Forecasting Power Output of Photovoltaic Systems Based on Weather Classification and Support Vector Machines

By Jie Shi, Weijen Lee, Yongqian Liu, Yongping Yang, Peng Wang. IEEE transactions on industry applications, 2011

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Short-Term Photovoltaic Power Forecasting Using an LSTM Neural Network and Synthetic Weather Forecast (2020, methodology): “The weather classification and SVM are used to develop four PV forecasting models corresponding to four types of days in [24].”
Generative adversarial networks and convolutional neural networks based weather classification model for day ahead short-term photovoltaic power forecasting (2019, background): “According to the existing achievements in relevant studies, weather classification has been regarded as an effective pre-processing step in order to enhance the prediction accuracy for short-term solar forecasting [20-22], especially for day-ahead forecasting.”
Review of photovoltaic power forecasting (2016, background): “…et al., 2011a; Fonseca et al., 2011b; Lu et al., 2015; Monteiro et al., 2013a; Pelland et al., 2011; Almeida et al., 2015; Ramsami and Oree, 2015; Shi et al., 2011; Tao et al., 2010; Zamo et al., 2014a; Zhang et al., 2015a; Hong et al., in press; Leva et al., 2015; Ogliari et al., 2013; Simonov…”