Digital Twins in energy and power systems: architectures, applications, enabling tools, and actionable roadmap for utility-scale implementation

Digital Twin (DT) technology is accelerating the digitalization of energy and power systems by facilitating real-time synchronization of physical assets with virtual models. In this paper, a systematic and comprehensive analysis of the DT architectures, enabling technologies, and domain-specific applications across smart grids, renewable energy systems, and predictive maintenance is conducted. A four-layer DT framework, including the physical entity, digital replica, communication infrastructure, and intelligent service layer, is analyzed alongside the standards and platforms that support interoperability and scalability. The paper emphasizes the role of DT in grid monitoring, demand response, forecasting, fault diagnostics, and asset health management. A comparative analysis of major platforms and standards provides insights into real-time integration, scalability, and interoperability of DT. Also, the technical challenges, future trends, and research directions in the field of the DT platform for energy and power systems are analyzed. As a key contribution, this paper proposes a utility-scale DT deployment roadmap, which is supported by four key contributions: (i) strategic insights for adoption across utilities, (ii) a DT maturity and implementation index (DTMII) for quantitative readiness assessment, (iii) a phased rollout plan linking DTMII targets with implementation milestones, and (iv) a policy and institutional framework bridging technological advancement with organizational readiness. Hence, these contributions create a comprehensive plan for resilient, smart, and interoperable DT ecosystems, offering practical guidance for researchers, engineers, and utility stakeholders dedicated to advancing digital transformation in energy systems.