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PV resource evaluation based on Xception and VGG19 two-layer network algorithm

Li, Lifeng; Yang, Zaimin; Yang, Xiongping; Li, Jiaming; Zhou, Qianyufan*
Science Citation Index Expanded
南方电网技术研究中心

摘要

With the increasing global demand for new energy sources, Photovoltaic (PV) is increasingly emphasized as a renewable energy source globally. Consequently, the assessment of PV resources has become crucial. Existing single frameworks and algorithms for PV resource assessment lead to low assessment accuracy. To alleviate the deficiency, this study proposes a two-layer network algorithm based on Xception and VGG19 for the evaluation of PV resources. The proposed method combines Xception convolutional neural network and VGG19 convolutional neural network. In addition, this study constructs a two-layer network framework based on the two-layer network algorithm. The feasibility and reliability of the proposed method are verified by simu-lating the proposed method under the case. Compared with existing algorithms, the proposed method and framework can improve the accuracy of PV resource assessment.

关键词

Photovoltaic resource assessment Convolutional neural networks Double layer network algorithm Two-tier network framework