Cryogenic air separation units (ASUs) are the most widely used technology for industrialscale
production of large amounts of high-purity air components. These are highly energyintensive
processes, which have motivated the development of demand response strategies
to adapt their operation in response to the increased volatility of the energy market. The
startup of ASUs warrants particular consideration within this context. ASUs are tightly
integrated, thermally and materially, and have slow dynamics. These result in startup
times on the order of hours to a day, during which electricity is consumed with limited
revenue generation. In the current environment of electricity price deregulation, it may be
economically advantageous for ASUs to shut down during periods of high electricity pricing,
increasing the occurrences of startups. This presents a promising research opportunity,
especially because ASU startup has received relatively little attention in the literature. This
thesis investigates the optimal startup of ASUs using dynamic optimization.
First, this thesis focuses on startup model development for the multiproduct ASU. Startup
model development requires accounting for discontinuities present at startup. Four main
discontinuities are considered: stage liquid flow discontinuity, stage vapor flow discontinuities,
flow liquid out of sumps and reboilers, and opening and closing valves. Other types of
discontinuities accounted for include the change in the number of phases of streams. These
discontinuities are approximated with smoothing formulations, using mostly hyperbolic tangent
functions, to allow application of gradient-based optimization. The modeling approach
was assessed through three case studies: dynamic simulation of a successful startup, dynamic
simulation of a failed startup, and dynamic optimization using a least-squares minimization
formulation.
Following startup model development, this thesis investigates the development of a framework
for optimizing ASU startups using readily interpretable metrics of time and economics.
For economics, cumulative profit over the startup horizon is considered. Two events are
tracked for the definition of time metrics: time taken to obtain product purities and time
to obtain steady-state product flows. Novel approaches are proposed for quantifying these
time metrics, which are used as objective functions and in formulating constraints. The / Thesis / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/29300 |
| Date | January 2023 |
| Creators | Quarshie, Anthony Worlanyo Kwaku |
| Contributors | Swartz, Christopher L. E., Chemical Engineering |
| Source Sets | McMaster University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
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