Control Of Induction Generator Research Articles

Model predictive control of a brushless cascadedoubly-fed induction generator with torque regulation for stand-alone applications

In this paper, a novel control method for Brushless Cascade Doubly-Fed Induction Generator (BCDFIG) control is proposed by integrating the Model Predictive Control (MPC) and the Direct Torque Control (DTC) methods. In previous studies, the DFIG's torque control has been performed, using different methods to improve power production. Here, direct torque control, assisted by model predictive control, is used to maintain output voltage during a change in wind speed and load. To reduce switching loss in the inverter, the model predictive unit selects the optimized switching vector and sends it to the DTC unit. According to a predefined switching table in each phase interval, the proper switching sequence for controlling the flux and torque for producing a constant output voltage will be selected. This method can be useful for wind farms and everywhere we need constant voltage, especially in stand-alone applications. Also, this proposed method can be used in grid-connected networks for injecting power into the grid or controlling reactive power. For evaluating this control method, in the first step, the BCDFIG setup is simulated in MATLAB software. Then an experimental setup has been realized in the lab to perform some tests. At the end, the obtained experimental results were investigated.

Direct torque control of a dual star induction generator based on a modified space vector PWM under fault conditions

Recent studies have shown that electrical systems in wind power conversion are subject to a 67 % failure rate, and conventional three-phase generators are considered to be the most sensitive to these faults. Induction generator current harmonics are a major source of torque ripples causing acoustic noise and vibrations. These ripples can progressively increase under faulty operating conditions. In six-phase machines, there is appearance of high harmonic currents in the air gap as space harmonics. Power electronic converters are also subject to faults, the most common being Short-Circuit (SC) and Open-Circuit (OC) faults. SC faults cause large peaks in the line currents, which trigger the protection devices, resulting in a complete shutdown of the production system. OC faults, on the other hand, cause imbalances in the phases, but the system remains in operation.Direct Torque Control (DTC) based on Space Vector Modulation (SVM) at constant switching frequency is an effective solution to tackle induction generator current harmonics. This paper proposes a DTC combined with a Proportional Integral Fuzzy Logic Controller (PIFLC) optimized by Particle Swarm Optimization (PSO) in order to overcome the problems of torque ripples. Furthermore, using Vector Space Decomposition (VSD) and the Modified Space Vector Pulse Width Modulation (MSVPWM) strategy, a significant reduction of harmonics in the air-gap can be achieved.Simulations were carried out under MATLAB/Simulink, and the results obtained demonstrate the superiority of the proposed DTC-PIFLC-PSO controller in terms of robustness against wind speed variations and under faulty switch conditions in the power converter of the Dual Star Induction Generator (DSIG) generator. In addition, a comparative study with the classical PI controller is presented to show the effectiveness of the DTC-PIFLC-PSO controller against faults with a significant reduction in the Total Harmonic Distortion (THD) during both faulty and non-faulty conditions.

Virtual impedance control of double-fed induction generator for damping enhancement in hvdc collection system

Virtual impedance control of double-fed induction generator for damping enhancement in hvdc collection system

Sliding mode control for doubly fed induction generators system-based a wind turbine

This paper presents a contribution to the control of a Doubly-Fed Induction Generator (DFIG) integrated into a wind turbine using nonlinear control. The parameters involved in this study are the active and reactive powers exchanged between the DFIG stator and the grid. For this purpose, the modeling of the DFIG with the cascaded rectifier-inverter PWM structure was established. A numerical simulation of the DFIG, powered by the cascaded structure and controlled by the developed strategies, was performed. The simulation results show that the sliding mode control (SMC) provides a better transient response , with a shorter response time and reduced overshoot. Furthermore, it maintains good performance and stability in the presence of parameter variations such as resistance and inductance. The proposed control algorithm is also robust against parameter variations and the resulting dynamic response is fast. The simulation results confirm the validity of the mentioned advantages and the effectiveness of the proposed method. The effectiveness and robustness of the control technique were implemented and tested under MATLAB/Simulink environment.

