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- Computing and Processing
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Talal Alharbi
Also published under:
Affiliation
Department of Electrical Engineering, College of Engineering, Qassim University, Buraydah, Saudi Arabia
Topic
Artificial Neural Network,Battery Management System,Charge Discharge Cycles,Convolutional Neural Network,Gated Recurrent Unit,Long Short-term Memory,Mean Absolute Error,Mean Absolute Percentage Error,Model Performance,Neural Network,Root Mean Square Error,1D Convolutional Neural Network,AC Microgrid,Active Control,Active Power Control,Adaptive Neuro-fuzzy Inference System,Apparent Power,Battery Capacity,Battery Degradation,Battery Management,Battery State-of-health,Bidirectional Long Short-term Memory,Bipolar Transistor,CatBoost,Circuit Breaker,Community Energy,Compensation Function,Control Signal,Controller Area Network,Conventional Detection,Conventional Detection Methods,Covariance Matrix,Current Flow,Current Sensor,Cycling Performance,Data Privacy,Deep Convolutional Neural Network,Deep Learning,Deep Learning Architectures,Deep Learning Models,Deep Learning Techniques,Deep Neural Network,Dense Layer,Depth Of Discharge,Detection Methods,Discharge Cycles,Distributed Energy Resources,Distribution Network,Distribution System,Dual Index,
Biography
Talal Alharbi (Member, IEEE) received the B.Sc. degree in electrical engineering from Qassim University, Saudi Arabia, in 2010, and the M.A.Sc. and Ph.D. degrees in electrical and computer engineering from the University of Waterloo, ON, Canada, in 2015 and 2020, respectively. In 2020, he rejoined the Department of Electrical Engineering, Qassim University, where he is currently an Assistant Professor. His research interests include electric vehicle, power system operation and optimization, energy management, energy storage systems, power electronic and artificial intelligence applications in power systems, and smart grids.