Cage Induction Generator Research Articles

Squirrel cage induction generator based micro grid voltage assessment with STATCOM using different metaheuristic approaches

Squirrel Cage Induction Generators are the most common machine to operate wind-based power plants. Microgrids are small-scale electrical systems that provide power to a local area, and optimization methods for microgrids aim to ensure that these systems operate in a way that is both efficient and cost-effective. In such applications, STATCOM is used as reactive power provider and It is necessary to use advanced controllers like the Genetic Algorithm (GA), Firefly Algorithm (FA), and Adaptive Neuro Fuzzy Inference System (ANFIS) as the usual approaches for setting gain factors of STATCOM controller which does not perform well in the case of sudden voltage level changes due to disturbances. The firefly algorithm is primarily required to estimate the gain factors of the STATCOM controller which is used in hybrid micro grid with SG and SCIG for controlling the output voltage in the occurrence of large probabilistic ambiguity. The effectiveness of firefly controlled STATCOM controller for voltage-reactive power control in hybrid microgrid is further examined and validated by comparing the results with other GA, ANN and ANFIS tuning techniques. The need for reactive power is accomplished by STATCOM to minimize the time required to control voltage transient response. The main contribution of this paper includes: an assessment of STATCOM performance with step variations in the input wind energy and reactive power load requirement under conditions of severe probabilistic uncertainty, system analyses conducted under dynamic conditions rather than using a composite load model. Additionally, a comparison of reactive power and voltage control by STATCOM is presented, and employing FA techniques to improve, a comparative of STATCOM reactive power and voltage control. Results comparing all tuning techniques shows that utilizing the Integral of Square of Errors (ISE) criterion, sophisticated tuning techniques can maintain excellent performances under a variety of disruptions.

Operation Characteristics When Applying a Double Squirrel Cage Induction Generator with Different Multiples of Locked Rotor Current

Operation Characteristics When Applying a Double Squirrel Cage Induction Generator with Different Multiples of Locked Rotor Current

Prediction of short circuit current of wind turbines based on artificial neural network model

The growth of renewable energy on a global scale is making significant strides in power plants. This is due to the increasing concern about climate change, the rising demand for electricity, and the necessity to reduce reliance on fossil fuels. Ensuring the successful integration of new energy resources into the existing network is just as crucial as it requires the system to be reliable and adaptable. For instance, wind energy, which is one of the renewable sources, has an intermittent nature that necessitates the ability to synchronize its actions to achieve the desired system performance. The objective of this study is to utilize a new neural network system to calculate the short circuit current of power plants. Specifically, the focus is on identifying and categorizing the short circuit faults that occur between the stator coils of the squirrel cage induction generator used in wind power generation. To achieve this, a system was developed to simulate turbine data. Subsequently, four feature extraction techniques and machine learning algorithms were employed to enable early detection of short circuit faults. The numerical results obtained from the simulation demonstrated the high efficiency and accuracy of the proposed model.

Energy management in gyms microgrid: Nonlinear control of stationary bikes and treadmills with parallel rectifiers and AC/DC conversion

This article presents the complete design of a nonlinear control system for multiple stationary bikes connected to a mechanical energy conversion system equipped with squirrel cage induction generators (SIGs) linked to AC/DC converters. The primary objective of this study is to investigate the feasibility of powering multiple treadmills using the DC bus via DC/AC converters. The novelty of our approach lies in the integration of a new strategy of control system to achieve multiple control objectives within a gym microgrid environment, and an energy management algorithm to ensure the energy flow between intermittent generation and the considered, somewhat random, demand. The system is composed of several subsystems: i) stationary bikes connected to the DC bus via inverters acting as intermittent power sources; ii) a Li-ion battery-based energy storage system interfaced through a Buck-Boost converter; iii) electromechanical loads, including treadmills, powered by DC/AC converters, in addition to other DC loads. The main control objectives are as follows: a) each stationary bike extracts energy from the DC network by regulating the torque applied by the athlete, ensuring that the torque follows the reference torque; b) the treadmill’s speed must follow the reference generated based on the athlete’s condition; c) ensuring the protection of the energy storage system by monitoring its current and voltage; d) all mentioned objectives are achieved while maintaining the DC bus voltage at a reference value. To achieve these objectives, a nonlinear control approach based on Lyapunov theory is used to design the controllers. A formal analysis is conducted to assess the performance of the studied system. The system’s performance is demonstrated using the MATLAB/Simulink environment. Numerous simulations demonstrate that every control objective is achieved. Specifically, the system maintained the DC bus voltage at 500 V with a maximum deviation of 1 V, and the treadmill speed followed the reference within a margin of 0.1 m/s.

