CN113922758A - A photovoltaic module fault diagnosis and identification system and method for mine management - Google Patents

A photovoltaic module fault diagnosis and identification system and method for mine management Download PDF

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CN113922758A
CN113922758A CN202111167692.5A CN202111167692A CN113922758A CN 113922758 A CN113922758 A CN 113922758A CN 202111167692 A CN202111167692 A CN 202111167692A CN 113922758 A CN113922758 A CN 113922758A
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fault
photovoltaic module
module
photovoltaic
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安爱民
赵莹莹
王茜茜
陈铜川
周妍
陈伟
徐逸凡
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Lanzhou University of Technology
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02S—GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRARED RADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, e.g. USING PHOTOVOLTAIC [PV] MODULES
    • H02S50/00—Monitoring or testing of PV systems, e.g. load balancing or fault identification
    • H02S50/10—Testing of PV devices, e.g. of PV modules or single PV cells
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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    • Y02E10/50—Photovoltaic [PV] energy

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Abstract

The invention discloses a photovoltaic module fault diagnosis and identification system and method for mine management. The invention comprises a preliminary fault early warning unit, a fault diagnosis unit and a fault type identification unit; firstly, according to the standard operation condition of the photovoltaic module and real-time operation data under the fault, preliminarily predicting the fault condition of the photovoltaic module and sending out an early warning prompt; secondly, starting a fault diagnosis unit to compare and analyze the real-time generating energy efficiency value with the generating energy efficiency average value of the previous day, judging whether the photovoltaic module has a fault or not and sending a signal to a fault type identification unit; and finally, analyzing the fault type by using a fault type identification unit, determining the detailed system fault type, and simultaneously informing personnel to prepare and overhaul. The invention accurately judges the fault and identifies the detailed system fault type through real-time running data, is convenient for maintenance personnel to make overhaul preparation in advance, has the advantages of high diagnosis efficiency and accurate identification result, and has important significance for the green development of intelligent mines in China.

Description

Photovoltaic module fault diagnosis and identification system and method for mine management
Technical Field
The invention relates to the technical field of photovoltaic module fault diagnosis, in particular to a photovoltaic module fault diagnosis and identification system and method for mine management.
Background
With the rapid development of the mining technology from mechanization-digital informatization-intellectualization, in order to build a modern mining industrial system which is economical, safe, efficient and green, the mine must face green development transformation, gradually realize green income and 'unmanned' treatment, and apply the existing zero-carbon energy power generation technology-photovoltaic to the intelligent mine treatment process. In 2020, the double-carbon targets of carbon peak reaching and carbon neutralization are provided in China, so that the decision of realizing low-carbon energy transformation and protecting the ecological environment in China is shown, and the vigorous development of photovoltaic power generation is also promoted to be inevitable. The photovoltaic and intelligent mine green treatment is the most friendly solution for comprehensively treating mines at the current stage, and has important significance for energy safety, economic transformation and ecological civilization of modern mine industrial systems in China.
Because the photovoltaic module is to operate in the open mine environment for a long time, the power generation performance of the photovoltaic module is greatly influenced by external environmental factors, especially the influence of solar irradiance, ambient temperature, dust and grid-connected faults is obvious, faults such as model aging, module shadow shielding, photovoltaic module connection error and hot spot effect are easy to occur, the power generation efficiency of the system is reduced, and a great deal of inconvenience is brought in the intelligent mine treatment process.
At present, when a photovoltaic module breaks down, the system cannot automatically diagnose and identify the faults, manual work is needed to go to a mine site for troubleshooting and finding fault positions, but a large-scale mine-photovoltaic power generation system only depends on manual troubleshooting to locate the faults of the photovoltaic module and maintain the faults, so that time is wasted, and efficiency is low. Therefore, the method for solving the problems of fault diagnosis and identification of the photovoltaic module applied to mine management by adopting the artificial intelligence technical method has important practical significance and wide application prospect.
Disclosure of Invention
The invention aims to provide a photovoltaic module fault diagnosis and identification system applied to intelligent mine green treatment, and the invention also aims to provide a photovoltaic module fault diagnosis and identification method applied to green mine treatment; in order to solve prior art down, photovoltaic module is through artifical when detecting, troubleshooting, inefficiency, the precision is poor, the trouble type is unclear and artifical maintenance cost is high problem.
In order to achieve the purpose, the photovoltaic module fault diagnosis and identification system applied to intelligent mine green management comprises a primary fault early warning unit, a fault diagnosis unit and a fault type identification unit; the preliminary fault early warning unit, the fault diagnosis unit and the fault type identification unit are electrically connected in sequence.
