Perfect-Foresight Flow-Rate Control of a Photovoltaic–Thermal Collector for Thermochemical Storage: An Exergy Upper Bound

Photovoltaic–thermal (PVT) collectors coupled to thermochemical energy storage (TCES) can turn intermittent low-grade solar heat into a dispatchable service, but solar intermittency poses a closed-loop control problem. A companion study established the feedback-only lower bound: a 937 kJ accumulated exergy-delivery-deficit benchmark under optimally tuned proportional–integral–derivative (PID) flow control. The corresponding upper bound is quantified here by means of a deliberately idealised search-based predictive controller that, at each 10 s step, enumerates 51 candidate pump rates, predicts the reactor-inlet temperature by a single forward-Euler step, and is granted perfect future irradiance. On the experimentally validated shared plant (matched to the companion baseline), against an optimally tuned PID, the perfect-foresight advantage is marginal: +0.96% daily exergy on synthetic days and +0.07–0.24% on two measured Walailak University monsoon days, all controllers tracking within 6–13 K on the measured days. Under tropical-monsoon irradiance, the 95 °C desorption setpoint is rarely sustained, so the delivered exergy is nearly controller-independent: the perfect-foresight upper bound lies just above the feedback-only lower bound, and together the two results bracket the exergy envelope available to any flow-rate controller of this system. A horizon sweep localises the bottleneck to internal-model fidelity, not anticipation depth. The eight-node plant is validated against measured module temperature (root-mean-square error 3.5 °C, coefficient of determination R2 = 0.89) and a copper-tube PVT prototype (1.5 °C; peak hot water up to 79 °C). The central contribution is therefore a rigorously defined, experimentally grounded upper bound showing that, at this scale and latitude, deployability rather than anticipation is the effective design lever.