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Dynamic and Memory-efficient Shape Based Methodologies for User Type Identification in Smart Grid Applications
Detecting behind-the-meter (BTM) equipment and major appliances at the residential level and tracking their changes in real time is important for aggregators and traditional electricity utilities.
A New Time Series Similarity Measure and Its Smart Grid Applications
As a result, there is a need for a new distance measure that can quantify both the amplitude and temporal changes of electricity time series for smart grid applications, e. g., demand response and load profiling.
IRMAC: Interpretable Refined Motifs in Binary Classification for Smart Grid Applications
In this paper, we seek to identify residential consumers based on their BTM equipment, mainly rooftop photovoltaic (PV) systems and electric heating, using imported/purchased energy data from utility meters.
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