1. Abdel-Basset, M., Hawash, H., Chakrabortty, R.K., et al.: Pv-net: an innovative deep learning approach for efficient forecasting of short-term photovoltaic energy production. J. Clean. Prod. 303(127), 037 (2021)
2. Agoua, X.G., Girard, R., Kariniotakis, G.: Short-term spatio-temporal forecasting of photovoltaic power production. IEEE Trans. Sustain. Energy 9(2), 538–546 (2017)
3. Behera, M.K., Majumder, I., Nayak, N.: Solar photovoltaic power forecasting using optimized modified extreme learning machine technique. Eng. Sci. Technol. Int. J. 21(3), 428–438 (2018)
4. Chen, B., Lin, P., Lai, Y., et al.: Very-short-term power prediction for PV power plants using a simple and effective RCC-LSTM model based on short term multivariate historical datasets. Electronics 9(2), 289 (2020)
5. Cheng, H., Ding, X., Zhou, W., et al.: A hybrid electricity price forecasting model with Bayesian optimization for German energy exchange. Int. J. Electr. Power Energy Syst. 110, 653–666 (2019)