Optimal capacity of renewable energy and methanation system in a remote island model considering frequency fluctuation

This paper presents a novel optimization framework for determining optimal renewable energy and methanation system capacities in remote island power grids while ensuring frequency stability constraints. The proposed method combines hierarchical clustering with mixed-integer linear programming to solve large-scale optimization problems efficiently while maintaining grid frequency within ±0.3 Hz. When applied to Japan’s Tsushima Island power system (peak demand: 36 MW), our approach achieves reductions of over 10 % in operating costs and 15 % in CO 2 emissions compared to conventional diesel-only systems. The key innovation lies in simultaneously addressing frequency stability constraints, renewable energy integration, and methanation system sizing through a comprehensive optimization framework that effectively manages both the variability of renewable sources and decarbonization goals. The optimal facility sizing is determined through the ɛ -constraint method and Pareto optimization to minimize both costs and emissions, thereby establishing a systematic methodology for implementing sustainable energy systems in isolated power grids.