Forecast Calibration and Charging Feedback in PV–Battery Scheduling Across Three Environments

Forecast calibration changes battery schedules, but its economic effect depends on how planned actions are executed. We cross two residual calibrations of photovoltaic (PV) and load forecasts with a charging-only feedback rule in hourly receding-horizon scheduling with five- or fifteen-minute execution. Environment A combines modeled PERFORM PV with scaled ERCOT Coast demand; B and C are metered CoSSMic households. Three environments, three forecast treatments, three feedback intensities, and three tariff scenarios give 81 configurations, 18 of which duplicate uncalibrated cells because validation selected zero weighted-mean gain for B and C. Median calibration lowers A’s first-step net-load mean absolute error by 8.47% yet raises its cost, whereas in B and C it increases the error by 0.695% and 0.629%. Under the reference tariff, the calibration-by-feedback interaction is −3622.9 currency units (CU) (−0.251%) in A, where the more accurate forecast costs more, and CU −0.279 (−0.088%) and CU −0.371 (−0.117%) in B and C, where feedback attenuates the cost of a worse correction. Identical charging requests can yield different actions because state-of-charge histories differ. Doubling storage in C reverses the interaction to CU +0.370 (+0.124%); A’s flat price interaction, CU +338 (+0.021%), has an interval that includes zero. Findings are conditional on hypothetical tariffs, reconstructed loads, and a restricted feedback rule.