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SEHRISH ALTAF
Aspiration Statement
My topmost priority is getting into a respectable PhD/research program in my area of focus, which revolves around Science, Technology and Society studies as well as renewable power research. With my science background, my career goal is to be placed in academia whether in S&TS, Philosophy or Engineering.
Core Skills
- Python/C++
- Arduino
- MATLAB/Simulink and PSSE
- Quantitative Research
- Analytics & Research
- Academic Writing
Academic Awards / Achievements
- Excellence Scholarship – Habib University
Experience
Leadership / Meta-curricular
- Prevention of Sexual Harassment Committee at Habib University - Member
- School Magazine - Assistant Editor
Internship / Volunteer Work
- OBEA Committee Habib University - Student Worker - EE
- Habib University - Teaching Assistant, Programming Fundamentals
Publications / Creative Projects
- Channel Modelling of Mm-wave Spectra for High Throughput Targets in Upper Atmosphere – Research Proposal; Wireless and Mobile Communication.
- High Voltage Direct Current (HVDC) Transmission; Electrical Machines.
- Motors and Motor Control Techniques used in TESLA Electric Vehicles.
Final Year Project
Project Title
State Estimation of Wind-Coupled 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. 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 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)
Project Pictures
