Fed Induction Generator Research Articles

Bursting oscillation characteristics and adaptive high‐order differential feedback controller of doubly fed induction generator system

SummaryTo address the problem of bursting oscillations in doubly fed induction generator (DFIG) systems under external disturbances, an analysis method based on fast‐slow dynamics and a control strategy based on an adaptive high‐order differential feedback controller (AHODFC) is proposed. The fast‐slow dynamics analysis method was adopted to reveal the formation mechanism of bursting oscillations from the DFIG system owing to the multi‐timescale coupling effect of perturbation, that is, the oscillation is in the form of a bursting oscillation with alternating large‐amplitude oscillation and micro‐amplitude oscillation. A control strategy based on the AHODFC with a high‐order differentiator (HOD) was proposed to address the problem of bursting oscillations in the DFIG system. The control strategy of the AHODFC has smooth control‐rate characteristics, does not depend on the exact mathematical model of the controlled system, and has good applicability and robustness to various types of bursting oscillations caused by different disturbance amplitudes and system parameters. Our simulations verified the feasibility and effectiveness of the proposed method.

Frequency Control of Interconnected Power System via SBO assisted Simultaneous Tuning Strategy in Presence of DFIG

To achieve the objectives of the automatic generation control (AGC) of wind integrated interconnected power system (WIIPS), better tuning and control strategies are required. This paper suggests simultaneous tuning strategy for the AGC and wind system controllers to improve the stability of the WIIPS. The bulk amount of wind is integrated into the grid using the doubly fed induction generator (DFIG) and its simplified model is used to simulate the WIIPS. Initially, classical controllers are opted in AGC mechanism to reduce the frequency disturbances caused by the load and wind generation uncertainties. Further, classical controllers of WIIPS are replaced with cascade controllers to enhance the system frequency profile during the disturbances. The optimal set of solutions of the classical and cascade controllers are examined by the satin bowerbird optimizer (SBO) with the help of integral square error as fitness function of the optimization problem. Comparisons are provided to show the merits of the WIIPS over normal interconnected power system, cascade controller over classical controller and simultaneous tuning strategy over regular tuning mechanism.

Wind‐assisted microgrid grid code compliance employing a hybrid Particle swarm optimization‐Artificial hummingbird algorithm optimizer‐tuned STATCOM

AbstractThe importance of resolving stability concerns in weak AC grid‐connected doubly fed induction generator (DFIG) wind energy systems during low‐voltage ride‐through (LVRT) events cannot be ignored, given the increasing popularity of wind power‐based microgrids. Furthermore, the emergence of generation loss and postfault oscillation within a microgrid (MG) due to grid faults has also become a significant concern. The static synchronous compensator (STATCOM) under consideration in this study is tuned using particle swarm optimization (PSO), the artificial hummingbird algorithm (AHA), and a hybrid approach incorporating both PSO and AHA. Faults of both a symmetrical and an asymmetrical nature have occurred on the power grid side. The proposed hybrid PSO‐AHA‐tuned STATCOM strategy aims to improve LVRT, minimize power generation loss during faults, and reduce oscillations after a fault by controlling the flow of reactive power between point of common coupling (PCC) and MG. The MATLAB simulation environment was used to simulate the 16 MW MG test system. The performance of the PSO‐AHA‐tuned STATCOM was assessed by comparing results with those from conventional STATCOM, PSO, and AHA optimizer‐tuned STATCOM in four fault situations. A comparison of the results shows that the proposed strategy performed better than other approaches mentioned in this paper and achieved the desired objectives.

