Review of smart meter data analytics: Applications, methodologies, and challenges
The widespread popularity of smart meters enables an immense amount of fine-grained
electricity consumption data to be collected. Meanwhile, the deregulation of the power …
electricity consumption data to be collected. Meanwhile, the deregulation of the power …
Generating realistic building electrical load profiles through the Generative Adversarial Network (GAN)
Building electrical load profiles can improve understanding of building energy efficiency,
demand flexibility, and building-grid interactions. Current approaches to generating load …
demand flexibility, and building-grid interactions. Current approaches to generating load …
Review of load data analytics using deep learning in smart grids: Open load datasets, methodologies, and application challenges
MF Elahe, M Jin, P Zeng - International Journal of Energy …, 2021 - Wiley Online Library
The collection and storage of large‐scale load data in a smart grid provide new approaches
for the efficient, economical, and safe operation of power systems. Deep Learning (DL) has …
for the efficient, economical, and safe operation of power systems. Deep Learning (DL) has …
[HTML][HTML] Deep learning assisted buildings energy consumption profiling using smart meter data
The exponential growth in population and their overall reliance on the usage of electrical
and electronic devices have increased the demand for energy production. It needs precise …
and electronic devices have increased the demand for energy production. It needs precise …
[HTML][HTML] Applied control and artificial intelligence for energy management: An overview of trends in EV charging, cyber-physical security and predictive maintenance
L Ricciardi Celsi, A Valli - Energies, 2023 - mdpi.com
On 28 February–2 March 2023, the 2023 States General of Artificial Intelligence (AI) event
was held in Italy under the sponsorship of several multinational companies. The purpose of …
was held in Italy under the sponsorship of several multinational companies. The purpose of …
Agent-based architecture for demand side management using real-time resources' priorities and a deterministic optimization algorithm
Microgrids and smart grids are largely accepted concepts in power energy systems. They
bring an innovative and distributed view to the old centralized system. This demands a more …
bring an innovative and distributed view to the old centralized system. This demands a more …
[HTML][HTML] Towards modified entropy mutual information feature selection to forecast medium-term load using a deep learning model in smart homes
Over the last decades, load forecasting is used by power companies to balance energy
demand and supply. Among the several load forecasting methods, medium-term load …
demand and supply. Among the several load forecasting methods, medium-term load …
Hierarchical clustering for smart meter electricity loads based on quantile autocovariances
In order to improve the efficiency and sustainability of electricity systems, most countries
worldwide are deploying advanced metering infrastructures, and in particular household …
worldwide are deploying advanced metering infrastructures, and in particular household …
The challenges of privacy and access control as key perspectives for the future electric smart grid
A Triantafyllou, JAP Jimenez… - IEEE Open Journal …, 2020 - ieeexplore.ieee.org
The Electric Smart Grid (ESG) is referred to as the next generation electricity power network.
The ESG is an intelligent critical infrastructure subject to various security vulnerabilities and …
The ESG is an intelligent critical infrastructure subject to various security vulnerabilities and …
Distributed evidential clustering toward time series with big data issue
To analyze time series data with large volume, most of the existing clustering algorithms
focus on data reduction techniques or multi-level strategies. However, the destruction of raw …
focus on data reduction techniques or multi-level strategies. However, the destruction of raw …