The invention relates to a photovoltaic module fault diagnosis and identification method applied to intelligent mine green management, which comprises the following steps:
the preliminary fault early warning unit preliminarily predicts the fault condition of the photovoltaic module and sends an early warning prompt by detecting data under the standard operation condition of the photovoltaic module and real-time operation data when the fault occurs and comparing the difference between the data and the preset difference value;
after the fault diagnosis unit receives the early warning signal sent by the preliminary fault early warning unit, the fault diagnosis system is triggered to formally start the fault diagnosis unit, and the fault diagnosis unit is used for confirming and judging the fault condition of each photovoltaic assembly;
the fault type identification unit starts the fault type identification unit according to the trigger signal; the fault type identification unit is an external fault and a system fault, and the external fault refers to shadow shielding; the system failure comprises: component connection failure, bypass diode failure, component or line aging, grid failure.
The operation steps of the preliminary fault early warning unit are as follows:
1) comparing the standard operation data with the real-time operation data of each photovoltaic module, performing preliminary fault diagnosis on each photovoltaic module, and performing difference processing on the standard operation data and the real-time operation data of each photovoltaic module to obtain operation difference value information;
2) according to the operation difference value information and the preset difference value range information, performing primary fault diagnosis on each photovoltaic module; when the difference value corresponding to the operation difference value information exceeds the preset difference value range information through comparison, the photovoltaic module is preliminarily judged to be in fault;
the step of obtaining the operation difference value information by performing difference processing on the standard operation data and the real-time operation data of each photovoltaic module specifically comprises the following steps:
according to the identification information of the photovoltaic modules, carrying out difference processing on the real-time operation data and the standard operation data of each photovoltaic module to obtain operation difference value information corresponding to each photovoltaic module;
the operation of the preliminary fault early warning unit comprises the following specific steps:
(1) firstly, detecting parameters (such as irradiance information, voltage information and current information) of a photovoltaic assembly in a photovoltaic power station in standard operation, and acquiring data in the standard operation for later use; secondly, detecting target operation parameters of each photovoltaic module in the photovoltaic power station to obtain real-time operation data of each photovoltaic module; and finally, performing fault prejudgment on each photovoltaic module according to the standard operation data and the real-time operation data of each photovoltaic module.
(2) And calculating difference of the two data parameters by actually detecting standard operation data of a certain time point and real-time operation data of the photovoltaic module to obtain operation difference information. And performing primary fault diagnosis on each photovoltaic module according to the operation difference value information and the preset difference value range information.
(3) If the difference value corresponding to the operation difference value information obtained through comparison exceeds the preset difference value range information, the photovoltaic module is preliminarily judged to be in fault, and a fault early warning prompt is sent out.
The fault diagnosis unit comprises a data processing module, a data analysis module and a diagnosis module which are electrically connected in sequence; the fault diagnosis unit operates as follows:
1) sending the result of the data processing module to a data analysis module, and sending the real-time generating energy effective value EnAverage value of power generation energy efficiency of previous day
Figure BDA0003292090960000034
Carrying out comparative analysis;
when the real-time power generation effective value EnAverage value of power generation energy efficiency of more than one day before
Figure BDA0003292090960000035
And 20% of the total number of the faults, the power station monitors and records the frequency of the situation, and the frequency recorded by the diagnosis module accounts for more than 5% of the total number of the faults in comparison, and then the lower-level fault type identification unit is triggered.
The operation of the fault diagnosis unit comprises the following specific steps:
according to the detected photovoltaic module data information, calculating a real-time power generation energy efficiency value E of the photovoltaic modulenAnd daily average value E of power generation energy efficiencyAVGAnd the real-time power generation energy efficiency value E is calculatednAverage value E of power generation energy efficiency of previous dayAVGAnd analyzing and comparing to formally determine that the photovoltaic module breaks down and remind system operation and maintenance personnel to rush to the power station for maintenance. The fault diagnosis unit comprises a data processing module, a data analysis module and a diagnosis module.
(1) The data processing module is used for receiving the fed back data information, performing calculation processing and calculating the real-time power generation effective value E of the photovoltaic modulenAnd the average value E of the power generation energy efficiency of each dayAVG(ii) a And calculating the real-time generating energy effective value EnAnd daily average value E of power generation efficiencyAVGAnd feeding back to the data analysis module.
(2) The data analysis module is used for receiving the real-time generating energy effective value EnAnd the average value E of the power generation energy efficiency of each dayAVG(ii) a The real-time generating energy effective value EnAverage value of power generation energy efficiency of previous day
Figure BDA0003292090960000031
Performing comparative analysis to record the times of meeting the preset condition value, and if the recorded times of meeting the preset condition value account for more than 5% of the total times, triggering a signal to the diagnosis module;
(3) diagnostic module for performingEnergy efficiency value E of time-varying power generationnAverage value of power generation energy efficiency of previous day
Figure BDA0003292090960000032
And determining whether to trigger the next-stage fault type identification unit or not according to the comparison result. In particular, if the energy efficiency value E of the power generation is real-timenAverage value of effective values of generated power calculated more than one day before
Figure BDA0003292090960000033
And 20% or more, the power station monitors and records the frequency of the situation, if the frequency accounts for 5% of the total frequency (namely when A is 1), the power station triggers a next-level signal, and timely reminds system operation and maintenance personnel to rush to the site for maintenance.
