Christy Green
ABSTRACT
Electric water heaters consume approximately 19% of the total energy in residential buildings and may be used as virtual batteries to provide a variety of ancillary services for the electric grid. With the proliferation of advanced metering infrastructure (AMI) smart meters, vast amounts of data have become available for non-intrusive load disaggregation. Disaggregating major appliances such as water heaters using low-resolution AMI data may assist in assessing residential virtual battery potential at a regional level. In this paper, we assess the use of a graph signal processing algorithm for non-intrusive load disaggregation of a hybrid heat pump water heater. Algorithm performance is evaluated for disaggregating the water heater signal in the presence of a variety of other loads and operational modes. Real-world data sampled in the field at a frequency of 1 minute and downsampled for the purpose of this study to 15 minutes were used to simulate typical AMI meter sampling frequency. Results demonstrate that F-measures (the harmonic mean of precision and recall values) > 0.90 are achievable for water heater disaggregation.
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Index Terms
- Non-Intrusive Load Monitoring of Water Heaters Using Low-Resolution Data
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