Hamid Karimi | Electrical Engineering | Best Researcher Award

Dr. Hamid Karimi | Electrical Engineering | Best Researcher Award

Qom University of Technology, Iran

Dr. Hamid Karimi is a distinguished researcher in Electrical Power Engineering, recognized internationally for his impactful contributions to renewable energy systems, smart grids, and multi-microgrid optimization. He earned his Ph.D. in Electrical Power Engineering from the Iran University of Science and Technology (2017–2022), where he also completed his M.Sc. (2015–2017) and later pursued postdoctoral research (2022–2023), following his B.Sc. in Electrical Power Engineering from Shahid Beheshti University (2011–2015). Professionally, Dr. Karimi serves as Head of the Central Library and Information Center and Member of the Research Council at Qom University of Technology, alongside roles as Scientific and Executive Editor of the Journal of Power, Control, and Data Processing Systems, and session chair and committee member at leading renewable energy conferences. His research interests span renewable energy integration, demand-side management, multi-energy systems, transactive energy markets, and the application of optimization and AI methods in power systems. With 67 Scopus-indexed publications, 1,355 citations, and an h-index of 22 (24 in Google Scholar, 1,726 citations), he has published in top journals including Applied Energy, Energy, Journal of Energy Storage, and Sustainable Cities and Society, reflecting his strong academic influence. His research skills encompass optimization techniques, stochastic and robust energy scheduling, AI-based resource management, demand response modeling, IoT-enabled smart grid applications, and sustainable system design, underpinned by extensive experience in both theoretical frameworks and applied projects supported by national and international institutions. Among his numerous awards and honors, Dr. Karimi has been consistently ranked as a top student and top research scholar during his academic career, recognized as an Outstanding Reviewer for leading journals, and listed among the world’s top 2% most highly cited scientists in 2024 and 2025, in addition to membership in the National Elite Foundation. In conclusion, Dr. Hamid Karimi exemplifies excellence in research, leadership, and innovation, making significant contributions to advancing sustainable energy solutions, and his proven academic achievements and global recognition highlight his strong potential to continue shaping the future of renewable energy and smart grid systems.

Profile: Scopus | ORCID

Featured Publication

  1. Karimi, H. (2022). A strategy-based coalition formation model for hybrid wind/PV/FC/MT/DG/battery multi-microgrid systems considering demand response programs. International Journal of Electrical Power & Energy Systems, 137, 107642.

  2. Karimi, H. (2022). Daily operation of multi‐energy systems based on stochastic optimization considering prediction of renewable energy generation. IET Renewable Power Generation, 16(2), 301–313.

  3. Karimi, H. (2021). Modeling of transactive energy in multi-microgrid systems by hybrid of competitive-cooperative games. Electric Power Systems Research, 199, 107546.

  4. Karimi, H. (2021). Two-stage economic, reliability, and environmental scheduling of multi-microgrid systems and fair cost allocation. Sustainable Energy, Grids and Networks, 28, 100546.

  5. Karimi, H. (2021). Cooperative energy management of multi-energy hub systems considering demand response programs and ice storage. International Journal of Electrical Power & Energy Systems, 133, 106904.

Duygu Bayram Kara | Engineering | Best Researcher Award

Assoc. Prof. Dr. Duygu Bayram Kara | Engineering | Best Researcher Award

Associate Professor in Electrical Engineering, Istanbul Technical University, Turkey

Duygu Bayram Kara is a seasoned academic and researcher with deep expertise in signal processing, soft computing, and machine learning, particularly applied to condition monitoring, diagnostics, and electric machinery. Currently serving as an Associate Professor at Istanbul Technical University in the Department of Electrical Engineering, she brings over a decade of academic and industry experience. Her research combines theoretical innovation with practical application, contributing to the evolving field of intelligent systems. Her academic journey has been rooted in Istanbul Technical University, where she earned her BSc, MSc, and PhD, focusing on induction motor design and diagnostics using advanced analytical tools such as finite element analysis and wavelet transforms. Duygu has complemented her academic work with international research experiences, notably as a Visiting Researcher at the University of Tennessee, Knoxville. She is also actively involved in public outreach and technical consulting, further underlining her multidisciplinary impact. Her commitment to lifelong learning is reflected in a broad range of certifications and training, including predictive modeling, diagnostics platforms, and simulation software. With a balanced profile that merges strong theoretical grounding, industrial relevance, and societal contribution, Duygu Bayram Kara stands out as a compelling candidate for research honors and recognition.

