Smart Meter Data-Driven Characterization of LV Electricity Distribution Networks

High resolution smart meter data provides increased visibility into electricity distribution networks and enables extraction of powerful insights about them. Many smart meter data-based tools for network planning tasks such as identification of customer phase connectivity, determination of customer topology and detection of distributed generation have been developed. However, these tools are mostly challenged by the incompleteness of available smart meter data and low levels of smart meter penetration. Investigation of the impact of these challenges on the performance of such tools is still a necessity. This paper acknowledges this requirement by developing smart meter data-driven model-free characterization tools for rooftop solar PV detection and size estimation, customer phase identification, and topology determination, and investigating the performance of developed tools by implementing them on a real low voltage feeder with varied levels of smart meter penetration.