JP2017181138A - Photovoltaic power generation facility abnormality diagnostic method, abnormality diagnostic device, and abnormality diagnostic program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To easily and appropriately detect or diagnose an abnormality or a failure in a photovoltaic power generation facility.SOLUTION: The present invention includes the steps of calculating the spectrum value of sound data acquired by collecting sounds generated from a photovoltaic power generation facility, on a frequency component-by-frequency component basis (step S1, S2); determining the generation of an abnormality or a failure in the photovoltaic power generation facility, using the spectrum value for each frequency component (step S3); and outputting an abnormal notification signal when the generation of an abnormality or a failure has been determined (step S4).SELECTED DRAWING: Figure 1

Description

  The present invention relates to an abnormality diagnosis method, an abnormality diagnosis apparatus, and an abnormality diagnosis program for photovoltaic power generation facilities. More specifically, the present invention relates to a technique suitable for use in diagnosis and detection of abnormality / failure in a photovoltaic power generation facility.

  As a photovoltaic power generation facility, it is composed of a solar cell array (specifically, a collection of solar cell panels) that converts sunlight energy into electric energy, and a power conditioner, and the generated power from the solar cell array is converted into a power conditioner. What outputs to an electric power system after performing DC / AC conversion etc. by NA is known.

  The solar cell array includes a plurality of solar cell strings configured by connecting a plurality of solar cell modules (having solar cell panels) in series, and the plurality of solar cell strings are connected in parallel, so that predetermined power is generated. It is configured to be able to generate electricity.

  The solar cell module includes a plurality of solar cell clusters configured by connecting a plurality of solar cells in series, and is configured by connecting the plurality of solar cell clusters in series. However, a solar cell module may be configured by connecting a plurality of solar cells in series without providing a collective configuration as a solar cell cluster.

  In such a photovoltaic power generation facility, when some solar battery clusters or solar battery cells break down or enter the shade, for example, the partial solar battery clusters or the partial solar battery clusters or Predetermined electric power is not generated in the solar battery module including the solar battery cells.

  For this reason, bypass diodes that form paths that bypass the solar cell clusters and solar cell modules are connected in parallel to both ends of each solar cell cluster and each solar cell module. In addition, as a connection mode of the bypass diode, specifically, in addition to a mode in which one bypass diode is connected to one solar cell cluster, one bypass diode is connected to a plurality of solar cell clusters. There is a mode in which a plurality of bypass diodes are connected to one solar cell cluster.

  By providing a bypass diode, when some solar battery clusters or solar battery cells break down or enter the shade, for example, the partial solar battery clusters or the partial solar battery clusters or solar batteries Although a predetermined electromotive force is not generated in the solar cell module including the cells (in other words, the generated power of the solar cell cluster or the solar cell module is reduced), before and after the partial solar cell cluster or the solar cell module. Current flows through the bypass diode. As a result, loss due to internal resistance of some solar cell clusters (specifically, solar cells) that have failed or entered the shade is avoided, and some solar cell clusters (specifically, solar cells) A decrease in the output of the entire solar cell array due to a failure of the battery cell) or shading is avoided.

JP 2007-088195 A

  However, with conventional solar power generation facilities, if the generated power output falls or fluctuates unnaturally, it may not be possible to identify the location / part where the failure has occurred. For this purpose, there is a problem that an inspection by directly contacting the solar power generation equipment (that is, connecting to the equipment circuit) is required.

  In the conventional solar power generation equipment, even if a part of a plurality of solar battery clusters or solar battery modules fails, the reduction and fluctuation of the output of generated power is suppressed by the action of the bypass diode. There is a problem that abnormalities / failures may not be detected in monitoring the change in the output of the generated power from the power generation facility to the outside.

  Accordingly, an object of the present invention is to provide an abnormality diagnosis method, an abnormality diagnosis apparatus, and an abnormality diagnosis program for a solar power generation facility that can appropriately and easily perform diagnosis and detection of an abnormality / failure in the solar power generation facility. And

  In order to achieve such an object, the method for diagnosing abnormality of a solar power generation facility according to the present invention calculates a spectrum value for each frequency component for sound data obtained by collecting sound generated from the solar power generation facility, Spectral values for each component are used to determine whether or not an abnormality or failure has occurred in the photovoltaic power generation facility.

  Further, in the abnormality diagnosis method for the photovoltaic power generation facility according to the present invention, the spectrum value for each frequency component is calculated for each of the sound data obtained by acquiring the sound generated from the photovoltaic power generation facility at a plurality of time points, The spectrum value for each frequency component at the time is used to determine whether an abnormality or failure has occurred in the photovoltaic power generation facility.

  Further, the abnormality diagnosis method for a photovoltaic power generation facility according to the present invention provides a frequency for each of sound data obtained by collecting sounds generated from a plurality of photovoltaic power generation facilities including at least the photovoltaic power generation facility to be diagnosed. The spectrum value for each component is calculated, and the spectrum value for each frequency component for each photovoltaic power generation facility is used to determine whether an abnormality or failure has occurred in the photovoltaic power generation facility to be diagnosed.

  Further, the abnormality diagnosis device for the photovoltaic power generation facility of the present invention is a means for collecting sound generated from the photovoltaic power generation facility and outputting sound data, a means for calculating a spectral value for each frequency component for the sound data, Means for determining the presence / absence of abnormality / failure in the photovoltaic power generation facility using the spectrum value for each frequency component.

  Further, the abnormality diagnosis program for the photovoltaic power generation facility according to the present invention includes a process for calculating a spectrum value for each frequency component for sound data acquired by collecting sound generated from the photovoltaic power generation facility, and a spectrum for each frequency component. It is made to make a computer perform the process which determines the presence or absence of generation | occurrence | production of the abnormality and failure in a solar power generation facility using a value.

  Therefore, according to the abnormality diagnosis method, abnormality diagnosis apparatus, and abnormality diagnosis program for these photovoltaic power generation facilities, whether or not an abnormality or failure has occurred in the photovoltaic power generation facility by collecting sound generated from the photovoltaic power generation facility Therefore, the diagnosis is performed while the solar power generation facility performs normal operation (that is, the output of the generated power), that is, the operation of the solar power generation facility is stopped or partly Diagnosis is performed without disconnection or direct electrical contact with the photovoltaic power generation equipment (that is, connection to the equipment circuit).

  According to the abnormality diagnosis method, abnormality diagnosis apparatus, and abnormality diagnosis program for these photovoltaic power generation facilities, it is further determined whether or not an abnormality or failure has occurred in the photovoltaic power generation facility based on the sound generated from the photovoltaic power generation facility. Therefore, it is difficult to detect the change in the output of the generated power from the photovoltaic power generation facility to the outside (for example, as a change in the output of the generated power due to the function of the bypass diode) Abnormalities and failures are also captured.

  Further, the abnormality diagnosis method, abnormality diagnosis apparatus, and abnormality diagnosis program for the photovoltaic power generation facility according to the present invention may collect sound generated from the bypass diode as sound generated from the photovoltaic power generation facility. In this case, an abnormal sound associated with the bypass diode is collected.

  Further, the abnormality diagnosis method, abnormality diagnosis apparatus, and abnormality diagnosis program for a photovoltaic power generation facility according to the present invention are such that the spectrum value of each frequency component is a frequency spectrum that is an integer multiple of the switching frequency in the power conditioner of the photovoltaic power generation facility It may be a spectrum value of a frequency other than the value or an integral multiple of the switching frequency. In this case, an abnormal sound that is manifested as a sound in a frequency band that is an integral multiple of the switching frequency in the power conditioner or a frequency band other than an integral multiple of the switching frequency is collected.

  Here, in the present invention, a magnetic field is generated around the wiring or the diode when the current flows through the wiring component or the diode, which is a component of the photovoltaic power generation facility, and a force is generated when the magnetic fields act on each other. Then, the object is vibrated and the sound is generated by this. Therefore, the photovoltaic power generation facility according to the present invention has a configuration in which a wiring or a diode vibrates and generates a sound wave when the magnetic fields generated by the wirings or the magnetic field generated by the wirings and the magnetic field generated by the diodes act on each other to exert force. It is preferable that it is the apparatus.

  On the other hand, for example, when the sound generated due to the current flowing through the wiring or diode is very low or no sound is generated, a magnet or the like is arranged so that the wiring or diode is likely to vibrate and the magnetic field is applied. It may be configured to amplify or generate a sound wave by intentionally generating it.

  Therefore, the abnormality diagnosis method for a photovoltaic power generation facility according to the present invention may be configured such that a magnetic field is applied to the photovoltaic power generation facility or a magnetic material is approached. In addition, the abnormality diagnosis device for a solar power generation facility according to the present invention may further include means for applying a magnetic field to the solar power generation facility or a magnetic material for making the solar power generation facility approach. good. In these cases, a magnetic field is artificially generated for the photovoltaic power generation equipment. For example, a force is generated by the action of a magnetic field generated by a current flowing through the wiring or diode, and the wiring or diode vibrates. It becomes easy.

  According to the abnormality diagnosis method, abnormality diagnosis apparatus, and abnormality diagnosis program of the solar power generation facility of the present invention, the solar power generation facility can perform diagnosis while performing normal operation (that is, output of generated power), In other words, the diagnosis can be performed without stopping the operation of the photovoltaic power generation facility, separating a part of the photovoltaic power generation facility, or electrically contacting the photovoltaic power generation facility directly (that is, connecting to the facility circuit). Diagnosis of the photovoltaic power generation facility can be performed appropriately and easily at any time, and as a result, it is possible to improve the usefulness as a method for detecting an abnormality or failure of the photovoltaic power generation facility.

