Performance Analysis of Clarke Components Prediction via Derivative-Functions of Different Orders Applied in Digital Frequency Estimation in Electric Power Systems

Abstract

The electrical frequency is a parameter of great importance for the full operation of Electric Power Systems (EPS), influencing the operation of equipment and the quality of the energy supplied. This work presents an innovative method for digital frequency estimation in EPS. The estimation technique is based on the analysis of the voltage waveforms of the network, which are decomposed into their α and β components using the Clarke Transform. Future values of the α and β components are predicted through their respective different orders derivative functions. From these values, the network frequency is then estimated as a function of the angle resulting from the product between the actual Clarke complex signal and the one given by the α and β components prediction. The proposed method was tested for frequency signals with ramp, exponential and damped sinusoidal variations. The methodology was evaluated in terms of convergence time and minimum and maximum errors before and after convergence, showing that the proposed technique has great precision and robustness against the simulated situations.