Identification of pressure points in modern power systems using transfer entropy
Katerina Tang, M. Vivienne Liu, C. Lindsay Anderson, Vivek Srikrishnan

TL;DR
This paper introduces a transfer entropy-based method to identify early warning signals of power shortages in modern, weather-dependent energy systems, aiding reliability planning amid increasing renewable integration.
Contribution
It applies transfer entropy to simulate and analyze complex interactions in future power grids, revealing critical pressure points that are not predictable by high-level scenario features.
Findings
Pressure points often result from system-wide interactions.
Identified pressure points align with known bottlenecks.
Method highlights the importance of holistic reliability planning.
Abstract
Integration of variable energy resources -- e.g., solar, wind, and hydro -- and end-use electrification increase modern energy systems' weather-dependence. Identifying critical infrastructure constraining the power grid's ability to meet electricity demand under weather-induced shocks and stressors is essential for understanding risks and guiding adaptation. We use transfer entropy to identify predictive pressure points: grid components whose utilization patterns provide early signals of downstream power shortages. We apply this method to simulations of New York State's proposed future grid under various meteorological and technological scenarios, showing that pressure points often arise from complex, system-wide interactions between generation, transmission, and demand. While transfer entropy does not support conclusions about causality, the identified pressure points align with known…
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