  According to the abnormality diagnosis method, abnormality diagnosis apparatus, and abnormality diagnosis program of the solar power generation facility of the present invention, an abnormality that is difficult to find by monitoring the change in the output of the generated power from the solar power generation facility to the outside Since it is possible to capture even malfunctions, it is possible to prevent omissions in the detection of abnormalities / failures in photovoltaic power generation facilities. Improvements can be made.

  In addition, the abnormality diagnosis method, abnormality diagnosis apparatus, and abnormality diagnosis program for a photovoltaic power generation facility according to the present invention collects abnormal sounds associated with the bypass diodes when sounds generated from the bypass diodes are collected. Therefore, it is possible to reliably detect abnormalities / failures related to bypass diodes that are difficult to detect, and thus to detect abnormalities / failures in photovoltaic power generation facilities. As a result, it is possible to further improve the usefulness and reliability.

  The abnormality diagnosis method, abnormality diagnosis apparatus, and abnormality diagnosis program for photovoltaic power generation facilities according to the present invention use a spectrum value of a frequency that is an integral multiple of the switching frequency in the power conditioner or a spectrum value of a frequency other than the integral multiple. In such a case, abnormal sounds that are manifested as sounds in a frequency band that is an integral multiple of the switching frequency in the power conditioner or in a frequency band other than an integral multiple can be collected. Thus, it is possible to further improve the usefulness and reliability as a method for detecting an abnormality or failure of a photovoltaic power generation facility.

  Further, the abnormality diagnosis method and abnormality diagnosis apparatus for the photovoltaic power generation facility according to the present invention, when a magnetic field is applied to the photovoltaic power generation facility or a magnetic material is made to approach, for example, a current to a wiring or a diode. Since the wiring and diodes can be vibrated by artificially generating a force due to the action of the magnetic field when the current flows, it is possible to reliably generate sound when current flows through these wirings and diodes. It is possible to improve certainty as a method for detecting an abnormality / failure of a photovoltaic power generation facility, thereby improving reliability.

It is a flowchart which shows an example of embodiment of the abnormality diagnosis method of the solar power generation facility of this invention. It is a functional block diagram which shows an example of embodiment of the abnormality diagnosis apparatus of the solar power generation facility of this invention. It is a functional block diagram of the abnormality diagnosis apparatus of the photovoltaic power generation facility realized by the program when the abnormality diagnostic method for the photovoltaic power generation facility of the embodiment is implemented using the abnormality diagnosis program for the photovoltaic power generation facility. It is a figure which shows the circuit structure of the solar cell module of embodiment. It is a figure explaining the electric current circuit when the one part of generated electric power among the some solar cell clusters which comprise the solar cell module of FIG. 4 falls.

  Hereinafter, the configuration of the present invention will be described in detail based on an example of an embodiment shown in the drawings.

  In the following description, in order to clarify that it is a unit, a symbol or character as a unit may be enclosed in [].

  1 to 5 show an example of an embodiment of an abnormality diagnosis method, an abnormality diagnosis device, and an abnormality diagnosis program for a photovoltaic power generation facility according to the present invention.

  In the present embodiment, a case where an example of the abnormality diagnosis method for solar power generation equipment of the present invention is applied to the solar cell module 20 whose circuit configuration is shown in FIG. 4 will be described. In FIG. 4, arrows indicate the direction of current flow in the circuit.

  In addition, as a whole solar power generation device, the aspect (it is also called a solar cell string) comprised by connecting the some solar cell module 20 in series can be assumed, for example.

  In addition, the generated power from the plurality of solar cell modules 20 (in other words, as a solar cell string) is output to a power conditioner (or an inverter for grid connection; not shown), and a direct current is output from the power conditioner. It is converted from electric power to AC power.

  In the present embodiment, a plurality of solar cells 22 are connected in series to constitute a solar cell cluster 21, and a plurality of solar cell clusters 21 are connected in series to constitute a solar cell module 20. Further, a bypass diode 23 is connected in parallel to each of the solar cell clusters 21.

  In the example shown in FIG. 4, a plurality of solar cell clusters 21A, 21B, 21C,..., 21X (however, any number) are connected in series to form a solar cell module 20, and solar cell clusters 21A, 21B, 21C, .., 21X are connected in parallel with bypass diodes 23A, 23B, 23C,.

  Each of the bypass diodes 23A, 23B, 23C,..., 23X decreases the generated power of the solar cell clusters 21A, 21B, 21C,. When an applied voltage from another solar cell module (not shown) reaches a predetermined forward voltage, by passing a current in the forward direction, each of the solar cell clusters 21A, 21B, 21C,..., 21X are formed as bypass paths.

  As a result, when a part of the plurality of solar cell clusters 21 breaks down or enters a shade, for example, the generated power is reduced via the bypass path formed by the bypass diode 23. Other solar cell clusters 21 that are adjacent to each other with the lowered solar cell cluster 21 interposed therebetween are connected to each other, or other solar cell clusters 21 that are adjacent to each other with the solar cell cluster 21 with the reduced generated power interposed therebetween, and other solar cells. A module (not shown) is connected to the power conditioner (not shown) of the generated power (from the solar cell string) from the plurality of solar cell modules 20 while avoiding the influence of failure or shade. Output to.

  In the example shown in FIG. 5, since the solar battery cell 22 of the solar battery cluster 21B has failed (reference numeral 29) and the generated power of the solar battery cluster 21B has decreased, the bypass diode connected in parallel to the solar battery cluster 21B. A current flows through 23B (in FIG. 5, the arrow indicates the direction of the main current flow in the circuit). Thereby, the solar cell cluster 21A and the solar cell cluster 21C adjacent to each other across the solar cell cluster 21B where the generated power is reduced are connected, and the generated power is avoided while avoiding the influence of the failure of the solar cell 22 in the solar cell cluster 21B. Is output.

  And the abnormality diagnosis method of the solar power generation facility of this embodiment applied to the solar cell module 20 as the solar power generation facility is a frequency component for the sound data acquired by collecting the sound generated from the solar power generation facility. Each spectrum value is calculated (S1, S2), and the spectrum value for each frequency component is used to determine whether or not an abnormality or failure has occurred in the photovoltaic power generation facility (S3) and an abnormality or failure occurs. If it is determined that the abnormality is detected, an abnormality notification signal is output (S4) (see FIG. 1).

  Moreover, the abnormality diagnosis apparatus 10 of the photovoltaic power generation facility according to the present embodiment includes a sound detection unit 1 as a means for collecting sound generated from the photovoltaic power generation facility and outputting sound data, and the sound data for each frequency component. When it is determined that an abnormality / failure has occurred in the photovoltaic power generation facility using the conversion unit 2 as a means for calculating the spectrum value and the spectrum value for each frequency component. Has a determination unit 3 as means for outputting an abnormality notification signal and an alarm output unit 4 as means for issuing an alarm in accordance with the abnormality notification signal (see FIG. 2).

  And as implementation of the abnormality diagnosis method of a solar power generation facility, first, the sound generated from the solar power generation facility is collected and sound data is acquired (S1).

  Specifically, the sound detection unit 1 having a sound collection function is installed for the photovoltaic power generation facility to be diagnosed, and the sound generated from the solar power generation facility is collected by the sound collection function of the sound detection unit 1. (In other words, the sound pressure signal of the sound is collected or the sound pressure level of the sound is measured).

  The specific mechanism that constitutes the sound collection function of the sound detector 1 is not limited to a specific device or apparatus, but is an operating sound generated from the photovoltaic power generation facility (however, due to the generation of the operating sound). Appropriate equipment for collecting (in other words, collecting and collecting sound) is appropriately selected. For example, a sound sensor (microphone) or a vibration sensor (vibration displacement detection type sensor, speed detection type sensor, or acceleration detection type sensor) can be used as a specific mechanism constituting the sound sampling function of the sound detection unit 1. .

  The mode of installation of the sound detection unit 1 is not limited to a specific mode, and an appropriate place or the like so that the operation sound generated from the photovoltaic power generation facility to be diagnosed can be collected (sound collection, sound collection). The method of installation and fixing is appropriately selected.

  Here, the sound detection unit 1 individually collects sound generated from each unit or module as a diagnostic unit related to the photovoltaic power generation facility (in other words, an abnormality / failure detection unit in the photovoltaic power generation facility). Alternatively, it may be installed and arranged corresponding to each of the units as diagnostic units.

  Specifically, for example, each of the solar power generation equipment, such as the solar battery cluster 21, the solar battery cell 22, the bypass diode 23, or the power conditioner (not shown), is individually generated. It may be arranged and arranged so that it can be collected. In this case, the sound detection unit 1 may be configured to be portable, and may be arranged in order so as to correspond to each of the units as diagnostic units. Alternatively, a directional microphone may be used as the sound detection unit 1, and the sound detection unit 1 may be directed in order with each unit such as a diagnostic unit as a target. Alternatively, individual sound detectors 1, that is, a plurality of sound detectors 1, may be provided for each of the units as diagnostic units.

  The sound detection unit 1 may be arranged so as to be separated from the outside of the casing or case constituting the photovoltaic power generation facility or in contact with the outer surface of the casing or case, Or you may make it arrange | position inside the housing | casing, case, etc. which comprise the solar power generation facility.

  Further, the sound detection unit 1 may be provided with a stethoscope and a sound stick (or a mechanism having a function similar to that of the stethoscope and the sound stick) as necessary.

