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An artificial neural network based online adaptive control of superconducting magnetic energy storage system (SMES) controller has been proposed to improve the dynamic performance of a permanent magnet synchronous generator (PMSG) wind system. The training data for the neural network has been generated through an improved particle swarm optimization (IPSO) algorithm. The weighting matrix for the radial...
Dynamic performance of a permanent magnet synchronous generator wind system can be improved by injecting real and reactive power from a superconducting magnetic energy storage system (SMES) system. This article presents a method of determining the optimum gains of the SMES controller through an improved particle swarm optimization (IPSO) procedure. The procedure involves finding the SMES controller...
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