Xueqian Fu is an Associate Professor at China Agricultural University (CAU), a Senior Member of IEEE, and Vice Chairman of IEEE Smart Village-CWG, IEEE Young Professionals. He is a one of the World’s Top 2% Scientists 2023 and has been recognized as 'Outstanding Talent' and 'Young Star B’ by China Agricultural University. Dr. Xu received his Ph.D. degree from South China University of Technology in 2015 and was a Post-Doctoral Researcher at Tsinghua University from 2015 to 2017. His current research interests include Statistical Machine Learning, Agricultural Energy Internet, and PV system integration. He serves as Deputy Editor-in-Chief for Information Processing in Agriculture and as Associate Editor for IET Renewable Power Generation, Artificial Intelligence and Applications, Protection and Control of Modern Power Systems and the Journal of Data Science and Intelligent Systems. He also serves as a youth editor for Clean Energy Science and Technology and Lead Guest Editor role for International Transactions on Electrical Energy Systems.

• 1. Review of PV Uncertainty Models2. LSTM-based Day-Ahead Photovoltaic Power Prediction3. Transformer-based Intra-Day Photovoltaic Power Prediction4. Unsupervised Learning-based Annual Photovoltaic Power Scene Reduction5. Adversarial Network-based Annual Photovoltaic Power Simulation6. Photovoltaic Power Generation Meteorological Information Mining and Forecasting7. Statistical Machine Learning-based Probabilistic Power Flow in PV-integrated Grid8. Statistical Machine Learning-based Stochastic Planning for Photovoltaics9. Photovoltaics and Artificial Intelligence Applications – Future Predictions and Summary

Xueqian Fu is an Associate Professor at China Agricultural University (CAU), a Senior Member of IEEE, and Vice Chairman of IEEE Smart Village-CWG, IEEE Young Professionals. He is a one of the World’s Top 2% Scientists 2023 and has been recognized as 'Outstanding Talent' and 'Young Star B’ by China Agricultural University. Dr. Xu received his Ph.D. degree from South China University of Technology in 2015 and was a Post-Doctoral Researcher at Tsinghua University from 2015 to 2017. His current research interests include Statistical Machine Learning, Agricultural Energy Internet, and PV system integration. He serves as Deputy Editor-in-Chief for Information Processing in Agriculture and as Associate Editor for IET Renewable Power Generation, Artificial Intelligence and Applications, Protection and Control of Modern Power Systems and the Journal of Data Science and Intelligent Systems. He also serves as a youth editor for Clean Energy Science and Technology and Lead Guest Editor role for International Transactions on Electrical Energy Systems.

• 1. Review of PV Uncertainty Models2. LSTM-based Day-Ahead Photovoltaic Power Prediction3. Transformer-based Intra-Day Photovoltaic Power Prediction4. Unsupervised Learning-based Annual Photovoltaic Power Scene Reduction5. Adversarial Network-based Annual Photovoltaic Power Simulation6. Photovoltaic Power Generation Meteorological Information Mining and Forecasting7. Statistical Machine Learning-based Probabilistic Power Flow in PV-integrated Grid8. Statistical Machine Learning-based Stochastic Planning for Photovoltaics9. Photovoltaics and Artificial Intelligence Applications – Future Predictions and Summary

Xueqian Fu is an Associate Professor at China Agricultural University (CAU), a Senior Member of IEEE, and Vice Chairman of IEEE Smart Village-CWG, IEEE Young Professionals. He is a one of the World’s Top 2% Scientists 2023 and has been recognized as 'Outstanding Talent' and 'Young Star B’ by China Agricultural University. Dr. Xu received his Ph.D. degree from South China University of Technology in 2015 and was a Post-Doctoral Researcher at Tsinghua University from 2015 to 2017. His current research interests include Statistical Machine Learning, Agricultural Energy Internet, and PV system integration. He serves as Deputy Editor-in-Chief for Information Processing in Agriculture and as Associate Editor for IET Renewable Power Generation, Artificial Intelligence and Applications, Protection and Control of Modern Power Systems and the Journal of Data Science and Intelligent Systems. He also serves as a youth editor for Clean Energy Science and Technology and Lead Guest Editor role for International Transactions on Electrical Energy Systems.

• 1. Review of PV Uncertainty Models2. LSTM-based Day-Ahead Photovoltaic Power Prediction3. Transformer-based Intra-Day Photovoltaic Power Prediction4. Unsupervised Learning-based Annual Photovoltaic Power Scene Reduction5. Adversarial Network-based Annual Photovoltaic Power Simulation6. Photovoltaic Power Generation Meteorological Information Mining and Forecasting7. Statistical Machine Learning-based Probabilistic Power Flow in PV-integrated Grid8. Statistical Machine Learning-based Stochastic Planning for Photovoltaics9. Photovoltaics and Artificial Intelligence Applications – Future Predictions and Summary