A research group led by Spain’s Valencia Polytechnic University has developed a novel single-parameter power forecasting method for residential PV installations. The proposed approach defines interval ...

A team of researchers have developed a domain adaption framework capable of transferring knowledge from solar power plants with abundant data to plants that need to be trained without labelled data.

A team of scientists from around the world has created the first system that can predict when and where extremely powerful solar storms, called superflares, are most likely to happen. These storms can ...

The in-depth observations of First Nations seasonal calendars could be key to improving solar power forecasting, according to a world-first study by Charles Darwin University (CDU). Subscribe to our ...

Scientists develop a forecasting system that predicts high-risk windows and regions for solar superflares, using 50 years of X-ray data and machine learning techniques.

A peer-reviewed study published in the Journal of Geophysical Research: Space Physics has established a method to forecast ...

Wednesday, November 26, in Sydney last year started out like a normal day, but over the space of just one hour at midday fortunes were won and lost in the wholesale electricity market. Demand for ...

Breakthroughs, discoveries, and DIY tips sent six days a week. Terms of Service and Privacy Policy. A truly sustainable future requires solar power, but trying to ...