JP2023081332A - Failure diagnosing method, failure diagnosing device, and failure detection device for solar cell module - Google Patents

Abstract

To facilitate failure diagnosis for a solar power generation facility without being affected by the environment.SOLUTION: A failure diagnosing method includes a ripple information acquiring step for acquiring information on a ripple superimposed on a DC current flowing on each string of a solar power generation facility and a determination step that determines a failure of a solar cell module when the magnitude of the ripple is increased compared to when the solar cell module is normal or when it is detected as a change of signal intensity to increase in a specific frequency band of a frequency spectrum obtained by frequency analysis of the current. When a change in ripple (i.e. an increase in ripple) is found that is not found on the solar cell module when it is normal, or when there occurs a change of increase in the signal intensity at some frequencies in the frequency spectrum when a frequency analysis is performed, the failure diagnosing method takes this as a phenomenon that indicates a failure and determines that a solar cell module is at fault.SELECTED DRAWING: Figure 10

Description

TECHNICAL FIELD The present invention relates to a failure diagnosis method, a failure diagnosis device, and a failure detection device for a solar cell module (also called a solar panel). More specifically, the present invention provides a failure diagnosis method, failure diagnosis device, and failure detection device suitable for use in diagnosing and detecting failures in solar cell modules of large-scale photovoltaic power generation facilities, such as photovoltaic power plants (mega solar). Regarding.

A solar cell module is generally configured by connecting in series a plurality of clusters each having several tens of solar cells connected in series. Then, a string is constructed by connecting a plurality of such solar cell modules in series, for example, about 10 to 20 modules. Furthermore, an array is constructed by connecting a plurality of sets of these strings in parallel and arranging them on a base/frame.

In such a photovoltaic power generation facility, in order to prevent the influence of a part of the clusters or cells from failing or being shaded from spreading over a wide area, both ends of each cluster or each photovoltaic module, and furthermore, Each string is connected in parallel with a bypass diode that forms a path bypassing the failed cluster, solar cell module, or string. For this reason, in the photovoltaic power generation equipment, even if a part of the solar cell module or a part of the cluster fails, the bypass diode works to suppress the decrease or fluctuation of the output of the generated power. Failures cannot be detected by monitoring changes in output of generated power to the outside.

A solar cell module has a so-called cluster structure, and generates power in cluster units. For this reason, when it is shaded or a failure occurs, the generated power decreases in units of clusters (sets of a plurality of cells connected in series). If only some of the clusters belonging to the string fail, no significant drop in operating voltage is observed, so it is difficult to find the failure. In addition, if the cluster failure is left unattended, it may lead to a fire. Therefore, it is desirable to be able to detect cluster failures at an early stage.

In order to meet this demand, the inventors of the present invention conducted various studies and experiments, and as a result of simulating a failure of a solar cell module, no sound was generated during normal operation (that is, when no failure occurred). However, when a failure is simulated, the sound pressure becomes strong at about 4 kHz, and when the normal state is restored, the sound pressure becomes weaker. It was clarified that a sound (4 kHz) was generated. By detecting this high-frequency sound, it is possible to evaluate the soundness of the bypass diode or diagnose the solar cell module by making use of the characteristics of the high-frequency sound (see Patent Document 1).

JP 2017-181138 A

However, the invention described in Patent Document 1 uses the sound caused by the vibration of the object caused by the action of the magnetic field generated when the current flows through the component parts of the photovoltaic power generation equipment, so the sound is very loud. may be small, or may not occur in some cases. In addition, solar power plants (mega solar) are sometimes installed outdoors or in noisy environments, so it is necessary to intentionally generate a magnetic field so that the component parts vibrate easily when current flows. Therefore, failure of the solar cell module may not be detected unless the sound wave is amplified or generated. Therefore, it is desired to develop a method that can detect panel failures by means of phenomena other than sound.

In order to meet such a demand, the present invention provides a failure diagnosis method, a failure diagnosis device, and a failure detection device for a solar cell module that can easily diagnose failures in a photovoltaic power generation facility without being influenced by the environment. With the goal.

In order to meet the above-mentioned demands, the inventors of the present invention conducted further experiments and research on the phenomena that occur when solar cell modules fail. It was discovered that the ripple contained in the DC current increases due to a fault in some modules in the string or a current flowing through a bypass diode, although a waveform with a high voltage is rarely generated. (see Figure 1). As a result of further experiments conducted by the inventors of the present invention regarding this phenomenon of increasing ripple, it was found that the combination of the solar cell module and the power conditioner (Power Conditioning Subsystem: PCS) used in the experiment did not generate electricity. As a result of frequency analysis of the ripple on the DC current, it was found that when the commercial frequency is 50 Hz, the signal strength remarkably increases around 100 Hz (see FIG. 2). Similarly, when the commercial frequency is 60 Hz, it increases around 120 Hz. In other words, we found that the signal strength increases very significantly near the second harmonic of the grid frequency. Furthermore, although not as much as the 2nd harmonic of the grid frequency, the signal strength also increases at lower harmonics, such as near the 3rd and 4th harmonics, compared to other frequency bands. was clarified (see Fig. 3). As for the phenomenon in which the ripple increases, a similar tendency was actually shown in the combination of the solar cell module and the PCS of several companies. From this, the inventors of the present invention have found that, as shown in the ripple frequency analysis results of FIGS. an increase in the nth harmonic, especially the lower harmonics, of the fundamental frequency (also referred to herein as the fundamental frequency), especially at the second harmonic, where the signal strength increases significantly over that of surrounding frequencies It has been found that it is possible to diagnose a failure of a solar cell module by utilizing the fact. In this specification, when describing the frequency and signal strength, unless otherwise specified, the frequency is the frequency when the pulsating component (that is, ripple) contained in the DC current is frequency-analyzed. Assume that we are referring to signal strength.

However, as a result of further experiments conducted by the present inventors on this phenomenon of ripple increase, as shown in the frequency analysis results of ripples in FIGS. In the vicinity, there is almost no change between when the solar cell module is healthy and when it fails, or rather it becomes slightly lower. It was found that there is also a PCS that increases upon module failure. Furthermore, as shown in the ripple frequency analysis results of FIGS. 10A and 10B, when the solar cell module fails, the vicinity of the second harmonic (100 Hz when the fundamental frequency is 50 Hz) increases. In addition, it was found that there are PCSs in which the signal strength changes also around 230 Hz, around 330 Hz, around 450 Hz (9th harmonic), and around 670 Hz. In other words, it was found that there are also PCSs in which the signal strength increases near the n-th harmonic other than the second harmonic and at some frequencies other than the n-th harmonic. From this, in view of the fact that the second harmonic of the grid power is generated both when the solar cell module is healthy and when the solar cell module fails in the result of ripple frequency analysis, it is possible that near the nth harmonic other than the second harmonic or If the signal intensity increases in a frequency range other than the n-th harmonic, it can be determined that the solar cell module has failed.

From these experimental results, the present inventors have found that when a solar cell module fails, in the ripple frequency analysis results, at a frequency higher than the frequency (fundamental frequency) of the electric power system, there is a characteristic A change in signal strength (a change in which the signal strength increases more than the signal strength of the surrounding frequencies, in other words, an increase in ripple) is exhibited, but at what Hz does the frequency exhibiting a characteristic increase in signal strength appear? It has been found that the difference may vary depending on the combination of the solar cell module and the PCS. Furthermore, since it is assumed that the characteristics of converting generated power to grid power vary within the allowable range depending on the PCS manufacturer and model, etc., the failure of the solar cell module occurs at a frequency higher than the frequency of the power grid. It is conceivable that at what frequency the characteristic change in signal strength occurs will differ depending on the manufacturer, type, etc. of the PCS. As a result of experiments on more than 10 types of PCS by the present inventors, as described above, in the results of ripple frequency analysis, there is a characteristic change in signal strength between the power system frequency and the second harmonic. Although there were no cases where it occurred, considering that the change in signal strength was confirmed at some frequency higher than the frequency of the power system, depending on the combination of the solar cell module and the PCS, the frequency of the power system may be affected by the second harmonic. It can be inferred that a characteristic signal intensity change occurs between waves.

