Dear Colleagues,

Solar photovoltaic (PV) energy is becoming an increasingly vital source in power grids for energy harvesting. Inspired by the plummeting cost and regulative incentives, the penetration of PV systems is increasing. Nonetheless, due to the stochastic nature of solar resources, there is a growing concern that the variable PV generation could strain the grid. On this point, solar forecasting, which consists of solar irradiance forecasting and PV power forecasting, has become an essential aspect to cope with solar variabilities, thereby bringing solar PV one step closer to “grid-friendly”. In modern power systems, solar forecasting has been widely applied in economic planning, auxiliary operations, frequency regulation, and real-time power balancing. By forecasting the solar irradiance and projected generation in the near future, it could offer remarkable control reliability and power quality advantages to the power system, in addition to promoting the local consumption of PV energy. In recent years, various solar forecasting methods have emerged owing to the rapid development of computational efficiency and sensing techniques, such as time series forecasting, machine-learning-based forecasting, image-based forecasting, numerical weather prediction etc., ranging from intra-minute to day-ahead timescales.

This Special Issue aims to collect emerging research achievements within the scope of solar forecasting (e.g., solar irradiance forecasting and photovoltaic power forecasting) and its application to PV system control and grid operations. Prospective authors are invited to submit original contributions or survey papers for peer review for publication in Electronics. Topics of interest in the Special Issue include, but are not limited to:

• Physical/data-driven methods for solar forecasting;
• AI and machine learning applications in solar PV systems;
• Reliability assessment of operational solar forecasting;
• Solar forecasting reconciliation and hierarchical forecasting;
• Atmospheric science applications in solar forecasting;
• Solar forecasting applications in PV system control/grid operations;
• Data articles for solar forecasting;
• Emerging sensing and measurement techniques;
• PV system/solar irradiance modeling and simulation techniques;
• Reliability modeling and characteristic analysis of high-PV-penetration power systems.

Dr. Xingshuo Li
Dr. Chenggang Cui
Dr. Xiaoyang Chen
Guest Editors

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• physical/data-driven methods for solar forecasting 
• AI and machine learning applications in solar PV systems 
• reliability assessment of operational solar forecasting 
• solar forecasting reconciliation and hierarchical forecasting 
• atmospheric science applications in solar forecasting 
• solar forecasting applications in PV system control/grid operations 
• data articles for solar forecasting
• emerging sensing and measurement techniques
• PV system/solar irradiance modeling and simulation techniques 
• reliability modeling and characteristic analysis of high-PV-penetration power systems