The data processing module comprises the following operation steps:
1) firstly, an irradiance sensor, a current sensor and a voltage sensor are needed to respectively monitor outdoor irradiance information S in real timenInformation of current InVoltage information Un；
2) And then processing the monitored data, wherein the real-time power generation energy efficiency value E of the photovoltaic modulenThe formula of (1) is: en＝Sn/(InUn) And n is the acquisition frequency of the data acquisition module.
The data analysis module specifically comprises the following operation steps:
3) comparing and analyzing the data information acquired in real time with a preset theoretical value;
4) when any one of irradiance information, current information and voltage information exceeds the preset theoretical value and the accumulated ratio of times exceeds 5% of the total times, the fault is diagnosed and the next-stage signal is triggered.
The fault type identification unit comprises an external shielding object interference elimination module, a system fault type identification module and a notification maintenance module which are electrically connected in sequence; the operation steps of the fault type identification unit are as follows:
step 1: excluded external obstruction interference module: judging whether the system fault is caused by a fixed shelter or not, if so, not processing the system fault, and removing the alarm; otherwise, entering step2, and judging the specific system fault type;
step 2: a system fault type identification module: system failures are divided into: the method comprises the following steps of (1) carrying out comparison and judgment on component connection errors, component diode bypasses, component or line ageing and power grid faults one by one to determine the type of system faults;
and step 3: notify and overhaul the module: after the specific fault type is determined, the maintenance personnel is informed in detail again to make maintenance preparation work, and the fault is solved in time.
The step1 comprises the following steps:
(1) calling current I, voltage U and temperature data of each string of photovoltaic modules in the photovoltaic array for nearly 3 days, and calculating fault judgment factors of abnormal strings of data according to the current and the voltage at the maximum power point of a single string of photovoltaic modules:
Figure BDA0003292090960000041
current fault determination factor threshold mu from abnormal string1Sum voltage failure determination threshold σ1If EIi＜μ1，EVi＜σ1If so, indicating that the system may have an external obstruction, and continuing further determination;
(2) the method comprises the steps of calculating the shadow area of a fixed shelter under sunlight according to the volume of the fixed shelter and the incident angle of sunlight by a mathematical method, covering a photovoltaic module by the calculated shadow area at a certain moment, measuring that the current of a string where the photovoltaic module is covered is reduced compared with the current under the normal working condition, namely judging that the system fault is caused by the shadow of the fixed shelter and is not used as a fault of the system, and automatically removing the alarm by the system.
The step2 comprises the following steps:
(1) defining current and voltage judgment factors when a photovoltaic assembly in a system has a fault:
Figure BDA0003292090960000051
Figure BDA0003292090960000052
Imand VmRespectively measuring the total current and the total voltage at the maximum power point of the photovoltaic array by the system;
Figure BDA0003292090960000053
and
Figure BDA0003292090960000054
the short-circuit current and the open-circuit voltage of the photovoltaic system are respectively calculated according to the following specific calculation formula:
Figure BDA0003292090960000055
(2) fault determination factor threshold F when open circuit fault of photovoltaic module exists in computing systemc1: when a certain photovoltaic module is in an open circuit state, the output current generated by the photovoltaic module is equivalent to the current generated by the wrong connection of the photovoltaic modules connected in series,
Figure BDA0003292090960000056
wherein
Figure BDA0003292090960000057
Fc1As a threshold for determining an open circuit of a single string of photovoltaic modules, Im0The current of the maximum power point of a single photovoltaic module is represented by the formula
Figure BDA0003292090960000058
Obtaining;
(3) fault determination factor threshold F when bypass fault of photovoltaic module exists in computing systemv1：
Figure BDA0003292090960000059
Wherein
Figure BDA00032920909600000510
Fv1As a threshold value for determining the bypassed state of an open circuit of a single string of photovoltaic modules, Vm0Voltage of maximum power point of single photovoltaic module is represented by formula
Figure BDA00032920909600000511
Obtaining;
(4) and (3) comparison and judgment: under normal operating conditions: fc＞Fc1,Fv＞Fv1(ii) a When F is presentc≤Fc1Or Fv≤Fv1When the current photovoltaic module fails, the corresponding failure type is shown as the following formula:
Figure BDA0003292090960000061
the invention relates to a photovoltaic module fault diagnosis and identification system and method for mine management, which have the beneficial effects that: through this application photovoltaic module fault diagnosis and identification system can judge the trouble and the trouble type of analysis subassembly certainly, improve the efficiency of fault diagnosis and maintenance, have that the diagnosis precision is high, the reliable advantage of identification result, bring positive effectual impetus to the green improvement in wisdom mine.
Drawings
FIG. 1 is a diagram of a photovoltaic module fault diagnosis and identification system applied to green management of smart mines;
FIG. 2 is a flow chart of a fault diagnosis unit;
FIG. 3 is a flow chart of a fault type discrimination unit;
fig. 4 shows the diagnostic results of simulation under four common fault types.
