In a major policy shift towards electricity market liberalization, China has introduced contract for difference (CfD) auctions for renewable energy plants and removed the energy storage mandate, which has driven up to 75% of the nation's demand to date.
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This paper presents an innovative approach to short-term (1 to 6 hour horizon) wind power forecasting at a national level. The method leverages Automated Deep Learning combined with Numerical Weather Predictions wind speed maps to accurately forecast wind power.
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