Ziegler-Nichols Based Controller Optimization for DFIG Wind Turbines

Wind power conversion systems are becoming the most preferable alternate renewable energy source. Doubly Fed Induction Generator’s utilization rotating parts in wind turbines is increasing with the wind power penetration to the electric grid. The observation becomes more noticeable when there are abnormal conditions within the electrical power system. In this paper, MPPT Controller is incorporated with DFIG through the MATLAB Simulink program is simulated. A conventional PI controller is tuned with Ziegler-Nichol’s (Z-N) method and was implemented to the DFIG Control Block. The rotor-side converter (RSC) is utilized to regulate the power generated by the doubly-fed induction generator (DFIG), while the direct current (DC) bus voltage is controlled by the grid-side converter (GSC). The DFIG's angular and comparative angular speeds are used to generate the reference torque value in the MPPT controller. This improved the time response, output power, electromotive torque, and other current and voltage characteristics. A comparison was made between the output evaluation of the inbuilt controller and the output evaluation of the proposed controller. The MPPT with tuned PI Controller's results show that the suggested system, which uses DFIG coupled to a rotor, is accurate, dependable, and feasible. DOI: https://doi.org/10.52783/tjjpt.v45.i02.6966

Impact of Short-Circuit Ratio on Control Parameter Settings of DFIG Wind Turbines

This work deals with doubly fed induction generator (DFIG) modeling and stability when connected to weak AC grids. A detailed state-space model that includes the phase-locked loop (PLL) is developed. This work aims to determine the influence of the network’s strength on DFIG stability through the short-circuit ratio (SCR). The critical values of the proportional control parameters of the grid-side and rotor-side converters (RSC and GSC), as well as PLL, which make the system unstable, are calculated for different SCR values. Finally, PSCAD/EMTDC dynamic simulations are used to validate the critical control parameters obtained by studying the eigenvalues of the DFIG state-space model regarding system stability.

Modified Multimachine Power System Design with DFIG-WECS and Damping Controller

Rotor angle stability, which involves electromechanical oscillation damping and control, is very important in maintaining the stability of modern power grid systems. Renewable energy sources like wind energy are undergoing massive integration into modern power grid systems to meet energy demands and decarbonize power grid systems of carbon emissions from fossil fuel generators. To enable increased integration of wind renewable energy sources, precise models are needed for research and analytical purposes. Wind renewable energy is generated through a wind energy conversion system (WECS); one such conversion system is the doubly fed induction generator (DFIG) system. In this study, a precise model of a DFIG-WECS was modeled and integrated into the IEEE’s two-area Kundur power test system, which represents the available power grid system, and is also a multimachine power system using the Matlab/Simulink 2023 software. A damping controller known as the power system stabilizer (PSS), whose optimal parameters were obtained using artificial eco-system optimization (AEO), was also incorporated into the integrated power grid system to control and damp electromechanical oscillations. The results showed that the PSS damping controller effectively damped electromechanical oscillations in the integrated power grid system.

Neural network predictive control for fault detection and identification in DFIG with SMES for low voltage ride-through requirements

The increasing reliance on renewable energy sources brings to light the operational challenges of doubly fed induction generators (DFIGs), particularly under grid disturbances. This study introduces an innovative approach employing Neural Network Predictive Control (NNPC) for fault detection and identification (FDI) in DFIG systems, integrated with Superconducting Magnetic Energy Storage (SMES) to meet Low Voltage Ride-Through (LVRT) requirements. Our method uniquely combines NNPC for dynamic wind speed prediction and precise control of rotor-side and grid-side converters with the stability enhancement offered by SMES. Simulation results demonstrate a notable improvement in DFIG performance under variable wind conditions and grid failures. The system-maintained voltage stability at the Point of Common Coupling (PCC) with less than 5% deviation during transients and ensured consistent power output, marking a significant advancement in LVRT compliance. However, the model assumes steady-state grid conditions and does not account for extreme weather scenarios, indicating areas for future research. This study's findings contribute valuable insights into the robust operation of DFIGs within modern renewable energy grids.

Maximum allowable hp rating of 3-phase induction motor fed through a stand-alone constant V/f controlled DFIG via RSC

This paper presents a scheme to start three-phase induction motors (IMs) directly connected to terminals of constant V/f controlled doubly fed induction generator (DFIG) through the rotor side converter (RSC). The proposed control is achieved by controlling the output voltage and frequency of stand-alone DFIG via controlling an injected voltage into the rotor circuit through the RSC. The control scheme provides a search for maximum rating of the three-phase IM which can be supplied from a DFIG. The search technique is based on using a simplified mathematical model to find the capability limits of the RSC and DFIG. It is found that these parameters depend on the stator frequency and rotor slip. Therefore, an investigation is performed to find the lowest frequency and the corresponding allowable maximum rating for the IM to be safely started. A typical example is provided in the paper for a 15 kW DFIG. It is shown that this generator could supply a three-phase IM with a maximum rating of 1-hp if it operated at nominal outputs, voltage and frequency, during start-up period. While, using the proposed technique, the same generator could start-up a three-phase IM with maximum power rating of 7.25 hp.

