DFIG-based damping controller design to damp low frequency oscillations in power plant industry

The adverse effects resulting from the intermittent nature of wind energy on power generation and stability is well documented in the literature. More specifically, the impact of power oscillations on doubly fed induction generator (DFIG)-based wind turbines can have drastic effects and even lead to large area blackouts, if not addressed properly. This paper deals with the design and implementation of a probabilistic coordinated approach for power systems with synchronous generators (SGs), DFIGs, and facts devices. The parameters of the power system stabilizers (PSSs) of the SG, power oscillation dampers (POD) of the DFIGs and STATCOM controllers were optimally coordinated using a modified Imperialist Competitive Algorithm (MICA) combined with a probabilistic eigenvalue approach. The proposed approach was implemented to a modified 39-bus New England power system. Its effectiveness in guaranteeing power system's dynamic stability was assessed using time domain analysis, eigenvalue mapping, and robustness analysis under various wind conditions. DFIG's realistic modes of operation, including normal, synchronous, and sub-synchronous modes were considered in the performance analysis. The obtained results were further compared to those of deterministic and uncoordinated approaches. A comparison of the MCA algorithm to other optimization approaches such as particle swarm optimization (PSO), genetic algorithm (GA), and imperialist competitive algorithm (ICA) is also carried out. The simulation results and robustness analysis confirmed the superiority of the proposed probabilistic approach over various other approaches.

In power system any unpredictable variations of consumption load will cause fluctuation in frequency and the transferred power between the lines. Load frequency control is one of the main problems in the power system which synchronizes with automatic generation control. Checking the different factors that cause unbalance in power system is necessary and one of the important factors of them is the load that randomly varies. In this paper, a three area power system in deregulated environments with participation of synchronized generation of wind with Doubly Fed Induction Generator (DFIG), hydro and thermal power plants are studied. The load in this power system is considered as a random variable which periodically and randomly has frequency of 0.25 around nominal amount. Fluctuations are caused due to considering load as a random variable and using wind-powered turbine with DFIG in power system. To improve the response of power system, the optimal fuzzy logic, PID controller and FACTS devices will be used. Imperialist Competitive Algorithm (ICA) has been used for optimizing the parameters of a fuzzy logic controller. PID Controller parameters have been optimized with three intelligent algorithms, ICA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) Algorithm and the results will be compared with each other. With comparison the result it is observed that in the case of using optimal fuzzy logic controller (OFLC) we have the fastest response with the minimum over shoot and under shoot, also in this case the transferred power between the areas is settled in the lowest value. The results show a significant reduction in losses in transmission lines.

With rapid proliferation of wind generation in current generation mix, the issue of low frequency oscillations (LFOs) may get escalated in the modern power grids. The eigenvalue and dynamic sensitivity analysis have been employed to examine the effect of wind integration on system damping. Further, a wide area based robust damping improvement control is suggested. It involves the coordinated control of power system stabilizers (PSSs) of synchronous generators (SGs) and power oscillation dampers (PODs) of doubly fed induction generators (DFIGs). The robust control is attained by employing a new fitness function based on eigenvalue and damping ratio and optimized by Whale Optimization Algorithm (WOA). The wide area POD inputs are selected using modal observability criterion, obtained using phasor measurement units (PMUs) located optimally in the system. The results are verified on IEEE benchmark 68 bus NY-NE (New York- New England) test system. The simulation results highlights the robustness of proposed control to changing system conditions and shows its effectiveness in augmenting system damping and thus small signal stability with high level of wind penetration.

The aim of this research work is to analyse sub-synchronous control interaction (SSCI) in doubly-fed induction generators (DFIGs) and to design a supplementary control technique for the mitigation of SSCI. A mathematical model of the DFIG is derived and linearized in order to perform an eigenvalue analysis. This analysis pinpoints the parameters of the system which are sensitive in making sub-synchronous modes unstable and hence are responsible for causing SSCI. A power oscillation damper (POD) is designed using a residue method to make the DFIG system immune to the SSCI. The POD control signal acts as a supplementary control, which is fed to the controller of the grid-side converter (GSC). The POD signal is applied to different summation junctions of the GSC controller in order to determine the best placement of the POD for effective mitigation of SSCI and for the increased damping of the system.

Optimal node selection of damping controller for power systems with high wind power penetration

This paper establishes a closed-loop interconnected dynamic model of a power system with a doubly fed induction generator (DFIG) for wind power generation, wherein, the DFIG and power system are modeled as two open-loop interconnected subsystems. The established model indicates that the impact of the dynamic interactions introduced by the DFIG on the power system's small-signal angular stability is the difference between the closed-loop and open-loop electromechanical oscillation modes (EOMs). The analysis conducted in this study reveals that when an open-loop DFIG oscillation mode (DOM) is close to an open-loop EOM on the complex plane, the modal coupling of the open-loop EOM and DOM can cause strong dynamic interactions between the DFIG and the power system; thus, the DFIG has a significant impact on the power system's small-signal angular stability. An example multimachine power system with grid-connected DFIGs is presented to demonstrate and validate the analysis and conclusions made in the paper.

