WSEAS Transactions on Systems
Print ISSN: 1109-2777, E-ISSN: 2224-2678
Volume 13, 2014
Special Issue: Multi-models for Complex Technological Systems Editors: C. Ciufudean, F. Neri Aggregation Modeling of Large Wind Farms using an Improved K-Means Algorithm
Authors: , , ,
Abstract: Large wind farms require modeling and simulation in their planning and construction process to provide a basis for grid planning. As a large wind farm is comprised of hundreds or even thousands of wind generators, the detailed-model building of wind farms is difficult, which are associated with slow simulation speeds and heavy workloads. In this paper, an improved K-means algorithm-based aggregation modeling method is proposed for large wind farms. A model is built for a typical 300 MW wind farm of the northern Jiangsu Province in China and its simulations are performed. The results based on a comparison between a single-fan aggregation model and a multi-fan aggregation model are obtained. The aggregation method proposed in this paper proves to be accurate and fast, which is able to meet the requirements for output simulation.
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Keywords: Wind farm, power grid, wind generator, aggregation modeling, output simulation, K-means clustering algorithm
Pages: 492-502
WSEAS Transactions on Systems, ISSN / E-ISSN: 1109-2777 / 2224-2678, Volume 13, 2014, Art. #49