Performance Analysis of Single Phase Grid Connected Sapf Using Rbfnn Control Algorithm

Le résumé fourni par la source

Due to our industrial excessive exposure and consumer requirements, Power Quality (PQ) has several disturbances, such as voltage fluctuations, Power factor, harmonic current, and load unbalance, which are among the PQ issues that can affect a 1-phase grid-connected power distribution system. In order to overcome these PQ issues, compensation is required. This paper introduces a novel and simplified design of a radial basis function neural network (RBFNN) controller for a 1-phase shunt active power filter (SAPF) aimed at mitigating PQ issues. The network is trained online to effectively manage inverter control and reduce power quality disturbances. The proposed design features a single hidden-layer neuron with one input corresponding to the current drawn by the load. The fundamental component of load current is extracted from the controller. Tracking is completed in a single cycle and is quick. for load adjustment, the trained model performs exceptionally well under a range of loading circumstances. It has been demonstrated that simulation results are valid with the proposed Adaptive RBFNN controller.

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