Under the disruption of communication system, the wide area controller may fail to stabilize power oscillations. As a result, the power grids may be jeopardized due to the undamped oscillations. To improve the grid resiliency, a new design method of the two-level robust coordinated stabilizing control of power oscillation damper (POD) of wind turbine with doubly-fed induction generator (DFIG), and power system stabilizer (PSS) is presented in this paper. The two-level control of POD and PSS consists of centralized and local levels. As the main controllers, the centralized POD and PSS are applied to damp out power oscillations. When the communication failure occurs, the local POD and PSS act as the backup controllers to stabilize power oscillations instead of the centralized POD and PSS. The geometric measures of controllability and observability are adopted to determine the suitable input signals of POD and PSS. The structure of POD and PSS is represented by a practical 2nd-order lead/lag compensator. The control parameters of POD and PSS of each control level are separately optimized under various operating conditions so that the damping effect and robustness can be guaranteed. Simulation study is conducted to show the stabilizing effect of the proposed controller on the enhancement of grid resiliency against severe short circuits, line outages, various power flow levels, wind speeds, variable communication latency, and communication failure.

With the increasing penetration of doubly fed induction generators (DFIGs), the impact of the DFIG on transient stability attracts great attention. Transient stability is largely dominated by generator types in the power system, and the dynamic characteristics of DFIG wind turbines are different from that of the synchronous generators in the conventional power plants. The analysis of the transient stability on DFIG integrated power systems has become a very important issue. This paper reviews the current research on the issue from two aspects. One is to describe the methods to improve the fault ride through capability of DFIG wind turbines and the other is to analyse the impact of the DFIG wind farm on transient stability of power systems.

With large wind energy integration into power systems, wind farms begin to influence power systems in a much more significant manner. As wind energy systems utilize different generator technologies from the one utilized in the conventional power plants, the steady-state, transient and small-signal dynamics, as well as, power system stability will thus be significantly affected. The impact of wind energy systems on the power system dynamics and stability is thus of practical importance. As there is a significant increase in installation of wind turbines equipped with doubly-fed induction generator (DFIG) in recent years, a dynamic model of the DFIG wind turbine is firstly developed in this thesis. The model is validated against field measurement data, and the validation gives confidence about the accuracy and applicability of the developed model. DFIG wind farms consist of tens to hundreds of identical DFIG wind turbines increasing the complexity of the wind farm model and simulation time. A novel aggregation technique is developed in this thesis that incorporates a multiplication factor, namely mechanical torque compensation factor (MTCF), to the mechanical torque of the full aggregated wind farm model. The MTCF is initially constructed to approximate a Gaussian function by using fuzzy logic method. By optimizing the MTCF on a trial and error basis, less than 10 percent discrepancy is then achieved between the proposed aggregated model and the complete model. The proposed aggregation technique is then applied to a 120 MVA offshore wind farm comprising of 72 DFIG wind turbines and shows higher accuracy in approximating the wind farm dynamics as it appears at the point of common coupling (PCC) as compared to the full aggregated model. The proposed aggregated model computes faster than the complete wind farm model by 90.3 percent during normal operations and 87 percent during grid disturbances. To overcome the adverse effects due to the fluctuating nature of wind, two wind power smoothing methods are proposed using a fuzzy logic pitch angle controller for a smooth performance with a minimum drop in output power. One method performs partial smoothing with only 4.74 percent drop in the output power while the other method offers complete smoothing with a 8.28 percent drop in output power. The impact of wind energy integration on power system transient stability (PSTS) is studied quantitatively with the transient energy margin (TEM), which is calculated through the evaluation of the transient energy function (TEF). This study is carried out in two ways in the thesis. One is to analyse the impact of transient fault on the DFIG wind turbine as compared to SGs for different factors, like the fault clearing time, the grid coupling, the inertia constant and the voltage sag. The study reveals that transient stability of the DFIG wind turbine is hardly affected by the grid coupling, the inertia constant and the generator terminal voltage sag variations indicating its consistent transient performance within a wide range of these factors. The fault clearing time should be almost 11 percent faster for the system with the DFIG than the synchronous generator (SG). The other is to investigate the impact of the DFIG wind farm on the PSTS with the variation of different factors, which are the voltage sag, the fault clearing time, the load and the wind power penetration level. The study reveals that power systems integrated with DFIG wind farms are sensitive to transient events with high voltage sag, high fault clearing time, low load operation and high wind power penetration level. Machines at different locations individually possess distinct fault response and suffer from a large-scale power imbalance. As a result, reliable operation of DFIG wind farm integrated power systems demands upgraded equipment, such as advanced switchgear, fast breakers/isolators, efficient power reserve systems and advanced reactive power compensating device, etc.

