Quantifying and Monetizing Renewable Energy Resiliency
Abstract
As part of the seed LDRD in 2017 we generated catastrophe models to look at the value of resiliency from an insurance perspective. These data sets reflect the inputs and outputs of that analysis.
- Authors:
-
- National Renewable Energy Laboratory
- Publication Date:
- Other Number(s):
- 80
- Research Org.:
- National Renewable Energy Laboratory - Data (NREL-DATA), Golden, CO (United States); National Renewable Energy Laboratory
- Sponsoring Org.:
- USDOE Office of Electricity Delivery and Energy Reliability (OE)
- Collaborations:
- National Renewable Energy Laboratory
- Subject:
- 14 SOLAR ENERGY; 17 WIND ENERGY; 20 FOSSIL-FUELED POWER PLANTS; 2017; 25 ENERGY STORAGE; LDRD; NREL; New York; USA; catastrophe models; data; energy; hybrid systems; insurance premiums; reopt; resiliency; solar energy; wind energy
- OSTI Identifier:
- 1432836
- DOI:
- https://doi.org/10.7799/1432836
Citation Formats
Lisell, Lars, Anderson, Kate, Laws, Nick, Marr, Spencer, Lohman, Dag, Li, Xiangkun, Jimenez, Tony, Cutler, Dylan, and Case, Tria. Quantifying and Monetizing Renewable Energy Resiliency. United States: N. p., 1969.
Web. doi:10.7799/1432836.
Lisell, Lars, Anderson, Kate, Laws, Nick, Marr, Spencer, Lohman, Dag, Li, Xiangkun, Jimenez, Tony, Cutler, Dylan, & Case, Tria. Quantifying and Monetizing Renewable Energy Resiliency. United States. doi:https://doi.org/10.7799/1432836
Lisell, Lars, Anderson, Kate, Laws, Nick, Marr, Spencer, Lohman, Dag, Li, Xiangkun, Jimenez, Tony, Cutler, Dylan, and Case, Tria. 1969.
"Quantifying and Monetizing Renewable Energy Resiliency". United States. doi:https://doi.org/10.7799/1432836. https://www.osti.gov/servlets/purl/1432836. Pub date:Wed Dec 31 23:00:00 EST 1969
@article{osti_1432836,
title = {Quantifying and Monetizing Renewable Energy Resiliency},
author = {Lisell, Lars and Anderson, Kate and Laws, Nick and Marr, Spencer and Lohman, Dag and Li, Xiangkun and Jimenez, Tony and Cutler, Dylan and Case, Tria},
abstractNote = {As part of the seed LDRD in 2017 we generated catastrophe models to look at the value of resiliency from an insurance perspective. These data sets reflect the inputs and outputs of that analysis.},
doi = {10.7799/1432836},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Dec 31 23:00:00 EST 1969},
month = {Wed Dec 31 23:00:00 EST 1969}
}
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