KR20160078532A - A Photovoltaic Modular Abnormal Condition Diagnosis System and Method thereof - Google Patents

Abstract

The present invention relates to a modular abnormal condition diagnosis system for diagnosing photovoltaic modular abnormal conditions in photovoltaic power generator systems, and more specifically, to a photovoltaic modular abnormal condition diagnosis system and a method thereof, capable of quickly and accurately diagnosing photovoltaic modular abnormal conditions, by defining a group of control modules which are to be compared with the module under diagnosis, using the modules under identical environmental conditions and/or sharing identical generator characteristics only, or more specifically, using the modules under identical environmental conditions and/or sharing generator characteristics among modules that are closest to the module under diagnosis.

Description

Technical Field [0001] The present invention relates to a photovoltaic module,

The present invention relates to a module anomaly diagnosis system for diagnosing whether or not an abnormality occurs in each solar module in a photovoltaic power generation system and more specifically, Can be identified only by the modules having the same environmental condition and / or generation characteristic, more specifically, by the modules having the same environmental condition and / or generation characteristic among the modules located closest to the module to be diagnosed The present invention relates to an abnormality diagnosis system for a solar module, and a method thereof.

Solar cells are devices that convert solar light energy into electrical energy. A solar cell is a cell module that generates electricity from the light energy of the sunlight (hereinafter referred to as a "cell"), a cell module that combines the cells and transmits electricity generated in each cell to the outside (Hereinafter referred to as "module"), and a cell array (hereinafter referred to as "array") defined by a combination of the modules.

Here, the technology of the photovoltaic device according to the present invention is disclosed in Korean Patent Publication Nos. 10-0455250 (2004.10.22), 10-1028159 (2011,04,01) and 10-1049786 (2011, 07,11). That is, the photovoltaic power generation apparatus constitutes a photovoltaic power generation apparatus (system) when the power generation system using the photovoltaic cell that generates electricity as described above further includes a module composed of solar cells, a storage battery, and a power conversion inverter.

In the event that abnormalities occur in a specific module among many modules due to various causes such as shading, failure, and aging in the operation and operation process of the solar power generation apparatus, the maintenance for the diagnosis of the module in which the abnormality occurs, Although it is becoming more important than now, it is not easy to diagnose the abnormality of each specific module in which the abnormality occurs, and it is difficult to guarantee the accuracy even if the module diagnosis is performed.

(Patent Literature)

Japanese Registered Patent Publication No. JP5413933 (registered on Mar. 11, 2013) "Method and Apparatus for Determining Failure of Photovoltaic Power Plant"

The Japanese patent disclosed in the above patent also calculates the solar radiation amount of the panel inclined surface from the total solar irradiance condition, the date and time and the installation conditions of the solar power generation panel measured for each solar power generation panel, calculates the partial generation amount of each solar power generation panel, In order to accurately diagnose the module in which the abnormality occurs, it is necessary to consider only the solar radiation condition of each panel and the power generation characteristics of each panel. It is not related to accurately distinguishing modules to be compared in comparison with other modules.

That is, in order to accurately diagnose the abnormality of each photovoltaic module, it is necessary to make a judgment based on the difference of the output characteristics of the corresponding module in comparison with other modules. The verification module group ') can be improved only if the modules are placed under the same environmental conditions. However, the specific method of the verification module group has not been studied so far.

SUMMARY OF THE INVENTION The present invention has been made to solve the above problems,

It is an object of the present invention to provide a method and system for diagnosing an abnormality in each solar module by allowing modules having the same environmental condition and / And to provide a fault diagnosis system and method for each solar module.

Another object of the present invention is to provide a system and method for enabling a quick and accurate diagnosis by allowing a group of verification modules to be identified only by modules having the same environmental condition and / or generation characteristics among the modules located closest to the module to be diagnosed And to provide a fault diagnosis system and method for each solar module.

The above and other objects, features and advantages of the present invention will be more apparent from the following detailed description taken in conjunction with the accompanying drawings, in which: FIG.

An anomaly diagnosis system for each solar module according to an embodiment of the present invention includes an array including at least one solar module for converting solar energy into electric energy; An output sensing unit for measuring an output value of each module of the array; And an abnormality diagnosis unit for diagnosing whether abnormality occurs in a specific module based on the output value of each module measured by the output detection unit, wherein the abnormality diagnosis unit includes a plurality of The verification module group is identified only by the modules having the same output value around the specific module to be diagnosed in specifying the verification module group.