From this, the present inventors have found that when a solar cell module fails, the DC current flowing in the string is not limited to the nth harmonic of the frequency of the power system, but is included in the direct current flowing in the string at any frequency higher than the frequency of the power system. When a change that increases the ripple occurs, more specifically, when the ripple is frequency analyzed, a specific frequency in a frequency band higher than the fundamental frequency (not the entire frequency band higher than the fundamental frequency, but a part of it) (frequency of )), it has been found that the failure of the solar cell module can be considered when it is detected as a change in the increase in signal strength. That is, although it is difficult to determine that a failure is due to an increase or decrease in overall signal strength in a frequency band higher than the frequency of the power system, a prominent change in signal strength near a specific frequency higher than the frequency of the power system, such as power Local changes (i.e., n-th harmonics other than the second harmonic) that deviate from or protrude from a shape that is on (or along) an envelope showing changes in a frequency range higher than the frequency of the system If an increase in signal strength occurring at some frequency other than the vicinity and the nth harmonic) is found, it can be regarded as a fault.

The failure determination method for a solar cell module of the present invention is based on such knowledge, and includes a ripple information acquisition step of acquiring information on ripples superimposed on a direct current flowing in each string of photovoltaic power generation equipment; When the size of the solar cell module increases compared to when it is normal, or when it is detected as a change in which the signal strength increases in a specific frequency band of the frequency spectrum obtained by frequency analysis of the current, the solar cell and a judgment step for judging that the module has failed.

Here, in the determining step, it is preferable that the failure of the solar cell module is determined when an increase in signal strength is detected at any frequency higher than the frequency of the grid power in the frequency spectrum.

In addition, in the determination step, when the signal strength increases compared to when the solar cell module is normal at an n-th harmonic higher than the frequency of the grid power in the frequency spectrum or at a specific frequency or frequency range other than the n-th harmonic, It may be determined that the solar cell module has failed. In addition, in the determination step, if the signal strength of the n-order harmonic higher than the frequency of the grid power in the frequency spectrum increases compared to when the solar cell module is normal, it may be determined that the solar cell module has failed. good. Further, in the determination step, it may be determined that the solar cell module is malfunctioning when the signal strength increases in a frequency range other than the nth harmonic of the frequency spectrum. In the determination step, the ripple information is obtained when the solar cell module of the string starts to operate or when the operation is normal, and this ripple information data is compared with the ripple information data at the time of measurement. You may make it carry out by comparison with. Further, in the determination step, the magnitude of the signal intensity that changes at a frequency higher than the frequency of the grid power when the solar cell module is simulated failure is set as a threshold, and the threshold is used to superimpose the current of all the strings on the grid. This may be done by comparing the magnitude of the signal strength of frequencies higher than the frequency of the power. Further, in the determination step, among strings having the same number of modules in the same power plant, the magnitude of ripple generated in other strings is set as a threshold value, and the magnitude of ripples between the string to be measured and the other strings are compared with each other. It may be performed by comparing.

Further, in the failure determination method for a solar cell module of the present invention, the determining step compares the signal strength of the n-th harmonic of the frequency spectrum with the signal strength of the frequency portion other than the n-th harmonic, and You may make it presume that it is out of order when a difference arises.

Further, in the method for determining a failure of a solar cell module of the present invention, the determination step includes the step of determining that the magnitude of the signal strength at a specific frequency higher than the frequency of the grid power in the frequency spectrum increases compared to the normal state, and that the signal strength A failure may be determined when the failure is detected continuously for a predetermined time or more, or when the failure is detected continuously in a plurality of determinations with different measurement times.

Further, the fault determination apparatus for a solar cell module of the present invention includes: a current measuring means for measuring a direct current flowing through a string of a solar power generation facility; a ripple information acquiring section for acquiring information on a ripple superimposed on the direct current; When the magnitude of the solar cell module increases compared to when the solar cell module is normal, or when it is detected as a change in which the signal strength increases in a specific frequency band of the frequency spectrum obtained by frequency analysis of the current, the solar A determination unit for determining whether or not a failure has occurred in the battery module, and a determination result output unit for outputting the determination result are provided.

Further, the failure detection device for a solar cell module of the present invention further comprises an output means for continuously transmitting a signal indicating failure when the determination unit determines that a failure has occurred.

Furthermore, the fault determination device for a solar cell module has a resonance circuit that resonates at a specific frequency in the frequency spectrum obtained by frequency analysis of the current. A fault in the panel is audibly or visually displayed by ringing or emitting light to inform the watchman or the like.

Here, it is preferable that the signal notifying of the failure be composed of sound, light, signal, radio waves, or a combination thereof.

Further, the fault diagnosis program for a solar cell module of the present invention includes a ripple information acquisition process for acquiring information on a ripple superimposed on a direct current flowing in each string of photovoltaic power generation equipment, and a judgment process for judging a failure when the signal strength increases compared to the normal state, or when the signal strength is detected as a change that increases in a specific frequency band of the frequency spectrum obtained by frequency analysis of the current. I have the computer do it.

According to the fault diagnosis method, fault diagnosis device, and fault diagnosis program for photovoltaic power generation equipment of the present invention, the presence or absence of a fault in a solar cell module is determined by measuring the change in the magnitude of the ripple superimposed on the direct current flowing through the string. Therefore, failure diagnosis can be performed without stopping the operation of the photovoltaic power generation equipment (that is, while outputting the generated power). Moreover, failures of the solar cell modules that are difficult to detect by monitoring changes in the output of the generated power from the solar power generation equipment to the outside, such as a change in the output of the generated power to the outside due to the action of the bypass diode, do not appear. Faults are also captured.

Further, according to the failure detection device for photovoltaic power generation equipment of the present invention, when a failure of a solar cell module is detected for each string, a signal indicating failure, such as sound, light, signal, radio wave, or a combination thereof, is generated. Since the signal consisting of continues to be transmitted, it is possible to easily grasp the faulty string at the timing of inspection by drones, automatic driving vehicles, etc., as well as inspection by inspectors. Moreover, monitoring from a remote location is also possible. Therefore, it is possible to save labor for maintenance and inspection in a large-scale solar power plant.

It is a graph which shows the measurement result of the electric current which flows into a string, an upper line is a waveform at the time of normal of a solar cell module, and a lower line is a waveform at the time of failure. 4 is a graph showing the results of frequency analysis of the current flowing through the string when normal and when faulty. FIG. 3 is a graph showing frequency analysis results of current flowing through a string in a combination of a solar cell module and a PCS different from those in FIG. 2 during normal operation and failure. FIG. 2 is a schematic diagram showing an example of a string to which the solar cell module failure diagnosis method is applied; BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a functional block diagram showing an example of an embodiment of a solar cell module failure diagnosis method and failure diagnosis device of the present invention; 1 is a functional block diagram showing an example of a failure diagnosis device for a solar cell module according to the present invention; FIG. 1 is a flow chart showing an example of an embodiment of a method for diagnosing a failure of a solar cell module according to the present invention; It is a graph which shows the frequency analysis result of the electric current which flows into a string when A company's PCS is used, (A) shows normal time, (B) shows the time of failure, respectively. It is a graph which shows the frequency-analysis result of the electric current which flows into a string when B company's PCS is used, (A) shows normal time, (B) shows the time of failure, respectively. It is a graph which shows the frequency analysis result of the electric current which flows into a string when PCS made by C company is used, (A) shows normal time, (B) shows the time of failure, respectively.

