欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
为解决金属氧化物避雷器（MOA）老化在线监测问题,提出一种基于粒子群算法（PSO）的MOA在线监测技术。通过PSO算法较好地拟合逼近效果,计算MOA等效模型中反应MOA老化情况的α、k、c值,进而实现在线监测MOA的老化状态。此外,利用MATLAB仿真分析了电网电压中谐波电压对该算法的影响。仿真分析表明：PSO算法可以较好地将模型中的计算泄漏电流拟合逼近实际测量的泄漏电流,求解出α、k、c值,实现对MOA老化监测。此外,文中算法对于电力电网系统运行电压中谐波电压含量及其初相位具有较好的抗干扰性,验证了文中算法的可靠性,提高了MOA在线监测的准确性。
英文摘要：
An on-line monitoring technology of metal oxide arrester （MOA） degradation based on the particle swarm optimization algorithm is proposed for on-line aging monitoring of MOA. PSO algorithm is employed to compute the aging parameters, α.k and c of the MOA equivalent model for monitoring the degradation of MOA. In addition, the simulation by the MATLAB to analysis the impact of the voltage harmonic in the power grid to the algorithm in this paper. Simulation shows that PSO algorithm can fit the calculated leakage current of the equivalent model to the measured one, and calculate the parameters α,k and c, which change during the aging period of MOA, for monitoring. It is concluded that the proposed on-line aging monitoring technology can suppress the influences of the content and initial phase of working voltage harmonies to raise its accuracy, and is effective and reliable.
同期刊论文项目
同项目期刊论文
Three-dimensional propagation characteristics of the leaders in the attachment process of a downward
Numerical simulation of the effects of randomness and characteristics of electrical environment on g
Numerical simulation of the effect of lower positive charge region in thunderstorms on different typ
Three-dimensional propagation characteristics of the upward connecting leaders in six negative tall-
期刊信息
位置：