TES Discharge Screen

Annual storage optimisation often treats thermal storage like a battery with a constant charge/discharge power ceiling. For a sensible-heat packed bed serving a fixed process temperature, outlet temperature and deliverable high-quality heat fall during discharge. This project derives a state-dependent capability curve from a targeted dynamic model, carries it into annual optimisation, and measures whether the added fidelity changes cost, sizing or technology ranking.

• Reduced state: scalar state of charge is not sufficient for arbitrary hand-constructed packed-bed states, but realistic forward/backward cycling in the current model stays within the project's 5% reduced-state tolerance.
• Matched annual comparison: after removing earlier confounds, the isolated cost effect of the state-dependent discharge shape is documented as roughly 0.000% to 0.038% across the tested 2–12 h duration family.
• FMU cross-check: the committed verification reports 0.23% maximum temperature deviation and 0.0029% relative energy deviation between the Modelica/FMU and Python packed-bed implementations for the declared test.
• Decision boundary: temperature-quality requirements and heat-exchanger approach can matter far more than the small annual objective delta, including regimes where feasible storage sizing collapses.

This is a screening framework, not a design tool or a validated model of a real storage installation. Current cases use synthetic loads and prices; there is no measured-storage validation, materials degradation, corrosion/containment engineering, forecast uncertainty or plant-specific process dynamics. The repository documents these limits alongside the results.