Detailed Description
Example 1
The invention relates to a photovoltaic module fault diagnosis and identification system and method for mine management, as shown in figure 1, comprising a preliminary fault early warning unit, a fault diagnosis unit and a fault type identification unit; the preliminary fault early warning unit, the fault diagnosis unit and the fault type identification unit are electrically connected in sequence;
preliminary trouble early warning unit 1 for data and the real-time operating data when the trouble takes place under the detection photovoltaic module standard operation condition, make the difference and predetermine the difference and compare to both, preliminary prediction photovoltaic module's the trouble condition and send out the early warning suggestion, concrete step is as follows:
step 1: firstly, detecting parameters (such as irradiance information, voltage information and current information) of a photovoltaic module which is operated in a standard mode in a photovoltaic power station of an intelligent mine, and acquiring data of the standard operation for later use; secondly, detecting target operation parameters of each photovoltaic module in the photovoltaic power station to obtain real-time operation data of each photovoltaic module; finally, performing fault prejudgment on each photovoltaic module according to the standard operation data and the real-time operation data of each photovoltaic module;
step 2: the method comprises the steps that standard operation data at a certain time point and real-time operation data of a photovoltaic module are actually detected, and difference processing is carried out on two data parameters to obtain operation difference value information; according to the operation difference value information and the preset difference value range information, performing primary fault diagnosis on each photovoltaic module;
step 3: if the difference value corresponding to the operation difference value information obtained through comparison exceeds the preset difference value range information, the photovoltaic module is preliminarily judged to be in fault, and a fault early warning prompt is sent out;
after receiving the early warning signal sent by the preliminary fault early warning unit, the fault diagnosis unit 2 triggers a fault diagnosis system to formally start the fault diagnosis unit, and is used for confirming and judging the fault condition of each photovoltaic module; the method comprises the following specific steps:
calculating the real-time power generation energy efficiency value E of the photovoltaic module according to the detected data information of the photovoltaic modulenAnd daily average value E of power generation energy efficiencyAVGAnd the real-time power generation energy efficiency value E is calculatednAverage value E of power generation energy efficiency of previous dayAVGAnalyzing and comparing to formally determine that the photovoltaic module breaks down and remind system operation and maintenance personnel to rush to the power station for maintenance; the fault diagnosis unit comprises a data processing moduleThe data analysis module and the diagnosis module;
step 4: wherein, the data processing module 21 is configured to receive the fed back data information, perform calculation processing, and calculate a real-time power generation effective value E of the photovoltaic modulenAnd the average value E of the power generation energy efficiency of each dayAVG(ii) a And calculating the real-time generating energy effective value EnAnd daily average value E of power generation efficiencyAVGFeeding back to the data analysis module; real-time generating energy effective value E of photovoltaic modulenAnd the average value E of the daily power generation energy efficiency valueAVGThe calculation formula (2) is shown in the following formula (1):
Figure BDA0003292090960000071
in the formula, SnSampling the outdoor irradiance for the nth time; i isnSampling the current of the photovoltaic module for the nth time; u shapenSampling the voltage of the photovoltaic module for the nth time; where n is the number of acquisitions, n is 1440 minutes per acquisition interval (minutes), where acquisition occurs every 10 minutes, and n is 144;
step 5: the data analysis module 22 is used for receiving the real-time generating effective value EnAnd the average value E of the power generation energy efficiency of each dayAVG(ii) a The real-time generating energy effective value EnAverage value of power generation energy efficiency of previous day
Figure BDA0003292090960000074
Performing comparative analysis to record the times of meeting the preset condition value, and if the recorded times of meeting the preset condition value account for more than 5% of the total times, triggering a signal to the diagnosis module;
specifically, in this embodiment, the preset condition values are: if the real-time power generation energy efficiency value EnAverage value of effective values of generated power calculated more than one day before
Figure BDA0003292090960000072
When the number of times exceeds 20% or more, the number of times is monitored and recorded, and if the number of times exceeds 5% of the total number of times (i.e., when A is 1), the number of times is countedSending a signal to a diagnosis module to remind system maintenance personnel to rush to the site for maintenance in time; if the number of times is less than 5% of the total number of times (namely when A is 0), the average value of the effective values of the generated power of the photovoltaic modules monitored in real time on the same day is compared
Figure BDA0003292090960000073
Updating to the reference value of the next day; specifically, the following formula (2) is shown;
Figure BDA0003292090960000081
in the formula (I), the compound is shown in the specification,
Figure BDA0003292090960000082
calculating the average value of the generating energy effective values of the photovoltaic modules for the previous day;
Figure BDA0003292090960000083
calculating the average value of the generating energy effective values of the photovoltaic modules for the same day; enCalculating a real-time power generation energy efficiency value of the photovoltaic module for the nth sampling in the same day, wherein n is 144; a is 1, and A is 0 and corresponds to the starting and the shutting of the photovoltaic module diagnosis module respectively;
step 6: a diagnosis module 23 for generating an effective value E according to the real-time powernAverage value of power generation energy efficiency of previous day
Figure BDA0003292090960000084
Determining whether to trigger a next-stage fault type identification unit or not according to the comparison result;
in particular, if the energy efficiency value E of the power generation is real-timenAverage value of effective values of generated power calculated more than one day before
