Open AccessA Recursive Least-Squares Approach with Memorizing Factor for Deriving Dynamic Equivalents of Power Systems
Author(s) -
Ali Karami
Publication year - 2021
Publication title -
advances in technology innovation
Language(s) - English
Resource type - Journals
eISSN - 2518-2994
pISSN - 2415-0436
DOI - 10.46604/aiti.2021.7853
Subject(s) - control theory (sociology) , electric power system , matlab , transient (computer programming) , fault (geology) , computer science , stability (learning theory) , identification (biology) , software , least squares function approximation , system identification , power (physics) , control engineering , algorithm , engineering , mathematics , data modeling , artificial intelligence , statistics , control (management) , machine learning , database , estimator , biology , operating system , quantum mechanics , programming language , physics , botany , seismology , geology
In this research, a two-stage identification-based approach is proposed to obtain a two-machine equivalent (TME) system of an interconnected power system for transient stability studies. To estimate the parameters of the equivalent system, a three-phase fault is applied near and/or at the bus of a local machine in the original multimachine system. The electrical parameters of the equivalent system are calculated in the first stage by equating the active and reactive powers of the local machine in both the original and the predefined equivalent systems. The mechanical parameters are estimated in the second stage by using a recursive least-squares estimation (RLSE) technique with a factor called “memorizing factor”. The approach is demonstrated on New England 10-machine 39-bus system, and its accuracy and efficiency are verified by computer simulation in MATLAB software. The results obtained from the TME system agree well with those obtained from the original multimachine system.