Station site2.

<div><p>This study focuses on the short-term power prediction of photovoltaic power stations, aiming to address the intermittent and fluctuating problems of photovoltaic power generation, in order to improve the prediction accuracy and ensure the stable operation of the power system. Inn...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Jiangli Yu (4601986) (author)
مؤلفون آخرون:	Gaoyi Liang (22311429) (author), Lei Wang (6656) (author), Huiyuan He (22311432) (author), Yuxin Liu (505575) (author), Qi Liu (33068) (author), Xinjie Cui (498116) (author), Hao Wang (39217) (author)
منشور في:	2025
الموضوعات:	Biotechnology Plant Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified mean absolute error decomposed modal components solid data foundation reduce data complexity photovoltaic power stations photovoltaic power generation term power prediction traditional prediction model lstm combined model kepler optimization algorithm kepler algorithm prediction accuracy data preprocessing power system power changes lstm leverages xlink "> three work subsequent predictions study focuses strongly proves stable operation significant optimization result correction reliable method proposed method innovatively introduce innovative idea grid connection great significance frequency characteristics fluctuating problems evaluation indicators entire process dynamic trends deeply integrated
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Station site2.

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