Zuzana Florkova

In recent years, there has been a growing emphasis on the efficient utilization of natural resources across various facets of life. One such area of focus is transportation, particularly electric mobility in conjunction with the deployment of renewable energy sources. To fully realize this objective, it is crucial to quantify the probability of achieving the desired state—production exceeding consumption. This article deals with the computation of the probability that the energy required to charge an electric vehicle will originate from a renewable source at a specific time and for a predetermined charging duration. The base of the model lies in artificial neural networks, which serve as an ancillary tool for the actual probability assessment. Neural networks are used to forecast the values of energy production and consumption. Following the processing of these data, the probability of energy availability for a given day and month is determined. A total of seven scenarios are calculated, representing individual days of the week. These findings can help users in their decision-making process regarding when and for how long to connect their electric vehicle to a charging station to receive assured clean energy from a local photovoltaic source.

The main objective of this article is to provide new information on the effects of mechanical pretreatment of AZ80 magnesium alloy ground with SiC emery papers of different grain sizes on the plasma electrolytic oxidation (PEO) process and corrosion properties of AZ80 in 0.1 M NaCl solution. Then, the roughness of the coated samples was measured by confocal microscopy. The corrosion properties of the ground and coated surfaces were determined by potentiodynamic polarization (PDP) within 1 h of exposure, and electrochemical impedance spectroscopy (EIS) was performed during 168 h of exposure at laboratory temperature. Consequently, the obtained results of the PDP measurements were evaluated by the Tafel analysis and the EIS evaluation was performed by the equivalent circuit analysis through Nyquist diagrams. The morphology and structure of PEO coatings were observed by scanning electron microscopy (SEM) through the secondary imaging technology, and the presence of certain elements in PEO coatings was analyzed by EDS analysis.