粒子群优化算法在电气设备特高频局部放电源定位中的应用

Application of Particle Swarm Optimization Algorithm in Electrical Equipment UHF PD Source Positioning

带电检测是判断高压电气设备内部绝缘性能的重要手段之一,特高频局部放电检测技术可以实现由绝缘缺陷引起其内部局部放电源放电类型的诊断及定位。采用粒子群优化算法求解不同时间段局部放电源所在位置,建立三维空间模型,采用粒子群优化算法优化定位初值,降低电气设备特高频局部放电定位精度对到达时间差法时延的依懒性。试验证明带电检测过程中对特高频局部放电定位采用粒子群优化算法求解与优化可以将外界环境对到达时间差算法的时延干扰降至最低,提高定位精度与定位速率,适用于高压电气设备内部局部放电的带电检测。

The live detection technology is one of the most important methods to judge the internal insulation performance of high voltage electrical equipment. Ultra-High frequency partial discharge live detection technology can be used to realize the diagnosis and positioning of insulation discharge caused by partial discharge resuhed from insulation defects. Particle swarm optimization algorithm is adopted to solve the location of local power supply at different time periods. A three-dimensional spatial model is established, and particle swarm optimization algorithm is used to optimize the initial positioning value, so as to reduce the dependence of electrical equipment＇s ultra-high-frequency partial discharge positioning accuracy on time delay of arrival time difference method. The field test shows that the particle swarm optimization with cross grouping and layered approximation for the localization initial value of the UHF partial discharge can minimize the delay interference of the time difference of arrival algorithm, improve the positioning accuracy and speed, can be applied to the live detection of partial discharge in high voltage electrical equipment.