| 引用本文: | 王钢,梁远升,李海锋,李文辉.基于PSO算法和Butterworth低通滤波器的参数自适应故障测距时域法[J].电力自动化设备,2009,(3): |
| .Time domain fault locating with parameter self-adaptation based on PSO algorithm and Butterworth low-pass filter[J].Electric Power Automation Equipment,2009,(3): |
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| 摘要: |
| 利用故障前、后线路两端电气信息,分别建立参数自适应和故障测距时域观测方程;利用粒子群优化(PSO)算法的全局寻优能力,构造相应的PSO求解模型以求取最优解,从而确保了观测方程求解的精确性和稳定性;分析了所需信息时间窗与计算冗余时间的关系.另外,提出了Butterworth前置低通滤波器方案,以消除故障暂态高频信号频谱混淆和线路参数依频特性的影响.基于电磁暂态仿真程序ATP-EMTP,采用JMarti依频线路模型建立超高压输电系统仿真模型进行全面系统的仿真验证,结果表明所提故障测距方案在精度、稳定性和实用性等方面都能很好地满足工程要求. |
| 关键词: 故障测距 时域法 参数自适应 粒子群优化算法 Butterworth滤波器 |
| DOI： |
| 分类号:TM755 |
| 基金项目:国家自然科学基金重点项目，广东省自然科学基金? |
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| Time domain fault locating with parameter self-adaptation based on PSO algorithm and Butterworth low-pass filter |
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WANG Gang LIANG Yuansheng LI Haifeng LI Wenhui
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| Abstract: |
| The time domain observation equations of parameter self-adaptation and fault locating are established with the pre-and post-fault electrical signals and the PSO(Particle Swarm Optimization)algorithm is employed to search the global optimal solution,which ensures the accuracy and stability. The relationship between the needed time window and the calculating time is analyzed. A Butterworth low-pass pre-filter scheme is introduced to eliminate the effect of frequency spectrum confusion and line parameter frequ... |
| Key words: fault locating time domain analysis parameter self-adaptation particle swarm optimization Butterworth filters |
