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. |
Keywords
Submitted
• Mar •
13
2018
National Renewable Energy Laboratory
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. 10.7799/1432836
About This Dataset
80
10.7799/1432836
71143
Public
09/16/2022
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
License
View License
Digital Object Identifier
10.7799/1432836