Development of a logistic model for energy transition to renewable energy sources with energy security consideration - Zhukov, Oleksii; Boiko, Serhii; Koval, Andrii; Kotov, Olekcii; Vyshnevsʹkyy, Sviatoslav (Technology audit and production reserves, 2025)
The object of the study is the process of energy transition to renewable energy sources (RES) at the enterprise or regional level, aimed at replacing traditional carbon-based sources of electricity. One of the most problematic issues is the insufficient consideration of energy security factors in existing forecasting models, which leads to risks of electricity shortages, especially under conditions of RES intermittency and geopolitical challenges such as military attacks or import dependence. A literature review showed that existing models do not account for dynamic constraints in the implementation of RES, which limits their practical applicability for ensuring power system resilience. In the course of the research, numerical modeling methods were used, in particular an adaptation of the logistic growth equation with an integrated dynamic security factor Sb(t). This makes it possible to fill the gaps in existing models with regard to risk assessment and ensuring system stability. The obtained logistic model predicts the energy transition with RES reaching a 68% share in 24 years for a typical region without compromising security. This is due to the fact that the proposed model has such features as the integration of the coefficient of energy transition rate (CETR) and the dynamic constraint Sb(t), which adapts to changes in demand and reserve. This allows identifying the potential to increase system resilience through the optimal balance of RES and traditional sources during the transition. As a result, it becomes possible to achieve such indicator values as a 68% share of RES, owing to the model’s flexibility to local conditions (variations of ρ, γ, k) and the consideration of worst-case scenarios (CF.min). Compared with similar known models, this provides advantages such as adaptability to regional risks, more accurate forecasting of the transition rate, and reduction of blackout probability. This is particularly relevant for vulnerable power systems, both in Ukraine and worldwide.