CAJ | 학술논문

传统的人工智能算法在配电网馈线故障定位中的应用广泛，存在初始种群规模大，迭代次数多以及易陷入局部最优等缺陷。提出一种基于分布式估计算法的配电网故障区段定位方法，该方法将故障区段向量作为正确解，通过建立解空间内个体分布的概率模型，对模型采样，逐步提高最优故障区段向量在解空间内出现的概率。仿真结果表明将分布估计算法应用于多源开环条件下的配电网故障区段定位有着较快的故障定位速度和良好的容错性。
전통적인공지능산법재배전망궤선고장정위중적응용엄범，존재초시충군규모대，질대차수다이급역함입국부최우등결함。제출일충기우분포식고계산법적배전망고장구단정위방법，해방법장고장구단향량작위정학해，통과건립해공간내개체분포적개솔모형，대모형채양，축보제고최우고장구단향량재해공간내출현적개솔。방진결과표명장분포고계산법응용우다원개배조건하적배전망고장구단정위유착교쾌적고장정위속도화량호적용착성。
The use of traditional artificial intelligence algorithm in distribution network feeder fault location is wide. But some shortcomings such as large initial population, too much iterations and falling into optimum exist. This paper puts forward the estimation of distribution algorithm to realize the fault location, in which the fault section vector is regarded as the right solution. By sampling from the individual probability model established in the solution space, the probability of the optimal fault section vector is gradually improved. The simulation result shows that the application of estimation of distribution algo-rithm in the fault section location in multiple source ring-open distribution network has faster speed and good fault tolerance.