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作 者:史文博[1] 顾伟[1] 柳伟[1] 蒋平[1] 曹志煌 潘静 盛万兴 孙丽敬 SHI Wenbo;GU Wei;LIU Wei;JIANG Ping;CAO Zhihuang;PAN Jing;SHENG Wanxing;SUN Lijing(School of Electrical Engineering,Southeast University,Nanjing 210096,Jiangsu Province,China;State Grid Anhui Electric Power Corporation Research Institute,Hefei 230601,Anhui Province,China;China Electric Power Research Institute,Haidian District,Beijing 100192,China)
机构地区:[1]东南大学电气工程学院,江苏省南京市210096 [2]国网安徽省电力公司电力科学研究院,安徽省合肥市230601 [3]中国电力科学研究院有限公司,北京市海淀区100192
出 处:《中国电机工程学报》2019年第22期6592-6599,共8页Proceedings of the CSEE
基 金:国家重点研发计划项目(2016YFB0900404)~~
摘 要:针对动态全过程仿真中双馈风电模型多时间尺度特性带来的刚性问题,提出一套基于局部模型自适应切换和变步长积分算法结合的双馈风电模型及仿真方法。利用双馈风电各子模块在时间尺度上的可分性,对慢动态模块建立动态(dynamic state,DS)模型;对快动态模块建立动态模型和准稳态(quasi-steady state,QSS)模型,并在仿真中进行2种模型的局部切换。提出一种基于系统状态驱动的模型自适应切换策略,基于风电系统中存在的多反馈环节,以偏差量做为系统稳定判据,通过阈值比较实现切换时刻判别。在模型切换基础上,进一步应用TR-BDF2积分算法实现变步长仿真。仿真对比表明,提出的风电模型与不进行模型切换的传统模型相比,具有相同的精度和更快的仿真速度。In allusion to the stiff problem caused by the multi-time scale characteristics of doubly-fed wind power generation(DFIG)model for full dynamic simulation,this paper proposed a set of DFIG model and simulation method based on the combination of local model adaptive switching and variable step size algorithm.The DFIG wind turbine system was divided into different modules according to time scale.Dynamic state(DS)models of modules with slow response,dynamic and quasi-steady state(QSS)models of modules with fast response were established.A local model adaptive switching strategy according to system state was proposed.The system stability criterion could be calculated based on the deviation between the given value and the actual value in each sub-module.To obtain the switching time of the proposed model,the system stability criterion was compared with the preset precision threshold.Based on model switching,the TR-BDF2 variable step size algorithm was further applied to the full dynamic simulation.Finally,the effectiveness of the proposed method was verified by simulation,which indicated that compared with conventional dynamic model,the proposed model had faster simulation speed when the accuracy was the same.
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