National scale electricity sector model to strategize national clean energy transition

This study develops an open-source model adapted from Python for Power System Analysis (PyPSA), to analyze transition pathways through 2030 and 2050, validated against 2019 national data for Thailand's fossil fuel-dominated power sector. Utilizing 30 km × 30 km resource potential, hourly demand data, national policies, and energy strategies, PyPSA-TH (Thailand) evaluates ten scenarios. Pledged and higher ambition scenarios integrate supply-side renewable energy expansion with demand-side energy efficiency, flexibility, and regional hydro imports. In 100% clean energy scenarios (2050), model results project an installed capacity of 369.71 GW (7.4-fold higher than 2019), primarily driven by solar (132.74 GW), wind (76.10 GW), and battery storage (83.44 GW), generating 523.5 TWh. 100% clean energy supply combined with energy efficiency and demand-side flexibility scenario indicates a need for an installed capacity of 207.10 GW, where solar drives the key share (56.82 GW), followed by wind (48.14 GW) and battery storage (25.61 GW). Combining supply- and demand-side measures reduces power generation costs to €0.065/kWh, from €0.070/kWh with supply-side interventions alone. Demand-side strategies lower land requirements to 3152.64 km² (0.61% of Thailand's land) from 5612.87 km² (1.09%) compared to supply-side-only measures and investment needs for capacity expansion rises by 48%, generating 9.43 million new jobs, 1.33 times more than supply-side-only pathways. The emission pathway associated with supply-plus demand-side strategies provides clear near-term benefits compared to supply-side-only planning strategies. PyPSA-TH's transparent and reproducible framework is useful in deriving policy guidelines, including green financing and land-use management, to achieve a sustainable energy future for Thailand and similar developing nations.