Deep federated adaptation: An adaptative residential load forecasting approach with federated learning
Y Shi, X Xu - Sensors, 2022 - mdpi.com
Residential-level short-term load forecasting (STLF) is significant for power system
operation. Data-driven forecasting models, especially machine-learning-based models, are …
operation. Data-driven forecasting models, especially machine-learning-based models, are …
[HTML][HTML] Ethical considerations in advanced metering infrastructure integration: A systematic review
Abstract The integration of Advanced Metering Infrastructure (AMI) within energy utility
systems promises significant improvements in efficiency, service delivery, and sustainability …
systems promises significant improvements in efficiency, service delivery, and sustainability …
Smart meter data obfuscation with a hybrid privacy-preserving data publishing scheme without a trusted third party
Smart electricity meters as a prominent instance of the Internet of Things (IoT) have driven
more efficient energy services in smart grids but also created growing concerns of consumer …
more efficient energy services in smart grids but also created growing concerns of consumer …
Privacy design strategies for home energy management systems (hems)
Home energy management systems (HEMS) offer control and the ability to manage energy,
generating and collecting energy consumption data at the most detailed level. However …
generating and collecting energy consumption data at the most detailed level. However …
DFTMicroagg: a dual-level anonymization algorithm for smart grid data
The introduction of advanced metering infrastructure (AMI) smart meters has given rise to
fine-grained electricity usage data at different levels of time granularity. AMI collects high …
fine-grained electricity usage data at different levels of time granularity. AMI collects high …
[HTML][HTML] Energy disaggregation risk resilience through microaggregation and discrete Fourier transform
Progress in the field of Non-Intrusive Load Monitoring (NILM) has been attributed to the rise
in the application of artificial intelligence. Nevertheless, the ability of energy disaggregation …
in the application of artificial intelligence. Nevertheless, the ability of energy disaggregation …
Differentially private demand side management for incentivized dynamic pricing in smart grid
In order to efficiently provide demand side management (DSM) in smart grid, carrying out
pricing on the basis of real-time energy usage is considered to be the most vital tool …
pricing on the basis of real-time energy usage is considered to be the most vital tool …
A systematic literature review of deep learning approaches in smart meter data analytics
J Breitenbach, J Gross, M Wengert… - 2022 IEEE 46th …, 2022 - ieeexplore.ieee.org
As the identification of the energy consumption represents a crucial part of the smart grid,
smart meters are considered one of the most important devices in the evolution of the …
smart meters are considered one of the most important devices in the evolution of the …
Implementation path and reference model for Multilateral Data Circulation System (MDCS) in Datacentric Product-Service System (DPSS): from an industrial practice …
C Wang, X Ming, X Gao, X Zhang - Advanced Engineering Informatics, 2025 - Elsevier
With the digital transformation of enterprises and the development of digital infrastructure
(smart sensors, 5G/6G, IoT, Industrial Internet, etc.), large amounts of data are generated in …
(smart sensors, 5G/6G, IoT, Industrial Internet, etc.), large amounts of data are generated in …
Smart meter data masking using conditional generative adversarial networks
We present a novel two-stage smart meter (SM) data masking technique. In the first stage,
data masking is carried out at an individual SM using a light-weight approach …
data masking is carried out at an individual SM using a light-weight approach …