Electrical engineering
[Closed]
Work description
The work programme focuses on developing advanced real-time control and protection algorithms to address the evolving challenges in power systems due to the massive integration of renewable energy sources. These challenges include increased variability in system conditions and changing fault dynamics, which can impact the performance and coordination of protection schemes. The programme will involve implementing simulation models that incorporate centralized protection approaches, combined with optimization tools and machine learning techniques to enhance protection performance. The developed algorithms and models will be tested and validated using PHIL infrastructure and real-time simulators, such as OPAL-RT, at INESC TEC’s Smart Grid and Electric Vehicles Laboratory. Appropriate documentation will be prepared to detail the methodologies, testing processes, and results, ensuring transparency, reproducibility, and scalability of the developed solutions.
Minimum profile required
Knowledge of power system protection principles and dynamics. Experience in modeling and simulation of power systems using tools such as Matlab/Simulink or PowerFactory DigSilent. Basic understanding of optimization tools and machine learning techniques applied to protection systems.
Preference factors
Experience in power system protection and renewable energy integration. Familiarity with real-time digital simulators (e.g., OPAL-RT) and PHIL. Experience in modeling and simulation tools such as Matlab/Simulink or PowerFactory DigSilent. Programming experience in Python, particularly for optimization and machine learning applications. Knowledge of centralized protection schemes.
Application Period
Since 06 Feb 2025 to 19 Feb 2025
[Closed]
Centre
Power and Energy Systems