Quantifying and Monetizing Renewable Energy Resiliency

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.
3 Data Resources
Name Size Type Resource Description History
NYC_exp_S42xlsx.xlsx 2.71 MB Data Input data for site value (building, content, business interruption) that was used to populate the catastrophe model and set bounds on the insurance exposure
BIaal.combined.guBase.xlsx 386.8 KB Data Outputs from the catastrophe model using the baseline assumptions. The dataset reflects the annual average loss (AAL) for business loss in the study area.
BIaal.combined.gu.withCC.xlsx 231.8 KB Data Outputs from the catastrophe model using the sea level rise assumptions. The dataset reflects the annual average loss (AAL) for business loss in the study area.
Author Information
Lars Lisell, National Renewable Energy Laboratory
Kate Anderson, National Renewable Energy Laboratory
Nick Laws, National Renewable Energy Laboratory
Spencer Marr, City University of New York
Dag Lohman, Katrisk LLC
Xiangkun Li, National Renewable Energy Laboratory
Tony Jimenez, National Renewable Energy Laboratory
Dylan Cutler, National Renewable Energy Laboratory
Tria Case, City University of New York
Cite This Dataset
Lisell, Lars; Anderson, Kate; Laws, Nick; Marr, Spencer; Lohman, Dag; Li, Xiangkun; Jimenez, Tony; Cutler, Dylan; Case, Tria (2018): Quantifying and Monetizing Renewable Energy Resiliency. National Renewable Energy Laboratory. https://data.nrel.gov/submissions/80
About This Dataset
80
10.7799/1432836
71143
Public
03/13/2018
DOE Project
Value of Resiliency Seed Laboratory Directed Research and Development
Funding Organization
Department of Energy (DOE)
Sponsoring Organization
USDOE Office of Electricity Delivery and Energy Reliability (OE)
Research Areas
Grid Modernization
Solar Power
Wind Energy
Digital Object Identifier
10.7799/1432836