Doubly-fed Induction Generator Wind Farm Research Articles

Improving power swing detection in the presence of doubly-fed induction generator wind farms based on setting adaptation

Improving power swing detection in the presence of doubly-fed induction generator wind farms based on setting adaptation

Small signal stability and dynamic performance investigation on multi-machines power system including DFIG wind farm

<p>The boundless potential of wind power in augmenting global energy production is a promising prospect. The efficient design and cost-effectiveness of doubly fed induction generator (DFIG) wind systems make them an optimistic solution for incorporating wind power on a massive scale. However, integrating these systems into power grids poses several challenges, including power system stability. This study examines the small signal stability and dynamic performance of a modified Western System Coordinating Council (WSCC) 9-bus system including a DFIG wind farm using load flow analysis, and both electromechanical oscillations and eigenvalue analysis. Three case studies were conducted based on the DFIG location and power increment.The simulation is carried out with the aid of the power system analysis toolbox (PSAT) that operates within the MATLAB environment. The study’s findings suggest that the perturbation and location of the DFIG relative to the system’s load have a minimal influence on the overall system’s stability and efficiency. However, when considering damping ratio, power angle, and rotor speed deviations, generators 1 and 2 with the perturbed DFIG installed on bus 8 are the most sensitive units to instability. Hence, larger perturbations and different DFIG’s location influence on power systems necessitates further analysis.</p>

Enhancing transient stability and dynamic response of wind-penetrated power systems through PSS and STATCOM cooperation

The large-scale integration of doubly-fed induction generator (DFIG) based wind power plants poses stability challenges for power system operation. This study investigates the transient stability and dynamic performance of a modified 3-machine, 9-bus Western System Coordinating Council (WSCC) system. The investigation was conducted by connecting the DFIG wind farm to the sixth bus via a low-impedance transmission line and installing power system stabilizers (PSSs) on all automatic voltage regulators (AVRs). A three-phase fault simulation was carried out to test the system, with and without power system stabilizers and a static synchronous compensator (STATCOM) device. Time-domain simulations demonstrate improved transient response with PSS-STATCOM control. A 50% reduction in settling time and 70% decrease in power angle undershoots at the slack bus are achieved following disturbances, even at minimum wind penetration levels. Load flow analysis shows the coordinated controllers maintain voltages within 0.5% of nominal at 60% wind penetration, while voltages at load buses can deviate up to 15% without control. Eigenvalue analysis indicates the PSS-STATCOM boosts damping ratios of critical oscillatory modes from nearly 0% to over 30% under high wind injection. Together, the present findings provide significant evidence that PSS and STATCOM cooperation enhances dynamic voltage regulation, angle stability, and damping across operating ranges, thereby maintaining secure operation in systems with high renewable integration.

IOT based adjustment mechanism for direct reference model adaptive IMC to support voltage sag in DFIG wind farm

Sustainable energy sources are valuable energy sources.Renewable energy production boosts the economic status of a country. Wind energy is one of the most abundant renewable energy sources, and as a result, the technology to harvest energy from the wind is growing rapidly around the world. As load centers are far away from renewable energy sources, electricity must be transferred over long distances. The most common problems with power fluctuations are caused by long-range voltage sag riding (VSRT). DFIG (Doubly Fed Induction Generator) is very popular in wind energy conversion systems due to its variable speed, high energy collection, efficiency, excellent design and unique control of phase side converters and rotor side converters. Wind speed monitoring is done with the help of Internet of Things (IOT). This paper described the use of training networks in developing adjustment algorithms for direct reference model adaptive IMC for DFIG wind farms. Here, a novel training-based neural network MIT (NNMIT) adjustment mechanism using neural network method is developed and implemented in direct reference model adaptive IMC to improve the performance of the controller during voltage sag. Direct and quadrature axis rotor current controllers are developed and the resulting DFIG is balanced with the FuzzyMIT correction mechanism in the sag ride through the conditions in the wind farm. Improvements across the voltage sag are identified and presented using NNMIT. The proposed NNMIT attain 0.15% torque ripple and 1 ms response time better than the existing FuzzyMIT method. The proposed method preserves high accuracy ranges of 97.88% than the existing method. This approach gives better performance than other control design methods which assume that the flux in the stator is constant in amplitude.

