The widespread diffusion of nonlinear power electronics devices in power systems has radically changed their operating scenario. Voltage and currents can be significantly distorted, and conventional linear models of power system components may be not accurate enough. Simplified Volterra models with quasi-sinusoidal excitation have been recently proposed, and they are particularly suitable to represent the behavior of power systems devices. In this paper, the simplified Volterra approach is applied to the frequency-domain modeling of a typical highly-nonlinear load: a full-bridge rectifier feeding an ohmic-capacitive load. Model accuracy has been evaluated by means of numerical simulations, and its performance has been compared with that achieved by a conventional Volterra model. Results highlight the excellent accuracy of the proposed model in spite of the relatively small set of coefficients to be identified. This feature is extremely important when models have to be employed in frequency-domain simulations of large networks.
Modeling and identification of a bridge rectifier under quasi-sinusoidal conditions
Faifer, Marco;Laurano, Christian;Ottoboni, Roberto;Toscani, Sergio;Zanoni, Michele
2018-01-01
Abstract
The widespread diffusion of nonlinear power electronics devices in power systems has radically changed their operating scenario. Voltage and currents can be significantly distorted, and conventional linear models of power system components may be not accurate enough. Simplified Volterra models with quasi-sinusoidal excitation have been recently proposed, and they are particularly suitable to represent the behavior of power systems devices. In this paper, the simplified Volterra approach is applied to the frequency-domain modeling of a typical highly-nonlinear load: a full-bridge rectifier feeding an ohmic-capacitive load. Model accuracy has been evaluated by means of numerical simulations, and its performance has been compared with that achieved by a conventional Volterra model. Results highlight the excellent accuracy of the proposed model in spite of the relatively small set of coefficients to be identified. This feature is extremely important when models have to be employed in frequency-domain simulations of large networks.File | Dimensione | Formato | |
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