Метод оцінювання критерію резильєнтності під час оптимізації локальної енергетичної системи з ТЕЦ

• Дата: 2026
• Автор: Khodakivskyi, Vitalii
• Формат: Стаття
• Мова: Українська
• Опубліковано: General Energy Institute of the National Academy of Sciences of Ukraine 2026
• Теми: енергетична система; когенерація; ТЕЦ; стохастичне моделювання; централізоване теплопостачання (ЦТ); екоіндустріальні парки; енергетична безпека.
• Онлайн доступ: https://systemre.org/index.php/journal/article/view/942
• Назва журналу: System Research in Energy

This article develops a quantitative methodology for evaluating and integrating a dynamic resilience criterion of local energy systems with Combined Heat and Power (CHP). Traditional optimization models, focused mainly on cost minimization under deterministic conditions, fail to reflect the stochastic and adaptive nature of resilience during crises such as warfare or infrastructure disruption. The proposed method introduces a multi-stage adaptive algorithm that calculates an effective resilience factor for each generation unit and integrates it directly into the objective function. The model employs non-linear and stochastic functions to simulate real-world effects-such as saturation, thresholds, and sudden shocks stemming from both technical failures and direct physical damages (e.g., from military strikes on CHP utilities or upstream infrastructure), and establishes an economic feedback loop linking technical resilience with operational efficiency. It also accounts for the influence of external support from international organizations and location-based security factors, such as CHP placement within Eco-Industrial Parks (EIPs). By formalizing resilience as a dynamic, state-dependent parameter, this approach enables proactive planning and resource allocation to prevent system collapse rather than merely respond to it. The methodology offers policymakers and system operators a decision-support tool for prioritizing modernization investments that balance cost efficiency and resilience under high uncertainty. The study concludes that embedding resilience metrics into optimization models significantly enhances the sustainability and security of Ukraine’s energy infrastructure during reconstruction and future crisis scenarios, and these models can be replicated to other countries.