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This content will become publicly available on October 22, 2024

Title: Topological Guided Detection of Extreme Wind Phenomena: Implications for Wind Energy
Extreme wind phenomena play a crucial role in the efficient operation of wind farms for renewable energy generation. However, existing detection methods are computationally expensive and limited to specific coordinates. In real-world scenarios, understanding the occurrence of these phenomena over a large area is essential. Therefore, there is a significant demand for a fast and accurate approach to forecast such events. In this paper, we propose a novel method for detecting wind phenomena using topological analysis, leveraging the gradient of wind speed or critical points in a topological framework. By extracting topological features from the wind speed profile within a defined region, we employ topological distance to identify extreme wind phenomena. Our results demonstrate the effectiveness of utilizing topological features derived from regional wind speed profiles. We validate our approach using high-resolution simulations with the Weather Research and Forecasting model (WRF) over a month in the US East Coast.  more » « less
Award ID(s):
2136744
NSF-PAR ID:
10474750
Author(s) / Creator(s):
; ;
Publisher / Repository:
3rd Workshop on Energy Data Visualization
Date Published:
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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