Showing papers in "IEEE Transactions on Energy Conversion in 2003"
TL;DR: In this paper, the simulation results of a grid-connected wind driven doubly fed induction machine (DFIM) together with some real machine performance results are presented for operating conditions below and above synchronous speed, which are actually achieved by a double-sided PWM converter joining the machine rotor to the grid.
Abstract: This paper presents the simulation results of a grid-connected wind driven doubly fed induction machine (DFIM) together with some real machine performance results. The modeling of the machine considers operating conditions below and above synchronous speed, which are actually achieved by means of a double-sided PWM converter joining the machine rotor to the grid. In order to decouple the active and reactive powers generated by the machine, stator-flux-oriented vector control is applied. The wind generator mathematical model developed in this paper is used to show how such a control strategy offers the possibility of controlling the power factor of the energy to be generated.
800 citations
TL;DR: In this article, the authors focus on fundamental frequency simulations, also known as electromechanical transient simulations, where the network is represented as an impedance matrix and only the fundamental frequency component of voltages and currents is taken into account in order to reduce the computation time.
Abstract: Increasing numbers of wind turbines are being erected. In the near future, they may start to influence the dynamics of electrical power systems by interacting with conventional generation equipment and with loads. The impact of wind turbines on the dynamics of electrical power systems therefore becomes an important subject, studied by means of power system dynamics simulations. Various types of power system dynamics simulations exist and the approach depends on the aspect of power system dynamic behavior being investigated. In this paper, the focus is on fundamental frequency simulations, also known as electromechanical transient simulations. In this type of simulation, the network is represented as an impedance matrix and only the fundamental frequency component of voltages and currents is taken into account in order to reduce the computation time. This simulation approach is mainly used for voltage and angle stability investigations. Models of wind turbine generating systems that match the fundamental frequency simulation approach are presented and their responses are compared to measurements.
340 citations
TL;DR: Induction generators are increasingly being used in nonconventional energy systems such as wind, mini/micro-hydro, biogas, etc as mentioned in this paper, and the advantages of using an induction generator instead of synchronous generator are well known.
Abstract: Induction generators are increasingly being used in nonconventional energy systems such as wind, mini/micro-hydro, biogas, etc. The advantages of using an induction generator instead of synchronous generator are well known. Some of them are reduced unit cost and size, ruggedness, absence of separate DC source, ease of maintenance, self-protection against severe overloads and short circuits, etc. An attempt is made in this paper to present an exhaustive bibliography on the application of induction generators in nonconventional energy systems.
250 citations
TL;DR: The principles and criteria of the diagnosis process are surveyed, and the current research achievements to apply AI techniques in the diagnostic systems of electrical machines and drives are introduced.
Abstract: Condition monitoring leading to fault diagnosis and prediction of electrical machines and drives has recently become of importance. The topic has attracted researchers to work in during the past few years because of its great influence on the operational continuation of many industrial processes. Correct diagnosis and early detection of incipient faults result in fast unscheduled maintenance and short down time for the machine under consideration. It also avoids harmful, sometimes devastative, consequences and helps reduce financial loss. Reduction of the human experts involvement in the diagnosis process has gradually taken place upon the recent developments in the modern artificial intelligence (AI) tools. Artificial neural networks (ANNs), fuzzy and adaptive fuzzy systems, and expert systems are good candidates for the automation of the diagnostic procedures. This present work surveys the principles and criteria of the diagnosis process. It introduces the current research achievements to apply AI techniques in the diagnostic systems of electrical machines and drives.
193 citations
TL;DR: In this article, an analytical method of modeling permanent magnet (PM) motors is presented, which is based on the calculation of the air gap field density waveform at every time instant.
Abstract: This paper presents an analytical method of modeling permanent magnet (PM) motors. The model is dependent only on geometrical and materials data which makes it suitable for insertion into design programs, avoiding long finite element analysis (FEA) calculations. The modeling procedure is based on the calculation of the air gap field density waveform at every time instant. The waveform is the solution of the Laplacian/quasi-Poissonian field equations in polar coordinates in the air gap and takes into account slotting. The model allows the rated performance calculation but also such effects as cogging torque, ripple torque, back-EMF form prediction, some of which are neglected in commonly used analytical models.
