Open AccessPredictive control strategy to improve stability of DFIG‐based wind generation connected to a large‐scale power system
Author(s) -
Darabian Mohsen,
Jalilvand Abolfazl
Publication year - 2017
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/etep.2300
Subject(s) - control theory (sociology) , model predictive control , matlab , controller (irrigation) , ac power , rotor (electric) , stability (learning theory) , computer science , engineering , control engineering , control (management) , voltage , mechanical engineering , electrical engineering , artificial intelligence , machine learning , agronomy , biology , operating system
Summary The present article aims to improve the small signal stability in a large‐scale network using model predictive control (MPC). The predictive strategy is based on the Laguerre function so as to reduce computational time in MPC and increase precise detection of control signals. This strategy is implemented in such a way to control the active and reactive power on rotor‐side converter (RSC) and increase RSC yield in the presence of uncertainties through application of appropriate switching to inverter. Therefore, static synchronous compensator is used in a way that the reactive power is compensated and by designing a damping controller the interarea oscillations will be reduced in New England large‐scale system. The simulation results were evaluated using MATLAB software in the field of time and frequency under different scenarios. Moreover, the proposed method was compared with conventional MPC and proportional‐integral controller while its superiority to stabilize and reduce the computational time is clearly shown.