According to another embodiment of the present invention, in the fault diagnosis system for each solar module according to the present invention, the array is formed by arranging one or more solar modules in one or more rows and columns, A candidate group selection module sequentially selecting a plurality of candidate groups including a specific module to be diagnosed and a neighboring control module group in the array arranged in rows and columns of the candidate group, And a verification module group selection module for specifying a verification module group including only modules having the same output value in comparison with output values of the verification module group.

According to another embodiment of the present invention, in the fault diagnosis system for each photovoltaic module according to the present invention, the candidate group selection module groups the modules located in the rows and columns around the specific module to be diagnosed into a square shape, .

According to another embodiment of the present invention, in the abnormality diagnosis system for each solar module according to the present invention, the candidate group selection module includes a plurality of candidate groups of square form having 3 rows x 3 columns including specific modules to be diagnosed And sequentially selecting one of the plurality of pixels.

According to an embodiment of the present invention, there is provided an abnormality diagnosis method for each solar module, comprising: an output sensing step of measuring an output value of each module in an array in which one or more solar modules are arranged; And an abnormality diagnosis step of diagnosing whether abnormality occurs in a specific module based on the output value of each module measured in the output detection step, The verification module group is identified only by the modules having the same output value around the specific module to be diagnosed in specifying the plurality of verification module groups.

According to another embodiment of the present invention, in the abnormality diagnosis method for each solar module according to the present invention, the abnormality diagnosis step includes a specific module to be diagnosed in the array in which the solar module is arranged in a plurality of rows and columns, A candidate group selection step of sequentially selecting a plurality of candidate groups including a plurality of neighboring control module groups; and a control module group including only modules having the same output value in comparison with the output values of the control module groups included in the candidate group selected through the candidate group selection step And a verification module group selection step of specifying a verification module group.

According to another embodiment of the present invention, in the method for diagnosing an abnormality of each photovoltaic module according to the present invention, the candidate group selection step may include grouping modules located in rows and columns around a specific module to be diagnosed in a square form, .

According to another embodiment of the present invention, in the method for diagnosing an abnormality for each photovoltaic module according to the present invention, the candidate group selection step may include a plurality of candidate groups of square form having 3 rows x 3 columns including a specific module to be diagnosed And sequentially selecting one of the plurality of pixels.

The present invention can obtain the following effects by the above-described embodiment, the constitution described below, the combination, and the use relationship.

In the present invention, in the case of abnormality diagnosis for each solar module, it is possible to identify the corresponding module and the contrast module group to be compared with only the modules having the same environmental condition and / or power generation characteristic, .

The present invention has the effect of enabling quick and accurate diagnosis by allowing a group of verification modules to be identified only by modules having the same environmental condition and / or generation characteristics among the modules located closest to the module to be diagnosed.

BRIEF DESCRIPTION OF THE DRAWINGS FIG.
Fig. 2 is a reference diagram showing a state where shading occurs in a part in the array
3 is a block diagram showing the configuration of an abnormality diagnosis system for each solar module according to an embodiment of the present invention.
Fig. 4 is a reference view showing a case where shading (the same applies when the surface is covered with dirt or dust) around a specific module to be diagnosed
Fig. 5 is a reference view showing a case where shading (even when surface is covered with dirt or dust) occurs in a part of the periphery including a specific module to be diagnosed
6 is a block diagram illustrating a method for diagnosing an abnormality in each solar module according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, preferred embodiments of a fault diagnosis system and method for a photovoltaic module according to the present invention will be described in detail with reference to the accompanying drawings. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS In the following description of the present invention, a detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear. Throughout the specification, when an element is referred to as "including" an element, it is understood that the element may include other elements as well as other elements, The terms "part,"" module, "and the like denote a unit for processing at least one function or operation, which may be implemented as hardware or software or a combination of hardware and software.

1 is a reference view showing a remote monitoring system of a solar power generation apparatus. 1, the photovoltaic device includes a plurality of photovoltaic modules 10, which are the minimum units for actually sending out generated electricity (generated) to the outside, to form an array 20. In the case of large-scale photovoltaic power generation, The photovoltaic power generation apparatus also includes facilities such as the connection panel 30 and the inverter 40 and a sensor 50 for monitoring and transmission and reception And a coordinator 60 for the user). When the photovoltaic power generation apparatus is operated, the voltage of the photovoltaic module 10 is lowered (in other words, the efficiency of the corresponding module is lowered). At this time, If the cause of the voltage drop is notified to the operator, the corresponding module 10 is replaced, repaired, and cleaned.

