Elaheh Yaghoubi is a Ph.D. candidate in Electronic and Electrical Engineering at Karabuk University, Turkey, where she has achieved a perfect GPA of 4.0. Her research centers on power system analysis, microgrids, and renewable energy, showcasing her commitment to advancing smart grid technologies. With a robust background in electrical engineering, Elaheh combines academic excellence with practical experience in quality control and web development.
Author Metrics
Google Scholar Profile
Elaheh has several publications under review, showcasing her contributions to the fields of power systems and control strategies. Her works have been recognized for their innovation, particularly in model predictive control and the application of machine learning in smart grids, highlighting her emerging impact in the research community.
- Citations: Elaheh has accumulated a total of 77 citations, with 75 citations since 2019, indicating a strong and growing influence in her field.
- h-index: Her h-index is 6, reflecting that she has six publications that have each been cited at least six times, showcasing her impactful contributions to research.
- i10-index: Elaheh holds an i10-index of 4, meaning she has at least four publications with ten or more citations each, highlighting her ability to produce significant and recognized research outputs.
Education
Elaheh’s academic journey is marked by exceptional achievements: she is currently pursuing her Ph.D. at Karabuk University (2021-present) with a focus on optimal power control, following her M.Sc. from Islamic Azad University (2016-2018) and a B.Sc. from Aryan Institute of Science and Technology (2012-2014), both with a GPA of 4.0. Her strong educational foundation supports her research ambitions in advanced electrical engineering topics.
Research Focus
Her research primarily explores power system stability, microgrid management, and renewable energy integration. Elaheh is particularly interested in model predictive control (MPC) and the application of artificial intelligence techniques, such as machine learning and deep learning, to enhance the efficiency and reliability of smart grids.
Professional Journey
Elaheh’s professional experience includes roles as a Principal Researcher in the PEDAR Group and as a Senior Manager in multiple electronics companies. She has also contributed as a website designer, where she combined her engineering background with web development skills. This diverse experience reflects her capability to integrate technical expertise with managerial responsibilities.
Honors & Awards
She has received the Best Researcher Award, underscoring her dedication to excellence in her research endeavors. This recognition highlights her contributions to innovative solutions in electrical engineering, particularly in the context of microgrids and smart grids.
Publications Noted & Contributions
Elaheh has several publications in reputable journals, focusing on real-time operations in microgrids, model predictive control, and power system risk analysis. Her work aims to push the boundaries of traditional methods, integrating advanced technologies to address contemporary challenges in electrical engineering.
1. A systematic review and meta-analysis of machine learning, deep learning, and ensemble learning approaches in predicting EV charging behavior
- Authors: E. Yaghoubi, E. Yaghoubi, A. Khamees, D. Razmi, T. Lu
- Journal: Engineering Applications of Artificial Intelligence
- Publication Year: 2024
- Summary: This publication presents a comprehensive review and meta-analysis of various machine learning techniques applied to predict electric vehicle (EV) charging behavior. By synthesizing existing studies, it provides insights into the effectiveness and reliability of different algorithms, serving as a valuable resource for future research in EV infrastructure and smart grid integration.
2. A systematic review and meta-analysis of artificial neural network, machine learning, deep learning, and ensemble learning approaches in the field of geotechnical engineering
- Authors: E. Yaghoubi, E. Yaghoubi, A. Khamees, AH Vakili
- Journal: Neural Computing and Applications
- Publication Year: 2024
- Summary: This paper explores the application of advanced computational methods in geotechnical engineering. By evaluating the performance of neural networks and other machine learning techniques, it highlights their potential to improve predictive accuracy in engineering applications, thus contributing to enhanced design and safety standards.
3. Controlling and tracking the maximum active power point in a photovoltaic system connected to the grid using the fuzzy neural controller
- Authors: Z. Yusupov, E. Yaghoubi, E. Yaghoubi
- Conference: 14th International Conference on Electrical and Electronics Engineering
- Publication Year: 2023
- Summary: This conference paper discusses a fuzzy neural controller designed to optimize the power output of photovoltaic systems. By effectively managing the maximum power point tracking (MPPT), this research contributes to the efficiency of solar energy systems, which is crucial for integrating renewable sources into the grid.
4. Modeling and Control of Decentralized Microgrid Based on Renewable Energy and Electric Vehicle Charging Station
- Authors: Z. Yusupov, N. Almagrahi, E. Yaghoubi, E. Yaghoubi, A. Habbal, D. Kodirov
- Conference: World Conference on Intelligent System for Industrial Automation
- Publication Year: 2022
- Summary: This paper presents a model for decentralized microgrids that incorporates renewable energy sources and EV charging stations. The research emphasizes control strategies that enhance the reliability and sustainability of microgrid operations, aligning with the growing need for green energy solutions.
5. Real-time techno-economical operation of preserving microgrids via optimal NLMPC considering uncertainties
- Authors: E. Yaghoubi, E. Yaghoubi, Z. Yusupov, J. Rahebi
- Journal: Engineering Science and Technology, an International Journal
- Publication Year: 2024
- Summary: This study focuses on a novel non-linear model predictive control (NLMPC) approach for the real-time management of microgrids. By considering uncertainties, it aims to optimize techno-economic performance, thus enhancing the operational resilience and economic viability of microgrid systems.
Research Timeline
Elaheh’s research timeline includes her current Ph.D. work from 2021 onwards, with key publications submitted and under review throughout 2024. This timeline indicates her active engagement in research and continuous contributions to the field, aiming to establish a strong foundation for future innovations.
Conclusion
Dr. Elaheh Yaghoubi’s achievements as a Ph.D. candidate at Karabuk University exemplify her dedication to advancing the field of electrical engineering, particularly in power systems and renewable energy. Her innovative research, marked by significant contributions and a strong academic background, has earned her recognition as the Best Researcher. While there are areas for improvement, such as expanding her publication reach and enhancing collaboration efforts, her trajectory suggests a promising future in research. As she continues to push the boundaries of smart grid technologies, Elaheh is poised to make lasting impacts in her field and contribute to sustainable energy solutions.