Adaptive vector oriented control of doubly fed induction generator wind turbines using M5P model tree for robust dynamic performance

Doubly Fed Induction Generators (DFIGs) are commonly integrated into variable-speed wind energy systems due to their enhanced controllability, high efficiency, and cost-effectiveness. This research introduces a neural network-based control approach to maximize wind energy capture and efficiently regulate DFIG speed by adapting in real time to varying wind conditions. The first stage introduces an intelligent MPPT controller leveraging neural networks to ensure optimal DFIG operation under fluctuating wind speeds. To control active and reactive power, the second part of the system employs Fuzzy Logic Control (FLC) and a PI-based Field-Oriented Control method. The effectiveness of both methods is evaluated through MATLAB/Simulink simulations on a 1.5 MW grid-connected DFIG. As a result, the proposed FLC achieves optimal aerodynamic efficiency and precise speed regulation via ANN-based MPPT, while offering faster response, reduced power overshoot, improved stability, and diminished oscillations compared to FOC-PI. Moreover, the FLC notably decreases stator current THD from 0.91% to 0.38%, surpassing IEEE-519 requirements and highlighting its superior ability to suppress harmonics.

In this paper, control of inter-area oscillation in power systems with high wind power penetration is achieved via doubly fed induction generator (DFIG). The DFIG is modeled in Matlab <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">reg</sup> /Simulink. A two-area system is investigated with a wind farm connected in the area that exports power. Control schemes for active power and reactive power regulation are designed firstly. The paper finds that without active power and reactive power regulation, it is impossible to design an effective inter-area oscillation damping controller through DFIG machine side inverter. An auxiliary control loop for oscillation damping that adjusts the active power command can help damp the inter-area oscillation. Time domain simulations demonstrate the effectiveness of the control.

Doubly fed induction generator (DFIG) is now becoming one of most widely used wind turbines in global market for wind power generation, due to its outstanding advantages. However, the DFIG is sensitive to grid faults. The DFIG will have to be removed from the grid if there’s no protection appliance in it. Therefore, the crowbar protection is widely used in the world for improving the low voltage ride-through ability of wind turbines. This paper analysed the operating characteristics and short-circuit current of DFIG under symmetrical short-circuit fault with respect to different sags to grid voltage, which on the basis of DFIG wind turbine with crowbar protection. And the expressions of short-circuit current under symmetrical short-circuit fault for DFIG were derived. The effectiveness of the expression was simulated in PSCAD/EMTDC.

Many large wind farms have employed doubly fed induction generator (DFIG) variable speed wind turbines. These require accurate models of doubly fed induction generator wind turbines and their associated control and protection circuits. The goal of this paper is to study the theory and control for the doubly-fed induction generator (DFIG) based wind turbine, and further establish its model by using mathematical formulas. The work utilized the power system analysis software PSCAD / EMTDC, which can quickly and accurately show the simulation results.

Introduction. Nowadays, the most widely used wind energy conversion system in wind farms is based on a doubly fed induction generator (DFIG); it has a large speed range and can function in multiple modes. Problem. Harmonic distortion in wind energy conversion system can degrade output waveform quality, reduce power conversion efficiency. Goal. This study investigates the dynamic performance of a wind energy conversion system comprising a grid-connected load, a 13-level hybrid multilevel converter and a doubly fed induction generator (DFIG), using a PI controller. The study aims to evaluate the dynamic performance and power quality of wind energy conversion systems, and to develop a novel hybrid metaheuristic method combining differential evolution (DE) and grey wolf optimization (GWO)-based selective harmonic elimination pulse-width modulation (SHEPWM) control strategies. This method reduces total harmonic distortion (THD) and ensures compliance with IEEE 519 standards, while increasing the power transferred to the grid. Methodology. The system, which includes a grid-connected load, a 13-level converter, and a DFIG, is modeled and simulated in MATLAB/Simulink under steady-state wind conditions. Vector control via stator flow orientation was used to modify the energy quality provided by the DFIG, making the system comparable to the DC machine. Our approach was to use a PI controller in order to directly control the active and reactive DFIG power through multi-level converter then a hybrid metaheuristic algorithm combining DE and GWO is implemented to solve the SHEPWM nonlinear transcendental equations. The proposed algorithm is evaluated based on its ability to suppress lower-order harmonics and improve THD performance, these converters increase the power transmitted to the power grid by reducing harmonic content of the output voltages. Results. By using the DE-GWO hybrid method and a PI controller, lower-order harmonics were effectively removed and THD was reduced to meet IEEE 519 standards. Simulations showed an improvement in output wave quality and better energy conversion efficiency compared to conventional optimization methods. Scientific novelty of the proposed work lies in the fact that the study introduces a novel DE-GWO hybrid optimization method for PWM (SHEPWM) in 13-level hybrid multilevel converter applied to wind energy systems. Practical value. The novel method demonstrates that constant high performance in wind energy systems may be achieved by combining intelligent optimization algorithms with complex multilevel converter designs This means it can be effectively integrated into contemporary wind farms where meeting grid standards, adjusting to varying sizes, and ensuring long-term reliability are crucial. References 26, table 1, figures 19.

