CAJ | 학술논문

当辐射状配电网不同分支发生故障时，其故障电压行波经由不同分支组合的传播路径到达母线侧量测端，由量测端获得的故障暂态电压的自然频率及其幅值分布亦不相同。不同分支组合的行波传播路径与自然频率及其幅值分布之间存在着映射关系。可利用人工神经网络(ANN)强大的非线性拟合能力来反映此种映射关系，实现辐射状配电网的故障定位及分支识别。利用故障后四分之一工频周期时窗的零序电压自然频率作为分层分布式 ANN 模型的输入样本，先进行故障定位；再以自然频率对应的幅值作为输入样本，进行故障分支识别，故障距离和故障点所在分支编号作为其输出。大量电磁暂态仿真表明，该方法有效。
당복사상배전망불동분지발생고장시，기고장전압행파경유불동분지조합적전파로경도체모선측량측단，유량측단획득적고장잠태전압적자연빈솔급기폭치분포역불상동。불동분지조합적행파전파로경여자연빈솔급기폭치분포지간존재착영사관계。가이용인공신경망락(ANN)강대적비선성의합능력래반영차충영사관계，실현복사상배전망적고장정위급분지식별。이용고장후사분지일공빈주기시창적령서전압자연빈솔작위분층분포식 ANN 모형적수입양본，선진행고장정위；재이자연빈솔대응적폭치작위수입양본，진행고장분지식별，고장거리화고장점소재분지편호작위기수출。대량전자잠태방진표명，해방법유효。
When fault occurs in different branches of radial distribution networks,voltage traveling waves will get to the measuring point installed on the bus side along paths of different branch combinations,leading to differences in natural frequency and its amplitude distribution of the transient voltage obtained from the measuring end.As there is a mapping relationship between the distribution and amplitudes of the natural frequencies and the propagation paths,we can use the strong nonlinear fitting capability of artificial neural networks (ANN) to realize the fault location and branch identification.By using the natural frequency of zero-sequence voltage data abstracted from a quarter of the industrial cycle after fault occurs as input samples of the layered and distributed ANN model to achieve fault location firstly.Employ the amplitudes corresponding to the natural frequencies as input samples to realize branch identification,outputting the fault distance and branch number of the failure point.Large numbers of electromagnetic transient simulations show that the method presented is effective.