Enhancement of Hybrid Wind Farm performance using tuned SSSC based on Multi-Objective Genetic Algorithm
In: 2016 Eighteenth International Middle East Power Systems Conference (MEPCON), 2016-12-01
Online
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Zugriff:
The Static Synchronous Series Compensator (SSSC) consists two proportional integral (PI) controllers, AC voltage regulator and DC voltage regulator. The gains values of these PI controllers play an important role in performance of SSSC. The optimization technique is used to obtain the optimal values of these gains under single objectives or several objectives. Most of control problems consist of several objectives; theses objective have to be achieved together as much as possible. The multi-objective optimization technique is used to determine the control parameters that can achieve these multi-objectives at the same time in satisfactory way. This paper uses multi-objective genetic algorithm (MOGA) to tune the PI of SSSC in order to enhance the performance of Hybrid Wind farm (HWF). HWF is based on equality numbers of SCIG and DFIG wind turbines. The performance of HWF with and without tuned SSSC is studied and compared with the performance of HWF with regular SSSC during three phase fault. All simulation results are carried out using MATLAB Simulink program. Simulation results show the ability of tuned SSSC to enhance the performance of HWF.
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Enhancement of Hybrid Wind Farm performance using tuned SSSC based on Multi-Objective Genetic Algorithm
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Autor/in / Beteiligte Person: | Kamel, Salah ; Rashad, Ahmed |
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Zeitschrift: | 2016 Eighteenth International Middle East Power Systems Conference (MEPCON), 2016-12-01 |
Veröffentlichung: | IEEE, 2016 |
Medientyp: | unknown |
DOI: | 10.1109/mepcon.2016.7836983 |
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