Sabina Tomkins
ABSTRACT
As advanced metering infrastructure(AMI) installations increase worldwide there is a pressing need to utilize the information they provide, by creating actionable feedback for consumers. Disaggregating a coarse, hourly energy reading, into the appliances which were on for that hour, and the amount of energy they consumed, would enable personalized recommendations for energy reduction. We propose a contextual model for energy signal disaggregation and demonstrate its ability to predict the amount of energy consumed by an air conditioner.
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Cross Ref
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Index Terms
- Poster Abstract: Contextual Air Conditioning Disaggregation with Probabilistic Soft Logic
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