182 citations
TL;DR: In this paper, the authors proposed a fuzzy approach based on the stator current Concordia patterns, which can be used for accurate stator fault diagnosis if the input data are processed in an advantageous way, which is the case of the Concordia pattern.
Abstract: This paper deals with the problem of detection and diagnosis of induction motor faults. Using the fuzzy logic strategy, a better understanding of heuristics underlying the motor faults detection and diagnosis process can be achieved. The proposed fuzzy approach is based on the stator current Concordia patterns. Induction motor stator currents are measured, recorded, and used for Concordia patterns computation under different operating conditions, particularly for different load levels. Experimental results are presented in terms of accuracy in the detection of motor faults and knowledge extraction feasibility. The preliminary results show that the proposed fuzzy approach can be used for accurate stator fault diagnosis if the input data are processed in an advantageous way, which is the case of the Concordia patterns.
179 citations
TL;DR: In this article, a parallel stator resistance and rotor speed identification algorithm is developed for the rotor flux-based model reference adaptive system (MRAS) type of the speed estimator in conjunction with a rotor flux oriented control scheme.
Abstract: Accurate knowledge of stator resistance is of utmost importance for correct operation of a number of speed sensorless induction motor control schemes in the low speed region. Since stator resistance inevitably varies with operating conditions, stable and accurate operation at near-zero speed requires an appropriate online identification algorithm for the stator resistance. The paper proposes such an identification algorithm, which is developed for the rotor flux-based model reference adaptive system (MRAS) type of the speed estimator in conjunction with a rotor flux oriented control scheme. In this speed estimation method, only one degree of freedom (out of the two available) is utilized for speed estimation. It is proposed to utilize the second available degree of freedom as a means for adapting the stator resistance online. The parallel stator resistance and rotor speed identification algorithm is developed in a systematic manner, using Popov's hyperstability theory. It increases the complexity of the overall control system insignificantly and enables correct speed estimation and stable drive operation at near-zero speeds. The proposed speed estimator with parallel stator resistance identification is at first verified by simulation. Extensive experimentation is conducted next at low speeds of rotation and successful stator resistance identification is achieved down to 0.5-Hz frequency of rotation.
174 citations
TL;DR: Two controllers are proposed that determine the optimal turn-on and turn-off angles, respectively, for improving motor efficiency and torque ripple in current controlled switched reluctance motor drives.
Abstract: The problem of performance optimization in current controlled switched reluctance motor (SRM) drives is investigated. Two controllers are proposed that determine the optimal turn-on and turn-off angles, respectively, for improving motor efficiency and torque ripple. The suggested controllers are simple, do not affect the complexity of the drive, and are easily implemented since the knowledge of torque-angle-current characteristics or magnetization curves is not required. The proposed control scheme is demonstrated on a prototype experimental system.
130 citations
TL;DR: In this article, the relative air-gap-specific permeance distribution function by Schwarz-Christoffel transformation, considering the effect of slotting, is derived, and the instantaneous electromagnetic torque is computed, which underpins the quantitative analysis of torque ripple and the pulsation induced by commutation.
Abstract: This paper derives the relative air-gap-specific permeance distribution function by Schwarz-Christoffel transformation, considering the effect of slotting. Neglecting the iron saturation, and employing the analytical algorithm for partial differential equations, efficient and effective analytical calculations of no-load air-gap magnetic field distribution, armature field distribution, and phase electromotive force (EMF), are demonstrated, considering the stator slots. Subsequently, based on the main circuit topology of a brushless DC motor (BLDCM), the field-circuit coupling model is constructed for the motor, and then the phase current waveforms and load air-gap magnetic field distribution at any time are determined. Consequently, the instantaneous electromagnetic torque is computed, which underpins the quantitative analysis of torque ripple and the pulsation induced by commutation. Hence, the present work paves the way to precise prediction of the motor's performance and acoustic noise. It is a powerful tool for the design of surface permanent magnet brushless DC motors.
123 citations
TL;DR: In this paper, a new detection method based on wavelet ridge is presented for the detection of cage motor broken rotor bars, aiming at the motor's starting period during which the motor accelerates progressively and CFCFR approaches the power frequency gradually in frequency spectrum.