Figure BDA0003292090960000085
If the number of times exceeds 5% of the total number of times (namely when A is 1), the power station triggers a next-level signal and timely reminds system operation and maintenance personnel to rush to the site for maintenance;
the fault type identification unit 3 starts the fault type identification unit according to the trigger signal, and general fault types are divided into external faults and system faults, wherein the external faults refer to shadow shielding and the like; the system failure comprises: component connection faults, bypass diode faults, component or line aging, grid faults, and the like;
firstly, judging whether the shadow shielding condition exists according to the measurement data, and identifying the type of system fault after eliminating the external fault; the method comprises the following specific steps:
step 7: excluded from the obstruction interference module 31: judging whether the system fault is caused by a fixed shelter or not, if so, not processing the system fault, and removing the alarm; otherwise, entering step2, and judging the specific fault type;
step 8: system fault type discrimination module 32: system failures are divided into: the method comprises the following steps of comparing and judging three types of component connection errors, component bypass, aging and power grid errors one by one, and classifying system faults;
the specific method of excluding the external blocking object interference module 31 is as follows:
(1) calling current I, voltage U, temperature data and the like of each string of photovoltaic modules in the photovoltaic array for nearly 3 days, and calculating fault judgment factors of abnormal strings of data according to the current and the voltage at the maximum power point of a single string of photovoltaic modules:
Figure BDA0003292090960000091
in the formula IimThe measured current of each string of photovoltaic components; i isim2For each string of photovoltaic elements, specifically Iim2＝k1×Isc；VimThe measured voltage of each string of photovoltaic components; vim2For each string of photovoltaic modules, a theoretical voltage, in particular Vim2＝k2×Ns×Voc＝Vm1(ii) a Wherein: k is a radical of1The current proportionality constant is determined by the photovoltaic module, and the value range is as follows: 0.78-0.92; k is a radical of2Is a voltage ratioThe constant is specifically determined by the photovoltaic module, and the value range is as follows: 0.71-0.78; n is a radical ofsThe number of the photovoltaic modules connected in series in the photovoltaic array is; i isscShort-circuit current of a single photovoltaic component under the current irradiance and temperature conditions; vocThe open-circuit voltage of a single photovoltaic module under the current irradiance and temperature conditions;
current fault determination factor threshold mu from abnormal string1Sum voltage failure determination threshold σ1If EIi＜μ1，EVi＜σ1If so, the system is judged to have the external obstruction possibly, and the next judgment is carried out;
(2) calculating the shadow area of the fixed shelter under the sunlight according to the volume of the fixed shelter and the incident angle of the sunlight by a mathematical method, wherein if the calculated shadow area can cover the photovoltaic module at a certain moment, and the current of the string where the shielded photovoltaic module is located is measured to be reduced compared with the current under the normal working condition, namely the system fault is judged to be caused by the shadow of the fixed shelter and not taken as a fault of the system, and the system automatically releases the alarm;
the detailed steps of the system fault type identification module 32 are as follows:
(1) defining current and voltage judgment factors when a photovoltaic assembly in a system has a fault:
Figure BDA0003292090960000093
Figure BDA0003292090960000094
Imand VmRespectively measuring the total current and the total voltage at the maximum power point of the photovoltaic array by the system;
Figure BDA0003292090960000095
and
Figure BDA0003292090960000096
the short-circuit current and the open-circuit voltage of the photovoltaic system are respectively represented by the following specific calculation formula (4):
Figure BDA0003292090960000092
in the formula ISC,refThe short-circuit current of the photovoltaic module under the standard test condition is shown; a is the short-circuit current temperature coefficient of the photovoltaic module; t isrefIs the temperature, T, at which the photovoltaic module operates under standard test conditionsrefSetting the temperature at 25 ℃; t is the working temperature of the photovoltaic module at the current moment; voc,refThe open circuit voltage of the photovoltaic module under the standard test condition; alpha is an irradiance correction coefficient of the open-circuit voltage; beta is the open-circuit voltage temperature coefficient of the photovoltaic module; s is coplanar irradiance of the photovoltaic module at the current moment; srefThe coplanar irradiance of the photovoltaic component under the standard test condition is 1000W/m2；
(2) Fault determination factor threshold F when open circuit fault of photovoltaic module exists in computing systemc1: when a certain photovoltaic module is in an open circuit state, the output current generated by the photovoltaic module is equivalent to the current generated by the wrong connection of the photovoltaic modules connected in series,
Figure BDA0003292090960000101
wherein
Figure BDA0003292090960000102
Fc1As a threshold for determining an open circuit of a single string of photovoltaic modules, Im0The current of the maximum power point of a single photovoltaic module is represented by the formula
Figure BDA0003292090960000103
Obtaining;
(3) fault determination factor threshold F when bypass fault of photovoltaic module exists in computing systemv1：
Figure BDA0003292090960000104
Wherein
Figure BDA0003292090960000105
Fv1As a threshold value for determining the bypassed state of an open circuit of a single string of photovoltaic modules, Vm0As a single lightVoltage of maximum power point of the voltage component, from formula
Figure BDA0003292090960000106
Obtaining;
(4) and (3) comparison and judgment: under normal operating conditions: fc＞Fc1,Fv＞Fv1(ii) a When F is presentc≤Fc1Or Fv≤Fv1When the current photovoltaic module fails, the corresponding failure type is shown as a formula (5);
Figure BDA0003292090960000107
step 9: signaling and notification maintenance module 33: and after the specific fault type is determined, informing maintenance personnel in detail again to prepare maintenance work, sending a fault signal to mine photovoltaic power station workers, and informing the maintenance personnel to check and maintain in time.
