Application of wavelets and Prony method for disturbance detection in fixed speed wind farms

Abstract Voltage dips and transients are the most commonly encountered power quality disturbances in wind farms. Signal parameters estimation is an important prerequisite for power quality enhancement and for improving the fault-ride capability of wind farms and consequently, the voltage stability of the whole network. This paper examines the application of advanced signal processing methodologies such as the Prony method and wavelets for disturbance detection in wind farms. Both methodologies have been effectively tested with different disturbances simulated in a dynamic power network with a large amount of wind energy and with data signals measured at wind turbine terminals.

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