Chen Jie, Li Yong, Zeng Rong, Liu Junle, Chen An, Hou Liang, Zhao Long, Shahidehpour Mohammad
College of Electrical and Information Engineering, Hunan University, Changsha, 410082, China.
China Southern Power Grid Guangdong Zhongshan Power Supply Bureau, Zhongshan, 528400, China.
Sci Rep. 2024 Jun 2;14(1):12640. doi: 10.1038/s41598-024-62859-6.
The paper presents a fault region identification method for the active distribution network (ADN) with limited PMU. First, PMU configuration and region division strategies are proposed based on the network topology. Next, the difference in three-phase current variations between the normal and fault regions of the ADN is analyzed. A multi-dimensional state monitoring matrix is built using the measured current data. The spectral norm ratio coefficient is constructed based on the 2-norm to lower the complexity of the multi-dimensional state monitoring matrix and quantify the difference in state changes before and after the fault occurs in each region. Then, the fault region is identified by combining each region's spectral norm ratio coefficient and the change of the current phase. Finally, an IEEE 33-node simulation model is created to simulate faults under different working conditions. According to the simulation results, the suggested approach is less impacted by fault type, neutral point grounding mode, and transition resistance. Furthermore, even if the communication does not match the rigorous synchronization requirements, the proposed method can still complete the fault identification of the distribution network correctly and has high robustness.
本文提出了一种适用于配备有限数量相量测量单元(PMU)的有源配电网(ADN)的故障区域识别方法。首先,基于网络拓扑结构提出了PMU配置和区域划分策略。接下来,分析了ADN正常区域和故障区域之间三相电流变化的差异。利用测量得到的电流数据构建了一个多维状态监测矩阵。基于2-范数构建谱范数比系数,以降低多维状态监测矩阵的复杂度,并量化故障发生前后各区域状态变化的差异。然后,通过结合各区域的谱范数比系数和电流相位变化来识别故障区域。最后,创建了一个IEEE 33节点仿真模型,以模拟不同工况下的故障。根据仿真结果,所提方法受故障类型、中性点接地方式和过渡电阻的影响较小。此外,即使通信不满足严格的同步要求,该方法仍能正确完成配电网的故障识别,具有很高的鲁棒性。