Step 10: 4 common fault types including component connection error, component diode bypass, line aging and three-phase short circuit fault of a power grid are simulated, voltage and active power output by the photovoltaic component are collected and plotted to detect the effectiveness of fault diagnosis of the photovoltaic system, and the effectiveness of the diagnosis system is found through the curve.

Claims (8)

1.一种用于矿山治理的光伏组件故障诊断与鉴别系统，其特征在于：包括初步故障预警单元、故障诊断单元、故障类型鉴别单元；所述初步故障预警单元、故障诊断单元、故障类型鉴别单元依次电性连接；1. A photovoltaic module fault diagnosis and identification system for mine management, characterized in that: comprising a preliminary fault warning unit, a fault diagnosis unit, and a fault type identification unit; the preliminary fault early warning unit, a fault diagnosis unit, and a fault type identification unit The units are electrically connected in sequence; 所述初步故障预警单元，通过检测光伏组件标准运行情况下的数据以及故障发生时的实时运行数据，对两者作差与预设差值比较，初步预测光伏组件的故障情况并发出预警提示；The preliminary fault early warning unit, by detecting the data under the standard operating conditions of the photovoltaic modules and the real-time operating data when the fault occurs, compares the difference between the two with the preset difference, preliminarily predicts the fault of the photovoltaic module and issues an early warning prompt; 所述故障诊断单元，在接收到初步故障预警单元发出的预警信号后，故障诊断系统被触发，正式启动故障诊断单元，用于确认并判定各光伏组件的故障情况；The fault diagnosis unit, after receiving the early warning signal sent by the preliminary fault early warning unit, the fault diagnosis system is triggered, and the fault diagnosis unit is officially activated to confirm and determine the fault condition of each photovoltaic module; 所述故障类型鉴别单元，根据上述触发信号启动故障类型鉴别单元；所述故障类型鉴别单元为外在故障与系统故障，所述外在故障指阴影物遮挡；所述系统故障包括：组件连接故障、旁路二极管故障、组件或者线路老化、电网故障。The fault type identification unit starts the fault type identification unit according to the above trigger signal; the fault type identification unit is an external fault and a system fault, and the external fault refers to the occlusion of a shadow; the system fault includes: component connection faults , Bypass diode failure, component or line aging, grid failure. 2.如权利要求1所述一种用于矿山治理的光伏组件故障诊断与鉴别系统，其特征在于：2. A kind of photovoltaic module fault diagnosis and identification system for mine management as claimed in claim 1, is characterized in that: 所述初步故障预警单元运行步骤如下：The operation steps of the preliminary fault warning unit are as follows: 1)比较标准运行数据和各光伏组件的实时运行数据，对各光伏组件进行初步故障诊断，对标准运行数据和各光伏组件的实时运行数据进行求差处理，获取运行差值信息；1) Compare the standard operation data and the real-time operation data of each photovoltaic module, conduct preliminary fault diagnosis for each photovoltaic module, and perform difference processing between the standard operation data and the real-time operation data of each photovoltaic module, and obtain the operation difference information; 2)根据运行差值信息和预设差值范围信息，对各光伏组件进行初步故障诊断；当对比获知运行差值信息对应的差值超出预设差值范围信息，则初步判定光伏组件发生故障；2) Perform preliminary fault diagnosis for each photovoltaic module according to the operating difference information and the preset difference range information; when the difference corresponding to the operating difference information exceeds the preset difference range information, it is preliminarily determined that the photovoltaic module is faulty ; 对标准运行数据和各光伏组件的实时运行数据进行求差处理，获取运行差值信息的步骤具体包括：The standard operation data and the real-time operation data of each photovoltaic module are processed to obtain the difference, and the steps of obtaining the operation difference information include: 根据光伏组件的标识信息，将各光伏组件的实时运行数据与标准运行数据进行求差处理，获取各光伏组件对应的运行差值信息。According to the identification information of the photovoltaic modules, the difference processing is performed between the real-time operation data of each photovoltaic module and the standard operation data, and the operation difference information corresponding to each photovoltaic module is obtained. 3.如权利要求2所述一种用于矿山治理的光伏组件故障诊断与鉴别系统，其特征在于：所述故障诊断单元包括顺次电性连接的数据处理模块、数据分析模块、诊断模块；所述故障诊断单元运行步骤如下：3. A photovoltaic module fault diagnosis and identification system for mine management according to claim 2, wherein the fault diagnosis unit comprises a data processing module, a data analysis module and a diagnosis module that are electrically connected in sequence; The operation steps of the fault diagnosis unit are as follows: 1)将数据处理模块的结果发送到数据分析模块，将所述实时发电能效值En与前一天的发电能效平均值
