Grid-tied power electronic converters serve as power processing interfaces between the distributed generation units, energy storage systems, flexible loads, and the electrical power grids. Therefore, in the future 100% renewable power system, vast majority of electrical energy will be processed by power converters, which means that their responsibility for supporting the operation of the grid will dramatically increase.
In this context, grid-tied power converters will need to provide a wide variety of ancillary services such as frequency and voltage support, harmonic and unbalance compensation, as well as synthetic inertia emulation to ensure safe and stable operation of power grids. Another important functionality will be grid-forming capability, which means that such converters will be able to set up autonomous grids (also called microgrids) individually or in joint effort with other converters.
Most modern power converters use cascaded linear control to achieve aforementioned functionalities, as it allows analytical design and guaranteed performance. However, it also inevitably leads to several performance limitations, most notably high sensitivity, inflexibility and limited bandwidth.
Our research focuses on developing advanced control methods that take advantage of modern control and artificial intelligence theory as well as cutting-edge experimental platforms in order to push back the frontiers of science and generate new and improved control strategies of both individual and populations of smart grid tied power converters that will enable their smooth integration in the smart grid and also facilitate their application in other sectors.
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