Doubly Fed Induction Generator Wind Research Articles

Smoothing Intermittent Output Power in Grid-Connected Doubly Fed Induction Generator Wind Turbines with Li-Ion Batteries

Wind energy is an increasingly important renewable resource in today’s global energy landscape. However, it faces challenges due to the unpredictable nature of wind speeds, resulting in intermittent power generation. This intermittency can disrupt power grid stability when integrating doubly fed induction generators (DFIGs). To address this challenge, we propose integrating a Li-ion battery energy storage system (BESS) with the direct current (DC) link of grid-connected DFIGs to mitigate power fluctuations caused by variable wind speed conditions. Our approach entails meticulous battery modeling, sizing, and control methods, all tailored to match the required output power of DFIG wind turbines. To demonstrate how well our Li-ion battery solution works, we have developed a MATLAB/Simulink R2022a version model. This model enables us to compare situations with and without the Li-ion battery in various operating conditions, including steady-state and dynamic transient scenarios. We also designed a buck–boost bidirectional DC-DC converter controlled by a proportional integral controller for battery charging and discharging. The battery actively monitors the DC-link voltage of the DFIG wind turbine and dynamically adjusts its stored energy in response to the voltage level. Thus, DFIG wind turbines consistently generate 1.5 MW of active power, operating with a highly efficient power factor of 1.0, indicating there is no reactive power produced. Our simulation results confirm that Li-ion batteries effectively mitigate power fluctuations in grid-connected DFIG wind turbines. As a result, Li-ion batteries enhance grid power stability and quality by absorbing or releasing power to compensate for variations in wind energy production.

Improved nonlinear generalized model predictive control for robustness and power enhancement of a DFIG-based wind energy converter

Many studies have been made on the double-fed induction generator wind turbine system (DFIG-WTS) in recent decades due to its power management capability, speed control operation, low converter cost, and minimized energy losses. In contrast, induction machine control is a more complex task because of its multivariable and nonlinear nature. In this work, a new robust nonlinear generalized predictive control (RNGPC) is developed to maximize the extracted energy from the wind without the use of aerodynamic torque measurements or an observer. The aim of the predictive control is to produce an anticipated impact by employing explicit knowledge of the present condition. By revisiting the cost function of the conventional nonlinear generalized predictive control (NGPC), which is based on Taylor series expansion, in that way, the resilience of the system is improved. An integral action is included in the nonlinear predictive controller. As a result, if the closed loop system is stable, the suggested controller totally eliminates the steady state error, even if unknown perturbations and mismatched parameters are present. The output locating error’s convergence to the source is utilized to show the locked system’s stability. Simulation results demonstrate and verify the efficiency, the good performance, and robustness of this proposed control technique.

Performance analysis of reactive power control management for doubly fed induction generator wind turbines

The efficient operation of the Doubly Fed Induction Generator (DFIG) in wind power systems is significantly affected by reactive power flow. Depending on its excitation, the DFIG’s reactive power drawn either from the grid or fed into the grid, affects the voltage quality and stability of the wind turbine systems. In addition, an increase in DFIG excitation through the Machine Site Converter (MSC) above or below the rated excitation results in over-excited or under-excited operations of the generator respectively. Therefore, reactive power control management for DFIG wind turbines is crucial to overcoming these problems, thus, enhancing the performance of the DFIG wind turbine systems. The performance analysis of reactive power control management for DFIG wind turbines using the Lucas Nulle Wind Power Plant (LNWPP) WindSim software is presented.

Detailed Transients Simulation of a Doubly Fed Induction Generator Wind Turbine System with the EMTP-Type OVNI Simulator

Doubly fed induction generator wind turbines are increasingly used in new wind turbine installations all over the world. Growing concerns about the impact of a large number of these generators on transient and voltage stability of power system networks has led engineers to revisit modelling and simulation practices used for system stability analyses. In this paper, the latest advancements in design of the general purpose power system simulator OVNI developed at the University of British Columbia are presented, and its application to the simulation of a doubly fed induction generator (DFIG) wind turbine system is shown. Because OVNI is based on the EMTP methodology for accurate detailed modelling, and the Multilevel MATE (Multi-Area Thévenin Equivalent) concept, which, combined with hardware solutions, allows for fast simulation of large power system networks, it represents an ideal tool for testing and developing benchmark models of different wind turbine installations. Using the EMTP approach for modelling of a DFIG wind turbine system and its feeding power network we were able to study the responses of the wind turbine generator to different network events. The ultimate goal of our investigations is the development of a benchmarking process for testing different models of wind turbine generators and determining the range of validity of various degrees of approximations normally used for stability simulation purposes. Due to the rapid development of wind generation technology, it is essential to determine the minimum requirements for dynamic modeling of wind turbine generators for assessing impacts of their installations on the dynamic security and stability of power systems.