Control of dual star induction generator based on multi-level inverter used in wind energy conversion system

This paper presents vector control of dual star induction generator (DSIG) integrated into variable speed wind energy and supplied by three-level NPC converters. Now the DSIG is the most common among multiphase machines when used in high power generation systems, which is associated with two converters. Maximum power point tracking (MPPT) for extracting a maximum of power fluctuating wind speed is illustrated. In order to decrease the fluctuations that appear in the currents generated by DSIG to the electrical network, we propose the NPC structure three-level inverter. Simulation results of a 1.5 MW Wind turbine are presented to illustrate the validity of this application.

The wind turbine's direct power control of the doubly-fed induction generator

The study suggests a comprehensive approach to modeling and controlling variable-speed wind turbine systems that utilize doubly fed induction generators (DFIGs). To make sure that energy is transferred efficiently between the DFIG rotor and the grid, a two-level inverter with perfect bidirectional switches is used. Using the tip speed ratio algorithm and taking into consideration the randomness in wind speed, the maximum power at the wind turbine is optimized. Then, the control strategy utilizes direct power control (DPC) due to its various advantages. The advantages of employing this control technique are manifold. Firstly, it eliminates the necessity for rotor current control loops. Secondly, it obviates the need for controllers such as PI controllers to manage torque and flux. Furthermore, it has yielded exceptional simulation results when implementing direct power control (DPC) within the MATLAB/Simulink environment, specifically in the context of a doubly fed induction generator (DFIG) wind power system.

Robust Disturbance Rejection Rotor Current Control of Doubly-Fed Induction Generators

Robust Disturbance Rejection Rotor Current Control of Doubly-Fed Induction Generators

Performance analysis of DFIG support microgrid using GA optimized restricted Boltzmann Machine algorithm

Voltage and reactive power regulation in a deregulated microgrid can be achieved by strategically placing the Static Synchronous Compensator (STATCOM) in coordination with other renewable energy sources, thus ensuring high-end stability and independent control. STATCOM plays a crucial role in effectively addressing power quality issues such as voltage fluctuation and reactive power imbalances caused by the intermittent nature of wind energy conversion systems. To successfully integrate STATCOM into the existing system, it is essential that the control system employed for STATCOM coordination aligns with the Doubly-Fed Induction Generator (DFIG) controller within the microgrid. Therefore, an efficient control algorithm is required in the microgrid, capable of coordinating with the DFIG controller while maintaining system stability. The utilization of a Genetic Algorithm (GA) in calibrating the Restricted Boltzmannn Machine (RBM) can streamline the process of determining optimal hyperparameters for specific tasks, eliminating the need for computationally intensive and time-consuming grid searches or manual tuning. This approach is particularly advantageous when dealing with large datasets within short time durations. In this research, a Simulink model comprising a DFIG-based microgrid and STATCOM has been developed to demonstrate the effectiveness of the proposed control system using RBM in managing STATCOM and facilitating microgrid operations.

Field-Oriented Control of a Nine-Phase Cage Induction Generator with Large Speed Changes and Variable Load

This paper presents a voltage control system for multiphase squirrel-cage induction generators operating at a high variability of speed and variable load. Field-oriented vector control was used with a change in the sequence of the stator phase currents what changes the number of poles of the magnetic field produced by nine-phase stator winding. At low speeds, the current sequence is changed so that the number of poles increases allowing for the desired voltage to be obtained with greater efficiency. The task of the automatic control system was to control the DC voltage to a desired value at the output of the multiphase PWM converter. This is an alternative control method to the scalar control of voltage and frequency presented in a previous work. The control method and parameters of the automatic control system result from the mathematical model of the multiphase induction machine. The results of the laboratory tests were compared with the effects of the operation of the same nine-phase scalar controlled generator.

