Operating Reserve Quantification Using Prediction Intervals of Wind Power: An Integrated Probabilistic Forecasting and Decision Methodology

Adequate reserves are urgently needed to hedge against wind power forecasting uncertainties in power systems. Traditional reserve quantification sequentially acquires statistical features of wind power and then determines reserve amounts. This paper establishes a novel integrated probabilistic forec...

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Veröffentlicht in:	IEEE transactions on power systems Jg. 36; H. 4; S. 3701 - 3714
Hauptverfasser:	Zhao, Changfei, Wan, Can, Song, Yonghua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.07.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Confidence intervals Cost function Forecasting Integer programming Intervals Linear programming Machine learning Mathematical models Mixed integer Mixed integer linear programming Operating costs Operating reserve prediction interval probabilistic forecasting Probabilistic logic Reserves Statistical analysis Stochastic processes Uncertainty Wind forecasting Wind power Wind power generation
ISSN:	0885-8950, 1558-0679
Online-Zugang:	Volltext
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