Reference : Preventing Overloading Incidents on Smart Grids: A Multiobjective Combinatorial Optim...
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Computational Sciences
http://hdl.handle.net/10993/41329
Preventing Overloading Incidents on Smart Grids: A Multiobjective Combinatorial Optimization Approach
English
Antoniadis, Nikolaos mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Cordy, Maxime mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Sifaleras, Angelo mailto [University of Macedonia, Thessaloniki, Greece > Department of Applied Informatics > > Associate Professor of Mathematical Programming – Network Optimization]
Le Traon, Yves mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
15-Feb-2020
Communications in Computer and Information Science
Springer, Cham
vol 1173
269-281
Yes
International
978-3-030-41913-4
3rd International Conference on Optimization and Learning (OLA 2020)
from 17-02-2020 to 19-02-2020
University of Cadiz
Cadiz
Spain
[en] Smart grids ; Electrical safety ; Combinatorial Optimization ; Integer linear programming
[en] Cable overloading is one of the most critical disturbances that may occur in smart grids, as it can cause damage to the distribution power lines.
Therefore, the circuits are protected by fuses so that, the overload could trip the fuse, opening the circuit, and stopping the flow and heating. However, sustained overloads, even if they are below the safety limits, could also damage the wires. To prevent overload, smart grid operators can switch the fuses on or off to protect the circuits, or remotely curtail the over-producing/over-consuming users. Nevertheless, making the most appropriate decision is a daunting decision-making task, notably due to contractual and technical obligations. In this paper, we define and formulate the overloading prevention problem as a Multiobjective Mixed Integer Quadratically Constrained Program. We also suggest a solution method using a combinatorial optimization approach with a state-of-the-art exact solver. We evaluate this approach for this real-world problem together with Creos Luxembourg S.A., the leading grid operator in Luxembourg, and show that our method can suggest optimal countermeasures to operators facing potential overloading incidents.
http://hdl.handle.net/10993/41329
10.1007/978-3-030-41913-4_22

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