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.

In this paper, a comparison analysis of three different algorithms for the estimation of sine signal parameters in two-channel common frequency situations is presented. The relevance of this situation is clearly understood in multiple applications where the algorithms have been applied. They include impedance measurements, eddy currents testing, laser anemometry and radio receiver testing for example. The three algorithms belong to different categories because they are based on different approaches. The ellipse fit algorithm is a parametric fit based on the XY plot of the samples of both signals. The seven parameter sine fit algorithm is a least-squares algorithm based on the time domain fitting of a single tone sinewave model to the acquired samples. The spectral sinc fit performs a fitting in the frequency domain of the exact model of an acquired sinewave on the acquired spectrum. Multiple simulation situations and real measurements are included in the comparison to demonstrate the weaknesses and strong points of each algorithm.

International standards from IEC and IEEE regulate power grid parameters such as theRMSvalue, frequency, harmonic and interharmonic distortion, unbalance or the presence of transients, that are important to assure the quality of distributed power. Standard IEC 61000-4-30 suggests the zero crossing algorithm for the measurement of the power grid frequency, but also states that different algorithms can be used. This paper proposes a new algorithm, the Fractional Interpolated Discrete Fourier Transform, FracIpDFT, to estimate the power grid frequency, suitable for implementation in resource limited embedded measurement systems. It is based on the non-integer Goertzel algorithm followed by interpolation at non-integer multiples of the DFT frequency resolution. The proposed algorithm is validated and its performance compared with other algorithms through numerical simulations. Implementation details of the FracIpDFT in an ARM Cortex M4 processor are presented along with frequency measurement results performed with the proposed algorithm in the developed system.