Research group for optimal planning and control of electric power systems with a high share of renewable energy sources

Optimal planning and operation of transmission and distribution networks with a high share of RES and EV. In this part, the activities are related to:

• Development of methods for optimal extension planning of transmission/distribution networks with a high share of RES and electric vehicles,
• Development of methods for the optimal operational management of power networks to increase grid hosting capacity under the current network state,
• Analysis of the different sources of flexibility to create conditions for the energy transition of the classic power system to RES-based systems.

Optimal microgrid management. In this part, the activities include:

• Application of model-predictive control methods for optimization of microgrid operation and creation of conditions for participation in the  ancillary services market,
• Application of machine learning methods to develop generic approaches for optimal microgrid management.

Application of machine learning and deep learning methods  in power equipment diagnostics and relevant power system parameter forecasting. Activities in this section include:

• Development of methods for forecasting important market/power system parameters such as day-ahead / intra-day load forecasting,  forecasting the production of wind farms / PV power plants, forecasting hydrological conditions at the level of individual basins, etc.
• Development of methods based on machine learning and Bayesian statistics for forecasting and classification of equipment condition in power facilities.
• Development of methods based on machine learning for the analysis of transient stability and power system fault classification.