Regensburg 2019 – scientific programme
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DY: Fachverband Dynamik und Statistische Physik
DY 46: Energy Networks (joint SOE/DY) (joint session SOE/DY)
DY 46.1: Talk
Thursday, April 4, 2019, 11:30–11:45, H17
Principal flow patterns across renewable electricity networks — •Mirko Schäfer1, Fabian Hofmann2, Johannes Kruse3, Tom Brown4,2, Jonas Hörsch4,2, Stefan Schramm2, and Martin Greiner3 — 1Department of Sustainable Systems Engineering (INATECH), Albert-Ludwigs-Universität Freiburg — 2Frankfurt Institute for Advanced Studies — 3Department of Engineering, Aarhus University, Denmark — 4Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology
Using Principal Component Analysis (PCA), the nodal injection and line flow patterns in a network model of a future highly renewable European electricity system are investigated. Remarkably, the application of PCA to the transmission line power flow statistics shows that irrespectively of the spatial scale of the system representation a very low number of only 8 principal flow patterns is sufficient to capture 95% of the corresponding spatio-temporal variance. This result can be theoretically explained by a particular alignment of some principal injection patterns with topological patterns inherent to the network structure of the European transmission system. By connecting these insights to a spectral clustering method it is shown how through topological changes the flow patterns on the network can be controlled.