IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i12p4802-d1174489.html
   My bibliography  Save this article

A Grid Status Analysis Method with Large-Scale Wind Power Access Using Big Data

Author

Listed:
  • Dan Liu

    (State Grid Hubei Electric Power Research Institute, Wuhan 430077, China)

  • Yiqun Kang

    (State Grid Hubei Electric Power Research Institute, Wuhan 430077, China)

  • Heng Luo

    (State Grid Hubei Electric Power Research Institute, Wuhan 430077, China)

  • Xiaotong Ji

    (State Grid Hubei Electric Power Research Institute, Wuhan 430077, China)

  • Kan Cao

    (State Grid Hubei Electric Power Research Institute, Wuhan 430077, China)

  • Hengrui Ma

    (School of Electrical and Automation, Wuhan University, Wuhan 430077, China)

Abstract

Targeting the problem of the power grid facing greater risks with the connection of large-scale wind power, a method for power grid state analysis using big data is proposed. First, based on the big data, the wind power matrix and the branch power matrix are each constructed. Second, for the wind energy matrix, the eigenvalue index in the complex domain and the spectral density index in the real domain are constructed based on the circular law and the M-P law, respectively, to describe the variation of wind energy. Then, based on the concept of entropy and the M-P law, the index for describing the variation of the branch power is constructed. Finally, in order to analyze the real-time status of the grid connected to large-scale wind power, the proposed index is combined with the sliding time window. The simulation results based on the enhanced IEEE-33 bus system show that the proposed method can perform real-time analysis on the grid state of large-scale wind power connection from different perspectives, and its sensitivity is good.

