This study examines how to integrate flexibility into long-term energy system models by enhancing both temporal and spatial granularity. Traditional TIMES-based models, typically using 4–12 time slices and aggregated regional structures, cannot adequately capture renewable variability and grid constraints. To address this, we developed a framework incorporating substation-level transmission capacity and 200 time slices, including 184 hourly slices for one representative summer week. A two-stage approach was applied: first, a conventional 16-slice model simulated capacity expansion to 2045; second, a 200-slice model assessed short-term dynamics in 2050. Results demonstrate that hourly granularity reproduces variable renewable generation and storage behavior, especially under stringent CO₂ reduction (90%). While this study focused on pumped storage and batteries, broader flexibility sources such as grid expansion and electrolysis are essential future extensions. The findings indicate that integrating higher-resolution temporal and spatial structures into energy system models improves representation of flexibility needs and strengthens the robustness of decarbonization pathway assessments.
Hiroshi Hamasaki (2026) studied this question.