Abstract: Detection of cage motor broken rotor bars has long been an important but difficult job in the detection area of motor faults. The characteristic frequency component of faulted rotor (CFCFR) is very close to the power frequency component but by far less in amplitude, which brings about great difficulty for accurate detection. A new detection method based on wavelet ridge is presented in this paper. Aiming at the motor's starting period during which the motor accelerates progressively and CFCFR approaches the power frequency gradually in frequency spectrum, the wavelet ridge-based method is adopted to analyze this transient procedure and the CFCFR is extracted. The influence of power frequency can be effectively eliminated, and detection accuracy can be greatly improved by using the approach presented in this paper. Also, this is indeed a novel but excellent approach for the detection domain of cage induction motor broken rotor bars.
118 citations
TL;DR: In this article, a theoretical framework that unifies passivity and sliding mode techniques is proposed for the control of the output power of a solar/wind stand-alone system, which regulates the generation of the wind subsystem in order to satisfy the photovoltaic generation subsystem, the load and battery charge power demand.
Abstract: This paper deals with the control of the output power of a solar/wind stand-alone system. The control system regulates the generation of the wind subsystem in order to satisfy, jointly with the photovoltaic generation subsystem, the load and battery charge power demand. The controller is designed using a theoretical framework that unifies passivity and sliding mode techniques. The resultant control law does not need wind measurement and only relies on rotational speed and current measurements. An analysis of the acceleration estimate error is carried out and a countermeasure to compensate its effects is proposed. Finally, the performance of the controller is assessed through computer simulation, using a comprehensive nonlinear model of the plant.
TL;DR: In this paper, the issue of appropriate test conditions with regard to reactive power injection to the grid is discussed and the stabilizing impact of rotating machines and resonant circuits is evaluated in detail.
Abstract: A major safety issue in grid-connected photovoltaics is to avoid nonintentional operation in islanding mode when the grid is being tripped. Worst-case conditions under which islanding can occur are specified analytically. The circuit that is commonly used for testing is described. The issue of appropriate test conditions with regard to reactive-power injection to the grid is discussed and the stabilizing impact of rotating machines and resonant circuits is evaluated in detail. Islanding test results for small inverters are presented. They confirm that very simple islanding protection methods that are commonly used, are likely to fail, if inverters are loaded with considerable capacitance. The obtained results support the assessment of the islanding protection function. They emphasize important points when defining new certification procedures for upcoming guidelines and standards.
TL;DR: In this paper, the authors presented theoretical, simulation, and experimental study of the brushless doubly fed twin stator induction generator (BDFTSIG) dynamics under vector control based on the orientation on the power machine stator flux.
Abstract: This paper presents theoretical, simulation, and experimental study of the brushless doubly fed twin stator induction generator (BDFTSIG) dynamics under vector control based on the orientation on the power machine stator flux. A complex transfer function is derived which links the control current and power winding current space vectors in the field coordinates. Based on this result, the transient response of the BDFTSIG to step changes in the control current is examined theoretically. The oscillatory transients are explained in detail and linked to control flux transients triggered whenever operation point of the generator is changed. Furthermore, BDFTSIG operation with closed loop control of the power machine active and reactive powers is examined theoretically and experimentally. It is shown that in the closed loop operation, the system damping may be reduced so that the PI controller gains must be properly selected to achieve a good transient response.
TL;DR: In this paper, an adaptive minimum variance controller is developed for a fuel cell-microturbine hybrid power plant, where the parameters of the adaptive controller are obtained directly through their estimation in an appropriately defined plant model.
Abstract: The composition of natural gas may vary significantly, and load power varies randomly. Traditional control design approaches consider a fixed operating point in the hope that the resulting controller is robust enough to stabilize the system for different operating conditions. On the other hand, adaptive control incorporates the time-varying dynamical properties of the model and considers the disturbances acting at the fuel cell-microturbine hybrid power plant. It may be possible to identify the parameters of the adaptive controller. This scheme is called direct adaptive control, because we are going to obtain directly the required controller parameters through their estimation in an appropriately redefined plant model. An adaptive minimum variance controller is developed in this paper.
TL;DR: In this article, a more precise model for computation of three-phase squirrel cage induction machine inductances under different eccentric conditions is presented, and the evaluated inductances are compared to those calculated using different approximate geometrical models.
