CN113922758A - Photovoltaic module fault diagnosis and identification system and method for mine management - Google Patents
Photovoltaic module fault diagnosis and identification system and method for mine management Download PDFInfo
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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
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
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
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
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
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
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:
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:
Imand VmRespectively measuring the total current and the total voltage at the maximum power point of the photovoltaic array by the system;
and
the short-circuit current and the open-circuit voltage of the photovoltaic system are respectively calculated according to the following specific calculation formula:
(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,
wherein
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
Obtaining;
(3) fault determination factor threshold F when bypass fault of photovoltaic module exists in computing systemv1：
Wherein
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
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:
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):
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
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
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
Updating to the reference value of the next day; specifically, the following formula (2) is shown;
in the formula (I), the compound is shown in the specification,
calculating the average value of the generating energy effective values of the photovoltaic modules for the previous day;
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
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
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:
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:
Imand VmRespectively measuring the total current and the total voltage at the maximum power point of the photovoltaic array by the system;
and
the short-circuit current and the open-circuit voltage of the photovoltaic system are respectively represented by the following specific calculation formula (4):
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,
wherein
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
Obtaining;
(3) fault determination factor threshold F when bypass fault of photovoltaic module exists in computing systemv1：
Wherein
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
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);
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. The utility model provides a photovoltaic module fault diagnosis and identification system for mine is administered which characterized in that: the system comprises 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;
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.
2. The photovoltaic module fault diagnosis and identification system for mine treatment of claim 1, wherein:
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:
and 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.
3. The photovoltaic module fault diagnosis and identification system for mine treatment of claim 2, wherein: 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 results of the data processing module to the data analysis moduleThe real-time power generation effective value EnAverage value of power generation energy efficiency of previous day
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
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.
4. The photovoltaic module fault diagnosis and identification system for mine treatment of claim 1, wherein: 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.
5. The photovoltaic module fault diagnosis and identification system for mine treatment of claim 1, wherein:
the data analysis module comprises the following operation steps:
1) comparing and analyzing the data information acquired in real time with a preset theoretical value;
2) 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.
6. The photovoltaic module fault diagnosis and identification system for mine treatment of claim 1, wherein: 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 fault type identification unit operates 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.
7. The photovoltaic module fault diagnosis and identification system for mine treatment of claim 6, wherein:
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:
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.
8. The photovoltaic module fault diagnosis and identification system for mine administration of claim 6 or 7, wherein: the step2 comprises the following steps:
(1) defining current and voltage judgment factors when a photovoltaic assembly in a system has a fault:
Imand VmRespectively measuring the total current and the total voltage at the maximum power point of the photovoltaic array by the system;
and
the short-circuit current and the open-circuit voltage of the photovoltaic system are respectively calculated according to the following specific calculation formula:
(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，
Wherein
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
Obtaining;
(3) fault determination factor threshold F when bypass fault of photovoltaic module exists in computing systemv1：
Wherein
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
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:
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