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 …
among urban planners and policy makers to make responsible use of resources, conserve …
Application of load monitoring in appliances' energy management–A review
Energy monitoring is one of the important aspects of the energy management, as such there
is a need to monitor the power consumption of a premises before planning some of the …
is a need to monitor the power consumption of a premises before planning some of the …
[HTML][HTML] Non-intrusive load monitoring approaches for disaggregated energy sensing: A survey
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 …
them to obtain appliance-specific energy consumption statistics that can further be used to …
The ECO data set and the performance of non-intrusive load monitoring algorithms
Non-intrusive load monitoring (NILM) is a popular approach to estimate appliance-level
electricity consumption from aggregate consumption data of households. Assessing the …
electricity consumption from aggregate consumption data of households. Assessing the …
Non-intrusive load monitoring by using active and reactive power in additive Factorial Hidden Markov Models
Non-intrusive load monitoring (NILM) is the task of determining the appliances individual
contributions to the aggregate power consumption by using a set of electrical parameters …
contributions to the aggregate power consumption by using a set of electrical parameters …
Sliding window approach for online energy disaggregation using artificial neural networks
O Krystalakos, C Nalmpantis, D Vrakas - Proceedings of the 10th …, 2018 - dl.acm.org
Energy disaggregation is the process of extracting the power consumptions of multiple
appliances from the total consumption signal of a building. Artificial Neural Networks (ANN) …
appliances from the total consumption signal of a building. Artificial Neural Networks (ANN) …
A new approach for supervised power disaggregation by using a deep recurrent LSTM network
L Mauch, B Yang - 2015 IEEE global conference on signal and …, 2015 - ieeexplore.ieee.org
This paper presents a new approach for supervised power disaggregation by using a deep
recurrent long short term memory network. It is useful to extract the power signal of one …
recurrent long short term memory network. It is useful to extract the power signal of one …
On the accuracy of appliance identification based on distributed load metering data
Dynamic load management, ie, allowing electricity utilities to remotely turn electric
appliances in households on or off, represents a key element of the smart grid. Appliances …
appliances in households on or off, represents a key element of the smart grid. Appliances …
Machine learning approaches for non-intrusive load monitoring: from qualitative to quantitative comparation
C Nalmpantis, D Vrakas - Artificial Intelligence Review, 2019 - Springer
Non-intrusive load monitoring (NILM) is the prevailing method used to monitor the energy
profile of a domestic building and disaggregate the total power consumption into …
profile of a domestic building and disaggregate the total power consumption into …
Loced: Location-aware energy disaggregation framework
ASN Uttama Nambi, A Reyes Lua… - Proceedings of the 2nd …, 2015 - dl.acm.org
Providing detailed appliance level energy consumption information may lead consumers to
understand their usage behavior and encourage them to optimize the energy usage. Non …
understand their usage behavior and encourage them to optimize the energy usage. Non …