Three-phase model of SCIG-based variable speed wind turbine for unbalanced DSLF analysis

Steady state performances of the electric power distribution system are normally assessed or evaluated based on load flow analysis. To properly carry out the analysis, a valid steady state load flow model of each distribution system component, including the wind power plant (WPP), needs to be developed. The present paper proposes a method for modeling and integrating squirrel cage induction generator (SCIG)-based variable speed WPP into a three-phase unbalanced distribution system load flow (DSLF) analysis. The proposed method is based on a single-phase T-circuit model of fixed speed WPP, which has successfully been applied to balanced electric power systems. In the present work, the single-phase T-circuit model is extended and modified to be used in steady state load flow analysis of three-phase unbalanced distribution systems embedded with SCIG-based variable speed WPP. Results of the case studies confirm the validity of the proposed method.

Analysis of magnetic saturation effects in the squirrel cage induction generators

This work concerns an investigation on the analysis of the magnetic saturation effects in the three-phase squirrel cage induction generator which is considered as a main device in wind energy conversion systems. The magnetic saturation is considered as an important factor causing destructive effects on power qualities such as harmonics and distortion. Several approaches have been presented in the literature for the modeling of the electric machines considering magnetic saturation. The widely used and precise approach is the finite elements method which is particularly characterized by its high computational time. The novelty in this paper is that a state model has been developed for the healthy conditions of the three-phase squirrel cage induction generators considering the experimental variation of the magnetizing inductance in terms of the magnetizing current. Simulation and experimental tests are provided to extract some important signatures on stator voltages and currents. It will be deduced that the spectrum analysis of stator currents contains useful information on magnetic saturation. Experimental and theoretical results illustrate the consistency of this approach for the modeling and analysis of the squirrel cage induction generators considering the magnetic saturation.

FRT capability improvement of a wind power system using support vector regression and deep neural network models

ABSTRACT The increasing energy demand and environmental conditions have led many countries to favor renewable energy,such as wind and solar,over conventional power plants. As per the Central Electricity Authority (CEA), India’s wind power capacity has grown substantially, reaching 45,154 MW in 2023, from 22,465 MW in 2013. However, integrating wind generators to an existing power system network can reduce transient stability during faults. To prevent wind turbine disconnection during faults, Indian grid code authorities mandate Fault Ride Through (FRT) or Low Voltage Ride Through (LVRT) capability for wind turbines. This paper proposes Dynamic Voltage Restorer (DVR) for enhancing the FRT capability of a constant speed wind turbine. Analysis and simulation are done on a fixed speed wind turbine employing Squirrel Cage Induction Generator (SCIG) under balanced and unbalanced voltage sags. Performance of DVR with two Artificial Intelligence-based controllers, Support Vector Machines(SVM) Regression Model Based Supervised Machine Learning algorithm, and Deep Neural Network (DNN) controller, is analysed and compared. The SVM Regression algorithm, achieves 100% voltage sag compensation under unbalanced voltage sags, reduces torque pulsations to 25% and maintains rotor speed at rated values, enabling the turbine to remain connected to the grid. Additionally it reduces Total Harmonic Distortion to 2%.

