Influence of saturation on estimated synchronous machine parametersin standstill frequency response tests

In this paper the measurement results of a series of standstill frequency response tests, performed at different magnetization levels, are discussed. For each data set an individual model is estimated, which allows the variation of the different parameters to be seen as a function of the saturation. Further, an estimator is presented which uses the different data sets to estimate one global model, including the field to armature turns ratio. Finally the expected error level of a more traditional saturated synchronous machine model is studied     

On-line synchronous machine parameter estimation from smalldisturbance operating data

This paper presents a step-by-step system identification approach to estimate the parameters of a three-phase salient-pole synchronous machine rated at 5 kVA from online small disturbance responses. The machine equivalent circuit model linear parameters and the nonlinear saturated parameters are estimated. The estimation is performed using the maximum likelihood algorithm. Simulation studies based on the online measured small and large dynamic disturbances are performed to validate the accuracy of the identified machine model including the saturation     

Maximum likelihood estimation of synchronous machine parametersfrom standstill time response data

This paper presents a systematic approach for identification of a three-phase salient-pole synchronous machine rated at 5 kVA from standstill time-domain data. Machine time constant models and the equivalent circuit models are identified and their parameters are estimated. The initialization of the estimated parameters is achieved by the Laplace transformation of the recorded standstill time-response data and the derivation of the well-known operational inductances. The estimation is performed using the Maximum Likelihood algorithm. Based on the best estimated equivalent circuit models, simulation studies using the measured on-line dynamic responses are performed to validate the identified machine models     

Neural network based modeling of round rotor synchronous generatorrotor body parameters from operating data

It is generally accepted that in order to account for the effect of eddy currents in the solid rotor-iron of a round-rotor synchronous machine, two or more fictitious rotor-circuits are to be used in each axis of the d- and q-axis equivalent circuit representations of the machine model. This paper presents a novel technique to estimate the parameters of these rotor-circuits (hereinafter referred to as rotor body parameters) from measurements collected online at several operating conditions. The effects of generator saturation, rotor position and loading are included in the estimation process. Tests conducted on a round-rotor synchronous generator reveal that certain rotor-body parameters are nonlinear functions of generator operating condition. A novel artificial neural network (ANN) based technique is used to map variables representative of generator operating condition to each parameter being modeled. The developed ANN models are validated with measurements not used in the modeling process     

Time-domain identification of synchronous machine parameters fromsimple standstill tests

A set of standstill measurements that allow time-domain identification of linear model parameters for direct and quadrature axes of a synchronous machine is proposed. The advantages of this method over conventional standstill frequency response testing include the simplicity of test equipment, the higher current levels achieved, the speed with which the measurements can be obtained, and the fact that the models are obtained directly in parametric form (in per-unit or measured units). The proposed method is illustrated by results measured on a 3 kVA, 220 V microalternator     

Decoupled control of rotor torque and rotor electric power delivered in a salient-pole, synchronous machine

A drive system with a control algorithm that provides independent control of rotor torque and rotor electric power is described in this paper. One electromechanical machine is used for two purposes, viz., firstly to provide electromagnetic torque to rotate a rotor mounted load and secondly to provide electric power to equipment mounted on the rotor. The technique eliminates the need for slip rings. Simulation and practical results verifying the analysis are given. The system has applications such as rotational antennas and turret systems.     

Identification of synchronous machine parameters using loadrejection test data

This work shows a computational methodology for the determination of synchronous machines parameters using load rejection test data. By machine modeling one can obtain the quadrature parameters through a load rejection under an arbitrary reference, reducing the present difficulties. The proposed method is applied to a real machine     

Identification of synchronous machine linear parameters fromstandstill step voltage input data