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, the configuration of the present invention will be described in detail based on an example of an embodiment shown in the drawings.

This invention acquires information on the ripple superimposed on the direct current flowing in each string of the solar power generation equipment, and when a change in ripple (that is, an increase in ripple) that is not observed when the solar cell module is normal is found. In addition, when the signal intensity of some frequencies in the frequency spectrum increases when the frequency analysis is performed, it is regarded as a phenomenon indicating the time of failure, and it is determined that the solar cell module has failed.

Here, in the frequency spectrum obtained by frequency analysis of the current flowing in the string, the vicinity of a specific frequency or frequency band higher than the frequency of the grid power (that is, not the entire frequency band higher than the fundamental frequency of the grid power) , and some of the frequencies), typically when the signal strength increases in the vicinity of the nth harmonic of the grid power frequency compared to when the solar cell module is normal. (see FIG. 8). However, the second harmonic (100 Hz in this case) of the fundamental frequency (for example, 50 Hz) of the electric power system is generated (although it increases and decreases) even when the solar cell module is healthy and when it fails. Therefore, if any characteristic change in signal strength, such as an increase in signal strength, occurs in the nth harmonic other than the second harmonic or in the frequency or frequency band other than the nth harmonic, this is considered a failure. You can make a decision. For example, in the vicinity of the second harmonic, there is almost no change in the signal strength between the normal state and the failure state. If the signal strength increases at frequencies other than the high nth harmonic (near 280 Hz or 380 Hz) (see FIG. 9), or if the signal strength increases near the second harmonic, the second harmonic Near specific frequencies other than near 230 Hz, near 330 Hz, near 450 Hz (9th harmonic), near 670 Hz, near the nth harmonic other than the second harmonic and some frequencies other than the nth harmonic When the signal strength increases (see Fig. 10) even in may be determined to be a failure of the solar cell module.

In other words, when a solar module fails, an increase in signal strength occurs at any frequency higher than the frequency of the power grid, in other words, a specific frequency higher than the frequency of the power grid (i.e., some It has been clarified that a change in signal strength near the frequency) causes ripples to be superimposed on the direct current flowing in the string, and further increases the ripples. Therefore, according to the present invention, the ripple contained in the DC current flowing through the string is measured and detected by, for example, a clamp-type current sensor, or the ripple is frequency-analyzed to detect any frequency higher than the frequency of the electric power system. Failure of the solar cell module is detected by detecting any characteristic change in the signal intensity, specifically, an increase in the signal intensity.

Here, due to the failure of the solar cell module, a characteristic signal strength change (in other words, an increase in signal strength at some frequencies) is exhibited at a frequency higher than the power system frequency (fundamental frequency). It is considered that at what Hz the frequency at which the significant increase in signal intensity appears varies depending on the combination of the solar cell module and the PCS. Therefore, by simulating a failure of a solar cell module in advance, the frequency band in which a characteristic change in signal strength appears when the solar cell module fails is clarified (see FIGS. 2, 3, or 8 to 10). ), it is convenient to determine the presence or absence of a fault in the solar cell module using the change in signal intensity at the corresponding frequency or frequency band as a threshold. On the other hand, if the above-mentioned threshold value is not used or if the change in ripple at the time of failure is not clarified in advance, data of ripple information (referred to as ripple information) when the solar cell module is healthy is stored. A failure of the solar cell module may be determined by comparison with ripple information data. For example, in the results of frequency analysis of ripples at the start of operation of a solar cell module or during normal operation that is considered to be sound, a specific frequency or frequency band higher than the frequency of the grid power, for example, the nth harmonic or The signal strength of frequencies other than the n-th harmonic is obtained, and this signal strength is compared with the signal strength at the time of measurement. When a significant difference occurs near a specific frequency or in a frequency band, it is determined that a failure has occurred. You can do it.

As an example of a method of detecting a failure of a solar cell module, an example focusing on the nth harmonic will be specifically described below.
FIG. 1 shows an enlarged current waveform of the measurement result of the current flowing through the string when the grid power is 50 Hz. Here, the upper waveform is the waveform during normal operation (that is, the normal operation when there is no failure or the normal operation), and the lower waveform is the waveform during failure. According to this, the waveform in the normal state is substantially linear and no ripple is generated, but when a failure occurs, it appears as a sinusoidal ripple. Moreover, the wave height (that is, the height difference between the crest of the wave and the trough of the wave following it) overlaps as a large ripple.

FIG. 2 shows the results of frequency analysis of the DC current flowing through the strings when the grid power is 50 Hz. From this result, it can be seen that the signal strength increases at a frequency of 100 Hz, ie, the second harmonic of the grid power, both when the solar cell module is normal and when it fails. However, it is clearly shown that the signal intensity at failure is significantly increased compared to that at normal time.

Further, FIG. 3 shows the results of frequency analysis of the current flowing through the strings in a photovoltaic power plant (system power is 50 Hz) having different solar cell modules and PCS from the example in FIG. Also in this case, it can be seen that the signal strength increases at 100 Hz, which corresponds to the second harmonic of the grid power, both in the normal state and in the failure state. Moreover, it is clearly shown that the signal intensity at the time of failure is remarkably increased compared to that at the time of normal operation. In addition, the waveform around 100 Hz is well-ordered without being disturbed at the time of failure. Furthermore, at the time of failure, the signal strength also increased at 150 Hz (that is, the third harmonic of the grid power) and 200 Hz (the fourth harmonic of the grid power). Furthermore, in the frequency analysis results of the solar cell module incorporating Company A's PCS, the signal strength increased even at 150 Hz (that is, the third harmonic of the grid power) and 200 Hz (the fourth harmonic of the grid power). (see FIG. 8(B)). For this reason, when the solar cell module fails, the n-th harmonic of the frequency of the grid power, especially the second harmonic, and in some cases, the third harmonic or the fourth harmonic. It is believed that an increase in signal strength occurs. In other words, the change in ripple that occurs when a solar cell module fails is a signal in the vicinity of a part of the frequency band (that is, a specific frequency) higher than the frequency of the grid power in the results of frequency analysis of the current and ripples flowing in the string. A change in intensity is detected.

That is, in the combination of the solar cell module and the PCS used in the experiments in which the results shown in FIGS. There was a tendency for the signal strength to increase at 100.degree. C., and the increase in the signal strength was particularly remarkable in the frequency band of the second harmonic.

From this, the DC current flowing through the string is measured, and when the signal strength of the nth harmonic of the frequency of the grid power increases (that is, when the signal strength is greater than the normal one, in other words, the DC when the ripple superimposed on the current increases), it can be determined that the solar cell module is faulty.

In the solar cell module failure diagnosis method of the present embodiment, when a failure occurs in a part of a solar cell module in a string or in a part of cells of a solar cell module, a direct current flowing in the solar power generation equipment, for example, a direct current flowing in the string, is detected. This is based on the above-mentioned knowledge that the ripple superimposed on is increased compared to normal (that is, when no failure occurs). Here, a change in ripple appears as a change in the waveform of the current, and is detected as a change in signal strength in the vicinity of a specific frequency or frequency band by frequency analysis of the current. Therefore, in the method for diagnosing a failure of a solar cell module of the present invention, it is not limited to the case of measuring the change in the waveform of the current itself. It has been clarified that even when a change occurs in which the signal strength increases in the vicinity of a specific frequency or frequency band higher than the frequency of the electric power system, it can be regarded as a phenomenon representing failure of the solar cell module.

