Intelligent Controller Using Genetic Algorithm Applied on Wind Energy Conversion Systems: Design and Comparison Phases

This present paper suggests an intelligent nonlinear controller based on the powerful law which is the sliding mode (SM) combined with the fractional calculus (FC) and optimized using the genetic algorithm (GA). This improved controller is applied to the three-blade horizontal-axis variable-speed wind power (WP) to control its electromagnetic torque using the two-mass model of the mechanical part of this WP connected to the grid. The main purpose of this developed controller is to minimize the high peak of the electromagnetic torque and minimize the loads on the drive train thanks to mitigating the chattering phenomenon (noting that the chatter is the major disadvantage of the majority of the controllers existing in the literature due to the high-frequency oscillations that damage the system). The benefits earned from this advanced controller are the high tracking quality based on the maximum power point tracking (MPPT) algorithm, the enlarged lifespan of WP thanks to mitigating the chatter, reducing the peak value of the electromagnetic torque and ensuring stability. The emulation results are presented under MATLAB software using two wind speed profile scenarios to prove these cited benefits.