This paper presents the results of a time-domain identification procedure to estimate the linear parameters of a 15 kVA salient-pole synchronous machine at standstill. A step voltage input test is performed, and the parameters of the time constant models and equivalent circuit models are estimated. The maximum likelihood algorithm is used for the estimation, and the best-fit model is selected from a set of increasing order models. The initialization values for the parameters to be estimated are determined from the operational inductances derived directly from the measured time domain data. The simulated equivalent circuit model response is validated against the measured standstill time domain and frequency domain data. In addition, simulation of the model response to an on-line small disturbance test is compared to the measured dynamic response     

A `three transfer functions' approach for the standstill frequencyresponse test of synchronous machines

A three transfer functions approach for the standstill frequency response (SSFR) test of synchronous machines is proposed. Network theory is employed for the explanation of the three-function approach. The three-function and two-function approaches, as well as the one-function approach, are compared. The verification of the approach is obtained through simulations and an application to an SSFR test on a 3 kVA laboratory microalternator. The accuracy of the determined d-axis model parameters, particularly of the rotor circuits, is improved by the use of the suggested third transfer function (L _afo(s)) together with the two transfer functions ( L_d(s) and G(s)). This requires that the measurements of the three transfer functions be taken in the SSFR test and be involved in the d-axis model fitting instead of the common practice involving only L_d(s) and G(s)     

A fuzzy logic based stabilizer for a synchronous machine

The application of a fuzzy logic controller to improve the stability of electric power systems is presented. The stabilizing signal is computed using the standard fuzzy membership function depending on the speed acceleration state of the generator in the phase plane. The required measurement is the speed deviation over two samples. The effectiveness of the proposed stabilizer is demonstrated by simulation studies for different operating conditions and disturbances     

Identification of high-order synchronous generator models from SSFRtest data

This paper presents a direct maximum-likelihood estimation procedure to identify the synchronous machine models based on the standstill frequency response (SSFR) test data. The method presented in this study is the first and only algorithm utilizing all available SSFR test data under both shorted and open field circuit conditions to establish a unique equivalent circuit model by maximizing the conditional probability density function of the error residuals. The method is applied to the modeling of two well-known generators, namely the Rockport and Nanticoke generators, using the measured SSFR test data. The results of the study show that by incorporating both the open and short-circuit SSFR data in the modeling process, the SSFR characteristics of the two generators can be accurately represented by the established high order synchronous models up to 1 kHz. The identified synchronous machine model consists of five amortisseur windings on each axis. In addition, an eddy-current effect impedance is included in the d-axis model for representing the increased influence of rotor eddy current under the open-circuit test condition     

Estimation of a global synchronous machine model using a multiple-input multiple-output estimator

In this paper, the measurement results of a series of standstill frequency-response (SSFR) tests, performed at different magnetization levels, are discussed. For each data set, an individual d-axis model is estimated, which allows seeing the variation of the different parameters as a function of saturation. A global estimator is presented which uses the different data sets to estimate one global model, including the field-to-armature turns ratio. The global estimator is based on an impedance matrix representation of the synchronous machine. This global estimator assumes that only the d-axis main inductance is saturation dependent. The individual estimated models justify this assumption. Finally, the relative additional error of the global estimated d-axis equivalent circuit with the individual estimated ones is studied. The measurement results discussed in this paper are obtained on a four-pole 130-kVA synchronous machine.     

Identification of synchronous machine parameters using a multipleinput multiple output approach

This paper presents an alternative method for the identification of the d-axis parameters of a synchronous machine. The first part of the paper describes a multiple input multiple output (MIMO) broadband excitation and measurement method which is more time efficient than the standard standstill frequency response (SSFR) method. The second part describes a MIMO frequency domain identification procedure which estimates the d-axis parameters in 3 steps. The proposed identification procedure is self starting. It does not require starting values or other prior information. The measurement method and the identification procedure are tested on a 20 kVA salient pole synchronous machine     

Magnetic saturation effects on the control of a synchronous reluctance machine

Experimental results on the magnetic saturation effects on the control of a small synchronous reluctance machine (600 W) are presented in this paper. A new model of the machine, including saturation effects and cross magnetization is first developed. An approach based on total and mutual inductances is followed instead of the traditional approach through magnetizing and leakage inductances. All of the electrical and mechanical parameters measurements required for the simulations are given. A rotor-oriented vector control of the synchronous reluctance machine is achieved with a digital-signal-processor (DSP) board (TMS320C31) and experimental results are presented. When the magnetic circuit is saturated, the simulation with the developed model shows good, accurate results when compared to the experimental ones.     

