Dynamic Modeling of Wind Turbine Generation System based on Grey-box Identification with Genetic Algorithm

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• 英文论文题名：Dynamic Modeling of Wind Turbine Generation System based on Grey-box Identification with Genetic Algorithm
• 论文作者：Liu Jizhen ; Guo Junlin ; Hu Yang ; Wang Juan ; Liu Hong
• 英文论文作者：Liu Jizhen ; Guo Junlin ; Hu Yang ; Wang Juan ; Liu Hong ; State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources ; North China Electric Power University ; North China Electric Power University
• 年：2017
• 作者机构：State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources,North China Electric Power University;North China Electric Power University;
• 英文论文关键词：wind power generation ; grey-box identification ; parameter identification ; genetic algorithm
• 会议召开时间：2017-07-26
• 会议录名称：第36届中国控制会议论文集（B）
• 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
• 语种：英文
• 分类号：TM315;TP18
• 学会代码：KZLL
• 会议名称：第36届中国控制会议
• 会议地点：中国辽宁大连
• 主办单位：中国自动化学会控制理论专业委员会
• 学会名称：中国自动化学会控制理论专业委员会
• 页数：5
• 文件大小：414k
• 原文格式：D
• 会议级别：全国

摘要

The data-based parameter identification is an efficient way for the modeling of Wind Turbine Generation System(WTGS) which only reveals the external characteristic.However,the inner characteristic is unknown.In practice,the parameters of the mechanism model are changing with time.Thus,in the paper,the grey-box modeling approach which utilizes the operation data and operating mechanism together are proposed to realize the online parameter identification of WTGS under closed-loop.Considering the essential difference between aerodynamic system and the other systems,the driven-train system and the electrical system are identified together which also simplify the identification process and the switching mechanism is proposed for the parameters update of mechanism model which is much efficient and applicable in practice.Besides,the identification of driven-train system and electrical system in combination could ensure the global approximation ability to the dynamics of WTGS while the local approximation ability to the subsystems could also be validated when the identification parameters are obtained.In the paper,the combined state space model including the driven-train model and Doubly-Fed Induction Generator(DFIG) model is deduced.The GH Bladed Software would be used to generated the operation data for identification and the genetic algorithm is adopted to identify the model parameters.As a result,the nonlinear state space model could be obtained and its approximation ability to the dynamic characteristic of WTGS is validated through simulation.Then,the practical characteristic of wind turbine could be approximated more accurately.Note that the paper provides meaningful research basis for the control design and model-based fault diagnosis of large-scale WTGS.
The data-based parameter identification is an efficient way for the modeling of Wind Turbine Generation System(WTGS) which only reveals the external characteristic.However,the inner characteristic is unknown.In practice,the parameters of the mechanism model are changing with time.Thus,in the paper,the grey-box modeling approach which utilizes the operation data and operating mechanism together are proposed to realize the online parameter identification of WTGS under closed-loop.Considering the essential difference between aerodynamic system and the other systems,the driven-train system and the electrical system are identified together which also simplify the identification process and the switching mechanism is proposed for the parameters update of mechanism model which is much efficient and applicable in practice.Besides,the identification of driven-train system and electrical system in combination could ensure the global approximation ability to the dynamics of WTGS while the local approximation ability to the subsystems could also be validated when the identification parameters are obtained.In the paper,the combined state space model including the driven-train model and Doubly-Fed Induction Generator(DFIG) model is deduced.The GH Bladed Software would be used to generated the operation data for identification and the genetic algorithm is adopted to identify the model parameters.As a result,the nonlinear state space model could be obtained and its approximation ability to the dynamic characteristic of WTGS is validated through simulation.Then,the practical characteristic of wind turbine could be approximated more accurately.Note that the paper provides meaningful research basis for the control design and model-based fault diagnosis of large-scale WTGS.

引文

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