Wind power prediction method and system
A technology for wind power prediction and wind power, applied in system integration technology, information technology support systems, instruments, etc., can solve problems such as low calculation efficiency and low accuracy of wind power prediction, and achieve both rapidity and reduction in the number of effective scenarios Effect
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[0038] The historical wind power data used in this example are the measured values of wind power for a total of 364 days from June 1, 2015 to May 29, 2016 of the wind farms under the jurisdiction of German power grid operator TransnetBW, and the number of clusters K is set to 5 ,use figure 2 The shown K-means clustering method clusters the original scenes in each time period, and finally generates the final cluster centers in each time period, and the statistics are shown in Table 1 below. The final cluster center generated in each period is the representative scene of the period. For example, the five representative scenes in period 1 are 23MW, 10MW, 179MW, 29MW and 79MW respectively.
[0039] Table 1 Final cluster centers in each time period
[0040]
[0041] Table 2. Wind power range for the future forecast period
[0042]
[0043] Assuming that the upper and lower limits of the wind power forecast interval under the 90% confidence level in the future...
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