Real-time State Prediction Based Coordinated Control Strategy of LIQHYSMES

LIQHYSMES (Liquid hydrogen with superconducting magnetic energy storage) offers rapid response, substantial capacity, and low energy conversion losses, making it ideal for large scale renewable energy integration and power grid stability. However, challenges remain in fully coordinated utilization of the storage units and safe, stable operation of the storage magnets. Accurate state prediction and control are vital for the efficient operation and coordination of LIQHYSMES. This paper proposes a state prediction based LIQHYSMES coordinated control strategy. Firstly, a superconducting magnet state prediction model based on the random forest algorithm is established. Secondly, the coordinated control strategy is outlined. Finally, simulation analysis validates the prediction model and control strategy, demonstrating their accuracy and effectiveness.