AN INTEGRATED MODELING FRAMEWORK FOR CARBON MANAGEMENT TECHNOLOGIES
CO{sub 2} capture and storage (CCS) is gaining widespread interest as a potential method to control greenhouse gas emissions from fossil fuel sources, especially electric power plants. Commercial applications of CO{sub 2} separation and capture technologies are found in a number of industrial process operations worldwide. Many of these capture technologies also are applicable to fossil fuel power plants, although applications to large-scale power generation remain to be demonstrated. This report describes the development of a generalized modeling framework to assess alternative CO{sub 2} capture and storage options in the context of multi-pollutant control requirements for fossil fuel power plants. The focus of the report is on post-combustion CO{sub 2} capture using amine-based absorption systems at pulverized coal-fired plants, which are the most prevalent technology used for power generation today. The modeling framework builds on the previously developed Integrated Environmental Control Model (IECM). The expanded version with carbon sequestration is designated as IECM-cs. The expanded modeling capability also includes natural gas combined cycle (NGCC) power plants and integrated coal gasification combined cycle (IGCC) systems as well as pulverized coal (PC) plants. This report presents details of the performance and cost models developed for an amine-based CO{sub 2} capture system, representing the baseline of current commercial technology. The key uncertainties and variability in process design, performance and cost parameters which influence the overall cost of carbon mitigation also are characterized. The new performance and cost models for CO{sub 2} capture systems have been integrated into the IECM-cs, along with models to estimate CO{sub 2} transport and storage costs. The CO{sub 2} control system also interacts with other emission control technologies such as flue gas desulfurization (FGD) systems for SO{sub 2} control. The integrated model is applied to study the feasibility and cost of carbon capture and sequestration at both new and existing PC plants as well as new NGCC plants. The cost of CO{sub 2} avoidance using amine-based CO{sub 2} capture technology is found to be sensitive to assumptions about the reference plant design and operation, as well as assumptions about the CO{sub 2} capture system design. The case studies also reveal multi-pollutant interactions and potential tradeoffs in the capture of CO{sub 2}, SO{sub 2}, NO{sub 2} and NH{sub 3}. The potential for targeted R&D to reduce the cost of CO{sub 2} capture also is explored using the IECM-cs in conjunction with expert elicitations regarding potential improvements in key performance and cost parameters of amine-based systems. The results indicate that the performance of amine-based CO{sub 2} capture systems can be improved significantly, and the cost of CO{sub 2} capture reduced substantially over the next decade or two, via innovations such as new or improved sorbents with lower regeneration heat requirements, and improvements in power plant heat integration to reduce the (currently large) energy penalty of CO{sub 2} capture. Future work will explore in more detail a broader set of advanced technology options to lower the costs of CO{sub 2} capture and storage. Volume 2 of this report presents a detailed User's Manual for the IECM-cs computer model as a companion to the technical documentation in Volume 1.
- Research Organization:
- Carnegie Mellon University (US)
- Sponsoring Organization:
- (US)
- DOE Contract Number:
- FC26-00NT40935
- OSTI ID:
- 836715
- Resource Relation:
- Other Information: PBD: 1 Mar 2004
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
03 NATURAL GAS
20 FOSSIL-FUELED POWER PLANTS
29 ENERGY PLANNING
POLICY AND ECONOMY
CARBON
CARBON SEQUESTRATION
COAL GASIFICATION
COMBINED CYCLES
CONTROL SYSTEMS
ELECTRIC POWER
FLUE GAS
FOSSIL FUELS
FOSSIL-FUEL POWER PLANTS
GREENHOUSE GASES
MANAGEMENT
NATURAL GAS
POWER GENERATION
POWER PLANTS