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A systematic literature review on under-frequency load shedding protection using clustering methods

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  • Skrjanc, T.
  • Mihalic, R.
  • Rudez, U.

Abstract

System integrity protection schemes safeguard electric power systems’ overall integrity, among which under-frequency load shedding carries a flagship role. Although triggered rarely, it is irreplaceable in protecting the system from tremendous consequences of a blackout. The search for an optimal strategy has produced numerous innovations over the past 30 years, making it easy to lose track of the state-of-the-art due to the abundance. Given the increasing number of system splits in Europe and the ongoing operational paradigm shift, it is expected that existing load shedding concepts are about to be severely challenged. They are already expected to act more flexibly and, in the future, they may even require a complete redesign to support decarbonization efforts. This is why this research aims to provide a systematic review of existing load shedding algorithms. This is done by categorizing the accessible and adequately documented algorithms using machine learning clustering, more specifically, principal component analysis and t-distributed stochastic neighbour embedding combined with density-based spatial clustering of applications with noise. More than 380 publications were examined and both general and specific features were extracted from each of them. The study provides the description of 54 features along with their pros and cons related to their impact on system frequency stability. These efforts resulted in 28 recognized groups of algorithms, which can be helpful to stakeholders involved in securing and studying electric power system stability. The presented clustering proved very useful and can be extended to any technical field suffering from poor clarity of the state-of-the-art.

Suggested Citation

  • Skrjanc, T. & Mihalic, R. & Rudez, U., 2023. "A systematic literature review on under-frequency load shedding protection using clustering methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 180(C).
  • Handle: RePEc:eee:rensus:v:180:y:2023:i:c:s1364032123001508
    DOI: 10.1016/j.rser.2023.113294
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    References listed on IDEAS

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    1. Nieminen, Paavo & Pölönen, Ilkka & Sipola, Tuomo, 2013. "Research literature clustering using diffusion maps," Journal of Informetrics, Elsevier, vol. 7(4), pages 874-886.
    2. Bakar, Nur Najihah Abu & Hassan, Mohammad Yusri & Sulaima, Mohamad Fani & Mohd Nasir, Mohamad Na’im & Khamis, Aziah, 2017. "Microgrid and load shedding scheme during islanded mode: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 161-169.
    3. Khezri, Rahmat & Golshannavaz, Sajjad & Vakili, Ramin & Memar-Esfahani, Bahram, 2017. "Multi-layer fuzzy-based under-frequency load shedding in back-pressure smart industrial microgrids," Energy, Elsevier, vol. 132(C), pages 96-105.
    4. Yujin Lim & Hak-Man Kim & Tetsuo Kinoshita, 2014. "Distributed Load-Shedding System for Agent-Based Autonomous Microgrid Operations," Energies, MDPI, vol. 7(1), pages 1-17, January.
    5. Qi Wang & Yi Tang & Feng Li & Mengya Li & Yang Li & Ming Ni, 2016. "Coordinated Scheme of Under-Frequency Load Shedding with Intelligent Appliances in a Cyber Physical Power System," Energies, MDPI, vol. 9(8), pages 1-14, August.
    6. Denis Sodin & Rajne Ilievska & Andrej Čampa & Miha Smolnikar & Urban Rudez, 2020. "Proving a Concept of Flexible Under-Frequency Load Shedding with Hardware-in-the-Loop Testing," Energies, MDPI, vol. 13(14), pages 1-17, July.
    7. Tadej Skrjanc & Rafael Mihalic & Urban Rudez, 2020. "Principal Component Analysis (PCA)-Supported Underfrequency Load Shedding Algorithm," Energies, MDPI, vol. 13(22), pages 1-9, November.
    8. Jafar Jallad & Saad Mekhilef & Hazlie Mokhlis & Javed Laghari & Ola Badran, 2018. "Application of Hybrid Meta-Heuristic Techniques for Optimal Load Shedding Planning and Operation in an Islanded Distribution Network Integrated with Distributed Generation," Energies, MDPI, vol. 11(5), pages 1-25, May.
    9. Shun Li & Fei Tang & Youguo Shao & Qingfen Liao, 2017. "Adaptive Under-Frequency Load Shedding Scheme in System Integrated with High Wind Power Penetration: Impacts and Improvements," Energies, MDPI, vol. 10(9), pages 1-16, September.
    10. Mohammad Dreidy & Hazlie Mokhlis & Saad Mekhilef, 2017. "Application of Meta-Heuristic Techniques for Optimal Load Shedding in Islanded Distribution Network with High Penetration of Solar PV Generation," Energies, MDPI, vol. 10(2), pages 1-24, January.
    11. Xi Wu & Ping Jiang & Jing Lu, 2014. "Multiagent-Based Distributed Load Shedding for Islanded Microgrids," Energies, MDPI, vol. 7(9), pages 1-13, September.
    12. Yun, Jinhyuk & Ahn, Sejung & Lee, June Young, 2020. "Return to basics: Clustering of scientific literature using structural information," Journal of Informetrics, Elsevier, vol. 14(4).
    13. Shiau, Wen-Lung & Dwivedi, Yogesh K. & Yang, Han Suan, 2017. "Co-citation and cluster analyses of extant literature on social networks," International Journal of Information Management, Elsevier, vol. 37(5), pages 390-399.
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    1. Abbasizadeh, Ali & Azad-Farsani, Ehsan, 2024. "Cyber-constrained load shedding for smart grid resilience enhancement," Reliability Engineering and System Safety, Elsevier, vol. 243(C).

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