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基于PSO算法的定速风电机组三质块传动系统模型参数辨识

Parameter identification of three-mass drive-train system for fixed-speed wind turbine generator based on PSO algorithm

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【作者】 王慧潘学萍鞠平

【Author】 WANG Hui;PAN Xueping;JU Ping;College of Energy and Electrical Engineering,Hohai University;

【机构】 河海大学能源与电气学院

【摘要】 为获得传动系统模型的准确参数,提出阵风激励下三质块传动系统模型的参数辨识方法。根据定速风电机组机械动态与电气动态解耦的特性,提出在辨识传动系统模型参数时可忽略电气动态,据此获得定速风电机组的简化模型。采用轨迹灵敏度方法,分析了传动系统各参数的可辨识性及辨识的难易程度。基于粒子群优化算法(PSO)对传动系统模型进行了参数辨识。辨识结果与轨迹灵敏度分析结论一致,验证了提出的参数辨识方法的可行性。

【Abstract】 In order to obtain accurate parameters for a drive-train model,a method for parameter identification of a three-mass drive-train system with gusty wind excitation is proposed. According to the decoupling of the mechanical dynamics and electrical dynamics of fixed-speed wind turbine generators,the electrical dynamics can be neglected when identifying parameters of a drive-train model. Based on this,a simplified model for fixed-speed wind turbine generators was obtained. The identifiability of the parameters of the drive-train system and the difficulties in parameter identification were analyzed with the trajectory sensitivity analysis method. Finally,the parameters of the drive-train model were identified based on the particle swarm optimization(PSO) algorithm. The identified results are consistent with the trajectory sensitivity analysis results,verifying the feasibility of the proposed parameter identification method.

【基金】 国家自然科学基金重大项目(51190102);国家自然科学基金(51207045)
  • 【文献出处】 河海大学学报(自然科学版) ,Journal of Hohai University(Natural Sciences) , 编辑部邮箱 ,2016年01期
  • 【分类号】TM315
  • 【被引频次】12
  • 【下载频次】213
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