Figure FDA0003292090950000021
进行对比分析；1) Send the result of the data processing module to the data analysis module, and compare the real-time power generation energy efficiency value En and the average power generation energy efficiency of the previous day
Figure FDA0003292090950000021
carry out comparative analysis; 当实时发电能效值En超过前一天的发电能效平均值
Figure FDA0003292090950000022
的20％，则电站监测并记录此种情形次数，诊断模块记录的次数占比超过对比总次数的5％，则触发下级故障类型鉴别单元。When the real-time power generation energy efficiency value En exceeds the average value of the power generation energy efficiency of the previous day
Figure FDA0003292090950000022
20%, the power station monitors and records the number of times of this situation, and the number of times recorded by the diagnostic module exceeds 5% of the total number of comparisons, triggering the lower-level fault type identification unit. 4.如权利要求1所述一种用于矿山治理的光伏组件故障诊断与鉴别系统，其特征在于：所述数据处理模块运行步骤如下：4. A photovoltaic module fault diagnosis and identification system for mine management as claimed in claim 1, characterized in that: the operation steps of the data processing module are as follows: 1)首先需要辐照度传感器、电流传感器以及电压传感器，分别实时监测室外辐照度信息Sn，电流信息In，电压信息Un；1) First, an irradiance sensor, a current sensor and a voltage sensor are required to monitor the outdoor irradiance information Sn , the current information In, and the voltage information Un in real time respectively ; 2)然后对监测到的数据进行处理，所述光伏组件的实时的发电能效值En的公式为：En＝Sn/(InUn)，其中n为数据采集模块的采集次数。2) Then process the monitored data. The formula of the real-time power generation energy efficiency value En of the photovoltaic module is: En =S n /(I n U n ), where n is the collection times of the data collection module. 5.如权利要求1所述一种用于矿山治理的光伏组件故障诊断与鉴别系统，其特征在于：5. A photovoltaic module fault diagnosis and identification system for mine management as claimed in claim 1, characterized in that: 所述数据分析模块运行步骤如下：The operation steps of the data analysis module are as follows: 1)将实时采集的数据信息与预设的理论值进行对比分析；1) Compare and analyze the data information collected in real time with the preset theoretical value; 2)当辐照度信息、电流信息、电压信息中的任意一项信息超过所述预设的理论值且次数累计占比超过总次数的5％，则诊断故障，触发下一级信号。2) When any one of the irradiance information, current information and voltage information exceeds the preset theoretical value and the cumulative number of times exceeds 5% of the total number of times, the fault is diagnosed and the next level signal is triggered. 6.如权利要求1所述一种用于矿山治理的光伏组件故障诊断与鉴别系统，其特征在于：所述故障类型鉴别单元包括依次电性连接的排除外在遮挡物干扰模块、系统故障类型鉴别模块、通知检修模块；所述故障类型鉴别单元运行步骤如下：6. A photovoltaic module fault diagnosis and identification system for mine management according to claim 1, characterized in that: the fault type identification unit comprises a module for eliminating interference from external obstructions and a system fault type that are electrically connected in sequence. Identification module, notification maintenance module; the operation steps of the fault type identification unit are as follows: 步骤1：排除外在遮挡物干扰模块：判定系统故障是否由固定遮挡物引起，若是由固定遮挡物引起，则不作为系统故障处理，解除警报；否则进入步骤2，作具体的系统故障类型判定；Step 1: Exclude external obstruction interference module: determine whether the system failure is caused by a fixed obstruction, if it is caused by a fixed obstruction, it will not be treated as a system failure, and the alarm will be lifted; otherwise, go to Step 2 to determine the specific system failure type ; 步骤2：系统故障类型鉴别模块：将系统故障分为：组件连接错误，组件二极管旁路、组件或线路老化、电网故障，逐一比较判定，确定系统故障的类型；Step 2: System fault type identification module: divide the system faults into: component connection error, component diode bypass, component or line aging, power grid fault, compare and determine one by one, and determine the type of system fault; 步骤3：通知检修模块模块：在确定了具体的故障类型后，再次详细通知维修人员以做好维修准备工作，及时解决故障。Step 3: Notify the maintenance module module: After determining the specific fault type, notify the maintenance personnel in detail again to prepare for maintenance and solve the fault in time. 7.如权利要求6所述一种用于矿山治理的光伏组件故障诊断与鉴别系统，其特征在于：7. A photovoltaic module fault diagnosis and identification system for mine management as claimed in claim 6, characterized in that: 所述步骤1，包括以下步骤：The step 1 includes the following steps: (1)调用光伏阵列中各串光伏组件近3天的电流I、电压U、温度数据，根据单串光伏组件最大功率点处的电流、电压，计算数据出现异常串的故障判定因子：(1) Call the current I, voltage U, and temperature data of each string of photovoltaic modules in the photovoltaic array for the past 3 days, and calculate the fault determination factor for abnormal strings according to the current and voltage at the maximum power point of a single string of photovoltaic modules:
