Research
My research revolves around the domain of “Control and Optimization of Active Distribution Networks in the Presence of Uncertainties.” The key research themese are listed below.
Research themes
- Grid-aware Control Schemes for Active Distribution Networks
- Data-driven Control, Model-less Control Schemes in Data-limited Setting
- Network and State Parameter Estimation Under Data-limited Setting
- Synthetic Networks Generation
Grid-aware Control Schemes for Active Distribution Networks
My research focuses on developing different centralized and distributed algorithms to harness flexibility from various distributed energy resources to provide ancillary grid services while ensuring safe operation under various kinds of uncertainty. The developed algorithms (schematically shown in Figure below) were validated on real-world systems in collaboration with Distribution System Operators, establishing the realisticness of the proposed schemes and can be rolled out for commercialization.
Data-driven Control, Model-less Control Schemes in Data-limited Setting
My work also addresses challenges in data-limited settings by data-driven control and estimation schemes, ensuring robust solutions even when the grid data are incomplete. Methods were developed to derive network models using smart meters and phasor measurement units, which were then used for the optimal control of the network, as illustrated in Figure below. This approach was also experimentally validated on real-world networks.
Network and State Parameter Estimation Under Data-limited Setting
With the growing integration of stochastic renewable generation and adaptable resources in electrical distribution systems, distribution utilities are increasingly eager to improve the visibility of their networks using distribution system state estimation (DSSE). However, scarcity of measurements and a limited communication bandwidth challenges the ability of the distribution utilities to estimate distribution system states. This research tackles this problem by different state and parameter estimation method for distribution networks.
Synthetic Networks Generation
My research also looks at synthetic network generation of the power systems to tackle the problem of realistic network data. My previous work developed the first synthetic representation of the Swiss distribution systems to tackle the lack of realistic data and is made publicly available. Then it was used to perform a countrywide optimization of the solar hosting capacity of Swiss distribution systems and optimal planning of energy storage systems that would be required to exceed the solar hosting capacity limits of existing power networks.