Open AccessHybrid PSO-GSA algorithm-based optimal control strategy for performance enhancement of a grid-connected wind generator
Author(s) -
Mohamed A. Amin,
Mahmoud A. Soliman,
Hany M. Hasanien,
Almoataz Y. Abdelaziz
Publication year - 2021
Publication title -
international journal of applied power engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2624
pISSN - 2252-8792
DOI - 10.11591/ijape.v10.i2.pp151-158
Subject(s) - control theory (sociology) , permanent magnet synchronous generator , particle swarm optimization , grid , controller (irrigation) , variable speed wind turbine , wind power , computer science , engineering , algorithm , magnet , mathematics , control (management) , electrical engineering , agronomy , geometry , artificial intelligence , biology
Due to the great level of wind energy penetration in the existing network, huge efforts have been directed to enhance the grid-connected wind generator performance. This paper shows an application of a hybrid algorithm of the particle swarm optimization and the gravitational search algorithm (PSO-GSA) to enhance the transient stability of the grid-tied wind energy conversion system. The variable-speed wind turbine (VSWT) direct-drive permanent-magnet synchronous generator is connected to the network through a full-scale converter. The generator- and grid-side converters are controlled by utilizing an optimum proportional-integral (PI) controller. The criterion of the integral squared error is utilized as an objective function. The PSO-GSA based-PI controller efficacy is validated by comparing its results with that are obtained by utilizing the genetic algorithm (GA)-based-PI controller. The performance of the suggested control scheme is checked during various fault conditions. The control scheme quality is legalized by the simulation results that are obtained using MATLAB/Simulink program