Design of optimal energy management system in a residential microgrid based on smart control
Optimal use of microgrids for efficient and economic management of energy resources is of
special importance. At the residential level, energy costs can be reduced by using the …
special importance. At the residential level, energy costs can be reduced by using the …
Non-intrusive load disaggregation solutions for very low-rate smart meter data
With the active large-scale roll-out of smart metering worldwide, details about the type of
smart meter data that will be available for analysis are emerging. Consequently, focus has …
smart meter data that will be available for analysis are emerging. Consequently, focus has …
Non–intrusive load disaggregation of smart home appliances using the IPPO algorithm and FHM model
D Xia, S Ba, A Ahmadpour - Sustainable Cities and Society, 2021 - Elsevier
At present, producing the lowest power requires prognosticating the load operations in the
home automation systems. Several electrical household devices with various performances …
home automation systems. Several electrical household devices with various performances …
Spectral clustering for customer phase identification using AMI voltage timeseries
Smart grid technologies and wide-spread installation of advanced metering infrastructure
(AMI) equipment present new opportunities for the use of machine learning algorithms …
(AMI) equipment present new opportunities for the use of machine learning algorithms …
A deep recurrent neural network for non-intrusive load monitoring based on multi-feature input space and post-processing
Non-intrusive load monitoring (NILM) is a process of estimating operational states and
power consumption of individual appliances, which if implemented in real-time, can provide …
power consumption of individual appliances, which if implemented in real-time, can provide …
An open hardware design for internet of things power quality and energy saving solutions
An important challenge for our society is the transformation of traditional power systems to a
decentralized model based on renewable energy sources. In this new scenario, advanced …
decentralized model based on renewable energy sources. In this new scenario, advanced …
Time–frequency mask estimation based on deep neural network for flexible load disaggregation in buildings
In this paper, a novel mask-based load disaggregation scheme is presented to extract
flexible load profiles in buildings. Flexible loads are those that can be adjusted as needed …
flexible load profiles in buildings. Flexible loads are those that can be adjusted as needed …
Non-intrusive load transient identification based on multivariate LSTM neural network and time series data augmentation
Getting the specific energy consumption information of each appliance is an effective way to
reduce energy wastage and improve energy efficiency. The non-intrusive load monitoring is …
reduce energy wastage and improve energy efficiency. The non-intrusive load monitoring is …
[HTML][HTML] Comparison between artificial neural network and random forest for effective disaggregation of building cooling load
Detailed monitoring of loads can provide sufficient information about buildings and help in
improving the operation of energy systems. Non-intrusive load monitoring (NILM) has …
improving the operation of energy systems. Non-intrusive load monitoring (NILM) has …
Clustering-based reliability assessment of smart grids by fuzzy c-means algorithm considering direct cyber–physical interdependencies and system uncertainties
The steadily growing deployment of cyber systems in smart grids (SGs) has highlighted the
impacts of cyber–physical interdependencies (CPIs). Although much attention has been …
impacts of cyber–physical interdependencies (CPIs). Although much attention has been …