Design and analysis of grid integrated wind energy conversion system- adaptive moth flame optimization with ANN technique [articol]

Abstract

In the paper, adaptive technique is proposed for improving performance of the grid integrated WECS. The adaptive technique is the combination of Moth Flame Optimization (MFO) Algorithm and Artificial Neural Network (ANN) technique. The proposed method is utilized to analyze the dc link voltage and the grid side performances. Here, a cascaded H-bridge Multilevel Inverter is proposed to analyze the grid side variations and control the dynamic performances of the system. For the optimal pulses of cascaded MLI, the proposed adaptive MFO-ANN technique is developed and voltage, power regulation is achieved. The need of optimal switching operation is to avoid the complexity of the error voltage category. In the controller part, MFO algorithm is utilized to optimize the gain parameters of PID controller after that, ANN is utilized with the optimized gain values. After that, the optimal control pulse is generated to enhance the performance of grid integrated power system. The proposed adaptive MFO with ANN technique is implemented in MATLAB/Simulink working platform and the output performance is analyzed. In order to evaluate the performance of proposed method, this is contrasted with the existing techniques such as MFO and Firefly Algorithm (FA)-ANN technique.