Prediction error distributions for photovoltaic power from the DKASC and solar I datasets under various weather conditions and at different prediction horizons.

Prediction error distributions for photovoltaic power from the DKASC and solar I datasets under various weather conditions and at different prediction horizons.

<p>Prediction error distributions for photovoltaic power from the DKASC and solar I datasets under various weather conditions and at different prediction horizons.</p>

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Bibliographic Details
Main Author:	Yaopeng Han (22622718) (author)
Other Authors:	Chenxi Li (1459123) (author), Siqi Chen (387248) (author), Jinghao Zhao (10534757) (author), Yajun Tian (2414308) (author), Jun Wang (5906) (author)
Published:	2025
Subjects:	Biotechnology Ecology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified various weather conditions uncertainty analysis conducted recent benchmark models leverages data decomposition advanced iceemdan algorithm stratified heterogeneous network novel hybrid model monolithic modeling paradigms model &# 8217 power plant operations address complex non wise modeling stratified prediction model excels model employs complex dynamics xlink "> temporal information statistical stability results indicate rank tests primarily due precise component point predictions paper proposes mimo strategy median output inadequate representation high accuracy energy transformation accurately capture ablation experiments 1 %.
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