Professional  Profile

Educational Background

Duygu Bayram Kara holds a comprehensive academic background in Electrical Engineering, having completed all her higher education at the prestigious Istanbul Technical University. She earned her Bachelor of Science degree between 2001 and 2006, focusing on the design of squirrel cage induction motors, which laid the groundwork for her future specialization. Her Master’s degree, completed between 2006 and 2009, involved advanced finite element analysis, specifically examining the impact of time harmonic voltages on induction machines. This rigorous technical foundation was further strengthened by her PhD studies from 2009 to 2015, where she developed innovative methodologies for condition monitoring and fault detection in induction motors using geometric trending and stationary wavelet analysis. Her academic training provided her with solid skills in modeling, simulation, and diagnostics, essential for modern-day electrical engineering challenges. During her educational journey, Duygu not only acquired theoretical knowledge but also demonstrated an ability to apply these skills in research settings, earning her recognition as a technically proficient and research-driven scholar. Her educational pathway reflects a deep and focused commitment to mastering complex electromechanical systems and diagnostic methodologies, which she continues to explore in her academic and industrial collaborations.

Professional Experience

Duygu Bayram Kara has cultivated a rich and diverse professional career centered on electrical engineering, diagnostics, and intelligent systems. She currently serves as an Associate Professor in the Electrical Engineering Department of Istanbul Technical University, where she leads the Intelligent Condition Monitoring & Diagnostics Lab. Her academic journey at the university began as a Research Assistant in 2007, culminating in a decade-long role as Assistant Professor from 2016 to 2025. Beyond academia, she has also worked in industry as a Senior Researcher at MEKATRO Mechatronic Systems Research & Development Corp., where she contributed to the design and optimization of electric vehicle drive systems. Her international exposure includes a stint as a Visiting Researcher at the University of Tennessee, Knoxville, collaborating with the PROACT Lab on reliability and maintainability projects. In addition to her academic and research activities, she has provided consultancy and training for organizations such as the Directorate General of Coastal Safety of Turkiye and ARÇELIK, where she played a key role in designing high-efficiency electric motors. This blend of academic rigor, practical industry involvement, and international collaboration highlights her multifaceted professional profile, showcasing her ability to navigate and impact various sectors in the field of electrical engineering and applied diagnostics.

Research Interests

Duygu Bayram Kara’s research interests lie at the intersection of electrical engineering, machine learning, and system diagnostics. Her primary focus areas include signal processing, condition monitoring, fault diagnostics, soft computing, and electric machinery. She has a particular interest in using machine learning and wavelet-based approaches for predictive maintenance and early fault detection in rotating electrical machines such as induction motors. Her academic foundation in electric machine design allows her to approach diagnostics not only from a data perspective but also from an in-depth understanding of electromechanical system behavior. She is also actively engaged in finite element modeling (FEM) and simulation-based analysis, which she applies to complex system evaluations and component-level analysis. Over the years, Duygu has expanded her research to include intelligent monitoring systems, contributing to innovations in both hardware and software solutions for industrial applications. Her collaborative work in international labs and consulting roles further enriches her research perspective, bridging the gap between theoretical development and industrial needs. She continues to explore new frontiers in diagnostics and reliability engineering, ensuring her work remains aligned with technological advancements and real-world challenges in electrical engineering and system optimization.

Research Skills

Duygu Bayram Kara possesses a robust and versatile research skill set that spans theoretical modeling, computational simulation, experimental diagnostics, and machine learning applications. Her technical toolkit includes advanced proficiency in MATLAB, Python, and simulation software such as ANSYS Maxwell, RMxprt, and FEMM. She has substantial expertise in signal processing techniques, including wavelet analysis and time-frequency representations, used for condition monitoring and fault detection in electric machinery. Her ability to apply finite element analysis (FEA) to evaluate the behavior of electrical machines under different conditions highlights her simulation proficiency. Furthermore, Duygu is trained in using specialized tools such as the MATLAB Diagnostics and Prognostics Toolbox and has completed professional training in predictive modeling and empirical prognostics. She effectively integrates soft computing approaches and artificial intelligence algorithms into traditional electrical engineering problems, thereby contributing to the evolution of intelligent monitoring systems. Her experience working with vibration sensing platforms, coupled with her background in electric machine design, enables her to diagnose faults with high accuracy. This multidisciplinary skill set positions her as a valuable asset in both academic and industrial research environments. She demonstrates not only technical excellence but also a practical orientation, making her a well-rounded and impactful researcher.

