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Review of AI applications in harmonic analysis in power systems

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  • Eslami, Ahmadreza
  • Negnevitsky, Michael
  • Franklin, Evan
  • Lyden, Sarah

Abstract

Harmonics and waveform distortion is a significant power quality problem in modern power systems with high penetration of Renewable Energy Sources (RES). This problem has attracted more attention in recent decades, owing to the increasing integration of power electronic devices and nonlinear loads into power systems. In this paper, Artificial Intelligence (AI) techniques used in different aspects of analyzing harmonics in electrical power networks are reviewed. The tasks of spectrum analysis and waveform estimation or prediction, harmonic source classification, harmonic source location and estimation, determination of harmonic source contributions, harmonic data clustering, filter-based harmonic elimination, and Distributed Generation (DG) hosting capacity in the context of harmonics are considered. The applications of AI in these tasks have been addressed within the literature and are reviewed in this paper. Different AI techniques applied in the study of harmonics such as artificial neural networks, fuzzy systems, support vector machine and decision tree are reviewed. AI techniques mostly outperformed traditional methods in harmonic analysis, particularly under varying operating condition. However, there is still room for improvement regarding the use of combinations of techniques, ensemble learning, optimal structures, training algorithms and further comprehension. This review provides researchers with an insight into research trends in harmonic analysis and outlines opportunities for further research on this increasingly important topic.

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  • Eslami, Ahmadreza & Negnevitsky, Michael & Franklin, Evan & Lyden, Sarah, 2022. "Review of AI applications in harmonic analysis in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    • Handle: RePEc:eee:rensus:v:154:y:2022:i:c:s1364032121011643
    DOI: 10.1016/j.rser.2021.111897
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    References listed on IDEAS

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    1. Mahela, Om Prakash & Shaik, Abdul Gafoor & Gupta, Neeraj, 2015. "A critical review of detection and classification of power quality events," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 495-505.
    2. Kow, Ken Weng & Wong, Yee Wan & Rajkumar, Rajparthiban Kumar & Rajkumar, Rajprasad Kumar, 2016. "A review on performance of artificial intelligence and conventional method in mitigating PV grid-tied related power quality events," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 334-346.
    3. Sherif M. Ismael & Shady H. E. Abdel Aleem & Almoataz Y. Abdelaziz & Ahmed F. Zobaa, 2019. "Probabilistic Hosting Capacity Enhancement in Non-Sinusoidal Power Distribution Systems Using a Hybrid PSOGSA Optimization Algorithm," Energies, MDPI, vol. 12(6), pages 1-23, March.
    4. Khokhar, Suhail & Mohd Zin, Abdullah Asuhaimi B. & Mokhtar, Ahmad Safawi B. & Pesaran, Mahmoud, 2015. "A comprehensive overview on signal processing and artificial intelligence techniques applications in classification of power quality disturbances," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1650-1663.
    5. Juntao Fei & Shixi Hou, 2012. "Adaptive Fuzzy Control with Supervisory Compensator for Three-Phase Active Power Filter," Journal of Applied Mathematics, Hindawi, vol. 2012, pages 1-13, December.
    6. Yap Hoon & Mohd Amran Mohd Radzi & Mohd Khair Hassan & Nashiren Farzilah Mailah, 2017. "A Self-Tuning Filter-Based Adaptive Linear Neuron Approach for Operation of Three-Level Inverter-Based Shunt Active Power Filters under Non-Ideal Source Voltage Conditions," Energies, MDPI, vol. 10(5), pages 1-28, May.
    7. Grabowski, Dariusz & Maciążek, Marcin & Pasko, Marian & Piwowar, Anna, 2018. "Time-invariant and time-varying filters versus neural approach applied to DC component estimation in control algorithms of active power filters," Applied Mathematics and Computation, Elsevier, vol. 319(C), pages 203-217.
    8. Kalair, A. & Abas, N. & Kalair, A.R. & Saleem, Z. & Khan, N., 2017. "Review of harmonic analysis, modeling and mitigation techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1152-1187.
    9. Kuang-Hsiung Tan & Faa-Jeng Lin & Chao-Yang Tsai & Yung-Ruei Chang, 2018. "A Distribution Static Compensator Using a CFNN-AMF Controller for Power Quality Improvement and DC-Link Voltage Regulation," Energies, MDPI, vol. 11(8), pages 1-17, August.
    10. Ismael, Sherif M. & Abdel Aleem, Shady H.E. & Abdelaziz, Almoataz Y. & Zobaa, Ahmed F., 2019. "State-of-the-art of hosting capacity in modern power systems with distributed generation," Renewable Energy, Elsevier, vol. 130(C), pages 1002-1020.
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    2. Md Tariqul Islam & M. J. Hossain, 2023. "Artificial Intelligence for Hosting Capacity Analysis: A Systematic Literature Review," Energies, MDPI, vol. 16(4), pages 1-33, February.
    3. Ama Ranawaka & Damminda Alahakoon & Yuan Sun & Kushan Hewapathirana, 2024. "Leveraging the Synergy of Digital Twins and Artificial Intelligence for Sustainable Power Grids: A Scoping Review," Energies, MDPI, vol. 17(21), pages 1-52, October.
    4. Hammed Olabisi Omotoso & Abdullrahman A. Al-Shamma’a & Mohammed Alharbi & Hassan M. Hussein Farh & Abdulaziz Alkuhayli & Akram M. Abdurraqeeb & Faisal Alsaif & Umar Bawah & Khaled E. Addoweesh, 2023. "Machine Learning Supervisory Control of Grid-Forming Inverters in Islanded Mode," Sustainability, MDPI, vol. 15(10), pages 1-19, May.
    5. Karmaker, Ashish Kumar & Prakash, Krishneel & Siddique, Md Nazrul Islam & Hossain, Md Alamgir & Pota, Hemanshu, 2024. "Electric vehicle hosting capacity analysis: Challenges and solutions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    6. Ifaei, Pouya & Nazari-Heris, Morteza & Tayerani Charmchi, Amir Saman & Asadi, Somayeh & Yoo, ChangKyoo, 2023. "Sustainable energies and machine learning: An organized review of recent applications and challenges," Energy, Elsevier, vol. 266(C).
    7. Dawid Buła & Dariusz Grabowski & Marcin Maciążek, 2022. "A Review on Optimization of Active Power Filter Placement and Sizing Methods," Energies, MDPI, vol. 15(3), pages 1-35, February.

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