Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Avaliação da Qualidade de Energia× | Previsão de Carga× | |
|---|---|---|
| Área | Engenharia elétrica | Engenharia elétrica |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | 1995 | 1960s |
| Autor original≠ | IEEE Standards committee | Electrical utilities |
| Tipo | Computational pipeline | Computational pipeline |
| Fonte seminal≠ | IEEE Std 1159-2019: IEEE Recommended Practice for Monitoring Electric Power Quality. link ↗ | 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 ↗ |
| Outros nomes | PQ assessment, power quality survey, voltage quality analysis | demand forecasting, electricity consumption prediction, load demand estimation |
| Relacionados | 4 | 4 |
| Resumo≠ | Power quality assessment evaluates the suitability of electrical voltage and current waveforms for reliable equipment operation. It measures deviations from ideal sinusoidal waveforms, including voltage sags, swells, harmonics, transients, and imbalance. Comprehensive assessment is critical for ensuring equipment protection, identifying root causes of malfunctions, and optimizing mitigation strategies. | 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. |
| ScholarGateConjunto de dados ↗ |
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