Zusammenfassung
Das Straßenbeleuchtungsnetzwerk wird derzeit nur zur Beleuchtung verwendet. Zukünftige Strombedarfe im Niederspannungsnetz (LV), zum Beispiel E-Mobilität, legen es nah, das bestehende Netzwerk in einer verwalteten Weise für mehrere Anwendungen zu nutzen. Diese Verwaltung beruht jedoch auf detaillierten Kenntnissen der Netzwerktopologie, die aufgrund nicht verfolgter Änderungen nicht immer bekannt sind. Intelligente Lichtmasten, die Lasten messen und verwalten können, ermöglichen die Topologieerkennung. In dieser Arbeit wird eine automatische Methode zur Identifizierung von LV-Netzwerktopologien vorgestellt. Die Topologie wird durch Verbinden von Testlasten erkannt, während die gemessenen Spannungswerte über die Jenks Natural Breaks-Methode gruppiert werden und die Topologie mit dem Algorithmus rekonstruiert wird. Das Verfahren wurde mit einem PowerFactory-Modell evaluiert und erwies sich als eine robuste Methode. Die Methode stellt die Topologie dar und eignet sich als Input für Energiemanagementsysteme, sodass Lichtnetzwerke eine Plattform für Smart-City-Anwendungen werden können.
Abstract
The street lighting network is currently used only for illumination. Future electricity demands at the low voltage (LV) network, for example, e-mobility, suggests using the existing network in a managed way for multiple applications. This management relies on detailed knowledge of the network topology, which is not always known due to untracked changes. Intelligent lighting poles capable of measuring and managing loads allow for topology identification. In this work, an automatic method for identification of LV networks topology is presented. The topology is detected by connecting test loads, while the measured voltage values are clustered via Jenks Natural Breaks method, and the topology is reconstructed with the algorithm. The procedure is evaluated with a PowerFactory model and showed to be a robust method. The method proves to identify the topology and suitable as input for energy management systems, enabling lighting networks to become a platform for smart city applications.
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Acknowledgements
This work was carried out as part of the project, “Smarte Pfosten” (smart lamp post) and is funded by the ZIM program of the Federal Ministry for Economic Affairs (16KN062820).
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Ravanbach, B., Klement, P., Hanke, B., von Maydell, K. (2019). Automatic Topology Identification with Intelligent Lighting Poles. In: Marx Gómez, J., Solsbach, A., Klenke, T., Wohlgemuth, V. (eds) Smart Cities/Smart Regions – Technische, wirtschaftliche und gesellschaftliche Innovationen. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-25210-6_12
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