In other words, the failure diagnosis of the solar cell module of the present embodiment does not simply deal with the presence or absence of ripples, but rather the phenomenon that the ripples that are not observed in the normal state of the solar cell module continuously increase. Alternatively, when frequency analysis is performed on the measured current, a constant increase in signal strength occurring at a specific frequency higher than the frequency of the grid power, such as the n-th harmonic of the frequency of the grid power or a frequency part other than the n-th harmonic is used as a criterion for judgment. and For example, when the change in ripple is a problem, the magnitude of the ripple, for example, the magnitude of the amplitude or wave height, or the magnitude of the signal strength at the time of frequency analysis of the current, and its continuity are regarded as problems, When the magnitude of the ripple increases and continues, that is, when it is not affected by weather changes or shaded by trees or buildings, it is judged as a failure, and the amount of change is constant. It is preferable to determine that there is no failure when the value is below the value (when there is no significant difference) or when there is no change or does not continue. On the other hand, when an increase in ripple is detected from a change in which the signal strength of a specific frequency higher than the frequency of the grid power increases when the current is frequency-analyzed, the second harmonic and other than the second harmonic are detected. When an increase in signal strength occurs and continues at a frequency or frequency band other than the n-th harmonic of the n-th harmonic or the n-th harmonic, that is, when it is affected by weather changes or shaded by trees or buildings It is preferable to determine that there is no failure when there is no influence of all, and that there is no failure when the amount of change in signal strength is less than a certain value (when there is no significant difference), or when there is no change or does not continue.

When a solar cell module fails, an increase in ripple flowing through a string on the DC side, for example, can be detected in the form of an increase in the amplitude or wave height of the ripple. Failures can be determined in real time or at arbitrary timing. On the other hand, when a solar cell module fails, ripple occurs at a specific frequency higher than the grid power frequency at which the signal strength in current frequency analysis becomes strong, such as the nth harmonic of the grid power frequency or other frequencies. Since it can be detected in the form of an increase in the signal generated in the frequency part, by measuring and monitoring the signal strength at a specific frequency higher than the frequency of the grid power, such as the nth harmonic, failure of the solar cell module can be detected in real time or at any time. can be determined in time.

Here, the specific frequency higher than the frequency of the grid power whose signal strength is to be measured during frequency analysis is, for example, the nth harmonic, preferably from around 100 Hz (second harmonic) to 450 Hz (ninth harmonic). harmonics), especially near the second harmonic. The ripple superimposed on the DC current generated when the solar cell module fails changes extremely significantly in the second harmonic of the grid power (100 Hz for a 50 Hz commercial power supply, 120 Hz for a 60 Hz commercial power supply). Therefore, if the signal intensity in the frequency analysis of the current is normal or is larger than in the conventional case, it can be determined as a failure. Of course, the change in signal strength at 280 Hz or 380 Hz in FIG. 9B as a specific frequency other than the n-th harmonic is used as a threshold, or the frequency band other than the n-th harmonic as shown in FIG. 10B It goes without saying that the failure of the solar cell module may be determined by using as a threshold the change in the signal intensity that is more prominent than the signal intensity in the surrounding frequency range in the frequency part where the signal intensity is locally significantly changed in the . That is, when some characteristic change occurs in the signal strength (output strength) of the DC current flowing through the string, for example, when the signal strength changes as shown in FIG. 9(B) or FIG. 10(B) can be determined as failure of the solar cell module.

Moreover, since it is difficult to evaluate/judge the magnitude of the ripple with an absolute value, it is preferable to predetermine a value (that is, a threshold value) that serves as a criterion for judgment, or to evaluate/judge relatively. Here, for example, one solar cell module (or a part of the cluster) in the string is covered with a cloth or the like to shield it from light, thereby causing a simulated failure, so that the solar cell module cannot be seen when it is normal. Phenomenon of increase in ripple or change in signal strength occurring at a specific frequency higher than the frequency of the grid power when the ripple is frequency-analyzed, such as the n-th harmonic of the frequency of the grid power or a frequency part other than the n-th harmonic It is preferable to set by determining in advance whether (increase in signal strength) will occur. When the threshold value is set by a simulated failure, the magnitude of the ripple at each failure can be obtained in arbitrary units, such as cell units, cluster units, module units, and multiple module units. Therefore, by properly using these thresholds, it is possible to specify the scale and position of the failure. This reference value may be stored in a memory as a threshold value and used in the determination circuit, or may be used as a measurement sensitivity reference (adjusting the sensitivity of the measuring device) so as to detect only when the threshold value is exceeded. can be

The photovoltaic power plant (mega solar) is connected to the grid via a power conditioner (Power Conditioning Subsystem: PCS), which has the function of converting the generated power into grid power. The characteristics of the ripple generated in the direct current flowing in the string may differ depending on the PCS (in other words, the solar power plant). It is considered that there is no difference in the characteristics of generated ripples between strings. Therefore, if the photovoltaic power generation equipment of the same PCS, that is, the photovoltaic power plant, it is possible to determine the failure of the photovoltaic module for each string using the same threshold value or criterion. In other words, changes in ripple caused by failure of a solar cell module, or changes in signal strength occurring at a specific frequency higher than the frequency of the power grid during ripple frequency analysis, are similar between the same PCS and solar module combination. It exhibits the phenomenon of

Of course, the same threshold may be used within the same solar power plant, but setting different thresholds is not denied. In other words, there is a relationship between the scale of the failure of the solar cell module and the change in ripple or the magnitude of the signal strength generated at a specific frequency higher than the frequency of the grid power during the frequency analysis of the ripple. For example, the larger the number of faults or the like, the larger the amount of change in the magnitude of the ripple or the increase in the signal strength. For this reason, a plurality of thresholds associated with degrees of failure of solar cell modules (for example, the number of failed modules, the number of cluster failures, the number of damaged cells, etc.) may be used as the thresholds. In this case, the determination unit and thus the diagnostic device can specify the fault scale, such as the number of faulty modules or the number of cells, corresponding to the maximum threshold exceeded by the measured ripple amplitude or signal intensity increase. In addition, by changing the simulated fault position, estimation of the fault position is performed. You may make it presume the string which carries out. However, in order to detect a failure of a solar cell module in a string, it is necessary that at least one cluster failure of the solar cell module occurs. If a change in the increase in the signal strength of a specific frequency is used as a threshold for determination, even if a larger ripple, that is, one or more cluster failures or module failures, has occurred, it can be detected.

In addition, the above-described criteria (thresholds) are not always used in the failure determination of the solar cell module. For example, the measurement result at the start of operation or at the time of health can be used as a criterion for fault diagnosis. In other words, if there is no change compared to past measurement results, at least if there is no change from the past situation, that is, if the solar cell module was normal, it means that it is normal now. According to experiments by the present inventors, when the solar cell module is normal, as shown in FIG. When there is almost no occurrence, it can be determined as normal. On the other hand, when a solar cell module fails, the influence of ripple superimposed on the DC current flowing through the string increases, as shown in FIG. 1 as failure. If the magnitude of the ripple amplitude at the time of measurement is greater than the previous amplitude, it is determined that a failure has occurred in the solar cell module. In addition, when the signal strength at the time of frequency analysis is used as the failure determination criterion for the solar cell module, if the magnitude of the signal strength at a specific frequency at the time of measurement is greater than the previous signal strength, , it is determined that a failure has occurred in the solar cell module. Therefore, for example, the magnitude of the ripple waveform superimposed on the DC current flowing through the string when the solar cell module starts operating or is healthy, or the specific frequency or frequency band higher than the frequency of the grid power at the time of ripple frequency analysis. The signal strength (these are collectively called ripple information) is acquired, the data of this ripple information is compared with the data of the ripple information at the time of measurement, and the presence or absence of failure of the solar cell module is determined from the difference. can be

In addition, instead of a threshold value obtained in advance by simulated failure, etc., by comparing the currents flowing through all the strings in the same solar power plant, it is possible to determine whether a failure has occurred in the solar cell module and the failure of the solar cell. It may also be possible to specify the string in which the module is included. Within the same solar power plant (because of the same PCS), ripples with the same characteristics occur between strings with the same number of solar cell modules. On the other hand, in a photovoltaic power plant, due to the electrical characteristics of solar cells, when a failure cannot be detected from a decrease in output, only some strings have failures in the solar cell modules, and many others. It is assumed that no faults have occurred in the string. Therefore, strings that change relative to all strings with respect to the magnitude of the ripple or the magnitude of the signal strength of a specific frequency or frequency band higher than the frequency of the grid power when the ripple is frequency-analyzed, For example, if only one ripple has a prominent magnitude or signal strength, or if there is a peculiar waveform or change compared to the whole, it can be determined as a failure.

