变压器局部放电的泰勒?遗传综合定位法

Taylor-Genetic Algorithm Using for PD Location in Power Transformer

基于变压器时间差定位法的双曲面方程,提出一种用于变压器局部放电源定位的泰勒?遗传综合算法。该算法采用最大似然估计法建立最优方程寻求局部放电源出现最大概率的位置,通过泰勒展开将似然函数线性化,再由遗传算法全局搜索为泰勒展开提供合适的初始点,并利用定位双曲面函数方程个数多于定位所必须的最低个数时出现的冗余数据融合,不断修正定位结果,使得定位寻优过程快速。研究结果表明,冗余信息的增加能有效改善定位精度,利用遗传算法寻找合适的初始点大大提高了泰勒算法的可行性。

Based on time delay extraction by UHF sensors to locate partial discharge in power transformer, hyperbolic mathematical equations are nonlinear and hard to be solved. In this paper, Taylor-genetic algorithm is proposed to solve the hyperbolic equations, which used the maximum likelihood method to establish optimal equation to seek the greatest probability of PD source. Then made the optimal equation linear by Taylor expansion. Finally, usd genetic global searching to provide the right initial point for Taylor expansion, the location of PD source after some iteration steps was obtained. While the number of hyperboloid equations is larger than the minimum number for PD location, we can correct results by the redundant data fusion. The results show that the increase of redundant information can effectively improve location accuracy, and the use of genetic algorithms to find appropriate initial point greatly enhances the feasibility of the Taylor algorithm, making the searching process rapidly and accurately.