The Distributed Energy Resources Customer Adoption Model (DER-CAM)
DER CAM is a decision support model developed by Lawrence Berkeley National Laboratory to identify optimal combinations of distributed energy resources (e.g., solar PV, battery storage, CHP, and demand response) for buildings or multi-energy microgrids. Given load profiles, utility rates, and technology costs, DER CAM determines the DER mix, size, and operating schedule that minimize costs or emissions while meeting reliability requirements. Version 5.9 introduces features like wholesale market integration, modeling of generator aging, and improved representation of solar thermal systems. The tool helps facility managers, utilities, and planners evaluate investment decisions and design resilient, cost effective microgrids.
Citation Formats
TY - DATA
AB - DER CAM is a decision support model developed by Lawrence Berkeley National Laboratory to identify optimal combinations of distributed energy resources (e.g., solar PV, battery storage, CHP, and demand response) for buildings or multi-energy microgrids. Given load profiles, utility rates, and technology costs, DER CAM determines the DER mix, size, and operating schedule that minimize costs or emissions while meeting reliability requirements. Version 5.9 introduces features like wholesale market integration, modeling of generator aging, and improved representation of solar thermal systems. The tool helps facility managers, utilities, and planners evaluate investment decisions and design resilient, cost effective microgrids.
AU - Laboratory, National
DB - C-MIX - Community Microgrid Information Exchange
DP - Open EI | National Laboratory of the Rockies
DO -
KW - Battery energy storage
KW - Solar
KW - Photovoltaics
KW - PV
KW - Diesel generators
KW - Other liquid-fuel generators
KW - Wind energy
KW - Financing
KW - Business models
KW - Utility integration
KW - Bulk-system Integration
KW - Maintenance and operations
KW - Operations
KW - Maintenance
KW - Commissioning
LA - English
DA - 2025/01/01
PY - 2025
PB - Lawrence Berkeley National Laboratory
T1 - The Distributed Energy Resources Customer Adoption Model (DER-CAM)
UR - https://cmix.openei.org/submissions/264
ER -
Laboratory, National. The Distributed Energy Resources Customer Adoption Model (DER-CAM). Lawrence Berkeley National Laboratory, 1 January, 2025, C-MIX - Community Microgrid Information Exchange. https://cmix.openei.org/submissions/264.
Laboratory, N. (2025). The Distributed Energy Resources Customer Adoption Model (DER-CAM). [Data set]. C-MIX - Community Microgrid Information Exchange. Lawrence Berkeley National Laboratory. https://cmix.openei.org/submissions/264
Laboratory, National. The Distributed Energy Resources Customer Adoption Model (DER-CAM). Lawrence Berkeley National Laboratory, January, 1, 2025. Distributed by C-MIX - Community Microgrid Information Exchange. https://cmix.openei.org/submissions/264
@misc{CMIX_Dataset_264,
title = {The Distributed Energy Resources Customer Adoption Model (DER-CAM)},
author = {Laboratory, National},
abstractNote = {DER CAM is a decision support model developed by Lawrence Berkeley National Laboratory to identify optimal combinations of distributed energy resources (e.g., solar PV, battery storage, CHP, and demand response) for buildings or multi-energy microgrids. Given load profiles, utility rates, and technology costs, DER CAM determines the DER mix, size, and operating schedule that minimize costs or emissions while meeting reliability requirements. Version 5.9 introduces features like wholesale market integration, modeling of generator aging, and improved representation of solar thermal systems. The tool helps facility managers, utilities, and planners evaluate investment decisions and design resilient, cost effective microgrids.},
url = {https://cmix.openei.org/submissions/264},
year = {2025},
howpublished = {C-MIX - Community Microgrid Information Exchange, Lawrence Berkeley National Laboratory, https://cmix.openei.org/submissions/264},
note = {Accessed: 2026-08-06}
}
Details
Data from Jan 1, 2025
Last updated Mar 30, 2026
Submitted Jun 2, 2026
Organization
Lawrence Berkeley National Laboratory
Contact
Nicholas DeForest
Authors
