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@PHDTHESIS{ElWajeh:1009405,
author = {El Wajeh, Mohammad},
othercontributors = {Mitsos, Alexander and Swartz, Christopher L. E.},
title = {{O}ptimal dynamic operation of electrified biodiesel
production},
volume = {36},
school = {Rheinisch-Westfälische Technische Hochschule Aachen},
type = {Dissertation},
address = {Aachen},
publisher = {RWTH Aachen University},
reportid = {RWTH-2025-03483},
series = {Aachener Verfahrenstechnik series - AVT.SVT - Process
systems engineering},
pages = {1 Online-Ressource : Illustrationen},
year = {2025},
note = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
University; Dissertation, Rheinisch-Westfälische Technische
Hochschule Aachen, 2025},
abstract = {The flexible operation of electrified chemical processes
powered by renewable electricity offers both economic and
ecological benefits, contributing to more sustainable
chemical production. However, transitioning from
conventional steady-state operations presents a significant
challenge to process design and operation. While this change
in operational paradigm paves the way for achieving optimal
flexible operation and effective demand-side management, it
also necessitates incorporating process dynamics into
scheduling decisions to ensure both optimal and feasible
outcomes. This is particularly relevant for chemical plants,
such as biodiesel production processes, which operate on
time scales comparable to fluctuations in electricity
prices. In this dissertation, we develop and implement
modeling- and optimization-based methods and tools to
address key aspects of optimal dynamic operations in
electrified chemical processes. We develop and apply a
modeling and optimization framework that guides process
systems through essential stages to achieve the final goal
of optimal flexible operation for an electrified biodiesel
production process. The dissertation chapters are structured
around these main stages, beginning with model development,
followed by electrification and offline optimization with
process design considerations, and concluding with online
control. We begin with the model development phase, where we
introduce a rigorous mechanistic dynamic model of the
biodiesel production process, along with two plantwide
base-layer control structures. We simulate plant responses
under various disturbances to highlight the necessity of
model-based control strategies in meeting operational goals.
This model serves as the foundation for the subsequent
chapters. Moving to the offline optimization stage, we
formulate dynamic optimization problems that incorporate
flexibility-oriented process designs. We demonstrate the
dual role of buffer tanks for storing intermediate and final
products, which not only enhance operational flexibility but
also enable system decomposition for distributed
optimization by decoupling dynamics between different
process sections. Additionally, we explore the impact of
heat integration on operational flexibility and demonstrate
how incorporating additional electrified heating units
increases the degrees of freedom in optimization. Building
on the offline studies and flexibility-oriented process
configurations, we then move to the final stage—online
control—where we implement real-time control applications.
In particular, we leverage the process configuration that
supports distributed optimization to develop and apply
distributed economic nonlinear model predictive control. Our
distributed control strategies incorporate both sequential
and iterative communication architectures, as well as
compensation schemes for computational delays. These schemes
account for subsystem couplings and delays across multiple
sampling intervals. By systematically progressing through
these three stages, we achieve the final objective of
optimal and feasible flexible operation for chemical
processes. This dissertation not only demonstrates the
interconnectivity between these stages during both
development and implementation but also provides methods and
tools with broad applicability to other chemical processes
targeting optimal dynamic operations.},
cin = {416710},
ddc = {620},
cid = {$I:(DE-82)416710_20140620$},
pnm = {BMBF 03SFK3L1 - Kopernikus-Projekt SynErgie (03SFK3L1)},
pid = {G:(DE-82)03SFK3L1},
typ = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
doi = {10.18154/RWTH-2025-03483},
url = {https://publications.rwth-aachen.de/record/1009405},
}
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