Abstract
The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.
- Developers:
-
Guerra Fernandez, Omar Jose [1] ; Koleva, Mariya [1] ; Eichman, Joshua [1] ; Townsend, Aaron [1]
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Release Date:
- 2020-06-23
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Programming Languages:
-
GAMS
Batchfile
MATLAB
Python
Python
- Licenses:
-
BSD 3-clause "New" or "Revised" License
- Sponsoring Org.:
-
California Air Resources BoardUSDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Fuel Cell Technologies OfficePrimary Award/Contract Number:AC36-08GO28308
- Code ID:
- 45155
- Site Accession Number:
- SWR-20-67
- Research Org.:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Country of Origin:
- United States
Citation Formats
Guerra Fernandez, Omar Jose, Koleva, Mariya, Eichman, Joshua, and Townsend, Aaron.
RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67].
Computer Software.
https://github.com/NREL/RODeO.
California Air Resources Board, USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Fuel Cell Technologies Office.
23 Jun. 2020.
Web.
doi:10.11578/dc.20211029.3.
Guerra Fernandez, Omar Jose, Koleva, Mariya, Eichman, Joshua, & Townsend, Aaron.
(2020, June 23).
RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67].
[Computer software].
https://github.com/NREL/RODeO.
https://doi.org/10.11578/dc.20211029.3.
Guerra Fernandez, Omar Jose, Koleva, Mariya, Eichman, Joshua, and Townsend, Aaron.
"RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]." Computer software.
June 23, 2020.
https://github.com/NREL/RODeO.
https://doi.org/10.11578/dc.20211029.3.
@misc{
doecode_45155,
title = {RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]},
author = {Guerra Fernandez, Omar Jose and Koleva, Mariya and Eichman, Joshua and Townsend, Aaron},
abstractNote = {The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.},
doi = {10.11578/dc.20211029.3},
url = {https://doi.org/10.11578/dc.20211029.3},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20211029.3}},
year = {2020},
month = {jun}
}