Overview

This presentation will explore how decades of research in systems and control engineering can contribute to ongoing decarbonization efforts and the broader energy transition. 

Two key approaches from process systems engineering and control research will be concentrated: superstructure model-based optimization and stochastic optimal control. The speaker will discuss how we assess various CCUS technological strategies, focusing on their economic viability and potential for meaningful CO2 reduction. This evaluation involves techno-economic assessment (TEA) and life cycle analysis (LCA), where material and energy flows for different CCUS options are modelled through a superstructural framework.

Further, he will examine how the deployment planning of CCUS and green hydrogen production, amid the variabilities of renewable energy sources and prevailing uncertainties in technological and socioeconomic aspects, leads to a complex, multi-scale, multi-stage stochastic decision-making problem.

Speaker

Jay Lee, Choong Hoon Cho Chair and Professor, University of Southern California

Jay received his PhD degree in chemical engineering from Caltech in 1991. After having been a faculty member of various universities, including Auburn, Purdue, Georgia Tech, and KAIST, he is currently a Choong Hoon Cho Chair and Professor of Mork Family Department of Chemical Engineering and Materials Science at University of Southern California (USC).

From 2013-2023, he served as the founding director of Aramco-KAIST CO2 Management Center. He is a fellow of IEEE, IFAC and AIChE. He is a recipient of many awards including NSF Young Investigator Award, AIChE’s Computing in Chemical Engineering Award, and Roger Sargent’s Lectureship. He published ~300 manuscripts in SCI journals with more than 22000 citations. His research interests are in the areas of model-based control and machine learning with applications to energy transition and sustainability.

The material presented has not been peer-reviewed. Any opinions are the presenter’s own and do not necessarily represent those of IChemE or the Computer Aided Process Engineering Special Interest Group. The information is given in good faith but without any liability on the part of IChemE.

Time

08:00 –09:00 PDT. / 16:00 –17:00 BST.

Software

The presentation will be delivered via Microsoft Teams. We recommend downloading the app from the Microsoft website, rather than using the web portal.