Harmonic Elimination Using Grid Integrated Hybrid Renewable Energy System with Optimized Control for Nano Scale Based 31-Level MLI

This research focuses integration of grid integrated hybrid renewable energy system (HRES) with optimized control techniques for harmonic elimination using Nano Scale Based 31-Level Multi-Level Inverter (MLI). The proposed system combines Renewable Energy Sources (RES), such as Solar Photovoltaic (PV) and Wind Energy Conversion System (WECS) assisted with Doubly Fed Induction Generator (DFIG) to generate power for grid integration. Interleaved KY converter with novel Rain Optimized Algorithm assisted Artificial Neural Network (ROA-ANN) based Maximum Power Point Tracking (MPPT) is established, which is a hybridized approach extracting maximum PV power and optimizes power output for utilization. Excess energy generated from hybrid power sources is utilized to charge battery. The DC supply from hybrid sources is transferred to silicon carbide switches of 31 MLI for elimination of harmonics using Selective Harmonic Elimination Pulse Width Modulation (SHE-PWM). The 31-Level MLI facilitates conversion of DC voltage to AC with assistance of Particle Swarm Optimized Proportional Integral (PSO-PI) controller. Finally, controlled AC supply is transferred to LC filter, resulting in effective grid synchronization with reduced harmonics. The proposed system’s performance is validated using MATLAB Simulink, and obtained results demonstrate effectiveness with reduced total harmonic distortion (THD) of 0.66% in contrast to state-of-art approaches

The Analysis of Sub-Synchronous Resonance in a Wind Farm for a Doubly-Fed Induction Generator Using Modern Analytical Method

The occurrence of Sub-Synchronous Resonance (SSR) phenomena can be attributed to the interaction that takes place between wind turbine generators and series-compensated transmission lines. The Doubly-Fed Induction Generator (DFIG) is widely recognized as a prevalent generator form employed in wind energy conversion systems. The present paper commences with an extensive exposition on modal analysis techniques employed in a series of compensated wind farms featuring Doubly Fed Induction Generators (DFIGs). The system model encompasses various components, including the aerodynamics of a wind turbine, an induction generator characterized by a sixth-order model, a second-order two-mass shaft system, a series compensated transmission line described by a fourth-order model, controllers for the Rotor-Side Converter (RSC) and the Grid-Side Converter (GSC) represented by an eighth-order model, and a first-order DC-link model. The technique of eigenvalue-based SSR analysis is extensively utilized in various academic and research domains. The eigenvalue technique depends on the initial conditions of state variables to yield an accurate outcome. The non-iterative approach, previously employed for the computation of initial values of the state variables, has exhibited issues with convergence, lack of accuracy, and excessive computational time. The comparative study evaluates the time-domain simulation outcomes under different wind speeds and compensation levels, along side the eigenvalue analysis conducted using both the suggested and non-iterative methods. This comparative analysis is conducted to illustrate the proposed approach efficacy and precision. The results indicate that the eigenvalue analysis conducted using the proposed technique exhibits more accuracy, as it aligns with the findings of the simulations across all of the investigated instances. The process of validation is executed with the MATLAB program. Within the context of the investigation, it has been found that increasing compensation levels while simultaneously decreasing wind speed leads to system instability. Therefore, modifying the compensation level by the current wind speed is advisable.

