RENEWABLE ENERGY AND ENERGY INNOVATIONS: EXAMINING RELATIONSHIPS USING MARKOV SWITCHING REGRESSION MODEL

Accelerating the development of new energy infrastructure in the EU based on renewable energy sources is necessary for the targeted reduction of greenhouse gas emissions and increase in energy production from renewable sources. This article reviews current renewable energy development issues and research on energy innovations within the European energy policy. The effectiveness of energy generation from renewable resources and adaptation of energy innovations may be limited to the challenges of ensuring the flexibility of the pan-European energy system, as the development of energy storage systems and technologies to respond to demand is much slower than the development of renewable energy. Therefore, the study's primary purpose was to explain by mathematical modelling the determinism of variation in electricity production in the EU27 due to predictors of net electricity generation from certain types of renewable resources for 2017-2020. To identify the effects of the deployment of renewable energy in the EU27, a regression model of Markov switching for three regimes was chosen, consisting of selected predictors of clean energy generation from renewable sources (hydro, geothermal, wind, and solar). The statsmodels v0.13.2 toolkit in Python 3.10.5 was used to conduct this study. The variation between total electricity production and net electricity generation in the EU27 is not constant and depends on the mode of electricity production. That is, there is an asymmetry in the relationship between these parameters. The results also show that when the electricity generation rate in the EU27 is moderate, the net wind energy generation rate is not significant. Furthermore, the negative link between clean solar energy generation and electricity production in the EU is significant for all three regimes.