JP6946128B2 - Power generation performance evaluation system and power generation performance evaluation method - Google Patents

Description

The present invention relates to a power generation performance evaluation system and a power generation performance evaluation method.

In recent years, with the enforcement of the total purchase system, the number of solar power generation plants, especially large-scale solar power plants (mega solar) consisting of tens of thousands of solar cell modules, has increased dramatically. In addition, it has a track record of several years since the start of operation of mega solar, and the secondary market of buying and selling and securitizing power plants that can expect stable power generation income is revitalizing. Usually, when constructing a mega solar, a monitoring device for evaluating power generation performance is provided. If a new power plant can be constructed, a monitoring device can be newly assembled, so that the transmission interval of the data to be handled can be flexibly set. However, when a monitoring device is retrofitted to an existing power plant, the amount of data that can be stored is limited by the existing system, so data is stored at relatively long intervals, such as 1-minute interval data and 10-minute interval data. It is common that it is done.

As a technique for evaluating power generation performance, for example, in Patent Document 1, the electric output value of a solar cell in a state that can be regarded as a sunny day is accumulated, and the electric output value of the solar cell is compared under almost the same conditions. The method for evaluating the power generation performance of a solar power plant is described in. Further, for example, Patent Document 2 describes a method of determining that the weather is fine if the change in the amount of solar radiation or the current every few seconds is smaller than the predetermined amount of change.

Japanese Unexamined Patent Publication No. 2016-54632 Japanese Unexamined Patent Publication No. 2016-208683

As described above, when data is stored at relatively long intervals, in the methods such as Patent Document 1 and Patent Document 2, the number of samplings for evaluating the power generation performance is increased due to the long data interval. Run short. Therefore, for example, when looking at the transition of the amount of power generation in fine weather and the transition of the amount of power generation when the weather is fluctuating, the transitions of both are similar, and it is the amount of power generation in fine weather, or other than that. In some cases, it was not possible to determine whether the amount of power generated was during the weather. Therefore, there has been a demand for a technique capable of accurately evaluating the amount of power generation even when the number of samples is small.

An object of the present invention is to provide a power generation performance evaluation system capable of accurately evaluating the amount of power generation even when the number of samples is small, and a power generation performance evaluation method.

In order to solve the above problems, the power generation performance evaluation system according to the present invention is a control device that controls a short-circuit current of a solar cell array in which a plurality of solar cells connected in series are connected in parallel and the solar cell array. Based on the sample data obtained from the correlation between the estimated amount of solar radiation calculated based on the operating current measured in the above and the amount of solar radiation measured by the pyranometer, the estimated amount of solar radiation and the amount of solar radiation It is determined whether or not the calculation unit for obtaining the regression line between the two and the sample data is within the width between the predetermined upper limit value and the lower limit value set based on the regression line, and the sample data within the width is determined. A power generation performance evaluation system comprising a determination unit for evaluating the power generation performance of the solar cell array.

The present invention is also understood as a power generation performance evaluation method performed by the power generation performance evaluation system.

According to the present invention, it is possible to accurately evaluate the amount of power generation even when the number of samples is small.

It is a figure which shows the configuration example of the power generation performance evaluation system in this Example. It is a graph which shows the temporal transition (a) of the solar radiation amount and the transition (b) of the change of the solar radiation amount when the weather is stable. It is a graph which shows the temporal transition (a) of the solar radiation amount and the transition (b) of the change of the solar radiation amount when the weather is not stable. It is explanatory drawing in the case of acquiring sample data from each graph shown in FIG. 2A. It is explanatory drawing in the case of acquiring sample data from each graph shown in FIG. 2B. It is explanatory drawing which shows an example of the change of the current-voltage characteristic of the solar cell array shown in FIG. It is a graph comparing the time transition of the amount of solar radiation obtained from a solar cell and the time transition of the amount of solar radiation obtained from a pyranometer. It is a flowchart which shows the processing procedure of the sample data extraction processing for power generation performance evaluation performed in this system. It is a graph which shows the time transition (a) of the amount of solar radiation in the stable weather such as a sunny day, and the regression line (b) of the measured value of a pyranometer, and the assumed amount of solar radiation. It is a graph which shows the temporal transition (a) of the amount of solar radiation in the unstable weather which repeats sunny and cloudy weather, and the regression line (b) of the measured value of a pyranometer, and the assumed amount of solar radiation.

