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Joint Probabilistic Modeling Approach for Harmonic and Three-phase Unbalanced Disturbance Sources
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Yifan ZHANG1, 2, Dazhi PAN3, Yonghong ZHANG4, Lijian XIN1, Ying WANG5, Xinru WANG5
Journal of Power Supply | 2026, 24(7) : 243 - 252
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Journal of Power Supply | 2026, 24(7): 243-252
• Power Electronic Dominated Power Systems •
Joint Probabilistic Modeling Approach for Harmonic and Three-phase Unbalanced Disturbance Sources
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Yifan ZHANG1, 2, Dazhi PAN3, Yonghong ZHANG4, Lijian XIN1, Ying WANG5, Xinru WANG5
Affiliations
  • 1.Inner Mongolia Power (Group) Co., Ltd., Inner Mongolia Power Research Institute Branch, Hohhot 010020, China
  • 2.Inner Mongolia Key Laboratory of Smart Grid of New-type Power System, Hohhot 010020, China
  • 3.Inner Mongolia Power (Group) Co., Ltd., Hohhot 010020, China
  • 4.Inner Mongolia Power (Group) Co., Ltd., Ordos Power Supply Company, Ordos 017000, China
  • 5.College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Published: 2026-07-30 doi: 10.13234/j.issn.2095-2805.2026.7.243
Outline
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Harmonics and three-phase unbalance are two common forms of disturbances in power systems, which interact with each other and jointly cause more complex impacts on power systems. In order to more comprehensively and accurately analyze the distribution law and interaction mechanism of harmonics and three-phase unbalance, the joint emission level of harmonic and three-phase unbalanced disturbance sources (H-TU-DS) is investigated, and a joint probabilistic emission level modeling method is proposed. First, based on the multivariate correlation coefficients of disturbance source power, harmonic and three-phase unbalanced data, the disturbance source characteristic dataset is screened to realize the data dimensionality reduction. Subsequently, the fuzzy C-means (FCM) algorithm is used to complete the clustering division of the feature data, which lays the foundation for the disturbance source sub-condition analysis. Then, the joint probability model of H-TU-DS is constructed by the nonparametric kernel density estimation method. Finally, the effectiveness and accuracy of the proposed feature dataset screening method, operation condition classification method and joint probability modeling method are proved by comparing and verifying the simulated and measured data.

Harmonics  /  three-phase unbalance  /  nonparametric kernel density  /  probability modeling
张一帆, 潘大志, 张永宏, 辛力坚, 汪颖, 王心茹. 谐波和三相不平衡扰动源联合概率建模方法. 电源学报, 2026 , 24 (7) : 243 -252 . DOI: 10.13234/j.issn.2095-2805.2026.7.243
Yifan ZHANG, Dazhi PAN, Yonghong ZHANG, Lijian XIN, Ying WANG, Xinru WANG. Joint Probabilistic Modeling Approach for Harmonic and Three-phase Unbalanced Disturbance Sources[J]. Journal of Power Supply, 2026 , 24 (7) : 243 -252 . DOI: 10.13234/j.issn.2095-2805.2026.7.243
Funding
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  • 2023 Inner Mongolia Power (Group) Co., Ltd. Science and Technology Innovation “Unveiled Marshal” Project(2023-3-2)
  • 2023 Inner Mongolia Autonomous Region Science and Technology Program(2023KYPT0020)
Appendix
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Year 2026 volume 24 Issue 7
33
6
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Article Info
doi: 10.13234/j.issn.2095-2805.2026.7.243
  • Receive Date：2024-09-10
  • Online Date：2026-10-29
  • Published：2026-07-30
Article Data
Affiliations
History
  • Received：2024-09-10
  • Revised：2024-10-03
  • Accepted：2024-10-13
Funding
2023 Inner Mongolia Power (Group) Co., Ltd. Science and Technology Innovation “Unveiled Marshal” Project(2023-3-2)
2023 Inner Mongolia Autonomous Region Science and Technology Program(2023KYPT0020)
Affiliations
    1.Inner Mongolia Power (Group) Co., Ltd., Inner Mongolia Power Research Institute Branch, Hohhot 010020, China
    2.Inner Mongolia Key Laboratory of Smart Grid of New-type Power System, Hohhot 010020, China
    3.Inner Mongolia Power (Group) Co., Ltd., Hohhot 010020, China
    4.Inner Mongolia Power (Group) Co., Ltd., Ordos Power Supply Company, Ordos 017000, China
    5.College of Electrical Engineering, Sichuan University, Chengdu 610065, China
References
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https://castjournals.cast.org.cn/joweb/dyxb/EN/10.13234/j.issn.2095-2805.2026.7.243
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