JP6355491B2 - Pyrometer performance degradation state estimation device, psoriometer performance degradation state estimation system - Google Patents

Description

  The present invention relates to a pyranometer performance degradation state estimation device, a pyranometer performance degradation state estimation system, and a pyranometer performance degradation state estimation method for estimating a degradation state of a measurement performance of a pyranometer.

  In recent years, there is an increasing number of customers who install a distributed power source such as a solar power generation and supply electric power to an electric power load using the solar power generation and power from a commercial power system. Here, if a large amount of photovoltaic power generation is introduced, output fluctuation of the photovoltaic power generation affects the commercial power system, so it is important to accurately evaluate the output fluctuation of the photovoltaic power generation.

  And in order to accurately evaluate the output fluctuation of photovoltaic power generation, it is conceivable to install a pyranometer at multiple points and measure the solar radiation intensity at each point. There is a possibility that the output fluctuation of the photovoltaic power generation cannot be accurately grasped. For this reason, the technique which prevents the deterioration of a pyranometer conventionally is proposed (for example, refer patent document 1).

JP 2000-266595 A

  However, in the above conventional technique, there is a possibility that the pyranometer may continue to be used in a deteriorated state without noticing that the pyranometer has deteriorated.

  In other words, the conventional technology described above prevents the deterioration of the pyranometer. However, when the pyranometer is used over a long period of time, the pyranometer deteriorates little by little, and the pyranometer deteriorates. However, there is a risk that it will continue to be used in a deteriorated state without noticing. Also, even if the prevention of deterioration of the pyranometer is not functioning effectively, it will not be noticed that the pyranometer has deteriorated and will continue to be used in a deteriorated state.

  On the other hand, there may be a failure in the pyranometer due to external factors. Also in this case, there is a possibility that the output fluctuation of the photovoltaic power generation cannot be accurately grasped. For example, if the pyranometer is damaged by a flying object or the like, or if inundation such as rainwater occurs inside the pyranometer, the measurement accuracy of the pyranometer may be greatly reduced.

  For this reason, it is necessary to periodically perform calibration and inspection work on the pyranometer, but a large amount of pyranometer is required to accurately evaluate the effect of fluctuations in the output of photovoltaic power generation on the commercial power system. Therefore, it is necessary to periodically perform calibration work and inspection work for the large amount of pyranometer. Here, if it is possible to grasp the deterioration state and failure state of the pyranometer, it is no longer necessary to perform calibration and inspection work on the non-degraded pyranometer. Can be reduced. Therefore, a technique for estimating the degradation state of the measurement performance such as the deterioration state and failure state of the pyranometer is desired.

  Therefore, the present invention has been made in view of such problems, and a psoriometer performance degradation state estimation device, a psoriometer performance degradation state estimation system, and a solar radiation system that can estimate the degradation state of the measurement performance of a psoriometer. An object of the present invention is to provide a method for estimating the performance degradation state.

  In order to achieve the above object, a psoriometer performance degradation state estimation device according to an aspect of the present invention is a psoriometer performance degradation state estimation device that estimates a degradation state of a measurement performance of a psoriometer, wherein A solar radiation intensity acquisition unit for acquiring solar radiation intensity data indicating time series data of the measured solar radiation intensity, the acquired solar radiation intensity data, a trend component indicated by a polynomial, and subtracting the trend component from the solar radiation intensity data From the decomposition component acquisition unit that acquires the trend component and the residual component by decomposing into the residual component obtained, and the solar radiation from the acquired change in the trend component and change in the residual component A performance degradation state estimation unit that estimates a degradation state of the measurement performance of the meter.

  According to this, the insolation device performance degradation state estimating device decomposes the solar radiation intensity data obtained from the solar radiation meter into a trend component represented by a polynomial and a residual component obtained by subtracting the trend component from the solar radiation intensity data, From the change of the trend component and the change of the residual component, the degradation state of the measurement performance of the pyranometer is estimated. Here, the inventors of the present application, as a result of diligent research and examination, easily decomposes the solar radiation intensity data measured by the pyranometer into the trend component and the residual component, and evaluates the change of each component, thereby simplifying It was found that the degradation state of the measurement performance of the pyranometer can be estimated. In other words, the trend component can be generated by applying the solar radiation intensity data to the polynomial model, and the residual component can be generated by subtracting the trend component from the solar radiation intensity data. It can be easily broken down into components. Thereby, according to the pyranometer performance fall state estimation apparatus, the fall state of the measurement performance of a pyranometer can be estimated.

