Open AccessMulti‐machine equivalent model parameter identification method for double‐fed induction generator (DFIG)‐based wind power plant based on measurement data
Author(s) -
Luo Kui,
Shi Wenhui,
Qu Jixian
Publication year - 2017
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2017.0591
Subject(s) - wind power , control theory (sociology) , equivalent circuit , induction generator , computer science , generator (circuit theory) , turbine , doubly fed electric machine , estimation theory , identification (biology) , power (physics) , ac power , engineering , algorithm , physics , voltage , artificial intelligence , mechanical engineering , botany , control (management) , quantum mechanics , electrical engineering , biology
Dynamic equivalent modelling for wind power plant (WPP) has become an important tool to analyse the grid integration characteristics of large‐scale WPPs. Owing to the large differences of operational performance between wind turbines, multi‐machine equivalent model is more accurate to represent the WPP. In order to determine the generator parameters of multi‐machine equivalent model, this study proposed a multi‐machine equivalent model parameter identification method for DFIG‐based WPP only with data measured at the point of common coupling. On the basis of established clustering model, it is explained how the measurement data are properly processed for use as the input of parameter identification considering the collecting circuit and the estimated instantaneous power of equivalent wind turbine. The developed parameter determination method is tested against a large‐scale plant model, and simulation results confirm the effectiveness of the method.