The topic of the doctoral dissertation is in the field of measuring and evaluating the parameters of harmonic signals in frequency domain. Measurements of such electrical parameters are important for operation of power systems from both an engineering and economic point of view. The paper presents methods for non-parametric calculation of electrical signals with unknown frequency, amplitude, and phase shift. Due to the increasing use of nonlinear elements, the measured signals in the network often contain harmonic components, the amount of which is sometimes not negligible. Since the measured signals are mostly sinusoidal in shape and contain several components, it makes sense to perform the analysis in frequency space. Such an approach provides a better insight into the situation in the network, and at the same time can introduce a certain measurement error due to the final measurement time. As the measurement time increases, the magnitude of the error decreases, but the problem arises when measuring short-term transients of a period of several periods. In such situations, it is necessary to introduce methods for smoothing the measured signals.
The largest part of the error in frequency space analysis occurs due to nonstationarity of signals and incoherent sampling. In the latter case, the duration of the measurement is not equal to the multiple of the measured signal frequency, so after performing a discrete Fourier transform, certain harmonic components appear in the frequency spectrum, which are otherwise not present in the measured signal. In addition, the amplitude and frequency of the measured signal change, which makes it even more difficult to perform coherent sampling.
The dissertation describes 3 new algorithms for reducing the estimated systematic error or estimating the measurement uncertainty of type B using discrete Fourier interpolation (DFT) in combination with Rife-Vincent 1st order window functions (RV-1). Window functions are useful for reducing the outflow error in the frequency spectrum due to incoherence in time space. Strong windows eliminate the leakage error more significantly, but due to the wide main ridge, they have a worse effect on the resolution of the close-by lying components.
The interpolation of the measured or calculated parameters is performed in the frequency domain by summing the two, three or more largest DFT coefficients, thus reducing the systematic leakage error. Increasing the number of coefficients used reduces the leakage error, but at the same time increases the number of calculation steps and the complexity of the calculation.
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