Photovoltaic power station operation and maintenance quality evaluation method and device based on fault elimination efficiency

Abstract

The invention discloses a photovoltaic power station operation and maintenance quality evaluation method based on fault elimination efficiency, and the method comprises the steps: obtaining the state data Si1 and power generation data Gi1 of each to-be-detected device in a photovoltaic power station, and the to-be-detected device comprises each photovoltaic branch, an inverter and a box transformer substation; comparing the obtained state data Si1 and the power generation data Gi1 with reference group data respectively; when the comparison result is that the equipment fails, tracking and recording the failed equipment, the fault level and the fault duration; distributing different weights based on the fault equipment and the fault level to obtain an equipment weighting coefficient A and a fault level weighting coefficient L; according to the equipment weighting coefficient A and the fault level weighting coefficient L, the fault average processing duration T of the photovoltaic power station is determined; and comparing the average fault processing duration T with the operation and maintenance level grade coefficient O, determining the operation and maintenance quality grade of the photovoltaic power station, quantitatively evaluating the fault response speed and processing capability of the operation and maintenance team, and ensuring efficient and safe operation of the photovoltaic power station.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power station operation and maintenance management, and in particular to a photovoltaic power station operation and maintenance quality assessment method and device based on fault elimination efficiency. Background Art

[0002] With the vigorous development of the photovoltaic industry, the construction scale of photovoltaic power stations has continued to expand. The operation and maintenance management of the power station for 25 years after its completion has gradually become the focus of the photovoltaic industry, and the long-term operation and maintenance of the power station has become the key to the development of the industry. The operation and maintenance quality of photovoltaic power stations not only directly affects the power generation efficiency and economic benefits of the power station, but is also closely related to the safe operation of the power station. Therefore, high-quality operation and maintenance management is particularly critical. For photovoltaic groups, it is crucial to scientifically evaluate the operation and maintenance quality of the operation and maintenance team.

[0003] However, the photovoltaic group is currently relatively extensive in evaluating the operation and maintenance quality of its power stations, mainly relying on some basic indicators and extreme event indicators, such as "equivalent utilization hours", "number of personal safety accidents" and "number of fires", etc., and lacks detailed monitoring and evaluation methods for key performance indicators such as the efficiency of fault handling that often occurs in daily operation and maintenance. This is actually related to the large area and large number of equipment of photovoltaic power stations. A 100MW photovoltaic power station covers an area of ​​1,500 acres and has more than 8,000 branches. The time of occurrence and duration of each fault cannot be manually counted one by one. However, if only this extensive evaluation method is used, it will lead to the inability to distinguish between teams with high operation and maintenance efficiency and teams with low efficiency, which will in turn affect the enthusiasm of the operation and maintenance team to improve service quality, and ultimately have a negative impact on the overall revenue of the power station. Summary of the invention

[0004] The purpose of the present invention is to solve the above-mentioned technical problems and provide a photovoltaic power station operation and maintenance quality assessment method based on fault elimination efficiency, which can obtain the efficiency of fault handling by calculating the average fault handling time, so as to quantitatively evaluate the fault response speed and processing capability of the operation and maintenance team, and ensure the efficient and safe operation of the photovoltaic power station.

[0005] In order to solve the above problems, the present invention is implemented according to the following technical solutions:

[0006] In a first aspect, the present invention provides a method for evaluating the operation and maintenance quality of a photovoltaic power station based on fault elimination efficiency, the method comprising:

[0007] S100, obtaining status data Si1 and power generation data Gi1 of each device to be detected in the photovoltaic power station, wherein the device to be detected includes each photovoltaic branch, inverter and box transformer;

[0008] S200, comparing the acquired state data Si1 and power generation data Gi1 with the reference group data respectively;

[0009] S300, when the comparison result is a device failure, tracking and recording the failed device, the failure level and the failure duration;

[0010] S400, assigning different weights based on the faulty equipment and fault level to obtain equipment weighting coefficient A and fault level weighting coefficient L;

[0011] S500, determining an average fault processing time T of the photovoltaic power station according to the equipment weighting coefficient A and the fault level weighting coefficient L;

[0012] S600: Compare the average fault processing time T with the operation and maintenance level coefficient O to determine the operation and maintenance quality level of the photovoltaic power station.

[0013] Furthermore, the benchmark group data includes benchmark state data Si0 and benchmark power generation data Gi0; wherein the benchmark state data Si0 is data when the equipment is in normal state; and the benchmark power generation data Gi0 is the average power generation value of all branches of the same type of components in the same area.

