Method for correcting wind power data based on nonparametric kernel density estimation
A non-parametric kernel density, wind power technology, applied in electrical digital data processing, special data processing applications, calculations, etc., can solve the requirements of difficult to achieve unity, inability to deal with inconsistent wind power data, and higher accuracy. Handling methods and other issues to achieve the effect of good inclusiveness, improved accuracy, and improved effectiveness
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[0037] It should be noted that, in the case of no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other.
[0038] The present invention will be described in detail below in conjunction with embodiments and accompanying drawings.
[0039] Such as figure 1 Shown is a flow chart of the present invention.
[0040] according to figure 1 As shown in the process, first, read the measured wind speed and power data, arrange the measured wind speeds in ascending order, take the sorted measured wind speed as the abscissa, and the corresponding measured wind power as the ordinate, forming historical measured wind speed - measured wind power The statistical data group divides the measured wind speed into equal intervals with a certain resolution, and divides the measured wind power data into multiple sub-intervals;
[0041] Let the maximum wind power be P max , the minimum value is P min , the power interval is ΔP, then ...
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