Lecturer, University of khemis Meliana, Algeria
Sid-ali BLAIFI is a PhD holder in Electrical Engineering, specializing in the control, modeling, and monitoring of energy storage systems. He currently works at the Research Laboratory of Electrical Engineering and Automatics (LREA), University of Médéa, Algeria. His research interests encompass renewable energy, particularly photovoltaic systems, energy storage, and advanced control strategies. Sid-ali has made significant contributions to improving battery modeling, real-time monitoring systems, and optimizing energy systems with machine learning techniques. He is a prolific researcher with numerous publications in high-impact journals. His innovative approaches are highly regarded in the fields of energy storage and renewable energy technologies. 🌱⚡
Profile
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Education
Sid-ali BLAIFI earned his PhD in Electrical Engineering with a focus on Automatic Systems from the University of Médéa, Algeria. His doctoral research delved into advanced control strategies for energy storage systems, particularly batteries in photovoltaic applications. His Master’s project applied Fuzzy-based Direct Torque Control (DTC) to induction machines, which was experimentally validated on a TMS320F2812 DSP board. Over the years, Sid-ali has consistently improved his expertise in energy storage systems, optimization algorithms, and machine learning techniques, positioning him as an expert in the renewable energy field. 🎓📚
Experience
Sid-ali has extensive experience in energy storage and control systems, gained through both academic and research positions. He developed a robust charge controller for batteries in photovoltaic systems and contributed to the modeling of energy storage systems. He also built a real-time battery monitoring system using LabVIEW. His work on battery degradation and accelerated test procedures for photovoltaic and vehicular applications has been widely recognized. Post-PhD, Sid-ali applied machine learning to optimize control systems like Maximum Power Point Tracking (MPPT) in photovoltaic systems. His proficiency spans MATLAB/Simulink, LabVIEW, PSIM, and other tools used in energy systems research. 💼🔬
Research Focus
Sid-ali BLAIFI’s research primarily focuses on energy storage systems, particularly for renewable energy applications like photovoltaics and electric vehicles. He has worked extensively on dynamic modeling of batteries using Genetic Algorithms and Levenberg-Marquardt optimization, improving real-time battery monitoring systems. His research also integrates machine learning techniques with energy management systems, such as applying fuzzy logic and model trees for MPPT in PV systems. Additionally, he is developing microgrid control strategies using machine learning to enhance power sharing in distributed generation systems. His work is crucial in optimizing energy systems for efficiency and sustainability. 🔋🌞🤖
Publication Top Notes
- An enhanced dynamic model of battery using genetic algorithm suitable for photovoltaic applications 🌍🔋
- M5P model tree based fast fuzzy maximum power point tracker 🌞💡
- An enhanced dynamic modeling of PV module using Levenberg-Marquardt algorithm 🌞🔧
- Monitoring and enhanced dynamic modeling of battery by genetic algorithm using LabVIEW applied in photovoltaic system ⚡💻
- Improved model and simulation tool for dynamic SOH estimation and life prediction of Batteries used in PV systems 🔋🔍
- An improved dynamic battery model suitable for photovoltaic applications 🌅🔋
- Energy Storage and Photovoltaic Systems 🌞🔋
- Static and Dynamic Photovoltaic Cell/Module Parameters Identification 🌞📊
- Contribution to the development of a robust charge controller of a stationary battery for photovoltaic applications 🔋🔧