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SSRS (Stochastic Soaring Raptor Simulator)

RESOURCE

Publicly Accessible Repository
https://github.com/NREL/SSRS
https://doi.org/10.11578/dc.20210903.2
Documentation
https://github.com/NREL/SSRS/blob/master/README.md

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Abstract

SSRS (Stochastic Soaring Raptor Simulator) is a generalizable, probabilistic, and predictive tool for wind energy developers, ecologists, wildlife managers and industry consultants to estimate the potential for soaring raptors to interact with operating wind turbines, without the need for site-specific data collection. Rapid expansion of wind energy development across the world has exposed the risk of turbine collisions for birds and bats. The risk to obligate soaring raptors such as golden eagles is of particular concern due to their small population and influence on ecological balance. Golden eagles rely heavily on updrafts to subsidize their flight, putting them in direct conflict with operational wind turbines that utilize the same wind resource. Understanding the behavior of soaring raptors with varying atmospheric conditions is crucial for predicting and mitigating the risk of turbine collision. This software contains a predictive movement model that simulates individual flight paths of golden eagles during updraft-subsidized long-distance flight, including migration. For a given set of atmospheric conditions, the model simulates thousands of eagles at turbine-scale spatial resolution (50m) to produce a relative presence density map. The simulated eagles rely on updrafts to pursue uninterrupted directional flight with minimal energy expenditure, following fluid-flow principles. The simulator includes a  More>>
Developers:
Sandhu, Rimple [1] ;  Tripp, Charles [1] ;  Quon, Eliot [1] ;  Thedin, Regis [1] ;  Williams, Lindy [1] ;  Doubrawa, Paula [1] ;  Draxl, Caroline [1] ;  Lawson, Mike [1]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Release Date:
2021-10-18
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Programming Languages:
Python
Version:
1.0
Licenses:
BSD 3-clause "New" or "Revised" License
Sponsoring Org.:
Code ID:
63192
Site Accession Number:
NREL SWR-21-78
Research Org.:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Country of Origin:
United States
Keywords:
golden eagle, eagle, raptors, wind energy, wind turbine, collision risk, mapping, migration, updrafts

RESOURCE

Publicly Accessible Repository
https://github.com/NREL/SSRS
https://doi.org/10.11578/dc.20210903.2
Documentation
https://github.com/NREL/SSRS/blob/master/README.md

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Citation Formats

Sandhu, Rimple, Tripp, Charles, Quon, Eliot, Thedin, Regis, Williams, Lindy, Doubrawa, Paula, Draxl, Caroline, and Lawson, Mike. SSRS (Stochastic Soaring Raptor Simulator). Computer Software. https://github.com/NREL/SSRS. USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Wind Energy Technologies Office. 18 Oct. 2021. Web. doi:10.11578/dc.20210903.2.
Sandhu, Rimple, Tripp, Charles, Quon, Eliot, Thedin, Regis, Williams, Lindy, Doubrawa, Paula, Draxl, Caroline, & Lawson, Mike. (2021, October 18). SSRS (Stochastic Soaring Raptor Simulator). [Computer software]. https://github.com/NREL/SSRS. https://doi.org/10.11578/dc.20210903.2.
Sandhu, Rimple, Tripp, Charles, Quon, Eliot, Thedin, Regis, Williams, Lindy, Doubrawa, Paula, Draxl, Caroline, and Lawson, Mike. "SSRS (Stochastic Soaring Raptor Simulator)." Computer software. October 18, 2021. https://github.com/NREL/SSRS. https://doi.org/10.11578/dc.20210903.2.
@misc{ doecode_63192,
title = {SSRS (Stochastic Soaring Raptor Simulator)},
author = {Sandhu, Rimple and Tripp, Charles and Quon, Eliot and Thedin, Regis and Williams, Lindy and Doubrawa, Paula and Draxl, Caroline and Lawson, Mike},
abstractNote = {SSRS (Stochastic Soaring Raptor Simulator) is a generalizable, probabilistic, and predictive tool for wind energy developers, ecologists, wildlife managers and industry consultants to estimate the potential for soaring raptors to interact with operating wind turbines, without the need for site-specific data collection. Rapid expansion of wind energy development across the world has exposed the risk of turbine collisions for birds and bats. The risk to obligate soaring raptors such as golden eagles is of particular concern due to their small population and influence on ecological balance. Golden eagles rely heavily on updrafts to subsidize their flight, putting them in direct conflict with operational wind turbines that utilize the same wind resource. Understanding the behavior of soaring raptors with varying atmospheric conditions is crucial for predicting and mitigating the risk of turbine collision. This software contains a predictive movement model that simulates individual flight paths of golden eagles during updraft-subsidized long-distance flight, including migration. For a given set of atmospheric conditions, the model simulates thousands of eagles at turbine-scale spatial resolution (50m) to produce a relative presence density map. The simulated eagles rely on updrafts to pursue uninterrupted directional flight with minimal energy expenditure, following fluid-flow principles. The simulator includes a stochastic model of eagle behavior and a systematic method of accounting for spatiotemporal variations in atmospheric conditions. This framework only requires publicly available atmospheric data to estimate orographic and thermal updrafts, ensuring general usability.},
doi = {10.11578/dc.20210903.2},
url = {https://doi.org/10.11578/dc.20210903.2},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20210903.2}},
year = {2021},
month = {oct}
}