Fault location of the renewable energy sources connected distribution networks based on time differences of the modal traveling waves

• Published in: IEEE access 2023-01, Vol.11, p.1-1
• Main Authors: Ren, Xiaofeng, Pan, Yihang, Hou, Meng, Liang, Rui, Su, Lingdong, Wang, Quanjin, Zhang, Peng
• Format: Article
• Language: English
• Subjects: Algorithms; Attenuation; Data processing; Distributed generation; Distribution networks; Electrical grounding; Energy distribution; Fault location; Faults; Frequencies; Grounding; Heuristic algorithms; Particle swarm optimization; Power flow; preferred frequency band; Renewable energy sources; Resistance; Short circuits; Time-frequency analysis; Topology; traveling wave modulus time difference; Traveling wave tubes; Traveling waves; Wave attenuation; Wave velocity; Weight measurement; weighted deviation
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2023.3332633

The topology of the distribution network and direction of the power flow will change when distributed generators (DGs) are connected to it, making it difficult to locate faults using conventional techniques like the impedance approach. Aiming at the two-phase short-circuit grounding faults of active distribution networks, this paper proposes a fault location method based on the time difference of the traveling wave modulus. The first step is the proposal of a zero-mode time-of-arrival calibration method for the ideal frequency band through the analysis of the attenuation of zero-mode traveling wave transmission. Next, define the relative wave velocity, research the quantitative relationship between the modulus transmission time difference and the zero-mode and aerial-mode wave velocities, and establish equation constraints between the modulus transmission time difference, relative wave velocity, and transmission distance. Then, time bounds and dynamic inequality constraints that establish relative wave velocities by fitting. Finally, combined with the abnormal data processing strategy, with the goal of minimizing the weighted deviation of the modulus time difference, the particle swarm optimization (PSO) algorithm is used to solve the fault distance. The PSCAD simulation result demonstrates that the method proposed in this paper has the advantages of high accuracy, strong error tolerance, and strong adaptability, and can quickly and accurately locate faults.