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MAHAD ALI
Aspiration Statement
I plan to continue my higher studies in Electrical Engineering in the domain of Power. I want to specialize in renewable energy systems especially wind-powered related. As a career, I want to become a researcher in Academia. My other passions include cooking, cricket etc.
Core Skills
- Python
- LabVolt
- C++
- Powerworld
- MATLAB/Simulink
- Renewable Energy Systems
- Hybrid Electric Vehicles
- Energy Management
Academic Awards / Achievements
- Newscastle University - MS Electrical & Electronics Engineering
- HU TOPS 100% Scholarship
Experience
Internship / Volunteer Work
- NRF Engineering - Electrical Engineer
- Engineering Economics – Habib University - Peer Tutor
Publications / Creative Projects
- Parameter Calculation of a Squirrel Cage Induction Motor: Parameters included the internal impedances of the motor based on the general model of the induction motor.
- Harmonic Analyzer for an Inductive Load: The frequencies generated at the start of the operation with inductive load was observed. It had a hardware component and then a MATLAB simulation for visual results.
Final Year Project
Project Title
State Estimation of Wind Powered DFIG Using Bayesian Filters
Description
Wind-power generation is a complex process, provided a stable and steady electric supply, the wind has a random nature. In order to control and stabilize the electric power generated, we must have a control system. This control system will force certain parameters of the system to ensure stability. The problem is that we usually don’t have direct access to these parameters (non-measurable). Hence one way to get access to these parameters is Bayesian estimation. & NBSP; Bayesian estimation is a stochastic framework, in which we provide some knowledge about the system and quantify the uncertainties within the system. With the provided information about the system, we estimate the relevant hidden parameters. The algorithms used to estimate the parameters to reduce the uncertainties, hence they are Bayesian filters. Our project consists of a DFIG (wind turbine) connected to a complex power network (IEEE-39). We will estimate the states of DFIG using multiple different algorithms (Bayesians filters). (Group Project)