Intelligent hybrid technique for cascaded multilevel inverter based three phase grid-tie hybrid power system: a WPSNN technique

This dissertation introduces an intelligent hybrid technique for the design of modelling and controller of the three-phase hybrid network connection system based on CMI. The hybrid technique is the Recurrent Neural Network (RNN) assisted by Wolf Pack Search (WPS) and therefore it is known as WPSNN technique. Here, the three stage CMI control scheme is considered as two stages and these are analyzed with the help of the proposed intelligent controller. In first stage, the WPS is developed to demonstrating the PV total and wind voltages and the WPS algorithm of the second stage assisted to RNN is used to extracting the reference currents of network. In first stage, input of WPS algorithm is PV and wind reference voltages and the gain parameters is generated as the output for optimal tuning of PI controller. In the second phase, the RNN is trained with on line process; the output of RNN is given to the WPS algorithm. It provides the corresponding tuning parameters to achieve the network current. To regulate the dc link voltage and the extraction of network current is developed with established technique. CMI based on the established technique is synchronizes the firing work relationship and reduces the modulation load. By then, the established technique is evaluated in MATLAB/Simulink working stage and the execution is assessed to existing techniques.