Distributed Generation Market Demand (dGen) model

Stanley, Trevor; Blair, Nate; Bowen, Thomas; Das, Paritosh; Koebrich, Sam; McCabe, Kevin; Prasanna, Ashreeta; Ramdas, Ashwin; Sekar, Ashok; Sigrin, Ben

doi:10.25984/1804719

Title: Distributed Generation Market Demand (dGen) model

Dataset
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Abstract

The Distributed Generation Market Demand (dGen) model simulates customer adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the United States or other countries through 2050. The dGen model can be used for identifying the sectors, locations, and customers for whom adopting DERs would have a high economic value, for generating forecasts as an input to estimate distribution hosting capacity analysis, integrated resource planning, and load forecasting, and for understanding the economic or policy conditions in which DER adoption becomes viable, and for illustrating sensitivity to market and policy changes such as retail electricity rate structures, net energy metering, and technology costs.

Authors:

; Blair, Nate; Bowen, Thomas; Das, Paritosh; Koebrich, Sam; McCabe, Kevin; Prasanna, Ashreeta; Ramdas, Ashwin; Sekar, Ashok;

Publication Date:: Fri Oct 16 00:00:00 EDT 2020

Other Number(s):: 1931

DOE Contract Number:: 32307

Research Org.:: DOE Open Energy Data Initiative (OEDI); National Renewable Energy Laboratory (NREL)

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Multiple Programs (EE)

Collaborations:: National Renewable Energy Laboratory (NREL)

Subject:: Array

Keywords:: energy; distributed; solar; bass diffusion; model; geosptatial; DER; distributed energy resource; dGen; Distributed Generation Market Demand; wind; modeling; economics; forecast; AWS; GitHub; database; Database of State Incentives for Renewables Efficiency; CSP; diffusion; market

Geolocation:: 49.2637,-66.5318|24.5873,-66.5318|24.5873,-125.4514|49.2637,-125.4514|49.2637,-66.5318

OSTI Identifier:: 1804719

DOI:: https://doi.org/10.25984/1804719

Project Location:

Citation Formats


                    Stanley, Trevor, Blair, Nate, Bowen, Thomas, Das, Paritosh, Koebrich, Sam, McCabe, Kevin, Prasanna, Ashreeta, Ramdas, Ashwin, Sekar, Ashok, and Sigrin, Ben. Distributed Generation Market Demand (dGen) model.  United States: N. p., 2020. 
        Web.  doi:10.25984/1804719.

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                    Stanley, Trevor, Blair, Nate, Bowen, Thomas, Das, Paritosh, Koebrich, Sam, McCabe, Kevin, Prasanna, Ashreeta, Ramdas, Ashwin, Sekar, Ashok, & Sigrin, Ben. Distributed Generation Market Demand (dGen) model.  United States.  doi:https://doi.org/10.25984/1804719

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                    Stanley, Trevor, Blair, Nate, Bowen, Thomas, Das, Paritosh, Koebrich, Sam, McCabe, Kevin, Prasanna, Ashreeta, Ramdas, Ashwin, Sekar, Ashok, and Sigrin, Ben. 2020.  
"Distributed Generation Market Demand (dGen) model".  United States.  doi:https://doi.org/10.25984/1804719.  https://www.osti.gov/servlets/purl/1804719. Pub date:Fri Oct 16 00:00:00 EDT 2020

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@article{osti_1804719,

  title        = {Distributed Generation Market Demand (dGen) model},

  author       = {Stanley, Trevor and Blair, Nate and Bowen, Thomas and Das, Paritosh and Koebrich, Sam and McCabe, Kevin and Prasanna, Ashreeta and Ramdas, Ashwin and Sekar, Ashok and Sigrin, Ben},

  abstractNote = {The Distributed Generation Market Demand (dGen) model simulates customer adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the United States or other countries through 2050. The dGen model can be used for identifying the sectors, locations, and customers for whom adopting DERs would have a high economic value, for generating forecasts as an input to estimate distribution hosting capacity analysis, integrated resource planning, and load forecasting, and for understanding the economic or policy conditions in which DER adoption becomes viable, and for illustrating sensitivity to market and policy changes such as retail electricity rate structures, net energy metering, and technology costs.},

  doi          = {10.25984/1804719},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Fri Oct 16 00:00:00 EDT 2020},

  month        = {Fri Oct 16 00:00:00 EDT 2020}

}

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DOI: https://doi.org/10.25984/1804719

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