基于混沌粒子群的双馈风电机组LVRT实测建模及暂态参数辨识

高准确度仿真模型是进行大规模风电并网暂态稳定分析的基础,然而双馈风电机组(DFIG)控制策略与参数属于技术秘密难以获取,模型仿真准确性难以保证.针对DFIG故障暂态精确建模难题,提出了基于实测数据的DFIG建模及参数辨识方法.首先,基于电力系统综合稳定程序(PSASP)中DFIG模型及控制结构,建立低电压穿越(LVRT)控制数学模型并分析故障暂态过程,明确LVRT暂态控制核心参数.其次,基于DFIG的LVRT部分现场实测工况数据,利用混沌粒子群算法实现了DFIG故障暂态控制参数辨识.最后,基于剩余实测工况数据进行辨识参数准确性分析与校验,仿真验证了所提参数辨识方法的有效性及准确性.所提方法辨识...

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Published in	中国电力 Vol. 57; no. 8; pp. 75 - 84
Main Authors	李丹, 秦世耀, 李少林, 贺敬
Format	Magazine Article
Language	Chinese
Published	可再生能源并网全国重点实验室(中国电力科学研究院有限公司),北京 100192 28.08.2024
Subjects	混沌粒子群 double-fed induction generator chaotic particle swarm 双馈风电机组实测数据 low voltage ride through measured data 低压穿越参数辨识 parameter identification
Online Access	Get full text
ISSN	1004-9649
DOI	10.11930/j.issn.1004-9649.202310040

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Abstract	高准确度仿真模型是进行大规模风电并网暂态稳定分析的基础,然而双馈风电机组(DFIG)控制策略与参数属于技术秘密难以获取,模型仿真准确性难以保证.针对DFIG故障暂态精确建模难题,提出了基于实测数据的DFIG建模及参数辨识方法.首先,基于电力系统综合稳定程序(PSASP)中DFIG模型及控制结构,建立低电压穿越(LVRT)控制数学模型并分析故障暂态过程,明确LVRT暂态控制核心参数.其次,基于DFIG的LVRT部分现场实测工况数据,利用混沌粒子群算法实现了DFIG故障暂态控制参数辨识.最后,基于剩余实测工况数据进行辨识参数准确性分析与校验,仿真验证了所提参数辨识方法的有效性及准确性.所提方法辨识结果泛化能力强、准确度高,具有较高的工程应用价值.
AbstractList	高准确度仿真模型是进行大规模风电并网暂态稳定分析的基础,然而双馈风电机组(DFIG)控制策略与参数属于技术秘密难以获取,模型仿真准确性难以保证.针对DFIG故障暂态精确建模难题,提出了基于实测数据的DFIG建模及参数辨识方法.首先,基于电力系统综合稳定程序(PSASP)中DFIG模型及控制结构,建立低电压穿越(LVRT)控制数学模型并分析故障暂态过程,明确LVRT暂态控制核心参数.其次,基于DFIG的LVRT部分现场实测工况数据,利用混沌粒子群算法实现了DFIG故障暂态控制参数辨识.最后,基于剩余实测工况数据进行辨识参数准确性分析与校验,仿真验证了所提参数辨识方法的有效性及准确性.所提方法辨识结果泛化能力强、准确度高,具有较高的工程应用价值.
Abstract_FL	The high-accuracy simulation model is the basis for transient stability analysis of large-scale wind power integration.However,the control strategies and parameters of doubly-fed wind turbines are technical secrets that are difficult to obtain,and the accuracy of model simulation is difficult to guarantee.In order to address the fault transient modeling problems of doubly-fed wind turbines,a measured data-based modeling and parameter identification method of doubly-fed wind turbines is proposed.Firstly,based on the DFIG model and control structure of the Power System Integrated Stability Program(PSASP),a low voltage ride through(LVRT)control mathematical model is established to analyze the fault transient process,and the LVRT transient control core parameters are clarified.Secondly,based on part of the field measured LVRT data of doubly-fed wind turbines,the fault transient parameters are identified with the chaotic particle swarm optimization algorithm.Finally,the accuracy of the identification parameters are analyzed and verified based on the remaining measured data.The simulation results have verified the effectiveness and accuracy of the proposed parameter identification method.The proposed method has strong generalization ability and high accuracy of identification results,and is of great engineering application value.
Author	秦世耀贺敬李少林李丹
AuthorAffiliation	可再生能源并网全国重点实验室(中国电力科学研究院有限公司),北京 100192
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Author_FL	LI Dan LI Shaolin QIN Shiyao HE Jing
Author_FL_xml	– sequence: 1 fullname: LI Dan – sequence: 2 fullname: QIN Shiyao – sequence: 3 fullname: LI Shaolin – sequence: 4 fullname: HE Jing
Author_xml	– sequence: 1 fullname: 李丹 – sequence: 2 fullname: 秦世耀 – sequence: 3 fullname: 李少林 – sequence: 4 fullname: 贺敬
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