Suggested Citation

  • Dan Liu & Yiqun Kang & Heng Luo & Xiaotong Ji & Kan Cao & Hengrui Ma, 2023. "A Grid Status Analysis Method with Large-Scale Wind Power Access Using Big Data," Energies, MDPI, vol. 16(12), pages 1-12, June.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:12:p:4802-:d:1174489
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/12/4802/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/12/4802/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Piotr Łukaszewski & Łukasz Nogal & Artur Łukaszewski, 2022. "The Identification of Travelling Waves in a Voltage Sensor Signal in a Medium Voltage Grid Using the Short-Time Matrix Pencil Method," Energies, MDPI, vol. 15(12), pages 1-16, June.
    2. Ning Wang & Fei Zhao, 2020. "An Assessment of the Condition of Distribution Network Equipment Based on Large Data Fuzzy Decision-Making," Energies, MDPI, vol. 13(1), pages 1-13, January.
    3. Antonio E. Saldaña-González & Andreas Sumper & Mònica Aragüés-Peñalba & Miha Smolnikar, 2020. "Advanced Distribution Measurement Technologies and Data Applications for Smart Grids: A Review," Energies, MDPI, vol. 13(14), pages 1-34, July.
    4. Hengrui Ma & Bo Wang & Wenzhong Gao & Dichen Liu & Yong Sun & Zhijun Liu, 2018. "Optimal Scheduling of an Regional Integrated Energy System with Energy Storage Systems for Service Regulation," Energies, MDPI, vol. 11(1), pages 1-19, January.
    5. Yuyang Gao & Chao Qu & Kequan Zhang, 2016. "A Hybrid Method Based on Singular Spectrum Analysis, Firefly Algorithm, and BP Neural Network for Short-Term Wind Speed Forecasting," Energies, MDPI, vol. 9(10), pages 1-28, September.
    6. Thapat Silalertruksa & Chanipa Wirodcharuskul & Shabbir H. Gheewala, 2022. "Environmental Sustainability of Waste Circulation Models for Sugarcane Biorefinery System in Thailand," Energies, MDPI, vol. 15(24), pages 1-21, December.
    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. Lan, Puzhe & Han, Dong & Xu, Xiaoyuan & Yan, Zheng & Ren, Xijun & Xia, Shiwei, 2022. "Data-driven state estimation of integrated electric-gas energy system," Energy, Elsevier, vol. 252(C).
    2. Wenting Zhang & Minxing Yue, 2021. "The application of building energy management system based on IoT technology in smart city," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(4), pages 617-628, August.
    3. Shengqi Zhang & Yateendra Mishra & Bei Yuan & Jianfeng Zhao & Mohammad Shahidehpour, 2018. "Primary Frequency Controller with Prediction-Based Droop Coefficient for Wind-Storage Systems under Spot Market Rules," Energies, MDPI, vol. 11(9), pages 1-19, September.
    4. Prawat Sukphun & Chaweewan Ponuansri & Worapong Wongarmat & Sureewan Sittijunda & Kanathip Promnuan & Alissara Reungsang, 2023. "Advancing Energy Recovery from Sugarcane Leaf via Two-Stage Anaerobic Digestion for Hydrogen and Methane Production: Impacts on Greenhouse Gas Mitigation and Sustainable Energy Production," Energies, MDPI, vol. 16(23), pages 1-15, November.
    5. Jianfeng Li & Dongxiao Niu & Ming Wu & Yongli Wang & Fang Li & Huanran Dong, 2018. "Research on Battery Energy Storage as Backup Power in the Operation Optimization of a Regional Integrated Energy System," Energies, MDPI, vol. 11(11), pages 1-20, November.
    6. Akhyurna Swain & Elmouatamid Abdellatif & Ahmed Mousa & Philip W. T. Pong, 2022. "Sensor Technologies for Transmission and Distribution Systems: A Review of the Latest Developments," Energies, MDPI, vol. 15(19), pages 1-37, October.
    7. Ana Lagos & Joaquín E. Caicedo & Gustavo Coria & Andrés Romero Quete & Maximiliano Martínez & Gastón Suvire & Jesús Riquelme, 2022. "State-of-the-Art Using Bibliometric Analysis of Wind-Speed and -Power Forecasting Methods Applied in Power Systems," Energies, MDPI, vol. 15(18), pages 1-40, September.
    8. Giovanni Betta & Domenico Capriglione & Luigi Ferrigno & Marco Laracca & Gianfranco Miele & Nello Polese & Silvia Sangiovanni, 2021. "A Fault Diagnostic Scheme for Predictive Maintenance of AC/DC Converters in MV/LV Substations," Energies, MDPI, vol. 14(22), pages 1-23, November.
    9. Francisco Martínez-Álvarez & Alicia Troncoso & José C. Riquelme, 2017. "Recent Advances in Energy Time Series Forecasting," Energies, MDPI, vol. 10(6), pages 1-3, June.
    10. L. Alvarado-Barrios & A. Rodríguez del Nozal & A. Tapia & J. L. Martínez-Ramos & D. G. Reina, 2019. "An Evolutionary Computational Approach for the Problem of Unit Commitment and Economic Dispatch in Microgrids under Several Operation Modes," Energies, MDPI, vol. 12(11), pages 1-23, June.
    11. Dongmei Zhao & Xuan Xia & Ran Tao, 2019. "Optimal Configuration of Electric-Gas-Thermal Multi-Energy Storage System for Regional Integrated Energy System," Energies, MDPI, vol. 12(13), pages 1-22, July.
    12. Arika Bridhikitti & Jutamas Kaewsuk & Netiya Karaket & Richard Friend & Brett Sallach & James P. J. Chong & Kelly R. Redeker, 2023. "Balancing Agriculture and Industry through Waste Utilization for Sugarcane Sustainability," Sustainability, MDPI, vol. 15(20), pages 1-26, October.
    13. Kyu-Hyung Jo & Mun-Kyeom Kim, 2018. "Stochastic Unit Commitment Based on Multi-Scenario Tree Method Considering Uncertainty," Energies, MDPI, vol. 11(4), pages 1-17, March.
    14. Sepideh Radhoush & Trevor Vannoy & Kaveen Liyanage & Bradley M. Whitaker & Hashem Nehrir, 2023. "Distribution System State Estimation and False Data Injection Attack Detection with a Multi-Output Deep Neural Network," Energies, MDPI, vol. 16(5), pages 1-22, February.
    15. Zhou, Qingguo & Wang, Chen & Zhang, Gaofeng, 2019. "Hybrid forecasting system based on an optimal model selection strategy for different wind speed forecasting problems," Applied Energy, Elsevier, vol. 250(C), pages 1559-1580.
    16. Hun Mun & Byunghoon Moon & Soojin Park & Yongbeum Yoon, 2021. "A Study on the Economic Feasibility of Stand-Alone Microgrid for Carbon-Free Island in Korea," Energies, MDPI, vol. 14(7), pages 1-16, March.
    17. Jingtao Huang & Gang Niu & Haiping Guan & Shuzhong Song, 2023. "Ultra-Short-Term Wind Power Prediction Based on LSTM with Loss Shrinkage Adam," Energies, MDPI, vol. 16(9), pages 1-13, April.
    18. Rizeakos, V. & Bachoumis, A. & Andriopoulos, N. & Birbas, M. & Birbas, A., 2023. "Deep learning-based application for fault location identification and type classification in active distribution grids," Applied Energy, Elsevier, vol. 338(C).
    19. Sepideh Radhoush & Bradley M. Whitaker & Hashem Nehrir, 2023. "An Overview of Supervised Machine Learning Approaches for Applications in Active Distribution Networks," Energies, MDPI, vol. 16(16), pages 1-29, August.
    20. Zhou, Dengji & Yan, Siyun & Huang, Dawen & Shao, Tiemin & Xiao, Wang & Hao, Jiarui & Wang, Chen & Yu, Tianqi, 2022. "Modeling and simulation of the hydrogen blended gas-electricity integrated energy system and influence analysis of hydrogen blending modes," Energy, Elsevier, vol. 239(PA).

    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:16:y:2023:i:12:p:4802-:d:1174489. 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.