Furthermore, as another criterion for failure diagnosis, frequency analysis of the current flowing through the string is performed, and a specific frequency or frequency band higher than the frequency of the grid power is used. The signal strength of the frequency corresponding to the harmonic is compared with the signal strength of the other frequencies, and when a clear difference occurs in the signal strength in the frequency spectrum, as shown in FIG. You may make it presume that it exists. In other words, the ripple with increased signal strength at a specific frequency higher than the frequency of the grid power, such as the n-th harmonic of the frequency of the grid power or other frequency part, can reduce the power generated by the solar cell module to the commercial frequency. Since it is mainly generated in the PCS part that converts, it is considered that the influence of the PCS greatly contributes to the characteristics of the generated ripple. Therefore, by analyzing the frequency of the current flowing through the string and comparing the signal intensity of the n-th harmonic of the grid power frequency with the signal intensity of the frequency part other than the n-th harmonic component, the state of the solar cell module can be determined. can be diagnosed. Further, as an example only, the value of the signal strength of the n-order harmonic of the frequency of the grid power and the feature amount such as the average value of the signal strength of other frequency bands may be compared and determined. , the value of the signal strength of the n-th harmonic and any one or each of the signal strength values of the other frequency bands may be individually compared with each other.

The above-described method for diagnosing a failure of a solar cell module is realized by, for example, a failure diagnosis apparatus for a solar cell module shown in FIG.

FIG. 5 shows an embodiment of a failure diagnosis device that implements the failure diagnosis method for a solar cell module of the present invention. This solar cell module failure diagnosis apparatus includes a current measuring means 1 for measuring a current flowing through a solar power generation facility, for example, a current flowing through a string, a ripple measuring section 2 for measuring the magnitude of a ripple superimposed on a DC current, and a A judging unit that compares the calculated ripple information (threshold value), which serves as a criterion for judgment, with the magnitude of the measured ripple, and judges whether or not a failure has occurred in the solar cell module based on whether the magnitude of the ripple has increased. 3 and a determination result output unit 4 that outputs the determination result, acquires information on the ripple superimposed on the direct current flowing in each string of the photovoltaic power generation equipment, and increases the magnitude of the ripple compared to normal. It is determined that a failure has occurred when a failure occurs, and the occurrence of the failure is notified.

Here, as the current detection means 1, a current sensor suitable for measuring a waveform with ripples (AC superimposed on DC), for example, a wire-wound (CT) type current sensor such as a clamp-type current sensor (Fig. 4 ), a Hall element type current sensor, a Rogowski coil type current sensor, and a direct current sensor having an AC function such as a zero flux type of each of these current sensors. For example, when using the winding detection type current sensor shown in FIG. It is proportionally induced in the winding 8 and flows through the shunt resistor 9 to generate a voltage across the shunt resistor 9 . This voltage will be an output proportional to the ripple current flowing in conductor 6 . That is, only ripple information (that is, information only about the pulsation component) is detected without the DC component.

The current detection means 1 measures the value of the current flowing through the series connection circuit for each string. In this case, the current detection means 1 may, for example, measure the current flowing between the terminals of the series-connected circuit, or measure the current flowing through an arbitrary point between the terminals. Alternatively, the current through the ground wire may be measured. Since ripples are also superimposed on the current flowing through the ground line, the magnitude or amplitude of the ripple of the current flowing through the ground line increases as the magnitude or amplitude of the ripple of the current flowing through the series connection circuit, which is the main line, increases. .

The mode of installation of the current detection means 1 is not limited to a specific mode, and any place in the series connection circuit that can detect the ripple generated from the solar power generation equipment to be diagnosed, for example, the diagnosis of the solar power generation equipment Each cluster, module, or string as a unit (in other words, a failure detection unit in a photovoltaic power generation facility) may be fixedly installed to continuously measure the current, or in some cases, A portable current sensor such as a clamp meter (clamp measuring device) may be used to sequentially measure each diagnostic unit. In the case of this embodiment, specifically, the current detection means 1 is installed in the conductor of the string of the photovoltaic power plant to be diagnosed, and the direct current is measured (S1).

The ripple measuring unit 2 measures the magnitude of the ripple from the ripple information acquired by the current detecting means 1 (S2). Here, the ripple information is specifically, for example, data related to the waveform of the ripple, such as the magnitude of the amplitude or wave height of the ripple, or in some cases, the frequency of the grid power in the frequency spectrum obtained by frequency analysis of the measured current. It is the magnitude of the signal intensity that is generated in the vicinity of a specific frequency that is higher than the frequency of the grid power, such as the nth harmonic of the grid power frequency or a frequency other than the nth harmonic, but in some cases Alternatively, the ripple waveform itself or the frequency spectrum itself may be obtained as the waveform pattern.

Then, the magnitude of the detected ripple, for example, the amplitude value, is input to the determination unit 3, and is compared with a determination reference value (threshold value) by the determination unit 3 to determine whether a fault has occurred in the solar power generation equipment to be diagnosed. is determined. For example, compared with the ripple information data when the solar cell module is healthy, where the magnitude of the amplitude of the detected ripple is a predetermined threshold value or other determination reference value, the ripple is less than when the solar cell module is normal. If it is recognized that the has increased significantly, it is determined that a failure has occurred, and if it is below the threshold or when it is healthy, the frequency analysis data, that is, the ripple information data of a frequency higher than the frequency of the grid power does not change significantly If so, it is determined to be normal (S3). In addition, as ripple information, when a significant increase in signal strength is detected using the change in signal strength at some frequencies higher than the frequency of the grid power in the frequency spectrum obtained by frequency analysis of the measured current In addition, when judging the presence or absence of a failure of a solar cell module, the magnitude (threshold value) of the signal strength at a specific frequency when the solar cell module is in good condition, which is obtained in advance, is regarded as a phenomenon representing the time of failure, or other When the signal strength is found to be significantly increased compared to the normal state of the solar cell module, it is determined that a failure has occurred, and when the signal strength falls below the threshold or If there is no significant difference from the frequency analysis data when healthy, it is determined to be normal (S3).

The determination unit 3 determines a specific frequency higher than the frequency of the grid power, which is obtained in advance when the solar cell module is sound (normal), such as the nth harmonic of the frequency of the grid power or a signal of other frequency parts. The presence or absence of a failure is determined based on the results of measuring the current flowing through each string, using the magnitude of the intensity as a threshold value or collating with a mutually comparable reference value. Here, when a frequency showing a significant increase in signal strength is known in advance in a failure simulation test or the like, as shown in FIGS. By using the magnitude of the change as a threshold value, it is possible to determine whether or not there is a failure.

