Events Calendar

CEE Ph. D. Seminar

Speaker: Farrokh Jazizadeh, CE Ph.D. Candidate

Talk Title: User-Centric Smart Sensing For Non-Intrusive Electricity Consumption Disaggregation in Buildings

Abstract: Non-intrusive load monitoring (NILM) is a low-cost alternative to appliance level sub-metering, that leverages signal processing and machine learning techniques to estimate the power consumption of individual appliances from whole-home measurements. However, the difficulty associated with obtaining training data sets for the commonly used supervised NILM classification algorithms is a major obstacle in wide commercial adoption of the technology. The diversity of electrical load signatures (patterns of appliances’ power draw) demands in-situ training (labeling of the signatures), which often needs to be performed by users through user-system interaction. To produce the example signatures required for training, continuous interaction with users might be required, which could reduce the success of the training process due to user fatigue. Pre-populating a training data set could potentially reduce the need for user-system interaction. A heuristic unsupervised clustering algorithm has been presented and evaluated to enable autonomous partitioning of appliances signature space (i.e. feature space) for applications in electricity consumption disaggregation without a priori information. The algorithm determines the partition of a feature space recursively to account for multi-scale nature of the binary cluster tree.

Location: Seeley G. Mudd Building (SGM) - 101

Audiences: Everyone Is Invited

Contact: Evangeline Reyes