Data-driven modeling and diagnostics of electric-vehicle charging loads for distribution network harmonic mitigation

Xin ZHOU, Qiaoling CHEN, Li ZHANG, Qianggang WANG, Niancheng ZHOU, Junzhen PENG, Yongshuai ZHAO

Electric Power ›› 2026, Vol. 59 ›› Issue (8) : 226-236.

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Abbreviation (ISO4): Electric Power      Chairperson: Changyu OUYANG

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Electric Power ›› 2026, Vol. 59 ›› Issue (8) : 226-236. DOI: 10.11930/j.issn.1004-9649.202509066
Original article

Data-driven modeling and diagnostics of electric-vehicle charging loads for distribution network harmonic mitigation

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Abstract

To analyze the impacts of electric vehicle（EV） charging loads on distribution network harmonics，a frequency-domain analysis framework based on harmonic extended linear modeling（HELM）is established.The cross-frequency coupling between voltage and current harmonics is characterized using a frequency coupling matrix.Sampling at 20 kHz and adopting a steady-state window of three fundamental cycles，the spectrum is extracted via discrete Fourier transform.Indicators including total harmonic distortion（THD），total demand distortion （TDD），root-mean-square value，peak value and crest factor are calculated.Furthermore，kernel density estimation，empirical distribution，the Kolmogorov-Smirnov test，principal component analysis，k-means clustering and three-dimensional visualization are jointly employed to systematically compare two scenarios：＂EV loads superimposed with other loads＂and ＂other loads only＂.Simulation results reveal that the voltage distributions of the two scenarios are highly consistent，while discrepancies mainly emerge in current characteristics.For the scenario incorporating EVs，the current root-mean-square value， THD and crest factor are generally lower with smaller dispersion；the energy proportion of low-order harmonics （2nd-10th orders）decreases，demonstrating a more fundamental-wave-dominated spectral feature.The proposed research provides methodological support and quantitative references for distribution network harmonic mitigation， optimization of filtering and rectification schemes for charging facilities，and improvement of assessment criteria for power quality.

This work is supported by General Program of National Natural Science Foundation of China（No.52077017），Science and Technology Project of Electric Power Research Institute of Yunnan Power Grid Co.，Ltd.（No.056200KC24100043）.

Key words

electric-vehicle charging / harmonic extended linear modeling / frequency coupling matrix / power quality

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Xin ZHOU , Qiaoling CHEN , Li ZHANG , et al . Data-driven modeling and diagnostics of electric-vehicle charging loads for distribution network harmonic mitigation[J]. Electric Power. 2026, 59(8): 226-236 https://doi.org/10.11930/j.issn.1004-9649.202509066

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