Modeling, Design and Engineering Optimization of Energy Systems

This Reprint compiles cutting-edge research on modeling, design, and engineering optimization for sustainable energy systems. It addresses critical global challenges-climate change mitigation, renewable integration, and efficiency enhancement-through innovative methodologies and computational tools. Key themes in this collection include the following: Energy Storage and Conversion: Optimization of electrochemical/hybrid storage to balance renewable variability, bolster grid resilience, and quantify environmental benefits. Hydrogen and Fuel Cells: Advances in green hydrogen systems, including integrated power-to-gas with fuel cells, autonomous operation, carbon-trading incentives, and flexible cogeneration. AI-Driven Optimization: AI applications for precision carbon management, adaptive system reconfiguration, and risk-informed decision-making under uncertainty. Renewable Integration: Smart strategies for improving renewable penetration, featuring spatiotemporal modeling of EV mobility, cost-minimized charging infrastructure, and demand-side management. The contributions highlight co-optimization frameworks that minimize costs/emissions while enhancing reliability. This collection paves the way for low-carbon transitions in the power, transportation, and industrial sectors through interdisciplinary engineering solutions.