Abstract: This paper presents a more precise model for computation of three-phase squirrel cage induction machine inductances under different eccentric conditions. Generally, available techniques are based on the winding function theory and simplification and geometrical approximation of unsymmetrical models of the motor under mixed eccentricities. This paper determines a precise geometrical model under the mixed eccentricity conditions and evaluates the inductances. Meanwhile, the evaluated inductances are compared to those calculated using different approximate geometrical models and the best approximation is recommended for a geometrical modeling of induction motor under eccentricity conditions.
TL;DR: In this article, a two-layer recurrent neural network was used to estimate the damper currents from phase voltage, phase current, rotor position, and rotor speed, and then, the Damper parameters can be identified using maximum likelihood estimation techniques.
Abstract: Phase windings of switched reluctance machines are modeled by a nonlinear inductance and a resistance that can be estimated from standstill test data. During online operation, the model structures and parameters of SRMs may differ from the standstill ones because of saturation and losses, especially at high current. To model this effect, a damper winding is added into the model structure. This paper proposes an application of artificial neural network to identify the nonlinear model of SRMs from operating data. A two-layer recurrent neural network has been adopted here to estimate the damper currents from phase voltage, phase current, rotor position, and rotor speed. Then, the damper parameters can be identified using maximum likelihood estimation techniques. Finally, the new model and parameters are validated from operating data.
TL;DR: In this article, a novel technique to estimate and model parameters of a 460-MVA large steam turbine generator from operating data is presented, where data from small excitation disturbances are used to estimate linear model armature circuit and field winding parameters of the machine and for each set of steady state operating data, saturable inductances are identified and modeled using nonlinear mapping functions-based estimators.
Abstract: A novel technique to estimate and model parameters of a 460-MVA large steam turbine generator from operating data is presented First, data from small excitation disturbances are used to estimate linear model armature circuit and field winding parameters of the machine Subsequently, for each set of steady state operating data, saturable inductances L/sub ds/ and L/sub qs/ are identified and modeled using nonlinear mapping functions-based estimators Using the estimates of the armature circuit parameters, for each set of disturbance data collected at different operating conditions, the rotor body parameters of the generator are estimated using an output error method (OEM) The developed nonlinear models are validated with measurements not used in the estimation procedure
TL;DR: In this paper, a diagonally recurrent neural network (DRNN) is proposed for rotor position estimation on a permanent-magnet synchronous motor (PMSM) drive.
Abstract: Due to the drawbacks associated with the use of rotor position sensors in permanent-magnet synchronous motor (PMSM) drives, there has been significant interest in the so-called rotor position sensorless drive. Rotor position sensorless control of the PMSM typically requires knowledge of the PMSM structure and parameters, which in some situations are not readily available or may be difficult to obtain. Due to this limitation, an alternative approach to rotor position sensorless control of the PMSM using a diagonally recurrent neural network (DRNN) is considered. The DRNN, which captures the dynamic behavior of a system, requires fewer neurons and converges quickly compared to feedforward and fully recurrent neural networks. This makes the DRNN an ideal choice for implementation in a real-time PMSM drive system. A DRNN-based neural observer, whose architecture is based on a successful model-based approach, is designed to perform the rotor position estimation on the PMSM. The advantages of this approach are discussed and experimental results of the proposed system are presented.
TL;DR: In this paper, a three-phase permanent-magnet synchronous generator for automotive applications is designed using analytical algorithms, which is validated by comparing the analysis results using the model and those based on finite element analysis under no-load and full-load conditions for saturation considerations.
Abstract: The new 42-V automotive electric system comes up with new requirements for alternator design. A three-phase permanent-magnet (PM) synchronous generator for automotive applications is designed using analytical algorithms. The electromagnetic (EM) field for a certain design is analyzed based on a proposed equivalent magnetic circuit model. The proposed model is validated by comparing the analysis results using the model and those based on finite-element analysis under no-load and full-load conditions for saturation considerations. The analysis results demonstrate the effectiveness of the proposed machine design methodology.
TL;DR: A theoretical analysis is presented where a maximum torque to current condition that takes into account and compensates the effect of magnetic saturation in the synchronous reluctance motor drive performance is derived.
