Abstract:
In this paper, a novel optimal learning algorithm for partially unknown voltage-source inverters (VSIs) operating in parallel is presented. The algorithm designs game-the...View moreMetadata
Abstract:
In this paper, a novel optimal learning algorithm for partially unknown voltage-source inverters (VSIs) operating in parallel is presented. The algorithm designs game-theory-based distributed controllers to provide the appropriate working voltage magnitude and frequency at the load by converting dc voltage to ac voltage at the parallel VSIs. It takes advantage of information from the neighboring low pass L-C filters to improve harmonic distortion and guarantee equal sharing of the load current across the VSIs while avoiding current circulation during transient and ensuring stability and robustness. It builds upon the ideas of approximate dynamic programming (ADP) and uses only partial information of the system and the exosystem, which is connected only to some of the VSIs. The proposed framework was tested in simulations to show its effectiveness.
Published in: IEEE Transactions on Industrial Electronics ( Volume: 64, Issue: 5, May 2017)