Abstract
Enriching the fault identification methodology of the first paper, this second paper investigates the performance of the identification of main distribution line faults when broadband over power lines (BPL) networks are deployed. The main issue that is concerned in this paper is the impact of measurement differences on the fault identification process performance. The main contribution of this paper, which is focused on the identification of the main distribution line faults when measurement differences occur, is the application of the L1 piecewise monotonic data approximation (l1PMA) in order to cope with the measurement differences that influence the reflection coefficients derived from the extended TM2 method. Through the L1PMA application, measurement differences are confronted in order to prevent the trigger of a false alarm about the existence of a main distribution line fault. The combined operation of the extended TM2 method and L1PMA concludes the introductory phase (fault identification) of the main line fault localization methodology (MLFLM).
Highlights
The need for more intelligent, stable and autonomous transmission and distribution power grids is met by the deployment of the smart grid package, which comprises both hardware and software proposals, across the entire vintage power grid infrastructure [1]-[4]
As concerns the determination of the channel attenuation and reflection coefficient of overhead medium-voltage (OV MV) broadband over power lines (BPL) networks, the well-established hybrid method, which consists of [6], [10]-[26]: (i) a bottom-up approach that is based on the multiconductor transmission line (MTL) theory, eigenvalue decomposition (EVD) and singular value decomposition (SVD); and (ii) a top-down approach that is denoted as TM2 method and is based on the concatenation of multidimensional chain scattering matrices
To the measurement differences of OV MV BPL coupling transfer functions, the measurement differences that occur in OV MV BPL networks during the determination of reflection coefficients are typically described by continuous uniform distributions (CUDs) with range from 0 to a maximum CUD value that is equal to αMD
Summary
The need for more intelligent, stable and autonomous transmission and distribution power grids is met by the deployment of the smart grid package, which comprises both hardware and software proposals, across the entire vintage power grid infrastructure [1]-[4]. As concerns the smart grid hardware, broadband over power lines (BPL) networks have rightfully attracted the attention among the available wired and wireless communications media, which anyway may interoperate in the smart grid environment [5]-[7]. Trends in Renewable Energy, 3 can be supported by all the available wired and wireless communication solutions of smart grid, including BPL technology, since the traditional power grid can be further treated as an integrated intelligent IP-based network environment [2], [8]-[10]. As presented in [1], the comparison of the reflection coefficients between the normal operation, as given by the original TM2 method, and the fault operation, as determined by the extended TM2 method, defines the existence of main distribution line faults
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