Abstract: This paper investigates the influence of magnetic saturation in maximum torque to current vector controlled synchronous reluctance motor drives. A theoretical analysis is presented where a maximum torque to current condition that takes into account and compensates the effect of magnetic saturation in the synchronous reluctance motor drive performance is derived. The proposed controller does not affect the dynamic performance of the drive and is easily implemented, since an experimental procedure is used to determine its parameter. Therefore, the knowledge of the exact motor model is not required. Several experimental results are presented to validate the effectiveness of the proposed controlled scheme.
TL;DR: In this paper, a numerical method is proposed to calculate the stator current sidebands, which can be used to predict the voltage fluctuation at the system busbar, and it is shown that the pulsating torque associated with the rotor harmonics can induce speed ripple depending on the inertia.
Abstract: This paper is concerned with the low-frequency harmonics which originate from the rotor inverter of a doubly-fed induction generator (DFIG). By including the mechanical speed response, it expands the transformer approach previously taken to analyze the harmonic transfer in the machine. A numerical method is proposed to calculate the stator current sidebands, which can be used to predict the voltage fluctuation at the system busbar. It is shown that the pulsating torque associated with the rotor harmonics can induce speed ripple depending on the inertia, causing a significant change in the stator current spectrum. Experiment and simulation verify the analysis and the proposed calculation method.
TL;DR: In this article, a sensorless control system for induction motors, realized on a fixed-point digital signal processor (DSP) and field programmable gate arrays (FPGAs), is presented.
Abstract: This paper presents a sensorless control system for induction motors, which is realized on a fixed-point digital signal processor (DSP) and field programmable gate arrays (FPGAs). An observer system has been developed for estimation of speed and the other state variables. The proposed observer system is verified for different conditions of motor operation. Experimental results for the control system fed by voltage source inverter controlled using predictive current controller are presented.
TL;DR: In this paper, a new analytic formulation is presented that uses flux-linkage as the state variable and in which mutual coupling between phases is also represented, which results in a better fit with measured laboratory data, using the proposed approach, the simulated machine performance for a 12/8 SR motor is shown to compare favorably with experimental results measured in the laboratory.
Abstract: In analytical modeling of the switched reluctance (SR) machine, current is often chosen as the state variable, although flux-linkage provides a simpler and more efficient choice. Furthermore, it is typically the case that mutual inductance is neglected. In this paper, a new analytic formulation is presented that uses flux-linkage as the state variable and in which mutual coupling between phases is also represented. In addition, the paper presents an approach to determining the parameters of the flux-linkage curves of the machine that result in a better fit with measured laboratory data. Using the proposed approach, the simulated machine performance for a 12/8 SR motor is shown to compare favorably with experimental results measured in the laboratory.
TL;DR: In this article, an electrical drive model, implementing a doubly-fed differential drive (DFDD) is presented, and active power requirements for the machines and the inverters over the DFDD speed range are derived.
Abstract: In this paper, an electrical drive model, implementing a doubly-fed differential drive (DFDD) is presented. Two doubly-fed induction machines, having the corresponding rotor phases connected, constitutes the differential wheel drive. Two inverters are supplying the machine stators with three-phase power of variable magnitude and frequency. The power required to supply the inverters may be delivered from a constant voltage DC source like a battery. Active power requirements for the machines and the inverters over the DFDD speed range may be obtained. Reactive power requirements for minimum copper loss may be derived as well. The DFDD may provide propulsion to electrical vehicles.
TL;DR: In this article, an intelligent method of commutation tuning is developed to improve the torque generating capability of a switched reluctance motor (SRM), where the minimization of the motor drawn line current is employed as a performance index to equivalently yield maximum torque per ampere (TPA).
Abstract: Since the winding current and inductance profiles of a switched reluctance motor (SRM) are far from ideal, its torque generating characteristics are quite ambiguous and difficult to optimize quantitatively. In this paper, the intelligent commutation tuning control to improve the torque generating performance of an SRM is presented. First, the effect of the commutation instant on the torque characteristics of a singly excited SRM is observed. Then accordingly, an intelligent method of commutation tuning is developed to improve the torque generating capability. In making the tuning, the minimization of the motor drawn line current is employed as a performance index to equivalently yield maximum torque per ampere (TPA). Finally, the circuit implementation of the developed tuning scheme is carried out. The appropriate commutation makes the motor draw minimum current under any load condition. It follows that the motor conversion efficiency is also improved. In addition, owing to the increased torque generating capability, the tracking and regulation speed control performances are also improved. Some experimental results are provided to demonstrate the effectiveness of the proposed control scheme.
