[1] Pierro M, Bucci F, De Felice M, et al. Multi-model ensemble for day ahead prediction of photovoltaic power generation[J]. Solar Energy, 2016, 134(4): 132-146.
[3] Cheng K, Guo L M, Wang Y K, et al. Application of clustering analysis in the prediction of photovoltaic power generation based on neural network[J]. IOP Conf. Series: Earth and Environmental Science, 2017, 93(6): 120-124.
[8] Mashud Rana, Ashfaqur Rahman. Multiple steps ahead solar photovoltaic power forecasting based on univariate machine learning models and data re-sampling[J]. Sustainable Energy, Grids and Networks, 2020, 28(3): 21-26.
[10] Cheng Gang, Song Shaojian, Lin Yuzhang, et al. Enhanced state estimation and bad data identification in active power distribution networks using photovoltaic power forecasting[J]. Electric Power Systems Research, 2019, 42(10): 177-183.
[11] Gao Mingming, Li Jianjing, Feng Hong, et al. Day-ahead power forecasting in a large-scale photovoltaic plant based on weather classification using LSTM[J]. Energy, 2019, 18(8): 187-193.
