Cost and Performance Assumptions for Modeling Electricity Generation Technologies
Abstract
The goal of this project was to compare and contrast utility scale power plant characteristics used in data sets that support energy market models. Characteristics include both technology cost and technology performance projections to the year 2050. Cost parameters include installed capital costs and operation and maintenance (O&M) costs. Performance parameters include plant size, heat rate, capacity factor or availability factor, and plant lifetime. Conventional, renewable, and emerging electricity generating technologies were considered. Six data sets, each associated with a different model, were selected. Two of the data sets represent modeled results, not direct model inputs. These two data sets include cost and performance improvements that result from increased deployment as well as resulting capacity factors estimated from particular model runs; other data sets represent model input data. For the technologies contained in each data set, the levelized cost of energy (LCOE) was also evaluated, according to published cost, performance, and fuel assumptions.
- Authors:
-
- ICF International, Fairfax, VA (United States)
- Publication Date:
- Research Org.:
- ICF International, Fairfax, VA (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Analysis (EI-30) (Energy Analysis Corporate)
- OSTI Identifier:
- 1219277
- Report Number(s):
- NREL/SR-6A20-48595
5248
- DOE Contract Number:
- AC36-08GO28308
- Resource Type:
- Technical Report
- Country of Publication:
- United States
- Language:
- English
- Subject:
- cost and performance; electricity generation; power plants; utility scale; data; model inputs; model results; learning by doing; capacity factors; levelized cost of energy (LCOE); NEMS; National Energy Modeling System; EIA; Energy Information Administration; MARKAL; Market Allocation International Energy Agency; ReEDS; Regional Energy Deployment System; MiniCAM; Mini Climate Assessment Model; IPM; Integrated Planning Model; MERGE; Model for Estimating the Regional and Global Effects of Greenhouse Gas Reductions
Citation Formats
Tidball, Rick, Bluestein, Joel, Rodriguez, Nick, and Knoke, Stu. Cost and Performance Assumptions for Modeling Electricity Generation Technologies. United States: N. p., 2010.
Web. doi:10.2172/1219277.
Tidball, Rick, Bluestein, Joel, Rodriguez, Nick, & Knoke, Stu. Cost and Performance Assumptions for Modeling Electricity Generation Technologies. United States. https://doi.org/10.2172/1219277
Tidball, Rick, Bluestein, Joel, Rodriguez, Nick, and Knoke, Stu. 2010.
"Cost and Performance Assumptions for Modeling Electricity Generation Technologies". United States. https://doi.org/10.2172/1219277. https://www.osti.gov/servlets/purl/1219277.
@article{osti_1219277,
title = {Cost and Performance Assumptions for Modeling Electricity Generation Technologies},
author = {Tidball, Rick and Bluestein, Joel and Rodriguez, Nick and Knoke, Stu},
abstractNote = {The goal of this project was to compare and contrast utility scale power plant characteristics used in data sets that support energy market models. Characteristics include both technology cost and technology performance projections to the year 2050. Cost parameters include installed capital costs and operation and maintenance (O&M) costs. Performance parameters include plant size, heat rate, capacity factor or availability factor, and plant lifetime. Conventional, renewable, and emerging electricity generating technologies were considered. Six data sets, each associated with a different model, were selected. Two of the data sets represent modeled results, not direct model inputs. These two data sets include cost and performance improvements that result from increased deployment as well as resulting capacity factors estimated from particular model runs; other data sets represent model input data. For the technologies contained in each data set, the levelized cost of energy (LCOE) was also evaluated, according to published cost, performance, and fuel assumptions.},
doi = {10.2172/1219277},
url = {https://www.osti.gov/biblio/1219277},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Nov 01 00:00:00 EDT 2010},
month = {Mon Nov 01 00:00:00 EDT 2010}
}