Taxonomy of digital twins for power grids

• Presents a novel taxonomy tailored for digital twins in power grid systems. • Aligns with ISO/ IEC30186 :2025 standard while adding energy-sector specificity. • Introduces new dimensions: lifecycle integration, data architecture, cybersecurity. • Validated through KOEN, Elvia, and Bentley OpenUtilities digital twin case studies. • Provides open GitHub interactive tool for maturity benchmarking and visualization. Digital twins (DTs) are increasingly adopted in the energy sector, yet existing conceptual frameworks and maturity models remain largely generic, limiting their usefulness for power grid applications with stringent requirements for resilience, security, and lifecycle integration. This paper proposes an upgraded taxonomy of DTs tailored to power grid systems, extending earlier generic frameworks and aligning them with the ISO/ IEC30186 :2025 maturity model. The taxonomy introduces domain-specific dimensions, including cyber-physical security integration, intelligence level, and multi-layered data architectures, while ensuring compatibility with internationally standardized maturity aspects. A comprehensive literature analysis and co-occurrence study underpin the revisions, ensuring both methodological rigor and relevance to current research and practice. The taxonomy’s analytical and practical value is demonstrated through its application to three real-world DT use cases: KOEN (generation-focused), Elvia (distribution-focused), and Bentley OpenUtilities (lifecycle-integrated). Comparative benchmarking across these cases highlights both commonalities and context-dependent maturity profiles, confirming that DT maturity is not absolute but shaped by organizational objectives, technical architectures, and sectoral priorities. The taxonomy also enables scenario-based reasoning and role-specific insights, supporting cybersecurity analysis, operational decision-making, and business risk evaluation. By combining academic rigor, sector-specific focus, and alignment with international standards, the proposed taxonomy offers a replicable framework for assessing and improving DT maturity in power grids. An interactive tool, openly available on GitHub, further supports its practical application by enabling benchmarking, visualization, and recommendations. In this way, the work contributes both to scholarly discourse on DT conceptualization and to the practical adoption of maturity frameworks by utilities, regulators, and technology providers.