This paper proposes an advanced control strategy for DFIG based Wind Turbine. The designed method is based on a combination of Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN). PSO combined ANN is suggested to track the available maximum power point (MPPT) at varying wind speeds. Thus, PSO is used to improve the dynamic performance of Doubly Fed Induction Generator (DFIG) by optimizing its Proportional Integral (PI) controller gains. This work highlights the performance of the PSO optimized PI controller against classical one. The proposed control strategy is verified via 2 MW DFIG-WT using the MATLAB/Simulink environment. The obtained results validate the proposed PSO-PI as an effective tool for improving the dynamic behavior of DFIGWT, it reveals that the overshoots are reduced by 50 % compared to the classical PI. In addition, a faster transient response is achieved using the proposed control strategy.

Background: With the large-scale Doubly Fed Induction Generator (DFIG) wind turbine integrated into the power system, the DFIG inertia response of the wind turbine should be provided. Also, the frequency response should be similar to the conventional generation technologies. This paper investigated the influence of frequency response term and wind speed conditions on system frequency control. Methods: The specific operating conditions of four control strategies, including inertia control, droop control, over speed control and pitch angle control were researched in this paper. Multi-factor coordinated frequency control strategy of DFIG wind turbine was established based on the above researches. The strategy was composed of wind speed ranging from low to high. Results: According to the simulation results, the DFIG wind turbine, which was based on multifactor coordinated frequency control strategy, could respond to the system’s frequency change of power grid, effectively. Conclusion: It helps system frequency return to stable states better and faster than DFIG wind turbine and also could reduce the fluctuation of system frequency.

The growth rate of penetration of wind energy has addressed many challenges and impacts related to the power quality and power system stability because of its intermittent nature. Once a doubly fed induction generator (DFIG) is connected to a power system, it absorbs lagging reactive power during the grid operation causing instability issues to the grid voltages. In this research paper, a DFIG based wind turbine is being modeled considering the optimal power coefficient and reactive power control strategy. The optimal power coefficient correlates the power law exponent with the respect of velocity and elevation. The reactive power control strategy is modeled using back-to-back converter system. The paper also investigates the voltage improvement of a large distribution network connected with DFIG system. By using steady state analysis, the voltage magnitude profiles are determined during DFIG at point of common coupling. The proposed control shows that DFIG based wind-turbine integration to the large distribution network enhances the weak bus voltage.

Many wind turbine generations have been installed into power systems around the world, where in recent years doubly fed induction generator (DFIG) attracts a lot of attentions because of its efficiency and controllability. However, the DFIG is connected to the power system through inverters and originally does not have an ability to release the kinetic energy of the rotor or resorb the surplus power of the power system as the kinetic energy. Therefore, it has not been made clear how the DFIGs have an influence on small-signal stability in power systems. In this paper, we propose a control scheme of the DFIG and analyse its effect on the small-signal stability of the power system by eigenvalue calculations and time-domain simulations.

Satisfactory performance of doubly fed induction generator (DFIG) is indebted to determining the proportional-integral (PI) gains of the power electronic converter controls as accurate as possible to guarantee minimum transients when disturbances occurred in the power system. Since the DFIG is introduced as a dynamical system, PI gains must be changed according to the system requirements. Fuzzy controllers designed based on our best knowledge on the system behavior are able to continuously adjust parameters of the control system to enhance the performance of the system. In this paper, a control scheme based on self-tuning fuzzy PI (STFPI) is proposed to control the power electronic converters of the DFIG. Different arrangements of the STFPI controller are considered in the control scheme of active and reactive power. The performances of the DFIG in three operating modes are compared when the STFPI and the conventional PI are installed and the system experiences a single phase to ground short circuit fault. Super-synchronous, synchronous, and sub-synchronous operating modes are examined in the paper. The idea is implemented on a study system equipped with a DFIG wind turbine, and the obtained results show that when the proposed scheme is employed a superior performance can be achieved in transient conditions and the transients are significantly improved. Copyright © 2014 John Wiley & Sons, Ltd.

In this paper, a control strategy for operation of rotor side converter (RSC) of Doubly Fed Induction Generators (DFIG) is developed by injecting reactive power into the grid in order to support the grid voltage during and after grid fault events. The novel nonlinear control method is based on differential geometry theory, and exact feedback linearization is applied for control system design of DFIG. Then the optimal control for the linearized system is obtained through introducing the linear quadratic regulator (LQR) design method. Simulation results on a single machine infinite bus power system show that the proposed nonlinear control method can inject reactive power to fault grid rapidly, reduce the oscillation of active power and improve the transient stability of power system.