In this work, we analysed multi-annual data set of wind and solar production portfolio with different power frequency approaches and averaging methods in order to characterize power production variability at different temporal scales. All of the methods have their advantages depending on their scale and purpose, but also some shortcomings that limit their use. For the purposes of this work, we selected the method of explicit derivation as the most appropriate for the fast power change frequency analysis and characterization. The variability of power production from wind and solar power plants in Croatia is strongly present on an hourly, daily and seasonal level, while on an annual level the variability is much less pronounced. Since current electricity production and consumption must remain in balance to maintain the stability of the power network, this variability of production can pose significant challenges for the inclusion of large amounts of wind and solar energy in the power system of the Republic of Croatia. A particular challenge for the power system in terms of production variability is the fast change in power. Fast power change affects the quality of production forecasting and consequently causes higher imbalance costs. The impact on the management and balancing of the power system is particularly challenging.