SHORT-TERM PREDICTION OF PHOTOVOLTAIC POWER BASED ON IMPROVED PHASE SPACE RECONSTRUCTION AND MULTI-CHANNEL CONVOLUTION-FPN NETWORK

Zhao Xin; Luo Jiabin; Jiang Anqi; Hu Hao; Ma Yukun; Zhang Shuqing

doi:10.19912/j.0254-0096.tynxb.2024-1239

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (11) : 299-307. DOI: 10.19912/j.0254-0096.tynxb.2024-1239

SHORT-TERM PREDICTION OF PHOTOVOLTAIC POWER BASED ON IMPROVED PHASE SPACE RECONSTRUCTION AND MULTI-CHANNEL CONVOLUTION-FPN NETWORK

Zhao Xin¹, Luo Jiabin², Jiang Anqi², Hu Hao², Ma Yukun², Zhang Shuqing²

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Abstract

Aiming at the problem that the large uncertainty of PV power leads to its low prediction accuracy, a short-term prediction method of PV power based on improved phase space reconstruction and multi-channel convolution-feature pyramid networks（FPN） is proposed. Firstly, the phase space reconstruction method is improved to reduce the computation by finding the delay time via maximum joint entropy based on symbolic analysis, and the embedding dimension for unfolding the chaotic structure is quickly and automatically determined by the improved Cao algorithm, which has accuracy and efficiency. Then we reconstruct the PV power with the improved phase space method and prove that it has chaotic characteristics, extract the chaotic features by multi-channel convolutional neural network （Mul-CNN）, and at the same time, utilize the FPN network to fuse the chaotic features of the PV power with the meteorological features as the dynamic input features of the FPN network, to fully exploit the chaotic features of the FPN network. network, fully exploiting the spatial features between the data, and finally obtaining the prediction results through multiple fully connected layers. The method is evaluated on a domestic public dataset to do experiments, and compared with other network models, it proves that the prediction model is more accurate.

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neural networks / feature extraction / photovoltaic power generation / phase space methods / power prediction

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Zhao Xin, Luo Jiabin, Jiang Anqi, Hu Hao, Ma Yukun, Zhang Shuqing. SHORT-TERM PREDICTION OF PHOTOVOLTAIC POWER BASED ON IMPROVED PHASE SPACE RECONSTRUCTION AND MULTI-CHANNEL CONVOLUTION-FPN NETWORK[J]. Acta Energiae Solaris Sinica. 2025, 46(11): 299-307 https://doi.org/10.19912/j.0254-0096.tynxb.2024-1239

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