The power system is changing rapidly, and new tools for predicting unwanted events are needed to keep a high level of security of supply. Large volumes of data from the Norwegian power grid have been collected over several years, and unwanted events as interruptions, earth faults, voltage dips and...

... This paper explores the possibilities of shifting certain household consumer-based loads in time, to reduce unnecessary load peaks to the grid which again can cause challenges for Distribution System Operators (DSOs). Historical measured data on household consumption and the consumption profile...

There is a growing interest in applying machine learning methods on large amounts of data to solve complex problems, such as prediction of events and disturbances in the power system. This paper is a comparative study of the predictive performance of state-of-the-art supervised machine learning...