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Conference object . 2024
License: CC BY
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IET Conference Proceedings
Article . 2024 . Peer-reviewed
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An optimized probabilistic forecasting approach for hybridized wind power plants

Authors: Couto, António; Algarvio, Hugo; Estanqueiro, Ana;

An optimized probabilistic forecasting approach for hybridized wind power plants

Abstract

This study addresses the challenges of integrating hybrid power plants, combining wind and solar power, into power systems and electricity markets—a relatively new area of research. It introduces a probabilistic power forecasting approach tailored to hybridized wind and solar power plants. Key findings reveal that hybridization consistently increases the remuneration of producers compared to standalone wind power plants, with greater benefits observed in scenarios with higher generation complementarity between wind and solar. Moreover, the use of quantiles to calibrate forecasts significantly improves remuneration compared to traditional deterministic forecasting methods that rely on expected power values. This work has received funding from the EU Horizon 2020 research and innovation program under project TradeRES (grant agreement No 864276). 

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Top 10%
Average
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