Wound Rotor Induction Generator Research Articles

TCSC Application for Transient Stabilization of Wind Turbine with Fixed Speed Induction Generator

Wind turbines (WTs) are a desirable alternative to traditional nonrenewable power resources as a result of recent environmental concerns. Some of them are fixed speed wind generator (FSWG) and have been integrated to power system by squirrel cage induction generator (SCIG). Induction machine absorbs reactive power during all operating conditions, especially at fault condition may result in severe voltage drop which can lead to generator outage. This outage disconnects a significant amount of active power and consequently leads to frequency instability. In order to prevent induction generator (IG) outages in short circuit failures, this paper investigates thyristor-controlled series capacitor (TCSC) device as a candidate solution. TCSC compensates the IG terminal voltage drop by adjusting transmission line impedance at fault condition. In the proposed method, a metaheuristic technique means that shuffled frog leaping algorithm (SFLA) has been utilized to optimize the TCSC controller gains. The proposed scheme can be applied for both SCIGs and wound rotor induction generators (WRIGs) which is another advantage of this method. Single-machine infinite bus system is considered as case study, and various operating conditions and disturbances have been considered to verify the effectiveness of the proposed method.

Study on Dynamic analysis of Grid Interactive of offshore wind and Marine Current Farm

Abstract:-In day-to-day life due to growth of power demand worldwide. The use of conventional energy is increased and there is reduction in conventional resources. To fulfill the Demand, it is essential to increase the renewable resources like wind, tidal, solar etc. The energy which is sustainable means which is endless. The ocean has untapped energy resources in the form of tidal wave, geothermal, offshore wind etc. at different geographical locations.OWF combined with MCF, owing to their natural availability in close proximity, would become a new kind of integrated energy generation system in near future. Mainly there are TWO types of generators synchronous and asynchronous generator we use asynchronous generator because wind is not constant in offshore wind farm .There are FOUR types of generators used in offshore wind farm (OWF) which are named as:- Doubly fed induction generator (DFIG), Squirrel cage induction generator(SCIG) ,Wound-Rotor induction generator(WRIG) ,Permanent Magnet Synchronous generator (PMSG). And in our project, we have taken wind Energy as a source and our system is hybrid of offshore wind and marine-current farm connected to an onshore power grid via a high-voltage alternating current (HVAC) link. The performance of the studied offshore wind farm (OWF) is simulated by a doubly-fed induction generator (DFIG). DFIG system is a popular system in which the power electronic interface controls the rotor current to achieve the variable speed necessary for maximum energy capture in variable winds .while the operating characteristics of the studied marine current farm (MCF) are simulated by a squirrel-cage induction generator (SCIG).SCIG is attached to the wind turbine by means of a gearbox. The wind turbine is responsible for transforming wind power into kinetic energy .Both frequencydomain approach based on a linearized system model using Eigen value analysis and time-domain scheme based on a nonlinear system model subject to a disturbance condition are carried out. It can be concluded from the simulated steady-stated transient results that the proposed HVAC link can effectively stabilize the hybrid OWF and MCF under various disturbance conditions

Tomek Link and SMOTE Approaches for Machine Fault Classification with an Imbalanced Dataset.

Data-driven methods have prominently featured in the progressive research and development of modern condition monitoring systems for electrical machines. These methods have the advantage of simplicity when it comes to the implementation of effective fault detection and diagnostic systems. Despite their many advantages, the practical implementation of data-driven approaches still faces challenges such as data imbalance. The lack of sufficient and reliable labeled fault data from machines in the field often poses a challenge in developing accurate supervised learning-based condition monitoring systems. This research investigates the use of a Naïve Bayes classifier, support vector machine, and k-nearest neighbors together with synthetic minority oversampling technique, Tomek link, and the combination of these two resampling techniques for fault classification with simulation and experimental imbalanced data. A comparative analysis of these techniques is conducted for different imbalanced data cases to determine the suitability thereof for condition monitoring on a wound-rotor induction generator. The precision, recall, and f1-score matrices are applied for performance evaluation. The results indicate that the technique combining the synthetic minority oversampling technique with the Tomek link provides the best performance across all tested classifiers. The k-nearest neighbors, together with this combination resampling technique yielded the most accurate classification results. This research is of interest to researchers and practitioners working in the area of condition monitoring in electrical machines, and the findings and presented approach of the comparative analysis will assist with the selection of the most suitable technique for handling imbalanced fault data. This is especially important in the practice of condition monitoring on electrical rotating machines, where fault data are very limited.