Awards and Honors

While the provided profile does not list major competitive awards or honors explicitly, Duygu Bayram Kara has earned significant recognition through her academic, professional, and technical accomplishments. Notably, she became a Senior Member of IEEE in July 2021, a status granted to individuals with extensive experience and significant performance in their field. This recognition reflects her leadership, technical proficiency, and professional involvement in the global electrical engineering community. Additionally, she has participated in numerous prestigious training programs, such as IEEE’s Continuing Education workshops on condition-based monitoring and empirical modeling, as well as specialized certifications in predictive analytics and simulation tools. Her consultancy roles with organizations like ARÇELIK and the Directorate General of Coastal Safety indicate a high level of trust and credibility in her applied research expertise. Furthermore, her involvement in socially impactful events, such as organizing the EU Sustainable Energy Week and educational science outreach programs, speaks to her dedication to science communication and community engagement. Although competitive research awards or grant recognitions are not detailed in her profile, her accumulation of professional certificates, trusted consulting roles, and IEEE senior membership validate her achievements and contributions in the field of diagnostics and electric machinery.

Conclusion

In conclusion, Duygu Bayram Kara presents a compelling case as a candidate for the Best Researcher Award. Her work embodies a rare blend of academic depth, technical innovation, practical industry experience, and international collaboration. With a research focus on condition monitoring, signal processing, and electric machinery diagnostics, she has consistently contributed to both theoretical knowledge and practical solutions. Her robust academic background, enhanced by global exposure and multidisciplinary expertise, positions her as a leading figure in her field. Her profile reflects not only excellence in research but also a commitment to societal advancement through education and public engagement. Moreover, her consultancy experience and continuous professional development underscore her dynamic approach to solving real-world engineering challenges. While the profile could benefit from more detailed recognition through competitive research awards or high-profile grants, her achievements across teaching, research, and service clearly indicate sustained impact and leadership. Overall, Duygu Bayram Kara stands out as a researcher who combines innovative thinking with technical mastery, making her a worthy nominee for distinguished research accolades and recognition in the global academic and engineering community.

Publications Top Notes

  1. Degradation assessment of an IGBT with recurrence analysis and Kalman filter based data fusion
    Authors: Duygu Bayram Kara
    Journal: Chaos, Solitons and Fractals
    Year: 2024

  2. Park vector approach based misalignment detection strategy for IMs (Conference Paper)
    Authors: Ege Kahraman, Anil Erkut Ulusoy, Mehmet Ozan Şerifoğlu, Duygu Bayram Kara
    Year: 2024
    Citations: 1

 

Dongju Chen | Engineering | Best Researcher Award

Prof. Dongju Chen | Engineering | Best Researcher Award

university professor from Beijing University of Technology, China

Dongju Chen is a distinguished professor and doctoral supervisor at the College of Mechanical & Energy Engineering, Beijing University of Technology. With a Ph.D. in mechanical engineering from the University of Gombigne, France, and Harbin Institute of Technology, she has made significant contributions to precision machining and mechanical systems. She serves as an assistant director at the Institute of CNC Precision Machining Technology and has been recognized through multiple prestigious talent programs, including the “Rixin Talents” Training Program and the “Qingbai Talents” Hundred Talents Program. As a senior member of CMES, IEEE fellow, and Secretary of the Production Engineering Society of China, she plays a crucial role in advancing the field of mechanical engineering. Her research primarily focuses on ultra-precision machine tools, micro-nano processing, and hydrostatic spindle mechanics. She is an esteemed reviewer for several high-impact journals and an active participant in national research initiatives. Dongju Chen has authored numerous influential publications, contributing to advancements in manufacturing technology and precision machining.

