A comprehensive review and framework on the applications of digital twins for energy transition at the district level

Abstract

Districts face dual pressures: reducing carbon emissions while managing surging electricity demand from electrification and urban growth. Traditional grid expansion cannot match the speed and complexity required for modern energy transitions. District energy transitions require connecting different scales, from individual buildings to grid networks, and different timeframes, from daily operations to long-term planning. Despite growing interest in Digital Twin (DT) for energy management, their application to integrated district-level energy transitions remains poorly understood. This review investigates how DTs can enable district energy transitions by examining their applications in built environment and energy infrastructure at district level, analyzing implementations across Positive Energy Districts (PEDs), microgrids (MGs), and related district energy paradigms. DT components (physical models, core capabilities, data infrastructure, and functional evolution) are investigated to assess their integrative potential. The analysis reveals three disconnects: building and grid systems are modeled separately despite inherent interdependencies; operational insights rarely inform infrastructure planning; and intervention strategies overlook sequential dependencies. To address these gaps, we propose an integrated framework advancing DTs toward district energy planning. The framework bridges semantic, temporal, and sequential planning through: knowledge graph architectures enabling cross-domain data integration, coupled simulation pipelines capturing building-grid interactions, and reinforcement learning optimizing intervention sequences. Unlike optimization that fixes strategies upfront, sequential planning accommodates technology emergence and regulatory shifts inherent to multi-decade transitions. This integrated approach transforms DTs from domain-specific monitoring tools into strategic planning platforms where coordinated building improvements and distributed energy resources defer costly grid expansions while accelerating district decarbonization.