Hereinafter, embodiments of the power generation performance evaluation system and the power generation performance evaluation method according to the present invention will be described in detail with reference to the accompanying drawings.

FIG. 1 is a diagram showing a configuration example of the power generation performance evaluation system 1000 in this embodiment. As shown in FIG. 1, the power generation performance evaluation system 1000 includes an array system 1 having a plurality of solar cell arrays, a cubicle 2 provided for each array system, an external communication device group 3, and a monitoring system 4. It is configured to have an output device group 5.

As shown in FIG. 1, the array system 1 has one or more solar cell arrays A and a junction box 12. The solar cell array A is configured by connecting the solar cell strings 11 in parallel in the junction box 12. A backflow prevention diode 121 is attached to the junction box 12 to prevent a current in the reverse direction from flowing into each solar cell string 11. It is also possible to select the current path of each solar cell string 11 by selecting the switch 122. One or more junction boxes 12 are connected in parallel for each solar cell array A. Further, the positive electrode and the negative electrode of the plurality of solar cell arrays A connected in parallel via the junction box 12 are connected to the cubicle 2. The solar cell string 11 is composed of a plurality of solar cell modules 111 arranged in series.

The cubicle 2 is a high-voltage power receiving facility having a power conditioner (control device), and is an ammeter 21, a signal conversion transmission device 22, a sampling processing unit 23, a control waveform generation unit 24, and a DC / AC conversion unit. It includes 25, an ammeter 26, a voltmeter 27, and a control unit 28.

Controlling the maximum power from a plurality of solar cell arrays A is called MPPT control (Maximum Power Point Tracking). This MPPT control is achieved by using the DC power measured by the ammeter 26 and the voltmeter 27 inside the cubicle 2 and controlling the operation of the DC / AC converter 25 having the DC / DC converter circuit. Is to be done. The DC / AC converter circuit having a DC / DC converter circuit, which is a DC boost converter, boosts the DC voltage from the solar cell array A and supplies it to the DC / AC inverter section of the DC / AC converter 25. , Supply AC voltage to the outside.

Generally, in a large-scale photovoltaic power generation system, the DC voltage and DC current measured during MPPT control are sampled (sampled) by the sampling processing unit 23, and then the control waveform generation unit 24 and the signal conversion transmission device 22. Is output to the monitoring system 4 via the external communication device group 3. The solar radiation intensity measured by the pyranometer 21, that is, the amount of solar radiation per unit area (kW / m2) is unified as a meteorological signal in a transducer (not shown) and transmitted to the monitoring system 4 via the signal conversion transmission device 22. .. The signal transmitted to the control waveform generation unit 24 is used to generate a command signal for MPPT control. The control unit 28 controls the current and voltage so that the maximum power can be taken out from each solar cell string 11.

The external communication device group 3 includes a HUB 31, a PLC (Power Line Communication) 32, an OD ring 33, and a transmission device 34. The OD ring 32 connects each of the cubicles 2 via the HUB 31. Since each of these devices has a conventionally known configuration, a specific description thereof will be omitted here.

The monitoring system 4 is composed of, for example, one or a plurality of computers or clouds, which are generally used as hardware. These computers are composed of hardware that is common to computers, such as storage devices such as memory and HDD (Hard Disk Drive), and a CPU (Central Processing Unit) that controls each part of the system and executes arithmetic processing. ing. The processing in this system is actually realized by the CPU reading a program from the memory and executing it. The above program is provided by being pre-installed in a ROM or the like, or is a computer-readable recording medium such as a CD-ROM, CD-R, or DVD (Digital Versatile Disk) in an installable or executable format. It may be recorded and provided or distributed. Further, the above program may be provided or distributed by storing it on a computer connected to a network such as the Internet and downloading it via the network.

As shown in FIG. 1, the monitoring system 4 includes, for example, a data server 41, an application server 42, a Web server 43, a relay device 44, a physical switch 45, and a firewall 46.

The data server 41 is a server that stores data transmitted from each cubicle 2 in a storage device such as a memory or an HDD. The application server 42 is a server that executes various processes in the system (calculation unit, determination unit) using the data stored in the data server 41. The Web server 43 receives instructions and information for executing various processes in this system from the input / output device group 5, executes the application stored in the application server 42, and outputs the result to the input / output device group 5. It is a server to send.

