Authors: Surmann, Dirk
Ligges, Uwe
Weihs, Claus
Title: Predicting Measurements at Unobserved Locations in an Electrical Transmission System
Language (ISO): en
Abstract: Electrical Transmission Systems consist of a huge number of locations (nodes) with different types of measurements available. Our aim is to derive a subset of nodes which contains almost sufficient information to describe the whole energy network. We derive a parameter set which characterises every single measuring location or node, respectively. Via analysing the behaviour of each node with respect to its neighbours, we construct a feasible random field metamodel over the whole transmission system. The metamodel works in a discrete spatial domain to smooth the measurements across the network. In the next step we work with a subset of locations to predict the unobserved ones. We derive different graph kernels to define the missing covariance matrix from the neighbourhood structures of the network. This results in a metamodel that is able to predict unobserved locations in a spatial domain with non-isotropic distance functions.
Subject Headings: Measurement Prediction
Discrete Random Field Model
Graph Kernels
URI: http://hdl.handle.net/2003/34441
http://dx.doi.org/10.17877/DE290R-16497
Issue Date: 2016-01-06
Appears in Collections:DFG-Forschergruppe: Schutz- und Leittechnik zur zuverlässigen und sicheren Energieübertragung

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