Control of Self-Excited Induction generator based wind turbine using by IM controller

Control of Self-Excited Induction generator based wind turbine using by IM controller

Real-time Neural Sliding Mode Linearization Control for a Doubly Fed Induction Generator under Disturbances

Abstract This paper presents an experimental implementation of a Neural Sliding Mode Linearization approach for the control of a double-fed induction generator connected to an infinite bus via transmission lines. The rotor windings are connected to the grid via a back-to-back converter, while the stator windings are directly coupled to the network. The chosen control scheme is applied to obtain the required stator power trajectories by controlling the rotor currents and to track the desired values of the DC-link output voltage and the grid power factor. This controller is based on a neural identifier trained online using an Extended Kalman Filter. Based on such identifier, an adequate model is obtained, which is used for synthesizing the required controllers. The proposed control scheme is experimentally verified on 1/4 HP DFIG prototype considering normal and abnormal grid conditions. In addition, maximum power extraction from a random wind profile is tested in the presence of different grid scenarios. Moreover, a comparison with conventional control schemes is performed. The obtained results illustrate the capability of the proposed control scheme to achieve active power, reactive power, and DC voltage desired trajectories tracking and to operate the wind power system even in the presence of parameter variation and grid disturbances, which helps to ensure the stability of the system and improve generated power quality.

DC-Bus Voltage Control of Self-Excited Induction Generator for Variable-Speed Wind Turbine Generation Including Dynamic Saturation

DC-Bus Voltage Control of Self-Excited Induction Generator for Variable-Speed Wind Turbine Generation Including Dynamic Saturation

Control of self-excited induction generator based wind turbine using current and voltage control approaches

The self-excited induction generator (SEIG) is widely applied in the wind energy conversion system (WECS) to enhance power generation. The power generation from WECS is varied in terms of varying wind speed. Hence, to improve the working of SEIG-based WECS, the multi-stage coati optimized proportional integral (CPI) fractional order proportional integral derivative (FOPID) controller is proposed in this work. The proposed coati optimized proportional integral - fractional order proportional integral derivative controls the SEIG’s grid side converter and generator side converter. The coati optimization algorithm optimizes the controller parameters of a proposed multi-state controller. The proposed CPI-FOPID controls both the voltage at the grid side converter and the current at a generator side converter. Moreover, the pitch angle of the wind turbine (WT) is controlled by the fuzzy-based tilt integral derivative (F-TID) controller. The proposed work will be implemented on the Matlab/Simulink platform, and the THD of 0.63% has proven the efficacy of the proposed methodology.

Fuzzy Logic PI controller based Direct Torque control of a Self-Excited Induction Generator through a three-level Rectifier

The main goal of this work is to control the terminal voltage of a Self-excitation induction generator (SEIG) that supplies autonomous load and is driven by a variable speed wind turbine. More advanced strategies of control have been suggested and applied these through a two-level converter. However, in this paper, we propose to study a modified DTC approach which based on the use of three-level converter (NPC structure) and instead of the traditional PI controller, we use a PI fuzzy controller to reduce torque and flux ripples, the induction generator's stator flux and electromagnetic torque are controlled using voltage space vector selection. The proposed control strategy has to maintain constant DC bus voltage regardless of load or wind speed variations. Finally, it should be noted that this control accounts for the induction generator's magnetic saturation phenomenon.

A new integral-synergetic controller for direct reactive and active powers control of a dual-rotor wind system

This paper proposes a new integral-synergetic controller for direct reactive and active powers control (DARPC) for a grid-connected doubly-fed induction generators (DFIGs) in dual-rotor wind power generation applications. The proposed DARPC strategy employs integral-synergetic control (ISC) to regulate the reactive and active powers of the DFIG-based variable speed dual-rotor wind turbine systems. The proposed ISC technique is the contribution of this work, where this strategy is a development of synergetic control and simplicity and robustness are the most prominent features. The main advantages of the proposed ISC-DARPC technique are ease of implement, good dynamic response, simple structure, and constant switching frequency operation. The Matlab software is used to validate the design of the ISC-DARPC technique, and the obtained results are compared with traditional DARPC. In addition, the ISC-DARPC technique is able to fully minimize ripples in both torque and active power during grid voltage imbalance or parametric changes on the DFIG.

