Perturbation estimation based robust state feedback control for grid connected DFIG wind energy conversion system

Doubly-fed induction generator (DFIG) wind turbines connected to capacitive series-compensated transmission lines are prone to exhibit oscillatory behavior. The phenomena is called sub-synchronous resonances (SSRs), as these oscillations occur at frequencies below the fundamental component. This paper first develops a modeling methodology for DFIG wind turbines, based on impedance matrices, that is applied to model a real wind farm where SSRs were reported. The stability analysis performed shows how the interaction between the grid-side converter and the rotor-side converter contribute to the instability of DFIG wind energy conversion systems connected to series compensated grids. With this model, we propose a simple sub-synchronous resonance control strategy based on an orthogonal proportional action applied to the rotor currents, and a variable gain in the PI controller adjusted as a function of the DFIG rotational speed. This control strategy depends only on the rotor currents, which are local and already measured variables in any DFIG wind turbine, and is implemented in the rotor side converter, so it does not imply an additional cost at wind farm or wind turbine level and can be applied to any DFIG wind energy conversion system (WECS). Additionally, it proves to be robust for any line impedance series compensation level, and it does not need real-time information concerning the grid at which the wind turbine is connected, or its parameters. A real case study is considered, where the sub-synchronous resonance damping strategy presented in this work is able to stabilize the system for every possible line impedance compensation level.

Wind power as a renewable energy has the potential to become a clean energy source in almost all countries of the world but, there are lots of technical challenges that need to be addressed in advance. Wind speed variation (WSV) is one of the most important issues. Separate from its mechanical effects on wind turbines (WTs), it causes electrical power variations on WT as well. Doubly Fed Induction Generators (DFIGs) and Maximum Power Point Tracking (MPPT) system have been helpful so far but some problems such as inertia still needed to be solved. Inertia in the WTs causes a delay on MPPT. This paper proposes a novel method to increase WTs output power in which a DFIG equipped with an energy storage system such as Ultra-capacitor helps MPPT system to track the wind variations rapidly by absorption or injection energy during the wind changes. The ultra-capacitor and control system are modeled and simulated in Matlab/Simulink® environment. The simulation results proofs that the proposed system can improve electrical power and increase electrical energy during WSVs. The simulation model will lead to more penetration of wind power and also enables engineers to optimize the system.

In this paper, a modified control technique for doubly fed induction generator (DFIG) is presented to improve its power quality by controlling (minimizing) grid current harmonics. The problems of harmonics injection in grid current, especially due to the presence of nonlinear loads, are very crucial. The proposed control technique can transfer the power from grid to DFIG and vice versa and can also control the DC link voltage (Vdc ) against wide variations in wind speeds. The maximum power point tracking (MPPT) is used in rotor side converter (RSC) to control the power flow through the DFIG. The MPPT extracts the maximum electromagnetic torque Tem from wind energy even during wide variations in wind speeds. A comparison of hysteresis current control (HCC) and space vector pulse width modulation (SVPWM) techniques for harmonic mitigation is presented considering all wind speeds. Also, the control technique for RSC and GSC is discussed in detail in this paper. Finally, the performance of the modified control technique to improve DFIG power quality is checked with the help of MATLAB/SIMULINK software considering 2.6 MW DFIG connected to a power grid.

A robust non-linear feedback control strategy combined with neural network (NN) estimator is presented, for the non-linear model of bank-to-turn (BTT) missile with modeling uncertainties. The non-linearities in the missile dynamics are taken into account, including coupling items between three channels. Standard feedback linearisation is implemented to linearise and decouple the nominal system. In the presence of unknown bounded uncertainties, the performance will deteriorate because the precise model cannot be obtained. Then, linear matrix inequality (LMI) based guaranteed cost control (GCC) is adopted to solve the robust control problem for the linearised uncertain models. Further, adaptive neural network estimators, which use Lyapunov based tuning rules, are integrated in the control strategy to eliminate the effect of high-order uncertain terms. Simulation results on a specified BTT missile model are provided to demonstrate the feasibility and effectiveness of the proposed approach, which achieves more improved tracking performance comparing with conventional method.

In this paper we design a cooperative control scheme for a wind Double-Fed Induction Generator (DFIG) with an integrated energy storage. The proposed control scheme can enable the wind generator to provide new advanced capabilities and support to the grid. More specifically, we design a controller for the rotor side converter (RSC) that guarantees maximum power point tracking (MPPT) while the controller for the grid side converter (GSC) guarantees transient stabilization of a neighboring synchronous generator (SG). Simulations on a small test system verify that the proposed control scheme achieves the desired objectives with good dynamic performance.

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.

Renewable energy production plays a major role in satisfying electricity demand. Wind power conversion is one of the most popular renewable energy sources compared to other sources. Wind energy conversion has two major types of generators such as the Permanent Magnet Synchronous Generator (PMSG) and the Doubly Fed Induction Generator (DFIG). The maximum power tracking algorithm is a crucial controller, a wind energy conversion system for generating maximum power in different wind speed conditions. In this article, the DFIG wind energy conversion system was developed in Matrix Laboratory (MATLAB) and designed a machine learning (ML) algorithm for the rotor and grid side converter. The ML algorithm has been developed and trained in a MATLAB environment. There are two types of learning algorithms such as supervised and unsupervised learning. In this research supervised learning is used to power the neural networks and analysis is made for various hidden layers and activation functions. Simulation results are assessed to demonstrate the efficiency of the proposed system.

