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Prognose af elforbrug×Harmonisk forvrængningsanalyse×
FagområdeElektroteknikElektroteknik
FamilieProcess / pipelineProcess / pipeline
Oprindelsesår1960s1822
OphavspersonElectrical utilitiesJean-Baptiste Joseph Fourier
TypeComputational pipelineComputational pipeline
Oprindelig kildeHippert, 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 ↗
Aliasserdemand forecasting, electricity consumption prediction, load demand estimationharmonic content analysis, THD analysis, Fourier harmonic decomposition
Relaterede44
ResuméLoad 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.
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ScholarGateSammenlign metoder: Load Forecasting · Harmonic Distortion Analysis. Hentet 2026-06-17 fra https://scholargate.app/da/compare