Abstract

Phase angle differences on a power system are strongly correlated to active power transfer and system topology. The transition from centralized thermal generation to distributed generation is driving phase angle variation in unprecedented ways. This study studies PMU data from three sites across Ireland and other power system metrics, including system demand and wind generation. Linear regression is used to analyse phase angle variation from power system metrics; the results are used to identify system operating parameters and predict future operating conditions as Ireland’s wind resource expands. It is demonstrated that anticipated wind expansion may cause phase angle variation across the network that exceeds operational thresholds. The methods of wrangling and joining different power system data sources and the sequential forward selection regression function can be applied to the vast amounts of time series data generated from power system operation.

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