A Service-integrated Web Framework Supporting Reliability Tracing in Smart Distribution Networks
DOI:
https://doi.org/10.13052/jwe1540-9589.2541Keywords:
Smart Distribution Networks (SDNs), Service-Oriented Architecture (SOA), Reliability Tracing, Federated Architectures, Semantic Web Technologies, Fault Localization, Real-Time AnalyticsAbstract
Smart distribution networks (SDNs) now integrate more distributed energy resources, IoT devices, and multi-stakeholder systems, raising service collaboration complexity. This creates key challenges for real-time fault localization, cross-organizational service compatibility, and performance oversight. This paper presents a novel service-integrated web framework designed to address the challenges of reliability tracing, service integration, and performance monitoring SDNs. The framework leverages a modular architecture that integrates advanced methodologies, including a service-oriented architecture (SOA) for seamless cross-organizational collaboration, metadata management using semantic web technologies for enhanced interoperability, and real-time performance monitoring with anomaly detection. An end-to-end reliability tracing mechanism that combines event logging with causal relationship analysis is implemented to localize faults with high accuracy. The development process adopts a model-driven approach, utilizing UML and SysML for architectural modeling, and employs containerized deployment via Kubernetes for scalability. Unlike existing web-based reliability management systems that operate as isolated analytics or visualization layers, the proposed framework integrates service orchestration, semantic metadata reasoning, and fault-tracing analytics into a unified architecture. This service-integrated design enables end-to-end information flow – from data acquisition to reliability inference – under a common web infrastructure, representing a substantive advancement in the web engineering of power system reliability applications. Experimental validation in a simulated SDN environment demonstrates that the framework achieves a reliability tracing accuracy of 97.2%, a detection-to-reporting time of 1.8 s, and resource utilization increases of less than 5% per node. These metrics – tracing accuracy, latency, and resource efficiency – are directly aligned with the reliability evaluation indices defined in IEEE 762 and IEC 62559 standards for smart distribution networks, ensuring comparability with established system reliability benchmarks. These results highlight the framework’s ability to meet the demands of dynamic distributed systems while providing a foundation for future advancements.
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