However, conventionally, in the monitoring system of a photovoltaic power generation apparatus, a method of diagnosing that the output is simply degraded at the array stage, and then, in the array, the inspector manually measures each module of the array to identify the module in which the abnormality occurs In addition, although the recently developed module-based fault diagnosis system measures the amount of output for each module at the module end, the diagnosis for the corresponding module is performed by measuring the measured value in the corresponding module, It is a simple comparison that contrasts.

In this way, in order to diagnose abnormality of a specific module, a method of simply comparing the measured value measured by the module with the average value of the output of the entire array may cause various inaccuracies in diagnosis. Referring to FIG. 2 (FIG. 2 is a reference view showing a state in which a shadow is generated in a part of the array 20), when a shadow occurs due to a cloud, a building shadow or the like in a part of the array 20, The output voltage is lowered as a whole. In this state, when an abnormality as shown in FIG. 2 occurs based on the average value of the total output (for example, the voltage value can be used) of the array 20 in this state (for example, If the output value of the module 10-1 is compared with the output value of the module 10-1 in which the abnormality has occurred, However, since the average value of the total output is also in a deteriorated state, the diagnostic accuracy is significantly lower than that based on the average output value of the array 20 having no shadow at all.

2, even when it is assumed that the other module 10-2 belonging to the part where the shade occurs in the part of the array 20 is diagnosed as abnormal, even if there is no abnormality in the corresponding module 10-2 Even though the module 10-2 is included in the shade, the output value of the module 10-2 is lowered. In this case, Since the average value is relatively high compared to the case in which the whole is covered with the shade, when it is compared with this, the probability that the module 10-2 is diagnosed as having an abnormality occurs, and the accuracy of the diagnosis is lowered.

In order to fundamentally solve these problems, in the present invention, in order to diagnose an abnormality for each module, the control module group to be compared with the corresponding module (module to be diagnosed) is set as a control module composed only of modules having the same environmental condition and / It is aimed to increase the speed and accuracy of diagnosis by making it possible to identify by module group.

3 to 5, an abnormality diagnosis system for each photovoltaic module according to an embodiment of the present invention includes an output sensing unit 70 for measuring an output value of each module 10 of the array 20; And an abnormality diagnosis unit 80 for diagnosing whether abnormality occurs in the specific module 10 based on output values of the respective modules 10 measured by the output detection unit 70. The abnormality diagnosis unit 80 Is used to identify a plurality of verification module groups to be compared with the specific module 10 to be diagnosed, only the modules 10 having the same output value around the specific module 10 to be diagnosed .

The output sensing unit 70 is configured to measure the output value of each module 10 included in the array 20. For example, if the output value to be measured is a voltage value, a voltage measuring sensor or the like may be utilized .

The abnormality diagnosis unit 80 is configured to diagnose whether abnormality occurs in the specific module 10 based on output values of the respective modules 10 measured by the output detection unit 70. Particularly in the present invention, In order to fundamentally solve the problem pointed out as the problem of the specific module 10 to be diagnosed, in order to identify a plurality of verification module groups to be contrasted with the specific module 10 to be diagnosed, The verification module group is identified only by the modules 10 having the same output value.

That is, the modules 10 included in the control module group all have the same output value (environmental condition or power generation characteristic), and as a result, the verification module group in which the module included in the shade and the module not included in the shade are mixed Or a module in which dust and dirt-covered modules are mixed on the surface of the module 10 and a module in which no dust or dirt is covered on the surface of the module 10 is prevented from being generated. In addition, So that the specific module 10 to be diagnosed is in the shade, while the modules of the control module group are blocked from being out of the shadow, so that the accuracy of diagnosis .

More specifically, for example, when the array 20 is formed by arranging one or more solar modules 10 in one or more rows and columns as shown in FIG. 4 and the like, A candidate group selection module 810 for sequentially selecting a plurality of candidate groups consisting of a specific module to be diagnosed and a neighboring verification module group in the array () in which the optical module 10 is arranged in a plurality of rows and columns; And a verification module group selection module 820 for identifying the verification module group including only the modules having the same output value in comparison with the output values of the verification module group included in the candidate group selected through the candidate group selection module 810. [

The candidate group selection module 810 sequentially selects various combinations of the specific module to be diagnosed and the verification module group including the modules around the specific module with the specific module as a center. Preferably, the candidate group selection module 810 groups the modules located in the rows and columns around the specific module to be diagnosed into a square shape (for example, a square shape having 3 rows x 3 columns including a specific module to be diagnosed) A method of sequentially selecting a plurality of candidate groups may be applied, but the candidate group selection method is not limited thereto.

