Salīdzināt metodes

	Novērtēšana jaudas kvalitātes ziņā	Slodzes prognozēšana
Nozare	Elektrotehnika	Elektrotehnika
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1995	1960s
Autors	IEEE Standards committee	Electrical utilities
Tips	Computational pipeline	Computational pipeline
Pirmavots	IEEE Std 1159-2019: IEEE Recommended Practice for Monitoring Electric Power Quality.	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.
Citi nosaukumi	PQ assessment, power quality survey, voltage quality analysis	demand forecasting, electricity consumption prediction, load demand estimation
Saistītās	4	4
Kopsavilkums	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.