[0014] Further, S210, determining a power generation deviation value e according to the reference power generation data Gi0 and the power generation data Gi1 of the device to be detected; wherein, e=(Gi1-Gi0) / Gi0.

[0015] Further, S220, the state data Si1 of the device to be detected is compared with the reference state data Si0 to obtain the state of the device; the power generation deviation value e is compared with the fault sensitivity B to obtain the state of the device and the fault level when the device state is a fault.

[0016] Furthermore, the equipment weighting coefficient A includes a first equipment weighting coefficient A1, a second equipment weighting coefficient A2 and a third equipment weighting coefficient A3; the fault level weighting coefficient L includes a first fault level weighting coefficient L1 and a second fault level weighting coefficient L2; wherein, A1+A2+A3=1; L1+L2=1.

[0017] Furthermore, the average fault processing time T = (average fault time of box transformer level 1 fault * L1 + average fault time of box transformer level 2 fault * L2) * A1 + (average fault time of inverter level 1 fault * L1 + average fault time of inverter level 2 fault * L2) * A2 + (average fault time of branch level 1 fault * L1 + average fault time of branch level 2 fault * L2) * A3; wherein the average fault time is the arithmetic mean of all faults of this level under the device.

[0018] Furthermore, the operation and maintenance level coefficient O includes a first operation and maintenance level coefficient O1, a second operation and maintenance level coefficient O2, a third operation and maintenance level coefficient O3 and a fourth operation and maintenance level coefficient O4.

[0019] Further, S610, when T≥O4, the operation and maintenance quality level of the photovoltaic power station is level 1; when O3≤T<O4, the operation and maintenance quality level of the photovoltaic power station is level 2; when O2≤T<O3, the operation and maintenance quality level of the photovoltaic power station is level 3; when O1≤T<O2, the operation and maintenance quality level of the photovoltaic power station is level 4; when T<O1, the operation and maintenance quality level of the photovoltaic power station is level 5.

[0020] In the second aspect, the present invention provides a photovoltaic power station operation and maintenance quality assessment device based on fault elimination efficiency, and the photovoltaic power station operation and maintenance quality assessment device based on fault elimination efficiency is used to implement the photovoltaic power station operation and maintenance quality assessment method based on fault elimination efficiency as described in any one of the first aspects, and the device includes: a photovoltaic operation and maintenance intelligent monitoring box and a configuration system.

[0021] Furthermore, the photovoltaic operation and maintenance intelligent monitoring box is used to detect the status of each device in the photovoltaic power station and evaluate the operation and maintenance quality of the photovoltaic power station; the configuration system is used to set the fault sensitivity B, the equipment weighting coefficient A, the fault level weighting coefficient L and the operation and maintenance level coefficient O.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] The present invention provides a method for evaluating the operation and maintenance quality of a photovoltaic power station based on the efficiency of fault elimination. The method obtains the status data and power generation data of each transformer, inverter, and photovoltaic branch of the photovoltaic power station, and continuously tracks and records the faults. Different weight values ​​are set according to the different degrees of influence of the faulty equipment and fault level on the power generation. The average fault processing time of the photovoltaic power station is calculated accordingly, so as to judge the operation and maintenance quality of the photovoltaic power station. The method does not require the installation of sensors on the photovoltaic power station, and the monitoring range covers all photovoltaic components of the entire power station. The precision can reach the branch level, which is accurate and true, and can fully reflect the actual operation and maintenance efficiency of the power station. It does not require manual assistance, and can efficiently monitor the operation and maintenance quality of all photovoltaic power stations under the group.

[0024] The fault elimination efficiency is used to quantitatively evaluate the fault response speed and processing capabilities of the operation and maintenance team, monitor the efficiency of daily operation and maintenance work, and provide a unified evaluation and comparison standard for the operation and maintenance efficiency of multiple power station operation and maintenance teams under the group, thereby motivating each power station operation and maintenance team to continuously improve and enhance service quality and ensure efficient and safe operation of the power station. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The specific embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings, wherein:

[0026] Figure 1 is an implementation flow chart of a preferred embodiment of the present invention;

[0027] Figure 2 The present invention is a schematic diagram of the relationship between a photovoltaic power station box transformer, an inverter, and a branch circuit. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0029] The terms used in this application are only for the purpose of describing specific embodiments and are not intended to limit this application. Unless otherwise defined, the technical terms or scientific terms used in this specification should be understood by people with ordinary skills in the field to which this application belongs. The words "first", "second" and similar words used in this specification and claims do not indicate any order, quantity or importance, but are only used to distinguish different technical features.