Hereinafter, in order to facilitate understanding of the present invention, for example, the candidate group selection module 810 selects a candidate group sequentially in a square form of 3 rows x 3 columns including a specific module to be diagnosed .

FIG. 4 is a reference view showing a case where a shade (even when a surface is covered with dirt or dust) occurs around a specific module to be diagnosed. Referring to FIG. 4, the specific module 10- Is not included in the shade but only in the vicinity of the shade, the candidate group selection module 810 selects the candidate module 10-a including the specific module 10- A total of nine candidate groups 11-1 to 11-9 are sequentially selected and presented as a candidate group of a square shape consisting of three columns (nine modules 10 in total). At this time, the control module group selection module 820 The module selection module 810 selects only the modules included in the remaining verification module groups except for the specific module 10-a to be diagnosed with respect to the candidate groups 11-1 to 11-9 selected through the candidate group selection module 810 A comparison with only the modules having the same output value in comparison with the output values Module group is specified. In the example of FIG. 4, the modules included in the control module group are included in the shade and the modules not included in the other candidate groups 11-1 to 11-8 of the candidate groups 11-1 to 11-9 are mixed In the 11-9 candidate group, all of the modules included in the control module group are composed of only modules that are not included in the shade and are made up only of modules having the same output value as the specific module 10-a to be diagnosed Therefore, the control module group including only the remaining modules excluding the specific module 10-a included in the 11-9 candidate group to be diagnosed is specified. In this case, the specific module (10-a) to be diagnosed has a lower output value than the average output value of the corresponding control module group through comparison with the control module group which is higher than the same environmental condition (condition not included in the shade) In this case, the diagnostic accuracy is improved compared with the case where the other control module group is selected.

5 is a reference view showing a case where a shade (even when a surface is covered with dirt or dust) is formed on a part of a periphery including a specific module to be diagnosed. Referring to Fig. 5, The candidate group selection module 810 selects the specific module 10-b to be diagnosed as the center of the specific module 10-b to be diagnosed, as described above, A total of nine candidate groups 11-1 to 11-9 are successively selected as candidates of a square form composed of three rows and three columns (nine modules 10 in total) including the specific module 10-b The verification module group selection module 820 selects the candidate modules 11-1 to 11-9 selected through the candidate group selection module 810 and the specific module 10-b ) Is compared with the output values of only the modules included in the other control module groups The verification module group including only the modules having the output value is specified. In the example of FIG. 5, in the other candidate groups (11-1 to 11-4 and 11-6 to 11-9) among the candidate groups 11-1 to 11-9, the modules included in the control module group are included in the shade In the 11-5 candidate group, all the modules included in the control module group are composed of only the modules included in the shade as in the specific module (10-b) to be diagnosed. Output module, the control module group including only the modules other than the specific module 10-b to be diagnosed included in the 11-5 candidate group is specified. In this case, the specific module (10-b) to be diagnosed shows a lower output value than the output average value of the corresponding control module group through comparison with the control module group that is higher than the same environmental condition (condition included in the shade) (I.e., even if the specific module 10-b to be diagnosed itself is included in the shade, it is possible to receive an accurate diagnosis without being restricted thereto). As compared with the case where the other control module group is selected, Can be increased.

As described above, the abnormality diagnosis system for each solar module according to the present invention can detect the abnormality of the target module, regardless of whether the module to be diagnosed is in the shade or not, whether it is covered with dust or stains, It is possible to quickly identify the control module group placed in the same environmental condition (or the power generation condition) as a contrast object, and to perform diagnosis based on the comparison module. Therefore, .

Hereinafter, an abnormality diagnostic method for each solar module in which the system described above is implemented will be described.

6, an abnormality diagnosis method for each solar module according to an embodiment of the present invention includes the steps of measuring an output value of each module 10 in the array 20 in which one or more solar modules 10 are arranged An output detection step (S10); And an abnormality diagnosis step S20 for diagnosing whether abnormality occurs in the specific module 10 based on output values of the respective modules 10 measured in the output detection step S10. In the case of specifying a plurality of verification module groups to be compared with the specific module 10 to be diagnosed, only the modules 10 having the same output value around the specific module 10 to be diagnosed, .

The output sensing step S10 is a process of measuring output values of the respective modules 10 included in the array 20. For example, when the output value to be measured is a voltage value, a voltage measuring sensor or the like may be utilized .