Note that the threshold value is stored in a storage circuit provided in the determination unit 3, for example, so that the determination unit 3 can refer to the threshold value, in other words, the determination unit 3 can read the threshold value. . Then, the determination unit 3 compares the magnitude of the ripple, such as the amplitude or the wave height, superimposed on the current flowing through the string with a threshold value, and determines that there is a failure or the like when the magnitude of the ripple, such as the amplitude or the wave height, exceeds the threshold value. On the other hand, if the magnitude of the ripple, such as the amplitude or wave height, is less than the threshold, it is determined that there is no failure. Further, when the determination unit 3 regards the detection of a change in which the signal strength increases at some frequencies during the frequency analysis as a phenomenon representing the failure of the solar cell module, the current flowing through the string is superimposed. Compare the magnitude of the signal strength of either or both of a specific frequency higher than the frequency of the grid power, such as the nth harmonic of the frequency of the grid power or other frequency parts, with a threshold, and determine the magnitude of the signal strength If the signal intensity exceeds the threshold, it is determined that there is a failure or the like, and if the signal intensity is less than the threshold, it is determined that there is no failure.

Furthermore, the determination unit 3 does not necessarily use the above-described threshold, and when the frequency is not specified in advance (for example, when the characteristics of the PCS are unknown), the entire frequency range higher than the frequency of the power system This can be done by comparing the magnitude of the ripple or the magnitude of change in the signal strength during past operation when the solar cell module is considered to be healthy. For example, when detecting a change in signal strength to determine a failure of a solar cell module, the past measurement results for the same string, preferably at the start of operation or when it is recognized that the solar cell module is operating normally Frequency component data or signal strength values in a frequency band higher than the fundamental frequency of the grid power, intercomparison with the measurement results of other strings in the same power plant, or signal strength at the nth harmonic of the frequency of the grid power and that The presence or absence of a failure may be determined by comparing the signal intensity at frequencies other than the above, and a string including a failed solar cell module may be identified. Machine learning (pattern learning) is applied to the determination using the waveform pattern, and it is determined that a failure has occurred in the photovoltaic power generation equipment for which the determination data of a pattern different from other patterns is acquired. You can do it.

The determination result output unit 4 for outputting the determination result indicates the determination result to the observer or the like according to the determination result from the determination unit 3. For example, warning message display means such as a display, and sounding means such as a speaker or buzzer. , light-emitting diode (LED) lighting, warning lights, revolving lights, and other lighting means are employed.

In addition, except for the current measuring means 1 for measuring the current flowing through the string, the fault diagnosis device does not require the ripple measuring section 2, the determining section 3, and the determination result output section 4 to be arranged in the solar power plant. For example, direct current values measured by the current measuring means 1 may be collected and processed by a remote monitoring device remote from the solar power plant by communication via an information communication network such as an internetwork.

Further, in place of or together with the determination result output unit 4 for outputting the determination result, an output unit 5 for continuously transmitting a signal indicating failure is provided, and when it is determined that a failure has occurred in the solar cell module. Alternatively, it may be configured as a failure detection device for a solar cell module that continuously transmits a signal informing of a failure.

The signal notifying of failure does not have to be a specific signal, and preferably consists of, for example, sound, light, signal, radio waves, or a combination thereof. In this case, the output means 5 may be means for continuously transmitting a signal indicating a failure, such as a sounding means such as a speaker or a buzzer, lighting means such as a light-emitting diode (LED) illumination, a warning light, or a revolving light, or communication means such as radio. , warning message display means such as a display, or a combination thereof.

For example, light-emitting means such as light-emitting diode (LED) lighting or wireless communication devices such as Bluetooth (registered trademark) devices are provided at appropriate locations in a photovoltaic power plant, for example, for each array, each string, or each module (panel). is installed, and when a failure of the solar cell module is detected, the LED lighting is turned on to display the failure string so that it can be visually grasped, or a failure signal is transmitted by wireless communication to generate solar power It is possible to have the receiving device on the premises of the site (mega solar) receive it and inform the monitoring station in a remote location in real time, or continue to transmit from the transmitting device, and use it during inspections by patrol inspectors, drones, etc. You may make it grasp at the timing of inspection by. As a result, it is possible to save labor in maintenance and inspection at large-scale solar power plants. In particular, it can be managed centrally at a remote location by communication.

Here, it is preferable to use a wireless communication device that consumes less power, such as a Bluetooth (registered trademark) device. Use of Bluetooth technology designed for one-to-one communication because the communication is only to notify the detection of a failure, and the communication partner is a receiving device mounted on a predetermined partner, such as a drone. is preferred. Both the communication speed and communication distance are weaker than Wi-Fi, but the power consumption is low, and it is easy to introduce to devices that are used for a long time. If you first perform "pairing" to recognize each other, a remotely controlled drone or self-propelled vehicle equipped with the receiving device will automatically connect and receive the signal when it comes within the communication range. be able to. In addition, if the Bluetooth device also has a "direction finding function", the transmission angle and reception angle are determined by the signal emitted from the antenna of the transmitting Bluetooth device (beacon), and the paired Bluetooth device Since it is possible to see in which direction the sensor is located, a wide range of inspections can be easily performed using a Class 1 beacon (maximum output of 100mW, communication distance of approximately 100m (maximum of 400m or more)). In addition, since you can use the "multi-pairing" function that allows you to register and connect setting information to multiple devices on one Bluetooth device, it is possible to inspect drones and self-propelled vehicles equipped with one receiver Bluetooth device. becomes. Of course, when using a Bluetooth device equipped with a "direction finding function", by appropriately placing the receiving Bluetooth device within the communication range within the premises of the solar power plant (mega solar), continuous remote failure can be detected. It goes without saying that detection can be performed. Of course, if the problem of the power supply can be resolved, the Wi-Fi technology may be used in some cases to inform the user when a failure is detected.

According to the fault diagnosis apparatus for a solar cell module configured as described above, first, as shown in FIG. is acquired (S1). Then, the magnitude of the ripple is calculated (S2), and is compared with the threshold value indicating the failure of the solar cell module or the data of the ripple information during the past or present operation when the solar cell module is considered to be healthy in the judging section 3. A determination is made as to whether or not a failure has occurred (S3). Here, the process of determining whether or not a failure has occurred in the photovoltaic power generation equipment is preferably performed continuously as constant monitoring. can be Therefore, if it is determined that no failure has occurred in the solar cell module (S3: No), the diagnosis is temporarily terminated, or depending on the circumstances, the process returns to S1 at an appropriate interval or as necessary, and the process returns to S1. , the process of S3 is repeated.

On the other hand, if the determination unit 3 determines that the solar cell module is faulty (S3: Yes), it is determined that the solar power generation facility to be diagnosed is faulty. The result is output from the determination result output unit 4 (S4).

Further, in some cases, the output means 5 is caused to continue transmitting a signal informing of the failure (S4'). Specifically, for example, it emits sound toward workers and managers involved in solar power generation equipment, and unmanned monitoring devices such as drones), lights LED lighting, warning lights, rotating lights, etc., displays, etc. display a warning message or continue to emit a radio signal to notify of a failure.

Therefore, when a failure of a solar cell module is detected, a signal indicating the failure, such as sound, light, signal, radio wave, or a combination of these signals, is continuously transmitted. Of course, it is possible to easily grasp the faulty string at the timing of inspection by drones, automatic driving vehicles, etc. Moreover, monitoring from a remote location is also possible. Therefore, it is possible to save labor for maintenance and inspection in a large-scale solar power plant.

In a photovoltaic power plant, the effects on power generation are not limited to the effects of cell or cluster failures, but also include the effects of weather changes and the effects of shading by trees or buildings. Therefore, an increase in ripple is not limited to failure of the solar cell module, and similarly occurs when the solar cell module is shaded by trees and plants.

