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@PHDTHESIS{Voll:228954,
author = {Voll, Philip},
othercontributors = {Bardow, André},
title = {{A}utomated optimization based synthesis of distributed
energy supply systems; 1. {A}ufl.},
volume = {1},
address = {Aachen},
publisher = {Mainz},
reportid = {RWTH-CONV-143971},
isbn = {978-3-86130-474-6},
series = {Aachener Beiträge zur technischen Thermodynamik},
pages = {XXII, 185 S. : Ill., graph. Darst.},
year = {2014},
note = {Druckausg. ersch. im Buchhandel als Bd. 1 der Reihe des
Instituts für Technische Thermodynamik: Aachener Beiträge
zur Technischen Thermodynamik. - Druckausg.: Voll, Philip:
Automated optimization based synthesis of distributed energy
supply systems; Aachen, Techn. Hochsch., Diss., 2013},
abstract = {The conceptual synthesis of distributed energy supply
systems (DESS) is an inherently challenging problem that is
characterized by time-dependent constraints (e.g., energy
demands, ambient temperatures curves, etc.), economy of
scale of equipment investment, limited capacities of
standardized equipment, and part-load performance
characteristics of the considered energy conversion units.
Moreover, for optimal DESS synthesis, multiple redundant
units are generally to be expected. Optimization-based
synthesis methods offer great potentials for the synthesis
of cost-effective, energy-efficient, and sustainable
systems. However, a lack of adequate, user-friendly methods
has so far hindered routine application of optimization in
engineering practice. In research, most commonly,
superstructure-based synthesis is performed for optimal
systems synthesis. In this approach, a user-defined
superstructure is analyzed using mathematical programming
techniques to identify the optimal solution among the
alternatives encoded in the superstructure. Current
optimization software facilitates the use of
superstructure-based synthesis, e.g., by enabling easy
problem definition through graphical superstructure
modeling. However, the a priori definition of the
superstructure remains a serious obstacle for the use of
superstructure-based synthesis in industrial practice: On
the one hand, the manual superstructure definition bears the
risk to exclude the optimum from consideration; on the other
hand, the use of excessively large superstructures causes
prohibitively large computational effort. To circumvent
these drawbacks, superstructure-generation methods and
superstructure-free synthesis methods have been proposed.
Superstructure-generation methods automatically define a
superstructure for a given synthesis problem.
Superstructure-free methods avoid the use of a
superstructure by enabling simultaneous alternatives
generation and optimization. Available approaches involve
several drawbacks that impede their use for the optimal
synthesis of distributed energy supply systems:
Superstructure-generation methods neglect major DESS
characteristics; superstructure-free methods require the
manual definition of many technology-specific replacement
rules, which is equally difficult as the definition of an
appropriate superstructure. In this thesis, two novel
synthesis methodologies are proposed to facilitate the use
of optimization for efficient and reliable DESS synthesis,
thus making optimization accessible for practitioners: The
automated superstructure-based and the superstructure-free
synthesis methodology. The proposed methodologies avoid both
the a priori definition of a superstructure and the manual
definition of many technology-specific replacement rules
while accounting for the major characteristics inherent to
DESS synthesis problems. The superstructure-based framework
relies on an algorithm for automated
superstructure-generation. The method employs a successive
superstructure expansion and optimization strategy that
continuously increases the number of units included in the
superstructure until the optimal solution is identified. The
superstructure-free approach combines evolutionary
optimization and deterministic optimization for simultaneous
alternatives generation and optimization. A
knowledge-integrated mutation operator is proposed that
relies on a hierarchically-structured graph, the so-called
energy conversion hierarchy (ECH). The ECH efficiently
defines all reasonable replacement rules, thus avoiding
their manual definition. The mutation operator performs
structural replacements for the evolutionary generation of
solution alternatives. Both synthesis methodologies use a
generic component-based modeling framework, thus making the
methodologies independent of the employed mathematical
programming formulation. In this thesis, a robust MILP
formulation is used that allows to simultaneously optimize
the structure, sizing, and operation of distributed energy
supply systems accounting for time-varying load profiles,
continuous equipment sizing, economy of scale of equipment
investment, and part-load equipment performance. In this
thesis, it is shown that both synthesis methodologies
proposed in this thesis enable practitioners to perform
optimization-based synthesis of distributed energy supply
systems. It should be pointed out that the use of the
proposed synthesis methodologies only requires
energy-related expert knowledge that is usually prevailing
among engineers active in the field of energy systems
synthesis. In particular, no expert knowledge on
mathematical programming is required. Finally, this thesis
provides the foundation for future research as discussed in
the next section. Last but not least, based on the
experience gained during the work on this thesis, the author
comments on the necessity of optimization for the conceptual
DESS synthesis.},
keywords = {Optimierung (SWD) / Energieversorgung (SWD) / Entwurf
(SWD)},
cin = {412110},
ddc = {620},
cid = {$I:(DE-82)412110_20140620$},
shelfmark = {ZP 2900},
typ = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
urn = {urn:nbn:de:hbz:82-opus-49136},
url = {https://publications.rwth-aachen.de/record/228954},
}
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