Variable Power Tracking Control Strategy of Doubly Fed Induction Generators for Fast Frequency Responses

Frequency regulation and droop control of doubly fed induction generators (DFIGs) can quickly respond to frequency changes and reduce the maximum rate of frequency (MROFF) in power systems. However, due to real-time dynamic changes in the MPPT control loop, the ability to improve the lowest frequency point is limited. Therefore, this article first describes an in-depth analysis of the dynamic characteristics of the incremental power of frequency regulation with droop control using an equivalent linear model. The limitations of improving the lowest frequency point under the influence of dynamic changes in the MPPT control loop are revealed. Secondly, to address the impact of these dynamics, an improved decoupling frequency regulation (IDFR) strategy based on power tracking is proposed, aiming to increase the maximum frequency deviation (MFD) and MROCOF. Then, in order to overcome the difficulty of adjusting control coefficients in the IDFR strategy, an adaptive control coefficient tuning fuzzy control method based on frequency deviation and ROCOF was proposed to flexibly adjust control requirements under various working conditions, thereby improving the control stability and performance of the system and effectively solving the problem of control coefficient allocation. Finally, to verify the frequency regulation performance of the proposed IDFR strategy under various operating conditions, simulations were conducted based on different disturbances and wind conditions. The results show that the proposed IDFR strategy significantly improves the system MFD and MROCOF improvement ability under various conditions.

Model Predictive Control on Transient Flux Linkage and Reactive Power Compensation of Doubly Fed Induction Wind Generator

For weak grid scenario with high new energy proportion, large fluctuations of load are prone to cause low-voltage ride through. Moreover, stator transient magnetic flux will cause overvoltage and overcurrent problems in the rotor of doubly fed induction generator. Based on model predictive control, a control strategy for transient flux linkage and reactive power compensation is proposed. Firstly, regarding the issue of reactive power allocation of grid side converters (GSC) and rotor side converters (RSC), an allocation strategy is derived under minimizing winding energy loss on case of low-voltage ride through, enabling the wind energy conversion system to provide reactive power support during grid voltage recovery process. Meanwhile, an improved mixed second- and third-order generalized integrator (MSTOGI) phase-locked loop (PLL) is used to extract the positive and negative sequence components of the power grid voltage, further for RSC control. Secondly, in response to power grid faults, considering the influence of stator DC transient flux and negative sequence flux components on rotor current, by injecting rotor transient compensation current and stator flux feedforward compensation into RSC, the rotor impulse voltage and loop current are reduced. Moreover, combined with model predictive control algorithm, a control strategy of rotor current is designed. Finally, a simulation platform is built to validate the effectiveness of the proposed method based on comparing with several traditional vector control low-voltage ride through methods.

Mitigating SSO in an Actual DFIG-MTDC System: Field Implementation and Tests

Recently, a new type of subsynchronous oscillation (SSO) event was observed in the doubly fed induction generator (DFIG)-based wind farm connected to a multi-terminal dc (MTDC) grid. It has been established that converter-based devices can interact with each other and other grid components. Generally, it is difficult to replicate an SSO event and devise a mitigation scheme due to the complex and black-box nature of converter-based devices. This paper demonstrates the field implementation of a model-independent method to mitigate the SSO using additional band-rejection filters in the DFIG's converter controller. The proposed method is unique in the sense that the complete design and implementation were carried out without detailed models or prior EMT studies. Field results illustrate that the risk of SSO can be significantly reduced by supplementing the DFIGs with properly tuned band-rejection filters, which reshape the DFIGs' impedance characteristics at the desired frequency. The test results obtained under various operating conditions further confirm the effectiveness of the mitigation scheme. The implementation and field tests of the filter-based mitigation scheme in an actual system can provide a practical reference for solving similar SSO issues in other large-scale systems without going through detailed EMT studies.

