大型风机海上风电场集电系统拓扑优化

Topology Optimization of Offshore Wind Farm Power Collection System with Large Wind Turbine

海上风电机组呈现大型化发展趋势,集电系统的电压等级随着单机额定容量的变化而发生改变,使用模糊c-均值聚类算法(FCM算法)进行海上风电场集电系统拓扑优化在选取集电系统电压等级较低时,将面临串组内风电机组个数冗余度受限、集电系统拓扑结构更加复杂等问题,导致规划效率过低或规划失败。针对66kV及35kV集电系统,将FCM算法及Prim算法从边权条件、优化路径选取等方面进行改进,对整体规划进行降维分区,通过改进算法结构、改进寻优方式等方法,把复杂的集电系统优化分解为多个分区的优化问题,使改进算法在风机容量大型化的趋势下,可适用于不同电压等级的海上风电场集电系统拓扑优化,并通过算例证明优化算法具有较好的普适性、寻优性及规划效率。

The offshore wind turbine presents the trend of large-scale development,and the voltage level of the power collection system changes with the change of single unit rated capacity.The fuzzy c-means clustering algorithm(FCM algorithm)is used to optimize the topology of the offshore wind farm collection system.When the voltage level of the collection system is low,it will face the problems of limited redundancy of the number of wind turbines in the series and a more complex topology structure of the collection system,resulting in low planning efficiency or planning failure.For 66kV and 35kV Power collection systems,we improved the FCM algorithm and prim algorithm from the aspects of edge weight conditions and optimal path selection,and reduced and partitioned the dimension of the overall planning.By improving the algorithm structure and optimization method,we decomposed the optimization of the complex power collection system into the optimization problem of multiple partitions.This makes the improved algorithm can be applied to the topology optimization of offshore wind farm power collection system with different voltage levels in the trend of large-scale fan capacity.Moreover,an example was carried out to verify that the optimization algorithm has good universality,optimization,and planning efficiency.