Adaptive superconductive magnetic energy storage (SMES) control method and system

摘要

The adaptive superconductive magnetic energy storage (SMES) control method and system control a SMES device connected to a power generation system. A radial basis function neural network (RBFNN) connected to the controller adaptively adjusts gain constants of the controller. A processor executes an improved particle swarm optimization (IPSO) procedure to train the RBFNN from input-output training data created by the IPSO, and thereafter generate starting weights for the neural network. Tests carried out show that the proposed adaptive SMES controller maintains the DC capacitor voltage constant, thus improving the efficiency of wind energy transfer. The power output (reactive and real) of the SMES device improves the voltage profile following large voltage dips and provides added damping to the system.