Comparative analysis of fuzzy and ANFIS based MPPT controller for wind power generation system

Abstract

<span lang="EN-US">In recent years, huge developments in wind energy production and meet consumer demand. Numerous researchers have focused on maximum energy generation techniques for the wind system. The main reason for this work is to compare the different smart controllers for the maximum power generation techniques in the wind system. In this article, we developed and modeled a 250-watt wind power system in a MATLAB environment and simulated it in different weather conditions. Based on the simulation results, two intelligent controllers, such as fuzzy and ANFIS, were proposed and compared to obtain the maximum energy generation techniques in the wind system. Finally, the optimal smart controller was chosen based on performance.</span>

Cascaded H-bridge multilevel inverter-based DSTATCOM with an artificial neural fuzzy inference systembased controller

“…The voltage source inverter base can be categorized as: i) a cascaded H-bridge MLI (CHB MLI), ii) a neutral point clamped MLI (NPC MLI), and iii) a flying capacitor MLI (FC MLI) [6], [7]. The CHB-MLI is most preferred due to the complexity posed by the neutral point clamped and flying capacitor multilevel inverter [8]- [10]. The advantages of the CHB MLI are that any number of voltage levels can be realized with the addition of small voltage sources [11]- [13].…”

Simulation and Analysis of Optimal Power Injection System Based on Intelligent Controller

“…In addition, hybrid MPPT techniques include traditional methods and can detect the maximum power point (MPP) even in cases such as partial shading [10]. Maximum power point tracking algorithms using traditional methods approach the MPP of the PV with a fixed or variable step [11]. Accurate measurement of the energy produced or various methods of estimation can also lead to efficient energy use [12].…”