Professional Profile

Education

Dongju Chen holds a Ph.D. in mechanical engineering, earned through a joint program between the University of Gombigne in France and Harbin Institute of Technology in China. This dual-degree program provided her with an extensive foundation in advanced mechanical systems and manufacturing technologies. Her academic journey has been instrumental in shaping her expertise in ultra-precision machining, fluid mechanics, and micro-nano-scale processing. The rigorous training at these prestigious institutions equipped her with a deep understanding of both theoretical and applied aspects of mechanical engineering. Throughout her education, she actively engaged in research projects that explored error identification in machine tools and the influence of micro-scale fluids on machining performance. Her commitment to academic excellence led to numerous collaborations with international research teams and further strengthened her expertise in manufacturing technology.

Professional Experience

Dongju Chen has had a remarkable professional career, contributing significantly to academia and research in mechanical engineering. Since completing her Ph.D. in 2010, she has been a faculty member at Beijing University of Technology, serving as a professor and doctoral supervisor at the College of Mechanical & Energy Engineering. She is also an assistant director at the Institute of CNC Precision Machining Technology, where she leads research on precision machining techniques. Throughout her career, she has held key positions in professional societies, including Secretary of the Production Engineering Society of China and a senior CMES member. As a recognized expert, she has contributed to evaluating research projects for institutions like the National Natural Science Foundation of China and the Zhejiang Natural Science Foundation. Her role as a reviewer for prestigious journals, such as the Journal of Manufacturing Science and Technology (JMST) and Measurement and Advanced Manufacturing Technology (AMT), further highlights her influence in the field.

Research Interests

Dongju Chen’s research is centered on precision machining, ultra-precision machine tools, and fluid-structure interactions in mechanical systems. She is particularly interested in error identification and detection technologies for ultra-precision machine tools, investigating the dynamic behavior of hydrostatic spindles and their interactions with micro-scale fluids. Another key area of her research focuses on the influence of micro-nano-scale fluid mechanics on the performance of machine tool components. Additionally, her studies extend to the dynamic contact mechanisms of hydrostatic spindle-solid coupling under the influence of slip, contributing to enhanced machining accuracy and efficiency. She has also explored micro-nano-scale processing techniques and their implications in advanced manufacturing. Her work plays a crucial role in improving machining precision, enhancing industrial manufacturing processes, and developing innovative solutions for high-precision engineering applications.

Research Skills

Dongju Chen possesses a diverse set of research skills that have enabled her to make substantial contributions to mechanical engineering. Her expertise includes numerical simulation techniques, computational fluid dynamics (CFD), and finite element analysis (FEA) to study machining processes at micro and nano scales. She has extensive experience in error identification and detection methodologies, crucial for optimizing the performance of ultra-precision machine tools. Additionally, her skills in molecular dynamics simulations allow her to investigate the rheological performance of lubricant oils in machining applications. Her proficiency in tribology, hydrostatic spindle mechanics, and fluid-structure interactions further strengthen her research capabilities. Beyond computational methods, she has expertise in experimental techniques for evaluating spindle dynamics and machining accuracy. Her interdisciplinary approach, combining theoretical modeling with experimental validation, has been instrumental in advancing precision machining technologies.

Awards and Honors

Dongju Chen has received several prestigious awards in recognition of her contributions to mechanical engineering. She was selected for the “Rixin Talents” Training Program of Beijing University of Technology in 2012, highlighting her exceptional research potential. In 2016, she was honored as a “New Star of Science and Technology” in Beijing, acknowledging her impact on technological advancements in manufacturing. The same year, she was inducted into the “Qingbai Talents” Hundred Talents Program of Beijing University of Technology, further solidifying her status as a leading researcher in the field. Her contributions have also been recognized through memberships in esteemed professional societies, including IEEE fellowship and senior membership in CMES. Her publications in top-tier journals have received widespread acclaim, further affirming her influence and expertise in precision machining and advanced manufacturing technologies.

Conclusion

Dongju Chen is a highly accomplished researcher and professor in the field of mechanical engineering, with a strong focus on ultra-precision machining and fluid-structure interactions. Her contributions to research, education, and professional organizations have positioned her as a leading expert in precision engineering. Through her extensive academic background, numerous publications, and leadership roles, she has significantly influenced the development of advanced manufacturing technologies. Her commitment to innovation and excellence continues to drive progress in the field, making her a valuable asset to both academia and industry. As a mentor and educator, she plays a vital role in shaping the next generation of engineers, ensuring the continued advancement of precision machining technologies.

