[HTML][HTML] Artificial intelligence techniques for enabling Big Data services in distribution networks: A review
S Barja-Martinez, M Aragüés-Peñalba… - … and Sustainable Energy …, 2021 - Elsevier
Artificial intelligence techniques lead to data-driven energy services in distribution power
systems by extracting value from the data generated by the deployed metering and sensing …
systems by extracting value from the data generated by the deployed metering and sensing …
[HTML][HTML] Survey of Optimization Techniques for Microgrids Using High-Efficiency Converters
Microgrids play a crucial role in modern energy systems by integrating diverse energy
sources and enhancing grid resilience. This study addresses the optimization of microgrids …
sources and enhancing grid resilience. This study addresses the optimization of microgrids …
Deep learning-based application for fault location identification and type classification in active distribution grids
The high penetration of distributed energy resources, especially weather-dependent
sources, even at the edge of the distribution grids, has increased the power system …
sources, even at the edge of the distribution grids, has increased the power system …
Distribution system state estimation and false data injection attack detection with a multi-output deep neural network
Distribution system state estimation (DSSE) has been introduced to monitor distribution
grids; however, due to the incorporation of distributed generations (DGs), traditional DSSE …
grids; however, due to the incorporation of distributed generations (DGs), traditional DSSE …
Intelligent fault detection and classification schemes for smart grids based on deep neural networks
Effective fault detection, classification, and localization are vital for smart grid self-healing
and fault mitigation. Deep learning has the capability to autonomously extract fault …
and fault mitigation. Deep learning has the capability to autonomously extract fault …
The branch-and-bound algorithm in optimizing mathematical programming models to achieve power grid observability
Phasor Measurement Units (PMUs) are the backbone of smart grids that are able to
measure power system observability in real-time. The deployment of synchronized sensors …
measure power system observability in real-time. The deployment of synchronized sensors …
Gridtopo-GAN for distribution system topology identification
Due to the limited presence of monitoring and measurement devices, timely identification of
distribution grid topology has been challenging. Therefore, this article proposes a power grid …
distribution grid topology has been challenging. Therefore, this article proposes a power grid …
A study on the economic feasibility of stand-alone microgrid for carbon-free Island in Korea
H Mun, B Moon, S Park, Y Yoon - energies, 2021 - mdpi.com
The power industry is rapidly changing as demand for eco-friendly and stable power supply
increases along with global greenhouse gas emission regulations. Small-capacity …
increases along with global greenhouse gas emission regulations. Small-capacity …
Distribution network planning method: Integration of a recurrent neural network model for the prediction of scenarios
AE Saldaña-González, M Aragüés-Peñalba… - Electric Power Systems …, 2024 - Elsevier
The integration of new types of consumers and prosumers into distribution networks
presents significant challenges for network planners, especially given the uncertainties of …
presents significant challenges for network planners, especially given the uncertainties of …
An Overview of Supervised Machine Learning Approaches for Applications in Active Distribution Networks
Distribution grids must be regularly updated to meet the global electricity demand. Some of
these updates result in fundamental changes to the structure of the grid network. Some …
these updates result in fundamental changes to the structure of the grid network. Some …