Morgan Kelley

  • Program Year: 4
  • Academic Institution: University of Texas at Austin
  • Field of Study: Process Systems
  • Academic Advisor: Michael Baldea
  • Practicum(s):
    Argonne National Laboratory (2018)
  • Degree(s):
    B.S. Chemical Engineering, Arizona State University, 2016

Summary of Research

As a Chemical Engineering PhD student in The University of Texas at Austin Process and Energy Systems Engineering lab who is advised by Dr. Michael Baldea and Dr. Ross Baldick, my research focuses on the modeling, simulation, and optimization of complex energy systems. The rates of power generation from wind and solar photovoltaics vary considerably during the day; they typically (and unfortunately) reach a low point in the late afternoon hours, when the power demand from commercial and residential consumers is at its peak. An increased reliance on renewable power generation carries an energy security risk, manifest in the advent of brown-outs or black-outs at times when supply cannot meet demand.
Grid-level electricity storage systems remain cost-prohibitive, and managing demand, rather than generation rates (referred to as demand response (DR)) has emerged as an approach of choice. DR utilizes large-scale computational approaches, optimizing consumer operations and minimizing electricity cost given energy prices over a time period, thereby lowering electricity usage during peak demand hours. Predictive modeling of energy generation and storage systems requires that phenomena with disparate time and space horizons (i.e. chemical reactions, matter transport, and hourly/daily/seasonal variations in renewable energy sources) are captured. Inevitably, the multiscale mathematical models required are large-scale, nonlinear and stiff, posing particularly difficult computational challenges for simulation and optimization.
The main challenges for my research therefore reside in finding computationally efficient model representations of chemical processes, which can be embedded in the modeling and optimization of energy systems. I am currently working on the modeling aspects of the problem, where I have developed model reformulation techniques that will allow me to express the DR scheduling problem as a mixed-integer linear program (MILP), as well as novel optimization algorithms that will allow for solving this problem in real time.


Kelley, M. T., Baldick, R., & Baldea, M. (2020). A Discrete Multiple Shooting Formulation for Efficient Dynamic Optimization. 30th European Symposium on Computer Aided Process Engineering (ESCAPE30). Aug, 2020, Milano, Italy. Accepted.

Kelley, M. T., Baldick, R. & Baldea, M. Demand response scheduling under uncertainty: Chance-constrained framework and application to an air separation unit. AIChE J. 66, (2020).

Kelley, M. T., Baldick, R. & Baldea, M. An empirical study of moving horizon closed-loop demand response scheduling. J. Process Control 92, 137-148 (2020).

Kelley, M. T., Baldick, R. & Baldea, M. A direct transcription-based multiple shooting formulation for dynamic optimization. Comput. Chem. Eng. 140, 106846 (2020).

Simkoff, J. M., Lejarza, F., Kelley, M. T., Tsay, C. & Baldea, M. Process Control and Energy Efficiency. Annu. Rev. Chem. Biomol. Eng. 11, 423-445 (2020).

Kelley, M. T., Baldick, R., & Baldea, M. (2019). Demand Response Operation of Electricity-Intensive Chemical Processes for Reduced Greenhouse Gas Emissions: Application to an Air Separation Unit. ACS Sustainable Chemistry & Engineering, 7(2), 1909-1922.

Kelley, M. T., Pattison, R. C., Baldick, R., & Baldea, M. (2018). An MILP framework for optimizing demand response operation of air separation units. Applied Energy, 222, 951-966.

Kelley, M. T., Pattison, R. C., Baldick, R., & Baldea, M. (2018). An efficient MILP framework for integrating nonlinear process dynamics and control in optimal production scheduling calculations. Computers & Chemical Engineering, 110, 35-52.

Chen, H.; Kelley, M.; Guo, C.; Yarger, J. L.; Dai, L. L. (2015). Adsorption and Release of Surfactant into and from Multifunctional Zwitterionic Poly(NIPAm-co-DMAPMA-co-AAc) Microgel Particles, J. Colloid Interface Sci., 449, 332-340. (Invited).

Zander, T.; Kelley, M.; Bankers, J.; Adson, K. 2016. Detergent Unit Doses and Methods of Producing the Same. US Patent Application #: 14/954,349 filed February, 2016 Patent Pending.


Best Paper Award, Computers in Chemical Engineering, 2018
University of Texas at Austin Dean's Prestigious Fellowship, 2017-2020
University of Texas at Austin Thrust Fellowship, 2016-2020
Honorable Mention National Science Graduate Research Fellowship, 2016
Goldwater Scholar, 2015-2016
Outstanding Graduate for the Ira. A. Fulton Schools of Engineering, 2016
Outstanding Graduate for the School for Engineering of Matter, Transport, and Energy, 2016
Outstanding Graduate for Chemical Engineering, 2016
Outstanding Honors Research for Barrett, the Honors College, 2016
Best Presentation, Gulf Coast Undergraduate Research Symposium for oral research presentation, 2016
Outstanding Team Leader, Engineering Projects in Community Service (EPICS), for leading other students to develop a sustainable energy system for schools in Fiji and Uganda, 2014
ASU/UA NASA Space Grant Fellow: 2015-2016. Year long research grant awarded to students in space-related research at Arizona State University and the University of Arizona.
Fulton Undergraduate Research Initiative Award: 2013, 2014, 2015. Year-long research grant awarded by the ASU Ira A. Fulton Schools of Engineering.
Gore Scholar, for research experience and academic achievements, 2014-2015
Dell Social Innovation Challenge Semi-Finalist for proposal of solar charging in Fijian schools, 2013
Global Impact Award, EPICS, for implementing sustainable energy system in Fiji, 2013
Grand Challenge Scholar for commitment to solving the NAE Grand Challenges, 2012-2016
Science, Math, and Engineering Competition Award (SMECA) recipient, 2012-2016
Arlo Richardson Endowed Fellowship from Arizona State University for National Center for Women & Information Technology (NCWIT) Award in 2012, 2012-2016
Regent High Honors Endorsement Tuition Waiver for excelling on standardized testing, 2012-2016
Ralph M. Knight Award for Chemical Engineering, for community service and academic achievements, 2012