A hybrid model based on discrete wavelet transform (DWT) and bidirectional recurrent neural networks for wind speed prediction
A Barjasteh, SH Ghafouri, M Hashemi - Engineering Applications of …, 2024 - Elsevier
Wind speed is the main driver of wind power output, but its inherent fluctuations and
deviations present significant challenges for power system security and power quality …
deviations present significant challenges for power system security and power quality …
[HTML][HTML] Advanced Fault Detection in Power Transformers Using Improved Wavelet Analysis and LSTM Networks Considering Current Transformer Saturation and …
Power transformers are vital and costly components in power systems, essential for ensuring
a reliable and uninterrupted supply of electrical energy. Their protection is crucial for …
a reliable and uninterrupted supply of electrical energy. Their protection is crucial for …
[PDF][PDF] A novel approach for diagnosing transformer internal defects and inrush current based on 1DCNN and LSTM deep learning
In power systems, power transformer (Pt) protection plays a vital role in ensuring that
customers have a reliable power supply. Correctly recognizing inrush currents from internal …
customers have a reliable power supply. Correctly recognizing inrush currents from internal …
A new data mining application in smart monitoring systems using self organizing map neural network to distinguish disk space variations in distribution transformers
O Elahi, R Behkam, GB Gharehpetian… - 2022 IEEE Electrical …, 2022 - ieeexplore.ieee.org
Online monitoring of electric power components in smart grids is of great importance to
enhance reliability. Fault detection at primary levels in distribution transformers, the chief …
enhance reliability. Fault detection at primary levels in distribution transformers, the chief …
Real-Time Revolutionizing Internal Defect Detection in Power Transformers by Leveraging Wavelet Transform and Deep Learning LSTM in Cascading Application
In recent times, the real-time and online identification and prediction of power transformer
malfunctions play a vital part in maintaining the dependability and stability of electrical …
malfunctions play a vital part in maintaining the dependability and stability of electrical …
Intelligent Metal Welding Defect Detection Model on Improved FAST-PNN
J Liu, K Li - Coatings, 2022 - mdpi.com
In order to solve the problem of accurate and efficient detection of welding defects in the
process of batch welding of metal parts, an improved Probabilistic Neural Network (PNN) …
process of batch welding of metal parts, an improved Probabilistic Neural Network (PNN) …
Location of Multiple Types of Faults in Active Distribution Networks Considering Synchronization of Power Supply Area Data
G Ren, X Zha, B Jiang, X Hu, J Xu, K Tao - Applied Sciences, 2022 - mdpi.com
When a short circuit occurs in the power supply area of a distribution network with a high-
permeability distributed generation, the line current will increase, the voltage will drop …
permeability distributed generation, the line current will increase, the voltage will drop …
Research of Transformer Protection Based on Joint Deep Learning
Q Huang, Y Wang, SK Im - 2023 4th International Seminar on …, 2023 - ieeexplore.ieee.org
As the total electricity load and the proportion of renewable energy sources continue to rise
in China, the power grid is experiencing an expansion in scale and an increasing complexity …
in China, the power grid is experiencing an expansion in scale and an increasing complexity …
Discrimination between internal current and external fault in three phase power transformer by Using alienation coefficient
O Abdusalam, F Anayi… - 2022 57th International …, 2022 - ieeexplore.ieee.org
Transformers are essential equipment in a power system and require reliable solutions for
their protection to ensure smooth operation. This paper proposes a new method based on …
their protection to ensure smooth operation. This paper proposes a new method based on …