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Keywords

time series trend; typical scenarios; high voltage harmonic; dual incentive; comprehensive evaluation

Abstract

In response to the challenge of existing assessment indicators and methods struggling to distinguish harmonic curve differences in typical scenarios where trend characteristics vary significantly and CP95 values are close, rarely considering the time series trend characteristics and incapable of representing the differences scientifically and rationally in harmonic levels, a high‑voltage harmonic characteristic assessment approach that takes into account the time series trend characteristics of typical scenarios is proposed. Firstly, based on the dual excitation theory, the temporal trend characteristics of the data sequence are extracted, and a comprehensive evaluation index system that encompasses traditional harmonic indicators and temporal trend characteristic indicators is established for high‑voltage harmonics covering time series trend characteristics. Subsequently, considering the interrelation characteristics among the established indicators, a comprehensive assessment model is presented for high‑voltage harmonics in typical scenarios based on the combination of sequential relationship analysis and the CRITIC method. Finally, case analysis validates the rationality and effectiveness of the proposed method. The case analysis indicates that the established time series trend characteristic indicators can effectively characterize the temporal development characteristics of data curves. For multiple harmonic curves with close CP95 values, they can effectively represent the differences in harmonic levels. Finally, the case analysis demonstrates that the established temporal trend characteristic indicators can effectively represent the temporal development characteristics of data curves. For multiple harmonic curves with close CP95 values, the indicators can efficiently characterize the differences in harmonic levels. The analysis results validate the rationality and effectiveness of the proposed method.

DOI

10.19781/j.issn.1673-9140.2023.06.023

First Page

215

Last Page

224

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