John C. Eslick

Simultaneous process optimization and heat integration based on rigorous process simulations

Abstract This paper introduces a simultaneous process optimization and heat integration approach, which can be used directly with the rigorous models in process simulators. In this approach, the overall process is optimized utilizing external derivative-free optimizers, which interact directly with the process simulation. The heat integration subproblem is formulated as an LP model and solved simultaneously during optimization of the flowsheet to update the minimum utility and heat exchanger area targets. A piecewise linear approximation for the composite curve is applied to obtain more accurate heat integration results. This paper describes the application of this simultaneous approach for three cases: a recycle process, a separation process and a power plant with carbon capture. Case study results indicate that this simultaneous approach is relatively easy to implement and achieves higher profit and lower operating cost and, in the case of the power plant example, higher net efficiency than the sequential approach.

Advanced computational tools for optimization and uncertainty quantification of carbon capture processes

Advanced multi-scale modeling and simulation has the potential to dramatically reduce development time, resulting in considerable cost savings. The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and universities that is developing, demonstrating, and deploying a suite of multi-scale modeling and simulation tools. One significant computational tool is FOQUS, a Framework for Optimization and Quantification of Uncertainty and Sensitivity, which enables basic data submodels, including thermodynamics and kinetics, to be used within detailed process models to rapidly synthesize and optimize a process and determine the level of uncertainty associated with the resulting process. The overall approach of CCSI is described with a more detailed discussion of FOQUS and its application to carbon capture systems.

Simultaneous Optimization and Heat Integration Based on Rigorous Process Simulations

Abstract This paper introduces a novel simultaneous optimization and heat integration approach, which can be used directly with the rigorous models in process simulators. The approach is based on the formulation of Papoulias and Grossmann (1983), in which heat integration is formulated as a LP transshipment model and solved simultaneously during optimization of the flowsheet. In this case, the overall process is optimized utilizing external derivative free optimizers (DFOs), which interact directly with the process simulation. Heating and cooling loads are transferred to the heat integration module and solved for each iteration of the DFO to update the minimum utility targets. The heat integration subproblem is solved via calls to GAMS. This approach has been implemented and demonstrated within the Carbon Capture Simulation Initiative’s Framework for Optimization and Quantification of Uncertainty and Sensitivity (FOQUS). This paper describes the automated heat integration capabilities and demonstrates its application for integrating a post-combustion carbon capture and compression system with a supercritical pulverized coal power plant. The case study results indicate that this simultaneous approach is relatively easy to implement and achieves higher net power plant efficiency than the sequential approach.

Multi-objective Optimization of Membrane-based CO2 Capture

Abstract This work presents a multi-objective optimization framework that uses a nonlinear programming (NLP) mathematical model for the optimal design and operation of membrane-based post combustion CO2 capture plants. The proposed approach provides advanced decision-making tools for the power generation industry, involving the simultaneous optimization of alternative process configurations and operating conditions while analyzing different objectives such as cost of electricity and carbon capture target. The proposed approach was demonstrated with a case study from the literature and the mathematical model has been validated against a rigorous simulation model. Results show how the optimal flowsheet changes with different objectives.

Data management and simulation support accelerating carbon capture through computing

The Carbon Capture Simulation Initiative (CCSI) project has developed and deployed scientific infrastructure called the CCSI Toolset. The CCSI Toolset provides state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. Carbon capture technologies have the potential to dramatically reduce the carbon emissions from power plants. The CCSI Toolset provides end users in industry with a comprehensive, integrated suite of leading-edge, scientifically validated models with simulation, uncertainty quantification, optimization, risk analysis and decision making support. The CCSI Toolset has at its core an integrated framework that enables execution of simulations and workflows including optimization and uncertainty parameter sweeps using a wide variety of computing platforms including desktops, clusters, Clouds, and HPC systems. The integration framework enables the running of a variety of commercial process simulation packages as well as custom simulators. Moreover, the framework enables scientists to run and manage thousands of concurrent simulations to perform optimizations and uncertainty quantification. Components of the CCSI Toolset are connected through the use of a data management system that stores data to a repository and enables the tracking of provenance for each simulation as well as its associated components. The data management system tracks all the configurations, models, simulations, and results created during the design of a carbon capture system and supports the design life-cycle as well as decision making. The primary contribution of this paper is thus the design and implementation of the integration framework within the CCSI Toolset, which provides both data management and simulation support for CCSI. This integration framework has been deployed and is in use by several groups of researchers and commercial entities.