Machine learning driven smart electric power systems: Current trends and new perspectives

MS Ibrahim, W Dong, Q Yang - Applied Energy, 2020 - Elsevier
The current power systems are undergoing a rapid transition towards their more active,
flexible, and intelligent counterpart smart grid, which brings about tremendous challenges in …

Big data analytics in smart grids: a review

Y Zhang, T Huang, EF Bompard - Energy informatics, 2018 - Springer
Data analytics are now playing a more important role in the modern industrial systems.
Driven by the development of information and communication technology, an information …

Faults in smart grid systems: Monitoring, detection and classification

AEL Rivas, T Abrao - Electric Power Systems Research, 2020 - Elsevier
Smart Grid (SG) is a multidisciplinary concept related to the power system update and
improvement. SG implies real-time information with specific communication requirements …

Smart grid big data analytics: Survey of technologies, techniques, and applications

D Syed, A Zainab, A Ghrayeb, SS Refaat… - IEEE …, 2020 - ieeexplore.ieee.org
Smart grids have been gradually replacing the traditional power grids since the last decade.
Such transformation is linked to adding a large number of smart meters and other sources of …

An overview and comparative analysis of recurrent neural networks for short term load forecasting

FM Bianchi, E Maiorino, MC Kampffmeyer… - arXiv preprint arXiv …, 2017 - arxiv.org
The key component in forecasting demand and consumption of resources in a supply
network is an accurate prediction of real-valued time series. Indeed, both service …

Time-series classification methods: Review and applications to power systems data

GA Susto, A Cenedese, M Terzi - Big data application in power systems, 2018 - Elsevier
Chapter Overview The diffusion in power systems of distributed renewable energy
resources, electric vehicles, and controllable loads has made advanced monitoring systems …

Short-term electric load forecasting using echo state networks and PCA decomposition

FM Bianchi, E De Santis, A Rizzi, A Sadeghian - Ieee Access, 2015 - ieeexplore.ieee.org
In this paper, we approach the problem of forecasting a time series (TS) of an electrical load
measured on the Azienda Comunale Energia e Ambiente (ACEA) power grid, the company …

A survey on intelligent system application to fault diagnosis in electric power system transmission lines

VH Ferreira, R Zanghi, MZ Fortes, GG Sotelo… - Electric Power Systems …, 2016 - Elsevier
Fault analysis and diagnosis constitute a relevant problem in power systems, with important
economic impacts for operators, maintenance agents and the power industry in general …

The current state of the art in research on predictive maintenance in smart grid distribution network: Fault's types, causes, and prediction methods—A systematic …

MA Mahmoud, NR Md Nasir, M Gurunathan, P Raj… - Energies, 2021 - mdpi.com
With the exponential growth of science, Internet of Things (IoT) innovation, and expanding
significance in renewable energy, Smart Grid has become an advanced innovative thought …

Hierarchical genetic optimization of a fuzzy logic system for energy flows management in microgrids

E De Santis, A Rizzi, A Sadeghian - Applied Soft Computing, 2017 - Elsevier
Bio-inspired algorithms like Genetic Algorithms and Fuzzy Inference Systems (FIS) are
nowadays widely adopted as hybrid techniques in improving goods and services. In this …