Investigation of the Impact of SSSC-Based FLC on the Stability of Power Systems Connected to Wind Farms

The integration of renewable energy sources into power systems has increased significantly in recent years. Among various types of renewable energy, the use of wind energy is growing rapidly due to its low operating cost, wide distribution worldwide, and no greenhouse gas emissions. However, power systems integrated with wind energy may face stability and reliability issues due to the intermittent nature of wind power. Therefore, in power systems connected to wind farms, it is usually required to use some compensators such as static synchronous series compensator (SSSC) to increase the system performance under abnormal conditions. On the other hand, for an SSSC to be effective in improving the system performance, it must be equipped with a suitable controller. In this paper, a fuzzy logic controller (FLC) is used for the SSSC because of its advantages over conventional controllers. Extensive research has been conducted in power systems with wind turbines in which SSSC or FLC has been used; however, their simultaneous application in such systems has received less attention. Therefore, this article aims to fill this gap. The proposed method is implemented on two power systems and the simulation results are analyzed. In both systems, the dynamic behavior of three different wind farms is examined. In the first and second wind farms, either a squirrel cage induction generator (SCIG) or doubly-fed induction generator (DFIG) are used, whereas in the third one which is a combined wind farm (CWF), an equal number of SCIG and DFIG are employed. In wind farms with SCIG or DFIG, an SSSC is also utilized. Furthermore, an FLC is employed for the SSSC to improve its efficacy. A proportional integral (PI) controller is also considered for the SSSC, and its results are compared with FLC results. The simulation results confirm the superiority of FLC over PI controller.

Robust predictive control strategy of SCIG-based drive system

This article presents a robust finite control set predictive scheme for a stand-alone squirrel cage induction generator (SCIG) drive. This technique is considered an alternative to the drive system due to the inclusion of system nonlinearities and fast dynamic response. The control objective in the distributed generation environment is to fix the output voltage to follow the stand-alone requirement. The strategy establishes optimized switching instants for cost function minimization for both source and load converter control and diminished cross-coupling amid active and reactive power during transient scenarios. The scheme is designed to achieve the minimal effect caused by the parameter uncertainties. During source and load changes, this work will also address the maintenance of dc-link voltage, machine, and load variables at the set value, supported by machine and load-end converter control to achieve stand-alone load objectives. In addition, the presented scheme is also tested with random variation of speed to check the efficacy of the control configuration. The drive performance is evaluated by simulation using MATLAB/Simulink environment. Comprehensive real-time findings obtained from a scaled laboratory test bench using dSPACE-1104 are provided to verify the feasibility of the predictive solution.

Future Scope and Current Energy Situation of Wind Energy, with a Simulation of Small Wind Farm in Matrix Laboratory (MATLAB)

When the world is going through extreme energy shortage, mainly the non-renewable energies, wind energy is the hope along with solar energy, hydro energy, nuclear energy and bio mass energy to meet the energy demand. In the end of 2021, in India only, the wind capacity was 40 GWatt [8]. By the end of 2030, new 30 GWatt offshore wind capacity will be installed [8]. Wind turbines may be of various shapes and sizes. When more than one wind turbines are working together to create electrical power, they form a wind farm. The aim of this particular project is to make a simulation of a small wind farm of 4.5 MW in the simulation part of MATLAB software. Here squirrel cage induction generators are used as the electrical generators connected to the turbines. It generates power for the grid. SVC is connected to the wind turbines to control the overall reactive power. The aim is to make a MATLAB Simulink phasor model of a 4.5 MW wind farm with SVC with three fully functioning wind turbines.

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.

A new-fangled connection of UPQC tailored power device from wind farm to weak-grid