  Further, the solar radiation intensity acquisition unit obtains a ratio of the solar radiation intensity at the measurement point to the theoretical solar radiation intensity at the upper end of the atmosphere as a clear sky index, and converts each time series data of the solar radiation intensity measured by the solar radiation meter into the clear sky index. The obtained value may be acquired as the solar radiation intensity data.

  According to this, the radiation meter performance degradation state estimation device acquires values obtained by converting each time series data of the radiation intensity measured by the radiation meter into a clear sky index as radiation intensity data. Here, the solar radiation intensity input from sunlight varies greatly depending on the time (season), time, place (latitude, longitude), and the like. For this reason, the solar radiation performance degradation state estimation apparatus can handle the solar radiation intensity equivalently by converting the solar radiation intensity measured by the solar radiation meter into a clear sky index and normalizing it.

  In addition, the decomposition component acquisition unit, based on the solar radiation intensity data in the two corresponding periods among the plurality of solar radiation intensity data in the plurality of periods acquired by the solar radiation intensity acquisition unit, the trend component in the two periods The performance degradation state estimation unit may estimate the degradation state of the sensitivity performance of the pyranometer by comparing the trend components in the two periods.

  According to this, the pyranometer performance degradation state estimation device acquires and compares the trend components in the two periods from the corresponding solar radiation intensity data in the two periods among the plurality of solar radiation intensity data in the plurality of periods. Thus, the deterioration state of the sensitivity performance of the pyranometer is estimated. Here, as a result of intensive studies and examinations, the inventor of the present application has found that the deterioration state of the sensitivity performance of the pyranometer can be estimated from the change in the trend component of the solar radiation intensity data. That is, the trend component is an index for evaluating the magnitude of the output signal with respect to the input signal to the pyranometer. Thereby, according to the pyranometer performance fall state estimation apparatus, the fall state of the sensitivity performance of a pyranometer can be simply estimated by comparing the trend component of the solar radiation intensity data in two corresponding periods.

  In addition, the decomposition component acquisition unit is configured to obtain the residual in the two periods from the solar radiation intensity data in two corresponding periods among the plurality of solar radiation intensity data in the plurality of periods acquired by the solar radiation intensity acquisition unit. The performance degradation state estimation unit obtains a component, and estimates a degradation state of the response performance of the pyranometer by comparing time constants of step responses obtained from the residual components in the two periods. May be.

  According to this, the pyranometer performance degradation state estimation device acquires the residual component in the two periods from the solar radiation intensity data in the corresponding two periods of the plurality of solar radiation intensity data in the plurality of periods, By comparing the time constants of the step response obtained from the residual component, the degradation state of the response performance of the pyranometer is estimated. Here, the present inventor has found that, as a result of diligent research and examination, it is possible to estimate the deterioration state of the response performance of the pyranometer from the change in the time constant of the step response obtained from the residual component of the solar radiation intensity data. It was. That is, the residual component is an index for evaluating the delay time of the output signal when the step signal is input to the pyranometer. Thereby, according to the pyranometer performance degradation state estimation device, the degradation state of the pyranometer response performance is obtained by comparing the time constants of the step response obtained from the residual components of the solar radiation intensity data in the two corresponding periods. It can be easily estimated.

  Further, the solar radiation intensity data in the plurality of periods acquired by the solar radiation intensity acquisition unit is classified into a plurality of groups by the k-means method, and the solar radiation intensity data in the corresponding two periods in the same group is obtained. A solar radiation intensity extracting unit for extracting, and the decomposition component acquiring unit acquires the trend component and the residual component in the two periods from the solar radiation intensity data in the two periods, and the performance degradation state estimation The unit may estimate a decrease in measurement performance of the pyranometer from the change in the trend component during the two periods and the change in the residual component during the two periods.

