...
首页> 外文期刊>International Journal of Computational Intelligence and Applications >Shipboard Power System Stabilizer Optimization Using GA and QPSO Algorithm
【24h】

Shipboard Power System Stabilizer Optimization Using GA and QPSO Algorithm

机译:船舶电源系统稳定器优化使用GA和QPSO算法

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

In order to improve shipboard power system dynamic stability, two bio-inspired algorithms, the genetic algorithm (GA) and quantum-behaved particle swarm optimization (QPSO), method are proposed for the shipboard power system stabilizer (PSS) optimization. The proposed PSS optimization method is inspired by a hybrid-coordinated stabilizer for diesel engine generator and the bio-inspired algorithm. The simulations are conducted under load change disturbance and short-circuit fault case for the marine generator with/without the diesel engine speed governor. Simulation results show that the quantum particle swarm optimize strategy could improve the dynamic performance of the marine generator better than the GA method. The dynamic performance for shipboard power system always indicates the effectiveness, feasibility and robustness of the proposed approach.
机译:为了提高船舶电力系统动态稳定性,提出了两种生物启发算法,遗传算法(GA)和量子表现粒子群优化(QPSO),用于船舶电力系统稳定器(PSS)优化。 所提出的PSS优化方法是由柴油发动机发生器和生物启发算法的混合协调稳定器的启发。 使用/不带柴油机调速器的船用发电机的负载变化干扰和短路故障情况下进行模拟。 仿真结果表明,量子粒子群优化策略可以提高船舶发电机的动态性能,比GA方法更好。 船上电力系统的动态性能始终表明所提出的方法的有效性,可行性和鲁棒性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号