An efficient MPPT techniques for inter-harmonic reduction in grid connected hybrid wind and solar energy systems

In this work, the operation of photovoltaic system, wind turbine driven doubly fed induction generator along with battery has been observed. Also, a searching space minimization-based artificial bee colony scheme is developed for tracking the maximum power in a doubly fed induction generator-based system. To track maximum power in solar systems, an improved adaptive reference voltage approach has been presented. Several conventional and optimization-based techniques are used by DFIG and photovoltaic systems to get around the non-linearity features in the output parameters. Regarding DFIG, the artificial bee colony method based on searching space minimization can be used to solve the shortcomings of the perturb and observe algorithm. Because of its weather-sensitive nature, it can withstand sudden changes in wind speed. The suggested searching space minimization based artificial bee colony strategy uses a mechanism for determining the range of optimal rotor speed in order to track the maximum power point more quickly. The maximum power point tracking performance of the adaptive reference voltage technique is superior to that of current perturb and observed-based systems. However, a huge processing memory is required in order to track the maximum possible power point. This paper proposes an enhanced maximum power point tracking technique based on adaptive reference voltage that does not require a memory unit. Additionally, despite sudden changes in irradiation conditions, improved adaptive reference voltage can drift-free and reliably monitor the maximum power point. The new adaptive reference voltage technique uses temperature and radiation sensors to identify the region nearest to the maximum power point. This helps the system respond more quickly. The proposed system with searching space minimization based artificial bee colony and improved adaptive reference voltage schemes displays lower inter-harmonic content in grid current compared to perturb and observe scheme. The proposed scheme has been implemented in MATLAB & simulink atmosphere and OPAL-RT displayed satisfactory results.

Enhanced Control of Doubly Fed Induction Generator Based Wind Turbine System Using Fractional-Order Fuzzy PD+I Regulator

Enhanced Control of Doubly Fed Induction Generator Based Wind Turbine System Using Fractional-Order Fuzzy PD+I Regulator

Robust damping control for integrated wind turbine power networks during low inertia condition

AbstractThis paper presents a modal analysis‐based impact analysis of the change in system inertia due to the integration of the large‐scale doubly fed induction generator (DFIG)‐based wind turbine system (WTS) on the power system damping in inter‐area oscillation modes. The impact of replacement of a synchronous generator by WTS of same MVA capacity on system dynamics such as emergence of new critical modes of inter‐area oscillations affecting system stability is studied. Further, a double‐channel scheme‐based wide‐area damping controller (WADC) is proposed for WTS, which provides sufficient damping of prominent oscillation modes and enhanced stability margin to alleviate the negative impact of reduction in system inertia. The comparative assessment of the proposed controller with a PSS‐based WADC on a modified New England 10‐machine system validates the performance and is found to be more effective in mitigating inter‐area oscillation in the system. The real‐time feasibility of the proposed double‐channel WADC is evaluated on the Real‐Time Digital Simulator (RTDS) platform. The simulation results show that the proposed WADC can successfully mitigate various inter‐area modes simultaneously. Furthermore, it provides robust performance for a variety of contingencies, time delays in feedback signals, and uncertainties associated with different operating scenarios of WTS.

Maximum power point tracking improvement using type-2 fuzzy controller for wind system based on the double fed induction generator

Introduction. In this paper, to maximize energy transmission in wind power system, various Maximum Power Point Tracking (MPPT) approaches are available. Among these techniques, we have proposed the one based on typical fuzzy logic. Despite the somewhat reduced performance of fuzzy MPPT. For a number of reasons, fuzzy MPPT can replace conventional optimization techniques. In practice, the effectiveness of conventional MPPT methods depends mainly on the accuracy of the information given and the wind speed or knowledge of the aerodynamic properties of the wind system. Novelty. Our new MPPT for monitoring the maximum power point has been proposed. We developed an algorithm to improve control performance and govern the stator’s developed active and reactive power using the typical fuzzy logic 2 and enable robust control of a grid-connected, doubly fed induction generator. Purpose. MPPT which implies the wind turbine’s rotating speed should be modified in real time to capture the most wind energy, is necessary to achieve high efficiency for wind energy conversion, according to the aerodynamic characteristics of the wind turbine. Methods. Developing a mathematical model for a wind energy production system is complex, can be strongly affected by wind variation and is a non-linear problem. Thanks to these characteristics, thus, the Lyapunov technique is combined with a sliding mode control to ensure overall asymptotic stability and robustness with regard to parametric fluctuations in order to accomplish this goal. We contrasted our fuzzy type-2 algorithm’s performance with that of the fuzzy type-1 and Perturbation & Observation (P&O) suggested in the literature. Practical value. The simulation results demonstrate that the control performance is satisfactory when using the fuzzy logic technique. From these results, it can be said for the optimization of energy conversion in wind systems, the fuzzy type-2 technique may offer a workable option. Since it presents a great possibility to avoid problems either technical or economics linked to conventional strategies.

