As energy supply and demand rapidly evolve, Network in association with Kelvatek investigates the role of machine learning in the future development of the smart grid in a downloadable report.
Network operators are increasingly looking to take data from their energy assets then use algorithms and intelligent modelling to enhance their insight and decision making.
But with data science being a relatively new field for the energy sector, just how should it build a data network to support the physical network?
Power optimisation specialist Kelvatek, part of international engineer Camlin Group, has set up a Machine Learning Group to develop its expertise in data science and artificial intelligence for the energy sector.
Download our Kelvatek partnership study for
- Expert opinion from the Energy Data Task Force chair
- Insights into how Artificial Intelligence can help to meet future challenges in the energy networks
- Insights into the software and systems available today
- Information on today's trials and demonstration projects
- Views on the business case for predictive analytics and machine learning across the network
To download this partnership study please submit your details on the form on the left.