Cloud-Edge interoperability and hardware acceleration for resolving real time surveillance problems in smart grids comprising extended electronic instrumentation
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Date
2025-08-25
Authors
Τζανής, Νικόλαος
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Abstract
This dissertation presents a comprehensive framework for real-time monitoring of modern smart grids by enhancing conventional Wide Area Monitoring Systems (WAMS) with cloud-edge computing, hardware acceleration, and next-generation communication networks. It focuses on developing optimized hardware architectures for real-time transient state estimation and power event classification on resource-constrained edge devices. The work proposes and evaluates architectures that facilitate the strategic distribution of workloads across the cloud-edge continuum, guided by latency and processing demands, while supporting dynamic hardware reconfiguration. Additionally, a hardware-accelerated, real-time power grid simulator is introduced to emulate fast transient phenomena at the edge, enabling more responsive and intelligent local control. The research further integrates key 5G network features to support low-latency, privacy-preserving event classification at the edge, reducing reliance on centralized processing. This dissertation offers valuable insights into the design of modern smart grid monitoring systems by bridging emerging technologies in electronics, cloud computing, and next-generation telecommunications to meet the evolving demands of power grids.
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Keywords
Cloud Edge, Hardware acceleration, Wide area monitoring systems, Real time monitoring