We are working with data like this for a major fast food franchise. The series represents the demand for tacos in 15 minute intervals for the last 5 years (180,000 observations) . This series can be treated by building 96 separate models (4x24) for each 15 minute interval a daily model reflecting overall trends,level shifts,holiday effects etc in daily values. By integrating the impact of daily values and their history on each of the 96 models and then reconciling, we are able to accurately predict both the demand for 15 minute intervals and the daily totals. The reason you think the acf is significant is as Rob points out due to the sample size since the standard error of the acf is equal to 1/sqrt(N).
IrishStat
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