改进的QPSO算法在电网故障诊断系统中的应用
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太原理工大学信息工程学院,太原理工大学信息工程学院,甘肃省张掖供电公司,太原理工大学信息工程学院

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TM732

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中国博士后科学基金


Application of The Improved QPSO Algorithm in The Fault Diagnosis of Power System
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College of Information Engineering,Taiyuan University of Technology,Taiyuan,College of Information Engineering,Taiyuan University of Technology,Taiyuan,Power Company of Zhang Ye,Gansu Province,College of Information Engineering,Taiyuan University of Technology,Taiyuan

Fund Project:

China Postdoctoral Science Foundation

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    摘要:

    电网故障诊断系统通常基于建立的解析模型,通过分析保护和断路器的动作信息来推断可能的故障位置,从而识别保护与断路器的故障元件和误动作。本文根据保护动作原理,构建了一种改进的解析模型,并采用改进的量子粒子群算法对其目标函数进行优化求解。该模型不仅充分考虑到了保护和断路器的误动与拒动、断路器失灵保护等问题,且能辨识告警信息的误报和漏报。实验结果表明改进的算法不仅使故障诊断结果更精确,并能使故障情况很清晰的表示出来,有利于故障的及时恢复,同时使模型的运算速度和稳定性也进一步得到了提高。

    Abstract:

    The power fault diagnosis system is generally to identify the fault components and malfunction of the protective relays and circuit breakers, and it infers the fault location by analyzing the information of the movement of the protective relays and circuit breakers based on the analytic model. This paper constructs an improved analytical model based on the principle of the protected action and optimizes the solving of its objective function using the improved quantum particle swarm algorithm. The new model not only fully takes into account the false action and refusing action of the protective relays and circuit breakers, the malfunction of protective relays of the circuit breakers and other issues, but also identifies the false and missing alarm of the warning information. The experimental results showed that the improved algorithm not only makes the results of fault diagnosis more accurate but also makes the fault situation shown more clearly. It was conducive to timely recover the fault, while the computing speed and the stability of the model have been further improved.

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李凤莲,李园园,金铖,陈晓磊.改进的QPSO算法在电网故障诊断系统中的应用计算机测量与控制[J].,2014,22(12).

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  • 收稿日期:2014-04-24
  • 最后修改日期:2014-05-16
  • 录用日期:2014-05-20
  • 在线发布日期: 2014-12-10
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