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Development of a genetic algorithm for maximizing wind power integration rate into the electric grid.

Authors :
Ammous, Sahar
Halima, Nahla Ben
Oualha, Abdelmajid
Jebali, Mariam
Abdallah, Hsan Hadj
Source :
Journal of Renewable & Sustainable Energy. Mar2019, Vol. 11 Issue 2, pN.PAG-N.PAG. 13p. 5 Diagrams, 3 Charts, 8 Graphs.
Publication Year :
2019

Abstract

In this paper, a new method was proposed with the objective of maximizing the rate of wind power integration into the electric grid. This method was based on the optimization of the parameters of the turbine governors (TGs) by means of a genetic algorithm. The tuning of TGs' parameters was formulated relying on an objective function aiming at reaching the maximum wind power penetration rate. The dynamic grid modeling consisted of synchronous machines, regulators, and wind turbines. The IEEE 14-bus modified test system was adopted to test the grid using the Power System Analysis Toolbox. The simulation results revealed that, with the optimized TGs' parameters, the rate of wind power integration improved considerably. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19417012
Volume :
11
Issue :
2
Database :
Academic Search Index
Journal :
Journal of Renewable & Sustainable Energy
Publication Type :
Academic Journal
Accession number :
136185204
Full Text :
https://doi.org/10.1063/1.5068736