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Research on Short-Term Photovoltaic Power Prediction Method Based on an Improved Rime Optimization Algorithm
Power Generation Technology   Vol. 47, Issue 4, Pages: 761-773(2026)
Frontier AI Technologies and Large Model Applications for New Power Systems|Updated:2026-09-01
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    • Research on Short-Term Photovoltaic Power Prediction Method Based on an Improved Rime Optimization Algorithm

    • “The challenge of integrating photovoltaic power generation into the grid is severe. "Building a high-precision photovoltaic power prediction model and accurately depicting the fluctuations of photovoltaic power with meteorological conditions is of great significance for ensuring the stable operation of the power grid." The research team proposed the IRIME ResNet LSTM Dropout combination model, which effectively improves the prediction accuracy and provides theoretical support for the safe and stable operation of the power grid.”
    • DOI:10.12096/j.2096-4528.pgt.260408    

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    • Revised:2025-12-26,

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Related Author

PENG Chunhua
FU Xuepeng
LUO Yong
SUN Huijuan
LIU Zhiqiang
XIE Nan
KONG Fanxin
ZENG Zhixiang

Related Institution

School of Electrical and Automation Engineering, East China Jiaotong University
School of Energy Science and Engineering, Central South University
Xi’an Thermal Power Research Institute Co., Ltd.
Shandong Suoxiang Intelligent Technology Co., Ltd.
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