Publication Top Notes

  1. A study of the influence of speed effect on the kinematic behavior of aerostatic spindles

    • Authors: D. Chen, X. Du, J. Fan, K. Sun, H. Wang
    • Year: 2025
  2. Study on the mechanism of correlation between surface quality and tissue properties of Ti6Al4V alloy formed by selective laser melting

    • Authors: D. Chen, G. Li, P. Wang, Y. Tang
    • Year: 2025
  3. Optimization of multi-axis laser shock peening process for nickel alloy components based on workpiece curvature and equipment dynamic performance

    • Authors: R. Pan, Y. Xing, R. Wang, K. Sun, P. Gao
    • Year: 2024
  4. The tribological properties of nano-lubricants and their application on bearings: recent research progress

    • Authors: J. Li, D. Chen, H. Zhang, J. Fan, Y. Tang
    • Year: 2024
    • Citations: 2
  5. Tool inclination angle designing for low-deformation and high-efficiency machining of thin-wall blade based on edge-workpiece-engagement

    • Authors: D. Chen, S. Wu, J. Wu, J. Fan, Y. Tang
    • Year: 2024
  6. A systematic review of micro-texture formation based on milling: from mechanism, existing techniques, characterization to typical applications

    • Authors: Z. Jiang, D. Chen, K. Sun, J. Fan, Y. Tang
    • Year: 2024
  7. Coupling effect of partial composite texture and thermal effect on the performance of hydrostatic bearing

    • Authors: D. Chen, Y. Cui, K. Sun, J. Fan, K. Cheng
    • Year: 2024
  8. Ball-end milling stability and force analysis in the presence of inclination angles through a new algorithm with numerical chip thickness in edge-workpiece engagement

    • Authors: S. Wu, D. Chen, J. Fan, Y. Tang
    • Year: 2024
  9. Unbalanced vibration suppressing for aerostatic spindle using sliding mode control method and piezoelectric ceramics

    • Authors: D. Chen, X. Zhang, H. Wang, J. Fan, D. Liang
    • Year: 2024
  10. Analysis of the impact of graphene nano-lubricating oil on thermal performance of hydrostatic bearing

  • Authors: D. Chen, Y. Zhao, K. Sun, R. Pan, J. Fan
  • Year: 2024
  • Citations: 2

Ayman AL-Quraan | Engineering | Best Researcher Award

Assoc. Prof. Dr. Ayman AL-Quraan | Engineering | Best Researcher Award

Associate Professor at Yarmouk University, Jordan

Dr. Ayman A. Al-Quraan, born in Abu Dhabi, UAE in 1986, is an Associate Professor in the Department of Electrical Power and Energy at Yarmouk University in Irbid, Jordan. He earned his Ph.D. in Electrical and Computer Engineering from Concordia University, Montreal, in 2016. After completing his doctoral studies, he undertook a brief postdoctoral position at Concordia University before joining Yarmouk University in 2017. He is the founder of the Power and Energy Research Lab at Yarmouk University and has significantly contributed to research in the fields of power systems and renewable energy. His research interests focus on optimizing hybrid renewable energy systems (HRES) and developing capacity determination and energy management strategies. Dr. Al-Quraan has served in various editorial roles for top-tier international journals and has received several research grants and funding for his projects. He is also recognized for his extensive academic contributions, having published several articles in well-respected journals and conferences. His work in renewable energy optimization and system modeling reflects his commitment to addressing global energy challenges through research and innovation.

Professional Profile

Education:

Dr. Ayman A. Al-Quraan completed his academic journey with a Ph.D. in Electrical and Computer Engineering from Concordia University in Montreal, Canada, in 2016. Prior to this, he obtained his Master’s degree in Electrical Power Engineering in 2011 and his Bachelor’s degree in Electrical Power Engineering in 2009, both from Yarmouk University, Jordan. His academic pursuits reflect a strong foundation in power engineering, with particular emphasis on energy systems and optimization. During his doctoral studies, Dr. Al-Quraan conducted advanced research in the field of urban wind energy estimation, contributing to the understanding of renewable energy potential in urban environments. His graduate studies at Yarmouk University were marked by excellence, as evidenced by scholarships and awards, including the King Abdullah Fund Grant during his undergraduate years. The combination of his diverse educational background and solid academic performance has positioned Dr. Al-Quraan as a leading figure in the power and energy sector, fostering significant contributions to both research and teaching. His doctoral research, in particular, allowed him to engage deeply with renewable energy technologies, a key area in his ongoing work at Yarmouk University.

