Key performance indicators for resiliency assessment in power systems with renewable energy and electric vehicles integration

As modern energy systems become increasingly complex, microgrids and distributed energy resources (DERs) are emerging as critical infrastructures for enhancing power system resilience. This review critically examines and synthesizes key performance indicators (KPIs) used to evaluate resilience in the context of renewable energy integration, electric vehicles (EVs)—including fuel cell EVs—and intelligent control strategies. The study categorizes and assesses KPIs across technical, economic, environmental, and social dimensions, including reliability indices (e.g., SAIDI, SAIFI), renewable energy penetration, demand response responsiveness, cost-effectiveness, and community engagement. Special emphasis is placed on the limitations of conventional KPIs when applied to high-renewable systems and the need for dynamic, context-specific metrics tailored to evolving grid structures.

The review explores advanced approaches such as machine learning and artificial intelligence for predictive resilience analytics, and compares traditional indicators with multi-criteria decision-making methods like the TOPSIS-based Vulnerability Function. Additionally, the impact of hydrogen procurement reliability on energy system resilience and the role of fuel cell refueling infrastructure are discussed. By identifying gaps in current frameworks and offering recommendations for more adaptive, scalable, and data-driven KPIs, this study provides valuable insights to guide resilient energy system planning and policy-making. The findings highlight the need for standardization, real-world validation, and integration of AI tools to ensure robust, future-ready energy infrastructures.