AI for Flexible Energy Systems - Data driven methods for DSO smart grid operation in the context of 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, especially for the power system as it is the system accommodating these changes.

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 power system equipment has traditionally been designed with static ratings, while there are seasonal variations in the operating environment. This means that there will be unused capacity in the grid at certain times. The intermittent renewable energy production and changing demand is also leading to concerns for power distribution system operators (DSO), such as voltage violations and reverse power flow. At the same time, there are usually no real-time measurements in the low voltage distribution grid where the customers are connected.

The Ph.D project focuses on developments for digitizing these low voltage grids and create new data-driven models for adaptive DSO smart grid operation. These ethods aim to give the DSOs increased observability in the low voltage grids through online monitoring and forecasting tools. Such tools are of importance to safely integrate renewable generation as well as flexibility solutions in the power system and be an important step towards CO2 neutral energy systems, which lays the ground for a sustainable society. The flexible solutions can also support the future smart grids with ancillary services such as voltage and congestion 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.

PhD project

By: Emma Margareta Viktoria Blomgren

Section: Dynamical Systems

Principal supervisor: Henrik Madsen

Co-supervisors

Project title: AI for Flexible Energy Systems - Data driven methods for DSO smart grid operation in the context of flexible energy systems

Term

Contact

Henrik Madsen
Professor, Head of section
DTU Compute
+45 45 25 34 08