Robust Output Feedback Control Design for Inertia Emulation by Wind Turbine Generators

Wind generation has gained widespread use as a renewable energy source. Most wind turbines and other renewables connected to the grid through converters result in a reduction in the natural inertial response to grid frequency changes. The doubly-fed induction generator (DFIG) can be controlled to compensate for this reduction and, in fact, provide faster response than traditional synchronous machines. This paper proposes to design observer based output feedback linear quadratic regulator (LQR) and H∞ control laws to realize the inertia emulation function and deliver fast frequency support. The aim is to track the reference speed by a diesel synchronous generator (DSG) in order to reach the desired inertia. The control signal is computed based on a reduced order model using the balanced truncation technique. A comparison with selective modal analysis (SMA) and balanced truncation model reduction techniques is presented. Comprehensive results show the effective emulation of synthetic inertia by implementing the control laws on a nonlinear three-phase diesel-wind system. The proposed technique is analyzed for different short circuit ratio (SCR) scenarios.

The paper helps to understand the performance of the grid with battery and doubly-fed induction generator (DFIG) wind turbines when operating in a weak grid scenario with a low short circuit ratio (SCR). The concept will analyze the performance of the grid with battery connected DFIG both in steady state and transient scenario. The grid can be represented as a Thevenin equivalent circuit and is rated at 12.5 kV. A battery system and a wind system are connected at the point of common coupling (PCC). The battery system being modeled in PSCAD software is rated at 1 MW/1 MWh and the wind system model is rated at 2 MW. The grid has been characterized and analyzed based on two categories: strong grid and weak grid. A grid is considered to be weak when the flow of active and reactive power in the network causes a significant amount of voltage fluctuation at the point of common coupling. A grid is considered to be strong when the grid is stable with allowable nominal deviations with voltage and frequency. The strength of the grid can be measured by taking the ratio of grid's short circuit power with grid nominal power.

This paper presents a framework for model order reduction based on Balanced Truncation (BT) method and Artificial Neural Networks (ANN). As social, architectural and technical models are witnessing rapid complexity increase, it has become essential to find solutions to obtain a lower complex version of models while still preserving the model integrity. The main idea of the proposed framework is to reduce uncertainty by cascading two different Model Order Reduction (MOR) approaches, the BT technique and the Jordan Recurrent Neural Network (JRNN). The reduced model obtained by the JRNN network is estimated using the Instrument Variable (IV) estimation approach. Finally, the BT reduced model and the estimated JRNN reduced model are cascaded to obtain the final reduced order version of the original plant. The cascading procedure takes the powerfulness of both techniques and present them in a single system capable to compensate for possible errors and uncertainties. Simulation results prove the efficiency of the proposed framework in terms of the deduction strength and the integrity level.

Many wind turbine generators (WTGs) are installed in remote, rural areas, where the power grids are usually weak, characterized by unbalanced voltage conditions. If the voltage unbalance is not taken into account in the control system, it will cause poor power quality and poor operating performance of the WTG systems. This paper proposes a novel control scheme to improve the operating performance of a wind turbine equipped with a doubly fed induction generator (DFIG) under unbalanced network voltage conditions. The rotor-side converter (RSC) and grid-side converter (GSC) of the DFIG are controlled in a positive (dq)+ reference frame as well as in a negative (dq)- reference frame. Control of the RSC and GSC in the (dq)+ reference frame is the same as the regular control under balanced network conditions. The supplementary control of the RSC in the (dq)- reference frame minimizes the electromagnetic torque pulsations of the DFIG caused by the unbalanced network voltage; the supplementary control of the GSC in the (dq)- reference frame contributes to balance the total output currents of the DFIG. The proposed control scheme is implemented in PSCAD/EMTDC on a 3.6 MW DFIG wind turbine connected to a power network with unbalanced voltage. Results show that it improves the operating performance of the DFIG wind turbine system.