The abnormality diagnosis step S20 is a step of diagnosing whether abnormality occurs in the specific module 10 based on the output value of each module 10 measured in the output sensing step S10. A candidate group selecting step of sequentially selecting a plurality of candidate groups 11 composed of a specific module 10 to be diagnosed and a surrounding verification module group in the array 20 in which the plurality of candidate groups 11 are arranged in a plurality of rows and columns, And a verification module group selecting unit for selecting a verification module group including only the modules 10 having the same output value in comparison with the output values of the verification module group included in the candidate group 11 selected through the candidate group selection step S21 Step S22.

In the candidate group selection step S21, various combinations of the verification module group consisting of the specific module 10 to be diagnosed and the modules around the specific module 10 around the specific module 10 are divided into a plurality of candidate groups 11 ). ≪ / RTI > Preferably, in the candidate group selection step S21, the modules located in rows and columns around the specific module to be diagnosed are grouped into a square shape (for example, a square shape consisting of 3 rows x 3 columns including a specific module to be diagnosed) A method of sequentially selecting a plurality of candidate groups may be applied, but the candidate group selection method is not limited thereto. The method of sequentially selecting candidate groups in the candidate group selection step S21 is the same as that described above with reference to FIG. 4 and FIG. 5, so a description will be omitted in order to avoid redundant description.

The checking module group selecting step S22 may include comparing modules output from the comparing module group included in the candidate group 11 selected through the candidate group selecting step S21 to only the modules 10 having the same output value Becomes specific.

As described above, the abnormality diagnostic system for each solar module according to the present invention can be applied to the module 10 regardless of whether the module 10 to be diagnosed is contained in the shade or not, whether it is covered with dust or stains, It is possible to quickly identify a control module group that is in the same environmental condition (or power generation condition) as the target module 10 as a contrast target and to perform a diagnosis based on the comparison module. Therefore, It has the characteristic of being.

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, Should be interpreted as belonging to the scope.

10: Module 11: candidate
20: array 30: connection board
40: Inverter 50: Sensor
60: Coordinator 70: Output detection unit
80: abnormality diagnosis unit 810: candidate group selection module
820: Control module group selection module

Claims (8)

An array comprising at least one solar module for converting solar energy to electrical energy;
An output sensing unit for measuring an output value of each module of the array; And
And an abnormality diagnosis unit for diagnosing whether abnormality occurs in the specific module based on the output value of each module measured by the output sensing unit,
Wherein the abnormality diagnosis unit identifies a control module group only by modules having the same output value around a specific module to be diagnosed in specifying a plurality of control module groups to be compared with a specific module to be diagnosed, Fault diagnosis system per module. The method according to claim 1,
The array being formed by one or more solar modules arranged in one or more rows and columns,
Wherein the abnormality diagnosis unit comprises: a candidate group selection module for sequentially selecting a plurality of candidate groups including a specific module to be diagnosed and a neighboring verification module group in the array in which the solar module is arranged in a plurality of rows and columns; And a verification module group selection module for identifying a verification module group including only modules having the same output value in comparison with an output value of the verification module group included in the candidate group selected through the module. 3. The method of claim 2,
Wherein the candidate group selection module sequentially selects a plurality of candidate groups by grouping modules located in rows and columns around a specific module to be diagnosed in a square form. The method of claim 3,
Wherein the candidate group selection module sequentially selects a plurality of candidate groups in a square form having 3 rows and 3 columns including a specific module to be diagnosed. An output sensing step of measuring an output value of each module in an array in which one or more solar modules are arranged; And
And an abnormality diagnosis step of diagnosing whether abnormality occurs in the specific module based on the output value of each module measured in the output detection step,
Wherein the abnormality diagnosis step identifies the control module group only by the modules having the same output value around the specific module to be diagnosed in specifying the plurality of control module groups to be contrasted with the specific module to be diagnosed Fault diagnosis method for each photovoltaic module. 6. The method of claim 5,
Wherein the abnormality diagnosis step comprises a candidate group selecting step of sequentially selecting a plurality of candidate groups each consisting of a specific module to be diagnosed and a neighboring control module group in the array in which the solar module is arranged in a plurality of rows and columns, And a control module group selecting step of selecting a control module group including only modules having the same output value in comparison with the output values of the control module group included in the candidate group selected through the selection step . The method according to claim 6,
Wherein the candidate group selection step sequentially selects a plurality of candidate groups by grouping modules located in rows and columns around a specific module to be diagnosed in a square form. 8. The method of claim 7,
Wherein the candidate group selection step sequentially selects a plurality of candidate groups in a square form having 3 rows and 3 columns including a specific module to be diagnosed.

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