Optimal Allocation of Energy Storage System in DFIG Wind Farms for Frequency Support Considering Wake Effect

Energy storage systems (ESSs) are being utilized to improve wind farms’ (WF) frequency support capability due to their high reliability, fast response and the dual role of energy users and suppliers. Nevertheless, the problem of how much capacity should each ESS possesses in order to better serve the WFs has never been investigated. With this perspective, this paper proposes an optimal ESS allocation (OEA) scheme for doubly fed induction generator (DFIG) based WFs to mitigate the impact of wake effect in frequency support. Firstly, the synchronous stability of wind turbines under frequency dips is analyzed with the concept of frequency support margin (FSM), and the detrimental impact of the wake effect is also investigated. Subsequently, the role of ESSs to improve wind turbines’ synchronous stability is demonstrated. To make the OEA scheme practical, the wind turbines in a WF are segmented into different clusters based on the received wind speed. Afterwards, the OEA problem is formulated, where the objective is to optimize the coherency of the wind turbine clusters’ FSM level. The simulation results show that ESS can provide secondary frequency support under major grid frequency drops, and the proposed OEA scheme can reduce the risk of loss of synchronous stability.

Impedance Modeling and Stability Analysis of DFIG Wind Farm With LCC-HVDC Transmission

In China, the high-penetrated doubly-fed induction generators (DFIG) wind turbine (WT) is undergoing the centralized collection and long-distance line-commutated converter (LCC) high voltage DC (HVDC) transmission. In such high-penetrated renewable generation and transmission system, the dynamics of power electronics become dominant over the conventional synchronous generator so that its modeling and stability analysis needs re-examining. However, the interaction among interconnected wind farm, and LCC-HVDC, and weak grid remains unclear but may easily incur the stability issue. This paper firstly builds the wind farm model by aggregating each WT and collection transmission with the consideration about the frequency coupling. The double Fourier transform is further used to derive the mapping function in frequency-domain relates the current and voltage harmonics between DC and AC sides of the 6-pulse LCC converter, based on which the analytical 6-pulse LCC-HVDC impedance from AC side can be theoretically developed. The developed analytical impedance of DFIG wind farm with LCC-HVDC transmission system is verified by the comparison with the frequency sweeping simulation results and the oscillation reproduction in MATLAB/Simulink. The major parameter influence on system impedance characteristics is finally analyzed and compared in detail.

Damping of Subsynchronous Resonance in Utility DFIG-Based Wind Farms Using Wide-Area Fuzzy Control Approach

This paper presents a novel fuzzy control scheme for damping the subsynchronous resonance (SSR) according to the wide-area measurement system (WAMS) in power systems including doubly fed induction generator (DFIG)-based wind farms connected to series capacitive compensated transmission networks. The SSR damping is attained by adding the fuzzy controller as a supplementary signal at the stator voltage loop of the grid-side converter (GSC) of DFIG wind farms. Additionally, time delays due to communication signals are important when using WAMSs. If the time delays are ignored, it causes system instability. In this paper, the time delays are modeled with a separate fuzzy input to the controller. The new fuzzy control approach is executed by using the angular velocity of synchronous generators (w) and its variation in the angular velocity (dw/dt). The effectiveness and success of the WAMS-based fuzzy controller is demonstrated by comparison with the particle swarm optimization (PSO) and imperialist competitive algorithm (ICA) optimization methods. The efficacy and validity of the planned auxiliary damping control are verified on a modified version of the IEEE second benchmark model including DFIG-based wind farms via time simulations using the MATLAB/Simulink toolbox.

Optimal Energy Harvesting of Large-Scale Wind Farm Using Marine Predators Algorithm

A new optimal control strategy for the grid side converter (GSC) and rotor side converter (RSC) of a doubly-fed induction generator (DFIG) is developed in this paper using the Marine Predators algorithm (MPA). To accomplish this study, a comprehensive comparison between the suggested MPA-based control strategy and a well matured Particle Swarm Optimizer (PSO) to enhance transient stability of large-scale wind systems has been presented. MPA is used to determine the optimal gains of proportional-integral (PI) controllers for GSC and RSC to ensure a maximum power point tracking (MPPT) of a large-scale wind farm. The proposed optimal control strategy is analyzed and verified via a benchmark 9-MW DFIG wind farm using MATLAB/SIMULINK simulation. The attained results of the suggested MPA-PI-based controllers are compared to the conventional PI-based MPPT controllers to validate the efficacy of the developed optimal control strategy. The superiority of the proposed MPA-PI and PSO-PI-based optimal controllers over the traditional PI regulators towards enhancing the DFIG system dynamic performance has been proved. The presented MPA-PI-based control scheme has been succeeded in extracting the maximum power of the DFIG wind farm with a reduced settling time of about 1.8% and overshooting range 97% lower than the conventional controller.

