Energy management using non-intrusive load monitoring techniques–State-of-the-art and future research directions

R Gopinath, M Kumar, CPC Joshua… - Sustainable Cities and …, 2020 - Elsevier
In recent years, the development of smart sustainable cities has become the primary focus
among urban planners and policy makers to make responsible use of resources, conserve …

Machine learning driven smart electric power systems: Current trends and new perspectives

MS Ibrahim, W Dong, Q Yang - Applied Energy, 2020 - Elsevier
The current power systems are undergoing a rapid transition towards their more active,
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …

Exploiting HMM sparsity to perform online real-time nonintrusive load monitoring

S Makonin, F Popowich, IV Bajić, B Gill… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
Understanding how appliances in a house consume power is important when making
intelligent and informed decisions about conserving energy. Appliances can turn ON and …

Non-intrusive load monitoring approaches for disaggregated energy sensing: A survey

A Zoha, A Gluhak, MA Imran, S Rajasegarar - Sensors, 2012 - mdpi.com
Appliance Load Monitoring (ALM) is essential for energy management solutions, allowing
them to obtain appliance-specific energy consumption statistics that can further be used to …

Electric energy disaggregation via non-intrusive load monitoring: A state-of-the-art systematic review

S Dash, NC Sahoo - Electric Power Systems Research, 2022 - Elsevier
Appliance energy consumption tracking in a building is one of the vital enablers of energy
and cost saving. An economical and viable solution would be to estimate individual …

Toward non-intrusive load monitoring via multi-label classification

SM Tabatabaei, S Dick, W Xu - IEEE Transactions on Smart …, 2016 - ieeexplore.ieee.org
Demand-side management technology is a key element of the proposed smart grid, which
will help utilities make more efficient use of their generation assets by reducing consumers' …

Approximate inference in additive factorial hmms with application to energy disaggregation

JZ Kolter, T Jaakkola - Artificial intelligence and statistics, 2012 - proceedings.mlr.press
This paper considers additive factorial hidden Markov models, an extension to HMMs where
the state factors into multiple independent chains, and the output is an additive function of all …

Is disaggregation the holy grail of energy efficiency? The case of electricity

KC Armel, A Gupta, G Shrimali, A Albert - Energy policy, 2013 - Elsevier
This paper aims to address two timely energy problems. First, significant low-cost energy
reductions can be made in the residential and commercial sectors, but these savings have …

Nonintrusive appliance load monitoring: Review and outlook

M Zeifman, K Roth - IEEE transactions on Consumer …, 2011 - ieeexplore.ieee.org
Consumer systems for home energy management can provide significant energy saving.
Such systems may be based on nonintrusive appliance load monitoring (NIALM), in which …

An event-driven convolutional neural architecture for non-intrusive load monitoring of residential appliance

D Yang, X Gao, L Kong, Y Pang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Nowadays, the advancement of non-intrusive load monitoring (NILM) is hastened by the
everincreasing requirements for smart power utilization and demand side management …