Experimental Study on Low Voltage Ride-Through of DFIG-Based Wind Turbine

This paper presents an architecture of the Doubly-Fed Induction Generator based on Wind Energy Conversion System (DFIG-WECS) to study with the Low Voltage Ride Through (LVRT) capability. The proposed architecture consists of three main parts namely the wind turbine, electric generator, control systems. The wind turbine and gearbox are modeled by a servo motor driven by using an inverter system. The electric generator uses the Wound Rotor Induction Generator (WRIG). The control system composes of the rotor-side converter (RSC) and the grid-side converter (GSC). The integration of the digital signal processor (DSP) with the Simulink/Matlab software of the vector control scheme is implemented to control both RSC and GSC. Besides, to protect the overcurrent of the generator’s rotor and overvoltage of the DC-link, the crowbar and chopper circuits and the logical scheme between the crowbar and the RSC are also proposed. To approve the control algorithms implemented in DSP as hardware in the loops, the proposed 0.8kW DFIG-WESC system has been performed under the experimental environment considering LVRT requirement in German grid code.

Nghiên cứu chế độ làm việc của máy phát điện cảm ứng kích từ kép khi có ngắn mạch trên lưới gần nhà máy điện gió

In this paper, the operating mode of a doubly fed induction generator (DFIG) wind turbine is studied in order to evaluate its fault ride-through and transient stability with a grid’s short circuit fault at near the wind power plant. Based on the structure of DFIG, external resistors are directly connected to rotor windings, then the generator operates as a wound rotor induction generator (WRIG) when there is a short circuit fault on the grid. According to the simulation results in Matlab, the active power is consumed on the crowbar resistor, causing the active power characteristic of generator is changed from high to low. As a result, the amount of excess mechanical energy is not much, so the generator be not accelerated significantly. These simulation results show that it is appropriate to use the crowbar resistor to change the power characteristic of the DFIG. Thanks to this change, the generator is still connected to the grid, stable operation both during and after a short circuit.

An Unsupervised Learning Approach to Condition Assessment on a Wound-Rotor Induction Generator

Accurate online diagnosis of incipient faults and condition assessment on generators is especially challenging to automate through supervised learning techniques, because of data imbalance. Fault-condition training and test data are either not available or are experimentally emulated, and therefore do not precisely account for all the eventualities and nuances of practical operating conditions. Thus, it would be more convenient to harness the ability of unsupervised learning in these applications. An investigation into the use of unsupervised learning as a means of recognizing incipient fault patterns and assessing the condition of a wound-rotor induction generator is presented. High-dimension clustering is performed using stator and rotor current and voltage signatures measured under healthy and varying fault conditions on an experimental wound-rotor induction generator. An analysis and validation of the clustering results are carried out to determine the performance and suitability of the technique. Results indicate that the presented technique can accurately distinguish the different incipient faults investigated in an unsupervised manner. This research will contribute to the ongoing development of unsupervised learning frameworks in data-driven diagnostic systems for WRIGs and similar electrical machines.

Design and investigations of MPPT strategies for a wind energy conversion system based on doubly fed induction generator

The purpose of this work is to design and to discuss various strategies to optimize the production of a wind energy conversion chain based on the doubly fed induction generator (DFIG), by capturing the maximum power at the wind turbine, using maximum power point tracking (MPPT) and pitch control. The proposed controls allow the generator to monitor the optimal operating points of the turbines regardless of wind speed variations, system parameters disturbance, and parameters variation. Simulation of WECS based on a 1.5 MW wound rotor induction generator under MATLAB/SIMULINK is carried out using the PI controller (PIC), RST controller and fuzzy logic controller (FLC). Analysis and comparisons are made for different operating scenarios: Reference tracking, robustness under variable wind speed conditions and parameters variation. The application of FLC provides a very interesting outcome for the robustness and the dynamic challenges.

