Problem class: LP, MIP, MINLP
The electricity generation sector in the U.S. is a major contributor of CO2 emissions. Thus emissions reductions from this sector will play a central role in any coordinated CO2 emission reduction effort aimed at combating climate change. One technology option that may help the electricity generation sector meet this challenge is carbon capture and storage (CCS). Carbon capture technologies can significantly reduce atmospheric emissions of CO2 from fossil fuel power plants. The captured CO2 is then transported through a network of pipelines and stored safely. A widespread deployment of these technologies is necessary to significantly reduce greenhouse gas emissions and contribute to a clean energy portfolio. But the deployment is both expensive and time-consuming: bringing such technologies online can take industries between 20 and 30 years.
The U.S. Department of Energy is using GAMS in two projects aimed at advancing carbon capture technologies. The NETL CO2 Capture, Transport, Utilization and Storage (CTUS) model optimizes potential networks of CO2 pipelines and storage infrastructure. The Carbon Capture Simulation Initiative (CCSI), founded by the U.S. Department of Energy, aims at making carbon capture technologies more easily available for industries. Their Optimization Toolset enables industry to rapidly assess and utilize these new technologies. GAMS is proud to be a part of these projects designed to make carbon capture a success.
The U.S. Department of Energy uses GAMS to analyze potential CO2 emission reduction scenarios in which CCS may play a role in meeting emission goals. The NETL CO2 Capture, Transport, Utilization and Storage (CTUS) model developed by the DOE National Energy Technology Laboratory is written in GAMS. It optimizes by minimizing the cost of the transport and storage network, via a mixed integer program (MIP), evaluating potential networks of CO2 pipelines and storage infrastructure amenable to handling the transport and storage of captured CO2 from the CCS enabled electricity sector. This type of problem was particularly well-suited for GAMS due to the volume of data processed, the solution methodology, the ability to integrate with other modeling platforms, and the stringent requirements for solve time required of this capability in order to eventually integrate into more holistic energy-economy models.
Thus far, the CTUS model has been integrated into the National Energy Modeling System (NEMS) and is also being integrated into the MARKAL energy model. When integrated into NEMS as the CTUS sub-module, a detailed portrayal of carbon capture and storage in energy economy projections is rendered. Through this capability, cost variability and capacity constraints are introduced into the energy-economy forecast as it considers CCS systems as an option in climate mitigation scenarios. This capability makes possible identification of location and time specific volumes of CO2 transported and stored throughout the projection period. A version of CTUS has been modified and incorporated into the U.S. Energy Information Administration’s (EIA’s) version of NEMS and is in turn used to produce the Annual Energy Outlook.
It is the express goal of the Carbon Capture Simulation Initiative to speed up the deployment process of carbon capture technologies. Founded by the U.S. Department of Energy in 2011, CCSI is a partnership among national laboratories, industry and academic institutions. The CCSI optimization toolset helps industry to develop and deploy advanced carbon capture and energy related technologies.
The technical and economic performance of a new technology is strongly dependent on its equipment configuration and operating conditions. Thus, to rigorously screen and evaluate new technologies, it is important to ensure that an optimal process is used. The optimization tools identify optimal equipment configurations and operating conditions for potential CO2 capture processes, thereby significantly reducing cost, time and risk involved in the implementation.
The CCSI research group has developed two advanced optimization capabilities as part of its Framework for Optimization and Quantification of Uncertainty and Surrogates (FOQUS) tool. Both utilize GAMS as an essential element. The first tool performs simultaneous process optimization and heat integration based on rigorous models. The heat integration subproblem is modeled in GAMS as LPs and MIPs and solved by CPLEX. The other tool optimizes the design and operation of a CO2 capture system. The carbon capture system is represented as a MINLP model, which is implemented in GAMS and solved by DICOPT or BARON. By identifying the optimal configurations and conditions for CO2 capture processes, these CCSI optimization tools allow more effective screening of materials and concepts for future technologies.
The CCSI toolset includes
- Rigorous process models.
- Framework for Optimization, Quantification of Uncertainty and Surrogates (FOQUS), which enables simulation-based process optimization, heat integration (GAMS), uncertainty quantification, generating algebraic surrogate models and building dynamic reduced models.
- Advanced superstructure optimization models (GAMS).
- Advanced process control framework.
- Data management framework.