Fatemeh Najibi

Overview

Fatemeh is a Ph.D. student at the City University of London. Currently, she is working on “machine learning applications for Probabilistic Microgrids optimization” under the supervision of Eduardo Alonso and Dimitra Apostolopoulou.

Before joining Ph.D., she involved in both academia and industry. She worked as a researcher for Iran Power Transmission, Generation and Distribution Company (TAVANIR). She is experienced with different industrial software such as CYMDIST, DIgSILENT, ArcGIS, AutoCAD, NEPLAN, DIALux as well as Academic software such as MATLAB and GAMS.

She published 2 booklets for CYMDISt and DigSILENT in Persian language, 2 journal papers in Elsevier, 1 conference paper. Currently, she is working on machine learning application for forecasting renewable energy output and also as a TA, teaching different modules such as Mathematics in computing, Operating System, System Architecture, introduction to algorithms, Power System Design and Engineering Mathematics in City University of London.


RESEARCH INTERESTS

• Power systems dynamics and operation
• Deep learning
• Dynamic Modeling of Renewable Energy Sources
• Smart Grids
• Machine learning
• Optimization methods
• Electric vehicles
• Stochastic programming
• Intelligent Optimization Algorithms
• Probabilistic analysis and correlation studies
• Solar energy
• Mathematical and evolutionary computations


PROFESSIONAL ACTIVITIES & AWARDS
• Reviewer of UKACC Control Conference since 2018.
• Won London 2050 Mega-City essay Competition, 2019.
• Teaching fellow certificate, City University of London, London, Uk.
• Poster presentation in Ph.D. symposium city university of London, July 2018
• Teaching Matlab and Simulink to B.Sc. students in Shiraz University of technology
• Research Scholarship Award of National Elite Institute, Iran in 2012.
• Award as a promotion for the best consultant for Iran Power Transmission, Generation and Distribution Company (TAVANIR), Shiraz, Iran, 2015.
• Development and innovation, Technical and Vocational Training Corporation, Shiraz, Iran, Oct. 2010.


SOFTWARE SKILLS
• DigSILENT Power Factory (Professional at DPL and DSL).
• AutoCAD
• CYMDIST
• ArcGIS
• DIALux
• GAMS and MATLAB
• Python
• Netplan


PUBLICATIONS
1. F. Najibi, T. Niknam, A. Kavousi-fard, “Optimal stochastic management of renewable MG (micro-grids) considering the electro-thermal model of PV (photovoltaic)”, Energy. 2016. Cited by 10.

2. F. Najibi, T. Niknam, “Stochastic scheduling of renewable micro-grids considering photovoltaic source uncertainties”, Energy Conversion and Management. 2015. Cited by 29.

3. F. Najibi, E. Alonso, D. Apostolopoulou, “Optimal Dispatch of Pumped Storage Hydro Cascade Under Uncertainty”, UKACC 12th International Conference on Control (CONTROL), 2018, Sheffield, UK, 5-7 September 2018


BOOKS
1. Fatemeh Najibi, CYMDIST guide, a booklet for Iran Power Generation and Transmission Company (TAVANIR), in Persian, 2015.

2. Fatemeh Najibi, DigSilent guide, a booklet for Iran Power Generation and Transmission Company (TAVANIR), in Persian, 2015.


TEACHING EXPERIENCE:
Teaching Assistant: in the following courses:
Mathematics for computing
Power System Design
Engineering mathematics
Operating System
Introduction to Algorithms
System Architecture
Undergraduate project marker
Electrical Circuit
Engineering Mathematics Teaching Assistant: Electric Machine (II).
MATLAB and Simulink Lab
Power system Analysis

Postgraduate training

1. Deep learning in probabilistic optimal Micro Grid operation, City University of London, London, United Kingdom, Jan 2018

Employment

1. Research PhD student, City University of London, Jan 2018 – present

Title of thesis: Machine Learning for Power System Optimization

Jan 2018 – Mar 2021

Summary of research

My research is mainly about using Deep learning and optimization tools to solve an optimal probabilistic microgrid operation problem. I predict renewable energy resources output using machine learning and deep learning tools.