A feature fusion technique for improved non-intrusive load monitoring
نویسندگان
چکیده
منابع مشابه
Non-Intrusive Load Monitoring
Non-Intrusive Load Monitoring (NILM) is a technique that determines the load composition of a household through a single point of measurement at the main power feed. Here we presented an unsupervised approach to determine the number of appliances in the household, their power consumption and the state of each one at any given moment.
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Non-intrusive load monitoring (NILM) identifies used appliances in a total power load according to their individual load characteristics. In this paper we propose an evolutionary optimization algorithm to identify appliances, which are modeled as on/off appliances. We evaluate our proposed evolutionary optimization by simulation with Matlab, where we use a random total load and randomly generat...
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Better water consumption decisions benefit from detailed use information. Easily installed non-intrusive vibration sensors provide a “no-fuss” retrofit solution for detecting the operation of water consuming appliances. The sensors measure pipe vibration, which are revealed to be a rich source of information for identifying loads. Vibration is processed to extract power spectral density based f...
متن کاملShipboard Applications of Non-Intrusive Load Monitoring
The Non-Intrusive Load Monitor (NILM) provides a method of measuring component performance and source power quality through a single point of entry in the power distribution system. A study was performed utilizing the NILM onboard three different ships (along with experimentation in the laboratory) to determine its effectiveness in determining the state of mechanical systems through analysis of...
متن کاملAn Active Learning Framework for Non-Intrusive Load Monitoring: Preprint
Non-Intrusive Load Monitoring (NILM) is a set of techniques that estimates the electricity usage of individual appliances from power measurements taken at a limited number of locations in a building. One of the key challenges in NILM is having too many data lacking class labels, but being unable to label the data manually for cost or time constraints. This paper presents an active learning fram...
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ژورنال
عنوان ژورنال: Energy Informatics
سال: 2020
ISSN: 2520-8942
DOI: 10.1186/s42162-020-00112-w