Here, when the failure judgment of the solar cell module is performed on site, or when image information can be obtained by taking an image with a drone, etc., the factor of the ripple detection is that the solar cell module is in the shade. Since it is possible to clearly determine whether the cause is due to other factors, it is possible to instantly determine that there is a failure when an increase in ripple is measured even though the device is not in the shade.

On the other hand, when judging the presence or absence of a failure in a remote location only by signals, it is difficult to obtain information whether it is due to the influence of the weather or the shade caused by trees, etc., so it is difficult to determine whether there is a failure in the solar cell module. . Therefore, in the case of remote measurement, when an increase in ripple or an increase in signal strength of some frequencies in frequency analysis is continuously detected for a certain period of time (for example, across days), It is preferable to determine that a failure has occurred when a failure is continuously detected in a plurality of determinations with different values. For example, if the current can be measured continuously and an increase in ripple can be detected at least every day over several days or for several days, it will not be in the shade due to weather effects (casting shadows of clouds), but failure or It is considered that there is no problem even if it is determined that light is blocked by being covered by flying objects. Such continuous determination increases the reliability of the determination. Of course, if a solar cell module is covered by flying objects and a continuous increase in ripple or an increase in the signal strength of some frequencies is detected in frequency analysis, a field survey for confirmation or Remote photography with a drone or the like makes it clear at a glance, and it can be determined that the cause of the increase in ripple was not the failure.

In this embodiment, a number of solar cell modules forming one string has been described as an example, but the present invention is not limited to this, and the same applies to the case of applying to a plurality of cells forming one solar cell module. is. In other words, as the number of cells in which a failure or the like occurs among a plurality of cells constituting one solar cell module increases, the magnitude of the ripple generated in the current flowing through the series connection circuit of the solar cell module increases. increases.

Further, in the present embodiment, a case is shown in which the presence or absence of a failure or the like is determined based on the amplitude of the ripple. As another example, a case where the ripple having a signal component of a part of the frequency occurs increases, in other words, If the signal strength of some frequencies increases when frequency analysis is performed, it can be regarded as a phenomenon indicating a failure. You may make it judge. That is, when the frequency analysis is performed, the signal strength of the other string in the same power plant, which is considered to represent the healthy state of the solar cell module, is compared with the signal strength, which is the threshold value set in advance for the change in the signal strength of some frequencies. or by comparing the signal strength at the nth harmonic of the grid power frequency with the signal strength at other frequencies. You can

Further, the ripple measurement unit 2, determination unit 3, and determination result output unit 4 described above may be realized by a computer by executing a failure diagnosis program for the solar cell module on the computer.

FIG. 6 shows the overall configuration of a computer 19 for executing the fault diagnosis program 17 for solar cell modules.

This computer 19 comprises a control section 11, a storage section 12, an input section 13, a display section 14, and a memory 15, which are interconnected by a signal line such as a bus.

The control unit 11 controls the entire computer 19 and performs calculations related to fault diagnosis and detection of the solar cell module by means of a solar cell module fault diagnosis program 17 stored in the storage unit 12. For example, a CPU (central processing unit) processing equipment).

The storage unit 12 is a device capable of storing at least data and programs, such as 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. Note that the input unit 13 may have a plurality of types of interfaces such as both a keyboard and a mouse.

The display unit 14 draws and displays characters, figures, images, etc. under the control of the control unit 11, and is, for example, a display.

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

Further, the computer 19 is provided with a wired signal transmission/reception mechanism as described above so that the current detection means 1 can transmit/receive signals such as data and control commands (i.e., input/output). or a wireless signal transmission/reception mechanism or a combination of these signal transmission/reception mechanisms.

The control unit 11 of the computer 19 includes a data receiving unit 11a for receiving an input of a DC current value taken in from the current measuring means 1 by executing the failure diagnosis program 17 for the solar cell module, and a DC current value. A ripple measurement unit 11b that calculates the magnitude of the ripple superimposed on the current, and the magnitude of the ripple measured by the ripple measurement unit 11b and the threshold value read from the memory or the measured past operating time considered to be healthy, for example, at the start of operation A determination unit 11c for determining whether or not there is a failure in the solar cell module using the change in the ripple as a determination reference value, and outputting a determination result signal when it is determined that a failure has occurred, and a determination result signal and a determination result output unit 11d that performs processing for issuing an alarm according to the above.

Also, the computer 19 may not include the determination result output unit 11d. In this case, the computer 19 outputs an abnormality notification signal to the determination result output unit 4 provided separately from the computer 19 or to the output means 5 for continuously transmitting the signal informing of the failure. Alternatively, an abnormality notification signal may be output to a control device/control unit that controls the operation of the solar power generation equipment to be diagnosed.

According to the fault diagnosis method, fault diagnosis device, and fault diagnosis program for a solar cell module having the above configurations, when the magnitude of the ripple contained in the DC current flowing through the string increases compared to normal, or when the ripple is Increase in signal strength near a certain frequency or frequency band (e.g., nth harmonic of the frequency of the grid power or other specific frequencies) higher than the frequency of the grid power by frequency analysis is detected, it can be determined that a failure has occurred in the string or the photovoltaic power generation equipment. This fault diagnosis can be performed remotely or on-site while the solar power plant is in normal operation, i.e., the solar power plant is shut down or partly disconnected, or the solar power plant is Diagnosis can be performed without direct electrical contact (that is, wiring to equipment circuits). For this reason, it becomes possible to diagnose the solar power generation equipment at any time, appropriately and easily, and furthermore, it becomes possible to improve the usefulness as a method of detecting a failure of the solar power generation equipment.

Furthermore, according to the above-described solar cell module failure detection apparatus, when it is determined that a solar cell module has failed based on the current flowing through the string, the output means 5 sends a signal, such as sound, light, or signal, to inform the failure. , radio waves, or a combination of these, so the timing of inspections by patrolling observers, drones, self-propelled inspection vehicles, etc., or receiving equipment on the premises of solar power plants (mega solar) The failure can be easily grasped by receiving the failure signal through wired or wireless communication and informing a monitoring station or the like in a remote location in real time. Therefore, it is possible to save labor in maintenance and inspection at a large-scale solar power plant.

Although the above 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. can be modified in various ways.

For example, in the above-described embodiments, the ripple current superimposed on the direct current flowing in the string (or solar cell module, cluster, or cell) is measured. The presence or absence of failure in the solar cell module may be determined based on the above.

In addition, in the above-described embodiment, as a result of judging that there is a failure, the fact is displayed on the display, or a signal such as sound, light (LED), or radio is continuously emitted as a failure notification signal. It is not an essential configuration in the present invention that the determination result output unit 4 that outputs and the output means 5 that continues to transmit a signal informing of a failure are not essential in the present invention. Various ways of using the determination result of (1) may be considered, and various devices and apparatuses may be used in combination.

In addition, in the above-described embodiments, an example of a large-scale power generation facility such as a photovoltaic power plant has been mainly described. It is needless to say that it is also possible to apply it to the power generation equipment of

Furthermore, the ripple information used in determining a failure is not limited to the magnitude of the ripple (amplitude value or peak value) or signal strength in frequency analysis), but rather than the feature value of the ripple waveform and the frequency of the grid power. A characteristic value such as an average value or a variance value of signal strength in a predetermined frequency band centered on a specific high frequency, for example, the n-th harmonic, or a frequency portion other than the n-th harmonic may be used.

When using the ripple feature amount, for example, machine learning (also called pattern learning) is used in determining whether a failure has occurred in the solar cell module by comparing the reference feature amount data with the measured ripple feature amount data. ) may be used, for example, the feature amount of the ripple waveform may be extracted and the determination may be made by pattern matching or the like.

