Mahabuba Abdulrahim
@hct.ac.ae
Electrical Engineering Faculty Member
Higher Colleges of Technology, Dubai, United Arab EMirates
Lecture, Senior Lecturer and Assistant Professor in B.S.A. Crescent Engineering College, Chennai, India.
Instructor and Assistant Professor, Al Ghurair University, Dubai, U.A.E.
Electrical Engineering Faculty, Institute of Applied Technology, Ajman, U.A.E
Lecturer, Dubai Men’s College, Higher Colleges of Technology, Dubai, U.A.E.
Teaching Interests: Power generation and Transmission; Electrical Power Distribution; Electrical Machines, Engineering Electromagnetics; Electric Circuits; Control Systems ; Advanced Power Systems.
I love teaching; Teaching is always my passion. I feel younger when I am doing my teaching and learning process with my students; I love travelling and listening to good music.
EDUCATION
2003 to 2009 | PhD (Power System Engineering Department)-Anna University, Chennai, India
2000-08-01 to 2003-01-03 | ME (Instrumentation Engineering) Anna University-Chennai ,India
1990-1994 BE (Electrical and Electronics Engineering) University of Madras, Chennai, India
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering, Control and Systems Engineering, Renewable Energy, Sustainability and the Environment, Biomedical Engineering
FUTURE PROJECTS
Integration of Advanced Technologies for Energy Storage Systems
The transition to renewable energy is a global priority as we seek to mitigate climate change and reduce dependency on fossil fuels. Solar and wind energy, two of the most widely adopted renewable sources, present unique challenges due to their intermittent and variable nature. Energy storage systems are critical in addressing these challenges, ensuring a stable and reliable power supply. However, conventional energy storage systems struggle to efficiently manage the rapid fluctuations inherent in renewable energy generation. This proposal seeks to develop a Hybrid Energy Storage System (HESS) that integrates supercapacitors, lithium-ion batteries, and multi-level inverters. The aim is to enhance the overall performance, efficiency, and reliability of hybrid solar-wind energy systems by leveraging the strengths of each component: supercapacitors for rapid response to power fluctuations, batteries for long-term energy storage, and multi-level inverters for high power quality.
Applications Invited
Researchers
Smart Guard: Advanced Wearable Health Monitoring and Alert System
The "Smart Guard: Advanced Wearable Health Monitoring and Emergency Alert System" is designed to enhance personal health monitoring through an integrated wearable device that tracks critical health metrics, including heart rate, body temperature, blood oxygen levels, diabetes management, stress level, GPS location, electrical activity of the heart (ECG), and it also detects when a person falls due to any health issue. This system aims to provide real-time monitoring and emergency alerts, making it particularly valuable for individuals with chronic health conditions, elderly people and athletes. The wearable device utilizes advanced sensors and microcontrollers to continuously gather and analyze data, which is then transmitted to a mobile application for real-time tracking and alerting. In case of an abnormal health event, such as a fall or a significant deviation in vital signs, the system automatically sends an alert to pre-configured emergency contacts with the wearer’s GPS location.
Applications Invited
Researchers
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
T. Logeswaran, M. Senthil Raja, Jennathu Beevi Sahul Hameed, and Mahabuba Abdulrahim
Elsevier BV
Ashfaq Ur Rehman Mohamed Riazuddin, Mahabuba Abdulrahim, Jennathu Beevi Sahul Hameed, and Jayashree Ramasubramaniam
Seventh Sense Research Group Journals
Mahabuba Abdurrahim, Abdullah Khan M., and Ali Ahmed Edriss
SPIE
This paper presents a design procedure for a Robust and Adaptive Fuzzy Logic based Power System Stabilizer (RAFLPSS) to improve the small signal stability of Power System. The parameters of RAFLPSS are tuned by adaptive neural network. This RAFLPSS uses ANFIS network (Adaptive Network based Fuzzy Inference System) which provides a natural framework of multi-layered feed forward adaptive network using fuzzy logic inference system. In this approach, the hybrid-learning algorithm tunes the fuzzy rules and the membership functions of the RAFLPSS. The dynamic performance of SMIB system with the proposed RAFLPSS under different operating conditions and change in system parameters has been investigated. The simulation results obtained from the conventional PSS (CPSS) and Fuzzy logic based PSS (FPSS) are compared with the proposed RAFLPSS. The simulation results demonstrate that the proposed RAFLPSS performs well in damping and quicker response when compared with the other two PSSs.
A. Mahabuba and M. Abdullah Khan
Wiley
AbstractThis paper presents a design procedure for a robust and adaptive fuzzy neural network‐based power system stabilizer (RAFNNPSS) and investigates the robustness and adaptive feature of the RAFNNPSS for a single machine connected to an infinite bus system and multi‐machine power systems in order to enhance the dynamic stability (small signal stability of the system). The parameters of RAFNNPSS are tuned by adaptive neural network (NN). This RAFNNPSS uses adaptive network‐based fuzzy inference system (ANFIS) network, which provides a natural framework of multi‐layered feed forward adaptive network using fuzzy logic inference system. In this approach, the hybrid‐learning algorithm tunes the fuzzy rules and the membership functions of the RAFNNPSS. Speed deviation of synchronous generator and its derivative are chosen as the input signals to the RAFNNPSS. The dynamic performance of single‐machine infinite bus (SMIB) system, a two‐area, five‐machine, eight‐bus power system and a large power system (10‐machine, 39‐bus New England system) with the proposed RAFNNPSS under different operating conditions and change in system parameters have been investigated. The simulation results obtained from the conventional PSS (CPSS) and Fuzzy logic‐based PSS (FPSS) are compared with the proposed RAFNNPSS. The simulation results demonstrate that the proposed RAFNNPSS performs well in damping and quicker response when compared with the other two PSSs. Copyright © 2008 John Wiley & Sons, Ltd.
M. Abdulrahim, Zakaria Fadl Almoula, Hafid Al-Hafid, Nader Barsoum, Sermsak Uatrongjit, and Pandian Vasant
AIP
Optimal tuning of power system stabilizer (PSS) parameters using genetic algorithm with single objective function is presented in this paper. A Single Machine Infinite Bus (SMIB) system is considered. The main objective of this research paper is to investigate the suitability of genetic algorithm for effective tuning of parameters of the power system stabilizer in a single machine infinite bus system. A conventional speed based lead‐lag PSS is used. A simple and effective method of tuning the parameters of PSS is proposed which is posed as an optimization formulation by maximizing the damping of modes of oscillations of the SMIB system over a wide range of loading conditions and different system configurations. It is found that GA based PSS with single objective design shows improved dynamic performance over Conventional PSS over a wide range of operating conditions and different system parameters.