It is now recognized that many large wind farms will employ doubly fed induction generator (DFIG) variable speed wind turbines. A number of such wind farms are already in operation and more are planned or under construction. With the rising penetration of wind power into electricity networks, increasingly comprehensive studies are required to identify the interaction between the wind farm(s) and the power system. These require accurate models of doubly fed induction generator wind turbines and their associated control and protection circuits. A dynamic model has been derived, which can be used to simulate the DFIG wind turbine using a single-cage and double-cage representation of the generator rotor, as well as a representation of its control and protection circuits. The model is suitable for use in transient stability programs that can be used to investigate large power systems. The behavior of a wind farm and the network under various system disturbances was studied using this dynamic model. The influence of the DFIG control on the stability of the wind farm was also investigated by considering different control gains and by applying network voltage control through both stator side and rotor side converters.

Doubly fed induction generator (DFIG) wind turbines are widely utilized as a promising form of electricity generation. Now the great attention is paid to the dispatch, protection and control of power systems integrated with large capacity wind power. In this paper, the mathematical model of DFIG wind turbines is built in PSCAD software. Simulation and analysis of three type of asymmetry fault are made. Then the fault characteristics of different control method are discussed in order to clarify the effect of particular control strategy. (6 pages)

This paper describes a Fault Tolerant Control (FTC) of a doubly-fed induction generator (DFIG) based wind turbine model suitable for the simulation of this generator in the mode faulty mode. The dynamic model of a DFIG with stator inter-turn short circuit fault is proposed. A model (abc) is developed, which can represent both the healthy and faulty conditions. The DFIG is directly connected to the grid whereas the rotor winding is fed by back-to-back PWM converters .the Control schemes for active and reactive power regulation are designed firstly. Under different wind speed, maximum power point tracing (MPPT) control is implemented to ensure the optimum active power output. The numerical simulation developed in Matlab/Simulink studies the effects of stator inter-turn short-circuit in the DFIG. Afterward, the application of Approach technique of Adaptive Obs

This article discusses the applications of Artificial Neural Network (ANN) and Fuzzy Logic Control (FLC) strategies in a control context of a grid connected Wind Energy Conversion System (WECS), using a Doubly-Fed Induction Generator (DFIG). To rigorously explore the performance of the controllers, a systemic approach based on an ideal model and a nominal model of the wind turbine is used for the comparative analysis between PI, FLC and ANN. It turns out that the PI is less efficient than ANN and FLC. It turns out that the PI is less efficient than ANN and FLC. Whereas, for a high level of control, the FLC has better performance than the ANN. For a low level, the performance of the ANN is very slightly superior to the FLC. In addition, one notes a good rejection of disturbance and a good robustness with the FLC compared to the ANN. The latter has a Total Harmonic Distortion (THD) and cos ϕ ≈ 1 slightly better than the FLC. In short, the ANN and FLC present great advantages for the WECS and the results obtained are satisfactory. The platform used for modeling and simulation studies is MATLAB/Simulink.KeywordsWind Energy Conversion SystemFuzzy Logic Control (FLC)Artificial Neural Network (ANN)DFIGPower grid

This paper presents the modeling of the wind power system and low voltage ride through (LVRT) techniques for doubly-fed induction generator (DFIG) wind energy system. Firstly the equivalent circuit and power transfer principle of DFIG are reviewed. A simulation model of DFIG system has been constructed in PSCAD, where the gird-side double closed loop vector control strategy is used to maintain a constant DC bus voltage and compensate for reactive power at power grid, while the stator-flux-oriented vector control is adopted in rotorside converter to achieve maximum power point tracking (MPPT) for the DFIG wind turbine. LVRT techniques of DFIG are investigated and crowbar protection circuits were researched for this DFIG wind energy system.

