IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i18p11749-d918780.html
   My bibliography  Save this article

A Novel Fault Detection and Classification Strategy for Photovoltaic Distribution Network Using Improved Hilbert–Huang Transform and Ensemble Learning Technique

Author

Listed:
  • Younis M. Nsaif

    (Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia
    General Company of Electricity Production, Middle Region, Iraqi Ministry of Electricity, Baghdad 10045, Iraq)

  • Molla Shahadat Hossain Lipu

    (Department of Electrical and Electronic Engineering, Green University of Bangladesh, Dhaka 1207, Bangladesh)

  • Aini Hussain

    (Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia
    Centre for Automotive Research (CAR), Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia)

  • Afida Ayob

    (Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia
    Centre for Automotive Research (CAR), Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia)

  • Yushaizad Yusof

    (Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia)

  • Muhammad Ammirrul A. M. Zainuri

    (Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia)

Abstract

Due to the increased integration of distributed generations in distributed networks, their development and operation are facing protection challenges that traditional protection systems are incapable of addressing. These problems include variations in the fault current during various operation modes, diverse distributed network topology, and high impedance faults. Therefore, appropriate and reasonable fault detection is highly encouraged to improve the protection and dependability of the distributed network. This paper proposes a novel technique that employs an improved Hilbert–Huang Transform (HHT) and ensemble learning techniques to resolve these challenges in a photovoltaic distributed network. First, improved HHT is utilized to extract energy features from the current signal. Second, variational mode decomposition (VMD) is applied to extract the intrinsic mode function from the zero component of the current signal. Then, the acquired energy feature and intrinsic mode function are input to the ensemble learning technique for fault detection and classification. The proposed technique is implemented using MATLAB software environment, including a classification learner app and SIMULINK. An evaluation of the results is conducted under normal connected mode (NCM) and island mode (ISM) for radial and mesh-soft normally open point (SNOP) configurations. The accuracy of the ensemble bagged trees technique is higher when compared to the narrow-neural network, fine tree, quadratic SVM, fine-gaussian SVM, and wide-neural network. The presented technique depends only on local variables and has no requirements for connection latency. Consequently, the detection and classification of faults using the proposed technology are reasonable. The simulation results demonstrate that the proposed technique is superior to the neural network and support vector machine, achieving 100%, 99.2% and 99.7% accurate symmetrical and unsymmetrical fault detection and classification throughout NCM, ISM, and dynamic operation mode, respectively. Moreover, the developed technique protects DN effectively in radial and mesh-SNOP topologies. The suggested strategy can detect and classify faults accurately in DN with/without DGs. Additionally, this technique can precisely detect high and low impedance faults within 4.8 ms.

