A renewable-ammonia export chain must reconcile two mismatched rhythms: electricity from wind/solar arrives stochastically, but Haber-Bosch synthesis runs best near steady-state and ships load in large discrete batches on a fixed schedule. A buffer storage tank is the mass-balance element that absorbs the mismatch:
dS/dt = P(t) − D(t)
P(t) = Pmax · CF(t), CF(t) = clip(CF0 + noise(t), 0, 1)
0 ≤ S(t) ≤ Smax (tank capacity)
D(t) = shipload / Tship at each scheduled loading event
Here S is the tank inventory (tonnes NH₃), P(t) is the instantaneous production rate set by the renewable capacity factor CF(t) — modelled as a mean-reverting stochastic process (an Ornstein-Uhlenbeck-style walk) so power fluctuates realistically around its mean rather than jumping randomly each frame. When the tank is full (S = Smax) any further production is curtailed — the electrolyzer/synthesis loop must throttle down or dump excess renewable power, a real economic loss in these projects. When a ship arrives and the tank holds less than a full cargo, the loading is capacity-limited and the plant is in stockout, which delays vessel departure and cascades through the shipping schedule.
- Mean capacity factor — average renewable output as a fraction of the plant's rated capacity (typical offshore-wind-fed green-ammonia projects target 40–55%).
- Variability — how strongly instantaneous power swings around that mean (calm/steady grid mix vs. gusty/intermittent).
- Buffer tank size — larger tanks smooth more variability but cost more capital; this is the core sizing trade-off in real project design.
- Ship interval — how often a fixed-size cargo is drawn from the tank; tighter shipping schedules need proportionally larger buffers to avoid stockouts.
Real-world relevance: exactly this buffer-sizing problem determines the capital cost and reliability of proposed green-ammonia export hubs (e.g. Western Australia, Chile, Namibia) where wind/solar-only synthesis plants must still deliver ammonia to a fixed shipping schedule.