This paper deals with the design of robust state feedback controller based on fuzzy logic and its evaluation in adjusting the speed of an induction machine. The basic idea of the proposed controller is similar to the gain scheduling approach. The design is based on a reduced order state space model of the motor drive from which a family of local state space models covering the operating range of the drive system are defined. We then use the state feedback design concept to get a linear state feedback controller for each local model using pole placement topology. The performance of the fuzzy state feedback controller is evaluated under different operating regimes of the drive system.

This paper presents the design and control of wind diesel hybrid system feeding 3-phase 4-wire distribution network. The grid is energized by conventional diesel generators. Wind energy block consists of a wind turbine coupled to DFIG (Double Fed Induction Generator) equipped with MPPT (Maximum Power Point Tracking). The MPPT demands regulation of the turbine speed which is realized with the help of rotor side converter. The DFIG control consists of two voltage source converters connected back to back at DC bus with a battery bank. The control system is designed such that the loading of diesel generator(s) remains in optimum loading condition keeping currents of wind generator as well as diesel generators balanced. Any surplus or deficient energy is circulated through a battery bank connected to the DC side of both converters. The complete system is modeled using Simpowersystem tool box of MATLAB 7.10 and its results are presented for conditions such as synchronisation of wind generator, load variation, nonlinear load and unbalanced load, varying wind speed etc. Under all the above conditions, the currents flowing through DFIG and diesel generators are balanced.

A vector decomposition approach to F–M model realization and its application to robust observed-state feedback control

This paper presents the design and implementation of optimal and robust state feedback controller for rotary inverted pendulum system. The Particle Swarm Optimization (PSO) method is used to find the optimal values of the state feedback gains subject to time response specifications and H_∞ constraints. To improve the tracking of the system, a robust state feedback plus integral controller is designed. The simulation results show that the proposed controller can effectively stabilize the pendulum at the upright position. Further, the proposed controller can compensate the variations in system parameters. The effectiveness of the proposed controller is verified experimentally using real rotary inverted pendulum.

This paper presents the development of a phase advance network to enhance the performance of a variable-speed doubly-fed induction generator (DFIG) driven by a wind turbine under various operating conditions at Zafarana wind farm, Egypt. Firstly a fairly detailed simulation of a real DFIG-based wind energy conversion system is built using Matlab/SimPower environment. The simulation output is verified by comparing the simulation output with similar practical results and also with that published by Gamesa G5x standard test results. A phase advance network is designed and implemented to enhance the DFIG-based Gamesa G5x wind energy conversion unit. The FRT characteristics is examined when the system is subjected to a three phase short circuit test and the results obtained using the various enhancement techniques have presented in a comparative form with similar results using the implementation of the phase advance network. The results illustrate significant improvement in overall system performance and superior operation of the wind conversion unit using the phase network.

This paper deals with the modeling, analysis, control and simulation of a doubly-fed induction generator (DFIG) driven by a wind turbine. This grid connected wind energy conversion system (WECS) is composed of DFIG and two back-to-back PWM voltage-source converters in the rotor circuit. A mathematical model of the machine, derived in an appropriate dq reference frame is established. The grid voltage oriented vector control is used for the grid side converter (GSC) in order to maintain a constant DC bus voltage and to compensate for reactive power at the power network. The stator voltage orientated vector control is adopted in the rotor side converter (RSC) control strategy, providing efficient handling of active and reactive power at the stator, as well as a maximum power point tracking (MPPT) method for the DFIG-based wind turbine. The proposed system is simulated for different operating conditions to illustrate the reliability of the control technique. Corresponding system simulation results under nonlinear load variations and wind speed transients are presented to demonstrate the significance of MPPT in WECS, and the effectiveness of adopted control technique.

This paper concerns the problems of robust stability analysis and stabilization for uncertain linear system with time-varying delay. In order to obtain a robust stability criterion with less conservative for uncertain linear delay system, a quadratic integral inequality is improved by matrix decomposition. Further, two different kinds of controller, i.e., linear memoryless state feedback controller and linear state feedback controller with state delay, are derived in terms of the robust stability criteria. Two numeral examples are provided to demonstrate the validity of the proposed methods.

A hybrid modulation strategy (HMS) for a two-stage matrix converter (TSMC) is presented in this paper. According to the variation of voltage transfer ratio, different combinations of modulation modes for rectifier-side converter (RSC) and inverter-side converter (ISC) of TSMC are adopted. Two different current space vector modulation methods are used for RSC to obtain maximum and minor DC voltages. The power loss of TSMC is reduced based on the minor DC voltage. In addition to the linear space vector modulation for ISC, an overmodulation method is presented in order to increase the voltage transfer ratio of TSMC. HMS ensures smooth switching between different modulation modes and makes the best use of the advantage of these modes. Finally, HMS is applied in the case where TSMC is used as an AC-excitation converter for doubly fed induction generator (DFIG) to achieve maximum power point tracking (MPPT). The simulation results confirm the accuracy and feasibility of HMS and the good performance of the MPPT operation of DFIG excited by TSMC.