Suggested Citation

  • Younis M. Nsaif & Molla Shahadat Hossain Lipu & Aini Hussain & Afida Ayob & Yushaizad Yusof & Muhammad Ammirrul A. M. Zainuri, 2022. "A Novel Fault Detection and Classification Strategy for Photovoltaic Distribution Network Using Improved Hilbert–Huang Transform and Ensemble Learning Technique," Sustainability, MDPI, vol. 14(18), pages 1-19, September.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11749-:d:918780
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/18/11749/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/18/11749/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ibrahim Mohamed Diaaeldin & Shady H. E. Abdel Aleem & Ahmed El-Rafei & Almoataz Y. Abdelaziz & Ahmed F. Zobaa, 2020. "Enhancement of Hosting Capacity with Soft Open Points and Distribution System Reconfiguration: Multi-Objective Bilevel Stochastic Optimization," Energies, MDPI, vol. 13(20), pages 1-20, October.
    2. Theerasak Patcharoen & Atthapol Ngaopitakkul, 2019. "Fault Classifications in Distribution Systems Consisting of Wind Power as Distributed Generation Using Discrete Wavelet Transforms," Sustainability, MDPI, vol. 11(24), pages 1-16, December.
    3. Yijin Li & Jianhua Lin & Geng Niu & Ming Wu & Xuteng Wei, 2021. "A Hilbert–Huang Transform-Based Adaptive Fault Detection and Classification Method for Microgrids," Energies, MDPI, vol. 14(16), pages 1-16, August.
    4. Cao, Wanyu & Wu, Jianzhong & Jenkins, Nick & Wang, Chengshan & Green, Timothy, 2016. "Operating principle of Soft Open Points for electrical distribution network operation," Applied Energy, Elsevier, vol. 164(C), pages 245-257.
    5. Edmilson Bermudes Rocha Junior & Oureste Elias Batista & Domingos Sávio Lyrio Simonetti, 2022. "Differential Analysis of Fault Currents in a Power Distribution Feeder Using abc , αβ0 , and dq0 Reference Frames," Energies, MDPI, vol. 15(2), pages 1-22, January.
    6. Masoud Ahmadipour & Hashim Hizam & Mohammad Lutfi Othman & Mohd Amran Mohd Radzi & Nikta Chireh, 2019. "A Fast Fault Identification in a Grid-Connected Photovoltaic System Using Wavelet Multi-Resolution Singular Spectrum Entropy and Support Vector Machine," Energies, MDPI, vol. 12(13), pages 1-18, June.
    7. Md Shafiul Alam & Mohammad Ali Yousef Abido & Ibrahim El-Amin, 2018. "Fault Current Limiters in Power Systems: A Comprehensive Review," Energies, MDPI, vol. 11(5), pages 1-24, April.
    8. Abdulaziz Aljohani & Ibrahim Habiballah, 2020. "High-Impedance Fault Diagnosis: A Review," Energies, MDPI, vol. 13(23), pages 1-18, December.
    9. Raquel Martinez & Pablo Castro & Alberto Arroyo & Mario Manana & Noemi Galan & Fidel Simon Moreno & Sergio Bustamante & Alberto Laso, 2022. "Techniques to Locate the Origin of Power Quality Disturbances in a Power System: A Review," Sustainability, MDPI, vol. 14(12), pages 1-27, June.
    10. Dehua Zheng & Abinet Tesfaye Eseye & Jianhua Zhang, 2018. "A Communication-Supported Comprehensive Protection Strategy for Converter-Interfaced Islanded Microgrids," Sustainability, MDPI, vol. 10(5), pages 1-24, April.
    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. Ana-Maria Moldovan & Mircea Ion Buzdugan, 2023. "Prediction of Faults Location and Type in Electrical Cables Using Artificial Neural Network," Sustainability, MDPI, vol. 15(7), pages 1-19, April.
    2. Younis M. Nsaif & Molla Shahadat Hossain Lipu & Aini Hussain & Afida Ayob & Yushaizad Yusof & Muhammad Ammirrul A. M. Zainuri, 2022. "A New Voltage Based Fault Detection Technique for Distribution Network Connected to Photovoltaic Sources Using Variational Mode Decomposition Integrated Ensemble Bagged Trees Approach," Energies, MDPI, vol. 15(20), pages 1-20, 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. Younis M. Nsaif & Molla Shahadat Hossain Lipu & Aini Hussain & Afida Ayob & Yushaizad Yusof & Muhammad Ammirrul A. M. Zainuri, 2022. "A New Voltage Based Fault Detection Technique for Distribution Network Connected to Photovoltaic Sources Using Variational Mode Decomposition Integrated Ensemble Bagged Trees Approach," Energies, MDPI, vol. 15(20), pages 1-20, October.
    2. Shamam Alwash & Sarmad Ibrahim & Azher M. Abed, 2022. "Distribution System Reconfiguration with Soft Open Point for Power Loss Reduction in Distribution Systems Based on Hybrid Water Cycle Algorithm," Energies, MDPI, vol. 16(1), pages 1-22, December.
    3. Li, Peng & Ji, Haoran & Yu, Hao & Zhao, Jinli & Wang, Chengshan & Song, Guanyu & Wu, Jianzhong, 2019. "Combined decentralized and local voltage control strategy of soft open points in active distribution networks," Applied Energy, Elsevier, vol. 241(C), pages 613-624.