  Here, the present invention collects and uses the sound generated by the action of a magnetic field generated when a current flows through the components of the photovoltaic power generation facility, and the object vibrates due to the force. Is. However, depending on the photovoltaic power generation equipment, the sound generated when a current flows through the component may be very small or no sound may be generated. Therefore, by intentionally generating a magnetic field so that the components easily vibrate when a current flows, the sound waves are amplified or generated, that is, the sound generated from the photovoltaic power generation equipment is collected. You may make it easy to do.

  Specifically, it is conceivable to apply a magnetic field from the outside to the solar power generation facility or to bring a magnetic material closer to the solar power generation facility.

  When applying a magnetic field from outside to a photovoltaic power generation facility, specifically, a permanent magnet or an electromagnet is placed near the photovoltaic power generation facility, and each unit or module as a diagnostic unit, if necessary. It is conceivable that sound is collected in the vicinity of the sound detection unit 1 and in some cases in the vicinity of the sound detection unit 1 (in other words, together with the sound detection unit 1). As the permanent magnet, specifically, for example, a ferrite magnet or a neodymium magnet can be used.

  When a magnetic material is brought close to the solar power generation facility, specifically, a magnetic material such as an iron plate is placed in the vicinity of the solar power generation facility, if necessary, for each unit or module as a diagnostic unit. In particular, it is conceivable that sound is collected in the vicinity of the sound detection unit 1 and in some cases in the vicinity of the sound detection unit 1 (in other words, together with the sound detection unit 1). Even when the magnetic material is disposed in the vicinity of the solar power generation facility, the magnetic material is attracted to the magnetic field generated around the component parts and vibrates to generate sound.

  The sound detection unit 1 includes an amplification function as necessary in addition to a sound collection function, and also includes an A / D conversion function.

  Then, the sound generated from the photovoltaic power generation facility to be diagnosed is collected as sound (in other words, sound pressure or sound pressure level) by the sound detection unit 1, amplified as necessary, and converted into a digital signal. Output after being converted. Here, the digital signal output from the sound detection unit 1 is referred to as “sound data”.

  In addition, it is not an essential structure in the present invention that the sound detection unit 1 includes a sound sampling function, an amplification function as necessary, an A / D conversion function, and a signal output function as an integrated device / device. The sound detection unit 1 may be configured as a collection / combination of separate devices / devices having these functions.

  Moreover, you may make it the abnormality diagnostic apparatus 10 of one photovoltaic power generation installation provide the some sound detection part 1. FIG. In this case, the following processing after S2 is performed on each of the sound data output from the plurality of sound detectors 1.

  Next, the frequency intensity is calculated for the sound data acquired by the process of S1 (S2).

  Specifically, the sound data output from the sound detection unit 1 in the process of S1 is input to the conversion unit 2, and in the present embodiment, the conversion unit 2 performs a Fourier transform process or a wavelet transform process on the sound data. The frequency intensity P (f) at the frequency f [Hz] is calculated as a spectral value for each frequency component. When the Fourier transform process or the wavelet transform process is performed, the frequency intensity includes time information (T) and can be expressed as “P (f, T)”. Both are expressed as “P (f)” as being subjected to the conversion process and the wavelet conversion process.

  Here, the method of calculating the spectrum value for each frequency component of the sound data is not limited to the Fourier transform process or the wavelet transform process, and the frequency intensity P (() at the frequency f [Hz] is used as the spectrum value for each frequency component. A suitable method by which f) can be calculated is appropriately selected.

  Then, the conversion unit 2 outputs the calculated frequency intensity P (f) associated with the frequency f [Hz] (in other words, as combined data of the frequency f [Hz] and the frequency intensity P (f)). Is done.

  Here, the frequency intensity P (f) at the frequency f [Hz] (in other words, the frequency f [Hz] and the frequency intensity P obtained from the sound data obtained by collecting the sound generated from the photovoltaic power generation facility. (combination data with (f)) is called “determination data”.

  Next, the value of the frequency intensity calculated by the process of S2 is used to determine whether or not an abnormality / failure has occurred in the photovoltaic power generation facility (S3).

  Specifically, the combination data of the frequency f [Hz] and the frequency intensity P (f) output from the conversion unit 2 in the process of S2 is input to the determination unit 3, and the determination unit 3 receives the sunlight to be diagnosed. It is determined whether an abnormality or failure has occurred in the power generation facility.

The method of determining whether an abnormality or failure has occurred in a photovoltaic power generation facility can be broadly divided into the following three types. Hereinafter, each of the following (1) to (3) will be described.
(1) Focus on the frequency intensity of a predetermined frequency related to the photovoltaic power generation facility to be diagnosed.
(2) Pay attention to the frequency intensity at a plurality of points in time for the photovoltaic power generation facility to be diagnosed.
(3) Focus on the frequency intensity related to each of a plurality of photovoltaic power generation facilities.

(1) A method of paying attention to the frequency intensity of a predetermined frequency related to the photovoltaic power generation facility to be diagnosed In this method, based on the strength of the frequency intensity of the predetermined frequency in the determination data related to the photovoltaic power generation facility to be diagnosed, It is determined whether an abnormality or failure has occurred in the photovoltaic power generation facility.

Specifically, it is determined that an abnormality / failure has occurred in the photovoltaic power generation facility in the following cases.
A) When the frequency intensity of a predetermined frequency in the judgment data exceeds a predetermined threshold value (in other words, when a sound of a predetermined frequency is collected above a predetermined level)
A) When the frequency intensity of the predetermined frequency in the judgment data falls below a predetermined threshold value (in other words, when the sound of the predetermined frequency is not collected above the predetermined level)

  In the case of (a), since no current flows in a normal state, no sound is generated or hardly generated at a predetermined frequency (that is, no sound is collected or hardly collected). The sound is sampled at the predetermined frequency because an abnormality / failure has occurred (specifically, for example, an electric current flows due to the occurrence of an abnormality / failure). Presumed.

  In the case of (a), since a current flows in a normal state and a sound is generated at a specific frequency (that is, the sound is collected), a sound having a loudness exceeding a predetermined threshold is (I.e., the sound of the specific frequency becomes louder than normal), or is sampled at a predetermined frequency different from the specific frequency (i.e., the frequency of the collected sound changes) It is presumed that an error / failure has occurred (specifically, for example, because the flow of current has changed with the occurrence of an error / failure).

  In the case of the above (i), since current flows in a normal state, sound is generated at a specific frequency (that is, sound is collected), and the volume of sound collected at the specific frequency is predetermined. It is presumed that the value of the threshold value has fallen below this threshold value because of the occurrence of an abnormality / failure (specifically, for example, the current has stopped flowing or almost ceased due to the occurrence of the abnormality / failure).

  Here, the predetermined frequency of interest in the frequency intensity P (f) for each frequency f as the determination data is not limited to a specific frequency, and an abnormality / failure occurs in the photovoltaic power generation facility to be diagnosed. Appropriately set to an appropriate frequency corresponding to the frequency of the sound that appears, disappears, or changes when it occurs, or is considered to be generated, disappeared, or changed based on the results of prior analysis and examination as necessary .

  The predetermined frequency of interest may be a specific frequency f [Hz] or a frequency band centered on a specific frequency f [Hz]. In addition, the entire frequency band targeted for collection in the process of S1 or the entire frequency band targeted for calculation in the process of S2 may be set to a predetermined frequency.

  Further, the threshold value relating to the frequency intensity used in the method (1) is not limited to a specific value, and the volume of sound generated when an abnormality or failure occurs in the photovoltaic power generation facility to be diagnosed ( In other words, sound pressure, spectral values) and appropriate values corresponding to the volume of sound that is generated under normal conditions are appropriately set based on the results of prior analysis and examination as necessary. .

  Specifically, for example, a sound is collected when a component or mechanism of the same type and type as that used in a photovoltaic power generation facility to be diagnosed is intentionally broken and the component or mechanism is broken. The sound frequency or frequency band and the frequency intensity when the components / mechanisms of the photovoltaic power generation equipment are broken by analyzing the spectrum value for each frequency component obtained from the sound data. Then, based on the frequency / frequency band and frequency intensity specified for the sound at the time of the failure, a predetermined frequency of interest is set, or a threshold value for frequency intensity is set. Also good.

  Alternatively, sound data is obtained by collecting sound in the normal state of the photovoltaic power generation facility itself to be diagnosed or in the normal state of the solar power generation facility of the same type or the same type as the photovoltaic power generation facility to be diagnosed. The spectrum value for each frequency component obtained for the data is analyzed to identify the frequency or frequency band and frequency intensity of the sound when the solar power generation facility is in a normal state, and the normal sound In consideration of the frequency / frequency band and frequency intensity specified with respect to, a predetermined frequency of interest may be set, or a threshold related to frequency intensity may be set.

  Of the frequency intensities P (f) for each frequency f as determination data, the predetermined frequency of interest in the method (1), or more specifically, for example, is as follows.

i) A frequency that is an integral multiple of the switching frequency in the power conditioner A frequency that is an integral multiple of the switching frequency in the conversion from DC power to AC power in the power conditioner (not shown) of the photovoltaic power generation facility to be diagnosed The frequency intensity P (f) of the determination data is used. In this case, only one integer multiple frequency may be used among the multiples of the switching frequency, or a plurality of integer multiple frequencies may be used.

ii) Frequency other than an integral multiple of the switching frequency in the power conditioner The judgment data of a frequency other than an integral multiple of the switching frequency at the time of conversion from DC power to AC power in the power conditioner of the photovoltaic power generation facility to be diagnosed The frequency intensity P (f) is used. In this case, only one frequency may be used among frequencies other than an integral multiple of the switching frequency, or a plurality of frequencies may be used.

