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Decision Tree for Online Voltage Stability Margin Assessment Using C4.5 and Relief-F Algorithms

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  • Xiangfei Meng

    (School of Electrical Engineering, Beijing Jiaotong University, No.3 Shangyuancun, Haidian District, Beijing 100044, China)

  • Pei Zhang

    (School of Electrical Engineering, Beijing Jiaotong University, No.3 Shangyuancun, Haidian District, Beijing 100044, China)

  • Dahai Zhang

    (School of Electrical Engineering, Beijing Jiaotong University, No.3 Shangyuancun, Haidian District, Beijing 100044, China)

Abstract

In practical power system operation, knowing the voltage stability limits of the system is important. This paper proposes using a decision tree (DT) to extract guidelines through offline study results for assessing system voltage stability status online. Firstly, a sample set of DTs is determined offline by active power injection and bus voltage magnitude (P-V) curve analysis. Secondly, participation factor (PF) analysis and the Relief-F algorithm are used successively for attribute selection, which takes both the physical significance and the classification capabilities into consideration. Finally, the C4.5 algorithm is used to build the DT because it is more suitable for handling continuous variables. A practical power system is implemented to verify the feasibility of the proposed online voltage stability margin (VSM) assessment framework. Study results indicate that the operating guidelines extracted from the DT can help power system operators assess real time VSM effectively.

Suggested Citation

  • Xiangfei Meng & Pei Zhang & Dahai Zhang, 2020. "Decision Tree for Online Voltage Stability Margin Assessment Using C4.5 and Relief-F Algorithms," Energies, MDPI, vol. 13(15), pages 1-13, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3824-:d:389721
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    Citations

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    Cited by:

    1. Ayat N. Hussain, 2022. "Gait Classification Using Machine Learning for Foot Disseises Diagnosis," Technium, Technium Science, vol. 4(1), pages 37-49.
    2. Maciej Klimas & Dariusz Grabowski & Dawid Buła, 2021. "Application of Decision Trees for Optimal Allocation of Harmonic Filters in Medium-Voltage Networks," Energies, MDPI, vol. 14(4), pages 1-24, February.

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