| Summary: | As Distributed Energy Resources become more prevalent in the power grid, the challenges facing grid operators have intensified. The integration of micro-synchrophasors (micro-PMUs) into the grid infrastructure has provided access to high-resolution data, yet analyzing such vast amounts of information presents its own set of obstacles. This study examines thirty days of micro-PMU data from April 2023, employing statistical analysis and unsupervised learning techniques to identify various voltage events over time. Real-world data from grid-connected solar farms in Norfolk, England, is utilized to detect and analyze these voltage events, as well as to explore their distinct patterns.
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