Event-Detection Algorithms for Low Sampling Nonintrusive Load Monitoring Systems Based on Low Complexity Statistical Features

Date
2019-04-12
Authors
Rehman, AU
Lie, T
Valles, B
Tito, SR
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers
Abstract

One of the key techniques towards energy efficiency and conservation is Non-Intrusive Load Monitoring (NILM) which lies in the domain of energy monitoring. Event detection is a core component of event-based NILM systems. This paper proposes two new low-complexity and computationally fast algorithms that detect the variations of load data and return the time occurrences of the corresponding events. The proposed algorithms are based on the phenomenon of a sliding window that tracks the statistical features of the acquired aggregated load data. The performance of the proposed algorithms is evaluated using real-world data and a comparative analysis has been carried out with one of the recently proposed event detection algorithms. Based on the simulations and sensitivity analysis it is shown that the proposed algorithm can provide the results of up to 93% and 88% in terms of recall and precision respectively.

Description
Keywords
Energy Monitoring; Event Detection; Non-Intrusive Load Monitoring; Smart Grids
Source
IEEE Transactions on Instrumentation and Measurement, doi: 10.1109/TIM.2019.2904351
Rights statement
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