The energy sector is nowadays undergoing a huge structural transformation. In a couple of decades, the energy grid will operate very differently than today. There 2 important reasons for these transition.

First, with global population increasing, and 750 millions people with no access to electricity at all, energy production must increase to give everyone a chance to benefit for it. Secondly, at the same time energy must become cleaner. We must keep global warming from going above 1.5 degrees Celsius to avoid most severe consequences.

This transformation brings challenges: renewable energy sources are by nature intermittent and are generated in a highly decentralized fashion. There is also a lack of coordination between energy providers ad consumers, which makes it difficult to match demand and supply. 

Overcoming these challenges requires integration of various data driven and Artificial Intelligence techniques to enable a better communication between demand and supply and a better flexibility of the grid.

In this use case context, we focus on the prediction of the energy demand. So let's learn how the SAP Business Technology Platform (BTP) can help in the global energy transition. Explore an AI-powered use case for utilities, focusing on the prediction of energy demand. Discover the solution architecture and prototype scope based on BTP, while keeping S/4HANA Cloud core clean.