z-logo
open-access-imgOpen Access
Active and Reactive Power Control of Dcig Wind Power System using Evolutionary Algorithm Based Fraction Order Controllers.
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.f1146.0486s419
Subject(s) - control theory (sociology) , wind power , convergence (economics) , stability (learning theory) , lift (data mining) , generator (circuit theory) , computer science , algorithm , engineering , power (physics) , control (management) , artificial intelligence , economics , electrical engineering , physics , quantum mechanics , machine learning , data mining , economic growth
This paper commences an exalted control scenario for Wind Energy Systems(WES) adopting Doubly Cater Induction Generator (DCIG) . A vigorous Ant Lion Optimizer(ALO) technique is assented with a Fractional Order PI assessor to optimize the powers and to lift the aggressive performance of WES[2][3]. The enforcement and adequacy of ALOFOPI assessor shows amusing countenance in terms of blather devaluation confined concurrence time and hefty against specifications[1]. The proposed ALOFOPI algorithm shows a great convergence and enhanced stability

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom