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Schedule Strategy Research Of Large Wind Farm

Posted on:2016-06-19Degree:MasterType:Thesis
Country:ChinaCandidate:Y X LiFull Text:PDF
GTID:2272330470972136Subject:Control theory and control engineering
Abstract/Summary:PDF Full Text Request
With the deterioration of ecological environment in today’s society, clean energy generation occupancy is increasing. Wind itself as a clean energy and resources is extremely rich. Wind energy based on the technical aspects of wind power, wind power technology matures; On the application level, wind power is more convenient compared to other clean energy generation, more extensive, more environmentally friendly, so wind power in the grid is increasing year by year. With the increasing penetration of wind power, Wind farm active power control and scheduling has become an important means to ensure the safe operation of the power grid.Due to large-scale wind farms/groups span the region, the location of wind farm turbine dispersion leads through fan speed and power output of each wind turbine there is a big difference. Cluster the wind turbines base on average of wind speed and fluctuation of active power output by using UPGMA and method of diffusion distance in this paper. Clustering on the basis of the results obtained with the reference scheduling policy.According to the clustering results, First, propose wind farm distinction threshold level scheduling strategy, Based on the threshold value, propose weighted distribution load scheduling strategy and complex scheduling policy based scheduling policy relative running start and stop loss with relative loss of a combination of both. At last, according to historical operating data of a wind farm was simulated for scheduling strategy, verify that the new strategy not only to meet the power requirements for wind farms, but also reducing the overall power output of wind farms and wind farm volatility of each fan is running and start and stop loss.
Keywords/Search Tags:wind generation, wind power dispatching, Cluster analysis, Turbine output power characteristics, Complex scheduling policies
PDF Full Text Request
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