Abstract
We report our implementation of DLMS/COSEM (Device Language Message Specification/Companion Specification for Energy Metering) enabled advanced smart metering data collection using our in-house developed data-driven multivariate data pruning technique. Aiming at near real-time smart metering data collection, a working model of a smart energy meter with a data pruning subsystem is developed and incorporated with the data pruning and communication module. The implementation of DLMS/COSEM service layer enables standard pull-based data collection from multiple meters that are connected with a commercial head-end system. Our implementation enables to fetch smart meter readings from multiple meters with significantly reduced data footprint. Our empirical results demonstrate that, dynamic data pruning capability reduces the number of samples by nearly 85%. The bandwidth saving increases with the increasing batch size, by accounting for all protocol overheads the endto- end communication bandwidth saving is up to 85%. The DLMS overhead is negligible for larger batch size.
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