DEVELOPMENT OF A MEASUREMENT SYSTEM AND SOFTWARE PRODUCT TO COLLECT AND ANALYSE ELECTRICITY QUALITY PARAMETERS

Abstract

In the real operating conditions of electrical networks, there are modes of operation characterised by deviations of their parameters from their nominal values. Of particular importance for the operation of electrical equipment are variations in the amplitude and frequency of the supply voltage. The permissible and limit deviations of these parameters are regulated in accordance with national standards. To calculate the main power quality parameters it is not sufficient to know only the methods of their calculation. Additional algorithms are needed to determine fundamental harmonic voltages and frequencies. Such a method is the discrete Fourier transform. This algorithm is designed for signal analysis. However, this algorithm was not widely used in calculating Fourier coefficients in modern software packages. The reason is that it takes much time and computer resources to determine the Fourier coefficients which reduces the attractiveness of this approach. For this reason, it is advisable to use the fast Fourier transform algorithm. This algorithm uses the periodicity properties of the trigonometric function, which allows reducing the number of multiplication operations. The results of using the fast Fourier transform algorithm are similar to the discrete Fourier algorithm, but the number of operations required for calculation is several times less. At the same time, fast and discrete Fourier transform algorithms can give quite a significant error in determining the frequency estimate. This deviation is related to multiplicity of time between signal measurements and its period. If the period of the analogue signal is a multiple of the sampled signal measurement distance, an additional Quin method must be used to reduce the error in determining the frequency of the main signal. In this regard, the development of algorithms and software complex for automated measurement systems of electrical power quality indicators using digital data acquisition and processing devices in real time is an urgent task.