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@PHDTHESIS{Dognini:994701,
author = {Dognini, Alberto},
othercontributors = {Monti, Antonello and Ulbig, Andreas},
title = {{M}ulti-criteria service restoration methods for {AC} and
{AC}/{DC} distribution grids; 1. {A}uflage},
volume = {132},
school = {RWTH Aachen University},
type = {Dissertation},
address = {Aachen},
publisher = {E.ON Energy Research Center, RWTH Aachen University},
reportid = {RWTH-2024-09488},
isbn = {978-3-948234-46-1},
series = {E.On Energy Research Center},
pages = {1 Online-Ressource : Illustrationen},
year = {2024},
note = {Druckausgabe: 2024. - Auch veröffentlicht auf dem
Publikationsserver der RWTH Aachen University; Dissertation,
RWTH Aachen University, 2024},
abstract = {The continuous increase of electrical energy demand, driven
by technological advancements as well as the proliferation
of electric devices, and the dissemination of Distributed
Energy Resources (DER) are posing unprecedented challenges
to the distribution grids, like the greater risk of fault
occurrences. In this regard, the enhancement of self-healing
features of distribution networks, consisting of smart
automated responses to faults, addresses the growing
requirements for reliability and quality of supply. Anyway,
the existing Service Restoration (SR) algorithms need more
sophisticated approaches to properly exploit the
capabilities of remotely controllable devices, entail the
behavior of DER components in fault conditions, and
implement solutions in line with the complex, multiple
objectives posed by grid operators. Additionally, specific
attention is placed on the increasing likelihood of
disasters (i.e., wide area blackouts, potentially caused by
extreme weather events, cyberattacks, and other threats)
that can cause extended and multiple outages in different
areas of the power systems. Moreover, the design of SR
approaches for modern distribution networks has to confront,
as a novel layer of complexity, the increasing role of DC
technology. In fact, the AC/DC distribution grids are
gaining a consistent research interest; they are constituted
by DC lines, which link DC-based generators and loads, to
interconnect the AC distribution feeders. Further
characterizations are needed for the protection schemes of
AC/DC distribution grids, which must include the control of
power converters to optimize the power transfer among AC and
DC sub-networks. This dissertation analyzes the design and
deployment of SR algorithms, according to the main
requirements described hereafter. 1. The determination of
restoration solutions based on the grid conditions preceding
the fault repair: on the one hand, the SR shall account for
unstable conditions typical of High Impact Low Probability
(HILP) events; on the other hand, the power flow in the
hours following the SR must be considered. 2. The
combination of multiple SR objectives: the computation of
the SR solution depends on various goals, defined by grid
operators to enhance the energy management, which must be
merged together while maintaining their mathematical
consistency. 3. The suitability for AC/DC distribution
grids: the optimized role of DC sub-networks and AC/DC
converters has to be included in the SR process. Based on
the requirements depicted in the previous section, specific
algorithms for SR have been developed and tested, leading to
the following scientific contributions. An SR algorithm for
AC distribution grids at the Medium Voltage (MV) level is
proposed, corresponding to the first contribution. Its
deployment entails the specific conditions of HILP events
(addressing to the first requirement), which are
characterized by grid instability due to multiple and
subsequent faults that involve large grid portions. The
algorithm deploys a state estimator, combining real-time
measurements from field devices with forecasts, to assess
the feasibility of SR candidate solutions. To overcome the
computational weaknesses introduced by the weighted-sum
technique, normally deployed by the SR algorithms present in
the literature, in the multi-objective optimization (related
to the second requirement), a Multiple-Criteria Decision
Analysis (MCDA) technique is implemented: it is based on, as
a first step, the pair-wise comparison of criteria and, as a
second step, the calculation of the Euclidean distances
between each SR candidate solution and the ideal solutions.
The second contribution corresponds to a SR algorithm for
AC/DC distribution grids at the MV level (with respect to
the third requirement). The computation of network
reconfiguration solutions includes the opening of
normally-closed switches, in addition to the closing of
normally-open switches, and accounts for the calculated
priorities of the de-energized buses. Being specifically
designed for AC/DC networks, the algorithm integrates a
convexified optimal power flow that strengthens the SR
performance by optimizing the operational control of DER and
AC/DC converters. The MCDA technique is integrated into this
SR algorithm to determine, among the feasible candidates,
the near-optimal SR solution. The considered criteria
consist of: (i) the minimization of power losses in the
network, (ii) the employment of remotely controllable
switches, and (iii) the applicability of the proposed SR
solution at the long term (in the time period preceding the
fault reparation, according to the first requirement) by
considering generation and loads forecasts. As a third
contribution, the two SR algorithms are deployed as
microservices in dedicated energy platforms. In addition to
the real-time grid simulator, multi-vendor protection relays
are integrated in the setup to perform the
Hardware-in-the-Loop (HiL) validation tests. On the one
hand, the SR for AC distribution grids is implemented in a
cloud-based energy platform with a context broker as a
central component; on the other hand, the automation system
that hosts the SR for AC/DC distribution grids includes
several communication gateways to manage the standard
communication protocols. The validation results confirm the
applicability of the proposed SR algorithms in automation
systems of electrical distribution grids.},
cin = {616310 / 080052},
ddc = {621.3},
cid = {$I:(DE-82)616310_20140620$ / $I:(DE-82)080052_20160101$},
typ = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
doi = {10.18154/RWTH-2024-09488},
url = {https://publications.rwth-aachen.de/record/994701},
}
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