[HTML][HTML] A systematic review of machine learning techniques related to local energy communities

A Hernandez-Matheus, M Löschenbrand, K Berg… - … and Sustainable Energy …, 2022 - Elsevier
In recent years, digitalisation has rendered machine learning a key tool for improving
processes in several sectors, as in the case of electrical power systems. Machine learning …

[HTML][HTML] Advancements in digital twin technology and machine learning for energy systems: A comprehensive review of applications in smart grids, renewable energy …

O Das, MH Zafar, F Sanfilippo, S Rudra… - Energy Conversion and …, 2024 - Elsevier
The growing interest in Digital Twin (DT) Technology represents a significant advancement
in academic research and industrial applications. Leveraging advancements in Internet of …

[HTML][HTML] Do uncertainties affect clean energy markets? Comparisons from a multi-frequency and multi-quantile framework

Y Li, C Yan, X Ren - Energy Economics, 2023 - Elsevier
Clean energy market has great potential to promote the balance between economic
development and environmental protection, and has gradually become one of the vital …

Convolutional neural network-based deep transfer learning for fault detection of gas turbine combustion chambers

M Bai, X Yang, J Liu, J Liu, D Yu - Applied Energy, 2021 - Elsevier
Gas turbine combustion chambers work in highly adverse environment and thus malfunction
more easily compared to other components. Fault detection of gas turbine combustion …

Modeling of energy consumption factors for an industrial cement vertical roller mill by SHAP-XGBoost: a" conscious lab" approach

R Fatahi, H Nasiri, E Dadfar, S Chehreh Chelgani - Scientific Reports, 2022 - nature.com
Cement production is one of the most energy-intensive manufacturing industries, and the
milling circuit of cement plants consumes around 4% of a year's global electrical energy …

Spatial-temporal recurrent graph neural networks for fault diagnostics in power distribution systems

BLH Nguyen, TV Vu, TT Nguyen, M Panwar… - IEEE …, 2023 - ieeexplore.ieee.org
Fault diagnostics are extremely important to decide proper actions toward fault isolation and
system restoration. The growing integration of inverter-based distributed energy resources …

[HTML][HTML] A novel hybrid model combined with ensemble embedded feature selection method for estimating reference evapotranspiration in the North China Plain

H Zhou, L Ma, X Niu, Y **ang, J Chen, Y Su, J Li… - Agricultural Water …, 2024 - Elsevier
The reference evapotranspiration (ETo) is a key parameter in achieving sustainable use of
agricultural water resources. To accurately acquire ETo under limited conditions, this study …

A comprehensive survey of HVDC protection system: fault analysis, methodology, issues, challenges, and future perspective

A Pragati, M Mishra, PK Rout, DA Gadanayak, S Hasan… - Energies, 2023 - mdpi.com
The extensive application of power transfer through high-voltage direct current (HVDC)
transmission links in smart grid scenarios is due to many factors such as high-power transfer …

Data-driven modeling-based digital twin of supercritical coal-fired boiler for metal temperature anomaly detection

Z Cui, J Xu, W Liu, G Zhao, S Ma - Energy, 2023 - Elsevier
The flexible operation of coal-fired boilers deteriorates the heat transfer capacity of tubes,
leading to localized overheating, tube cracking, and even boiler failure. This study presents …

A novel MODWT-based fault detection and classification scheme in VSC-HVDC transmission line

A Imani, Z Moravej, M Pazoki - Electric Power Systems Research, 2023 - Elsevier
This paper proposes a protection scheme according to the transient wavelet energy of DC
pole's current signals by using an illustrative signal processing technique called maximum …