Optimization Control Strategy for Large Doubly-Fed Induction Generator Wind Farm Based on Grouped Wind Turbine

This paper proposes a grouped, reactive power optimization control strategy to maximize the active power output of a doubly-fed induction generator (DFIG) based on a large wind farm (WF). Optimization problems are formulated based on established grouped loss models and the reactive power limits of the wind turbines (WTs). The WTs in the WF are grouped to relieve computational burden. The particle swarm optimization (PSO) algorithm is applied to optimize the distribution of reactive power among groups, and a proportional control strategy is used to distribute the reactive power requirements in each group. Furthermore, the proposed control strategy optimizes the reactive power distribution between the stator and the grid side converter (GSC) in each WT. The proposed control strategy greatly reduces the number of variables for optimization, and increases the calculation speed of the algorithm. Thus, the control strategy can not only increase the active power output of the WF but also enable the WF to track the reactive power dispatching instruction of the power grid. A simulation of the DFIG WF is given to verify the effectiveness of the proposed control strategy at different wind speeds and reactive power references.

MPC Based Coordinated Active and Reactive Power Control Strategy of DFIG Wind Farm with Distributed ESSs

The ESS is considered as an effective tool for enhancing the flexibility and controllability of a wind farm, and the optimal control scheme of a wind farm with distributed ESSs is vital to the stable operation of wind power generation. In this paper, a coordinated active and reactive power control strategy based on model predictive control (MPC) is proposed for doubly fed induction generator (DFIG)-based wind farm (WF) with distributed energy storage systems (ESSs). The proposed control scheme coordinates the active and reactive power output among DFIG wind turbines (WTs), grid-side converters (GSCs), and distributed ESSs inside the WF, and the aim is to decrease fatigue loads of WTs, make the WT terminal voltage inside the extent practicable, and take the WF economic operation into consideration. Moreover, the best reactive power references of DFIG stator and GSC are produced independently based on their dynamics. At last, the control scheme generates optimal power references for all ESS to make the SOC of each ESS converge to their average state. With the distributed ESSs, the WF controller regulates the WTs inside WF more flexibly. A WF composed of 10 DFIG WTs was utilized to verify the control performance of the proposed coordinated active and reactive power control strategy.

Design of Capacitive Bridge Fault Current Limiter for Low-Voltage Ride-Through Capacity Enrichment of Doubly Fed Induction Generator-Based Wind Farm

The increase in penetration of wind farms operating with doubly fed induction generators (DFIG) results in stability issues such as voltage dips and high short circuit currents in the case of faults. To overcome these issues, and to achieve reliable and sustainable power from an uncertain wind source, fault current limiters (FCL) are incorporated. This work focuses on limiting the short circuit current level and fulfilling the reactive power compensation of a DFIG wind farm using a capacitive bridge fault current limiter (CBFCL). To deliver sustainable wind power to the grid, a fuzzy-based CBFCL is designed for generating optimal reactive power to suppress the instantaneous voltage drop during the fault and in the recovery state. The performance of the proposed fuzzy-based CBFCL is presented under a fault condition to account for real-time conditions. The results show that the proposed fuzzy-based CBFCL offers a more effective solution for overcoming the low voltage ride through (LVRT) problem than a traditional controller.

New type of bridge fault current limiter with reduced power losses for transient stability improvement of DFIG wind farm

The paper presents a new active diode bridge fault current limiter (FCL) topology, and compares it to the classic diode bridge, Series Dynamic Breaking Resistor (SDBR), and active diode bridge FCL circuits. The comparison is done using a benchmark system that includes a 9 MW wind turbine with a doubly fed induction generator (DFIG), two 50 MW synchronous generators, and three step-up transformers. The results show that all three FCLs improve transient stability by limiting the currents peak, terminal voltage drop, active and reactive powers, and torque transients.

