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This article presents the optimal design of a permanent magnet synchronous generator (PMSG). A finite element (FE) model is used to construct a metamodel, which afterward is utilized to define the objective function that models the PMSG. Kriging modeling is employed along with the design of experiments based on Latin hypercube sampling. The utilization of a surrogate model allows to speed up the optimization process while keeping the accuracy since they are developed from the FE analysis. On the other hand, it has been reported that the non-sorting genetic algorithm (NSGA) III is better than NSGA-II because it can solve multi- and many-objective optimization problems. This article demonstrates by numerical experiments that NSGA-III can be successfully used in the optimal design of PMSG with three objectives. [ABSTRACT FROM AUTHOR]

This paper presents the application of the time-domain chirp signal excitation to obtain the dq axis parameters of a synchronous machine model. The latest advances on computation tools have allowed the research of existing and novel experimental procedures for the parameter estimation of synchronous-generator models. Hence, different experimental methodologies to reduce the amount of testing time and to obtain more accurate model parameters have been proposed. The chirp is a linear swept-frequency sinusoidal signal that allows exciting the generator over a specified frequency bandwidth. This excitation is applied to the dq axis positions while the generator is at standstill. The estimation of the fundamental parameters is made by using a hybrid optimization algorithm composed by a genetic and a quasi-Newton algorithm. The proposed test has the advantage of requiring a low testing time. The set of estimated parameters was validated using test data of a sudden three-phase short-circuit fault. A 7 kVA, 220 V, 60 Hz, 1800 r/min, four salient-pole synchronous machine was used to evaluate the proposed estimation approach. [ABSTRACT FROM AUTHOR]

This paper presents the parameter estimation of a synchronous generator model based on the Gaussian Modulated Sinusoidal Pulse (GMSP). A 2D Finite Element (FE) model is used to evaluate the proposed signal in the estimation of the equivalent-circuit parameters of the generator. The presented methodology is based on the application of a FE model to simulate a standstill test. The FE model is validated against GMSP experimental results whilst the generator is at standstill. Afterwards, the FE simulation results are used to estimate the equivalent circuit parameters using a genetic algorithm. Finally, the estimated parameters are validated by comparing the simulation results against experimental data of a sudden three-phase short-circuit fault. A synchronous generator of a 7 kVA, 220V, 60 Hz, 1800 rpm, four-pole was employed for validating the estimated model parameters. [ABSTRACT FROM AUTHOR]

The parameter estimation of a salient-pole synchronous generator using the DC decay test at standstill is presented in this article. A dedicated experimental setup for this test was constructed, and it consists of a Labview program, a data acquisition system, sensors, and a mercury relay. The parameter estimation is performed using the stator and field current responses from the d-axis test, while for the q-axis, the stator current response is used. The two-axis theory is used to model the generator and, hence, equivalent circuits are used to represent it. The genetic and Gauss-Newton algorithms are employed in the estimation process of the fundamental model parameters, where data from the standstill DC decay experiment are used. The estimated parameters correspond to a low-level excitation perturbation, and to see their validity under a large disturbance, the sudden three-phase short-circuit fault was chosen. It is found that a model with the DC decay based parameters can predict with good accuracy the sudden short-circuit fault. The experiments are made on a 7-kVA, 220-V, 1800-rpm, 60-Hz synchronous generator. [ABSTRACT FROM AUTHOR]

Parameter estimation of synchronous generators has been a topic of interest of many investigators for several decades. Different ratings of synchronous machines have been used, and they vary from fractional to hundreds of megawatts. Several time-domain tests have been proposed, along with their implementation methodology, over the years. Those tests have had different impacts on the synchronous machine; some of them are applied when the machine is at a standstill, while others are applied when the machine is online. This paper deals with the application of a novel standstill time-domain test, which is based on the application of a sine cardinal perturbation, for estimating the parameters of the electrical d– q-axis equivalent circuits of a synchronous generator. The set of fundamental parameters for a 7-kVA 1800-r/min 60-Hz salient-pole wye-connected synchronous generator is obtained using a genetic algorithm, and the resulting model is validated against a sudden three-phase short-circuit test. [ABSTRACT FROM AUTHOR]

Integrating finite elements (FEs) into the design procedure of electromagnetic devices has always been a challenge for researchers and design engineering community. This paper presents the application of a hybrid method that involves the application of a conventional design methodology commonly employed by transformer manufacturers and 2-D FEs. The optimization is carried out using a genetic algorithm (GA) which allows finding the global minimum and then a deterministic algorithm is used to find the final solution. The methodology is illustrated in the design of a 1500-kVA, 13.2/0.22-kV, 60-Hz, delta-wye oil-filled distribution transformer. It is demonstrated that computation time can be reduced by using the design proposal and at the same time the FE is kept in the design process. [ABSTRACT FROM AUTHOR]