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Distributed Solar Technoeconomic Agent Characteristics dSTAC

Publicly accessible License 

These data files summarize key techno-economic metrics used in the NREL dGen model for modeling adoption of distributed solar by representative residential commercial and industrial entities for each county in the continental United States. As described further below many of the metrics are derived as summaries of outputs from dGen. Specifically each county and sector in these file are summarized as a single agent that is the weighted average of 10 statistically-representative agents weighed by the statistical frequency. The dGen simulation used to derive this dataset was conducted in 2018 using the NREL 2018 Standard Scenario Mid Case assumptions https//www.nrel.gov/docs/fy19osti/71913.pdf.

Citation Formats

National Renewable Energy Laboratory. (2019). Distributed Solar Technoeconomic Agent Characteristics dSTAC [data set]. Retrieved from b6cb4c30-d7de-4536-8cf2-2637a11a0053.
Export Citation to RIS
Kwasnik, , Sigrin, . Distributed Solar Technoeconomic Agent Characteristics dSTAC. United States: N.p., 07 Feb, 2019. Web. b6cb4c30-d7de-4536-8cf2-2637a11a0053.
Kwasnik, , Sigrin, . Distributed Solar Technoeconomic Agent Characteristics dSTAC. United States. b6cb4c30-d7de-4536-8cf2-2637a11a0053
Kwasnik, , Sigrin, . 2019. "Distributed Solar Technoeconomic Agent Characteristics dSTAC". United States. b6cb4c30-d7de-4536-8cf2-2637a11a0053.
@div{oedi_6330, title = {Distributed Solar Technoeconomic Agent Characteristics dSTAC}, author = {Kwasnik, , Sigrin, .}, abstractNote = {These data files summarize key techno-economic metrics used in the NREL dGen model for modeling adoption of distributed solar by representative residential commercial and industrial entities for each county in the continental United States. As described further below many of the metrics are derived as summaries of outputs from dGen. Specifically each county and sector in these file are summarized as a single agent that is the weighted average of 10 statistically-representative agents weighed by the statistical frequency. The dGen simulation used to derive this dataset was conducted in 2018 using the NREL 2018 Standard Scenario Mid Case assumptions https//www.nrel.gov/docs/fy19osti/71913.pdf.}, doi = {}, url = {b6cb4c30-d7de-4536-8cf2-2637a11a0053}, journal = {}, number = , volume = , place = {United States}, year = {2019}, month = {02}}

Details

Data from Feb 7, 2019

Last updated Dec 18, 2024

Submitted Feb 7, 2019

Organization

National Renewable Energy Laboratory

Contact

Ted Kwasnik

Authors

Kwasnik

National Renewable Energy Laboratory

Sigrin

National Renewable Energy Laboratory

Research Areas

DOE Project Details

Project Name Mass Market Breakout of Distributed Solar

Project Number GO28308

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