  According to this, the solar radiation performance degradation state estimation device classifies solar radiation intensity data into a plurality of groups by the k-means method, extracts solar radiation intensity data in two corresponding periods within the same group, and the 2 From the change in the trend component of the solar radiation intensity data and the change in the residual component in one period, the deterioration state of the measurement performance of the solar radiation meter is estimated. Here, as a result of earnest research and examination, the inventor of the present application uses the k-means method to accurately classify solar radiation intensity data into groups having similar conditions (statistical features) that can be compared. I found that I can do it. By using this method, natural sunlight can be used as input light (test light) without being conscious of fluctuations in sunlight due to clouds, etc. No field work is required. For this reason, according to the psoriometer performance degradation state estimation device, the measurement performance of the psoriometer is determined from the change in the trend component and residual component of the solar radiation intensity data in the corresponding two periods within the same group classified by the k-means method. Can be accurately estimated.

  In addition, the solar radiation intensity extracting unit calculates the entropy between two groups and determines a boundary between the two groups in the plurality of groups classified by the k-means method, thereby determining the boundary between the two groups. May be reclassified, and the solar radiation intensity data in two corresponding periods within the same reclassified group may be extracted.

  According to this, the psoriometer performance degradation state estimating apparatus calculates entropy between two groups classified by the k-means method, and determines a boundary between the two groups, thereby re-creating a plurality of groups. Classification is performed to extract solar radiation intensity data in two corresponding periods within the same group. Here, the inventor of the present application has made it possible to improve the accuracy of group classification by calculating entropy between two groups and determining the boundary between the two groups as a result of intensive research and examination. I found it. For this reason, according to the pyranometer performance degradation state estimation apparatus, the degradation state of the pyranometer measurement performance can be accurately estimated by calculating the entropy and reclassifying the group.

  The solar radiation intensity extracting unit may classify the plurality of solar radiation intensity data in the plurality of periods into the plurality of groups according to the magnitude of the solar radiation intensity data and the magnitude of fluctuation of the solar radiation intensity data.

  According to this, the solar radiation performance degradation state estimation device classifies the solar radiation intensity data into a plurality of groups according to the magnitude of the solar radiation intensity data and the magnitude of fluctuation of the solar radiation intensity data. For this reason, since the solar radiation performance degradation state estimation apparatus can easily classify solar radiation intensity data into a plurality of groups, it is possible to easily estimate the degradation state of the solar radiation measurement performance.

  Further, the solar radiation intensity extraction unit calculates a daily average value of the solar radiation intensity data as a size of the solar radiation intensity data, and calculates an integrated value in a predetermined cycle of a power spectrum density of the solar radiation intensity data as a variation of the solar radiation intensity data. By calculating as the magnitude of, the plurality of solar radiation intensity data in the plurality of periods may be classified into the plurality of groups.

  According to this, the solar radiation performance degradation state estimating device classifies the solar radiation intensity data into a plurality of groups based on the daily average value of the solar radiation intensity data and the integrated value of the power spectrum density of the solar radiation intensity data in a predetermined cycle. For this reason, since the solar radiation performance degradation state estimation device can accurately classify the solar radiation intensity data into a plurality of groups, it can accurately estimate the degradation state of the measurement performance of the solar radiation meter.

  In addition, the present invention can be realized not only as such a pyranometer performance degradation state estimation device, but also the above-mentioned pyranometer and the above-mentioned pyranometer performance degradation state estimation device that estimates the degradation state of the measurement performance of the pyranometer It can implement | achieve as a psoriometer performance degradation state estimation system provided with.

  In addition, the present invention can also be realized as a method for estimating a psoriometer performance degradation state that includes a characteristic process performed by a processing unit included in the above-described psometer performance degradation state estimation apparatus. Further, it can be realized as a program or an integrated circuit for causing a computer to execute characteristic processing included in the method for estimating the degradation state of the pyranometer. Needless to say, such a program can be distributed via a recording medium such as a CD-ROM and a transmission medium such as the Internet.

  ADVANTAGE OF THE INVENTION According to this invention, the pyranometer performance fall state estimation apparatus which can estimate the fall state of the measurement performance of a pyranometer can be provided.

