Pioneering Self-Sufficient Renewable Energy SystemsAre you ready to drive innovation in renewable hydrogen production systems? Join our team to develop advanced methodologies for large-signal stability analysis and control, enabling self-sufficient operation of grid-forming renewable hydrogen systems under dynamic grid conditions.
Job DescriptionAs the Netherlands moves toward its ambitious goal of 70% renewable electricity by 2030, renewable hydrogen systems play a vital role in integrating intermittent renewable energy sources like wind and solar. These systems, powered by grid-forming power converters, aim to operate autonomously while reducing dependence on external grid support. Achieving self-sufficiency in renewable hydrogen systems under large disturbances is essential for their scalability and resilience in the evolving energy landscape.
This postdoc position focuses on advancing the large-signal stability analysis and enhancement of grid-forming renewable hydrogen systems, enabling robust, independent operation. Your research will address the dynamic challenges of maintaining stability and performance in these systems, ensuring their reliability as a cornerstone of the sustainable energy future.
Key Contributions:
-
Dynamic Modeling for Self-Sufficient Systems: Develop dynamic analytical models of grid-forming hydrogen systems to assess their large-signal stability and autonomous operation under various scenarios.
-
Large-Signal Stability Analysis: Investigate the design-oriented large-scale stability analysis methodologies to guarantee stable operation of grid-forming hydrogen system during large disturbances, such as grid voltage dips, rapid changing of renewable generation, various dc and ac faults and transients, etc.
-
Control Strategy Development: Design and implement innovative grid-forming control strategies to enhance the self-sufficiency and stability of renewable hydrogen systems without reliance on grid support.
-
Simulation and Experimental Validation: Use EMT-based simulation tools and experimental setups to validate your models and control solutions, ensuring real-world applicability.