  The frequency intensity P (f) in the above may be a value of the frequency intensity at a specific frequency f [Hz], or a predetermined frequency centered on a specific frequency f [Hz]. It may be a feature amount such as an average value or a variance value of frequency intensities in the band. In this case, the width of the frequency band as the predetermined frequency band (that is, the range expressed as the frequency f1 [Hz] to f2 [Hz]) is not limited to a specific size. Appropriate size is set in consideration of the results of prior analysis and examination. Based on the above, P (f) includes both the value of the frequency intensity at a specific frequency f and the feature quantity related to the frequency intensity in a predetermined frequency band centered on the frequency f (in other words, , Representing either).

  It should be noted that, for example, a suitable storage circuit is provided in the determination unit 3 so that the determination unit 3 can refer to the predetermined frequency value or frequency intensity of interest so that the determination unit 3 can read the threshold value. Is provided and stored in the memory circuit.

  Then, the frequency intensity at a predetermined frequency of interest in the determination data acquired regarding the photovoltaic power generation facility to be diagnosed is compared with a threshold value relating to a predetermined frequency intensity.

  Note that the predetermined frequency of interest may be one or plural. When focusing on a plurality of frequencies (including the frequency band as described above), for example, the first frequency fa is less than or equal to the threshold and the second frequency fb exceeds the threshold or the first When both the frequency fa and the second frequency fb exceed the threshold value, it is determined that an abnormality or failure has occurred in the photovoltaic power generation facility, while the second frequency fb is also applied to the first frequency fa. If the threshold value is less than or equal to the threshold value, it is determined that no abnormality or failure has occurred in the photovoltaic power generation facility. Whether or not a failure has occurred may be determined. As a precaution, the example given above focuses on the first and second frequencies, but it is also possible to focus on three or more frequencies.

  In addition, the occurrence of abnormalities / failures in photovoltaic power generation facilities, taking into account the continuity and discontinuity of the relationship between frequency intensity and threshold, which are grasped using judgment data at multiple points in time, at multiple points in time. The presence or absence of may be determined.

(2) A method of paying attention to frequency intensities at a plurality of points in time for a photovoltaic power generation facility to be diagnosed In this method, the reference data and the determination data for the photovoltaic power generation facility to be diagnosed are compared, and a predetermined one of these reference data Based on the difference between the frequency intensity of the frequency and the frequency intensity of the predetermined frequency in the determination data, it is determined whether an abnormality or failure has occurred in the photovoltaic power generation facility.

  The reference data is obtained with respect to sound data obtained by collecting sound generated from the photovoltaic power generation facility before starting the determination processing for the occurrence of abnormality / failure (that is, the above-described S1 and S2). Frequency intensity Po (f) at the frequency f [Hz] (in other words, combination data of the frequency f [Hz] and the frequency intensity Po (f)).

  The acquisition of the reference data is performed, for example, during the test operation of the photovoltaic power generation facility to be diagnosed or at the initial stage of full-scale operation as an actual machine. In this case, it is expected that the photovoltaic power generation facility is in a healthy and stable state, that is, it is expected that the photovoltaic power generation facility is in a normal state in which no abnormality or failure has occurred. By comparing with such reference data, the device status compared with the normal status is diagnosed.

  The acquisition of the reference data may be performed after the solar power generation facility is selected as a diagnosis target. In this case, since the photovoltaic power generation facility is operating although it cannot be said to be in the initial state, that is, the photovoltaic power generation facility is operating without any problem as a full-scale operation of the actual machine. By comparing with the data, the device state compared with the normal operation state is diagnosed.

  The reference data may be set individually for each photovoltaic power generation facility to be diagnosed, or may be set for each type / model of the photovoltaic power generation facility.

  Note that the combination data of the frequency f [Hz] and the frequency intensity Po (f) as the reference data can be referred to by the determination unit 3, in other words, for example, the determination unit 3 can read the combination data. An appropriate storage circuit is provided in the unit 3 and stored in the storage circuit.

  The predetermined frequency of interest among the frequency intensities Po (f) and P (f) for each frequency f as reference data and determination data is not limited to a specific frequency, and is a photovoltaic power generation facility to be diagnosed Based on the results of prior analysis and examination, if necessary, at an appropriate frequency corresponding to the frequency of the sound that appears, disappears, or changes when an abnormality or failure occurs in Is set as appropriate.

  The predetermined frequency of interest may be a specific frequency f [Hz] or a frequency band centered on a specific frequency f [Hz]. In addition, the entire frequency band targeted for collection in the process of S1 or the entire frequency band targeted for calculation in the process of S2 may be set to a predetermined frequency.

  Specifically, for example, the predetermined frequency of interest is set by the method described as the method of setting the predetermined frequency of interest in the above-described method (1), or is also noted in the above-described method (1). It is conceivable that i) and ii) mentioned as specific examples of the predetermined frequency are used.

  And the frequency intensity | strength Po (f) and P (f) in the predetermined | prescribed frequency of interest of the reference | standard data and determination data which were acquired regarding the photovoltaic power generation installation of diagnostic object are compared.

  As a result, when there is a difference between these two frequency intensities Po (f) and P (f), it is determined that an abnormality / failure has occurred in the photovoltaic power generation facility.

  The frequency intensities Po (f) and P (f) in the above may be values of frequency intensities at a specific frequency f [Hz], or center on a specific frequency f [Hz]. May be a feature quantity such as an average value or a variance value of frequency intensities in a predetermined frequency band. In this case, the width of the frequency band as the predetermined frequency band (that is, the range expressed as the frequency f1 [Hz] to f2 [Hz]) is not limited to a specific size. Appropriate size is set in consideration of the results of prior analysis and examination. Based on the above, Po (f) and P (f) are either the value of the frequency intensity at a specific frequency f or the feature quantity related to the frequency intensity in a predetermined frequency band centered on the frequency f. (In other words, it represents either one).

  Note that the predetermined frequency of interest (including the frequency band as described above) may be one or plural.

  As an index for determining whether or not there is a difference between the two frequency intensities Po (f) and P (f), for example, an absolute error (ie, | P (f) −Po (f) | ), Relative error (ie, | P (f) −Po (f) | / Po (f)), or ratio (ie, P (f) / Po (f) or Po (f) / P (f)) Etc. can be used. However, the determination index for the presence / absence of the difference is not limited to these, and another index may be used.

  When the index values as exemplified above are not more than a predetermined threshold corresponding to each index, there is no difference between the two frequency intensities Po (f) and P (f). On the other hand, if it is greater than the threshold, it is determined that there is a difference between the two frequency intensities Po (f) and P (f).

  The threshold value for each index is not limited to a specific value, and is appropriately set to an appropriate value in consideration of, for example, a prior analysis / consideration result.

  Further, only one type of index value is used, and it is determined whether there is a difference between the two frequency intensities Po (f) and P (f) by comparison with a threshold value related to the one type of index value. Alternatively, a difference between the two frequency intensities Po (f) and P (f) may be obtained by using a plurality of types of index values and comparing the threshold values with respect to each of the plurality of types of index values. It may be determined whether or not there is.

  Further, frequency intensities at a plurality of time points may be used for each of the reference data and the determination data. For example, the frequency intensity Po (f) at one point as reference data and the frequency intensity P (f) at multiple points as determination data are compared, or the frequency intensity Po (f at multiple points as reference data is compared. ) And frequency intensities P (f) at a plurality of time points as determination data may be compared. The difference between the two frequency intensities Po (f) and P (f) is taken into consideration between the Po (f) and P (f) after considering the continuity and discontinuity at a plurality of time points. It may be determined whether or not there is a difference.

  In addition, machine learning (also called pattern learning) may be used in determining whether or not an abnormality / failure has occurred in the photovoltaic power generation facility by comparing the reference data with the determination data.

  In this case, the frequency intensity Po (f) of the reference data and the frequency intensity P (f) of the determination data are used, or the feature amount obtained from the frequency intensity Po (f) and the frequency intensity P (f ) Is used, and the frequency intensity P (f) or the feature quantity related thereto is a pattern different from the frequency intensity Po (f) corresponding to the teacher data in machine learning or the feature quantity related thereto. It is sometimes determined that an abnormality or failure has occurred in the photovoltaic power generation facility.

  Further, instead of the reference data, the frequency intensity Pw () at the frequency f [Hz] obtained for the sound data obtained by collecting the sound generated in the state where the abnormality or failure occurs in the photovoltaic power generation facility. f) (in other words, combination data of the frequency f [Hz] and the frequency intensity Pw (f); referred to as “failure data”) may be used.

  In this case, the frequency intensity Pw (f) of the failure data and the frequency intensity P (f) of the determination data are used, or the feature amount obtained from the frequency intensity Pw (f) and the frequency intensity P (f ) Is used, and the frequency intensity P (f) or the feature quantity related thereto is the same as the frequency intensity Pw (f) corresponding to the teacher data in machine learning or the feature quantity related thereto (in other words, It is determined that an abnormality / failure has occurred in the photovoltaic power generation facility when the pattern is similar or not.

