The present application relates to the technical field of prediction optimization, and discloses a photovoltaic power prediction optimization method and
system for a
photovoltaic power station, which comprises the following steps: step 1, normalizing photovoltaic probability prediction into quantile form, and determining a default probability budget and a standby trigger probability budget; step 2, comparing a confidence level prediction value with a maximum available output to obtain a baseline output; step 3, determining an upward adjustment standby capacity and a downward adjustment standby capacity, and setting a power
range constraint; step 4, determining a bid curve segmentation, a standby quota and an
energy storage plan; step 5, calculating a real-
time deviation, and determining an error cost threshold; step 6, determining
energy storage supplement charging capacity, discharging capacity and necessary limiting generation capacity, and solving a minimum total cost of rescheduling; and step 7, counting a
default rate and a standby
trigger rate, updating unified risk budget parameters, and generating a default and standby trigger probability budget. The present application realizes the efficiency and stability of
power grid dispatching, and improves the power generation
utilization rate of the
photovoltaic power station.