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- W4387376722 abstract "The implementation of wind power grid parity has created an urgent technological demand for optimized design in wind farms. The optimization of the topology structure of wind farm collector lines has become a hot topic in both domestic and international research and project development. Traditional clustering methods for wind turbine units often use Euclidean distance, which only provides block-like results with spatial proximity. This approach has limitations in obtaining more accurate results. In this paper, we propose an improved fuzzy C-means clustering algorithm based on azimuth angle, Euclidean distance, and a correction factor that considers the distance between the turbine position and the cluster center. We also introduce a capacity factor to rationalize the partitioning of collector line circuits. Furthermore, we integrate the dynamic Prim algorithm into the optimization process. Through case studies, we validate the effectiveness of our proposed method in reducing the construction cost of collector lines, demonstrating its practical engineering application value." @default.
- W4387376722 created "2023-10-06" @default.
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- W4387376722 date "2023-10-05" @default.
- W4387376722 modified "2023-10-16" @default.
- W4387376722 title "Topological Structure Optimization of Wind Farm Collector Lines Considering Wind Turbine Circuit Division" @default.
- W4387376722 doi "https://doi.org/10.3233/atde230293" @default.
- W4387376722 hasPublicationYear "2023" @default.
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