An Advanced Hybrid Boot-LSTM-ICSO-PP Approach for Day-Ahead Probabilistic PV Power Yield Forecasting and Intra-Hour Power Fluctuation Estimation

An Advanced Hybrid Boot-LSTM-ICSO-PP Approach for Day-Ahead Probabilistic PV Power Yield Forecasting and Intra-Hour Power Fluctuation Estimation

Probabilistic forecasting models have been developed over the past years in order to aid in the estimation of the uncertainty of the predictive results. A hybrid, bootstrapping long-short term memory (Boot-LSTM)-based model is proposed in this paper, in order to construct accurate prediction interva...

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Bibliographic Details
Main Authors: Ioannis K. Bazionis, Markos A. Kousounadis-Knousen, Vasileios E. Katsigiannis, Francky Catthoor, Pavlos S. Georgilakis
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Solar power forecasting
long short-term memory
bootstrap
prediction intervals
chicken swarm optimizer
seasonal analysis
Online Access:https://ieeexplore.ieee.org/document/10477983/

Internet

https://ieeexplore.ieee.org/document/10477983/

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