The transformation to a climate-neutral electricity economy makes the sustainable generation of electricity from renewable energies a key technology. However, the widespread use of renewable energy faces several challenges, especially its volatility and locally limited availability. Addressing the temporal and geographic mismatch between renewable energy supply and demand is therefore crucial for a successful carbon-neutral electricity economy. Large-scale, transportable, and storable energy carriers are a key element in redressing this imbalance. Besides hydrogen-based fuels, metal fuels and iron in particular are promising alternatives to serve this purpose: electrical energy from renewable sources is stored by thermochemical reduction of iron oxides with green hydrogen and can be converted back into electricity by thermochemical oxidation (e.g., in retrofitted coal-fired power plants) spatially and temporally separated from the storage process. Despite the increasing interest in metal fuels, not many cycle analyses are available. This study provides quantitative and qualitative information on the thermodynamic performance of two thermodynamically controlled regeneration processes for iron oxides utilising a shaft furnace and a flash reactor, respectively. For the shaft furnace direct reduction of iron oxides energetic and exergetic efficiencies of 59.4% and 51.4 %, respectively, are determined. A sensitivity analysis indicates that energetic efficiencies up to 63.0% might be achievable within the model assumptions. The evaluation of the flash reactor direct reduction of iron oxides shows energetic and exergetic efficiencies of 68.5% and 59.9 %, respectively. In this case, optimal values based on sensitivity analyses lead to an energetic efficiency of 71.0% within the model assumptions. In addition to the use of commercial software, a modelling environment with direct access to mathematical optimisation techniques is in development and showcased for the flash reduction process leading to energetic efficiencies of 73.1 %. The developed models are the foundation for future thermoeconomic evaluations.