Professional Experience:

Dr. Ayman A. Al-Quraan has extensive professional experience in both academic and industry settings. After completing his doctoral studies at Concordia University, he joined Yarmouk University in 2017, where he currently serves as an Associate Professor in the Department of Electrical Power and Energy. He has held various roles at Yarmouk University, including Assistant Professor and Research Assistant, and has contributed to the development of the university’s Power and Energy Research Lab. Additionally, he has participated as a Principal Investigator in several research projects, such as those focused on optimizing Hybrid Renewable Energy Systems (HRES), receiving funding from Yarmouk University for his innovative work. Dr. Al-Quraan’s professional background also includes industry experience at the National Electrical Power Company (NEPCO) in Jordan, where he worked as an Electrical Substation Engineer from 2008 to 2009. His industry experience complements his academic roles, allowing him to bridge the gap between theoretical research and practical application. Furthermore, Dr. Al-Quraan’s role as an editor and guest editor for several international journals, including those in the renewable energy field, further demonstrates his significant impact on the academic and professional community.

Research Interests:

Dr. Ayman A. Al-Quraan’s research interests lie at the intersection of renewable energy systems, power optimization, and energy management strategies. His work primarily focuses on the development and optimization of Hybrid Renewable Energy Systems (HRES), specifically addressing the challenges of integrating multiple energy sources, such as solar and wind, into a cohesive system for efficient power generation. He has conducted extensive research on predictive control and capacity determination strategies for renewable energy systems, aimed at maximizing energy yield and ensuring sustainability in both connected and isolated systems. Additionally, Dr. Al-Quraan is interested in the application of optimization techniques to solve complex energy management problems, such as those found in off-grid systems and urban energy solutions. His interdisciplinary approach combines electrical engineering, energy optimization, and control systems. As a Principal Investigator (PI) for a project related to n-layers optimization for HRES, Dr. Al-Quraan continues to push the boundaries of research in energy systems. His expertise in modeling and control has led to significant contributions to the understanding and development of efficient energy solutions that are critical to addressing global energy demands.

Research Skills:

Dr. Ayman A. Al-Quraan possesses a robust skill set that allows him to lead cutting-edge research in the fields of power engineering and renewable energy systems. His skills in modeling and optimization techniques have been critical in his work on Hybrid Renewable Energy Systems (HRES), where he applies advanced mathematical models to optimize energy production and consumption. Dr. Al-Quraan is proficient in the use of predictive control systems, which is central to his research on energy management strategies for renewable systems. He is also skilled in wind and solar energy estimation techniques, utilizing tools such as wind tunnels and data collection for urban energy analysis. As an academic editor and reviewer for several international journals, Dr. Al-Quraan demonstrates a keen eye for quality research and contributes his expertise to the scientific community. His ability to collaborate across disciplines, along with his strong knowledge of electrical power systems and renewable energy technologies, further enhances his research capabilities. Dr. Al-Quraan’s technical skills are complemented by his leadership in securing research funding, which has enabled him to spearhead innovative projects in energy optimization.

Awards and Honors:

Dr. Ayman A. Al-Quraan’s academic journey has been marked by numerous awards and honors that reflect his dedication and excellence in research and education. As a graduate student, he was awarded the Graduate Research Assistantship at Concordia University from 2012 to 2016, recognizing his outstanding research capabilities during his Ph.D. studies. He also received a Ph.D. scholarship from Yarmouk University, which supported his doctoral research in renewable energy. His undergraduate and graduate studies were funded by prestigious scholarships, including the King Abdullah Fund Grant, which allowed him to pursue his education with distinction. Dr. Al-Quraan was ranked first in both his Bachelor’s and Master’s degrees in Electrical Power Engineering at Yarmouk University, which is a testament to his academic excellence. These awards highlight Dr. Al-Quraan’s strong commitment to advancing the field of electrical power and energy systems, especially in the areas of renewable energy optimization and energy management strategies. His accomplishments have earned him recognition both locally and internationally, making him a prominent figure in the academic and professional energy sectors.