(3) Method of paying attention to frequency intensity relating to each of a plurality of photovoltaic power generation facilities In this method, a plurality of photovoltaic power generation facilities including at least a photovoltaic power generation facility to be diagnosed (that is, a plurality of all of which are diagnostic targets) Each of the determination data of each of the plurality of determination data) is compared with each other, and one of the determination data when the frequency intensity of a predetermined frequency among these determination data is compared side by side. Based on the difference between the frequency intensity and the frequency intensity of other (in other words, the remaining) determination data, is there any abnormality or failure in the photovoltaic power generation facility from which the one determination data is obtained? It is determined whether or not.

  Specifically, the “plurality of units” relating to the photovoltaic power generation facility in this method is three or more units.

  In the case of this method, the process of S1 is performed in each of the plurality of solar power generation facilities and the process of S2 is performed for each of the sound data for each solar power generation facility, and corresponds to each solar power generation facility. A plurality of frequency intensities Pn (f) (where n is an identifier assigned to each photovoltaic power generation facility in order to distinguish a plurality of photovoltaic power generation facilities) (Representing an identifier given to the photovoltaic power generation facility from which sound data relating to the frequency intensity has been acquired) is input to the determination unit 3.

  The predetermined frequency of interest among the frequency intensities Pn (f) for each frequency f as the determination data is not limited to a specific frequency, and when an abnormality or failure occurs in the photovoltaic power generation facility to be diagnosed If necessary, the frequency is appropriately set based on the results of prior analysis and examination, etc., as appropriate, corresponding to the frequency of the sound that appears, disappears, or changes or is considered to be generated, disappeared, or changed.

  The predetermined frequency of interest may be a specific frequency f [Hz] or a frequency band centered on a specific frequency f [Hz]. In addition, the entire frequency band targeted for collection in the process of S1 or the entire frequency band targeted for calculation in the process of S2 may be set to a predetermined frequency.

  Specifically, for example, the predetermined frequency of interest is set by the method described as the method of setting the predetermined frequency of interest in the above-described method (1), or is also noted in the above-described method (1). It is conceivable that i) and ii) mentioned as specific examples of the predetermined frequency are used.

  And the frequency intensity | strength Pn (f) in the predetermined | prescribed frequency of interest of the determination data acquired regarding each of several photovoltaic power generation equipment is compared with each other side by side.

  As a result, when there is a difference between the frequency intensity of one determination data and the frequency intensity of other (remaining) determination data, the photovoltaic power generation facility from which the one determination data is acquired It is determined that an abnormality or failure has occurred.

  The frequency intensity Pn (f) in the above may be a value of the frequency intensity at a specific frequency f [Hz], or a predetermined frequency centered on a specific frequency f [Hz]. It may be a feature amount such as an average value or a variance value of frequency intensities in the band. In this case, the width of the frequency band as the predetermined frequency band (that is, the range expressed as the frequency f1 [Hz] to f2 [Hz]) is not limited to a specific size. Appropriate size is set in consideration of the results of prior analysis and examination. Based on the above, Pn (f) includes both the value of the frequency intensity at a specific frequency f and the feature quantity related to the frequency intensity in a predetermined frequency band centered on the frequency f (in other words, , Representing either).

  Note that the predetermined frequency of interest (including the frequency band as described above) may be one or plural.

  The method for determining whether there is a difference between one frequency strength and another (remaining) frequency strength is not limited to a specific method. The determination may be made by comparing the frequency intensity value with a feature quantity such as an average value of the other frequency intensity, or one frequency intensity value and one of the other frequency intensity values. You may make it judge after comparing each individually. The concept of the determination index (index value) for the presence / absence of differences in the method (3) and the threshold value for each determination index is based on the determination index (index value) and the threshold value for each determination index in the method (2) described above. It is the same as the way of thinking.

  In addition, for each of the determination data for each of the plurality of photovoltaic power generation facilities, the frequency intensities Pn (f) at a plurality of times may be used to perform comparison at a plurality of times. Then, taking into consideration the continuity and discontinuity of a difference between a certain frequency strength and other frequency strengths at a plurality of points in time, between these certain frequency strengths and other frequency strengths. It may be determined whether or not there is a difference.

  Also, machine learning (pattern learning) is applied to the judgment data for each of the multiple photovoltaic power generation facilities, and an abnormality or failure occurs in the photovoltaic power generation equipment for which judgment data with a pattern different from other patterns is acquired. You may make it determine with having carried out.

  The above is description of (1) thru | or (3) regarding the method of determination of the presence or absence of generation | occurrence | production of abnormality / failure in the photovoltaic power generation equipment by the determination part 3. FIG.

  If it is not determined that an abnormality / failure has occurred in the photovoltaic power generation facility to be diagnosed (S3: No), the diagnosis regarding the photovoltaic power generation facility is terminated or necessary. Accordingly, the process returns to the process of S1 and the processes of S1 to S3 are repeatedly performed.

  On the other hand, when it is determined that an abnormality / failure has occurred in the photovoltaic power generation facility to be diagnosed (S3: Yes), the determination unit 3 causes the abnormality / failure in the photovoltaic power generation facility to be diagnosed. A predetermined signal (referred to as an “abnormality notification signal”) for notifying that the error has occurred is output.

  When an abnormality notification signal is output in the process of S3, an alarm is issued (S4).

  Specifically, for example, an abnormality notification signal is output from the determination unit 3 of the abnormality diagnosis device 10 of the solar power generation facility to the alarm output unit 4, and thereby, the alarm output unit 4 externally (specifically, for example, solar Warnings are issued to workers and managers related to photovoltaic power generation facilities.

  In accordance with the abnormality notification signal from the determination unit 3, the alarm output unit 4 emits a sound by a speaker, a buzzer, or the like, lights a light by a warning light or a rotating light, or warns a display or the like. An alarm is issued by displaying a message or vibrating with a vibration function.

  Here, the determination process for the occurrence of abnormality / failure in the photovoltaic power generation facility may be performed, for example, regularly or irregularly as maintenance inspections at predetermined intervals, or continuously. It may be implemented as a constant monitoring.

  Moreover, the above-described abnormality diagnosis device 10 for photovoltaic power generation equipment is configured as a device having a portable size with all the parts being integrated, or installed in or near the photovoltaic power generation equipment to be diagnosed. Alternatively, each unit may be distributed and installed at a plurality of locations.

  Moreover, each part which needs to be connected among each part which comprises the abnormality diagnosis apparatus 10 of photovoltaic power generation equipment seems to be able to transmit / receive (namely, input / output) signals, such as data and a control command. Is electrically connected.

  Specifically, when each part which comprises the abnormality diagnosis apparatus 10 of a solar power generation facility is comprised as an integral thing, each part which needs a connection is connected suitably by signal lines, such as a bus | bath, for example.

  Moreover, when each part which comprises the abnormality diagnosis apparatus 10 of a solar power generation facility is comprised as a different thing (Furthermore, when each part is disperse | distributed and installed in several places, each part which needs a connection) As appropriate, for example, it is connected by a wired signal transmission / reception mechanism in which cables laid and connected to each other are used, or by a wireless signal transmission / reception mechanism in which a wireless signal transceiver connected to each is used Or these signal transmission / reception mechanisms are combined and connected.

<When an abnormality diagnosis program for a photovoltaic power generation facility is executed on a computer>
The above-described conversion unit 2, determination unit 3, and alarm output unit 4 may be realized by the computer by executing an abnormality diagnosis program for the photovoltaic power generation facility on the computer.

  FIG. 3 shows the overall configuration of the computer 19 for executing the abnormality diagnosis program 17 for the photovoltaic power generation facility.

  The computer 19 includes a control unit 11, a storage unit 12, an input unit 13, a display unit 14, and a memory 15, which are connected to each other by a signal line such as a bus.

  The control unit 11 performs control related to overall control of the computer 19 and diagnosis / detection of abnormality / failure of the photovoltaic power generation facility by the abnormality diagnosis program 17 of the photovoltaic power generation facility stored in the storage unit 12, For example, a CPU (Central Processing Unit).

  The storage unit 12 is a device that can store at least data and programs, and is, for example, a hard disk.

  The input unit 13 is an interface (that is, an information input mechanism) for giving at least an operator's command and various information to the control unit 11, and is, for example, a keyboard, a mouse, or a touch panel. For example, a plurality of types of interfaces such as a keyboard and a mouse may be provided as the input unit 13.

  The display unit 14 performs drawing / display of characters, figures, images, and the like under the control of the control unit 11 and is, for example, a display.

  The memory 15 serves as a memory space that is a work area when the control unit 11 executes various controls and operations, and is, for example, a RAM (abbreviation of Random Access Memory).

  In addition, in the computer 19, specifically, for example, a wired signal transmission / reception mechanism as described above so that the sound detection unit 1 can transmit and receive (that is, input and output) signals such as data and control commands. Or a wireless signal transmission / reception mechanism or a combination of these signal transmission / reception mechanisms.

  The control unit 11 of the computer 19 receives sound data output from the sound detection unit 1 that collects sound generated from the solar power generation facility by executing the abnormality diagnosis program 17 of the solar power generation facility. Data receiving unit 11a that performs the process of receiving the noise, conversion unit 11b that performs the process of calculating the spectrum value for each frequency component of the sound data, and the occurrence of an abnormality or failure in the photovoltaic power generation facility using the spectrum value for each frequency component A determination unit 11c that performs processing to output an abnormality notification signal when it is determined that an abnormality / failure has occurred, and an alarm output unit 11d that performs processing to issue an alarm according to the abnormality notification signal; Is configured.