Variable-Gain Super-Twisting Sliding Mode Damping Control of Series-Compensated DFIG-Based Wind Power System for SSCI Mitigation

Subsynchronous oscillation, caused by the interaction between the rotor side converter (RSC) control of the doubly fed induction generator (DFIG) and series-compensated transmission line, is an alleged subsynchronous control interaction (SSCI). SSCI can cause DFIGs to go offline and crowbar circuit breakdown, and then deteriorate power system stability. This paper proposes a novel adaptive super-twisting sliding mode SSCI mitigation method for series-compensated DFIG-based wind power systems. Rotor currents were constrained to track the reference values which are determined by maximum power point tracking (MPPT) and reactive power demand. Super-twisting control laws were designed to generate RSC control signals. True adaptive and non-overestimated control gains were conceived with the aid of barrier function, without need of upper bound of uncertainty derivatives. Stability proof of the studied closed-loop power system was demonstrated in detail with the help of the Lyapunov method. Time-domain simulation for 100 MW aggregated DFIG wind farm was executed on MATLAB/Simulink platform. Some comparative simulation results with conventional PI control, partial feedback linearization control, and first-order sliding mode were also obtained, which verify the validity, robustness, and superiority of the proposed control strategy.

ESS equipped DFIG wind farm with coordinated power control under grid fault conditions

A new structure for doubly fed induction generator (DFIG) wind farms with coordinated power control under grid fault conditions are proposed in this paper. The proposed structure uses one grid side converter (GSC) and one energy storage system (ESS) for the entire wind farm unlike conventional structures, which have one GSC for each of the DFIGs. A converter loss decrease and a reliability enhancement are some of the advantages of the proposed wind farm, under normal operating conditions. The proposed wind farm follows the new grid codes to remain connected to the grid. In addition, it supports the network voltage and frequency stability by generating reactive and active power during and after faults. The ESS is coordinated with the wind farm to generate smooth active power under normal operation. This improves the low voltage ride-through capability of the wind farm under-voltage fault conditions and enhances the frequency response of the wind farm under frequency faults. MATLAB/Simulink software was used to simulate the proposed wind farm structure. An experimental setup was also provided to test the operation of the proposed power circuit topology.

Equivalent Modeling of Dfig-Based Wind Farms for Sub-Synchronous Resonance Analysis

The order of the detailed model of doubly-fed induction generator (DFIG) wind farms are too high and the simulation is difficult. Most of the existing research has used a single-machine equivalent model and clustering aggregation model for equivalence and few papers have explored the principles and equivalent conditions of the single-machine equivalent model under sub-synchronous resonance (SSR). Due to this reason, this paper equates DFIG wind farms connected with series compensated transmission network to two separate units based on the principle of matrix similarity transformation and the mathematical model and physical model of each unit has been studied. Then, the DFIG wind farm equivalent model’s validity is analyzed in number difference and collecting line difference based on linearization analysis. Finally, the system model is built in EMTDC/PSCAD, the damping analysis method is used to test the equivalent model’s validity and further reveal the mechanism of the system’s unstable operation. The results show that: the equivalent model can effectively reduce the system dimension and accurately reflect the dominant oscillation characteristics of DFIG wind farm under SSR; when SSR occurs, the damping coefficient of DFIG wind farm is negative under the oscillation frequency.

Neural Network-Based Supplementary Frequency Controller for a DFIG Wind Farm

An artificial neural network (ANN)-based supplementary frequency controller is designed for a doubly fed induction generator (DFIG) wind farm in a local power system. Since the optimal controller gain that gives highest the frequency nadir or lowest peak frequency is a complicated nonlinear function of load disturbance and system variables, it is not easy to use analytical methods to derive the optimal gain. The optimal gain can be reached through an exhaustive search method. However, the exhaustive search method is not suitable for online applications, since it takes a long time to perform a great number of simulations. In this work, an ANN that uses load disturbance, wind penetration, and wind speed as the inputs and the desired controller gain as the output is proposed. Once trained by a proper set of training patterns, the ANN can be employed to yield the desired gain in a very efficient manner, even when the operating condition is not included in the training set. Therefore, the proposed ANN-based controller can be used for real-time frequency control. Results from MATLAB/SIMULINK simulations performed on a local power system in Taiwan reveal that the proposed ANN can yield a better frequency response than the fixed-gain controller.

