自适应细菌觅食算法的局部放电定位
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1.上海电力大学电子与信息工程学院;2.上海电机学院电子信息学院;3.华北电力大学新能源电力系统国家重点实验室;4.上海大学机电工程与自动化学院

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TM406

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国家自然科学基金(61202369、61401269和61572311);上海市科技创新项目(17020500900);由上海教育发展基金会和上海市教委主办的


BACTERIAL FORAGING IMPROVED ALGORITHM FOR TRANSFORMER PARTIAL DISCHARGE LOCALIZATION STUDY
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School of Electronics and Information Engineering, Shanghai Electric Power University

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    摘要:

    实现局部放电(PD)源准确定位对保证电气设备长期安全运行具有重要意义。为提高PD源定位的精度,基于到达时间差(TDOA)法的原理,提出自适应惯性权重细菌觅食定位算法(AIW-BFA),自适应调整搜索步长,通过驱化、复制和分散进行全局寻优。由于电磁波在变压器内传播会发生反射、折射和衍射,使得PD源的定位变得更为复杂,基于最短光程原理,提出在变压器箱体内存在障碍物情况下的电磁波传输路径计算模型,来降低时延误差。通过仿真实验和现场实验,AIW-BFA定位精度可以满足定位需求,并且优于BFA法和PSO法,证明了提出模型以及定位算法的有效性。

    Abstract:

    Achieving accurate localization of partial discharge (PD) sources is of great importance to ensure the long-term safe operation of electrical equipment. To improve the accuracy of PD source localization, the adaptive inertial weight bacterial foraging localization algorithm (AIW-BFA) is proposed based on the principle of time difference of arrival (TDOA) method, which adaptively adjusts the search step size and performs global optimization seeking through repulsion, replication and dispersion. Since the electromagnetic wave propagation inside the transformer will be reflected, refracted and diffracted, which makes the localization of PD source more complicated, based on the principle of shortest optical range, the computational model of electromagnetic wave transmission path in the presence of obstacles inside the transformer box is proposed to reduce the time delay difference. Through simulation and field experiments, the AIW-BFA localization accuracy can meet the localization requirements and is better than the BFA and PSO methods, which proves the effectiveness of the proposed model and the localization algorithm.

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引用本文

雪婷,杨俊杰,薛乃凡,等. 自适应细菌觅食算法的局部放电定位[J]. 科学技术与工程, , ():

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  • 收稿日期:2022-02-09
  • 最后修改日期:2022-05-08
  • 录用日期:2022-05-13
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