Conclusion:

Dr. Ayman A. Al-Quraan is an exemplary candidate for the Research for Best Researcher Award due to his profound contributions to the fields of electrical power engineering and renewable energy systems. His expertise in optimizing hybrid energy systems, coupled with his leadership in establishing research labs and securing funding, positions him as a leader in his field. Dr. Al-Quraan’s involvement in prestigious editorial roles and his publication record in top-tier journals further attests to his influence in the academic community. His work on energy management strategies, particularly in the context of hybrid renewable energy systems, has significant implications for sustainable energy solutions. While there are opportunities for further industry collaboration and public outreach, Dr. Al-Quraan’s research continues to drive innovation in energy systems, contributing to the global pursuit of sustainability. With a strong foundation in both academic research and practical experience, he is highly deserving of this prestigious award.

Publication Top Notes

  • Title: Urban wind energy: Some views on potential and challenges
    • Authors: T. Stathopoulos, H. Alrawashdeh, A. Al-Quraan, B. Blocken, A. Dilimulati, …
    • Journal: Journal of Wind Engineering and Industrial Aerodynamics
    • Volume: 179
    • Pages: 146-157
    • Citations: 229
    • Year: 2018
  • Title: Comparison of wind tunnel and on-site measurements for urban wind energy estimation of potential yield
    • Authors: A. Al-Quraan, T. Stathopoulos, P. Pillay
    • Journal: Journal of Wind Engineering and Industrial Aerodynamics
    • Volume: 158
    • Pages: 1-10
    • Citations: 80
    • Year: 2016
  • Title: Modelling, design and control of a standalone hybrid PV-wind micro-grid system
    • Authors: A. Al-Quraan, M. Al-Qaisi
    • Journal: Energies
    • Volume: 14 (16)
    • Article Number: 4849
    • Citations: 61
    • Year: 2021
  • Title: Active and reactive power control for wind turbines based DFIG using LQR controller with optimal Gain‐scheduling
    • Authors: A. Radaideh, M. Bodoor, A. Al-Quraan
    • Journal: Journal of Electrical and Computer Engineering
    • Year: 2021
    • Article Number: 1218236
    • Citations: 38
  • Title: Assessment of wind energy resources in Jordan using different optimization techniques
    • Authors: B. Al-Mhairat, A. Al-Quraan
    • Journal: Processes
    • Volume: 10 (1)
    • Article Number: 105
    • Citations: 29
    • Year: 2022
  • Title: Optimal coordination of wind power and pumped hydro energy storage
    • Authors: H. M. K. Al-Masri, A. Al-Quraan, A. AbuElrub, M. Ehsani
    • Journal: Energies
    • Volume: 12 (22)
    • Article Number: 4387
    • Citations: 25
    • Year: 2019
  • Title: Rolling horizon control architecture for distributed agents of thermostatically controlled loads enabling long-term grid-level ancillary services
    • Authors: A. Radaideh, A. Al-Quraan, H. Al-Masri, Z. Albataineh
    • Journal: International Journal of Electrical Power & Energy Systems
    • Volume: 127
    • Article Number: 106630
    • Citations: 22
    • Year: 2021
  • Title: Optimal prediction of wind energy resources based on WOA—A case study in Jordan
    • Authors: A. Al-Quraan, B. Al-Mhairat, A. M. A. Malkawi, A. Radaideh, H. M. K. Al-Masri
    • Journal: Sustainability
    • Volume: 15 (5)
    • Article Number: 3927
    • Citations: 20
    • Year: 2023
  • Title: Minimizing the utilized area of PV systems by generating the optimal inter-row spacing factor
    • Authors: A. Al-Quraan, M. Al-Mahmodi, K. Alzaareer, C. El-Bayeh, U. Eicker
    • Journal: Sustainability
    • Volume: 14 (10)
    • Article Number: 6077
    • Citations: 20
    • Year: 2022
  • Title: Machine learning classification and prediction of wind estimation using artificial intelligence techniques and normal PDF
    • Authors: H. H. Darwish, A. Al-Quraan
    • Journal: Sustainability
    • Volume: 15 (4)
    • Article Number: 3270
    • Citations: 19
    • Year: 2023