MAXIMUM-LIKELIHOOD-ESTIMATION OF GENERATOR STABILITY-CONSTANTS USING SSFR TEST DATA

被引：26

作者：

KEYHANI, A ^{[1
]}

HAO, SG ^{[1
]}

SCHULZ, RP ^{[1
]}

机构：

[1] AMER ELECT POWER SERV CORP,DEPT SYST PLANNING,COLUMBUS,OH 43215

来源：

IEEE TRANSACTIONS ON ENERGY CONVERSION | 1991年 / 6卷 / 01期

关键词：

SYNCHRONOUS MACHINE MODELS; MAXIMUM LIKELIHOOD IDENTIFICATION; PARAMETER ESTIMATION;

D O I：

10.1109/60.73801

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This paper presents an evaluation of the performance of the Maximum Likelihood (ML) method when used to determine simulation data for generators from Standstill Frequency Response (SSFR) tests. The generator or synchronous machine data found by this process or similar processes are used in simulation models for many kinds of stability and dynamic performance calculations. The robustness of the ML method is demonstrated by analyses made with SSFR data from tests on the Rockport 722 MVA generator. It is shown that a unique set of parameters can be obtained and the noise effects can be dealt with effectively when the Maximum Likelihood estimation (ML) technique is used to estimate machine parameters.

引用

页码：140 / 154

页数：15

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