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A New Approach to the Analysis of Network Observability in Medium and Low Voltage Electrical Grids

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Smart Grid Inspired Future Technologies (SmartGift 2017)

Abstract

Medium and low voltage electrical power grids are typically sparsely instrumented, and thus, not observable in a systems’ theory sense. However, this is a requirement to carry out state estimation methods. To this end, many approaches for optimal sensor placement are proposed in the literature. Such methods are typically motivated from a mathematical perspective, not taking the physical properties of the network into account. As a consequence, the dimensionality of the mathematical problem is typically quite large resulting in significant numerical complexity. Therefore, a new approach is proposed here which is based on analyzing the characteristic observable and unobservable nodes by using singular value decomposition (SVD) and the breadth-first search method. The aim of the method is to identify all possibilities for the placement of measuring equipment to achieve observability. The proposed method does render the network observable with a minimal number of sensors. In this way, this reduces the dimensionality for conventional optimal sensor placement algorithms substantially.

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Acknowledgement

This work is part of the European Metrology Research Program (EMRP) Joint Research Project ENG63. The EMRP is jointly funded by the EMRP participating countries within EURAMET and the European Union.

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Correspondence to Guosong Lin .

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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Lin, G., Eichstädt, S., Turschner, D., Beck, HP. (2017). A New Approach to the Analysis of Network Observability in Medium and Low Voltage Electrical Grids. In: Lau, E., et al. Smart Grid Inspired Future Technologies. SmartGift 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 203. Springer, Cham. https://doi.org/10.1007/978-3-319-61813-5_12

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  • DOI: https://doi.org/10.1007/978-3-319-61813-5_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61812-8

  • Online ISBN: 978-3-319-61813-5

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