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Photovoltaic power prediction plays an extremely important role in the construction of smart power grid and power grid security protection. In order to solve the problem of unstable power generation and even damages to the power grid caused by the ever changing irradiance and meteorological conditions, this paper leverages the traditional time series prediction modeling method to the machine learning approaches, such as recurrent neural network (RNN), convolutional neural network (CNN) and decision tree (DT), and uses the ensemble machine learning method to improve the final prediction accurac...

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