It is a figure which shows the structure of a pyranometer performance fall state estimation system provided with the pyranometer performance fall state estimation apparatus which concerns on embodiment of this invention. It is a block diagram which shows the functional structure of the pyranometer performance degradation state estimation apparatus which concerns on embodiment of this invention. It is a flowchart which shows an example of the process which the pyranometer performance fall state estimation apparatus which concerns on embodiment of this invention performs. It is a flowchart which shows an example of the process in which the solar radiation intensity acquisition part which concerns on embodiment of this invention acquires solar radiation intensity data. It is a flowchart which shows an example of the process which the solar radiation intensity extraction part which concerns on embodiment of this invention extracts solar radiation intensity data. It is a figure explaining the process in which the solar radiation intensity extraction part which concerns on embodiment of this invention classifies several solar radiation intensity data according to the magnitude | size of a solar radiation intensity data, and the magnitude | size of a fluctuation | variation. It is a figure explaining the process in which the solar radiation intensity extraction part which concerns on embodiment of this invention classifies several solar radiation intensity data according to the magnitude | size of a solar radiation intensity data, and the magnitude | size of a fluctuation | variation. It is a figure explaining the process which the solar radiation intensity extraction part which concerns on embodiment of this invention classify | categorizes several solar radiation intensity data into a some group by k-means method. It is a figure explaining the process in which the solar radiation intensity extraction part which concerns on embodiment of this invention calculates an entropy, and determines the boundary between two groups. It is a figure explaining the process which the solar radiation intensity extraction part which concerns on embodiment of this invention reclassifies a some group. It is a flowchart which shows an example of the process in which the decomposition | disassembly component acquisition part which concerns on embodiment of this invention acquires a trend component and a residual component. It is a figure explaining the process which the decomposition | disassembly component acquisition part which concerns on embodiment of this invention isolate | separates a trend component and a residual component. It is a figure explaining the process which the decomposition | disassembly component acquisition part which concerns on embodiment of this invention isolate | separates a trend component and a residual component. It is a flowchart which shows an example of the process in which the performance fall state estimation part which concerns on embodiment of this invention estimates the fall state of the measurement performance of a pyranometer. It is a figure explaining the process in which the performance fall state estimation part which concerns on embodiment of this invention estimates the fall state of the sensitivity performance of a pyranometer. It is a figure explaining the process in which the performance fall state estimation part which concerns on embodiment of this invention estimates the fall state of the response performance of a pyranometer. It is a figure explaining the process in which the performance fall state estimation part which concerns on embodiment of this invention estimates the fall state of the response performance of a pyranometer. It is a block diagram which shows the minimum structure of the pyranometer performance degradation state estimation apparatus which concerns on embodiment of this invention.

  Hereinafter, a pyranometer performance degradation state estimation device and a pyranometer performance degradation state estimation system according to an embodiment of the present invention will be described with reference to the drawings.

  Each of the embodiments described below shows a preferred specific example of the present invention. The numerical values, shapes, components, arrangement positions and connection forms of components, steps, order of steps, and the like shown in the following embodiments are merely examples, and are not intended to limit the present invention. In addition, among the constituent elements in the following embodiments, constituent elements that are not described in the independent claims indicating the highest concept of the present invention are described as optional constituent elements that constitute a more preferable embodiment.

(Embodiment)
FIG. 1 is a diagram showing a configuration of a pyranometer performance degradation state estimation system 10 including a pyranometer performance degradation state estimation device 100 according to an embodiment of the present invention.

  As shown in FIG. 1, the pyranometer performance degradation state estimation system 10 includes a pyranometer performance degradation state estimation device 100 and a pyranometer 200.

  The pyranometer performance degradation state estimation device 100 is a computer that estimates the degradation state of the measurement performance of the pyranometer 200. Here, estimating the deterioration state of the measurement performance of the pyranometer 200 includes estimating the deterioration state of the pyranometer 200 or estimating the failure state of the pyranometer 200. The pyranometer performance degradation state estimation apparatus 100 may be realized by a general-purpose computer system such as a personal computer executing a program, or may be realized by a dedicated computer system. A detailed configuration of the pyranometer performance degradation state estimation device 100 will be described later.

