ScholarGate
助手

方法对比

并排查看您选择的方法;存在差异的行会高亮显示。

负荷预测×谐波失真分析×
领域电气工程电气工程
方法族Process / pipelineProcess / pipeline
起源年份1960s1822
提出者Electrical utilitiesJean-Baptiste Joseph Fourier
类型Computational pipelineComputational pipeline
开创性文献Hippert, H. S., Pedreira, C. E., & Souza, R. C. (2001). Neural networks for short-term load forecasting: A review and evaluation. IEEE Transactions on Power Systems, 16(1), 44-55. DOI ↗IEEE Std 519-1992: IEEE Recommended Practices and Requirements for Harmonic Control in Electrical Power Systems. link ↗
别名demand forecasting, electricity consumption prediction, load demand estimationharmonic content analysis, THD analysis, Fourier harmonic decomposition
相关44
摘要Load forecasting predicts future electrical demand on power systems across various time horizons: minutes to hours (short-term), days to weeks (medium-term), and months to years (long-term). Accurate forecasting is essential for economic dispatch, unit commitment, and system reliability. Methods range from classical statistical regression to modern machine learning approaches.Harmonic distortion analysis quantifies the deviation of voltage or current waveforms from sinusoidal shape due to nonlinear loads. Using Fourier decomposition, engineers separate the waveform into its fundamental frequency and harmonic components (integer multiples of 50 or 60 Hz). Harmonic analysis is critical for assessing power quality and designing filters in modern power systems with high penetration of nonlinear devices.
ScholarGate数据集
  1. v1
  2. 3 来源
  3. PUBLISHED
  1. v1
  2. 3 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: Load Forecasting · Harmonic Distortion Analysis. 于 2026-06-17 检索自 https://scholargate.app/zh/compare