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Three-phase power electronics converters (PECs) are commonly used as an interconnection of DC loads/sources with the electrical AC power system. Their important goal is to ensure three-phase symmetrical and pure sinusoidal grid current waveforms. Unfortunately, frequent adverse of grid voltage conditions like the occurrence of higher order harmonics and dips/sags leads to problems in maintaining high-quality parameters of current and stable operation of PEC. Therefore, a more complex control algorithms are usually used to solve those problems. In this paper, effective and simple control is proposed to mitigate grid current distortions caused by grid-voltage harmonics. This improvement of current quality can be easily obtained in control of grid-connected PEC using only band notch filtered grid voltage as a feedforward without any additional control loops parallel connected to linear current controllers (tuned to fundamental frequency). Theoretical analysis with simulation and experimental investigations are presented, which prove very good properties and advantages of the proposed control idea. INDEX TERMS Current harmonics mitigation, DC-AC power conversion, grid distortions, harmonic distortion, voltage control.

Organic farming in Poland has been developing dynamically since the accession to the EU. However, there are considerable differences in the level of organic farming development in particular regions. Therefore, it is vital to identify the primary factors and conditions for this development and their importance considering their spatial distribution. The presented paper aims to estimate the relationships between the level of organic agriculture development and selected conditions of financial and environmental character. The investigation is based on primary data for 2017 retrieved from the Local Data Bank of the Main Statistical Office and Agricultural and Food Quality Inspection database for all Poland districts. In order to achieve this objective, a multivariate statistical analysis method—the canonical correlation was applied. The analysis was preceded by constructing the composite indices of organic agriculture development and its conditions based on a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method and correlation analysis between the indices developed by the authors. The performed canonical analysis showed two statistically significant canonical variables with relatively high values of the canonical correlation (0.74 and 0.59). It proves that the degree of explaining the variability of one set of variables through linear relationships (referring to the level of organic farming development), by the second input data set (describing the determinants of the development), by successive pairs of canonical variables is high. This means that the created model describes relatively well the considered data sets.

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