The relay device 44 is a device that relays communication between various devices constituting the monitoring system 4, such as a router, a hub, and a bridge. The physical switch 45 is a device that distributes data communication to various devices constituting the monitoring system 4. The firewall 46 controls communication between the monitoring system 4 and the input / output device group 5.

The input / output device group 5 includes a PC device 51 and a portable device 52. The PC device 51 is a general PC (Personal Computer) as hardware, and is an input device such as a keyboard that receives input of information necessary for executing and setting the system from a user, and a processing result executed by the system. It is a computer having an output device such as a display that outputs. The portable device 52 is a general mobile terminal (for example, a smartphone or tablet terminal) as hardware, and is a computer having an input device and an output device having the same functions as the PC device 51. The networks N1 and N2 are, for example, general public network such as the Internet. The specific processing executed by each of the above parts constituting this system will be described later.

FIG. 2A is a graph showing the temporal transition (a) of the amount of solar radiation and the transition (b) of the change in the amount of solar radiation when the weather is stable. Further, FIG. 2B is a graph showing a temporal transition (a) of the amount of solar radiation and a transition (b) of the change in the amount of solar radiation when the weather is not stable.

As shown in FIG. 2A (a), when the weather is stable, for example, in fine weather, the amount of solar radiation in a certain day changes as shown in Graph 21 while maintaining a certain correlation with the weather. It can be seen that the solar radiation change amount 22 indicating the change in the solar radiation amount at this time changes between a certain width D as shown in FIG. 2A (b). This is because the amount of solar radiation is stably obtained, so the difference between the amount of solar radiation measured at a certain point in time and the amount of solar radiation measured immediately before (or immediately after) is within the above width D. Is shown. In FIG. 2A (b), it can be seen that the amount of change in solar radiation 22 per second is within ± 0.01, which is the width D, in almost all time zones of the day.

On the other hand, as shown in FIG. 2B (a), when the weather is unstable, for example, when sunny and cloudy weather repeats, the amount of solar radiation in a certain day does not have a certain correlation with the weather and is shown in Graph 23. It changes like this. It can be seen that the amount of change in solar radiation 24, which indicates the amount of change in solar radiation at this time, does not necessarily change within a certain width D, as shown in FIG. 2B (b). This indicates that since the amount of solar radiation cannot be stably obtained, the difference between the amount of solar radiation measured at a certain point in time and the amount of solar radiation measured immediately before (or immediately after) does not fall within the above width D. There is. In FIG. 2B (b), it can be seen that the amount of change in solar radiation 24 per second does not fall within the width D of ± 0.01 in a time zone of more than half of the day.

FIG. 3A is an explanatory diagram in the case of acquiring sample data from each graph shown in FIG. 2A. FIG. 3B is an explanatory diagram in the case of acquiring sample data from each graph shown in FIG. 2B.

When data is acquired from the graph showing the transition of the amount of solar radiation shown in FIG. 3A at a relatively long interval with respect to the horizontal axis (10-minute interval in FIG. 3A), as shown in FIG. 3A (a), Data of X11 to X15 can be obtained. As a change in the amount of solar radiation at this time, as shown in FIG. 3A (b), data of Y11 to Y14 can be obtained.

Similarly, when data is acquired from the graph showing the transition of the amount of solar radiation shown in FIG. 3B at a relatively long interval with respect to the horizontal axis (10-minute interval in FIG. 3B), it is shown in FIG. 3B (a). As described above, the data of X21 to X25 can be obtained. As a change in the amount of solar radiation at this time, as shown in FIG. 3B (b), data of Y21 to Y24 can be obtained.

Comparing the graphs shown in (b) of FIG. 3A and (b) of FIG. Even though the weather is perceived or stable, there is a possibility that it will be misrecognized as unstable weather with repeated sunny and cloudy weather. As described above, the longer the acquisition interval of the sample data, the higher the possibility of causing the above-mentioned misrecognition.