D, Q reference frames for the simulation of multiphase (six phase) wound rotor induction generator driven by a wind turbine for disperse generation

The wound rotor induction machine has been traditionally accepted for a long time in a wind energy conversion system. Despite numerous concepts have been established on wound rotor induction generator (WRIG), the WRIG is lacking in the area of the multi-phase system. Hence the interest of research fraternity starts growing toward modelling of un-conventional WRIG with Wind Energy Conversion System. In this direction, six-phase wound rotor induction generator (SPWRIG) can be a game changer, because it has the property of WRIG as well as multi-phase technology. This study introduces the novel SPWRIG based on mathematical modelling, control technique, simulation and experimental results. As a major novelty, this study has included a comparison of various currents and its importance in the excitation reference frame, rotor reference frame, stator reference frame. The accuracy of mathematical modelling has been tested by experimental and simulation results.

Dynamic Behavior of Wind Turbine Generator Configurations during Ferroresonant Conditions

In this paper the dynamic behavior of different wind turbine generator configurations including doubly fed induction generators (DFIG), squirrel cage induction generator (SCIG), wound rotor induction generator (WRIG), and permanent magnet synchronous generator (PMSG) under ferroresonant conditions of energization and de-energization was investigated using Simulink/MATLAB (version 2017B, MathWorks, Natick, MA, USA). The result showed that SCIG had the highest overvoltage of 10.1 PU during energization, followed by WRIG and PMSG, while the least was DFIG. During de-energization, PMSG had the highest overvoltage of 9.58 PU while WRIG had the least. Characterization of the ferroresonance was done using a phase plane diagram to identify the harmfulness of the ferroresonance existing in the system. It was observed that for most of the wind turbine configurations, a chaotic mode of ferroresonance exists for both energization and de-energization scenarios. Although overvoltage during energization for wind turbine generator configurations was higher than in the de-energization with an exception of PMSG, their phase plane diagrams showed that de-energization scenarios were more chaotic than energization scenarios. The study showed that WRIG was the least susceptible to ferroresonance while PMSG was the most susceptible to ferroresonance.

Investigation of Combined Electrical Modalities for Fault Diagnosis on a Wound-Rotor Induction Generator

An online method for fault diagnosis on a wound rotor induction generator using stator voltage and current, and rotor current are investigated. The diagnostic method comprises processing of the generators signals and classification of the machine's condition according to healthy or specific fault type. The signal processing phase of the intelligent fault diagnosis process extracts features, which are frequency-based, interrelated to specific fault modes, i.e., stator winding, rotor winding, and brush faults. Finite element modeling of a wound-rotor induction generator is carried out under normal and different fault conditions for the purpose of conducting preliminary design and testing of the classification system. An experimental setup is then used to validate the computational results and verify the diagnostic method. The results indicate that the stator voltage, stator current, and rotor current modalities exhibit patterned sensitivities to the investigated faults. It is found that the classifier works well with a large number of features offered by the combination of these modalities yielding a best overall diagnostic accuracy of 99% in an experimental setting.

Nonlinear Controller with Rotor Crowbar and DC-Chopper Fault Ride Through Technique for Grid-Connected Doubly-Fed Induction Generator

The most significant drawback of the Doubly Fed Induction Generator (DFIG) is its susceptibility to grid fault due to its stator windings being directly connected to the grid. The stator and rotor of the DFIG are electromagnetically coupled, therefore, the resulting stator current surge during low voltage dip provokes inrush current at the delicate back-to-back converters and an overcharge of the DC-link capacitor. In this paper, a robust nonlinear controller, under the context of Lyapunov stability theory, is first employed to control the Rotor and Grid Side Power Converters under normal grid conditions. Under grid fault, the nonlinear controller is then coupled with Active crowbar and DC chopper protection schemes to ameliorate the performance of the DFIG system to ride through fault. Simulation of a 1.5MW wound rotor induction generator under MATLAB/SIMULINK is carried out using the PI-controller (PIC) and Adaptive Backstepping Controller (ABC). Analysis and comparisons are made for different operating scenarios: speed variation, grid fault, grid fault with protection schemes activated.

