Data-Driven Dynamic Probabilistic Reserve Sizing Based on Dynamic Bayesian Belief Networks

Due to the variability and partial unpredictability of renewable energy sources (RES), generation reserve sizing is key for managing operational risks and enhancing grid reliability. Most existing approaches for reserve sizing estimate the forecasting error for RES using either simple point forecast...

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Veröffentlicht in:	IEEE transactions on power systems 2019-05, Vol.34 (3), p.2281-2291
Hauptverfasser:	Fahiman, Fateme, Disano, Steven, Erfani, Sarah Monazam, Mancarella, Pierluigi, Leckie, Christopher
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Bayes methods Bayesian analysis Belief networks data-driven model Dynamic Bayesian belief networks Economic forecasting Energy management Gaussian distribution Mathematical analysis Mathematical models Normal distribution Power system dynamics Power system reliability Pricing probabilistic forecasting Probabilistic logic Probabilistic methods probabilistic reserve sizing Probability theory Reliability Renewable energy sources Risk management Sizing Statistical analysis Uncertainty
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