Impedance Modeling of DFIG Wind Farms With Various Rotor Speeds and Frequency Coupling

The oscillation phenomenon frequently occurs in large-scale grid-connected doubly-fed induction generators (DFIG) wind farms and the impedance-based analysis has gradually become a widely used method to analyze the wind power oscillation issues. The rotor speed of each wind turbine (WT) is usually different as an important factor to determine the operating point and affect the output impedance. This brief develops a DFIG wind farm impedance model considering different rotor speeds. The impedance of each WT is firstly obtained according to various rotor speeds and all the WTs are aggregated considering the complex frequency coupling effects to describe the overall wind farm impedance. The comparison between the simplified aggregation method of wind farms and the proposed model is given to indicate that the proposed model can provide more accurate modeling and stability analysis results.

A Novel Hybrid Machine Learning Classifier Based Digital Differential Protection Scheme for Intertie Zone of Large-Scale Centralized DFIG based Wind Farms

The protection of intertie zone between wind farm and grid line is critical for stable and safe operation of both the grid line and wind farm in the event of fault within or outside the intertie zone. As a reliable source of renewable energy doubly fed induction generator (DFIG)-based wind farms have been increasingly integrated to the power grid over the last two decades. Nowadays with the enormous penetration of large-scale DFIG wind farms, the commonly used distance relays are no longer reliable due to their incapability of providing accurate impedance measurement during internal and external faults. Thus, it results in maloperation, false tripping, and/or delayed operation. Therefore, in this article a digital differential-based protective relay (DBPR) scheme is designed and developed to provide reliable protection for wind farm intertie zone. Additionally, a new Bayesian-based optimized support vector machine (SVM), as a supervised machine learning classifier approach, is developed to take into account both the dynamic behaviors of wind speed and the current measured by the current transformers. Thus, the proposed hybrid SVM-DBPR scheme can distinguish among the normal operation, internal and external faults correctly that helps to avoid any false tripping. In a laboratory environment the proposed DBPR is implemented in realtime using FPGA DE2-115 board equipped with Cyclone IV-E device (EP4CE115F29C7). It is found from both simulation and experimental results that the proposed hybrid SVM-DBPR is able to provide reliable, efficient, and robust protection for the intertie zone of wind farms with 97.5% accuracy rate.

Analysis, reduction and robust stabiliser design of sub‐synchronous resonance in an IEEE FBM augmented by DFIG‐based wind farm

This study modifies the IEEE first benchmark model (FBM) by connecting nearby doubly-fed induction generator (DFIG) wind farms to utilize the inbuilt convertor controller for damping the sub-synchronous resonance (SSR) oscillations. The overall model was evaluated to determine the induction generator effect (IGE) and torsional interaction (TI) of sub-synchronous resonance (SSR) at various compensation levels, wind speeds, and system parameter settings both with and without a DFIG wind farm. The results of this detailed analysis demonstrated that augmenting an IEEE FBM with a DFIG wind farm suppresses SSR-induced IGE in the power system. An optimal orientation was investigated from rotor-side converter (RSC) and grid-side converter (GSC) of DFIG wind farm using residue configuration to design a SSR supplementary damping controller (SSDC). To suppress the TI effect of SSR, the SSDC implements damping control using three different feedback signals: line current, line power, and voltage across a series capacitor. A robust signal for achieving smooth damping under various operating conditions was defined in terms of several key characteristics, namely, high average residue magnitude, average phase angle of residue and avoidance of destabilisation of other dominant modes. The proposed model was validated using eigenvalue analysis, participation factor calculation and time-domain simulation.

A Dynamic Weighted Aggregation Equivalent Modeling Approach for the DFIG Wind Farm Considering the Weibull Distribution for Fault Analysis

The developing process of the aggregated dynamic equivalent model (DEM) for doubly-fed induction generator (DFIG) wind farms could be less computational and more efficient compared with the multimachine DEM, but less accurate when wind speed differences exist inside the wind farm. In addition, the wind speed differences contribute to the different activation patterns of the crowbar systems of DFIGs. Therefore, a dynamic weighted aggregation modeling approach is proposed in this paper to improve the applicability of the aggregated DEM for DFIG wind farm. First, the Gaussian density distance clustering algorithm is applied to segment the wind speed power curve into different zones such that each segmented zone is corresponded to one equivalent aggregated machine. Then the dynamic weighted aggregation equivalent model could be developed based on the conventional aggregated DEM, where the weighting factors for each generator are calculated according to the Weibull distribution of wind speeds. Different scenarios are simulated in MATLAB/Simulink environment to analyze the applicability of the proposed dynamic weighting equivalent model. The simulation results show the effectiveness of the proposed method.