Hybrid approach for 3 phase bridgeless AC to DC Cuk converter for WECS

ABSTRACT This manuscript proposes a novel hybrid method based on a single-stage three-phase bridgeless alternating current (AC) to direct current (DC) Cuk converter for wind energy conversion systems (WECS). The proposed hybrid method is the combination of Mexican Axolotl Optimization (MAO) and Fuzzy Wavelet Neural Network (FWNN), hence it is named as MAO-FWNN method. Moreover, the proposed method enhanced the system performance by distributing the defined reactive-power to harmonic reduction and doubly fed induction generator (DFIG). The proposed converter is modelled under a discontinuous mode of the inductor current. The converter’s output inductor is modelled as a continuous inductor current mode, and it functions to provide enhanced power quality (PQ) and low DC (Direct Current) voltage ripple. At that point, the MATLAB platform is used to execute the performance of the proposed method, and it is compared with existing methods. The performance of the proposed method provides the 0.095 to 0.096 times/sec, which is higher than the existing methods. As a result, the proposed technique is well established compared to the existing techniques.

Nonlinear Model Predictive Control for Doubly Fed Induction Generator with Uncertainties

Doubly fed induction generators (DFIG) find extensive application in variable-speed wind power plants, providing notable advantages such as cost-effectiveness, operational flexibility across varying speeds, and enhanced power quality. This research focuses on the control of DFIGs employed in variable-speed wind turbine configurations. A suitable mathematical model is chosen for representative systems following a comprehensive review of contemporary research. Subsequent analysis reveals the instability of the open-loop time response of the system. To address this instability, the initial approach involves the implementation of the conventional model predictive controller (MPC). However, the outcomes indicate that this controller falls short of delivering satisfactory performance despite the enhanced stability. In the subsequent phase, efforts are made to mitigate the impact of wind input variability by utilizing the Kalman filter, given its effectiveness in handling high variability. Following this, a novel methodology is introduced, which combines nonlinear MPC with the Lyapunov function. This method is based on the nonlinear model of the system. By using the Lyapunov function in the nonlinear MPC structure, the stability of the designed controller is guaranteed. To validate the proposed control approach, the results are compared with PID based controller in MATLAB/Simulink. The simulation results showed that the output variables of the modeled DFIG system achieve stability within a reasonable timeframe applying the input.

Performance Enhancement of Droop Controlled DC Microgrid Using Solar Fed Hybrid BIFRED Converter with RBFNN

Electric power system’s structure is shifting from a generator to a converter-based, posing the risk of reduced system inertia. This transition is due to the increased penetration of power electronics-based renewable energy sources (RESs) and Energy Storage Systems (ESS). The microgrid concept supports their accommodation into electric networks; however, it requires appropriate control to solve the voltage stability issues created by reduced inertia. The proposed DC microgrid aims to maintain voltage stability in DC-link comprising wind, solar, and ESS, irrespective of changes in operating conditions. An improved Z source- Boost Integrated Fly Back Rectifier/Energy Storage DC–DC (BIFRED) converter is proposed to increase the output voltage of photovoltaic (PV) system to achieve better DC-link voltage stability. Radial basis function neural network (RBFNN) approach is used to harvest the maximum power possible from the PV panel and to improve the conversion efficiency. The proposed DC microgrid also includes Wind Energy Conversion System (WECS) powered by a Doubly Fed Induction Generator (DFIG). It integrates droop control with virtual inertia and damping control and effectively handles the voltage stability issues brought out by RESs and loads. Artificial neural network (ANN) optimized droop-controlled bidirectional converter (BDC) is implemented to integrate ESS and resolve the imbalance created by ESS. The work is validated by MATLAB simulation model and a laboratory prototype.