Comparative Analysis of Advanced Controllers for Standalone WECs for DC Microgrid Applications

2022 ◽  
pp. 38-82
Author(s):  
Bhavya Dharmesh Pandya ◽  
Siddharth Joshi

The small-scale wind energy generation system is one of the solutions to empower the isolated loads and provides a promising solution to decrease the greenhouse effect. This chapter describes the simulation analysis for wind energy conversion system incorporated with maximum power point tracking feature. The MPPT algorithms like variable current perturb and observe algorithm and variable step perturb and observe algorithm are incorporated with WECS. The comparative analysis is done in the closed-loop model in continuous time-varying wind speed. The closed-loop simulation is performed using a conventional fixed gain controller. To address the limitations of the fixed gain controller, the analysis is done using the gain scheduling proportional integral controller and the good gain method to tune the proportional integral controller. The comparative analysis between the fixed gain controller, the gain scheduling proportional integral controller, and the good gain method to tune proportional integral controller for above-stated MPPT methods is shown.

2020 ◽  
pp. 0309524X1989290 ◽  
Author(s):  
Marwa Hannachi ◽  
Omessaad Elbeji ◽  
Mouna Benhamed ◽  
Lassaad Sbita

This article presents the problem of the energy system optimization for wind generators. The goal of this work is to maximize power extraction for a permanent magnet synchronous generator–based wind turbine with maximum power point technique. This goal is achieved using a proportional–integral controller for optimal torque tuning with the particle swarm optimization algorithm. In order to indicate the effectiveness and superiority of the particle swarm optimization algorithm–based proposal, a comparison with the genetic algorithm and the artificial bee colony algorithm is studied. The system is modeled and tested under MATLAB/Simulink environment. Simulation results validate the advantages of the designed particle swarm optimization–tuned proportional–integral controller compared to P&O and the proportional–integral controller manually in terms of performance index.


Author(s):  
Hichem Othmani ◽  
D. Mezghani ◽  
A. Mami

In this article, we have set up a vector control law of induction machine where we tried different type of speed controllers. Our control strategy is of type Field Orientated Control (FOC). In this structure we designed a Fuzzy Gain-Scheduling Proportional–Integral (Pi) controller to obtain best result regarding the speed of induction machine. At the beginning we designed a Pi controller with fixed parameters. We came up to these parameters by identifying the transfer function of this controller to that of Broïda (second order transfer function). Then we designed a fuzzy logic (FL) controller. Based on simulation results, we highlight the performances of each controller. To improve the speed behaviour of the induction machine, we have designend a controller called “Fuzzy Gain-Scheduling Proportional–Integral controller” (FGS-PI controller) which inherited the pros of the aforementioned controllers. The simulation result of this controller will strengthen its performances.


Author(s):  
Viyils Sangregorio-Soto ◽  
Claudia L. Garzon-Castro ◽  
Gianfranco Mazzanti ◽  
Manuel Figueredo ◽  
John A. Cortes-Romero

Sign in / Sign up

Export Citation Format

Share Document