Demand-Charge Memory and Forecast Quality: A Controlled One-Year Study of PV–Battery Dispatch at a Container Terminal

Port electrification under the green-port transition sharpens peaks and raises demand charges, motivating photovoltaic–battery energy storage (PV–BESS). Yet PV–BESS value depends on forecast error, operating policy and tariff peak memory, a ratchet carrying one peak-setting error across months; evaluations under perfect foresight or monthly-only billing leave their interaction unquantified. We quantify it in a controlled one-year Korean container-terminal simulation (synthetic load, public PV data, rolling dispatch). Three peak-memory structures and forecast-error levels are tested for four published policies; re-billing, an execution-layer ablation and 20 PV-forecast realizations separate mechanical from behavioral effects. At calibrated error, the ratchet raised mean point-forecast regret by 6–8 million KRW/yr (bootstrap interval excluding zero for one policy; no sign test significant), reduced scenario-policy regret by 3 million (nominally significant), multiplied annual-tariff dispersion two- to ninefold and made its sign event-dependent. In the reference realization, threshold-induced early depletion under monthly-only billing interacted with 12-month re-billing, raising point-forecast regret to 2.4–3.3 times the monthly-only value; with that response off, four of five policies matched the re-billing benchmark. Scenario information was worth 12.5 million KRW/yr under the ratchet, 2.7 under monthly-only billing. PV–BESS value thus depends jointly on forecast accuracy, tariff peak memory, policy information use and event-level dispatch.