A significant portion of wind power conversion systems worldwide comprise wind farms (WFs) that use Squirrel Cage Induction Generator (SCIG) and are directly linked to the power grid. In facilities that generate electrical energy at a moderate level, WFs are connected by means of distribution systems that use medium voltage (MV). It is not uncommon for such a system to produce a scenario in which the amount of electricity generated corresponds to the grid’s transit volume. When a wind farm’s wind power generation system is connected to a weak grid, the lack of potential control of the Point of Common Coupling (PCC) is a primary issue. This strategy is called a “Wind Farm with Weak Grid Connection.” Therefore, the amalgamation of weak grids, fluctuating electricity from wind, and variations in load on the system cause disruptions in the PCC voltage, further degrading the Power Quality (PQ) and the WF stability. Either the control method at the production level or the compensating strategies at the PCC level can improve this situation. If wind farms are built on SCIG and are directly linked to the grid, it is essential to utilise the last substitute. The technology known as Custom Power Devices (CUPS), proved extremely helpful for this type of application. This study presents a compensation technique based on a specific CUPS device, known as the Unified Power Quality Compensator (UPQC), as a possible solution. The potential terminals of WF needed to be regulated, and the voltage fluctuations on the grid side required to be reduced, so a custom-made control strategy for the UPQC device was designed internally. The control of power, such as active and reactive in the UPQC’s series and shunt converters, as well as the transmission of power via the UPQC DC-Link between converters, are the foundation of the internal control strategy that has been developed. Compared to other bespoke tactics that use reactive power, this strategy increases the UPQC’s capability to provide compensation. The suggested study calculates THD using a FUZZY controller. The results are compared to PI controller results. Simulation findings show how the suggested compensating strategy can minimise THD values and improve wind farm power and stability. The simulations suggest that the proposed compensating strategy enhances WF power and stability.

Power Limitation at High Wind Speed for a Variable Speed Fixed Pitch Wind Turbine using Close-Loop Scalar Control

This paper represents the speed regulation for a fixed pitch stall-regulated variable speed wind energy conversion system. The speed regulation in the high (above rated) wind speeds region is the main topic of this paper where in this region, the rotor/generator speed activity is controlled by using the concept of adjustable or variable speed drive (ASD/VSD). Speeds need to be controlled in order to maintain the generated power by reducing the power coefficient from the peak of Cp curve. It can be achieved by reducing the tip speed ratio from the optimum value when wind speed vary from rated wind speed to cut-out wind speed. Therefore, closed-loop scalar speed control with the concept of constant ratio of voltage/frequency was being applied. In addition, simple algorithms of drive train and squirrel cage induction generator were being used. A proportional integral (PI) controller was used to control the generator slip speed. Results demonstrate that such a closed-loop scalar control with proportional integral (PI) controller is good enough to accurately maintain constant power by restraining the rotational speed corresponding to the wind speed variation at the rated wind speed.

Comparing SCIG and DFIG for Wind Generating Conditions in Macedonia

The wind energy has become the most potential renewable energy source recently. The technological and industrial development in the wind power generation indicates that wind power should be seen as one of the main domestic sources for electricity generation in all countries. This paper gives an overall observation of the most commonly used electrical machines, i.e. the squirrel cage induction generators (SCIG) and doubly fed induction generators (DFIG) in the wind generation systems. Using the Matlab/Simulink, a simulation of wind farm with the two types of generators has been made in order to compare the results and to comment on the best option based on the output characteristics of the generator and wind turbine.

Constant Voltage Model of SCIG-Based Variable Speed Wind Power Plant for Load Flow Analysis

In recent years, the application of variable-speed wind power plants (WPPs) has become more and more popular and surpassed fixed-speed WPPs. This popularity is mainly because variable-speed WPPs are much more efficient in capturing or extracting wind energy than fixed-speed WPPs. Due to its relatively cheaper cost, the use of SCIG (Squirrel Cage Induction Generator)-based variable-speed WPP is currently increasing. This type of WPP is usually equipped with a power electronics converter to obtain a broader range of variable-speed operations. Modeling the power system components is undoubtedly necessary for performing the system analysis (including load flow analysis). This paper discusses the steady-state model of SCIG-based variable-speed WPP for load flow analysis of electric power distribution systems. The proposed model can be used for SCIG-based variable-speed WPP with voltage control operating mode. The model was developed based on formulas that calculate the turbine mechanical power input and the WPP electrical power output. This paper also presents a case study in which the proposed model is applied to a representative electric power distribution system.

