N.B. Posters, Presentations, PhD Thesis, etc. are available on my Research Gate Profile. If you do not have one, mail me.
Renewable Energies play a key role in the decarbonization process. Unfortunately, they affect the traditional planning and operation of power systems. A great effort must be done to effectively integrate the variable renewable energies to realize electrical grids with high shares of renewables.
Global Warming is increasing the intensity and frequency of many weather events, causing long and extensive blackouts. Traditional reliability-oriented planning and operation strategies may be not effective against these extreme events. For this reason, novel decision-making tools resilience-oriented must be developed and applied in the industry to make the power systems more resilient.
Effective decision-making is critical for power generation companies and system operators. However, the presence of numerous uncertain variables in the current power systems can undermine the effectiveness of deterministic-based decision-making tools. To address this issue, the industry can utilize stochastic, Bayesian, Affine Arithmetic, and data-driven based tools to support power system operators in making informed and effective decisions.
The proliferation of converter-based power generation sources, electric vehicles, and complex loads, along with the increasing size of power systems, makes it challenging to predict system behavior accurately. A Digital Twin is an online replica of a physical system that can simulate the system's behavior under various conditions, test real-time algorithms, and analyze the interaction of physical devices with the simulated power system using hardware-in-the-loop (HIL) techniques.