Erphan A. Bhuiyan, Md. Zahid Hossain, S. M. Muyeen, Shahriar Rahman Fahim et al.
Erphan A. Bhuiyan, Md. Maeenul Azad Akhand, Sajal K. Das, Md. Firoj Ali et al.
Saleh Mohammed Shahriar, Erphan A. Bhuiyan, Md. Nahiduzzaman, Mominul Ahsan et al.
Enhancing the accuracy of the battery state of charge (SOC) estimation is essential in developing more effective, dependable, and convenient electric vehicles. In this paper, a hybrid CNN and gated recurrent unit-long short-term memory (CNN-GRU-LSTM) approach, which is a recurrent neural network (RN...
Md. Sihab Uddin, Md. Zahid Hossain, Shahriar Rahman Fahim, Subrata K. Sarker et al.
Transmission lines (TLs) of power networks are often encountered with a number of faults. To continue normal operation and reduce the damage due to the TL faults, it is a must to identify and classify faults as early as possible. In this paper, the design and development of an intelligent machine le...
Erphan A. Bhuiyan, Maeenul Azad Akhand, Shahriar Rahman Fahim, Subrata K. Sarker et al.
The reliable operation of power systems becomes a formidable job these days due to the high amount of complexities in the expanded power system networks. The power system networks often comprise microgrids that encounter over 80% of faults due to their exposure to unpredictable weather conditions, w...
Shahriar Rahman Fahim, Erphan A. Bhuiyan, Yeahia Sarker, Subrata K. Sarker et al.
Faults in a power electronic component (inverter, converter, modules, etc.) can severely affect the reliability, efficiency, as well as the security of the entire power conversion system if not detected by early warning. The inverters that are the most common power converters in the industry are wid...
Md. Sihab Uddin, Erphan A. Bhuiyan, Subrata K. Sarker, Sajal K. Das et al.
This paper focuses on presenting a novel fault detection and classification (FDC) scheme that can classify shut faults occur in overhead transmission lines with a very promising performance. Immediate diagnosis of TL faults is important to avoid power system damage. Several fault detection and class...
Ananta Bijoy Bhadra, Most. Humayra Khanom Rime, Yeahia Sarker, Erphan A. Bhuiyan et al.
This paper presents a novel deep learning framework based on a Dual Graph Attention Network (DualGAT) to enhance the accuracy and robustness of fault diagnosis in photovoltaic (PV) inverters operating under diverse environmental and operational conditions. Given the critical role of PV inverters in ...
Erphan A. Bhuiyan, Shahriar Rahman Fahim, Subrata K. Sarker, Sajal K. Das et al.
Microgrids frequently experience a massive amount of faults, which compromise stable operation, disrupts the loads, and increases the grid recovery expenditures. The diagnosis of microgrid system faults is severely reliant on dimensionality reduction and requires complex data acquisition. To address...
Fozlur Rayhan, Md. Shariare Shaurov, Md. Alam Nashrah Khan, Shahriar Jahan et al.
Condition monitoring and diagnosis of rotor broken bar (BRB) induction motors is critical for the proper functioning of imperative industrial applications. Traditional fault diagnosis methods typically employ deep learning techniques that are trained on the chronological sequence of the accumulated ...
Erphan A. Bhuiyan, Yeahia Sarker, Shahriar Rahman Fahim, Mohammad Abdul Mannan et al.
In order to increase the availability and reliability of photovoltaic (PV) systems, fault diagnosis and condition monitoring of inverters are of crucial means to meet the goals. Numerous methods are implemented for fault diagnosis of PV inverters, providing robust features and handling massive amoun...
Ananta Bijoy Bhadra, Sheikh Shafaet Islam, Kazi Hasan, Niloy Sarker et al.
This paper aims to develop an intelligent protection scheme for microgrids with a number of distributed generation units considering different modes of operation. The conventional computational intelligence-based shunt fault detection and classification approaches have shallow architecture and invol...
Erphan A. Bhuiyan, S. M. Muyeen, Shahriar Rahman Fahim, Subrata K. Sarker et al.
This paper introduces a greedy layer-wise learning algorithm to diagnose open-circuit faults of grid-connected inverters. Inverters play important roles in energy conversion, especially when converting direct current to alternating current. The accurate functioning of inverters is essential for succ...
Ananta Bijoy Bhadra, Fozlur Rayhan, Most. Humayra Khanom Rime, Shahriar Jahan et al.