[0030] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0031] like Figure 1 As shown, a photovoltaic power station operation and maintenance quality assessment method based on fault elimination efficiency according to the present invention comprises the following steps:

[0032] S100, obtaining status data Si1 and power generation data Gi1 of each device to be detected in the photovoltaic power station, where the devices to be detected include each photovoltaic branch, inverter and box transformer.

[0033] It should be noted that the box transformer refers to a box-type transformer. In a photovoltaic power station, each photovoltaic branch, inverter and box transformer are the most critical components. Their failure will directly affect the power generation efficiency and safe operation of the power station. Figure 2As shown, a schematic diagram of the relationship between a photovoltaic power station box transformer, an inverter, and a branch is disclosed, wherein the box transformer is connected in parallel with multiple photovoltaic inverters, and each photovoltaic inverter is connected in parallel with multiple photovoltaic branches. The photovoltaic branch includes photovoltaic modules and related DC circuits. Problems such as module damage, hot spot effect, cell disconnection, cable breakage, connector or junction box burnout may lead to reduced power generation efficiency or safety hazards. For example, insufficient module voltage, reverse connection of PV input terminals, failure of the DC switch to close, improper connection of the connector when the module is connected in series, or short circuit of the module may cause the inverter to fail to work properly. The inverter is a key device for converting DC power into AC power, and its failure may cause a power outage in the power station. The box transformer is used to boost the low-voltage AC power output by the inverter to a high-voltage power suitable for grid transmission. Cable faults, such as loose connectors and damaged insulation, may lead to poor contact, increased resistance or even disconnection, or cause short circuit or leakage accidents. Therefore, by obtaining the status data and power generation data of each box transformer, inverter, and photovoltaic branch of the photovoltaic power station, and continuously tracking and recording the faulty equipment, fault level, and fault duration, the fault handling efficiency can be obtained, thereby evaluating the operation and maintenance quality of the photovoltaic power station, and providing a unified evaluation and comparison standard for the operation and maintenance efficiency of multiple power station operation and maintenance teams under the group, thereby motivating the operation and maintenance teams of each power station to continuously improve and enhance the service quality and ensure the efficient and safe operation of the power station.

[0034] S200 , comparing the acquired state data Si1 and power generation data Gi1 with the reference group data respectively.

[0035] Furthermore, the benchmark group data includes benchmark state data Si0 and benchmark power generation data Gi0; wherein, the benchmark state data Si0 is data when the equipment is in normal state; and the benchmark power generation data Gi0 is the average power generation value of all branches of the same type of components in the same area.

[0036] Furthermore, the power generation deviation value e is determined according to the reference power generation data Gi0 and the power generation data Gi1 of the device to be detected; wherein, e=(Gi1-Gi0) / Gi0.

[0037] Furthermore, the state data Si1 of the device to be detected is compared with the reference state data Si0 to obtain the state of the device; the power generation deviation value e is compared with the fault sensitivity B to obtain the state of the device and the fault level when the device state is a fault.

[0038] In one embodiment, the data when each device is in a normal state can be recorded as Si0 (a0, b0, c0...), and the acquired real-time state data of each device can be recorded as Si1 (a1, b1, c1...). Compared with the reference state data, when a1 = a0, it indicates that there is no fault, and when a1 ≠ a0, it indicates that there is a fault. According to the actual situation, the fault sensitivity B (B1, B2) is set in the system background, and the power generation deviation value e is compared with the fault sensitivity B. When e ≥ B2, it indicates that there is no fault; when B1 ≤ e < B2, it indicates that a level 1 fault has occurred;

[0039] When e<B1, it indicates that a level 2 fault occurs.

[0040] S300: When the comparison result is a device failure, track and record the failed device, the failure level, and the failure duration.

[0041] S400 , assigning different weights based on the faulty equipment and fault level to obtain equipment weighting coefficient A and fault level weighting coefficient L.

[0042] Furthermore, the equipment weighting coefficient A includes a first equipment weighting coefficient A1, a second equipment weighting coefficient A2 and a third equipment weighting coefficient A3. The fault level weighting coefficient L includes a first fault level weighting coefficient L1 and a second fault level weighting coefficient L2; wherein A1+A2+A3=1; L1+L2=1

[0043] S500 : Determine the average fault processing time T of the photovoltaic power station according to the equipment weighting coefficient A and the fault level weighting coefficient L.