  The sound detection unit 1 performs the above-described processing of S1 and outputs sound data. The sound data is input to the data receiving unit 11a of the computer 19, stored in the memory 15, and stored in the memory 15. The sound data is used, the conversion unit 11b performs the same process as the conversion unit 2 described above as the process of S2, and the determination unit 11c performs the same process as the determination unit 3 described above as the process of S3. When it is determined that an abnormality or failure has occurred in the solar power generation facility, an abnormality notification signal is output, and the alarm output unit 11d performs the same process as the alarm output unit 4 described above as the process of S4. .

  The sound data may be input to the data receiving unit 11a via a storage medium in which the sound data output from the sound detection unit 1 is recorded.

  Further, the computer 19 may not include the alarm output unit 11d. In this case, the computer 19 outputs an abnormality notification signal to an alarm output unit provided separately from the computer 19 or controls the operation of the photovoltaic power generation facility to be diagnosed. An abnormality notification signal may be output to the control device / control unit.

<Determining whether or not an abnormality or failure has occurred focusing on the bypass diodes of solar power generation facilities>
While examining the method of abnormality diagnosis of solar power generation equipment using sound, the present inventors have measured the surface of some solar battery clusters 21 as a simulation of failure of the solar battery cluster 21 in the solar power generation equipment. (In other words, a part of the surface of the solar cell panel) is covered to block sunlight, thereby reducing the generated power of the solar cell cluster 21 and allowing the current to flow through the bypass diode 23. In the state where the power is collected from the solar cell cluster 21 and the current flows through the bypass diode 23, a sound is generated from the bypass diode 23, and the sound is detected by detecting the sound. It was found that it was possible to determine the presence or absence of abnormalities or failures in solar power generation facilities.

  In this case, as an aspect of installation of the sound detection unit 1, an operation sound generated from the bypass diode 23 when current flows through the bypass diode 23 of the photovoltaic power generation facility to be diagnosed (sound collection, sound collection) Appropriate locations and installation / fixing methods are selected as appropriate.

  The sound detection unit 1 may be arranged so as to be separated from the outside of the casing or case covering the bypass diode 23 or in contact with the outer surface of the casing or case, or You may make it arrange | position inside the housing | casing, case, etc. which cover the bypass diode 23. FIG.

  Depending on the actual photovoltaic power generation facility (solar cell module 20), the bypass diodes 23A, 23B, 23C,..., 23X may be disposed separately from the case where the bypass diodes 23A, 23B, 23C,. There is a case. When a plurality of bypass diodes 23 are arranged in one place or a plurality of places, the one place is set as a sound collection target (in other words, a sampling unit), or each of the plurality of places is set as a sound collection unit. It is a collection target (collection unit). On the other hand, when a plurality of bypass diodes 23 are individually disposed, each of the plurality of bypass diodes 23 is a sound collection target (collection unit).

  In addition, for example, a permanent magnet or an electromagnet may be applied to the bypass diode 23 in the photovoltaic power generation equipment, for example, so that a magnetic field is applied from the outside, or a magnetic material such as an iron plate is allowed to approach. May be.

  And as a process corresponding to S1 in the above-mentioned description, the sound generated from the bypass diode 23 of the photovoltaic power generation facility to be diagnosed by the sound detection unit 1 as sound (in other words, sound pressure or sound pressure level) It is collected, amplified as necessary, converted into a digital signal, and output as sound data.

  Next, as processing corresponding to S2 in the above description, the conversion unit 2 calculates the frequency intensity of the sound data for the bypass diode 23, and the calculated frequency intensity P (f) is the frequency f [Hz]. Are output as determination data (that is, combination data of frequency f [Hz] and frequency intensity P (f)).

  Next, as a process corresponding to S3 in the above description, the determination unit 3 uses the determination data for the bypass diode 23 to determine whether or not an abnormality / failure has occurred in the photovoltaic power generation facility.

  The methods (1) to (3) in the above description can also be used in determining whether or not an abnormality / failure has occurred in the photovoltaic power generation facility when focusing on the bypass diode 23.

  When the method (1) in the above description is used, the photovoltaic power generation facility is abnormal based on the strength of the frequency intensity of the predetermined frequency in the determination data related to the bypass diode 23 of the photovoltaic power generation facility to be diagnosed. -It is determined whether or not a failure has occurred.

  When paying attention to the bypass diode 23, specifically, when the frequency intensity of the predetermined frequency in the determination data exceeds a predetermined threshold (in other words, the sound of the predetermined frequency has a predetermined level). It is determined that an abnormality / failure has occurred in the photovoltaic power generation facility.

  In the above case, no current flows through the bypass diode 23 when the photovoltaic power generation equipment is normal, so that no sound is generated or hardly generated at a predetermined frequency (that is, no sound is collected or hardly collected). However, the reason why a sound having a loudness exceeding a predetermined threshold is collected at the predetermined frequency is because an abnormality / failure has occurred (specifically, for example, occurrence of an abnormality / failure in the solar cell cluster 21). Therefore, it is estimated that the current flows through the bypass diode 23).

  However, even when a part of the solar battery cluster 21 or the solar battery cell 22 enters the shade, the power generation from the solar battery cluster 21 including the part of the solar battery cluster 21 or the part of the solar battery cell 22 is performed. Since the power output is reduced and a current flows through the bypass diode 23, it is confirmed that the solar battery cluster 21 and the solar battery cell 22 are not in the shade.

  Here, the predetermined frequency focused in the method (1) of the frequency intensities P (f) for each frequency f as the determination data is limited to a specific frequency even when focusing on the bypass diode 23. Rather, based on the results of prior analysis and examination, if necessary, an appropriate frequency corresponding to the frequency of the sound generated from the bypass diode 23 when an abnormality or failure occurs in the photovoltaic power generation facility to be diagnosed. Set as appropriate.

  Further, the threshold relating to the frequency intensity used in the method (1) is not limited to a specific value when focusing on the bypass diode 23, and an abnormality / failure occurs in the photovoltaic power generation facility to be diagnosed. Is appropriately set to an appropriate value corresponding to the volume of sound generated from the bypass diode 23 (in other words, sound pressure, spectral value) based on the results of prior analysis and examination as necessary.

  Specifically, for example, the surface of the solar cell cluster 21 (or solar cell 22) of a part of the photovoltaic power generation facility to be diagnosed (in other words, part of the surface of the solar cell panel) is covered with the sun. Sound generated when the current generated in the bypass diode 23 is reduced by blocking the light to reduce the generated power of the part of the solar cell clusters 21 and sound data is acquired, or the sun to be diagnosed Sound when current is flowing through the same kind and type of bypass diode 23 used in the photovoltaic power generation facility is collected and sound data is obtained, and the spectrum value for each frequency component obtained for the sound data is obtained. Sound generated when the current flows through the bypass diode 23 by analysis (hereinafter also referred to as “operation noise of the bypass diode 23”) Frequency or frequency band and frequency intensity are specified, and based on the frequency / frequency band and frequency intensity specified with respect to the operation sound of the bypass diode 23, a predetermined frequency of interest is set, or the frequency intensity Or a threshold value may be set.

  Of the frequency intensities P (f) for each frequency f as the determination data, as the predetermined frequency of interest in the method (1), or when paying attention to the bypass diode 23, attention is also paid to in the method of (1) above. I) and ii) given as specific examples of the predetermined frequency may be used.

  Note that the frequency of sound generated from the bypass diode 23 when a current is flowing through the bypass diode 23 varies depending on the type and model of the photovoltaic power generation facility. Specifically, there was a case where a sound having a frequency of 4 kHz was generated in the above test.

  When focusing on the bypass diode 23, the frequency intensity P (f) in the above may be a value of the frequency intensity at a specific frequency f [Hz] or a predetermined value centered on a specific frequency f [Hz]. It may be a feature quantity such as an average value or variance value of frequency intensity in the frequency band, and the predetermined frequency of interest may be a specific frequency f [Hz] or centered on a specific frequency f [Hz]. In the above method (1), the frequency band to be used, the predetermined frequency of interest may be one or more, and the determination data at a plurality of time points may be used. It is the same as the description.

  Further, when the method (2) in the above description is used, the reference data and the determination data regarding the bypass diode 23 of the photovoltaic power generation facility to be diagnosed are compared, and a predetermined frequency of the reference data is compared. Based on the difference between the frequency intensity and the frequency intensity of the predetermined frequency in the determination data, it is determined whether an abnormality / failure has occurred in the photovoltaic power generation facility.

  When focusing on the bypass diode 23, specifically, Po (f) <P between the frequency intensity Po (f) of the reference data and the frequency intensity P (f) of the determination data at a predetermined frequency. When the relationship (f) is established and there is a difference, it is determined that an abnormality / failure has occurred in the photovoltaic power generation facility. In this case, the index for determining whether or not there is a difference between the two frequency intensities Po (f) and P (f) and the concept of the threshold value for each index are described in the above method (1). It is the same as the description.

  In the above case, no current flows through the bypass diode 23 when the photovoltaic power generation equipment is normal, so that no sound is generated or hardly generated at a predetermined frequency (that is, no sound is collected or hardly collected). However, the difference between the reference data based on the normal state and the determination data at the time of diagnosis occurs at the predetermined frequency because of an abnormality or failure (specifically, for example, a solar cell cluster) It is estimated that the current flows through the bypass diode 23 due to the occurrence of an abnormality / failure at 21).

  However, even when a part of the solar battery cluster 21 or the solar battery cell 22 enters the shade, the power generation from the solar battery cluster 21 including the part of the solar battery cluster 21 or the part of the solar battery cell 22 is performed. Since the power output is reduced and a current flows through the bypass diode 23, it is confirmed that the solar battery cluster 21 and the solar battery cell 22 are not in the shade.

