Indirect power control of DFIG based on wind turbine operating in MPPT using backstepping approach

This paper describes a MPPT control of the stator powers of a DFIG operating within a wind energy system using the backstepping control technique. The objective of this work consists of providing a robust control to the rotor-side converter allowing the stator active power to be regulated at the maximum power extracted from the wind turbine, as well as maintaining the stator reactive power at zero to maintain the power factor at unity, under various conditions. We have used the Matlab/Simulink platform to model the wind system based on a 7.5 kW DFIG and to implement the MPPT control algorithm in a first step, then we have implemented the field-oriented control and the backstepping controller in a second step. The simulation results obtained were very satisfactory with a fast transient response and neglected power ripples. They furthermore confirmed the high robustness of the approach used in dealing with the variation of the internal parameters of the machine

Adaptive Sliding Mode Control of Permanent Magnet Direct-Drive Wind Turbine

The damping coefficient of permanent magnet direct-drive (PMDD) wind turbine is unmeasurable. To solve the problem, this paper attempts to design a sliding mode control (SMC) strategy that adapts to the speed of PMDD wind turbine. Firstly, the authors analyzed the features of wind turbines, and the nonlinear dynamic structural features of permanent magnet synchronous machine (PMSM). Next, the parameter adaptive law was designed based on Lyapunov stability theory, and backstepping control was combined with SMC into a comprehensive control strategy that regulates the speed of wind turbines. Simulation results show that the proposed strategy can compensate for the disturbance of uncertain parameters, and ensure the frequency stability of the wind turbine

PSO-backstepping controller of a grid connected DFIG based wind turbine

The paper demonstrates the feasibility of an optimal backstepping controller for doubly fed induction generator based wind turbine (DFIG). The main purpose is the extract of maximum energy and the control of active and reactive power exchanged between the generator and electrical grid in presence of uncertainty. The maximum energy is obtained by applying an algorithm based on artificial bee colony approach. Particle swarm optimization is used to select optimal value of backstepping’s parameters. The simulation is carried out on 2.4 MW DFIG based wind turbine system. The optimized performance of the proposed control technique under uncertainty parameters is established by simulation results

Backstepping nonlinear control to maximize energy capture in a variable speed wind turbine

We are considering the problem of maximum power point tracking MPPT in wind energy conversion system (WECS). The paper proposes a new control strategy to maximize the wind aerodynamic energy captured in variable speed wind turbine with a separately excited DC-Generator and transformed to the battery through a controlled DC-DC converter. The proposed strategy controls the stip speed ratio via the rotor angular speed to an optimum point at wich the power coefficient is maximal. The controller is designed using the backstepping technique. A formal analysis based on lyapunov stability is developed to describe the control system performances. In addition to closed-loop global asymptotic stability, it is proved that the controller actually meets the MPPT requirement. The above results are confirmed by simulations.

A Lyapunov Based Approach to Enchance Wind Turbine Stability

This paper introduces a nonlinear control of a wind turbine based on a Double Feed Induction Generator. The Rotor Side converter is controlled by using field oriented control and Backstepping strategy to enhance the dynamic stability response. The Grid Side converter is controlled by a sliding mode. These methods aim to increase dynamic system stability for variable wind speed. Hence, The Doubly Fed Induction Generator (DFIG) is studied in order to illustrate its behavior in case of severe disturbance, and its dynamic response in grid connected mode for variable speed wind operation. The model is presented and simulated under Matlab/ Simulink

Robust bounded control for uncertain nonlinear systems: application to a nonlinear strict feedback wind turbine model with explicit wind speed dynamics.

In this paper, a robust bounded control law for a class of uncertain nonlinear systems is proposed. The proposed bounded controller guarantees asymptotic stability, asymptotic tracking and asymptotic disturbance rejection of systems in strict feedback form with the sum of unmatched uncertainties and the unbounded exogenous disturbance. A feedback law emerged from Artstein's Theorem and Sontag's universal formulas are known to be useful to limit the control signal. However, the formulas are not robust as in many cases, being applied to the systems without uncertainties and disturbances. The controller proposed in this paper takes advantages of a mixed backstepping and Lyapunov redesign, which employed to enrich the Sontag's universal formulas. Therefore, the appealing feature of the proposed controller is that it satisfies small control property in order to preserve performance robustness and stability robustness with less control effort. Another advantage of the proposed controller is the formulas become applicable to higher order systems (i.e. order > 0). This paper also discusses fuzzy logic tuning approach for the controller parameters such that the closed loop system matrix remain Hurtwitz. For practicality, the proposed technique is applied to a variable speed control of a new strict feedback wind turbine system with wind dynamics appeared explicitly in the system model. The proposed controller guarantees the asymptotic tracking of the turbine rotor speed; maintains the optimal tip speed ratio and produces maximum power coefficient. This yields maximum power output from the turbine

Wind Turbine Active Fault Tolerant Control Based on Backstepping Active Disturbance Rejection Control and a Neurofuzzy Detector

© 2023 The Author(s). Licensee MDPI, Basel, Switzerland. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Wind energy conversion systems have become an important part of renewable energy history due to their accessibility and cost-effectiveness. Offshore wind farms are seen as the future of wind energy, but they can be very expensive to maintain if faults occur. To achieve a reliable and consistent performance, modern wind turbines require advanced fault detection and diagnosis methods. The current research introduces a proposed active fault-tolerant control (AFTC) system that uses backstepping active disturbance rejection theory (BADRC) and an adaptive neurofuzzy system (ANFIS) detector in combination with principal component analysis (PCA) to compensate for system disturbances and maintain performance even when a generator actuator fault occurs. The simulation outcomes demonstrate that the suggested method successfully addresses the actuator generator torque failure problem by isolating the faulty actuator, providing a reliable and robust solution to prevent further damage. The neurofuzzy detector demonstrates outstanding performance in detecting false data in torque, achieving a precision of 90.20% for real data and 100%, for false data. With a recall of 100%, no false negatives were observed. The overall accuracy of 95.10% highlights the detector’s ability to reliably classify data as true or false. These findings underscore the robustness of the detector in detecting false data, ensuring the accuracy and reliability of the application presented. Overall, the study concludes that BADRC and ANFIS detection and isolation can improve the reliability of offshore wind farms and address the issue of actuator generator torque failure.Peer reviewe