In this case, the information of the ripple superimposed on the current flowing through the string, that is, the waveform is extracted, and the nth harmonic around the time when the solar cell module corresponding to the teacher data in machine learning is normal or regarded as normal. It is determined that the solar cell module is normal when the feature amount of the ripple waveform and the feature amount of the ripple of the measured data are the same (in other words, there is no difference) or a similar pattern, and the patterns are different. Sometimes a solar module is determined to be faulty.

Also, machine learning may be used in determining whether or not a failure has occurred in the photovoltaic power generation equipment. In this case, the detection values of the current sensors provided for each of the plurality of strings, the plurality of photovoltaic modules, or the clusters of the solar power generation equipment to be diagnosed are compared with each other, and these current detection values are compared with each other. Signal strength near a certain frequency or frequency band higher than the frequency of the grid power by frequency analysis of the value (e.g. the nth harmonic of the frequency of the grid power or some other frequency at a particular frequency) It is determined whether or not a failure has occurred in any of the photovoltaic power generation facilities based on the difference when the sizes are compared side by side. Specifically, the magnitude of the signal strength at frequencies corresponding to the nth harmonic, such as the second harmonic, or specific frequencies other than the nth harmonic, such as 230 Hz, 280 Hz, and 380 Hz, were compared side by side. Based on the time difference, it is determined whether or not a failure has occurred in any of the photovoltaic power generation facilities.

Furthermore, the fault determination device for a solar cell module has a resonance circuit that resonates at a specific frequency in the frequency spectrum obtained by frequency analysis of the current. A fault in the panel may be audibly or visually displayed by ringing or emitting light to inform the watchman or the like. For example, the current detection means 1 incorporates a resonance circuit that resonates at a specific frequency higher than the frequency of the grid power, for example, the n-th harmonic of the frequency of the grid power or a specific frequency other than the n-th harmonic, and the current detection means 1 at a specific frequency higher than the frequency of the grid power, e.g. Alternatively, when a specific frequency other than the nth harmonic (for example, 280 Hz or 380 Hz shown in FIG. 9B, or near 230 Hz, 330 Hz, or 670 Hz shown in FIG. 10B) is detected, the resonance circuit , and when the ripple reaches a certain level, it emits a sound or emits light to audibly or visually indicate the failure of the panel and notify the observer, etc., of the failure of the solar cell module. You may make it comprise as a device.

Furthermore, the framework of having a DC power supply and connecting it to the grid through a DC-AC converter is not limited to the solar cell module of the above-described embodiment, and is the same when using a storage battery. In other words, the fault diagnosis technique of the present invention is not limited to the solar cell module described as an embodiment, but can be applied to general storage battery systems that convert direct current to alternating current (or vice versa) to enable grid connection. . In recent years, as a result of the spread of distributed energy resources introduced on the consumer side, such as cogeneration such as solar power generation and household fuel cells, storage batteries, electric vehicles, and negawatts (energy-saving power), The construction of a mechanism (called VPP (Virtual Power Plant)) that utilizes the energy resources of the electric power system is in progress. Therefore, even in a system that has a storage battery, for example, a VPP system that uses a car battery, if the storage battery system malfunctions, some kind of ripple appears in the current on the DC side. It can be detected as a change, eg, an increase, in signal strength in the vicinity of a frequency or in a frequency band.

1 Current measuring means 2 Ripple measuring part 3 Judging part 4 Judgment result outputting part 5 Sending means for continuously sending a signal informing of failure 10 Failure diagnosis device for photovoltaic power generation equipment

Claims (15)

a ripple information acquisition step of acquiring information on a ripple superimposed on a direct current flowing in each string of photovoltaic power generation equipment; a determination step of determining that the solar cell module has failed when a change in signal strength increases is detected in a specific frequency band of a frequency spectrum obtained by frequency analysis of the current. Module fault diagnosis method. 2. In the determining step, when an increase in the signal strength is detected at any frequency higher than the frequency of the grid power in the frequency spectrum, it is determined that the solar cell module has failed. A method for diagnosing a failure of a solar cell module as described. In the determination step, when the signal strength increases compared to when the solar cell module is normal at a specific frequency or frequency range other than the n-th harmonic higher than the frequency of the grid power in the frequency spectrum, 2. A failure diagnosis method for a solar cell module according to claim 1, wherein a failure of the solar cell module is determined. In the determining step, if the signal strength of the n-order harmonic higher than the frequency of the grid power in the frequency spectrum increases compared to when the solar cell module is normal, it is determined that the solar cell module has failed. The failure diagnosis method for a solar cell module according to claim 1. 2. The malfunction of the solar cell module according to claim 1, wherein, in the determining step, when the signal strength increases in a frequency region other than the nth harmonic of the frequency spectrum, the malfunction of the solar cell module is determined. diagnostic method. The determination step acquires the information on the ripple when the solar cell module of the string starts to operate or when the operation is normal, compares the information data on the ripple with the information data on the ripple at the time of measurement, and judges failure according to the difference. 2. The failure diagnosis method for a solar cell module according to claim 1, wherein the failure diagnosis method is performed by comparing with the determination. In the determination step, the magnitude of the signal intensity that changes at a frequency higher than the frequency of the grid power when a simulated failure occurs in the solar cell module is set as a threshold, and the grid power superimposed on the current of all the strings with the threshold. 2. A failure diagnosis method for a solar cell module according to claim 1, wherein the diagnosis is performed by comparing magnitudes of signal intensities of frequencies higher than the frequency of . In the determination step, between strings having the same number of modules in the same power plant, the magnitude of ripples generated in other strings is set as a threshold value, and the magnitudes of ripples of the string to be measured and the other strings are compared with each other. 2. The method of diagnosing a failure of a solar cell module according to claim 1, wherein the method is performed by: The determining step compares the signal strength of the nth harmonic of the frequency spectrum with the signal strength of a frequency portion other than the nth harmonic, and a failure occurs when an appreciable difference in signal strength occurs. 2. The method for diagnosing a failure of a solar cell module according to claim 1, wherein the estimation is made as follows. The determination step is performed when the magnitude of the signal strength at a specific frequency higher than the frequency of the grid power in the frequency spectrum increases compared to a normal state, and the signal strength is continuously detected for a predetermined time or longer. 2. The method of diagnosing a failure of a solar cell module according to claim 1, wherein the failure is determined when the failure is detected continuously in a plurality of determinations with different measurement times. A current measuring means for measuring a direct current flowing through a string of a photovoltaic power generation facility, a ripple information acquisition unit for acquiring information on a ripple superimposed on the direct current, and a magnitude of the ripple compared to when the solar cell module is normal. It is determined whether or not a failure has occurred in the solar cell module when the current is increasing, or when the change is detected as an increase in the signal intensity in a specific frequency band of the frequency spectrum obtained by frequency analysis of the current. A failure diagnosis device for a solar cell module, comprising a determination unit and a determination result output unit for outputting a determination result. 12. The failure detection device for a solar cell module according to claim 11, further comprising: an output means for continuously transmitting a signal indicating failure when said determination unit determines that a failure has occurred. A resonance circuit that resonates at a specific frequency of the frequency spectrum obtained by frequency analysis of the current is provided, and the resonance circuit is caused to resonate, and when the ripple reaches a certain level, it emits sound or emits light. 12. The failure detection device for a solar cell module according to claim 11, wherein the failure of the panel is audibly or visually displayed to notify a monitor or the like. 13. The failure detection device for a solar cell module according to claim 12, wherein the signal indicating the failure is one of sound, light, signal, radio wave, or a combination thereof. Ripple information acquisition processing for acquiring information on ripples superimposed on direct current flowing in each string of photovoltaic power generation equipment; A solar cell module characterized by causing a computer to perform determination processing for determining a failure when a change in signal strength increase is detected in a specific frequency band of a frequency spectrum obtained by frequency analysis of the current. diagnostic program.

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