TL;DR: In this article, an algorithm for optimum dynamic distribution of the available maximum inverter current into the flux-producing and the torque-producing stator current components is developed in order to improve response in these transients.
Abstract: Optimal efficiency control of induction motor drives implies operation at reduced flux levels with light loads. Two problems in light load operation are a large speed drop after sudden load torque increase and slow acceleration. In order to improve response in these transients, an algorithm for optimum dynamic distribution of the available maximum inverter current into the flux-producing and the torque-producing stator current components is developed in this paper. The proposed algorithm accounts for the main flux saturation effect in the machine and the dynamics of the flux variation. Its performance is illustrated by means of simulation and experimental results. Superiority of the developed algorithm over some of the existing methods is proved by comparing the speed drops, which result after sudden load torque increase during operation at light load, and by examining an acceleration transient under light load condition.
TL;DR: In this paper, a new comprehensive method for the calculation of inductance coefficients of squirrel cage induction machine based on combined winding function approach (WFA) and magnetic equivalent circuit (MEC) is presented.
Abstract: In this paper, a new comprehensive method for the calculation of inductance coefficients of squirrel cage induction machine based on combined winding function approach (WFA) and magnetic equivalent circuit (MEC) is presented. By taking into account machine geometry, rotor skewing, stator and rotor slots effects and type of windings connection, this method is able to model most of the important features of an induction machine. The effects of each machine parameter on the inductance coefficients are verified. Also, effects of several rotor asymmetries on these inductances are shown. Simulation results are verified by more elaborate nonlinear finite element model and finally with experimental results.
TL;DR: In this paper, an improved self-organizing map (SOM) with improved clustering indications is proposed for partial discharge (PD) classification of turbine generator analyzer data.
Abstract: Partial discharge (PD) classification is a powerful way to predict insulation problems of the windings of rotating machinery. While online PD tests have been carried out for over 40 years, effective diagnostic methods are still under development. In this paper, a practical diagnostic method is proposed based on an improved self-organizing map (SOM) with improved clustering indications. Three feature extraction methods are employed for the SOM implementation, including Weibull analysis, statistical operators, and fractal parameters. Experimental PD data of industrial model bars are used to validate the efficiency of using SOM for PD classification. The method is applied to investigate the turbine generator analyzer (TGA) data obtained from a power plant of British Nuclear Fuels Ltd. Diagnostic results are included to demonstrate that the relationship between the new PD measurement and historical data can be visualized and more confidential diagnostic information can be provided, especially when small-size database, new class of data, and doubtful measurements are involved in a practical environment.
TL;DR: The requirement for exact knowledge of the system dynamics, full state measurement, as well as other difficulties associated with feedback linearizing control for power systems are avoided in this approach.
Abstract: We present an adaptive feedback linearizing control scheme for excitation control and power system stabilization. The power system is a synchronous generator which is first modeled as an input-output nonlinear discrete-time system approximated by two neural networks. Then, the controller is synthesized to adaptively compute an appropriate feedback linearizing control law at each sampling instant using estimates provided by the neural system model. This formulation simplifies the problem to that of designing a linear pole-placement controller which is itself not a neural network but is adaptive in the sense that the neural estimator adapts itself online. Additionally, the requirement for exact knowledge of the system dynamics, full state measurement, as well as other difficulties associated with feedback linearizing control for power systems are avoided in this approach. Simulations demonstrate its application to a high-order single-machine system under various conditions.
TL;DR: In this article, a new form of tubular induction motor, in which the motion of the rotor conductor is along a helical path, is described, and an appropriate multi-layer analysis using cylindrical geometry is presented.
Abstract: The paper describes a new form of tubular induction motor, in which the motion of the rotor conductor is along a helical path. The winding arrangement described may include multi-polar system circumferentially and axially. The excitation produced by such winding is a helically travelling wave. An appropriate multi-layer analysis using cylindrical geometry is presented. Experimental and theoretical results are given and they show good correlation.