Machine learning (ML) can be applied at the ‘edge’ where data processing functions are tightly targeted and power consumption must be low.

“Machine learning technologies are becoming much more popular in power systems as they help improve various power system applications. As the demand for machine learning expertise grows, it is ...

To date, there are many algorithms that can estimate the power produced by photovoltaic systems several hours ahead by learning from previous data and analyzing current variables.

Given the complexity and scale of this data, machine learning and AI are essential to accurately forecast and automate maintenance, which is why we need to have all the data aligned.

The increased digitization of the power generation industry means that artificial intelligence (AI) and machine learning (ML) are becoming synonymous with power generation.

The proposed framework also can potentially shape research in supporting the application of machine learning in power system reliability and can act as an initial step toward more early warning tools, ...

This hands-on tutorial shows how to choose and run machine learning models for solar power prediction using Google Colaboratory.