Figure FDA0003292090950000031
Figure FDA0003292090950000031
 根据异常串的电流故障判定因子阈值μ1和电压故障判定阈值σ1，若EIi＜μ1，EVi＜σ1，则说明系统可能存在外在的遮挡物，继续进一步的判定；According to the current fault judgment factor threshold μ 1 and the voltage fault judgment threshold σ 1 of the abnormal string, if EI i < μ 1 and EV i <σ 1 , it means that there may be external obstructions in the system, and further judgment is continued; (2)依靠数学方法，根据固定遮挡物的体积和太阳光的入射角，计算固定遮挡物在阳光下的阴影面积，若某一时刻，计算出来的阴影面积能够遮住光伏组件，并且测得被遮挡光伏组件所在串的电流与正常工作情况下的电流相比减小，即判定此系统故障为固定遮挡物阴影所致，不作为系统的一种故障，系统将自动解除警报。(2) Relying on mathematical methods, according to the volume of the fixed shelter and the incident angle of sunlight, calculate the shadow area of the fixed shelter under the sun, if at a certain moment, the calculated shadow area can cover the photovoltaic module, and the measured The current of the string where the shaded PV modules are located is reduced compared with the current under normal working conditions, that is, it is determined that the system failure is caused by the shadow of the fixed shade, and it is not a fault of the system, and the system will automatically cancel the alarm. 8.如权利要求6或7所述一种用于矿山治理的光伏组件故障诊断与鉴别系统，其特征在于：所述步骤2，包括以下步骤：8. A photovoltaic module fault diagnosis and identification system for mine treatment according to claim 6 or 7, wherein the step 2 comprises the following steps: (1)定义系统中光伏组件存在故障时的电流、电压判定因子：
Figure FDA0003292090950000032
Figure FDA0003292090950000033
Im与Vm分别是系统测得的光伏阵列最大功率点处的总电流和总电压；
Figure FDA0003292090950000034
与
Figure FDA0003292090950000035
分别为光伏系统的短路电流和开路电压，具体计算公式如下：(1) Define the current and voltage judgment factors when the photovoltaic modules in the system are faulty:
Figure FDA0003292090950000032
Figure FDA0003292090950000033
Im and V m are the total current and total voltage at the maximum power point of the photovoltaic array measured by the system, respectively;
Figure FDA0003292090950000034
and
Figure FDA0003292090950000035
are the short-circuit current and open-circuit voltage of the photovoltaic system, respectively. The specific calculation formulas are as follows:
Figure FDA0003292090950000036
Figure FDA0003292090950000036
 (2)计算系统中存在光伏组件开路故障时的故障判定因子阈值Fc1：当某一光伏组件处于开路状态时，光伏组件产生的输出电流等效于串联的光伏组件错误连接产生的电流，
Figure FDA0003292090950000037
其中
Figure FDA0003292090950000038
Fc1作为判定单串光伏组件开路的阈值，Im0为单个光伏组件最大功率点的电流，由公式
Figure FDA0003292090950000039
求得；(2) The fault determination factor threshold F c1 when there is an open-circuit fault of a photovoltaic module in the calculation system: when a photovoltaic module is in an open-circuit state, the output current generated by the photovoltaic module is equivalent to the current generated by the wrong connection of the photovoltaic modules in series,
Figure FDA0003292090950000037
in
Figure FDA0003292090950000038
F c1 is used as the threshold for judging the open circuit of a single string of photovoltaic modules, and I m0 is the current at the maximum power point of a single photovoltaic module, which is determined by the formula
Figure FDA0003292090950000039
obtain; (3)计算系统中存在光伏组件被旁路故障时的故障判定因子阈值Fv1：
Figure FDA0003292090950000041
其中
Figure FDA0003292090950000042
Fv1作为判定单串光伏组件开路的被旁路时的阈值，Vm0为单个光伏组件最大功率点的电压，由公式
Figure FDA0003292090950000043
求得；(3) Calculate the threshold value F v1 of the fault determination factor when there is a bypass fault of the photovoltaic module in the calculation system:
Figure FDA0003292090950000041
in
Figure FDA0003292090950000042
F v1 is used as the threshold for judging the open circuit of a single string of photovoltaic modules when they are bypassed, and V m0 is the voltage at the maximum power point of a single photovoltaic module, which is determined by the formula
Figure FDA0003292090950000043
obtain; (4)比较判定：正常运行条件下：Fc＞Fc1,Fv＞Fv1；当Fc≤Fc1或Fv≤Fv1时，表明当前光伏组件出现故障，对应故障类型如下式所示：(4) Comparison judgment: under normal operating conditions: F c > F c1 , F v > F v1 ; when F c ≤ F c1 or F v ≤ F v1 , it indicates that the current photovoltaic module is faulty, and the corresponding fault type is as follows Show:
Figure FDA0003292090950000044
Figure FDA0003292090950000044
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