Debadatta Amaresh Gadanayak
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View article: A Deep Learning Approach for Fault Detection and Localization in MT-VSC-HVDC System Utilizing Wavelet Scattering Transform
A Deep Learning Approach for Fault Detection and Localization in MT-VSC-HVDC System Utilizing Wavelet Scattering Transform Open
This study presents a novel algorithm for automatic fault detection in multi-terminal voltage source converter-based high voltage direct current (MT-VSCHVDC) systems. The approach integrates the wavelet scattering transform (WST) to extrac…
View article: Signal processing and artificial intelligence based HVDC network protection: A systematic and state-up-the-art review
Signal processing and artificial intelligence based HVDC network protection: A systematic and state-up-the-art review Open
In this modern era, the smart grid (SG) is progressively empowered for direct current (DC) power transmission, either at high voltage (HV) or at medium voltage (MV). The high voltage direct current (HVDC) transmission systems have a signif…
View article: Real Time Intelligent Detection of PQ Disturbances With Variational Mode Energy Features and Hybrid Optimized Light GBM Classifier
Real Time Intelligent Detection of PQ Disturbances With Variational Mode Energy Features and Hybrid Optimized Light GBM Classifier Open
The modern era power system is constantly undergoing constructive changes and implementations both in source and load side. Certainly, the distributed generators, unconventional/nonlinear loads, charging stations etc are mostly integrated …
View article: Structural Approach to Convolutional Neural Network Trained With Novel Scaled Matrix Image for Pseudo Real-Time Power Quality Event Monitoring
Structural Approach to Convolutional Neural Network Trained With Novel Scaled Matrix Image for Pseudo Real-Time Power Quality Event Monitoring Open
The trend of integrating different distributed generation sources into the existing grid have increased the probability of power quality disturbances to a threatening level. Eventually, detection, protection and mitigation of these disturb…
View article: Islanding Detection and Power Quality Diagnosis of Wind Power Integrated Microgrid with Reduced Feature Trained Novel Optimized Random Decision Forest
Islanding Detection and Power Quality Diagnosis of Wind Power Integrated Microgrid with Reduced Feature Trained Novel Optimized Random Decision Forest Open
Distributed generations (DGs) have been increasingly addressing the ongoing power deficit in the electricity market. However, a significant concern in DG‐integrated microgrids is the detection of accidental islanding. To tackle this issue,…
View article: Enhanced Fault Localization in Multi-Terminal HVDC Systems Using Improved Gaussian Process Regression
Enhanced Fault Localization in Multi-Terminal HVDC Systems Using Improved Gaussian Process Regression Open
Accurate fault localization is crucial for protecting DC networks following the successful detection of internal faults in power transmission systems, as it minimizes the need for replacements and enables swift power recovery. This study p…
View article: A Comprehensive Survey of HVDC Protection System: Fault Analysis, Methodology, Issues, Challenges, and Future Perspective
A Comprehensive Survey of HVDC Protection System: Fault Analysis, Methodology, Issues, Challenges, and Future Perspective Open
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 efficiency, decoupled interconnection, control of AC netwo…
View article: Data-Mining Techniques Based Relaying Support for Symmetric-Monopolar-Multi-Terminal VSC-HVDC System
Data-Mining Techniques Based Relaying Support for Symmetric-Monopolar-Multi-Terminal VSC-HVDC System Open
Considering the advantage of the ability of data-mining techniques (DMTs) to detect and classify patterns, this paper explores their applicability for the protection of voltage source converter-based high voltage direct current (VSC-HVDC) …
View article: A novel hybrid downsampling and optimized random forest approach for islanding detection and non‐islanding power quality events classification in distributed generation integrated system
A novel hybrid downsampling and optimized random forest approach for islanding detection and non‐islanding power quality events classification in distributed generation integrated system Open
The quality of power in modern‐day power system is polluted with increased penetration of converter‐based distributed generations such as wind farm, solar PV system. In such scenarios detection of islanding and power quality disturbances a…