  Here, the predetermined frequency to be noted in the method (2) of the frequency intensities Po (f) and P (f) for each frequency f as the reference data and the determination data may be focused on the bypass diode 23. The frequency is not limited to a specific frequency, and an appropriate frequency corresponding to the frequency of the sound generated from the bypass diode 23 when an abnormality or failure occurs in the photovoltaic power generation facility to be diagnosed is set in advance as necessary. It is set as appropriate based on the results of analysis and examination.

  Specifically, for example, the frequency or frequency band of the bypass diode 23 and the frequency intensity are specified in the same manner as in the case where the method (1) is used with attention paid to the bypass diode 23, and A predetermined frequency of interest may be set based on the frequency / frequency band and frequency intensity specified for the operating sound of the bypass diode 23.

  The reference frequency or the determination data is the above-described frequency intensity Po (f), P (f) of the frequency f as a predetermined frequency of interest in the method (2), or when the bypass diode 23 is of interest. I) and ii) listed as specific examples of the predetermined frequency to be noted in the method (1) may be used.

  Further, when focusing on the bypass diode 23, the frequency intensities Po (f) and P (f) in the above may be values of frequency intensities at a specific frequency f [Hz] or a specific frequency f [Hz]. ] May be a feature value such as an average value or a variance value of frequency intensity in a predetermined frequency band centered on the center, and a predetermined frequency of interest may be a specific frequency f [Hz] The frequency band centered on the frequency f [Hz] may be used, and the predetermined frequency of interest may be one or more, as described in the above method (1).

  Further, when paying attention to the bypass diode 23, a determination index (index value) of whether or not there is a difference when it is determined whether or not there is a difference between the two frequency intensities Po (f) and P (f) It is the same as the description in the method (2) above that the concept of the threshold values for each judgment index and the frequency intensity at a plurality of points in time may be used for each of the reference data and the judgment data. .

  In addition, machine learning may be used in determining whether or not an abnormality or failure has occurred in a photovoltaic power generation facility by comparing reference data with determination data, and failure data is used instead of reference data. This may also be the same as described in the above method (2).

  Further, when the method (3) in the above description is used, the method is provided for each of the plurality of bypass diodes 23 provided in the photovoltaic power generation facility to be diagnosed or each of the plurality of solar power generation facilities. The determination data for each bypass diode 23 is compared with each other, and the frequency intensity of a predetermined frequency among these determination data is compared side by side with the frequency intensity of one determination data and the other (in other words, Based on the difference between the frequency intensity of the remaining determination data, an abnormality is detected in a component related to the bypass diode 23 (specifically, for example, the solar cell cluster 21) from which the certain determination data is acquired. -It is determined whether or not a failure has occurred.

  When attention is paid to the bypass diode 23, specifically, between the frequency intensity Pa (f) of one determination data at a predetermined frequency and the frequency intensity Pr (f) of other determination data ( However, if there is a relationship of Pa (f)> Pr (f) and there is a difference, it is related to the bypass diode 23 from which the one determination data is acquired. It is determined that an abnormality or failure has occurred in the component to be operated. In this case, an index for determining whether or not there is a difference between the two frequency intensities Pa (f) and Pr (f) and a concept of a threshold for each index are described in the above method (1). It is the same as the description.

  In the above case, no current flows through the bypass diode 23 when the photovoltaic power generation equipment is normal, so that no sound is generated or hardly generated at a predetermined frequency (that is, no sound is collected or hardly collected). However, the difference between one determination data and the other (remaining) determination data occurs at the predetermined frequency in relation to the bypass diode 23 from which the one determination data is acquired. It is presumed that this is because an abnormality / failure has occurred in a component or the like (specifically, for example, a current has flown through the bypass diode 23 due to the occurrence of an abnormality / failure in the solar cell cluster 21).

  However, even when a part of the solar battery cluster 21 or the solar battery cell 22 enters the shade, the power generation from the solar battery cluster 21 including the part of the solar battery cluster 21 or the part of the solar battery cell 22 is performed. Since the power output is reduced and a current flows through the bypass diode 23, it is confirmed that the solar battery cluster 21 and the solar battery cell 22 are not in the shade.

  Here, the predetermined frequency of interest in the method (3) of the frequency intensities Pa (f) and Pr (f) for each frequency f as the determination data is a specific frequency even when the bypass diode 23 is of interest. It is not limited to the above, and an appropriate frequency corresponding to the frequency of the sound generated from the bypass diode 23 when abnormality or failure occurs in the photovoltaic power generation facility to be diagnosed is analyzed and examined in advance as necessary. It is set as appropriate based on the results.

  Specifically, for example, the frequency or frequency band of the bypass diode 23 and the frequency intensity are specified in the same manner as in the case where the method (1) is used with attention paid to the bypass diode 23, and A predetermined frequency of interest may be set based on the frequency / frequency band and frequency intensity specified for the operating sound of the bypass diode 23.

  Of the frequency intensities Pa (f) and Pr (f) for each frequency f as determination data, the above-mentioned (1) can be used as a predetermined frequency to be focused on in the method (3) or when the bypass diode 23 is focused. )), I) and ii) listed as specific examples of the predetermined frequency of interest may be used.

  Further, when focusing on the bypass diode 23, the frequency intensities Pa (f) and Pr (f) in the above may be values of frequency intensities at a specific frequency f [Hz] or a specific frequency f [Hz]. ] May be a feature value such as an average value or a variance value of frequency intensity in a predetermined frequency band centered on the center, and a predetermined frequency of interest may be a specific frequency f [Hz] The frequency band centered on the frequency f [Hz] may be used, and the predetermined frequency of interest may be one or more, as described in the above method (1).

  Further, when paying attention to the bypass diode 23, a method for determining whether or not there is a difference when determining whether or not there is a difference between the frequency intensities Pa (f) and Pr (f) and a determination index for determining whether or not there is a difference ( (Index value) and the concept of the threshold value for each of these judgment indices, and the fact that the frequency intensities at a plurality of time points may be used for each of a plurality of determination data is the same as described in the method (3) above. It is.

  Further, the machine learning (pattern learning) may be applied to the determination data for each of the plurality of photovoltaic power generation facilities, as in the description of the method (3) described above.

  The above is description of the method of (1) thru | or (3) regarding the method of the presence or absence of generation | occurrence | production of abnormality / failure in a solar power generation facility by the determination part 3 when paying attention to the bypass diode 23. FIG.

  And the processing (specifically, S3: No, S3: Yes, and S4) after the determination of the presence / absence of occurrence of an abnormality / failure focusing on the bypass diode 23 is the same as described above.

<Inspection of bypass diode>
In the determination of whether or not an abnormality / failure has occurred focusing on the above-described bypass diode, when the frequency intensity of the determination data changes or fluctuates in the process of S3, for example, a bypass occurs because an abnormality / failure has occurred in the solar cell cluster 21. Since current flows through the diode 23, it is determined that an abnormality or failure has occurred in the photovoltaic power generation facility.

  With regard to this process, when the bypass diode 23 provided in the photovoltaic power generation facility to be diagnosed has failed, for example, even if an abnormality or failure has occurred in the solar cell cluster 21, a current flows through the bypass diode 23. Does not flow, so the frequency intensity of the judgment data does not change or fluctuate, so it cannot be judged that an abnormality / failure has occurred despite the occurrence of an abnormality / failure in the photovoltaic power generation facility. .

  For this reason, by detecting whether or not the bypass diode 23 itself has failed, it is possible to prevent a detection failure of occurrence of an abnormality / failure in the photovoltaic power generation facility.

  Therefore, the surface of the solar cell cluster 21 (in other words, the surface of the solar cell panel) is covered in a state where no sound exceeding the predetermined threshold is generated from the bypass diode 23 (in other words, not collected). Sound is collected after the generated power of the solar cell cluster 21 is reduced by blocking the sunlight so that a current flows through the bypass diode 23.

  When the sound exceeding the predetermined threshold is generated from the bypass diode 23 in the above situation (in other words, collected), it is determined that the bypass diode 23 has not failed. If no sound exceeding the predetermined threshold value is generated from the bypass diode 23 (in other words, not collected), it is determined that the bypass diode 23 has failed.

  In this way, by checking the bypass diode 23 itself, it is possible to more reliably determine whether or not an abnormality / failure has occurred in the photovoltaic power generation facility.

  Specifically, for example, the inspection of the bypass diode 23 itself is periodically performed independently, and it is determined whether or not the abnormality or failure of the photovoltaic power generation facility has occurred, or the abnormality of the photovoltaic power generation facility. It is conceivable that the inspection of the bypass diode 23 itself is performed together with the determination of whether or not a failure has occurred.

  In addition, the operation for intentionally flowing the current to the bypass diode 23 is limited to covering the surface of the solar cell cluster 21 as described above as long as the current flow in the bypass diode 23 can be controlled. Is not to be done.

<Determining whether or not an abnormality or failure has occurred by injecting a current of a predetermined frequency>
In the present invention, the process (S1) in which the sound generated from the solar power generation facility is collected is a circuit (specifically, a plurality of solar cell modules 20 and solar cell clusters 21) that are associated with the solar power generation facility. It may be performed while injecting a current of a predetermined frequency into a circuit in which the solar cells 22 are connected in series.

