Optimization of social welfare and mitigating privacy risks in P2P energy trading: Differential privacy for secure data reporting
With the growing demand for energy and the integration of distributed energy resources
(DERs), Peer-to-Peer (P2P) energy trading has emerged as a promising approach that …
(DERs), Peer-to-Peer (P2P) energy trading has emerged as a promising approach that …
POSMETER: proof-of-stake blockchain for enhanced smart meter data security
As smart home appliances have grown in popularity; a large amount of data has been
created on smart meters pertaining to various consumers. Due to privacy concerns, these …
created on smart meters pertaining to various consumers. Due to privacy concerns, these …
[HTML][HTML] Generative deep learning-based thermographic inspection of artwork
Infrared thermography is a widely utilized nondestructive testing technique in the field of
artwork inspection. However, raw thermograms often suffer from problems, such as limited …
artwork inspection. However, raw thermograms often suffer from problems, such as limited …
Customized load profiles synthesis for electricity customers based on conditional diffusion models
Customers' load profiles are critical resources to support data analytics applications in
modern power systems. However, there are usually insufficient historical load profiles for …
modern power systems. However, there are usually insufficient historical load profiles for …
An incremental photovoltaic power prediction method considering concept drift and privacy protection
Abstract Concept drift (CD) and regional data sharing were considered potential factors
critical to affecting data-driven model accuracy. In this paper, an incremental photovoltaic …
critical to affecting data-driven model accuracy. In this paper, an incremental photovoltaic …
[HTML][HTML] Capturing multiscale temporal dynamics in synthetic residential load profiles through Generative Adversarial Networks (GANs)
High-resolution residential smart meter data play a pivotal role in numerous applications,
ranging from assessing hosting capacity in low-voltage grids to evaluating the economic …
ranging from assessing hosting capacity in low-voltage grids to evaluating the economic …
Forecasting energy power consumption using federated learning in edge computing devices
EM de Moraes Sarmento, IF Ribeiro, PRN Marciano… - Internet of Things, 2024 - Elsevier
Several studies in the literature propose using machine learning algorithms to forecast
consumers' energy consumption. However, such data is sensitive and has privacy …
consumers' energy consumption. However, such data is sensitive and has privacy …
An adaptive privacy protection framework for user energy data using dictionary learning and watermarking techniques
H Chen, W Guo, K Sun, X Wang, S Wang, L Guo - Applied Energy, 2024 - Elsevier
With the rise of user energy consumption data as a significant data asset, data privacy has
emerged as a critical concern. To address users' diverse attitudes towards data sharing and …
emerged as a critical concern. To address users' diverse attitudes towards data sharing and …
Generative adversarial network for load data generation: Türkiye energy market case
B Yılmaz - Mathematical Modelling and Numerical Simulation with …, 2023 - dergipark.org.tr
Load modeling is crucial in improving energy efficiency and saving energy sources. In the
last decade, machine learning has become favored and has demonstrated exceptional …
last decade, machine learning has become favored and has demonstrated exceptional …
A cluster-based appliance-level-of-use demand response program design
The ever-intensifying threat of climate change renders the electric power system undergoing
a profound transition toward net-zero emissions. Energy efficiency measures, such as …
a profound transition toward net-zero emissions. Energy efficiency measures, such as …