Smart Grid Inspired Future Technologies. Second EAI International Conference, SmartGIFT 2017, London, UK, March 27–28, 2017, Proceedings

Research Article

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

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  • @INPROCEEDINGS{10.1007/978-3-319-61813-5_12,
        author={Guosong Lin and Sascha Eichst\aa{}dt and Dirk Turschner and Hans-Peter Beck},
        title={A New Approach to the Analysis of Network Observability in Medium and Low Voltage Electrical Grids},
        proceedings={Smart Grid Inspired Future Technologies. Second EAI International Conference, SmartGIFT 2017, London, UK, March 27--28, 2017, Proceedings},
        proceedings_a={SMARTGIFT},
        year={2017},
        month={9},
        keywords={Electrical grid State estimation Singular value decomposition Breadth-first search Optimal sensor placement},
        doi={10.1007/978-3-319-61813-5_12}
    }
    
  • Guosong Lin
    Sascha Eichstädt
    Dirk Turschner
    Hans-Peter Beck
    Year: 2017
    A New Approach to the Analysis of Network Observability in Medium and Low Voltage Electrical Grids
    SMARTGIFT
    Springer
    DOI: 10.1007/978-3-319-61813-5_12
Guosong Lin,*, Sascha Eichstädt,*, Dirk Turschner,*, Hans-Peter Beck,*
    *Contact email: Guosong_Lin@hotmail.de, Sascha.Eichstaedt@ptb.de, Turschner@iee.tu-clausthal.de, beck@iee.tu-clausthal.de

    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.