Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/591
Title: Preventing overloading incidents on smart grids: A multiobjective combinatorial optimization approach
Authors: Antoniadis, Nikolaos
Cordy, Maxime
Sifaleras, Angelo
Le Traon, Yves
Editors: Dorronsoro, Bernabé
Ruiz, Patricia
de la Torre, Juan Carlos
Urda, Daniel
Talbi, El-Ghazali
Type: Book chapter
Subjects: FRASCATI::Natural sciences::Mathematics::Applied Mathematics
FRASCATI::Engineering and technology::Electrical engineering, Electronic engineering, Information engineering
Keywords: Smart grids
Electrical safety
Combinatorial optimization
Integer linear programming
Multiobjective optimization
Issue Date: 15-Feb-2020
Publisher: Springer
Volume: 1173
First Page: 269
Last Page: 281
Volume Title: Optimization and Learning
Part of Series: Communications in Computer and Information Science
Part of Series: Communications in Computer and Information Science
Abstract: 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.
URI: https://doi.org/10.1007/978-3-030-41913-4_22
https://ruomo.lib.uom.gr/handle/7000/591
ISBN: 978-3-030-41912-7
978-3-030-41913-4
ISSN: 1865-0929
1865-0937
Other Identifiers: 10.1007/978-3-030-41913-4_22
Appears in Collections:Department of Applied Informatics



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