Design and Implementation of a Hybrid Neuro-Fuzzy Corrector for DC Bus Voltage Regulation

Abstract

The pursuit of the MPP and the control of the inverter play a very important role in a PV system connected to the utility grid. In this paper, an intelligent method is used to regulate the DC bus voltage. The hybrid neuro-fuzzy algorithm HNFtype is used. The latter is a combination of fuzzy logic and neural networks. The PV chain, dependent on climatic conditions needs mechanisms to optimize the power it delivers, but also the injection of good quality energy to the utility grid. Among these mechanisms, there is the control of the three-phase inverter: grid currents control and DC bus voltage regulation which is based on the HNF. The implementation of the model and its simulation under Matlab/Simulink indicates that only the active power is injected into the grid. They also reveal that the HNF has a response time (Rt) of 0.097 s, a rise time (rt) of 4.30610-3s and a THD of 0.85% compared to the modified PID which has a response time of 0.659 s, a rise time of 0.156 s and a THD of 2.74%.