Open AccessParameter Optimization of Doubly-Fed Induction Generator Based on Intelligent Optimization Algorithm
Author(s) -
Xiangwen Zhang,
Hua Ge,
Yiran Zhang,
Linjun Shi
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/677/5/052018
Subject(s) - particle swarm optimization , overshoot (microwave communication) , control theory (sociology) , multi swarm optimization , inertia , induction generator , controller (irrigation) , power (physics) , pid controller , generator (circuit theory) , wind power , computer science , optimization algorithm , algorithm , engineering , control engineering , mathematical optimization , mathematics , control (management) , temperature control , physics , artificial intelligence , biology , telecommunications , classical mechanics , quantum mechanics , agronomy , electrical engineering
The doubly-fed wind power generator control system consists of multiple PI controllers, each of which directly affects the dynamic characteristics of the wind power system. In this paper, a particle swarm optimization algorithm with improved inertia weight is used to simulate and analyze the control system optimized by algorithm. It is found that the improved characteristic curve has the advantages of small overshoot, fast adjustment speed and short adjustment time. The effectiveness and superiority of the particle swarm optimization algorithm for PI controller parameters optimization.