FIG. 4 is an explanatory diagram showing an example of changes in the current-voltage characteristics of the solar cell array A shown in FIG. In general, it is known that the soldering of the interconnector portion connecting adjacent cells of the solar cell module 111 is gradually peeled off as a cause of deterioration of the solar cell module 111. Since such deterioration occurs in the entire solar cell array A, the series resistance becomes large in all the solar cell cells constituting the solar cell array A.

As shown in FIG. 4A, the current-voltage characteristic in stable weather such as sunny weather draws a curve having a short-circuit current value I41 as shown in Graph 45. In this case, the maximum power by MPPT control can be obtained at the current value I42. On the other hand, as shown in Graph 46, the current-voltage characteristic in unstable weather where sunny and cloudy weather repeats draws a curve in which the short-circuit current value I43 is smaller than the current value I41. In this case, the maximum power by MPPT control can be obtained at a current value I44 smaller than the current value I42.

Usually, in a photovoltaic power generation facility, a silica gel pyranometer capable of picking up a wide wavelength of light is used to measure the amount of solar radiation. Silica gel can react to a wide wavelength, but its reaction speed is slow. According to the ISO9060 standard, the response speed is 15 seconds or less for Secondary --standard, 30 seconds or less for First --class, and 60 seconds or less for Second --class. It is set to be. As shown in FIG. 4A, the value of the short-circuit current of the current-voltage characteristic of the solar cell array A is proportional to the amount of solar radiation. FIG. 4B is a graph showing the temporal change of the short-circuit current of the solar cell. As shown in FIG. 4B, it can be seen that the value of the short-circuit current increases during the daytime because the amount of solar radiation is large, and decreases after the daytime.

Since solar cells are generally composed of silicon, the frequency band of the wavelength at which they react is slightly inferior to that of silica gel, but the reaction rate is relatively high. Therefore, it can be said that the measured short-circuit current value represents the magnitude of the amount of solar radiation at that time. On the other hand, it is known that the measured value of the pyranometer converges in 10 to 20 seconds at the earliest. FIG. 5 is a graph comparing the temporal transition of the amount of solar radiation obtained from the solar cell and the temporal transition of the amount of solar radiation obtained from the pyranometer. As shown in FIG. 5, compared with the graph 5A showing the temporal transition of the amount of solar radiation obtained from the solar cell, the graph 5B showing the temporal transition of the amount of solar radiation obtained from the pyranometer is obtained from the solar cell. It can be seen that the time to obtain the same amount of solar radiation as the amount of solar radiation received is delayed (there is a time lag). When such a time lag occurs, as shown below, the correlation between the measured value of the pyranometer and the estimated amount of solar radiation also deviates. In stable weather such as fine weather, sample data that maintains the correlation can be obtained even when the above time lag occurs, but in unstable weather where sunny and cloudy weather repeats, the amount of solar radiation Since the change is also large, it is easy to obtain sample data that deviates from the correlation. This system makes use of this difference in reaction.

Specifically, as shown in FIG. 4A, the current values I42 and I43 of the current (operating current) at the maximum power point where the power is maximized are MPPT controlled according to the change in solar radiation. .. The ratio of the operating current to the short-circuit current is r, the operating current of the solar cell module 111 group measured by the power conditioner that controls the solar cell is Iopa, the number of strings of the solar cell module 111 group is m, and the number of strings of the solar cell is m. Assuming that the short-circuit current is Isc, the estimated solar radiation amount p can be expressed by the equation (1).

p = (Iopa / m) / r / Isc… (1)
r is described in the non-patent document IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, VOL. 6, NO. 4, OCTOBER 2015 "A New Sensorless Hybrid MPPT Algorithm Based on Fractional Short-Circuit Current Measurement and P & O MPPT".

FIG. 6 is a flowchart showing a processing procedure of sample data extraction processing for power generation performance evaluation performed in this system. The process is executed by the application server 42 according to the instruction received from the input / output device group 5 via the Web server 43, and the process result is transmitted to the input / output device group 5.

As shown in FIG. 6, the application server 42 reads out the measured value of the pyranometer 21 accumulated in the data server 41 during a predetermined period (for example, 24 hours a day) specified in the input / output device group 5 ( In step S601), the value of the operating current IO stored in the data server 41 is read out in the same period (step S602).

Further, the application server 42 calculates the short-circuit current Isc from the read operating current Iop (step S603), and calculates the estimated solar radiation amount p (step S604). The estimated amount of solar radiation p can be calculated by the above equation (1).

