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9262-:d:995632
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/24/9262/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/24/9262/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Maximilian Hoffmann & Leander Kotzur & Detlef Stolten & Martin Robinius, 2020. "A Review on Time Series Aggregation Methods for Energy System Models," Energies, MDPI, vol. 13(3), pages 1-61, February.
    2. Vasiliki Vita, 2017. "Development of a Decision-Making Algorithm for the Optimum Size and Placement of Distributed Generation Units in Distribution Networks," Energies, MDPI, vol. 10(9), pages 1-13, September.
    3. Cattareeya Suwanasri & Surapol Saribut & Thanapong Suwanasri & Rattanakorn Phadungthin, 2021. "Risk Analysis Using Failure Modes, Effects, and Criticality Analysis for Transmission Network Assets," Energies, MDPI, vol. 14(4), pages 1-16, February.
    4. Mehleri, Eugenia D. & Sarimveis, Haralambos & Markatos, Nikolaos C. & Papageorgiou, Lazaros G., 2012. "A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level," Energy, Elsevier, vol. 44(1), pages 96-104.
    5. Gokturk Poyrazoglu & HyungSeon Oh, 2019. "Co-optimization of Transmission Maintenance Scheduling and Production Cost Minimization," Energies, MDPI, vol. 12(15), pages 1-18, July.
    6. Nenad Sijakovic & Aleksandar Terzic & Georgios Fotis & Ioannis Mentis & Magda Zafeiropoulou & Theodoros I. Maris & Emmanouil Zoulias & Charalambos Elias & Vladan Ristic & Vasiliki Vita, 2022. "Active System Management Approach for Flexibility Services to the Greek Transmission and Distribution System," Energies, MDPI, vol. 15(17), pages 1-31, August.
    7. Yixin Huang & Xinyi Liu & Zhi Zhang & Li Yang & Zhenzhi Lin & Yangqing Dan & Ke Sun & Zhou Lan & Keping Zhu, 2020. "Multi-Stage Transmission Network Planning Considering Transmission Congestion in the Power Market," Energies, MDPI, vol. 13(18), pages 1-22, September.
    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. Hoffmann, Maximilian & Priesmann, Jan & Nolting, Lars & Praktiknjo, Aaron & Kotzur, Leander & Stolten, Detlef, 2021. "Typical periods or typical time steps? A multi-model analysis to determine the optimal temporal aggregation for energy system models," Applied Energy, Elsevier, vol. 304(C).
    2. de Guibert, Paul & Shirizadeh, Behrang & Quirion, Philippe, 2020. "Variable time-step: A method for improving computational tractability for energy system models with long-term storage," Energy, Elsevier, vol. 213(C).
    3. Jingjing Tu & Zhongdong Yin & Yonghai Xu, 2018. "Study on the Evaluation Index System and Evaluation Method of Voltage Stability of Distribution Network with High DG Penetration," Energies, MDPI, vol. 11(1), pages 1-15, January.
    4. Theresa Liegl & Simon Schramm & Philipp Kuhn & Thomas Hamacher, 2023. "Considering Socio-Technical Parameters in Energy System Models—The Current Status and Next Steps," Energies, MDPI, vol. 16(20), pages 1-19, October.
    5. Clarke, Fiona & Dorneanu, Bogdan & Mechleri, Evgenia & Arellano-Garcia, Harvey, 2021. "Optimal design of heating and cooling pipeline networks for residential distributed energy resource systems," Energy, Elsevier, vol. 235(C).
    6. Entchev, E. & Yang, L. & Ghorab, M. & Lee, E.J., 2013. "Simulation of hybrid renewable microgeneration systems in load sharing applications," Energy, Elsevier, vol. 50(C), pages 252-261.
    7. Li, Ruonan & Mahalec, Vladimir, 2022. "Integrated design and operation of energy systems for residential buildings, commercial buildings, and light industries," Applied Energy, Elsevier, vol. 305(C).
    8. Xiaofeng Liu & Shijun Wang & Jiawen Sun, 2018. "Energy Management for Community Energy Network with CHP Based on Cooperative Game," Energies, MDPI, vol. 11(5), pages 1-18, April.
    9. Huang, Zishuo & Yu, Hang & Chu, Xiangyang & Peng, Zhenwei, 2017. "A goal programming based model system for community energy plan," Energy, Elsevier, vol. 134(C), pages 893-901.
    10. Sameti, Mohammad & Haghighat, Fariborz, 2018. "Integration of distributed energy storage into net-zero energy district systems: Optimum design and operation," Energy, Elsevier, vol. 153(C), pages 575-591.
    11. Sachin Kumar & Kumari Sarita & Akanksha Singh S Vardhan & Rajvikram Madurai Elavarasan & R. K. Saket & Narottam Das, 2020. "Reliability Assessment of Wind-Solar PV Integrated Distribution System Using Electrical Loss Minimization Technique," Energies, MDPI, vol. 13(21), pages 1-30, October.
    12. Zare, Mohsen & Niknam, Taher, 2013. "A new multi-objective for environmental and economic management of Volt/Var Control considering renewable energy resources," Energy, Elsevier, vol. 55(C), pages 236-252.
    13. Cailian Gu & Yibo Wang & Weisheng Wang & Yang Gao, 2023. "Research on Load State Sensing and Early Warning Method of Distribution Network under High Penetration Distributed Generation Access," Energies, MDPI, vol. 16(7), pages 1-15, March.
    14. Ahmad Khan, Aftab & Naeem, Muhammad & Iqbal, Muhammad & Qaisar, Saad & Anpalagan, Alagan, 2016. "A compendium of optimization objectives, constraints, tools and algorithms for energy management in microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1664-1683.
    15. Capuder, Tomislav & Mancarella, Pierluigi, 2014. "Techno-economic and environmental modelling and optimization of flexible distributed multi-generation options," Energy, Elsevier, vol. 71(C), pages 516-533.
    16. Di Somma, M. & Graditi, G. & Heydarian-Forushani, E. & Shafie-khah, M. & Siano, P., 2018. "Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects," Renewable Energy, Elsevier, vol. 116(PA), pages 272-287.
    17. Ito, Masakazu & Takano, Akihisa & Shinji, Takao & Yagi, Takahiro & Hayashi, Yasuhiro, 2017. "Electricity adjustment for capacity market auction by a district heating and cooling system," Applied Energy, Elsevier, vol. 206(C), pages 623-633.
    18. Reveron Baecker, Beneharo & Candas, Soner, 2022. "Co-optimizing transmission and active distribution grids to assess demand-side flexibilities of a carbon-neutral German energy system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    19. Liu, Liuchen & Cui, Guomin & Chen, Jiaxing & Huang, Xiaohuang & Li, Di, 2022. "Two-stage superstructure model for optimization of distributed energy systems (DES) part I: Model development and verification," Energy, Elsevier, vol. 245(C).
    20. Tayyab Ali & Suheel Abdullah Malik & Amil Daraz & Sheraz Aslam & Tamim Alkhalifah, 2022. "Dandelion Optimizer-Based Combined Automatic Voltage Regulation and Load Frequency Control in a Multi-Area, Multi-Source Interconnected Power System with Nonlinearities," Energies, MDPI, vol. 15(22), pages 1-34, November.

    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:15:y:2022:i:24:p:9262-:d:995632. 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.