@inproceedings{1b7cca7b4b5b4120bd73f7dd8b93c5a2,
title = "The maximum transmission switching flow problem",
abstract = "The Maximum Transmission Switching Flow (MTSF) is the problem of maximizing the power flow of a power grid by switching off lines. This static transmission design problem is known to be NP-hard even on strongly restricted graph classes. In this paper, we study the combinatorial structure of the MTSF problem and its relationship to familiar problems. We tackle the problem by exploiting the structure of the power grid leading to the first algorithms for MTSF having provable performance guarantees. We decrease the theoretical gap not only by developing algorithms with guarantees, but also by proving that the decision problem of MTSF is NP-hard even when the network contains only one generator and one load. In this context, we introduce the Dominating Theta Path, which is an exact algorithm on certain graph structures and can be used as a switching metric in general. Our simulations show that the algorithms provide very good results (in many cases near-optimal) on the NESTA benchmark cases that provide realistic thermal line limits.",
keywords = "Approximation, Graph algorithms, Topology optimization, Transmission network control, Transmission switching",
author = "Alban Grastien and Ignaz Rutter and Dorothea Wagner and Franziska Wegner and Matthias Wolf",
note = "Publisher Copyright: {\textcopyright} 2018 Association for Computing Machinery.; 9th ACM International Conference on Future Energy Systems, e-Energy 2018 ; Conference date: 12-06-2018 Through 15-06-2018",
year = "2018",
month = jun,
day = "12",
doi = "10.1145/3208903.3208910",
language = "English",
series = "e-Energy 2018 - Proceedings of the 9th ACM International Conference on Future Energy Systems",
publisher = "Association for Computing Machinery (ACM)",
pages = "340--360",
booktitle = "e-Energy 2018 - Proceedings of the 9th ACM International Conference on Future Energy Systems",
address = "United States",
}