The application server 42 obtains a correlation between the measured value of the pyranometer obtained in step S601 and the estimated amount of solar radiation obtained in step S604 (step S605).

FIG. 7 is a graph showing a temporal transition (a) of the amount of solar radiation in stable weather such as fine weather, and a regression line (b) between the measured value of the pyranometer and the assumed amount of solar radiation. Further, FIG. 8 is a graph showing a temporal transition (a) of the amount of solar radiation in unstable weather in which sunny weather and cloudy weather are repeated, and a regression line (b) of the measured value of the pyranometer and the assumed amount of solar radiation.

Similar to the case of FIG. 2A (a), FIG. 7 (a) shows the temporal change of the amount of solar radiation in stable weather such as sunny weather, and in this case, the weather is stable such as sunny weather. It can be seen that the value of the amount of solar radiation gradually increases during the daytime. FIG. 7B is a graph showing the correlation between the transitional amount of solar radiation as shown in FIG. 7A and the assumed amount of solar radiation at that time by a regression line. In FIG. 7B, the measured value of the pyranometer 21 at a certain time is on the horizontal axis, and the assumed solar radiation calculated by the above equation (1) using the operating current and the short-circuit current obtained from the solar cell at that time. The point P11 is plotted with the amount on the vertical axis, and the regression line f is calculated. Further, as in the case of FIG. 2A (b), there is little variation at almost all points, and the variation is within a certain width D centered on the regression line f. Therefore, it can be seen that there is a strong correlation between the estimated amount of solar radiation and the measured value of the pyranometer in the case of stable weather such as fine weather. Therefore, for example, all of these points are used as a judgment material for determining that the weather is fine.

On the other hand, FIG. 8A shows a temporal change in the amount of solar radiation in unstable weather in which sunny weather and cloudy weather are repeated, as in the case of FIG. 2B (a). In this case, sunny weather and cloudy weather are shown. It can be seen that the increase and decrease in the amount of solar radiation is conspicuous during the daytime due to the unstable weather that repeats. FIG. 8B is a graph showing the correlation between the transitional amount of solar radiation as shown in FIG. 8A and the assumed amount of solar radiation at that time by a regression line. In FIG. 8B, points P21a and P22a are plotted with the measured value of the pyranometer 21 on the horizontal axis and the estimated amount of solar radiation on the vertical axis as in the case of FIG. 7B, and the regression line f is calculated. doing. Further, as in the case of FIG. 2B (b), there are variations in many points, and the width D does not fall within a certain width D centered on the regression line f. For example, the point P21a is within the skin D, but the point 22a is not within the width D. Therefore, in the case of unstable weather in which sunny weather and cloudy weather are repeated, it can be seen that there is no correlation between the estimated amount of solar radiation and the measured value of the pyranometer as in the case of stable weather such as sunny weather. Therefore, for example, of all these points, only the points within the width D, which has a high correlation, are used as the judgment material for determining that the weather is fine. For the width D, for example, a predetermined upper limit value (for example, +0.01) and a lower limit value (for example, −0.01) are set at each point constituting the regression line. The explanation will be continued by returning to FIG.

When the application server 42 obtains the correlation with the assumed amount of solar radiation in step S605, it determines whether or not the obtained correlation is high (step S605). When the correlation is high, for example, it is determined whether or not the points are plotted within the range of the width D shown in (b) of FIG. 7 and (b) of FIG. Is within the range of the width D. When the application server 42 determines that the obtained correlation is high (step S605; Yes), the application server 42 outputs this point as data to be evaluated for power generation performance (step S607). On the other hand, when the application server 42 determines that the obtained correlation is not high (step S605; Yes), the application server 42 discards the point without outputting it as data to be evaluated for power generation performance (step S608).

In this system, as described above, the data to be evaluated for power generation performance is selected according to the presence or absence of the correlation between the estimated amount of solar radiation and the measured value of the pyranometer. Therefore, for example, in the case of stable weather such as fine weather, the power generation performance can be evaluated more accurately than in the past by targeting a large number of correlated points as evaluation targets. On the other hand, for example, in the case of unstable weather in which sunny weather and cloudy weather are repeated, the amount of power generation can be accurately measured even when the number of samples is small by targeting a small amount of correlated points for evaluation. It is possible to determine the state of stable weather such as fine weather, and to evaluate the power generation performance with high accuracy as in the case of stable weather such as fine weather.

