GGNet: A novel graph structure for power forecasting in renewable power plants considering temporal lead-lag correlations

Author:

Zhu Nanyang,Wang Ying,Yuan Kun,Yan Jiahao,Li Yaping,Zhang Kaifeng

Funder

State Grid Corporation of China

Publisher

Elsevier BV

Reference56 articles.

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3. A comprehensive review on deep learning approaches in wind forecasting applications;Wu;CAAI Trans Intellig Technol,2022

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5. Short-term wind power forecast based on ARX models;Duran;J Energy Eng,2007

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