Transient thermal characteristics of induction machine rotor cage

Thermal analysis of an induction machine cage rotor during stall conditions forms an important part of design calculations. The study of rotor circuit thermal behavior is also useful to identify causes of failure in large cage rotor induction machines. The authors present a three-dimensional finite-element-based electrical-thermal analysis of the bar and end-ring area of a large rotor to examine its thermal characteristics during a stall. Details of temperature variations at key locations in the bar and end ring are provided. The calculations are compared to experimental results, and the advantages and limitations of the solution technique for rotor analysis are discussed     

On-line estimation of variable parameters of synchronous machinesusing a novel adaptive algorithm-principles and procedures

A novel adaptive algorithm is presented for the online estimation of the variable parameters of a synchronous machine (SM) as a function of the operating conditions. The concept of a synthesized information factor (SIF) is proposed as the core of the novel adaptive algorithm. For a continuous process, the SIF optimally combines information from the past with that at the present. Adaptive principles based on the SIF are discussed and adaptive estimation procedures are developed. Computer simulation results are given to highlight the advantages of the novel adaptive algorithm over conventional least mean square and recurrence least square algorithms     

Determination of synchronous machine parameters using networksynthesis techniques

This paper deals with the problem of the determination of synchronous machine parameters starting from two-port information. Network synthesis techniques are used to show that no unique solution can be found for models containing more than one damper winding. Only a limited number of parameters can be determined in a unique way from two-port information     

On-line estimation of synchronous Generator parameters using a damper current observer and a graphic user interface

This paper presents a method to identify synchronous generator parameters from on-line data measured at the terminals of the machine. An observer for estimation of synchronous generator damper currents is designed and implemented. The observer-estimator is used in a Graphic User Interface (GUI) application. Possible internal machine fault conditions can be detected and remedial action can be applied. Noise filtering and bad data detection and rejection are implemented to increase the reliability of the estimates. Saturation of the synchronous generator inductances is also considered. Secondary objectives include calculation of the error characteristics of the estimation, development of an index of confidence, study of the observability of generator parameters, and evaluation of alternative GUI features.     

Iteratively reweighted least squares for maximum likelihoodidentification of synchronous machine parameters from on-line tests

This paper presents a new approach for the statistical identification of synchronous-machine parameters from on-line test data that were recorded on a 202 MVA hydro-generator at Hydro-Quebec's La Grande 3 generating station. Data processing is performed to remove harmonics in noise-corrupted measurements. The time-domain parameter identification is carried out by means of our proposed maximum-likelihood estimation method, also called the iteratively reweighted least-squares algorithm. A comparison of the results with the ordinary weighted least-squares estimation, which is equivalent to the maximum-likelihood estimation only when the noise is white, shows the superiority of the proposed method. This procedure appears more convenient than previous schemes for parameter identification of the synchronous-machine linear equivalent-circuits, especially when the noise statistics are poorly known     

Analysis of leakage flux distributions in a salient-pole synchronous machine using finite elements

It is important to understand the relationship between iron core configurations and leakage flux distributions to get a better design of synchronous machines. This paper presents a method for calculating the steadyand transient-state leakage flux distributions in salient-pole synchronous machines. The method provides information on leakage flux distributions that cannot be obtained by terminal quantities. The method analyzes the leakage inductances that properly represent the corresponding leakage fluxes. They are calculated using the gap flux distributions by finite elements with magnetic saturation. The calculated leakage inductances of a synchronous machine under various loads are also shown and the relationship between the inductances and magnetic saturation is discussed.