Third-Order Sliding Mode Applied to the Direct Field-Oriented Control of the Asynchronous Generator for Variable-Speed Contra-Rotating Wind Turbine Generation Systems

Dynamic performance of rotor-side nonlinear control technique for doubly-fed multi-rotor wind energy based on improved super-twisting algorithms under variable wind speed

The paper proposes a nonlinear controller called dual super-twisting sliding mode command (DSTSMC) for controlling and regulating the rotor side converter (RSC) of multi-rotor wind power systems that use doubly-fed induction generators. It was proposed that this controller be developed as an alternative to the direct power control (DPC), which makes use of a pulse width modulation (PWM) strategy to regulate the RSC's functioning. Overcoming the power/current quality issue with the proposed technique (DPC-DSTSMC-PWM) is characterized by great robustness and excellent performance. The designed strategy was contrasted with the standard method of control and other methods already in use. So, the unique proposed control strategy's robustness, performance, efficiency, and efficacy in enhancing system characteristics were tested and validated in Matlab/Simulink. In both tests, the proposed method resulted in significant improvements, reducing active power ripples by 83.33%, 57.14%, and 48.57% in the proposed tests. When compared with the traditional regulation method, the reduction rates of reactive power ripples are 64.06%, 52.47%, and 68.7% in the tests. However, in contrast to the conventional method, the proposed tests showed a decrease of between 72.46%, 50%, and 76.22% in the value of total harmonic distortion (THD) of the provided currents. These ratios show how effective the proposed plan is in ameliorating and enhancing aspects of the energy system.

Application of fractional-order synergetic-proportional integral controller based on PSO algorithm to improve the output power of the wind turbine power system

It is noted that the traditional direct filed-oriented control (DFOC) is widely used in the field of electric power generation from wind due to its fast response dynamic, ease of implementation and simplicity, but this strategy is characterized by the presence of large ripples at the level of both active and reactive powers. This work presents a new algorithm for DFOC strategy of an asynchronous generator (AG) in a wind power (WP) system, which is based on the use of a new nonlinear controller called fractional-order synergetic control-fractional-order proportional-integral (FOSC-FOPI) controller, where the proposed technique parameters are calculated using the particle swarm optimization (PSO) strategy. It has been observed that the DFOC-FOSC-FOPI-PSO strategy is robust and works well in case of changing generator parameters. Three tests were performed to study the behavior of the designed technique under different working conditions, where the behavior of the DFOC-FOSC-FOPI-PSO strategy was compared with the behavior of the traditional DFOC technique in terms of power ripple ratio, overshoot, steady-state error, response time, tracking reference, and current quality. The simulation of the designed technique based on the FOSC-FOPI-PSO strategy of the AG-WP system is carried out using Matlab software, where the simulation results showed that the suggested technique is better than the classical technique (with PI controller) in terms of improving response time of active power (33.33%) and reactive power (10%) in second test, reduction of the steady-state error of reactive power (96.95%) and active power (97.14) in first test, minimization of harmonic distortion of current (96.57%) in third test and significant minimization of ripples of active power (99.67%, 44.69%, and 98.95%) and reactive power (99.25%, 53.65%, and 70.50%) in the three tests. The effectiveness of the DFOC-FOSC-FOPI-PSO strategy is very high, so it can be a reliable solution for controlling various generators.

Synergetic-PI controller based on genetic algorithm for DPC-PWM strategy of a multi-rotor wind power system

This work designs a powerful new nonlinear control technique using synergetic control (SC), proportional-integral (PI) controller, and genetic algorithm (GA) for multi-rotor wind energy (MRWE) conversion systems, whereby an asynchronous generator (AG) is used to achieve optimal energy extraction. The direct power control (DPC) technique is used based on the proposed SC-PI-GA (SPI-GA) technique to control the AG-based MRWE system, where this new nonlinear control technique is used to achieve stable control characteristics under random changes in wind speed and to provide great robustness against modeling uncertainties. Moreover, the pulse width modulation (PWM) technique is used to control the AG inverter due to its simplicity and ease of implementation. In this proposed DPC-SPI-GA technique, we need to measure current and voltage to estimate the active power and the reactive power. Also, inner loops are not used in this proposed DPC-SPI-GA technique as is the case in the field-oriented control (FOC) technique, where the proposed system in this work is characterized by an integrated structure. Three different tests are proposed to study and verify the behavior of the designed DPC-SPI-GA strategy compared to the traditional DPC technique.

Direct Power Control Based on Modified Sliding Mode Controller for a Variable-Speed Multi-Rotor Wind Turbine System Using PWM Strategy

A robust and improved control scheme of a variable speed multi-rotor wind turbine (MRWT) system with a doubly fed asynchronous generator (DFAG) is displayed in this work. In order to improve the performances and effectiveness of the traditional direct power control (DPC) strategy of the DFAG, a new kind of sliding mode controller (SMC) called modified SMC (MSMC) is proposed. The most important advantage of the DPC-MSMC strategy is to reduce the power ripples and improve the quality of the currents provided to the grid. In addition, to control the rotor inverter, a pulse width modulation (PWM) technique is used. The proposed DPC-MSMC strategy was modeled and simulated using MATLAB/Simulink software. The simulation results showed that the ripples in stator currents, active and reactive powers and torque were considerably reduced for the proposed DPC-MSMC strategy compared to the traditional DPC. Additionally, the proposed DPC-MSMC method works excellently to reduce the total harmonic distortion (THD) of the stator current in the case of variable wind speed. On the other hand, a robustness test against parametric variations showed and confirmed the robustness of the proposed technique compared to the classical method.

Application of Fractional-Order PI Controllers and Neuro-Fuzzy PWM Technique to Multi-Rotor Wind Turbine Systems

In recent years, the methods of controlling electrical machines have been witnessing increasing development to reduce torque and electric current fluctuations in electrical power generation systems from renewable sources such as wind energy. The generation of electric power from wind plants imposes the need for an efficient and more robust method in order to obtain fewer ripples in active and reactive power. In this work, a new fractional-order proportional-integral (FOPI) controller and intelligent PWM (IPWM) technique are proposed to control an existing asynchronous generator (AG) in variable-speed multi-rotor wind turbines (VSMRWTs). This proposed method depends on combining or using two methods, namely nonlinear area and fractional calculus, to obtain a more robust method and to reduce current and torque ripples. In the framework of this study, the electric power generation system consists of a 1.5 MW AG and VSMRWTs. The AG is controlled using a simpler and easily accomplished method called direct vector control, based on FOPI controllers and the IPWM technique (DVC-FOPI-IPWM). The maximum power point tracking (MPPT) method is used to generate the maximum energy from the VSMRWTs. The proposed DVC-FOPI-IPWM technique is modeled in the Matlab/Simulink platform to obtain good quality current and active power. Simulation results show that the proposed strategy reduces the ripples of torque, current, and active power compared to the classical technique. Moreover, the reduction ratio is about 85%, 99%, and 93.33% for the current, active power, and torque, respectively.

A Neural Controller for Induction Motors: Fractional-Order Stability Analysis and Online Learning Algorithm

In this study, an intelligent control scheme is developed for induction motors (IMs). The dynamics of IMs are unknown and are perturbed by the variation of rotor resistance and load changes. The control system has two stages. In the identification stage, the group method of data-handling (GMDH) neural network (NN) was designed for online modeling of the IM. In the control stage, the GMDH-NN was applied to compensate for the impacts of disturbances and uncertainties. The stability is shown by the Lyapunov approach. Simulations demonstrated the good accuracy of the suggested new control approach under disturbances and unknown dynamics.