2023
DOI: 10.1088/1742-6596/2631/1/012022
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Application of a novel generative adversarial network to wind power forecasting

G C Liao,
R C Wu,
T T Wu
et al.

Abstract: As the global economy rapidly develops, energy consumption and carbon dioxide emissions have increased annually, prompting countries to strive for carbon neutrality by 2050. Accurate wind power forecasting can aid power system dispatch departments to obtain wind farms’ output and improve the power system’s new energy absorption capacity by coordinating multiple power generation resources. To this end, this study proposes a novel method for wind power forecasting: the Generative Adversarial Network method-based… Show more

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