首页> 外文会议>International Conference on Recent Advances in Engineering Computational Sciences >Load Frequency Control of Multi Area System Using Hybrid Particle Swarm Optimization
【24h】

Load Frequency Control of Multi Area System Using Hybrid Particle Swarm Optimization

机译:使用混合粒子群优化的多区域系统负载频率控制

获取原文

摘要

The essential point of the Automatic Generation Control (AGC) is to keep up the system frequency and tie-line power interchange within the limits by controlling the electrical power generated, whenever the fluctuations in the power system occur due to change in load demand. This paper proposes few online smart control techniques to understand the Load Frequency Control (LFC) of multi area system. The main reason to develop smart control techniques to improve the transient response of the power system by reducing the overshoot, undershoot and settling time of the multi area system. The proposed method in this paper is combination of Bacterial Foraging Algorithm (BFA) and Particle Swarm Optimization (PSO) we call it as Hybrid-PSO (H-PSO). The modelling of multi area power system and tuning of the controller are carried out in MATLAB/Simulink environment. After the analysis of results it is observed that H-PSO is better as compare to BFA and PSO.
机译:自动生成控制(AGC)的基本点是通过控制由于负载需求的变化而发生电力系统的波动时,在限制内保持系统频率和扎线功率交换。本文提出了一些在线智能控制技术来了解多区域系统的负载频率控制(LFC)。开发智能控制技术的主要原因,通过减少多区域系统的过冲,下冲和稳定时间来改善电力系统的瞬态响应。本文所提出的方法是细菌觅食算法(BFA)和粒子群优化(PSO)的组合,我们称之为Hybrid-PSO(H-PSO)。在Matlab / Simulink环境中执行多区域电力系统和控制器调谐的建模。在分析结果之后,观察到H-PSO更好地与BFA和PSO进行比较。

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