自动化博览
自動化博覽
자동화박람
AUTOMAITON PANORAMA
2013年
z2期
116-121
,共6页
戴长春%王正风%张兆阳%毕天姝
戴長春%王正風%張兆暘%畢天姝
대장춘%왕정풍%장조양%필천주
输电线路%参数辨识%抗差最小二乘%IGG抗差准则%PMU数据
輸電線路%參數辨識%抗差最小二乘%IGG抗差準則%PMU數據
수전선로%삼수변식%항차최소이승%IGG항차준칙%PMU수거
Transmission Line%Parameter Identification%Robust Least Square%IGG Robust Criterion%PMU Data
针对实测数据中会存在粗差而传统最小二乘不具备抗差能力,本文将IGG抗差方法应用到输电线路参数辨识中,提出了基于IGG准则的抗差最小二乘的输电线路参数辨识方法。具体的,本文在介绍基于双端PMU数据的线路线性数学模型和相应的最小二乘辨识的基础上,通过对目标函数的改造,引入基于IGG法的抗差准则,即对有效的观测信息保权,对可利用观测信息降权,对有害观测信息拒绝,从而使得改造后的最小二乘方法具备了较强的抗差能力。基于PSCAD仿真数据的测试验证了本文方法的有效性、抗噪能力及抗差能力;基于实测PMU数据的运行参数辨识结果表明了本文方法的实用性。
針對實測數據中會存在粗差而傳統最小二乘不具備抗差能力,本文將IGG抗差方法應用到輸電線路參數辨識中,提齣瞭基于IGG準則的抗差最小二乘的輸電線路參數辨識方法。具體的,本文在介紹基于雙耑PMU數據的線路線性數學模型和相應的最小二乘辨識的基礎上,通過對目標函數的改造,引入基于IGG法的抗差準則,即對有效的觀測信息保權,對可利用觀測信息降權,對有害觀測信息拒絕,從而使得改造後的最小二乘方法具備瞭較彊的抗差能力。基于PSCAD倣真數據的測試驗證瞭本文方法的有效性、抗譟能力及抗差能力;基于實測PMU數據的運行參數辨識結果錶明瞭本文方法的實用性。
침대실측수거중회존재조차이전통최소이승불구비항차능력,본문장IGG항차방법응용도수전선로삼수변식중,제출료기우IGG준칙적항차최소이승적수전선로삼수변식방법。구체적,본문재개소기우쌍단PMU수거적선로선성수학모형화상응적최소이승변식적기출상,통과대목표함수적개조,인입기우IGG법적항차준칙,즉대유효적관측신식보권,대가이용관측신식강권,대유해관측신식거절,종이사득개조후적최소이승방법구비료교강적항차능력。기우PSCAD방진수거적측시험증료본문방법적유효성、항조능력급항차능력;기우실측PMU수거적운행삼수변식결과표명료본문방법적실용성。
In the parameter identification for transmission line, there often exists the gross error in the measured data and lacking of robustness with the traditional least square. This paper applies the IGG robust estimation to the transmission line parameter, i.e., proposes a robust least square estimation to transmission line parameter identification based on IGG robust criterion. In detail, it firstly presents the linear model for transmission line based on the PMU data of both ends and introduces the traditional least square estimation method. And then, after the introduction of the IGG robust criterion, i.e., retaining the weight of the effective observation, reducing the weight of the available observation, but refusing the harmful observation, it proposes the robust least square estimation by modifying the objective function of the traditional least square estimation for parameter identification. The simulation results based on PSCAD demonstrate the effectiveness, noise immunity ability and robust ability of the proposed method. Furthermore, the results based on field PMU data show the effectiveness of the proposed method in application.