Planetary Gear Fault Detection Based on Mechanical Torque and Stator Current Signatures of a Wound Rotor Induction Generator

In this paper, an approach for tooth localized fault detection in the sun gear of a planetary gear, using the measured mechanical torque and the stator current of a wound rotor induction generator (WRIG), is proposed. A theoretical background is developed to demonstrate that the faulty sun gear produces periodic fault signatures in the mechanical torque and consequently fault-related frequencies in the stator current of the WRIG. The employed technique needs knowledge of mechanical system torsional natural frequencies, which aid in identifying the most sensitive fault characteristic harmonics in both mechanical torque and stator current spectra. It is illustrated by simulation and experimental results that the amplitude of these harmonics can be used as a fault index for diagnosis of tooth localized defect in planetary gears. A test rig based on a 5.5 kW WRIG, shaft connected to the sun gear of a planetary gear through a high-speed shaft and couplings, was utilized for validation of the proposed technique.

Electrical & mechanical diagnostic indicators of wind turbine induction generator rotor faults

In MW-sized wind turbines, the most widely-used generator is the wound rotor induction machine, with a partially-rated voltage source converter connected to the rotor. This generator is a significant cause of wind turbine fault modes. In this paper, a harmonic time-stepped generator model is applied to derive wound rotor induction generator electrical & mechanical signals for fault measurement, and propose simple closed-form analytical expressions to describe them. Predictions are then validated with tests on a 30 kW induction generator test rig. Results show that generator rotor unbalance produces substantial increases in the side-bands of supply frequency and slotting harmonic frequencies in the spectra of current, power, speed, mechanical torque and vibration measurements. It is believed that this is the first occasion in which such comprehensive approach has been presented for this type of machine, with healthy & faulty conditions at varying loads and rotor faults. Clear recommendations of the relative merits of various electrical & mechanical signals for detecting rotor faults are given, and reliable fault indicators are identified for incorporation into wind turbine condition monitoring systems. Finally, the paper proposes that fault detectability and reliability could be improved by data fusion of some of these electrical & mechanical signals.

Analysis and modeling of standalone wind driven doubly fed induction generator

This paper briefly enlightens on the analysis and modeling aspects of the standalone operation of doubly fed induction generator (DFIG) based wind energy conversion system (WECS). The DFIG in WECS is controlled via a single converter on the rotor terminals. The battery at the converter terminal fulfills the active/reactive power demand of the load. Whereas, the incorporation of the speed estimation technique makes the WECS free from the complexities associated with the speed sensors, thus provide a robust and reliable operation. The control technique used is simple and based on controlling the stator voltage and frequency by their comparison with a reference voltage and frequency using a simple PI controller. The supportive results for the analysis and modelling has been presented for a 7.5 kW wound rotor induction generator in MATLAB/Simulink environment.

Maximizing Output Power in Oscillating Water Column Wave Power Plants: An Optimization Based MPPT Algorithm

This paper proposes an optimization based maximum power point tracking (MPPT) algorithm for selection of appropriate external rotor resistances of wound rotor induction generator (WRIG). The generator coupled with a Wells turbine is used in oscillating water column (OWC) wave power plants. The Wells turbine suffers with stalling behaviour that reduces the average output power significantly. Hence, the objective is to prevent aerodynamic stalling of the Wells turbine and hence maximizing the output power simultaneously. But inappropriate selection of rotor resistance leads to excessive power loss. Therefore, two approaches have been applied: (i) the rotor resistance values are selected manually by trial and error method or non-optimized approach (ii) a performance index has been derived and minimized using particle swarm optimization technique to obtain the optimized values of rotor resistance. Simulation results have been performed for turbine efficiency, output power and power loss in external rotor resistance. Finally, the proposed control approach is illustrated for two particular cases of regular and irregular waves.

Sensor fault control scheme for a variable speed wind energy system in a stand-alone DC micro grid

This paper describes sensor fault control (SFC) scheme for a wound rotor induction generator (WRIG)-based wind energy system (WES) connected to a standalone DC micro grid (DCM). The DCM provides excitation for WRIG through a rotor side converter (RSC). The stator voltage and frequency are regulated using PI controllers. The generated power is supplied to loads, and excess power is supplied to DCM by PWM rectification operation of RSC. During stall mode, DCM supplies load through RSC by PWM inversion operation. To execute a smooth changeover of modes, supervisory control algorithm is employed. The control scheme involves sensors which may not be ideal and if fault occurs might lead to system collapse. To compensate the electrical sensor faults, a fault detection and compensation (FDC) scheme based on adaptive neuro-fuzzy inference system (ANFIS) is employed. For compensating mechanical sensor faults, an electrical sensor is employed. The system is experimentally tested to show the effectiveness of SFC scheme.