Power Quality Analysis of Wind Turbines. Part I – Static Analysis

This paper shows a study on Power Quality (PQ) analysis of Wind Turbines (WT) installed in wind farms. A specifically designed measurement system has been installed in three wind farms with three different types of asynchronous generators of 600 kW and 700 kW classes. – Conventional, squirrel cage induction generator directly connected and with fixed pitch (SQIG). – Wound rotor, induction generator with external variable resistance and variable pitch (VRIG). – Doubly fed asynchronous generator with external variable resistance and variable pitch (DFIG). This part shows static relationships among active and reactive power, voltage drops and harmonics. In the second part, a dynamic study has been performed, focused on transient, connection and disconnection events.

LCL Filter Design of STATCOM using Genetic Algorithm Scheme for SCIG Based Microgrid Operation

In a microgrid static Compensator (STATCOM) is the most prominent inverter circuit for stabilizing the bidirectional power flow requirements of the system. This inverter circuit is the primary source of harmonics when the supply current feeds from the microgrid to the main grid. Improved control strategy and proper filter design may give solution to these issues and so, there is a huge scope of research in the field of the converter control techniques and filter designing for such microgrid based power system. The key objectives of this paper are (i) to develop an adequate current control scheme for adjusting real and reactive power fluctuations produced by load time to time, and (ii) to reduce the harmonic level of output characteristics in terms of real and reactive power flow and current frequency. For this, an approach is presented to estimate the filter design parameters for current controlled STATCOM connected to squirrel cage induction generator (SCIG) based microgrid. A nature-inspired optimization namely, genetic algorithm (GA), is implemented to estimate the most suitable parameters for the LCL filter. Results obtained through GA are validated with a conventional mathematical method in terms of real and reactive power flow through microgrid along with harmonic-based studies.

Performing Wind System with Rectifier with Near Sinusoidal Input Current

The RNSIC-1 (rectifier with near sinusoidal input currents converter), is the foundation of a wind generator system that is presented. The three inductances that make up a traditional RNSIC–1 converter are eliminated in the proposed arrangement, and the SCIG generator's leakage inductances fill their place. This is what makes it new. The wind system's role in the load currents is discussed. Lower power losses, smaller harmonic input currents, fewer EMI issues, excellent dependability, and cheaper costs are characteristics of the new wind system. This new wind system could be used for partial variable speed wind turbines (usually 70% to 100% synchronous speed) and lower hydro connector squirrel cage induction generators (SCIG).

Analysis and design of wind energy system based on nonlinear speed controller

This paper presents a control fuzzy robuste strategy for a squirrel cage Induction generator (SCIG)-based wind energy conversion system. Control strategies is presented along with the mathematical modeling of the employed configuration. The maximum power point extraction of the wind turbine is addressed along with the proposed strategy. The approach method is introduced to control the generator speed and regulate the flux. The wind system is then simulated in Matlab-Simulink and the developed model is used to illustrate the behavior of the system. The simulation results are presented and discussed at the end of this paper.

An intelligent wind turbine with yaw mechanism using machine learning to reduce high-cost sensors quantity

In this paper, with the assistance of some tools and a machine learning model, a smart wind turbine was formed that eliminates some expensive sensors and reduces sensor complexity. Squirrel cage induction generator (SCIG) and six rotor blades make up the proposed design, and depending on the wind's direction, the turbine itself can rotate the rotor hub to produce energy more effectively. Additionally, two stepper motors are coupled to the yaw mechanism with the aid of the rotor hub, and the entire controlling procedure will depend on the direction of the wind. The rotor hub must continuously revolve in the same direction as the wind to maximize wind energy utilization. Additionally, to correctly predict wind degrees, a machine learning model was deployed. Random forest regression was used to train and predict the wind direction. The model is deployed in Raspberry Pi, where the incoming sensor values are being stored. Using the generated data, machine learning model was trained and it can be concluded that the model can potentially replace some of the expensive sensors to reduce cost. The model can be used for similar weather conditions only based on machine learning model and fewer sensors.