Advances in Control Strategies for Renewable Energy Systems

The field of renewable energy systems is witnessing significant advancements in control strategies, aiming to enhance stability, efficiency, and resilience. Researchers are exploring innovative approaches to address the challenges posed by intermittent energy sources and grid integration. Notably, the development of robust control strategies for wind turbines and grid-forming converters is gaining attention. These strategies focus on ensuring stable power delivery, preventing switch failures, and mitigating DC source saturation under overloaded conditions. The use of physics-informed neural networks and dissipativity-based distributed control is also being investigated to improve system stability and performance. Furthermore, studies are examining the transient synchronization stability of renewable energy grid-tied systems, including the analysis of low-voltage ride-through processes and the development of stability assessment methods. Overall, these advancements are contributing to the creation of more efficient, reliable, and responsive renewable energy systems. Noteworthy papers include:

  • A robust mechanical sensorless control strategy for active rectification of small wind turbines, which allows for the removal of mechanical sensors despite uncertainties in resistance and inductance parameters.
  • A dissipativity-based distributed control approach for DC microgrids, which provides a unified framework for co-designing distributed controllers and communication topologies to ensure stability despite destabilizing constant power load effects.

Sources

A robust mechanical sensorless control strategy for active rectification of small wind turbines

Transient synchronization stability analysis and assessment of DFIG system under severe faults

Small-Signal Stability Condition of Inverter-Integrated Power Systems: Closed-Form Expression by Stationary Power Flow Variables

Dissipativity-Based Distributed Control and Communication Topology Co-Design for DC Microgrids with ZIP Loads

Physics-Informed Neural Network-Based Control for Grid-Forming Converter's Stability Under Overload Conditions

Open-loop control design for contraction in affine nonlinear systems

Small-gain conditions for exponential incremental stability in feedback interconnections

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