In the evaluation of power generation performance, for example, the accuracy of the operating current obtained from the measuring instrument built in the power conditioner (that is, the measurement error of the power conditioner) is determined at n points within the range of the width D. Assuming x%, the application server 42 uses the equation x / √n%, which is the value obtained by dividing the measurement error of the power conditioner by the square root of the number of sample data to be evaluated, in the array system 1. Calculate the error in the evaluation of the power generation performance of. Therefore, it is possible to accurately evaluate the power generation performance from the determination of fine weather and the obtained data, and it can be applied to the performance analysis and failure diagnosis of photovoltaic power generation. As described above, according to this system, it is possible to provide a highly accurate monitoring function regardless of the existing sampling points at the site to be maintained afterwards.

The present invention is not limited to the above embodiment, includes various modifications, and is not necessarily limited to those having all the configurations described above. Further, it is possible to replace a part of the configuration of a certain embodiment with the configuration of another embodiment, or add, delete, or replace a part of the configuration of each embodiment with another configuration. For example, in the above embodiment, the case where the monitoring system 4 is configured by a plurality of servers is shown, but these may be configured as one server, and the input / output device group 5 constitutes the monitoring system 4. It may be provided on the server. Further, in the above embodiment, the junction boxes 12 are connected in parallel and the current output from the junction box 12 is input to the cubicle 2, but the cubicle 2 is provided for each junction box 12 and the junction box 12 is used as one unit. It may be possible to collect an electric current. In this case, since the current is collected for each array system 1 having the junction box 12, the power generation performance can be evaluated accurately for each array system 1.

1000 Power generation performance evaluation system 1 Array system 11 Solar cell string 111 Solar cell module 12 Junction box 121 Backflow prevention diode 122 Switch 2 Cubicles 21 Ammeter 22 Signal conversion transmission device 23 Sampling processing unit 24 Control waveform generator 25 DC / AC conversion unit 26 Ammeter 27 Voltmeter 28 Control unit 3 External communication device group 31 HUB
32 PLC
33 OD ring 34 Transmission device 4 Monitoring system 41 Data server 42 Application server 43 Web server 44 Relay device 45 Physical switch 46 Firewall 5 Input / output device group 51 PC device 52 Portable device N1, N2 network.

Claims (2)

For each of the first weather and the second weather, the short-circuit current of the solar cell array in which a plurality of solar cells connected in series are connected in parallel and the short-circuit current of the solar cell array are measured by a control device that controls the solar cell array. A regression line between the estimated amount of solar radiation and the amount of solar radiation based on the sample data obtained from the correlation between the estimated amount of solar radiation calculated based on the operating current and the amount of solar radiation measured by the pyranometer. And the calculation unit to find
It is determined whether or not the sample data is within the width between the predetermined upper limit value and the lower limit value set based on the regression line, and the sample data within the width is used to evaluate the power generation performance of the solar cell array. Judgment unit to be the target data and
Equipped with a,
The determination unit calculates an error in evaluating the power generation performance of the solar cell array based on the value obtained by dividing the accuracy of the operating current obtained from the control device by the square root of the number of sample data to be evaluated. do,
A power generation performance evaluation system characterized by this. For each of the first weather and the second weather, the short-circuit current of the solar cell array in which a plurality of solar cells connected in series are connected in parallel and the short-circuit current of the solar cell array are measured by a control device that controls the solar cell array. A regression line between the estimated amount of solar radiation and the amount of solar radiation based on the sample data obtained from the correlation between the estimated amount of solar radiation calculated based on the operating current and the amount of solar radiation measured by the solar radiation meter. Seeking,
It is determined whether or not the sample data is within the width between the predetermined upper limit value and the lower limit value set based on the regression line, and the sample data within the width is used to evaluate the power generation performance of the solar cell array. In the power generation performance evaluation method used as the target data
In the determination, an error in evaluating the power generation performance of the solar cell array is calculated based on the value obtained by dividing the accuracy of the operating current obtained from the control device by the square root of the number of sample data to be evaluated. ,
A power generation performance evaluation method characterized by this.

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