Phasor measurement unit implementation across embedded, edge, and cloud environments for modern grid monitoring systems

Phasor Measurement Units (PMUs) play a critical role in ensuring reliable, real-time monitoring of electrical power grids, but traditional PMU designs often face scalability challenges due to high costs and specialized hardware requirements. This dissertation addresses these limitations by investigating three distinct implementation approaches: a low-cost embedded PMU, a virtualized PMU operating on edge devices, and a novel cloudbased PMU concept. The first approach focuses on designing a cost-effective, stand-alone PMU using embedded technology, achieving high measurement precision while reducing production costs. The second approach leverages edge computing to virtualize PMU functions, implementing a virtual PMU on an edge device to reduce reliance on dedicated hardware. The third approach extends PMU capabilities to a cloud environment, where synchrophasor estimation is performed within cloud infrastructure, offering potential for improved scalability and accessibility in large-scale grid monitoring. Each implementation is evaluated to determine its feasibility, performance, and suitability for real-world grid applications. Through these three approaches, this research demonstrates that PMUs can be adapted and optimized for a wide range of system architectures, from low-cost embedded devices to scalable cloud infrastructures, paving the way for more accessible grid monitoring solutions.