Scalable Hybrid Classification-Regression Solution for High-Frequency
Nonintrusive Load Monitoring
- URL: http://arxiv.org/abs/2208.10638v1
- Date: Mon, 22 Aug 2022 22:21:42 GMT
- Title: Scalable Hybrid Classification-Regression Solution for High-Frequency
Nonintrusive Load Monitoring
- Authors: Govind Saraswat, Blake Lundstrom and Murti V Salapaka
- Abstract summary: We present a novel multiclass nonintrusive load monitoring (NILM) approach that enables effective net-load monitoring capabilities at high-frequency.
The proposed machine learning based solution provides accurate multiclass state predictions while operating at a faster timescale.
We also introduce an innovative hybrid classification-regression method that allows for the prediction of not only load on/off states via classification but also individual load operating power levels via regression.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Residential buildings with the ability to monitor and control their net-load
(sum of load and generation) can provide valuable flexibility to power grid
operators. We present a novel multiclass nonintrusive load monitoring (NILM)
approach that enables effective net-load monitoring capabilities at
high-frequency with minimal additional equipment and cost. The proposed machine
learning based solution provides accurate multiclass state predictions while
operating at a faster timescale (able to provide a prediction for each 60-Hz ac
cycle used in US power grid) without relying on event-detection techniques. We
also introduce an innovative hybrid classification-regression method that
allows for the prediction of not only load on/off states via classification but
also individual load operating power levels via regression. A test bed with
eight residential appliances is used for validating the NILM approach. Results
show that the overall method has high accuracy and, good scaling and
generalization properties. Furthermore, the method is shown to have sufficient
response time (within 160ms, corresponding to 10 ac cycles) to support building
grid-interactive control at fast timescales relevant to the provision of grid
frequency support services.
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