Design of an adaptive controller for double-fed induction wind turbine power

The doubly-fed induction wind turbine has gradually become the mainstream model of wind power generation. Power control is one of the advantages of doubly-fed induction wind generators and has been widely studied. However, existing power control strategies for these turbines have issues with low efficiency. An adaptive control method is proposed in this work, aiming at the power control system of doubly-fed induction wind turbines. Firstly, the power model is obtained, and then the adaptive controller is designed according to the model. Finally, simulation results verify the effectiveness of this method.

Design Method of Differential Cascading for Dual-Stator Brushless Doubly-Fed Induction Wind Generator With Staggered Dual Cage Rotor

This article proposes a new differential-cascading-based dual-stator brushless doubly-fed induction machine with a staggered dual cage rotor. Conventional differential mode of the brushless doubly-fed machine with cage rotor suffers from the low number of rotor bars because of the low equivalent synchronous pole pairs of |p1-p2|, and thus, severe rotor flux leakage, low capacity of magnetic field conversion of the rotor and low efficiency. To overcome the obstacle of the excessive harmonics of the rotor, a design method based on the differential cascading is proposed which enables the cage rotor with a high number of conductor bars even in the case of low pole pairs of |p1-p2|, hence the greatly reduced rotor leakage inductance and enhanced performance of the machine. The rotating magneto-motive force theory is applied to derive the interconnection rule of the staggered dual cage rotor, and meanwhile, the corresponding examples are illustrated. The performance comparisons between the differential cascading and the sum cascading based on the proposed machine are carried out. The results show that the proposed machine based on the differential cascading obtains higher power densities comparing to the sum cascading at the region of sub-natural synchronous speed, while its drawback is the increment of the loss due to the high rotor frequency, gaining lower efficiencies at the region of super-natural synchronous speed.

A new model of connected renewable resource with power system and damping of low frequency oscillations by a new coordinated stabilizer based on modified multi-objective optimization algorithm

This study was an attempted to present an organized structure of double-fed induction generator wind power plant with power oscillation damper (POD) in operational way and adjustable error-driven stabilizer to increase low-band oscillation reacted to their impacts in the energy system in state of charging. A novel non-linear stabilizer is suggested in the current research to compensate for the drawback of traditional stabilizers in monitoring the oscillation conditions which are internal and consequently to achieve better results in a greater range of disorders. Actually, the applied stabilizer is elastic and error-driven. Adjusting parameters of the suggested method properly plays a vital role in its efficiency. Consequently, the parameters set serve as an optimization problem which is solved by an algorithm of virus colony search (VCS) with several objectives time-domain and complex-domain. The reason behind using this algorithm is to make sure that solutions are not entrapped in local optima under the condition that the grid undergoes optimizing a great number of variables. The developed probabilistic method in frequency-domain chooses just the most favorable positions under the condition of providing the whole generators with stabilizer due to decreasing the initial expense. Lastly, a novel improved virus colony search algorithm with several objectives is implemented to provide solution for optimum adjusting of suggested stabilizer and power oscillation damper variables which serve as an optimization problem with several objectives. Confirming the efficiency of the planned method was conducted via concurrent use of eigenvalue analysis and time domain non-linear modeling in terms of various functioning states. The low frequency oscillations (LFOs) could be damped in the optimal way and as a result the stability performance of the case study system would develop meaningfully.

Dynamic Behaviour of Wind Turbine Dfig Generator under Grid Fault Conditions (Lvrt – Symmeterical Fault)

Across modern renewable power industry in globally, significant advances was established in the wind industry. Rising limit involves wind generation has to keep up steady activity during matrix shortcoming conditions, can be determined in the low voltage ride through ability. Double Fed Induction generator in wind turbines were normally utilized in wind industry applications, which are delicate to aggravations after force matrix. Thus, various sorts of assurance paths also different regulator strategies are incurred to Double Fed Induction Generator Wind Turbines for Low Voltage Ride Through ability upgrade. Here provides as an exhaustive survey additionally assessment for projected Low Voltage Ride Through arrangements utilized in Double Fed Induction generator wind turbines, of internal control techniques.