This paper proposes an easy, new and practical technique for connecting a Doubly Fed Induction Generator (DFIG) based Wind Turbine Generator (WTG) to the distribution grid. In fact, a DFIG can be assimilated to a synchronous generator except for an AC supply in the rotor windings. Therefore, eventually, the DFIG can be coupled to the grid in a similar way to the synchronous machine through rotor windings supply control. Actually, this technique is found practical, as it does not require any type of control loops, but in contrast, the DFIG is ready for any type of control (Flux Oriented Control, Direct Torque Control…) once starting is completed with this technique. In addition to steps of this procedure, a state model of the system is given including two DFIG models (before and after connection). These models were simulated on a 300 kW wind generation system using Matlab/SIMULINK environment. According to the simulation results, a behaviour assessment of the generator before, during and after connection is given so to evince benefits and drawbacks of this procedure.

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)

Recently, a doubly fed induction generator (DFIG) wind turbine has been extensively paid attentions as a renewable energy source in the DC microgrid. However, the inevitable problems of DFIG wind turbine are low voltage ride through (LVRT) due to the occurrence of faults as well as the power fluctuation. To overcome both problems, a superconducting magnetic energy storage (SMES) unit which is able to provide fast control of active and reactive power, can be used. This paper applies a SMES unit to enhance LVRT performance and alleviate the power fluctuation of DFIG wind turbine in the DC microgrid. The SMES circuit is mainly composed of the DC chopper. The PI controllers of DC chopper are used to control the exchange energy between the superconducting coil and the system. Simulation study using MATLAB/SimPowerSystems ensures the SMES control effect on both enhancing LVRT performance and smoothing power fluctuation of DFIG wind turbine.

Balanced truncation (BT) model order reduction (MOR) is known for its superior accuracy and computable error bounds. Balanced stochastic truncation (BST) is a particular BT procedure that provides a general, structure-independent MOR framework to preserve both passivity and stability of original models. Its application toward large scale systems, however, has been limited by the complexity of solving large size continuous time algebraic Riccati equations (CAREs). This paper introduces a novel quadratic extension of the alternating direction implicit (ADI) iteration, called QADI, that efficiently solves a CARE. A Cholesky factor variant of QADI, called CFQADI, further exploits low rank matrices and and produces solution in factor form that greatly accelerates BST. Remarkable efficiency of the proposed BST/(CF)QADI integration is demonstrated with numerical examples.

High automotive hydrocarbon emission during cold start is a well recognized challenge with increasing importance in moving towards green vehicles. In this work the application of a linear model reduction technique on the design of a controller for a nonlinear system is discussed. A reduced order cold start model of an SI engine and aftertreatment system is realized using a balanced truncation technique. Sliding mode controllers, derived from a nonlinear physical model and the reduced order model, are designed to reduce tailpipe hydrocarbon emissions. The comparison results indicate the controller derived from the balanced truncated model performs better since it adjusts the control inputs such that it favors the certain desired trajectories which are more influential on the final control target.

We propose a new framework to design controllers for high-dimensional nonlinear systems. The control is designed through the iterative linear quadratic regulator (ILQR), an algorithm that computes control by iteratively applying the linear quadratic regulator on the local linearization of the system at each time step. Since ILQR is computationally expensive, we propose to first construct reduced-order models (ROMs) of the high-dimensional nonlinear system. We derive nonlinear ROMs via projection, where the basis is computed via balanced truncation (BT) and LQG balanced truncation (LQG-BT). Numerical experiments are performed on a semi-discretized nonlinear Burgers equation. We find that the ILQR algorithm produces good control on ROMs constructed either by BT or LQG-BT, with BT-ROM based controllers outperforming LQG-BT slightly for very low-dimensional systems.