[0044] Furthermore, the average fault handling time T = (average fault time of box transformer level 1 fault * L1 + average fault time of box transformer level 2 fault * L2) * A1 + (average fault time of inverter level 1 fault * L1 + average fault time of inverter level 2 fault * L2) * A2 + (average fault time of branch level 1 fault * L1 + average fault time of branch level 2 fault * L2) * A3; where the average fault time is the arithmetic mean of all faults of this level under the device. For example, a photovoltaic power station has box transformer #99 and box transformer #100, and the average fault time of box transformer level 1 fault represents the average fault time of all level 1 faults that occurred in these two box transformers.

[0045] S600: Compare the average fault handling time T with the operation and maintenance level coefficient O to determine the operation and maintenance quality level of the photovoltaic power station.

[0046] Furthermore, the operation and maintenance level coefficient O includes a first operation and maintenance level coefficient O1, a second operation and maintenance level coefficient O2, a third operation and maintenance level coefficient O3 and a fourth operation and maintenance level coefficient O4.

[0047] Furthermore, when T≥O4, the operation and maintenance quality level of the photovoltaic power station is level 1; when O3≤T<O4, the operation and maintenance quality level of the photovoltaic power station is level 2; when O2≤T<O3, the operation and maintenance quality level of the photovoltaic power station is level 3; when O1≤T<O2, the operation and maintenance quality level of the photovoltaic power station is level 4; when T<O1, the operation and maintenance quality level of the photovoltaic power station is level 5.

[0048] The present invention also provides a photovoltaic power station operation and maintenance quality assessment device based on fault elimination efficiency. The photovoltaic power station operation and maintenance quality assessment device based on fault elimination efficiency is used to implement any of the above-mentioned photovoltaic power station operation and maintenance quality assessment methods based on fault elimination efficiency. The device includes: a photovoltaic operation and maintenance intelligent monitoring box and a configuration system.

[0049] In this device, the photovoltaic operation and maintenance intelligent monitoring box is used to detect the status of each device in the photovoltaic power station and evaluate the operation and maintenance quality of the photovoltaic power station. The configuration system is used to set the fault sensitivity B, the equipment weighting coefficient A, the fault level weighting coefficient L and the operation and maintenance level coefficient O.

[0050] It should be noted that the photovoltaic operation and maintenance intelligent monitoring box has a built-in single-chip computer and storage unit, which can detect faults and evaluate the operation and maintenance quality of power stations. Among them, fault detection includes detecting faults of box transformers, inverters and photovoltaic branches. The monitored data types include faulty equipment name, fault level, fault duration, etc. The fault level is divided into level 1 fault and level 2 fault according to the fault sensitivity B (B1, B2). Fault detection compares the relevant data of the analysis group with the benchmark group to determine whether there is a fault. For example, the relative deviation value of the power generation data of the first branch in the first inverter under the first box transformer is compared with the benchmark power generation data, and whether the photovoltaic branch has a fault and the fault level is determined according to the fault sensitivity B (B1, B2). On the other hand, through the above-mentioned monitored faulty equipment name, fault type and fault duration, the average fault processing time is determined according to the equipment weighting coefficient A and the fault level weighting coefficient L, and then the operation and maintenance quality level of the photovoltaic power station is determined according to the operation and maintenance level coefficient O.

[0051] Furthermore, the photovoltaic operation and maintenance intelligent monitoring device also includes a display screen. The display screen is connected to the photovoltaic operation and maintenance intelligent monitoring box, and is used to set the fault sensitivity B, the equipment weighting coefficient A, the fault level weighting coefficient L and the operation and maintenance level coefficient O, and display the operation and maintenance quality level of each power station.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] The present invention provides a method for evaluating the operation and maintenance quality of a photovoltaic power station based on the efficiency of fault elimination. The method obtains the status data and power generation data of each transformer, inverter, and photovoltaic branch of the photovoltaic power station, and continuously tracks and records the faults. Different weight values ​​are set according to the different degrees of influence of the faulty equipment and fault level on the power generation. The average fault processing time of the photovoltaic power station is calculated accordingly, so as to judge the operation and maintenance quality of the photovoltaic power station. The method does not require the installation of sensors on the photovoltaic power station, and the monitoring range covers all photovoltaic components of the entire power station. The precision can reach the branch level, which is accurate and true, and can fully reflect the actual operation and maintenance efficiency of the power station. It does not require manual assistance, and can efficiently monitor the operation and maintenance quality of all photovoltaic power stations under the group.

