DR. MOHD. MUSTAFA
DR. MOHD. MUSTAFA

Designation: Associate professor

Qualification: B.Tech, M.Tech, Ph.D

Vidwan ID: 495900

Full Name

DR. MOHD. MUSTAFA


Email

mustafakmcet@methodist.edu.in


Total Experience

22 [Teaching: 7, Industrial: 15]


Paper Publications

International: 5, National: 7

Subjects Handled

Power systems, electrical machines, Electrical circuits, Renewable energy sources, Control systems, Power electronics

Research Area

Renewable energy and energy Management system. 

Papers Published/Books Published

1. Hybrid Renewable Power Generation for Modeling and controlling the Battery Storage  Photovoltaic System.                                                          2. Design of a P-Q Theory controller based solar PV system with shunt active filter to improve power quality .                                                            3.EnergyManagement system of Grid Connected Hybrid Stand-alone System using ANFIS.                                                                          4.Abatement of Faults in Grid by using Solar Inverters.                                                                 

5. A Review on Energy Management of Hybrid Renewable energy sources for  interconnected Grid Applications.                                                       6. A new interleaved Three -phase single stage PFC AC-DC CONVERTER With flying Capacitor.

7.Shuffled Differential Evolution for Economic load Dispatch problem. 

8. A predictive Technique Approaches on optimal solar panel Designs.                                                                                                                          9. A new multi-level inverter with facts capabilities for wind Applications.                                                                                                                     10. A novel control scheme for a Grid  Connected wind -farm and Marine -current farm using a STATCOM.  

11.Performance of Modular Multilevel Converter in Electric Vehicles Charging Station.

12.. Different Perspective of Deep Learning: Medcical Image Diagonosing.

 

 

Awards

Best Faculty award 2014,2015,2016,2018,2019