    4. Shen, Boyang & Chen, Yu & Li, Chuanyue & Wang, Sheng & Chen, Xiaoyuan, 2021. "Superconducting fault current limiter (SFCL): Experiment and the simulation from finite-element method (FEM) to power/energy system software," Energy, Elsevier, vol. 234(C).
    5. Sung-Hun Lim & Jin-O. Kim & Youngjin Jeong, 2020. "Fault Current Limiting and Breaking Characteristics of SFCLB Using Flux Coupling with Tap Changer," Energies, MDPI, vol. 13(19), pages 1-14, October.
    6. Mingang Tan & Chaohai Zhang & Bin Chen, 2022. "Size Estimation of Bulk Capacitor Removal Using Limited Power Quality Monitors in the Distribution Network," Sustainability, MDPI, vol. 14(22), pages 1-14, November.
    7. Wang, Chengshan & Song, Guanyu & Li, Peng & Ji, Haoran & Zhao, Jinli & Wu, Jianzhong, 2017. "Optimal siting and sizing of soft open points in active electrical distribution networks," Applied Energy, Elsevier, vol. 189(C), pages 301-309.
    8. Jaesik Kang, 2022. "Comprehensive Analysis of Transient Overvoltage Phenomena for Metal-Oxide Varistor Surge Arrester in LCC-HVDC Transmission System with Special Protection Scheme," Energies, MDPI, vol. 15(19), pages 1-17, September.
    9. Khalfan Al Kharusi & Abdelsalam El Haffar & Mostefa Mesbah, 2022. "Fault Detection and Classification in Transmission Lines Connected to Inverter-Based Generators Using Machine Learning," Energies, MDPI, vol. 15(15), pages 1-23, July.
    10. Ji, Haoran & Wang, Chengshan & Li, Peng & Song, Guanyu & Yu, Hao & Wu, Jianzhong, 2019. "Quantified analysis method for operational flexibility of active distribution networks with high penetration of distributed generators," Applied Energy, Elsevier, vol. 239(C), pages 706-714.
    11. John Linden & Yasha Nikulshin & Alex Friedman & Yosef Yeshurun & Shuki Wolfus, 2019. "Design Optimization of a Permanent-Magnet Saturated-Core Fault-Current Limiter," Energies, MDPI, vol. 12(10), pages 1-11, May.
    12. Irina I. Picioroaga & Andrei M. Tudose & Dorian O. Sidea & Constantin Bulac, 2022. "Supply Restoration in Active Distribution Networks Based on Soft Open Points with Embedded DC Microgrids," Mathematics, MDPI, vol. 10(2), pages 1-21, January.
    13. Md. Shafiul Alam & Tanzi Ahmed Chowdhury & Abhishak Dhar & Fahad Saleh Al-Ismail & M. S. H. Choudhury & Md Shafiullah & Md. Ismail Hossain & Md. Alamgir Hossain & Aasim Ullah & Syed Masiur Rahman, 2023. "Solar and Wind Energy Integrated System Frequency Control: A Critical Review on Recent Developments," Energies, MDPI, vol. 16(2), pages 1-31, January.
    14. Muhyaddin Rawa & Abdullah Abusorrah & Yusuf Al-Turki & Saad Mekhilef & Mostafa H. Mostafa & Ziad M. Ali & Shady H. E. Abdel Aleem, 2020. "Optimal Allocation and Economic Analysis of Battery Energy Storage Systems: Self-Consumption Rate and Hosting Capacity Enhancement for Microgrids with High Renewable Penetration," Sustainability, MDPI, vol. 12(23), pages 1-25, December.
    15. Wang, Ke & Xue, Yixun & Zhou, Yue & Li, Zening & Chang, Xinyue & Sun, Hongbin, 2024. "Distributed coordinated reconfiguration with soft open points for resilience-oriented restoration in integrated electric and heating systems," Applied Energy, Elsevier, vol. 365(C).
    16. Muhammad Ahmad & Zhixin Wang, 2019. "A Hybrid DC Circuit Breaker with Fault-Current-Limiting Capability for VSC-HVDC Transmission System," Energies, MDPI, vol. 12(12), pages 1-16, June.
    17. Ahmed M. Mahmoud & Shady H. E. Abdel Aleem & Almoataz Y. Abdelaziz & Mohamed Ezzat, 2022. "Towards Maximizing Hosting Capacity by Optimal Planning of Active and Reactive Power Compensators and Voltage Regulators: Case Study," Sustainability, MDPI, vol. 14(20), pages 1-34, October.
    18. Gonzalez Venegas, Felipe & Petit, Marc & Perez, Yannick, 2021. "Active integration of electric vehicles into distribution grids: Barriers and frameworks for flexibility services," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    19. Abdulaziz Alanazi & Mohana Alanazi, 2022. "Artificial Electric Field Algorithm-Pattern Search for Many-Criteria Networks Reconfiguration Considering Power Quality and Energy Not Supplied," Energies, MDPI, vol. 15(14), pages 1-27, July.
    20. Kuei-Hsiang Chao & Chen-Hou Ke, 2020. "Fault Diagnosis and Tolerant Control of Three-Level Neutral-Point Clamped Inverters in Motor Drives," Energies, MDPI, vol. 13(23), pages 1-25, 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:jsusta:v:14:y:2022:i:18:p:11749-:d:918780. 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.