Wind resource assessment method based on optimization time window

Abstract

The invention discloses a wind resource assessment method based on an optimization time window. The method includes the following steps of 1, extracting data, wherein local wind speed data information is extracted, original data is verified and corrected, and a series of continuous wind speed data at equal time intervals is obtained and serves as a sample time series of a model; 2, calculating the wind speed significance period, wherein the significance period of the wind speed under different time scales is calculated with the wavelet transformation technology and serves as a new time window for wind resource assessment; 3, determining the optimal time window, wherein fitting of the Weibull function is carried out under a traditional time window and the new time window, obtained through calculation in the step 2, with the wind speed periodicity considered, the goodness of fit of the two windows is compared, the difference value of the fit average wind speed and the actual average wind speed is obtained, and thus the better time window is selected; 4, calculating wind resource characteristic indexes, wherein the indexes of local wind resource characteristics are calculated under the time window selected in the step 3 and include the average wind speed, the wind speed distribution parameter, the wind shear index and the wind power density, and a wind profile, a wind direction rose and a wind energy rose are drawn.

Description

technical field [0001] The invention belongs to the technical field of wind power generation, and in particular relates to a wind resource evaluation method based on an optimized time window. Background technique [0002] Wind resource assessment refers to the evaluation of potential wind energy resources and power generation in the life cycle of alternative wind farms, so as to conduct macro site selection and unit selection of wind farms. Accurate wind resource assessment is the premise of wind farm planning and construction, and the accuracy of the assessment is directly related to the economic benefits of wind farms in the future. [0003] The output power of wind turbines is directly proportional to the cube of wind speed, so the wind speed is the core of all evaluation indicators of wind resources. Since wind speed has no obvious periodicity, traditional wind resource assessment methods generally use months, quarters, and years as time windows to calculate various ind...

AI Technical Summary

Problems solved by technology

However, in fact, there are several periodic components contained in the wind speed sequence, and the period length of each component is different from the traditional wind resource assessment time window (month, quarter, year), which has been used in the previous wind resource assessment process. has been ignored

Images