BibTex Citation Data :
@article{GT4707, author = {Tejo Sukmadi}, title = {SIMULASI SISTEM EKSITASI UNTUK KONDENSATOR SINKRON PADA PEMBANGKIT LISTRIK TENAGA ANGIN}, journal = {Gema Teknologi}, volume = {16}, number = {4}, year = {2012}, keywords = {}, abstract = { Tejo Sukmadi, in paper a model of wind energy power generation excitation system will be simulated. The focuse was on the modelling and parameters optimization of the DC1A type excitation systems for synchronous condenser as voltage regulation on the power plant. Excitation system optimization is made by using genetic algorithms method. The parameters o ptimization should have the optimal combination and the voltage regulation of wind energy power plants model find the best vale when there is a change in the wind speed. The simulation and analysis found tha t systems with excitation system parameterized combination of genetic algorithms experiment using crossovers opportunities 0.6 and mutations opportunities 0.032, which Ka = 297.2350, Ke = 0.6162, Kf = 0.01, Ta = 0.01, Te = 0.01 and Tf = 0.6278 is the best combination of excitation parameters obtained. By generating the 115.6604 ITAE value, over shoot 1,54%, steady state 0,44 s, the smallest voltage value after wind speed change is 0.9957 pu and the largest voltage value after wind speed change is 1.0025 pu. Key w ord s : wind energy power generation, excitation system, synchronous condenser, genetic algorithms. }, issn = {2656-582X}, pages = {194--202} doi = {10.14710/gt.v16i4.4707}, url = {https://ejournal.undip.ac.id/index.php/gema_teknologi/article/view/4707} }
Refworks Citation Data :
Tejo Sukmadi, in paper a model of wind energy power generation excitation system will be simulated. The focuse was on the modelling and parameters optimization of the DC1A type excitation systems for synchronous condenser as voltage regulation on the power plant. Excitation system optimization is made by using genetic algorithms method. The parameters optimization should have the optimal combination and the voltage regulation of wind energy power plants model find the best vale when there is a change in the wind speed. The simulation and analysis found that systems with excitation system parameterized combination of genetic algorithms experiment using crossovers opportunities 0.6 and mutations opportunities 0.032, which Ka = 297.2350, Ke = 0.6162, Kf = 0.01, Ta = 0.01, Te = 0.01 and Tf = 0.6278 is the best combination of excitation parameters obtained. By generating the 115.6604 ITAE value, over shoot 1,54%, steady state 0,44 s, the smallest voltage value after wind speed change is 0.9957 pu and the largest voltage value after wind speed change is 1.0025 pu.
Keywords : wind energy power generation, excitation system, synchronous condenser, genetic algorithms.
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