Control and power transfer operation of WRIG‐based WECS in a hybrid AC/DC microgrid

In this study, the control and power transfer operation of wound rotor induction generator (WRIG)-based wind energy conversion system (WECS) in a hybrid AC/DC microgrid (DCM), delivering power during islanded and utility-tied conditions are dealt. The system encompasses WRIG, rotor-side converter (RSC) and stator SC (SSC) connected back–back with DCM. AC loads, AC end of SSC, stator of WRIG and a switchable utility frames the AC microgrid. During islanded mode, stator voltage and frequency are regulated with proportional–integral (PI) controllers through RSC. During utility-tied mode, RSC is currently controlled to perform bidirectional slip power transfer. Load compensation is achieved by current-controlled SSC at all conditions. Instantaneous power theory is employed in the current control of RSC and SSC for generating reference currents. On the basis of wind/load conditions, all possible operational modes are formulated. The power transfer operation during occasional conditions such as shorted winding, over loading, low wind, machine stall and no load claims the merit of the setup. A supervisory control algorithm is developed for executing smooth power transfer. The dynamic operation is experimentally analysed to confirm the efficacious working of the WECS.

ANFIS‐based sensor fault‐tolerant control for hybrid grid

This paper describes an intelligent sensor fault detection and compensation (FDC) scheme for a hybrid grid involving renewable energy (RE) sources with power electronic interfaces. To evaluate the sensor FDC scheme, a wound rotor induction generator (WRIG)-based wind energy system connected to the hybrid grid is examined. The system employs a WRIG with excitation from DC RE grid via a single, rotor side converter. To analyse the dynamic performance, a decoupled voltage vector control is employed. The sensors involved in the control algorithm may not be ideal and if fault occurs might lead to system collapse. To overcome electrical sensor failure, a robust, intelligent sensor fault control scheme is proposed with ANFIS. A hardware-free solution with PLL block is proposed for mechanical sensor fault. The ANFIS-based FDC scheme involves a bank of observers that computes residuals, detects and isolates faults. When fault occurs, the observer output is utilised for the execution of control algorithm thereby avoiding system collapse. The focused system is simulated in MATLAB and experimentally tested with a dSPACE controller for various fault scenarios. The results show the effectiveness of the FDC scheme.

A Control Strategy for Reliable Power Output From a Stand-alone WRIG With Battery-Supported DC Link

This paper proposes a versatile control strategy for a standalone wound rotor induction generator (WRIG) with back-to-back converters supported by a battery at dc-link. The principal feature of the study is the operation of the generator as a commanded current source, to supply only sinusoidal current as desired, and the operation of battery fed Front End Converter (FEC) as a constant voltage source, which adapts to varying load conditions. Further, in implementing this feature, in a significant deviation from conventional approaches, to Rotor Side Converter (RSC) and FEC are redefined with a view to achieve versatility and reliability in stand-alone operation. In particular, the RSC is employed to track the maximum power (instead of load voltage and frequency control), whereas the FEC maintains a constant load voltage and frequency. It is revealed that there are multiple benefits of the proposed strategy such as inherent load balancing; capability to support critical loads solely by battery through the FEC as in an uninterruptible power supply (UPS), especially at low wind speeds; compensating unbalanced or harmonic load currents via FEC (as in an active power filter); and smooth transition between the MPPT mode and the UPS mode by synchronization. Simulation results of a 2-MW wind turbine, along with test results of a 2.3-kW laboratory setup, validate the proposed strategy.

Two Level Versus Matrix Converters Performance in Wind Energy Conversion Systems Employing DFIG

Wind power capacity has received enormous growth during past decades. With substantial development of wind power, it is expected to provide a fifth of world’s electricity by the end of 2030. In wind energy conversion system, the power electronic converters play an important role. This paper presents the two level and matrix converters performance in wind energy conversion system employing Doubly Fed Induction Generator (DFIG). The DFIG is a wound rotor induction generator. Because of the advantages of the DFIG over other generators it is being used for most of the wind applications. This paper also discusses control of converters using the space vector pulse width modulation technique. The MATLAB/SIMULINK ® software is used to study the performance of the converters.