Assoc. Prof. Dr. Fatih Ünal | Energy Simulation | Best Researcher Award

Fatih Ünal | Energy Simulation | Best Researcher Award

Mechanical Engineering, Mersin University, Turkey

Fatih Ünal is an Associate Professor in the Department of Mechanical Engineering at Mersin University, specializing in energy systems, renewable energy applications, and thermal sciences. He earned his Bachelor’s degree in Mechanical Engineering from Dumlupinar University, followed by a Master’s degree in Heat and Process Engineering at Yildiz Technical University, where he conducted a thesis on the exergy analysis of thermal power plants. He later completed his Ph.D. in the same field at Yildiz Technical University, focusing on the applicability of solar-assisted vertical ground source heat pumps in Mardin. His academic career began at Mardin Artuklu University, where he served as Lecturer, Assistant Professor, and Head of Department, as well as Director of the Distance Teaching Application and Research Center. He later joined Mersin University, advancing to the rank of Associate Professor. His research contributions span photovoltaic performance analysis, solar-assisted Rankine cycles, hybrid energy systems, and geothermal heating applications, with numerous publications in international refereed journals. To date, he has authored 12 scientific documents that have been cited 86 times by 80 different sources, reflecting an h-index of 5, which highlights the growing recognition of his work. His academic journey reflects dedication to advancing renewable energy and sustainable engineering solutions.

Profile: Scopus | ORCID | Google Scholar

Featured Publications

Ünal, F., Şentürk Acar, M., & Demir, B. (2024). Evaluating photovoltaic panel efficiency during the cooling season in Mersin: Insights from alternative performance models. International Journal of Advanced Natural Sciences and Engineering Researches, 8(11), 636–640.

Ünal, F., Şentürk Acar, M., & Demir, B. (2024). Assessment of photovoltaic panel efficiency at various tilt angles in Mersin Province during the cooling season. International Journal of Advanced Natural Sciences and Engineering Researches, 8(11), 641–646.

Ünal, F., & Şentürk Acar, M. (2024). Exergoeconomic analysis of a solar assisted organic Rankine cycle: Case study of Mardin, Turkey. Thermal Science.

Boz, İ., Ayanoğlu, A., Ayas, G., & Ünal, F. (2022). Investigation of temperature effect on electrical efficiency for a photovoltaic–thermal hybrid system. International Journal of Science and Research, 11(8), 1158–1163.

Ünal, F., Akan, A. E., Demir, B., & Yaman, K. (2022). 4E analysis of an underfloor heating system integrated to the geothermal heat pump for greenhouse heating. Turkish Journal of Agriculture and Forestry, 46(5), 762–780.

Dr. Caixin Yan | Power System Optimization | Best Researcher Award

Dr. Caixin Yan | Power System Optimization | Best Researcher Award

PhD Student, Central South University, China

Dr. Caixin Yan is a distinguished researcher at the National Engineering Research Centre of Advanced Energy Storage Materials in Changsha, China. With a deep passion for energy systems and artificial intelligence applications in power grids, Dr. Yan has contributed significantly to the field of energy optimization and power market strategies. His expertise in reinforcement learning and grid stability has made him a prominent figure in the domain of advanced energy storage and smart grid technologies.

Publication Profile

ORCID

🎓 Education:

Dr. Yan pursued his higher education in automation and electrical engineering, focusing on intelligent power grid management and optimization. His academic journey has equipped him with extensive knowledge in multi-energy systems, deep reinforcement learning, and industrial load flexibility.

💼 Experience:

Currently associated with the National Engineering Research Centre of Advanced Energy Storage Materials, Dr. Yan has also collaborated with institutions like the School of Automation at Central South University and the Hunan Xiangjiang Artificial Intelligence Academy. His research focuses on optimizing power systems through artificial intelligence and developing cutting-edge solutions for market-based power regulation.

🏆 Awards and Honors:

While specific awards and honors are not listed, Dr. Yan’s impactful contributions to energy storage, power market strategies, and reinforcement learning applications have been recognized through his publications and collaborations. His research is gaining traction, as evidenced by his growing citation count.

🔍 Research Focus:

Dr. Yan’s research revolves around power grid optimization, energy storage integration, and AI-driven solutions for smart grids. His work on hierarchical reinforcement learning for power grid topology regulation and multi-energy systems operation strategies has been instrumental in advancing the field of intelligent energy management.

🔚 Conclusion:

Dr. Caixin Yan is a rising expert in energy storage and AI-driven power grid optimization. His contributions to power market strategies, reinforcement learning applications, and energy system integration are paving the way for a smarter and more efficient electricity landscape. With growing recognition and impactful research, he continues to make significant strides in the field of intelligent energy solutions. 🚀

📚 Publications :

Review of Power Market Optimization Strategies Based on Industrial Load Flexibility – Analyzing the role of industrial flexibility in power markets.

Power Grid Topology Regulation Method Based on Hierarchical Reinforcement Learning – Exploring AI-driven strategies for grid topology adjustments.

Deep Reinforcement Learning for Strategic Bidding in Incomplete Information Market – Applying AI to strategic bidding in uncertain energy markets.

Optimal Operation Strategies of Multi-Energy Systems Integrated with Liquid Air Energy Storage Using Information Gap Decision Theory – Investigating operational strategies for multi-energy systems.

Load Frequency Control of Photovoltaic Generation-Integrated Multi-Area Interconnected Power Systems Based on Double Equivalent-Input-Disturbance Controllers – Developing control mechanisms for PV-integrated power systems.