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Assist. Prof. Dr. Ehsanolah Assareh | Energy | Editorial Board Member 

Assistant Professor | Yeungnam University | South Korea

Ehsanolah Assareh is an accomplished assistant professor affiliated with YU University in South Korea and IAUD University in Iran, with a strong interdisciplinary background in hydrogen energy, artificial intelligence, renewable energy technologies, engineering thermodynamics, and cogeneration systems. He is widely recognized for his influential contributions to energy modeling, optimization, and sustainable energy system design, reflected in more than 2000 citations, an h-index of 22, and an i10-index of 39. His early highly cited works on artificial neural networks for solar radiation prediction and on particle swarm optimization and genetic algorithms for energy demand forecasting in Iran laid a strong foundation for the application of intelligent optimization techniques in energy systems engineering. Over the years, his research has expanded to include advanced forecasting of oil demand, carbon dioxide emissions, and wind speed, as well as the optimization of wind turbines, heat exchangers, and composite structures using evolutionary algorithms. In recent years, his focus has shifted strongly toward integrated renewable and multigeneration systems, particularly the coupling of solar, geothermal, and thermoelectric generators for electricity, cooling, and desalination, along with detailed energy, exergy, and exergoeconomic analyses. He has also made notable contributions to green hydrogen production, power-to-hydrogen and hydrogen-to-power conversion, and techno-economic feasibility studies of hybrid wind–solar systems for rural electrification. His publications in leading journals such as Energy, Solar Energy, Fuel, Renewable and Sustainable Energy Reviews, Geothermics, and the International Journal of Hydrogen Energy demonstrate both technical depth and practical relevance. Through consistent high-impact research, international collaborations, and editorial service, Assareh has played a significant role in advancing intelligent energy systems, sustainable power generation, and hydrogen-based energy solutions at both national and global levels.

Profile: Google Scholar

Featured Publications

  1. Behrang, M. A., Assareh, E., Ghanbarzadeh, A., & Noghrehabadi, A. R. (2010). The potential of different artificial neural network techniques in daily global solar radiation modeling based on meteorological data. Solar Energy, 84(8), 1468–1480.

  2. Assareh, E., Behrang, M. A., Assari, M. R., & Ghanbarzadeh, A. (2010). Application of particle swarm optimization and genetic algorithm techniques on demand estimation of oil in Iran. Energy, 35(12), 5223–5229.

  3. Behrang, M. A., Assareh, E., Noghrehabadi, A. R., & Ghanbarzadeh, A. (2011). New sunshine-based models for predicting global solar radiation using particle swarm optimization technique. Energy, 36(5), 3036–3049.

  4. Alirahmi, S. M., & Assareh, E. (2020). Energy, exergy, and exergoeconomic analysis and multi-objective optimization of a multi-generation energy system for day and night time power generation. International Journal of Hydrogen Energy, 45(56), 31555–31573.

  5. Assareh, E., & Biglari, M. (2015). A novel approach to capture the maximum power from variable speed wind turbines using PI controller, RBF neural network and gravitational search algorithm. Renewable and Sustainable Energy Reviews, 51, 1023–1037.

Ehsanolah Assareh’s research bridges artificial intelligence with renewable and hydrogen energy systems to deliver high-impact solutions for sustainable power generation and energy optimization. His innovations in smart forecasting, multigeneration systems, and green hydrogen technologies support global decarbonization, energy security, and the transition to clean, resilient energy infrastructures.

Ehsanolah Assareh | Energy | Editorial Board Member

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