Photovoltaic power station fault diagnosis method

Abstract

The invention discloses a photovoltaic power station fault diagnosis method. The method has the advantages that the automatic testing optimization design is achieved, the fault coverage rate of a testing scheme is increased, the fault ambiguity, the average test cost and the average test time are reduced, the test redundancy is designed according to needs, the overall test cost is reduced, and the test time is shortened; a photovoltaic power station fault strategy is automatically generated, online automatic diagnosis of photovoltaic power station faults is achieved, shut-down is avoided in the diagnosis process, the faults are fast and accurate to locate, the harm time of the faults is shortened, the fault shut-down time is shortened, and the power generation time of a photovoltaic power station is prolonged; dependence, on the technical level of personnel, of the photovoltaic power station faults is reduced, the diagnosis cost is low, the diagnosis level is stable, the diagnosis work amount is small, the requirement for test equipment is low, fast maintaining can be achieved, the power generation time is guaranteed, the diagnostic procedure is fast, and therefore further deterioration of the faults is prevented.

Description

technical field [0001] The invention relates to a fault diagnosis method for a photovoltaic power station. Background technique [0002] Photovoltaic power station systems (including distributed photovoltaic power stations) are mainly composed of photovoltaic panels, DC cables, DC combiner boxes, inverters, AC cables, AC combiner boxes, transformers, etc. Problems such as battery pollution, short circuit, switch damage, line wear, and aging in the photovoltaic power station system will cause the power generation of the photovoltaic power station to drop or even shut down. [0003] The current photovoltaic power station only has a monitoring system, such as figure 1 As shown, the fault diagnosis method of the photovoltaic power station is a diagnosis method based on single-point monitoring. The photovoltaic power station monitoring system can monitor the voltage and current of the photovoltaic cell string, the voltage and current of the combiner box, and the input and output...

AI Technical Summary

Problems solved by technology

When a certain device fails, it will lead to abnormal operation status of a series of devices. For example, when a wire connecting the photovoltaic cell array and the DC combiner box is disconnected or the impedance becomes large, the output voltage of the battery array will rise, and the output current will increase. decrease, the input voltage of the inverter rises, and the output current decreases. The monitoring system may recognize that the state of the inverter, DC combiner box, and battery array is abnormal, but it cannot locate the specific device that is faulty.

[0004] The current method is: after monitoring the abnormal state, according to the work experience of the operation and maintenance personnel, through manual guessing, the method of test and replacement is used to find the specific fault location, which has low work efficiency and high cost, and cannot realize online diagnosis and positioning.

[0005] In short, at present, the fault diagnosis of photovoltaic power plants only stays at the level of condition monitoring and manual trial replacement, and the degree of automation is low.

Its diagnosis depends on the technical level of the maintenance personnel, and requires specialized technical experts to realize it. The labor cost is high, the technology is unstable, and the fault location takes a long time. The diagnosis process needs to be shut down, which affects the power generation time

Due to the long time to find the problem, it will lead to further deterioration of the fault

The manual diagnosis process requires constant attempts to replace equipment, and the diagnosis process requires a large amount of work. The diagnosis process requires professional equipment for various manual tests, and the test cost is high.

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