An online location method for single-phase fault in distribution network

Abstract

The embodiment of the invention provides an online positioning method for distribution network single-phase fault, which relates to the field of power system fault positioning and can judge a fault circuit without depending on zero-sequence current and realize quick online positioning on the distribution network single-phase grounding fault. The method of the specific scheme comprises steps: when SCADA (Supervisory Control And Data Acquisition) determines a single-phase fault judgment condition is met, a phase current recording command is sent to K RTUs (Remote Terminal Unit), wherein the phase current recording command comprises the fault happening time determined by the SCADA and the fault phase information; the K RTUs sample fault phase current signals in M cycles before and after the fault happening time, effective energy is obtained through wavelet transformation, and the effective energy is transmitted to the SCADA; and according to the effective energy returned by the K RTUs, the SCADA judges a single-phase fault line from lines monitored by the K RTUs. The method of the invention is used for judging the single-phase fault line.

Description

technical field [0001] Embodiments of the present invention relate to the field of fault location in power systems, and in particular to an online location method for single-phase faults in distribution networks. Background technique [0002] In order to maximize the reliability of power supply, most of my country's medium-voltage distribution network is a small-current grounding system, which can run without power for a period of time after a single-phase ground fault occurs in the system; at the same time, in order to avoid the insulation caused by long-term faulty operation When problems such as damage and fault range expansion occur, it is very important to quickly identify and isolate single-phase faults. [0003] At this stage, the above problems need to be solved in three steps successively by means of fault diagnosis, fault line selection and fault location: first, the zero-sequence voltage at the busbar exceeds the setting value of three times as the fault start crit...

AI Technical Summary

Problems solved by technology

However, due to the large number of lower-level branch lines outgoing from the busbar and the serious shortage of observables, the existing zero-sequence current-based fault identification methods have many deficiencies.

[0005] For example, passive positioning methods represented by the fifth harmonic method, capacitive current method and first half-wave method rely more on the acquisition of zero-sequence current, but due to the complex structure of the zero-sequence transformer or zero-sequence filter of the lower branch line , expensive, and inconvenient to install. Once installed or replaced, it is necessary to re-select the matching section switch, so it cannot be widely used in overhead lines, and the reliability of the judgment result is affected by the large error; in the prior art, S The active positioning method represented by the injection method and the medium resistance switching method often has a huge investment in hardware, and the interharmonic injection is easy to affect other smart devices, especially when the medium resistance switching method is used, the original neutral point of the power grid is changed. The nature of grounding destroys its reliability advantages in single-phase fault scenarios; in the prior art, the solutions for locating faults based on fault location, such as the traveling wave method, have the disadvantages of requiring multi-terminal time synchronization, difficult detection of wave heads, and being affected by transitions. In addition to the inherent defects of the influence of resistance, the effect on the distribution network with uneven parameters is not ideal; in the prior art, there are also solutions for locating faults based on intelligent algorithms such as genetic algorithms, expert systems, and simulated evolutionary algorithms, although they have good fault tolerance. , but heavily relies on expert experience and knowledge, the construction of the evaluation function is complex, and the adaptability to changes in the structure of the distribution network is low

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