Research On Clustering Effect Of Wind Generations Based On The Measured Data

The production and living of modern society are inseparable from the power of support,with the development of electricity,the drawbacks of traditional energy increasingly obvious,mainly in the energy shortage and environmental pollution.Therefore,the search for rich reserves of clean energy is the basis for future power development,which wind energy with its characteristics of the rich reserves and easily acquisition is becoming one of the most rapid development of the clean energy in the world.With the development of China's wind power technology,more and more wind farms are running,and the wind farm is gradually large,with the spatially characteristic of wind power that differences in time and space distribution is fully reflected in the large-scale wind farm,expressed as that the total output power of the wind farm group distinguishes its components,its phenomenon that volatility is weakened is the convergence effect.Wind power access grid need to overcome the point that is the volatility of wind power,it is of great value to study the convergence effect of wind farm.All the research and analysis of this paper are based on practical engineering.First,the mechanism of convergence effect is analyzed from the perspective of wind power fluctuation trend.Then,the output power of single field and field is described mathematically from the angle of fluctuation and macroscopic characteristics,through comparative analysis,determine the evolution trend of convergence effect.In addition,a hierarchical aggregation rule based on fuzzy clustering method is established,and summarizes the convergence phenomenon and its evolution rule of wind power generation at different levels.And then through the trend extrapolation method to predict the planned target annual output power eigenvalues,a prediction model of continuous power curve is constructed.Finally,an example is given to verify the evolution of the convergence effect and prove the effectiveness of the model.In this paper,three-dimensional latitude and longitude is transformed into two-dimensional relative position,which makes geographical data more suitable for mathematical modeling and engineering application.In this paper,a hierarchical aggregation rule based on fuzzy clustering method is established to converge the actual wind farm group to layer by layer,So as to establish the prediction model of the eigenvalue of the convergence effect.The data processing method and convergence research process proposed in this paper are more suitable for the use of practical engineering,and proved by examples,with theoretical value and practical significance.