2024-08-20
2024-07-22
2024-06-20
Abstract—For better solving the problem of multi-terminal fault location in the distribution network, this paper proposes a new fault location method based on Strong Tracking Filter (STF) and Parameter Adaptive Differential Evolution Algorithm (PADEA), which can be applied to asynchronous sampling systems. STF is adopted for real-time fundamental wave amplitudes’ extraction of voltage and current. STF can achieve the fast track of power parameters’ mutation, and also make the construction of the Distributed Generators’ (DG) impedance model more accurate. On the basis of the establishment of impedance model and fault feature analysis, the fault feature value is defined by using only the amplitude of signals measured at the measurement points without introducing the phase angle, which can avoid the introduction of the sampling error radically. PADEA is adopted in the precise fault location part. The use of PADEA can improve the simulation efficiency and result accuracy. Simulation results in MATLAB/Simulink show that the method proposed in this paper has advantages of high accuracy and strong robustness. Index Terms—Strong Tracking Filter (STF), fault location, Parameter Adaptive Differential Evolution Algorithm (PADEA), asynchronous sampling Cite: Zhongjian Kang, Ruiying Liu, and Yanyan Feng, "Research on Fault Location Method in Distribution Network with DG Based on PADEA," Journal of Communications, vol. 10, no. 8, pp. 621-628, 2015. Doi: 10.12720/jcm.10.8.621-628