Using Flux Linkage Difference Vector in Early Inter-Turn Short Circuit Detection for the Windings of Offshore Wind DFIGs

Winding faults are the most commonly occurring type of fault in offshore doubly-fed generator units. Such faults are difficult to detect and repair, and therefore higher fault identification accuracy is required. Most of the existing research analyzes stator and rotor winding faults separately, but due to the coupling characteristics between windings, it is necessary to analyze doubly-fed induction generator (DFIG) winding faults in a unified way. This paper proposes a general fault diagnosis method that can be applied to both the stator and rotor winding faults of DFIGs. First, a general mathematical model of a windings short circuit of a doubly-fed generator is established. Then, according to the mechanism of a turn-to-turn short circuit fault of a DFIG and the expression of a bilateral flux linkage between stator winding and rotor winding, a new fault feature-bilateral flux linkage difference vector (FLDV) is obtained by mathematical derivation. Finally, the recommended value for an experimental motor of feature quantity is set. The proposed method for inter-turn fault (ITF) diagnosis of stator and rotor windings provides technical support for the sustainable development of offshore wind power. A simulation and experiment prove that FLDV has high sensitivity and high reliability for windings ITF diagnosis.

Modelling and dynamic state estimation of a doubly fed induction generator wind turbine

PurposeThis paper aims to propose an 18th-order nonlinear model for doubly fed induction generator (DFIG) wind turbines. Based on the proposed model, which is more complete than the models previously developed, an extended Kalman filter (EKF) is used to estimate the DFIG state variables.Design/methodology/approachState estimation is a popular approach in power system control and monitoring because of minimizing measurement noise level and obtaining non-measured state variables. To estimate all state variables of DFIG wind turbine, it is necessary to develop a model that considers all state variables. So, an 18th-order nonlinear model is proposed for DFIG wind turbines. EKF is used to estimate the DFIG state variables based on the proposed model.FindingsAn 18th-order nonlinear model is proposed for DFIG wind turbines. Furthermore, based on the proposed model, its state variables are estimated. Simulation studies are done in four cases to verify the ability of the proposed model in the estimation of state variables under noisy, wind speed variation and fault condition. The results demonstrate priority of the proposed model in the estimation of DFIG state variables.Originality/valueEvaluating DFIG model to estimate its state variables precisely.

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.

Integration of a Heuristic Multi-Agent Protection System into a Distribution Network Interconnected with Distributed Energy Resources

In conventional method protection schemes are devised for certain operation conditions with fixed settings throughout their operation life, however, protection systems in interconnected distribution networks rely on a detailed analysis of fault current contribution and variation in operation conditions under real-world scenarios. In fact, the concept of Adaptive Protection System (APS) and possibility of the adjustment for protection settings within modern Intelligent Electronic Devices (IEDs) have introduced desired functionalities for protection systems to cope with complex operation scenarios envisioned within future power system networks. In this paper, a novel protection system based on Multi-Agent System (MAS) and heuristic decision-making is proposed to update protection settings of the protection IEDs with respect to prevailing operation conditions in an interconnected distribution network. The adopted methodology is reliant on real-time simulation of a distribution network interconnected with Doubly-fed Induction Generator (DFIG) wind farms where different fault scenarios are applied to evaluate the functionality and performance of the proposed Multi-Agent Protection System (MAPS). In addition to that, combination of knowledge sharing between different protection IEDs and logic reasoning are integrated to fulfill protection task under real-world operation scenarios. The significance of the proposed MAPS is the improvement in protection system of the interconnected distribution network.

A robust adaptive control method for reactive power of doubly-fed induction wind generator

Some of the existing control strategies for reactive power of doubly-fed wind generators are only based on the simplified transfer function model without considering the existence of disturbance and some require real-time adjustment of the algorithm to meet different operating conditions. In order to overcome the above problems, a robust adaptive control method is introduced into the field of reactive power control of doubly-fed induction wind generator in this paper. An adaptive reactive power control strategy for the grid-side converter of doubly-fed wind generator is proposed, and the effectiveness of the algorithm is verified through simulation verification.

Dynamic Equivalent Modeling for Wind Farms With DFIGs Using the Artificial Bee Colony With K-Means Algorithm

With the increasing penetration of wind power, it is recognized that wind power will have a greater and greater impact on the planning and operation of the original power system. And the detailed modeling of wind farm with doubly-fed induction wind generator (DFIG) will require large storage and computation resources, which poses technical challenges for equivalent modeling of wind farm. In this paper, a multi-machine dynamic equivalent modeling method for wind farms with DFIGs is proposed. First, the artificial bee colony with k-means (ABC-KM) algorithm is proposed to improve the effectiveness of wind farm clustering. Second, the operating data composed of wind speed, pitch angle, rotor angular velocity, rotor current, real-time active and reactive power are selected as clustering indicators. A wind farm with DFIGs is divided into several groups and DFIGs in the same group are clustered as one DFIG through equivalent parameter aggregation. The proposed wind farm modeling method consisting of clustering method and clustering indicators is verified by comparing the simulation results of equivalent and detailed models at steady-state and dynamic-state cases.

