Frequency Control

Frequency control in power grids aims to maintain stable grid frequency despite fluctuating energy sources and loads, ensuring reliable power delivery. Current research emphasizes robust control strategies for systems with variable inertia, often employing machine learning techniques like reinforcement learning (RL) and neural networks (e.g., Neural-PI controllers) to adapt to dynamic conditions and mitigate cyber threats. This work is crucial for integrating renewable energy sources and improving grid resilience, with applications ranging from optimizing energy storage utilization to enabling efficient Vehicle-to-Grid (V2G) technologies and enhancing market participation of renewable energy assets. The development of model-free and explainable AI methods is also improving controller design and understanding of complex grid interactions.