Dan li | Smart Energy System | Research Excellence Award

Published on by Natural Scientist Awards

Dr. Dan li | Smart Energy System | Research Excellence Award

Dr. Dan li | China Three Gorges University | China

Dr. Dan Li is an accomplished researcher in intelligent energy systems, with a strong focus on optimal scheduling, risk measurement, and intelligent decision-making for multi-energy systems operating under a high proportion of renewable energy. His work addresses the increasing complexity and uncertainty of modern power grids by developing advanced computational approaches that integrate artificial intelligence with domain-specific physical principles. Through three significant completed and ongoing research projects, he has contributed to flexible resource regulation and control technology for new-energy pumped storage power stations, the development and application of key technologies for grid-connected performance testing and analysis of renewable energy stations, and the functional debugging and data-processing framework for intelligent network-source coordinated control and risk early-warning decision-making platforms. His key scientific contribution lies in accurately defining the physical constraints, operational limits, and security boundaries of unit commitment and economic dispatch problems, and translating these elements into optimization objectives and state spaces suitable for advanced algorithms. Dr. Li introduced a physics-informed exploration strategy for deep reinforcement learning by embedding prior knowledge, including power-flow equations and unit ramp-rate constraints, directly into the reward design, reducing invalid exploration and improving algorithmic convergence by over 50 percent. This approach demonstrates a powerful integration of domain expertise and advanced computational tools, contributing significantly to enhancing the reliability, efficiency, and intelligence of next-generation power systems. His published research, including his recent article on optimization solutions for power generation planning, reflects strong scientific rigor and technological relevance, reinforcing his position as a promising contributor to the advancement of intelligent and sustainable energy systems.

Profile: ORCID

Featured Publications

Li, D., Zhang, L., Mi, N., & Zhong, H. (2025). Optimization solution for unit power generation plan based on the integration of constraint identification and deep reinforcement learning. Processes.

 

Ziyodulla Yusupov | Renewable Energy | Editorial Board Member

Published on by Natural Scientist Awards

Prof. Dr. Ziyodulla Yusupov | Renewable Energy | Editorial Board Member

Professor | Karabuk University | Turkey

Prof. Dr. Ziyodulla Yusupov is a leading researcher in electrical power systems with a strong focus on optimization, intelligent control, microgrid operation, renewable energy integration, and electric vehicle–based energy solutions. His work centers on enhancing system reliability, improving energy efficiency, and advancing sustainable technologies for future power networks. He has played a key role in major international and national research initiatives, most notably the Uzbekistan–Belarus collaborative project (2024–2025) on decentralized electric vehicle charging systems, where he contributes to proposal development, intelligent scheduling strategies, system design, and annual research reporting. His earlier national projects span critical areas such as frequency-adjustable electric drives, resource-saving control modes, energy-efficient pump station operations for mining and agriculture, and the modeling and optimization of electric, hydraulic, and mechanical processes in pump systems. These projects highlight his long-standing expertise in energy management, dynamic system modeling, and the development of rational control principles that improve operational sustainability across industrial utilities. Prof. Yusupov’s research output includes widely cited publications on superconducting magnetic energy storage optimization, integrated photovoltaic systems for power system stability, renewable energy assessment, and the role of clean energy in reducing emissions. His work contributes to advancing the understanding of how renewable resources, storage technologies, and smart control systems can be harmonized to support resilient, low-carbon energy infrastructures. Through his extensive research contributions, collaborative projects, and sustained focus on innovation, he continues to influence the evolution of modern power systems and supports global efforts toward cleaner, smarter, and more efficient energy solutions.

Profile:  Scopus  |  ORCID  |  Google Scholar

Featured Publications

Khaleel, M., Yusupov, Z., Nassar, Y., El-Khozondar, H. J., Ahmed, A., & Alsharif, A. (2023). Technical challenges and optimization of superconducting magnetic energy storage in electrical power systems. e-Prime: Advances in Electrical Engineering, Electronics and Energy, 5, 100223.

Khaleel, M., Yusupov, Z., Ahmed, A., Alsharif, A., Nassar, Y., & El-Khozondar, H. (2023). Towards sustainable renewable energy. Applied Solar Energy, 59(4), 557–567.

Nassar, Y., El-Khozondar, H. J., Ghaboun, G., Khaleel, M., Yusupov, Z., … (2023). Solar and wind atlas for Libya. International Journal of Electrical Engineering and Sustainability, 27–43.

Khaleel, M., Yusupov, Z., Yasser, N., El-Khozondar, H., & Ahmed, A. A. (2023). An integrated PV farm to the unified power flow controller for electrical power system stability. International Journal of Electrical Engineering and Sustainability, 18–30.

Khaleel, M., Yusupov, Z., Alderoubi, N., Abdul_jabbar, R. L., Elmnifi, M., … (2024). Evolution of emissions: The role of clean energy in sustainable development. Challenges in Sustainability, 12(2), 122–135.