Economic Modeling of Energy Security of Distributed Power Systems in the Post-Crisis Period: Scenario Analysis and Assessment of Tail Risks

This study investigates the transformation of energy security in distributed energy systems under growing uncertainty, geopolitical shocks, and fuel market volatility. A risk-based multi-objective optimization framework is proposed that integrates economic performance (LCOE, CAPEX, and OPEX), system reliability, and systemic risk measured by Conditional Value-at-Risk (CVaR). The empirical analysis is based on European electricity market data for 2010–2025 and combines historical analysis with stochastic scenario generation and Monte Carlo simulation to evaluate the impacts of exogenous shocks. The results reveal a structural shift in the European electricity market after 2021, characterized by increased sensitivity to fuel price fluctuations and a transition to a more volatile operating regime. Although a higher share of renewable energy improves economic and environmental performance, it does not ensure system resilience without complementary flexibility measures, including energy storage and demand-side management. The proposed framework demonstrates that integrating these measures substantially reduces systemic risk under crisis conditions. The analysis also identifies a persistent post-crisis risk pattern, reflected in elevated CVaR values after market stabilization, which is consistent with the hypothesis of risk hysteresis. Rather than proving hysteresis, the results indicate sustained risk persistence following major external shocks. The proposed framework extends existing approaches to energy security assessment by integrating economic efficiency, reliability, and risk within a unified optimization model. Its modular structure enables adaptation to different electricity markets through recalibration of local parameters, providing a practical decision-support tool for strategic planning under uncertainty.