Harmonic Impedance Estimation Method Based on Improved Tornado Optimization Algorithm
[1]XIA Yankun,ZHENG Gaoping,HUANG Peng,et al.Harmonic Impedance Estimation Method Based on Improved Tornado Optimization Algorithm[J].Journal of Zhengzhou University (Engineering Science),2027,48(XX):1-10.[doi:10.13705/j.issn.1671-6833.2027.01.002]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
48
Number of periods:
2027 XX
Page number:
1-10
Column:
Public date:
2027-12-10
- Title:
- Harmonic Impedance Estimation Method Based on Improved Tornado Optimization Algorithm
- Keywords:
- System-side harmonic impedance; maximum information coefficient; PELT algorithm; deep hybrid kernel extreme learning machine; Tornado optimizer with Coriolis force
- CLC:
- TM711 TP18
- Abstract:
- To address the issue of sudden changes in system‑side harmonic impedance under operating conditions such as changes in power grid operating modes and capacitor switching, as well as the decline in estimation accuracy when background harmonic fluctuations are significant, a harmonic impedance estimation method based on the deep hybrid kernel extreme learning machine (DHKELM) optimized by improved tornado optimization algorithm was proposed. Firstly, to mitigate the effects of background harmonics and outliers, the maximum information coefficient (MIC) was used to filter data with strong correlations between harmonic voltage and harmonic current amplitudes. Secondly, the harmonic data samples were segmented based on the abrupt change points in the coarse impedance estimates detected by the PELT algorithm. Finally, the system‑side harmonic impedance was estimated for each segment of harmonic data using the DHKELM. Furthermore, to improve the model’s prediction accuracy, a tornado optimization algorithm (ITOC) enhanced by multi‑strategy chaos and the Nelder‑Mead simplex method was proposed to optimize the number of hidden layer nodes, kernel parameters, and weights of the DHKELM model. Simulations were conducted using the Norton equivalent model and an IEEE 13‑node system, and case studies were performed in conjunction with measured data. The results showed that, when the harmonic impedance on the customer‑side was no greater than that on the system‑side, the errors in impedance estimation under different background harmonic coefficients in the Norton simulation were all relatively small. In the IEEE 13‑node system simulation, the RMSE for amplitude and phase angle estimates were 0.002 Ω and 0.058°, respectively. In the case study analysis, the RMSE for amplitude and phase angle were 0.03 Ω and 0.02°, respectively, demonstrating high estimation accuracy and stability.
- References:
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Last Update:
2026-07-24
