Digitalization, electrification, and cybersecurity of urban energy services: smart grid optimization and fleet management

The accelerating digitalization and electrification of urban energy services are reshaping the role of Distribution System Operators (DSOs), requiring new tools for observability, flexibility, and cross sector integration. This thesis develops a comprehensive framework that unites Digital Twin (DT) technologies, heuristic state estimation, optimization methods, and cybersecurity risk assessment to support the reliable and sustainable operation of modern distribution networks and urban services. The research has been conducted in close collaboration with ASM Terni, a municipal multi-utility in Italy, ensuring methodological rigor and practical validation. The first contribution lies in the development of a modular DT framework for distribution networks under low-observability conditions. By integrating Genetic Algorithm-based State Estimation (GA-SE) with SARIMA forecasting, the DT enables accurate monitoring of medium-voltage nodes using only low-voltage Power Quality Analyzer data. This hybrid approach enhances situational awareness and demonstrates how DSOs can extend observability without pervasive sensor deployment. Building on this foundation, the thesis introduces a DT-informed feedback loop for flexibility activation. Real-world case studies on water pumps and virtual batteries show how state estimation outputs can guide load shifting and balancing, reducing peak imports and improving self-consumption. The approach demonstrates that even existing assets can provide grid-supportive services when coupled with digital intelligence. Beyond grid operations, the research extends to the electrification and optimization of urban fleets. A dedicated methodology integrates Mixed Integer Linear Programming (MILP), clustering techniques, and anomaly detection for electric vehicle charging optimization, while a complementary study evaluates routing and electrification pathways for municipal waste collection. Together, these case studies highlight how digital tools can deliver cost reductions, emission savings, and operational efficiency across multiple urban domains. The thesis also addresses the emerging cybersecurity risks of digitalized grids. A standards-aligned risk assessment methodology is developed and applied to DT-enabled infrastructures, evaluating vulnerabilities such as false data injection and denial-of-service. The results provide DSOs with practical strategies for securing critical assets while maintaining operational performance. Overall, this work demonstrates that DT-enabled observability, flexibility, and cross-sector optimization can transform distribution grids into proactive, resilient, and user-centric infrastructures. By integrating power systems engineering, data science, and cybersecurity, the thesis provides a pathway for DSOs and municipalities to navigate the complexity of the energy transition and support the development of sustainable, data-driven cities.