Optimal Frequency and Voltage Control of Self-Excited Induction Generator for Wind Power Generation Using PWM Converter and Load Management

Optimal Frequency and Voltage Control of Self-Excited Induction Generator for Wind Power Generation Using PWM Converter and Load Management

An adaptive control strategy for grid-forming of SCIG-based wind energy conversion systems

One of the crucial issues in the expansion of isolated wind energy conversion systems (WECSs) is the design of a grid forming control structure that is robust to changes of the system’s operating point in the steady-state as well as transient conditions. This paper has addressed the voltage/frequency control of a local microgrid as well as flux and slip control of a squirrel cage induction generator that feeds the microgrid via a back-to-back converter in an isolated WECS. An adaptive nonlinear voltage control structure has been proposed for load side converter (LSC) consists of a constant frequency voltage regulator and a current controller based on the Lyapunov function method (LFM), which are connected in cascade. In an outer loop, the reference current of LSC is generated by the voltage regulator designated for maintaining the voltage/frequency of the microgrid. In an inner loop, the reference signals are robustly tracked by the current controller. In a novel reference frame that its angle difference with the stationary reference frame is determined by a dual loop DC link voltage controller, an LFM-based nonlinear flux controller is proposed for the machine side converter (MSC). Using the proposed flux control structure, in addition to maintaining the flux magnitude at a nominal value, by controlling the generator slip through adjusting the speed of the proposed reference frame, the power balance is established and the DC voltage is maintained at a pre-set value. The performance of the proposed controllers has been investigated through simulation in the MATLAB® software. The obtained results confirm the robustness and stability of the proposed control structure with respect to various disturbances and uncertainties.

Optimal Efficiency Control of Wind Mill Induction Generator Using Loss Minimization Technique

Improvement of the operating efficiency of generators used in large wind power generation systems becomes important since such a large machine's power loss is not negligible. In the conventional method integral controller is used to reduce the power loss by up to 25 % at low wind speeds. The proposed PID controller method is based on flux level reduction, where the flux level is computed from the machine model for the optimum d-axis current of the generator. For the vector-controlled induction generator, the d-axis current controls the excitation level to minimize generator loss. In contrast, the q-axis current controls the generator torque, by which the speed of the induction generator is controlled according to the variation of the wind speed in order to produce the maximum output power, thereby improve the efficiency of the induction generator.

Chaos Control of Doubly-Fed Induction Generator via Delayed Feedback Control

With the increasing wind power penetration, wind farms are directly influencing the power systems, so the need to improve the quality of the system is an open research topic. A Doubly-Fed Induction Generator (DFIG) is often used in wind power systems. However, DFIG has a complex structure and often works in harsh environments, so potential faults may occur. Faults can cause the system to fall into a chaotic working state, which is a harmful phenomenon for DFIG, since it makes the operating quality of the system worse, even leading to system destruction if not fixed on time. This study presents simulations of the chaotic phenomenon that occurs for a DFIG under specific working conditions based on Lyapunov’s exponents. The delay feedback controller is designed, and along with the selection of the appropriate controller parameters, the chaotic phenomenon is quickly eliminated, bringing the system back to stable operation.

Grid-forming control of doubly-fed induction generators based on the rotor flux orientation

The increasing penetration of renewable energies in power systems demands new services from renewable generation plants. System operators are concerned about system stability since renewable generators behave as constant power sources. Therefore, new requirements have been imposed to grid-following generators to improve their contribution to system stability acting as grid-supporting generators. Nevertheless, grid-supporting control can still compromise system stability for high penetration of renewables, and grid-forming control has arised to ensure proper operation. This paper proposes a novel grid-forming control scheme for doubly-fed induction generators, so they behave as real voltage sources. The proposed grid-forming control is based on the rotor flux orientation to a reference axis obtained from the emulation of the synchronous generator swing equation. The rotor flux is oriented to the reference axis by means of a flux controller that also controls the flux magnitude. The flux orientation in turn allows to control the doubly-fed induction generator torque, while the flux magnitude control allows to regulate the generator reactive power or terminal voltage. The proposed control system has been validated through a comprehensive real-time simulation with hardware in the loop, assessing its grid-forming capability. Moreover, small signal analysis has also been performed to assess system stability.