Posts

Optimization of process families for improved deployment of industrial decarbonization processes using machine learning surrogates

Stinchfield, G., Ammari, B., Morgan, J. C., Siirola, J. D., Zamarripa, M. A., & Laird, C. D. (2023). Optimization of process families for improved deployment of industrial decarbonization processes using machine learning surrogates. In Kokossis, A., Georgiadis, M., & Pistikopoulos, S. (Eds.), 33rd European Symposium on Computer Aided Process Engineering. Elsevier.

Multi-scale modeling using IDAES

Burgard, A., Zitney, S, & Omell, B. (2023, April 18-20). Multi-scale modeling using IDAES [Conference presentation]. 2023 FECM / NETL Spring R&D Project Review Meeting, Pittsburgh, PA. https://www.osti.gov/biblio/1971246

NMPC for setpoint tracking operation of a solid oxide electrolysis cell system

Allan, D. A., Dabadghao, V., Li, M., Eslick, J. C., Ma, J., Bhattacharyya, D., Zitney, S. E., and Biegler, L. T. (2023, January 8-12). NMPC for setpoint tracking operation of a solid oxide electrolysis cell system [Paper presentation]. Foundations of Computer Aided Process Operations / Chemical Process Control (FOCAPO/CPC 2023), San Antonio, TX. https://www.osti.gov/biblio/1964151

An optimization model for expansion planning of reliable power generation systems

Cho, S. & Grossmann, I.E. (2022). An optimization model for expansion planning of reliable power generation systems. In L. Montastruc & S. Negny (Eds.), 32nd European symposium on Computer Aided Process Engineering (ESCAPE32), Computer-Aided Chemical Engineering, 51 (pp 841-846). Elsevier. https://doi.org/10.1016/B978-0-323-95879-0.50141-7

An optimization model for expansion planning of reliable power generation systems

Cho, S. & Grossmann, I. E. (2022). An optimization model for the design and operation of reliable power generation systems. In Y. Yamashita & M. Kano (Eds.), 14th International Symposium on Process Systems Engineering (PSE2021+), Computer Aided Chemical Engineering, 49 (pp. 709-714). Elsevier. https://doi.org/10.1016/B978-0-323-85159-6.50118-4

Estimating energy market schedules using historical price data

Cortes, N.P., Gao, X., Knueven, B. & Dowling, A.W. (2022) Estimating energy market schedules using historical price data. In Y. Yamashita & M. Kano (Eds.), 14th International Symposium on Process Systems Engineering (PSE2021+), Computer Aided Chemical Engineering, 49 (pp. 517-522). Elsevier. https://doi.org/10.1016/B978-0-323-85159-6.50086-5

A multi-scale modeling paradigm for energy system operation and design

Gao, X., & Dowling, A. W. (2021, November 7-11). A multi-scale modeling paradigm for energy system operation and design [Paper presentation]. 2021 AIChE Annual Meeting, Boston, MA. https://www.aiche.org/academy/conferences/aiche-annual-meeting/2021/proceeding/paper/182e-ow-multi-scale-modeling-for-energy-paradigm-energy-system-operation-and-design

Design centering through derivative-free optimization

Zhao, F., Grossmann, I. E., Garcia-Munoz, S., & Stamatis, S. D. (2021, November 7-11). Design centering through derivative-free optimization [Paper presentation]. 2021 AIChE Annual Meeting, Boston, MA.

Diagnostic tools for nonlinear algebraic models of dynamic chemical processes in Pyomo.Dae

Parker, R., Nicholson, B., Siirola, J., & Biegler L. T. (2021, November 7-11). Diagnostic tools for nonlinear algebraic models of dynamic chemical processes in Pyomo.Dae [Paper presentation]. 2021 AIChE Annual Meeting, Boston, MA. https://www.osti.gov/servlets/purl/1897361

Nonlinear model predictive control simulations of gas-solid reactors for chemical looping combustion of methane

Parker, R., & Biegler, L. T. (2021, November 7-11). Nonlinear model predictive control simulations of gas-solid reactors for chemical looping combustion of methane [Paper presentation]. 2021 AIChE Annual Meeting, Boston, MA. https://www.aiche.org/academy/conferences/aiche-annual-meeting/2021/proceeding/paper/492f-nonlinear-model-predictive-control-simulations-gas-solid-reactors-chemical-looping-combustion