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Comparative analysis of machine learning techniques for non-intrusive load monitoring
Non-intrusive load monitoring (NILM) has emerged as a pivotal technology in energy
management applications by enabling precise monitoring of individual appliance energy …
management applications by enabling precise monitoring of individual appliance energy …
Appliance-level anomaly detection in nonintrusive load monitoring via power consumption-based feature analysis
In the majority of current supervised nonintrusive load monitoring (NILM) techniques the
characteristics of the training and test datasets are assumed to be constant. However, in …
characteristics of the training and test datasets are assumed to be constant. However, in …
Characterizing energy flexibility of buildings with electric vehicles and shiftable appliances on single building level and aggregated level
Residential energy flexibility is considered one of the efficient concepts to alleviate the ever-
increasing concerns of better balancing supply and demand. A positive assumption that all …
increasing concerns of better balancing supply and demand. A positive assumption that all …
Residential energy flexibility characterization using non-intrusive load monitoring
To accelerate progress in building sustainability as well as to aid balance supply and
demand in the presence of renewable energy generation, a tailored characterization method …
demand in the presence of renewable energy generation, a tailored characterization method …
[HTML][HTML] Non-intrusive load monitoring of residential loads via laplacian eigenmaps and hybrid deep learning procedures
Today, introducing useful and practical solutions to residential load disaggregation as
subsets of energy management has created numerous challenges. In this study, an …
subsets of energy management has created numerous challenges. In this study, an …
Quantification of disaggregation difficulty with respect to the number of smart meters
A promising approach toward efficient energy management is non-intrusive load monitoring
(NILM), that is to extract the consumption of appliances by analyzing the aggregated …
(NILM), that is to extract the consumption of appliances by analyzing the aggregated …
[HTML][HTML] Appliance-level anomaly detection by using control charts and artificial neural networks with power profiles
H Apaydin-Özkan - Sensors, 2022 - mdpi.com
Nowadays, the development of the Internet of Things (IoT) concept has increased the
interest in some technologies, one of which is the detection of anomalies in home …
interest in some technologies, one of which is the detection of anomalies in home …
[HTML][HTML] Power profile and thresholding assisted multi-label NILM classification
Next-generation power systems aim at optimizing the energy consumption of household
appliances by utilising computationally intelligent techniques, referred to as load monitoring …
appliances by utilising computationally intelligent techniques, referred to as load monitoring …
Active power-based event detection algorithm for real-time load monitoring systems
Non-intrusive load monitoring (NILM) has recently become a promising and trending topic in
energy management. Although several NILM-based solutions were proposed, a commercial …
energy management. Although several NILM-based solutions were proposed, a commercial …
Novel algorithms for filtering and event detection in non-intrusive load monitoring
The rise of the Internet of Things (IoT) and Industry 4.0 has brought about a connected
ecosystem where instruments and devices are interlinked. Within this framework, an array of …
ecosystem where instruments and devices are interlinked. Within this framework, an array of …