The large-scale connection of distributed energy resources, electric vehicles, and flexible loads, together with expanding low-voltage monitoring and edge sensing, is turning distribution networks into active cyber-physical systems. Conventional offline simulation cannot fully support the online state tracking, short-term scenario analysis, operational risk assessment, and closed-loop decision support now expected in network operation. Digital twins offer a way to address this gap by linking network models to operational data and revising those models as system conditions change. After systematically searching Scopus and the Web of Science, six application areas for digital twin applications in distribution network simulations are summarized: model construction, simulation and validation platforms; asset, equipment and spatial digitalization; DER (distributed energy resource), PV, EV (electric vehicle) and prosumer integration; operation, monitoring and situational awareness; protection, fault diagnosis and resilience; and optimization, control and planning. The review examines the architectures, enabling technologies, and applications reported across this evidence base. The literature indicates a gradual shift from conceptual digital representations toward real-time simulation, hardware-in-the-loop validation, data-driven model updating, and distribution-side decision support. Persistent gaps concern low-voltage observability, data governance, model credibility assessment, standardized interfaces, cybersecurity, and closed-loop control.

The rapid integration of renewable energy is increasing the need for fast and sustained load-side frequency regulation, and public electric vehicle (EV) charging networks are promising providers. Their participation, however, is constrained by the volatile charging demand and strict service requirements, which make it difficult to balance regulation revenue with charging quality. This paper proposes a three-layer coordinated framework for multi-site charging networks participating in secondary frequency regulation, comprising market bidding, rolling planning, and fast-response tracking. At the market layer, baseline charging schedules are co-optimized with symmetric regulation capacity bids. At the planning layer, completion margin and progress protection constraints are introduced as tractable service safeguards that preserve charging continuity and deadline compliance. At the execution layer, coordinator-assisted distributed station-level tracking and charger-level urgency-aware allocation track automatic generation control (AGC) commands while correcting the charging progress in real time. The station-level problem is decomposed into local box-constrained subproblems coordinated by a scalar dual signal, enabling real-time AGC tracking with limited inter-station information exchange. Case studies on a reproducible simulated network with 20 stations and 600 chargers show that the proposed method improves ancillary service benefits while maintaining strong tracking performance and markedly improving the charging continuity, deadline compliance, and spatial load balance.