(Invited Seminar: Dr. Sunwoo Kim, Korea Institute of Energy Research) AI-Based Energy System Optimization Under Uncertainty

Dr. Sunwoo Kim from the Korea Institute of Energy Research (KIER) delivered an invited seminar on “Development of AI-Based Optimization Methods for Energy Systems Under Uncertainty.” During the seminar, he introduced advanced optimization approaches for planning and operating renewable energy systems under uncertainties in renewable energy generation, energy demand, and future investment costs. The presentation highlighted how artificial intelligence can be integrated with stochastic optimization to address the computational complexity of large-scale energy system planning. He also presented AI-assisted optimization frameworks combining Bayesian optimization, mixed-integer linear programming (MILP), and reinforcement learning for renewable energy system design and operation. Applications included international green hydrogen supply chain planning and multi-period capacity investment and energy management of distributed renewable energy systems. The seminar provided students and researchers with insights into how AI-driven optimization approaches can support robust and economically viable decision-making for future low-carbon energy systems.