Performance evaluation in non‐intrusive load monitoring: datasets, metrics, and tools—A review
Non‐intrusive load monitoring (also known as NILM or energy disaggregation) is the
process of estimating the energy consumption of individual appliances from electric power …
process of estimating the energy consumption of individual appliances from electric power …
A critical review of state-of-the-art non-intrusive load monitoring datasets
Abstract Nowadays Non-Intrusive Load Monitoring (NILM) is considered a hot topic among
researchers. The energy disaggregation datasets are used as the benchmark to validate the …
researchers. The energy disaggregation datasets are used as the benchmark to validate the …
A synthetic energy dataset for non-intrusive load monitoring in households
Research on smart grid technologies is expected to result in effective climate change
mitigation. Non-Intrusive Load Monitoring (NILM) is seen as a key technique for enabling …
mitigation. Non-Intrusive Load Monitoring (NILM) is seen as a key technique for enabling …
TraceGAN: Synthesizing appliance power signatures using generative adversarial networks
Non-intrusive load monitoring (NILM) allows users and energy providers to gain insight into
home appliance electricity consumption using only the building's smart meter. Most current …
home appliance electricity consumption using only the building's smart meter. Most current …
A generative model for non-intrusive load monitoring in commercial buildings
In the recent years, there has been an increasing academic and industrial interest for
analyzing the electrical consumption of commercial buildings. Whilst having similarities with …
analyzing the electrical consumption of commercial buildings. Whilst having similarities with …
How does load disaggregation performance depend on data characteristics? insights from a benchmarking study
Electrical consumption data contain a wealth of information, and their collection at scale is
facilitated by the deployment of smart meters. Data collected this way is an aggregation of …
facilitated by the deployment of smart meters. Data collected this way is an aggregation of …
elami—an innovative simulated dataset of electrical loads for advanced smart energy applications
Smart Energy Applications are particularly impacting, especially due to energy resource
scarcity and its high associated costs. Smart management of energy consumption derives …
scarcity and its high associated costs. Smart management of energy consumption derives …
Enhancing neural non-intrusive load monitoring with generative adversarial networks
Abstract The application of Deep Learning methodologies to Non-Intrusive Load Monitoring
(NILM) gave rise to a new family of Neural NILM approaches which increasingly outperform …
(NILM) gave rise to a new family of Neural NILM approaches which increasingly outperform …
Data augmentation strategies for high-frequency NILM datasets
The nonintrusive load monitoring (NILM) process aims to monitor the different appliances
connected to a power grid. It accomplishes this by analyzing one or multiple signals …
connected to a power grid. It accomplishes this by analyzing one or multiple signals …
Handling imbalance in an extended PLAID
The ability to classify appliances, given the current and voltage consumption of a household
is useful for a variety of applications, including demand response verification, and eco …
is useful for a variety of applications, including demand response verification, and eco …