  Specifically, for example, in a state where a current of a predetermined frequency is continuously injected or intermittently injected from a position 25 in the circuit configuration diagram of the solar cell module 20 illustrated in FIG. It is conceivable to collect sound generated from the photovoltaic power generation facility. In this case, it is conceivable that the predetermined frequency of interest in the above methods (1) to (3) is set to the predetermined frequency of the current injected into the circuit associated with the photovoltaic power generation facility.

  Here, the predetermined frequency of the current injected into the circuit associated with the photovoltaic power generation facility is not limited to a specific frequency, and an appropriate frequency is appropriately selected. For example, as an example only, when the photovoltaic power generation facility to be diagnosed is linked to a power transmission / distribution system, a frequency different from the commercial frequency related to the system can be selected.

  In this case, the abnormality diagnosis device 10 for the photovoltaic power generation facility supplies a current transformer for injecting current into a circuit associated with the photovoltaic power generation facility, and supplies a current having a predetermined frequency to the current transformer. You may make it be comprised as what further has a power supply part. Alternatively, instead of preparing a separate current transformer independent of the photovoltaic power generation facility, a part of the function / mechanism of the photovoltaic power generation facility is used to inject a current of a predetermined frequency. Also good. Specifically, for example, the software of the power conditioner (system connection inverter) may be changed so that a current of a predetermined frequency component is superimposed.

<Identification of abnormality / failure types>
In the present invention, in addition to the process for determining whether or not an abnormality or failure has occurred in the photovoltaic power generation facility to be diagnosed, when an abnormality or failure is detected, the type of abnormality / failure identification process is performed. good.

  When the type of abnormality / failure is identified, specifically, for example, the frequency intensity at the frequency f [Hz] as attribute data indicating what frequency component the spectrum value becomes large for each type of abnormality / failure. (Referred to as “abnormal sound data”) is prepared in advance, the determination data obtained in the process of S2 is compared with the abnormal sound data, and the type of abnormality / failure is based on the degree of similarity between the determination data and the abnormal sound data Is identified.

  Note that the method for evaluating the degree of similarity between the judgment data and abnormal sound data is not limited to a specific method, and the degree of similarity / correlation of features of a plurality of data groups is judged or measured. An appropriate technique to be obtained is appropriately selected.

  According to the abnormality diagnosis method, abnormality diagnosis apparatus, and abnormality diagnosis program for a photovoltaic power generation facility having the above configuration, the occurrence of an abnormality / failure in the photovoltaic power generation facility by collecting sound generated from the photovoltaic power generation facility. Therefore, it is possible to make a diagnosis while the solar power generation facility performs normal operation, that is, stop the operation of the solar power generation facility, disconnect a part of the solar power generation facility, or Diagnosis can be performed without making direct electrical contact with the photovoltaic power generation equipment (that is, connection to the equipment circuit), so that the diagnosis of the photovoltaic power generation equipment can be performed appropriately and easily at any time. As a result, it is possible to improve the usefulness as a method for detecting an abnormality or failure of a photovoltaic power generation facility.

  According to the abnormality diagnosis method, abnormality diagnosis apparatus, and abnormality diagnosis program for a photovoltaic power generation facility having the above configuration, the occurrence of an abnormality / failure in the photovoltaic power generation facility based on the sound generated from the photovoltaic power generation facility. Therefore, it is difficult to detect the change in the output of the generated power from the solar power generation facility to the outside (for example, the bypass diode works to Abnormalities / failures that are not manifested as changes in output) can be captured, which makes it possible to prevent the detection of abnormalities / failures in solar power generation facilities, and in turn, It is possible to improve the usefulness and reliability as a failure detection method.

  According to the abnormality diagnosis method, abnormality diagnosis apparatus, and abnormality diagnosis program for photovoltaic power generation equipment having the above-described configuration, the sound generated from each of the parts and parts of the photovoltaic power generation equipment is individually collected. If this is done, it will be possible to easily identify the location / part where the failure has occurred, and thus improve the usefulness as a detection method for abnormalities / failures in photovoltaic power generation facilities. It becomes possible to plan.

  Although the above-described embodiment is an example of a preferred embodiment for carrying out the present invention, the embodiment of the present invention is not limited to the above-described embodiment, and the present invention is not deviated from the gist of the present invention. Various modifications can be made.

  For example, in the above-described embodiment, the present invention is applied to the solar cell module 20 whose circuit configuration is shown in FIG. 4, but the configuration mode of the solar cell module to which the present invention can be applied is that in the above-described embodiment. It is not limited to. The present invention is characterized by collecting sound generated from the photovoltaic power generation facility, and can be applied to various photovoltaic power generation facilities as long as the condition that the sound of the facility can be collected is satisfied. .

  In the above-described embodiment, an alarm is issued according to an abnormality notification signal as an abnormality diagnosis method for the photovoltaic power generation facility (S4), and the alarm output unit 4 is provided as the abnormality diagnosis device 10 for the photovoltaic power generation facility. The alarm output unit 11d is configured in the control unit 11 of the computer 19 by executing the abnormality diagnosis program 17 of the photovoltaic power generation facility. The provision of 11d is not an essential configuration in the present invention, and various methods of using the determination result that abnormality / failure has occurred in the photovoltaic power generation facility to be diagnosed have been studied and variously These devices and apparatuses may be used in combination.

  Since the abnormality diagnosis technology according to the present invention can accurately diagnose and detect abnormality / failure in a photovoltaic power generation facility, the utility value is useful in fields such as power generation, power transmission / distribution performed by the photovoltaic power generation facility, for example. Is expensive.

DESCRIPTION OF SYMBOLS 1 Sound detection part 2 Conversion part 3 Judgment part 4 Alarm output part 10 Abnormality diagnostic apparatus 11 of solar power generation equipment 11 Control part 11a Data receiving part 11b Conversion part 11c Determination part 11d Alarm output part 12 Storage part 13 Input part 14 Display part 15 Memory 17 Abnormality diagnosis program for solar power generation equipment 19 Computer 20 Solar cell module 21 Solar cell cluster 21A, 21B, 21C Solar cell cluster 22 Solar cell 23 Bypass diode 23A, 23B, 23C Bypass diode

Claims (13)

  Spectral values for each frequency component are calculated for the sound data obtained by collecting the sound generated from the solar power generation facility, and the occurrence of an abnormality / failure in the solar power generation facility using the spectrum value for each frequency component. An abnormality diagnosis method for a photovoltaic power generation facility, characterized in that the presence or absence of a solar power generation facility is determined.   Spectral values for each frequency component are calculated for each of the sound data acquired by acquiring sounds generated from the photovoltaic power generation facilities at a plurality of points in time, and the spectrum values for the frequency components at the plurality of points in time are used to calculate the sunlight. An abnormality diagnosis method for a photovoltaic power generation facility, characterized in that it is determined whether or not an abnormality or failure has occurred in the power generation facility.   Spectral values for each frequency component are calculated for each of the sound data collected and acquired from multiple solar power generation facilities including at least the solar power generation facilities to be diagnosed. An abnormality diagnosis method for a photovoltaic power generation facility, wherein the spectrum value for each frequency component is used to determine whether or not an abnormality or failure has occurred in the photovoltaic power generation facility to be diagnosed.   The method for diagnosing an abnormality in a solar power generation facility according to any one of claims 1 to 3, wherein a sound generated from a bypass diode is collected as a sound generated from the solar power generation facility.   The spectrum value for each frequency component is a spectrum value of a frequency that is an integer multiple of a switching frequency in a power conditioner of the photovoltaic power generation facility or a spectrum value of a frequency other than an integer multiple of the switching frequency. Item 6. A method for diagnosing abnormality of a photovoltaic power generation facility according to any one of Items 1 to 3.   The method for diagnosing an abnormality in a solar power generation facility according to any one of claims 1 to 3, wherein a magnetic field is applied to the solar power generation facility or a magnetic material is approached. .   Means for collecting sound generated from solar power generation equipment and outputting sound data; means for calculating a spectral value for each frequency component of the sound data; and the solar power generation using the spectral value for each frequency component An apparatus for diagnosing abnormality in a photovoltaic power generation facility, comprising means for determining whether or not an abnormality or failure has occurred in the facility.   The abnormality diagnosis apparatus for a solar power generation facility according to claim 7, wherein a sound generated from a bypass diode is collected as the sound generated from the solar power generation facility.   The spectrum value for each frequency component is a spectrum value of a frequency that is an integer multiple of a switching frequency in a power conditioner of the photovoltaic power generation facility or a spectrum value of a frequency other than an integer multiple of the switching frequency. Item 7. An abnormality diagnosis device for a solar power generation facility according to Item 7.   The abnormality diagnosis of the solar power generation facility according to claim 7, further comprising means for applying a magnetic field to the solar power generation facility, or a magnetic material for making the solar power generation facility approached. apparatus.   Processing to calculate the spectrum value for each frequency component for the sound data obtained by collecting the sound generated from the photovoltaic power generation facility, and the occurrence of an abnormality / failure in the photovoltaic power generation facility using the spectrum value for each frequency component An abnormality diagnosis program for a photovoltaic power generation facility, characterized by causing a computer to perform processing for determining the presence or absence of a solar power generation facility.   The abnormality diagnosis program for a solar power generation facility according to claim 11, wherein a sound generated from a bypass diode is collected as a sound generated from the solar power generation facility.   The spectrum value for each frequency component is a spectrum value of a frequency that is an integer multiple of a switching frequency in a power conditioner of the photovoltaic power generation facility or a spectrum value of a frequency other than an integer multiple of the switching frequency. Item 12. An abnormality diagnosis program for a solar power generation facility according to item 11.

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