[0054] The fault elimination efficiency is used to quantitatively evaluate the fault response speed and processing capabilities of the operation and maintenance team, monitor the efficiency of daily operation and maintenance work, and provide a unified evaluation and comparison standard for the operation and maintenance efficiency of multiple power station operation and maintenance teams under the group, thereby motivating each power station operation and maintenance team to continuously improve and enhance service quality and ensure efficient and safe operation of the power station.

[0055] In a specific embodiment, the fault sensitivity B (B1, B2) is first set through the system background. The real-time status data Si1 (a1, b1, c1...) and power generation data Gi1 of each photovoltaic branch, inverter and box transformer to be detected in the photovoltaic power station are obtained through the photovoltaic operation and maintenance intelligent monitoring box.

[0056] In this embodiment, the real-time status data Si1 (a1, b1, c1...) is compared with the reference status data Si0 (a0, b0, c0...). When a1=a0, it indicates that there is no fault, and when a1≠a0, it indicates that a1 has a fault; when b1=b0, it indicates that there is no fault, and when b1≠b0, it indicates that b1 has a fault; when c1=c0, it indicates that there is no fault, and when c1≠c0, it indicates that c1 has a fault; and so on and so forth, the comparison is performed to obtain the status of the device.

[0057] In this embodiment, the power generation deviation value e after comparing the power generation data of each device with the reference power generation data is determined according to e=(Gi1-Gi0) / Gi0, and the power generation deviation value e is compared with the fault sensitivity B(B1, B2), that is, when e≥B2, it indicates that there is no fault; when B1≤e<B2, it indicates that a level 1 fault occurs; when e<B1, it indicates that a level 2 fault occurs. In this way, the state of the device and the fault level when the device state is a fault are obtained.

[0058] In this embodiment, when the result of comparing the real-time status data Si1 with the reference status data Si0 is a device failure, or when the result of comparing the power generation data Gi1 with the reference power generation data Gi0 is a device failure, the faulty device, fault level, and fault duration are tracked and recorded. The arithmetic mean of all faults of the same level under each device is calculated as the average fault duration of all faults of the same level under the device.

[0059] In this embodiment, based on the faulty device and fault level, the device weighting coefficient A (A1, A2, A3) is set through the system background to adjust the weighted proportion of different devices; the fault level weighting coefficient L (L1, L2) is set to adjust the weighted proportion of different fault levels. According to the device weighting coefficient A and the fault level weighting coefficient L, the fault formula: average processing time T = (average fault time of box transformer level 1 fault * L1 + average fault time of box transformer level 2 fault * L2) * A1 + (average fault time of inverter level 1 fault * L1 + average fault time of inverter level 2 fault * L2) * A2 + (average fault time of branch level 1 fault * L1 + average fault time of branch level 2 fault * L2) * A3 is used to determine the average fault processing time T of the photovoltaic power station.

[0060] In this embodiment, the operation and maintenance level coefficient O (O1, O2, O3, O4) is set through the system background. The average fault processing time T is compared with the operation and maintenance level coefficient O to determine the operation and maintenance quality level of the photovoltaic power station. That is, when T≥O4, it indicates that the operation and maintenance quality level of the photovoltaic power station is level 1; when O3≤T<O4, it indicates that the operation and maintenance quality level of the photovoltaic power station is level 2;

[0061] When O2≤T<O3, it indicates that the operation and maintenance quality level of the photovoltaic power station is level 3; when O1≤T<O2, it indicates that the operation and maintenance quality level of the photovoltaic power station is level 4; when T<O1, it indicates that the operation and maintenance quality level of the photovoltaic power station is level 5. Furthermore, by monitoring the operation and maintenance quality level of the photovoltaic power station, the power station operation and maintenance team is encouraged to continuously improve and enhance the service quality to ensure the efficient and safe operation of the power station.

[0062] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Therefore, any modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention shall still fall within the scope of the technical solution of the present invention.

