In this paper, an algorithm that monitors the power system to detect and classify power quality events in real time is presented. The algorithm is able to detect events caused by waveform distortions and variations of the RMS values of the voltage. Detection of the RMS events is done by comparing the RMS values with certain thresholds, while detection of waveform distortions is made using an algorithm based on multiharmonic leasts-squares fitting.
An implemented impedance measuring instrument is described in this paper. The device uses a dsPIC (Digital Signal Peripheral Interface Controller) as a processing unit, and a DDS (Direct Digital Synthesizer) to stimulate the measurement circuit composed by the reference impedance and the unknown impedance. The voltages across the impedances are amplified by programmable gain instrumentation amplifiers and then digitized by analog to digital converters. The impedance is measured by applying a seven-parameter sine-fitting algorithm to estimate the sine signal parameters. The dsPIC communicates through RS-232 or USB with a computer, where the measurement results can be analyzed. The device also has an LCD to display the measurement results.
The quality of the supplied power by electricity utilities is regulated and of concern to the end user. Power quality disturbances include interruptions, sags, swells, transients and harmonic distortion. The instruments used to measure these disturbances have to satisfy minimum requirements set by international standards. In this paper, an analysis of multi-harmonic least-squares fitting algorithms applied to total harmonic distortion (THD) estimation is presented. The results from the different least-squares algorithms are compared with the results from the discrete Fourier transform (DFT) algorithm. The algorithms are assessed in the different testing states required by the standards.