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Inertia Estimation of Synchronous Devices: Review of Available Techniques and Comparative Assessment of Conventional Measurement-Based Approaches

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  • Stelios C. Dimoulias

    (Power Systems Laboratory, School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece)

  • Eleftherios O. Kontis

    (Power Systems Laboratory, School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece)

  • Grigoris K. Papagiannis

    (Power Systems Laboratory, School of Electrical and Computer Engineering, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece)

Abstract

The increasing deployment of renewable energy sources (RESs) reduces the inertia levels of modern power systems, raising frequency stability issues. Therefore, it becomes crucial, for power-system operators, to monitor system inertia, in order to activate proper preventive remedial actions in a timely way, ensuring, this way, the reliable and secure operation of the power system. This paper presents a brief review of available techniques for inertia estimation of synchronous devices. Additionally, a comparative assessment of conventional measurement-based inertia-estimation techniques is performed. In particular, five conventional inertia-estimation techniques are considered and examined. The distinct features of each method are presented and discussed. The effect of several parameters on the accuracy of the examined methods is evaluated via Monte Carlo analysis. The performance of the examined methods is evaluated using dynamic responses, obtained via RMS simulations, conducted on the IEEE 9 bus test system. Based on the conducted analysis, recommendations to enhance the accuracy of the examined techniques are proposed.

Suggested Citation

  • Stelios C. Dimoulias & Eleftherios O. Kontis & Grigoris K. Papagiannis, 2022. "Inertia Estimation of Synchronous Devices: Review of Available Techniques and Comparative Assessment of Conventional Measurement-Based Approaches," Energies, MDPI, vol. 15(20), pages 1-30, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7767-:d:948652
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    References listed on IDEAS

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    1. Zhentao Xu & Junjie Ma & Yousong Gao & Yong Li & Haifeng Yu & Lu Wang, 2023. "Inertia Identification and Analysis for High-Power-Electronic-Penetrated Power System Based on Measurement Data," Energies, MDPI, vol. 16(10), pages 1-19, May.
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