AI for Flexible Energy Systems

Being a part of our sustainable development within the power and energy sector, smart grids are drawing more and more attention, and the entire energy system has to be flexible in order to be able to integrate a large amount of fluctuating renewable energy production from wind and solar.

Utilizing flexibility unlocks the possibility to integrate decentralized renewable energy production, combined with integrated physical and virtual storage solutions as well as flexible consumers and prosumers. The transition to a sustainable low-carbon society based on intermittent renewable energy sources calls for a change to an energy system where the demand follows the production. This requires development of new methods to enable flexibility at all levels of the energy system of the modern society.

For further development of smart grids and energy infrastructure of the future, research on forecasting flexibility as well as the intelligent operation of control is a keystone. The objective of the Ph.D project is to develop methods to utilize energy resources more efficiently and effectively (smarter). Furthermore the project aims to describe energy flexibility in integrated energy systems as well as providing innovative and data intelligent solutions for flexible energy systems. Applying AI and machine learning to enhance flexibility solutions for energy system could supposedly have a huge impact on the future energy systems (including smart grids) and be an important step towards CO2 neutral energy systems, which lays the ground for a sustainable society. Thus, the project will apply such methods for the energy market as well as operation and control of the grid, meaning for example ancillary services such as voltage and frequency control.

Additionally, the proposed Ph.D project will support the Innovation Fund Denmark project ‘Flexible Energy Denmark’ which aims at developing data intelligent methods for providing services for the future smart grids.