Application of artificial intelligence to wind power generation: modelling, control and fault detection

Power converters play a key-role in the grid-integration of wind power generation and as any physical device, they are prone to mal function and failure. There is, therefore, a need for converter health monitoring and fault detection to ensure a reliable and sustainable operation of the wind turbine. This paper presents different artificial intelligence-based fault detection using fuzzy and neuro-fuzzy techniques. The proposed methods are designed for the detection of one or two open-circuit fault in the power switches of the rotor side converter (RSC) of a doubly-fed induction generator (DFIG) wind energy conversion system (WECS). In the proposed detection method only the average values of the three-phase rotor current are used to identify the faulty switch. Alongside these condition monitoring strategies, the paper also present two fuzzy logic-based controllers for the regulation of the real and reactive power flow between the grid and the converter. The performances of the controllers are evaluated under different operating conditions of the power system and the reliability, feasibility and the effectiveness of the proposed fault detection have been verified under various open-switch fault conditions.

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.

Characteristic Analysis of DFIG Wind Turbine under Blade Mass Imbalance Fault in View of Wind Speed Spatiotemporal Distribution

The blade mass imbalance fault is one of the common faults of the DFIG (Doubly-Fed Induction Generator) wind turbines (WTs). In this paper, considering the spatiotemporal distribution of natural wind speed and the influence of wind shear and tower shadow effect, the influence of blade mass imbalance faults on the electrical characteristics of DFIG WTs is analyzed. Firstly, the analytical expressions and variation characteristics of electromagnetic torque and electromagnetic power under blade mass imbalance are derived before and after consideration of the spatiotemporal distribution of wind speed. Then simulations on the MATLAB/Simulink platform were done to verify the theoretical analysis results. The theoretical analysis and simulation results show that, considering the spatiotemporal distribution of wind speed and the influence of wind shear and tower shadow effect, the blade mass imbalance fault will cause fluctuation at the frequency of 1P (P = the frequency of rotor rotation), 3P, and 6P on electromagnetic power. Fluctuation at 1P is caused by mass imbalance while fluctuation at 3P and 6P are caused by wind speed spatiotemporal distribution; the amplitude of fluctuation at 1P is proportional to the degree of the imbalance fault. Since the equivalent wind speed has been used in this paper instead of the average wind speed, the data is more suitable for the actual operation of the WT in the natural world and can be applied for fault diagnosis in field WT operation.

Stability check of doubly fed induction generator (DFIG) micro grid power system

As of late, expanding interest of renewable energy and consumption of non-renewable energy source have prompted developing advancement of renewable energy technology, for example, wind energy. Wind energy has turned out to be one of the reliable sources of renewable energy, which requests extra transmission capacity and better methods for sustaining system reliability. As of now, doubly fed induction generator wind turbine is the most well-known wind turbine. This paper focuses on DFIG wind farm design using MATLAB/SIMULINK and also investigates the issues of the system stability of the DFIG wind turbine micro grid power system. This analysis includes the changes of voltage, current, real power and reactive power based on various conditions of the power system.

Stability check of doubly fed induction generator (DFIG) micro grid power system

As of late, expanding interest of renewable energy and consumption of non-renewable energy source have prompted developing advancement of renewable energy technology, for example, wind energy. Wind energy has turned out to be one of the reliable sources of renewable energy, which requests extra transmission capacity and better methods for sustaining system reliability. As of now, doubly fed induction generator wind turbine is the most well-known wind turbine. This paper focuses on DFIG wind farm design using MATLAB/SIMULINK and also investigates the issues of the system stability of the DFIG wind turbine micro grid power system. This analysis includes the changes of voltage, current, real power and reactive power based on various conditions of the power system.

A novel adaptive model predictive controller for load frequency control of power systems integrated with DFIG wind turbines

With the rapid growth of renewable energy resources, wind energy system is getting more interest everywhere throughout the world. However, its extensive use in power systems prompts many power system dynamics and stability problems. Load variation and anomalous operating conditions prompt inconsistencies in frequency and planned power trades. These inconsistencies should be remedied by load frequency control. This paper introduces a novel frequency control system utilizing a mix of adaptive model predictive controller (AMPC) and recursive polynomial model estimator (RPME) integrated with double fed induction generator wind turbines. Inside each control duration, the RPME is identifying a discrete-time online autoregressive exogenous model. The latter is used through the AMPC to update the interior plant model in order to achieve a successful nonlinear control. The performance of the proposed system has been verified and contrasted with the conventional MPC system through a computer simulation-based MATLAB/SIMULINK. The simulation results demonstrated the superiority of the proposed system as for the conventional MPC system.