基于粒子群算法的配电网故障定位研究

发布时间：2018-05-19 05:58

本文选题：配电网 + 故障定位　；参考：《安徽理工大学》2017年硕士论文

【摘要】：当配电网发生故障时,会影响供电的可靠性和安全性,会造成用电用户的生活不便。所以,提升配电网的供电可靠性是电力行业工作人员必须面对的课题。但是,随着电网结构的升级,电压等级也在不断的升高,配电网的拓扑结构变得越来越繁琐。虽然国家电网投入大量的资金来完善配电网,但是由于线路的老化、自然灾害的频发以及人为操作的失误等因素,配电网还是会经常发生故障。所以,如何提高配电网诊断故障的能力以及诊断结果的准确性成为未来一段时间的一个热门的研究课题。分布式电源的接入,对于配电网故障定位的领域,又带来了一个新的挑战。本文在大环境下,结合标准二进制粒子群算法在传统配电网故障定位中的应用方式,将其进行改进,引入压缩因子和线性递减的惯性权重,生成新的改进二进制粒子群算法,对改进的算法建立新的编码方式、开关函数和适应度函数,并将其运用在含DG的配电网故障定位中。用MATLAB进行仿真验证。在此基础上,本文设计一种ARM+FPGA的硬件装置来进行故障定位。本文总体围绕含分布式电源的配电网故障定位来进行研究,改进传统的算法并进行仿真,设计硬件装置来实现该方法的配电网故障定位。对后续含有分布式电源的配电网故障定位提供一定的基础。
[Abstract]:When the distribution network fails, it will affect the reliability and safety of power supply, and cause inconvenience to users. Therefore, to improve the distribution network power supply reliability is the power industry staff must face the subject. However, with the upgrading of power network structure and the increasing of voltage level, the topology of distribution network becomes more and more complicated. Although the State Grid has invested a lot of money to perfect the distribution network, due to the aging of the transmission line, frequent natural disasters and human error, the distribution network will often fail. Therefore, how to improve the ability of fault diagnosis and the accuracy of diagnosis results has become a hot research topic in the future. The access of distributed generation brings a new challenge to the field of distribution network fault location. In this paper, combined with the application of standard binary particle swarm optimization algorithm in traditional distribution network fault location, the compression factor and linear decreasing inertia weight are introduced to generate a new improved binary particle swarm optimization algorithm. A new coding method, switching function and fitness function are established for the improved algorithm, and they are applied to fault location of distribution network with DG. The simulation results are verified by MATLAB. On this basis, this paper designs a hardware device of ARM FPGA for fault location. This paper focuses on the distribution network fault location with distributed power generation, improves the traditional algorithm and simulates, and designs hardware devices to achieve the distribution network fault location. It provides a basis for fault location of distribution network with distributed power supply.
【学位授予单位】：安徽理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP18;TM711

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