풍력발전시스템은 기존의 발전시스템과 매우 다르다. 그러므로 전력계통에 풍력시스템을 연계하기 위해서는 동적특성에 대한 연구가 필요하다. 풍력발전기의 안정도해석은 전력계통의 운영에 있어서 중요 쟁점이다. 기존의 동기발전기만으로 구성된 전력계통의 위상각 안정도는 풍력발전기가 포함되면 그 결과가 달라진다. 즉, 풍력터빈에 연계된 발전기는 대부분 비동기인 유도발전기이기 때문이다. 위상각의 동기화 여부로 판별하는 위상각 안정도는 임계고장제거시간(CCT)을 계산하여 평가한다. 계통해석용 풍력터빈의 모델은 다양하여 그 해석에 어려움이 있으나 지금은 크게 4가지 타입으로 표준화가 되어있다. 본 논문에서는 PSS/E-32에서 제공하는 풍력터빈의 3번째 표준모델인 DFIG(Doubly-Fed induction Generator)모델을 이용하여 풍력단지가 연계된 전력계통의 CCT를 풍력단지의 위치와 용량을 고려하여 분석한다. Wind generation systems are very different in nature from conventional generation systems. Therefore it is necessary to research dynamic characteristics of wind generation systems connected to a power system. The stability analysis of wind turbine generator is an important issue in the operation of the power system. The result of angular stability of the power system that consists of only synchronous generators is different from that of the power system including wind turbine generators. This is due to the fact that generators connected to wind turbines are generally induction generators. The angular stability assessing synchronization of generators is determined by its corresponding critical clearing time(CCT). Wind turbine models for the analysis of power system are varied and difficult to use, but now these are standardized into four types. In this paper, the analysis of the CCT of the power system connected to wind farm considering the location and capacity is performed by using DFIG(Doubly-Fed induction Generator) wind turbine built-in type3 model in PSS/E-32.

Doubly fed induction generator (DFIG) based variable speed wind generator is vulnerable to any sort of grid fault, as the stator of the DFIG is directly connected to the grid. Likewise the symmetrical faults, the asymmetrical faults also may cause the DFIG face high mechanical stress which may lead to mechanical damage. Therefore, it is very important to investigate the fault ride through (FRT) capability of the DFIG system during the asymmetrical fault situations. In this work, in order to enhance the FRT capability of the DFIG based wind generation system, a DC resistive superconducting fault current limiter (SFCL) is proposed. The performance of the DC resistive SFCL is compared to that of the bridge type fault current limiter (BFCL). Simulations are accomplished by using the Matlab/Simulink software. Simulation results clearly indicate that the proposed DC resistive SFCL improves the FRT ability of the DFIG based variable speed wind generator system during any type of asymmetrical faults in the power network. Also, the performance of the proposed method is better than that of the BFCL.

The wind power plant is one of the fastest growing electrical power sources. The integration of wind turbine into the power grid originates various power quality problems. Low-voltage ride through (LVRT) capability improvement is impregnating exigency in recent power quality issue, which is acquainted with various renewable power generation resources like solar PV and wind power plant. Dynamic voltage restorer (DVR) is a custom power device (CPD), which is connected in series with the electrical system, and it is a contemporary and efficient CPD expended in the distribution system to curb the power quality problems. In this paper, LVRT capability of doubly fed induction generator (DFIG) wind turbine system connected to a power grid is enhanced by means of DVR. LVRT capability is improved by the introduction of neural network controller. This controller fulfils the various grid code requirements. Thus, the performance of the DVR becomes far superior by the robust control technique. The simulation results were compared with conventional PI controller and the proposed artificial neural network (ANN) controller. It is proved that the proposed system raises the reliability of grid-connected DFIG wind turbine system.

This paper presents some new findings in model order reduction of multi input-multi output (MIMO) systems of modern power grid with wind generation. A widely-used model reduction technique called Balanced Truncation (BT) is compared with a relatively new Interpolatory approach of Iterative Rational Krylov Algorithm (IRKA). It is demonstrated that both BT and IRKA can produce an acceptable accuracy during model reduction for power grids with synchronous generators. Whereas, when modern grid with wind generation is considered, BT fails to produce a stable reduced order model (ROM) while IRKA is still able to derive accurate stable ROM retaining the poorly-damped inter-area modes of the system.

In this study, an integral sliding mode control approach for controlling the power electronics converters of a doubly-fed induction generator (DFIG) wind turbine system is presented. The power electronics interface consists of back-to-back converters. The rotor side converter regulates the active and reactive powers at the DFIG stator through controlling the stator currents. The stator current dynamics, with respect to the rotor voltages, is developed from the conventional equations of the DFIG model. In this control configuration, the knowledge about the rotor currents is not required, which reduces the use of the current measurement sensors. The grid side converter ensures constant dc-link voltage while transferring the power from the DFIG rotor to the grid. The proposed control approach uses a composition of sliding mode and integral parts to improve the overall performance and robustness against parametric variations and uncertainties. A lab-scale DFIG wind turbine system is used to investigate the proposed control approach efficiency under various operating conditions. The experimental results show the effectiveness of the proposed control approach in achieving control objectives to operate the DFIG wind turbine system.