Researchers from South Korea’s Incheon National University says they have developed two new machine learning-based models that better estimate the power generated by solar systems, helping to boost output from solar farms and better integrate the technology into power grids. Machine learning – a form of artificial intelligence where a “machine” is taught how to “learn” to predict something – is already an integral part of many solar projects around the world, and is used to predict output hours in advance.

.One specific type of machine learning model, called adaptive neuro-fuzzy inference system (ANFIS), has been widely used for forecasting the performance of complex renewable energy systems, and been found to be highly accurate in predicting a renewable project’s performance. Now, under the leadership of Professor Jong Wan Hu, an Incheon University research team has developed two new ANFIS-based machine learning models to better estimate the power generated by solar PV systems and up to a full day ahead.

“In terms of software, […]