Claims

1. A photovoltaic power station operation and maintenance quality assessment method based on fault elimination efficiency, characterized in that: The method comprises: S100, obtaining status data Si1 and power generation data Gi1 of each device to be detected in the photovoltaic power station, wherein the device to be detected includes each photovoltaic branch, inverter and box transformer; S200, comparing the acquired state data Si1 and power generation data Gi1 with the reference group data respectively; S300, when the comparison result is a device failure, tracking and recording the failed device, the failure level and the failure duration; S400, assigning different weights based on the faulty equipment and fault level to obtain equipment weighting coefficient A and fault level weighting coefficient L; S500, determining an average fault processing time T of the photovoltaic power station according to the equipment weighting coefficient A and the fault level weighting coefficient L; S600: Compare the average fault processing time T with the operation and maintenance level coefficient O to determine the operation and maintenance quality level of the photovoltaic power station.

2. A photovoltaic power station operation and maintenance quality assessment method based on fault elimination efficiency according to claim 1, characterized in that: The reference group data includes reference state data Si0 and reference power generation data Gi0; The reference state data Si0 is data when the equipment is in normal state; the reference power generation data Gi0 is the average power generation value of all branches of the same type of components in the same area.

3. A photovoltaic power station operation and maintenance quality assessment method based on fault elimination efficiency according to claim 2, characterized in that: S210, determining a power generation deviation value e according to the reference power generation data Gi0 and the power generation data Gi1 of the device to be detected; Among them, e=(Gi1-Gi0) / Gi0.

4. A photovoltaic power station operation and maintenance quality assessment method based on fault elimination efficiency according to claim 3, characterized in that: S220, compare the state data Si1 of the device to be detected with the reference state data Si0 to obtain the state of the device; compare the power generation deviation value e with the fault sensitivity B to obtain the state of the device and the fault level when the device state is a fault.

5. A photovoltaic power station operation and maintenance quality assessment method based on fault elimination efficiency according to claim 1, characterized in that: The equipment weighting coefficient A includes a first equipment weighting coefficient A1, a second equipment weighting coefficient A2 and a third equipment weighting coefficient A3; The fault level weighting coefficient L includes a first fault level weighting coefficient L1 and a second fault level weighting coefficient L2; Among them, A1+A2+A3=1; L1+L2=1.

6. A photovoltaic power station operation and maintenance quality assessment method based on fault elimination efficiency according to claim 5, characterized in that: The average fault processing time T = (average fault time of box transformer level 1 fault * L1 + average fault time of box transformer level 2 fault * L2) * A1 + (average fault time of inverter level 1 fault * L1 + average fault time of inverter level 2 fault * L2) * A2 + (average fault time of branch level 1 fault * L1 + average fault time of branch level 2 fault * L2) * A3; The average fault duration is the arithmetic mean of all faults of this level under the device.

7. A photovoltaic power station operation and maintenance quality assessment method based on fault elimination efficiency according to claim 1, characterized in that: The operation and maintenance level coefficient O includes a first operation and maintenance level coefficient O1, a second operation and maintenance level coefficient O2, a third operation and maintenance level coefficient O3 and a fourth operation and maintenance level coefficient O4.

8. A photovoltaic power station operation and maintenance quality assessment method based on fault elimination efficiency according to claim 7, characterized in that: S610, when T≥O4, the operation and maintenance quality level of the photovoltaic power station is level 1; When O3≤T<O4, the operation and maintenance quality level of the photovoltaic power station is level 2; When O2≤T<O3, the operation and maintenance quality level of the photovoltaic power station is level 3; When O1≤T<O2, the operation and maintenance quality level of the photovoltaic power station is level 4; When T<O1, the operation and maintenance quality level of the photovoltaic power station is level 5.

9. A photovoltaic power station operation and maintenance quality assessment device based on fault elimination efficiency, the photovoltaic power station operation and maintenance quality assessment device based on fault elimination efficiency is used to implement the photovoltaic power station operation and maintenance quality assessment method based on fault elimination efficiency according to any one of claims 1 to 8, characterized in that: The device comprises: Photovoltaic operation and maintenance intelligent monitoring box and configuration system.

10. A photovoltaic power station operation and maintenance quality assessment device based on fault elimination efficiency according to claim 9, characterized in that: The photovoltaic operation and maintenance intelligent monitoring box is used to detect the status of each device in the photovoltaic power station and evaluate the operation and maintenance quality of the photovoltaic power station; The configuration system is used to set the fault sensitivity B, the equipment weighting coefficient A, the fault level weighting coefficient L and the operation and maintenance level coefficient O.

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