Email this article Virtual Topologies for Populating Overhead Low-Voltage Broadband over Powerlines Topology Classes by Exploiting Neural Network Topology Generator Methodology (NNTGM) - Part 2: Numerical Results
Abstract
In [1], Neural Network Topology Generator Methodology (NNTGM) has been theoretically proposed, so that its generated overhead low-voltage broadband over power lines topologies (NNTGM OV LV BPL topologies) may populate the existing OV LV BPL topology classes. Apart from the methodology, NNTGM default operation settings and the applied performance metrics, such as the average theoretical channel attenuation (ACA) and the root mean square delay-spread (RMS-DS), have been presented in [1]. In this companion paper, the new OV LV BPL topology class maps, which are defined by the graphical combination of ACA and RMS-DS of the OV LV BPL topologies, are shown. With reference to the graphical combination of ACA and RMS-DS, NNTGM OV LV BPL topology footprints for given indicative OV LV BPL topology are demonstrated on the OV LV BPL topology class maps. The impact on the relative position and the size of the NNTGM OV LV BPL topology footprints is assessed with reference to the following factors that affect the preparation of the Topology Identification Methodology (TIM) OV LV BPL topology database being used during the NNTGM operation, namely: (i) The inclusion or not of the examined indicative OV LV BPL topology; (ii) the length of the distribution / branch line segments; and (iii) the number of the distribution / branch line segments. The performance assessment of NNTGM is supported by suitable Graphical Performance Indicators (GPIs).
Citation: Lazaropoulos, A. (2024). Virtual Topologies for Populating Overhead Low-Voltage Broadband over Powerlines Topology Classes by Exploiting Neural Network Topology Generator Methodology (NNTGM) - Part 2: Numerical Results. Trends in Renewable Energy, 10(3), 315-334. doi:http://dx.doi.org/10.17737/tre.2024.10.3.00182
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DOI: http://dx.doi.org/10.17737/tre.2024.10.3.00182
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