An assessment on the capability of a doubly fed induction generator (DFIG) wind turbine for frequency regulation is presented. Detailed aerodynamic, structural and electrical dynamic models were used in this study. A control loop acting on the frequency deviation was added to the inertia contributing loop in order to enhance the inertia support from the DFIG wind turbine. The possibility of de-loading a wind turbine to provide primary and secondary frequency response was discussed. A frequency droop controller was examined where the droop is operating on the electronic torque set point below its maximum speed and is operating on the pitch demand at maximum speed. It is also shown that by reducing the generator torque set point the DFIG wind turbine can provide high frequency response.

A neural network controller is presented for the direct power control of a doubly fed induction generator (DFIG) in a wind turbine. Due to the variability of wind speed, aerodynamic control of the pitch angle of the turbine blades is necessary to capture maximum power from the wind. An alternative control strategy for tracking the maximum power that can be extracted is by accurate control of the turbine rotational speed. However, due to the nonlinearities inherent in a wind energy conversion system (WECS) and wind speed unpredictability, exact control of this speed becomes challenging. This is addressed by the use of an adaptive learning rate to guarantee convergence. Hence, the controller is robust to uncertainties in wind speed. The superior performance of the proposed control technique, under varying nominal wind speeds, is established by simulation results.

This paper investigates the effect of Series Dynamic Breaking Resistor (SDBR) sizing on a Doubly Fed Induction Generator (DFIG) based wind power conversion system. The boundary of the SDBR value is firstly derived by taking into account the controllability of the rotor side converter and the maximum allowable voltage of the stator. Then the impact of the SDBR value on the rotor current, stator voltage, DC-link voltage, reactive power capability and introduced power loss during voltage sag operation is evaluated by simulation. The presented study enables a trade-off sizing of the SDBR among the above performance factors.

In wind turbine systems, pitch angle controllers are employed to reduce the aerodynamic power gained during high wind speeds. On the other hand, passive filters are usually used to mitigate disturbances in grid connected Voltage Source Converters (VSCs). In order to avoid the risk of instability in the grid connected VSC, as a result of resonance in the capacitive and inductive components, it is necessary to consider damping. In this chapter, the low pass filter timing constant of the pitch angle controller of Doubly Fed Induction Generator (DFIG) wind turbine was varied considering different time constants. The best timing response of the low pass filter was further used to analyse different filter topologies, in addition to a new control strategy that uses two-trap passive filter with shunt RC as active damper, in augmenting the Doubly Fed Induction Generator wind turbine during grid fault. Simulation studies in PSCAD/EMTDC were carried out to compare the performance of the proposed scheme with some other conventional filter solutions for the DFIG wind generator, during a severe bolted three-phase to ground fault. The simulation results demonstrate the improved performance and faster recovery of the wind generator variables after the fault considering the proposed filter scheme.

The modern grid requirement has caused that the wind power system behaves more like conventional rotating generators, and it is able to support certain amount of the reactive power. For a typical doubly fed induction generator (DFIG) wind turbine system, the reactive power can be supported either through the rotor-side converter or the grid-side converter. This paper first compares the current ripples and supportive reactive power ranges between the conventional L and optimized LCL filter, if the reactive power is injected from the grid-side converter. Then, the loss distribution is evaluated both for the generator and the wind power converter in terms of the reactive power done by the rotor-side converter or the grid-side converter with various grid filters. Afterward, the annual energy loss is also estimated based on yearly wind profile. Finally, experimental results of the loss distribution are performed in a down-scaled DFIG system. It is concluded that overexcited reactive power injected from the grid-side converter has lower energy loss per year compared to the overexcited reactive power covered by the rotor-side converter. Furthermore, it is also found that the annual energy loss could even become lower with the optimized filter and thereby more energy production for the wind turbine.