  The pyranometer 200 is provided with a plurality of pyranometers (the pyranometers 201, 202, 203, etc.), and the respective pyranometers are arranged at different points and measure the solar radiation intensity at a constant time interval. In other words, the solar radiation meter 200 is a facility installed for grasping the power generation output of solar power generation. From the measured value of the solar radiation intensity by the solar radiation meter 200, the solar radiation near the solar radiation meter 200 is installed. The power generation output of power generation can be estimated. In addition, about the installation place of the solar radiation meter 200, and the frequency with which the solar radiation meter 200 measures solar radiation intensity, it does not specifically limit.

  In addition, the pyranometer 200 outputs the measured solar radiation intensity to the pyranometer performance degradation state estimation device 100. The pyranometer performance deterioration state estimation device 100 acquires the solar radiation intensity and estimates a degradation state of the measurement performance of the solar radiation meter 200 that measures the solar radiation intensity. Note that the timing at which the pyranometer 200 outputs the solar radiation intensity to the pyranometer performance degradation state estimation device 100 is not particularly limited. For example, the solar radiation meter 200 may output the solar radiation intensity to the solar radiation performance degradation state estimation device 100 each time the solar radiation intensity is measured, or may output the solar radiation intensity at a predetermined time interval, or the usage time has elapsed. You may output so that a transmission interval may become short, so that it is.

  Next, a detailed functional configuration of the pyranometer performance degradation state estimation device 100 will be described.

  FIG. 2 is a block diagram showing a functional configuration of the pyranometer performance degradation state estimation device 100 according to the embodiment of the present invention.

  The pyranometer performance degradation state estimation device 100 is a device that estimates the degradation state of the measurement performance of the pyranometer 200, and as shown in the figure, the solar radiation intensity acquisition unit 110, the solar radiation intensity extraction unit 120, and the decomposition component acquisition Unit 130, performance degradation state estimation unit 140, and storage unit 150.

  The solar radiation intensity acquisition unit 110 acquires solar radiation intensity data indicating time series data of solar radiation intensity measured by the solar radiation meter 200. Specifically, the solar radiation intensity acquisition unit 110 acquires, as solar radiation intensity data, values obtained by converting each time series data of solar radiation intensity measured by the solar radiation meter 200 into a clear sky index.

  Here, the ratio of the solar radiation intensity at the measurement point to the theoretical solar radiation intensity at the upper end of the atmosphere is defined as a clearness index (CI). In other words, the clear sky index is a value obtained by dividing the solar radiation intensity at the measurement point by the theoretical solar radiation intensity at the top of the atmosphere, and is normalized so that the solar radiation intensity can be handled equivalently without the influence of the position of the measurement point and the measurement time. Value.

  More specifically, the solar radiation intensity acquisition unit 110 first acquires time series data of the solar radiation intensity measured by the solar radiation meter 200 from the solar radiation meter 200. And the solar radiation intensity acquisition part 110 converts each time series data of the acquired solar radiation intensity into a clear sky index, and acquires each time series data of the solar radiation intensity after conversion as solar radiation intensity data. In this way, the solar radiation intensity acquisition unit 110 acquires a plurality of solar radiation intensity data in a plurality of periods.

  The “period” of the plurality of periods may be any period, for example, a period of a plurality of hours, a day, or a period of a plurality of days. It may be one year.

  The solar radiation intensity extraction unit 120 classifies a plurality of solar radiation intensity data in a plurality of periods acquired by the solar radiation intensity acquisition unit 110 into a plurality of groups by the k-means method, and the solar radiation intensity data in two corresponding periods in the same group. To extract.

  Specifically, first, the solar radiation intensity extraction unit 120 includes a plurality of solar radiation intensity data in a plurality of periods acquired by the solar radiation intensity acquisition unit 110, with a plurality of solar radiation intensity data and a variation magnitude of the solar radiation intensity data. Classify into groups. That is, the solar radiation intensity extraction unit 120 sorts a plurality of solar radiation intensity data for each magnitude and variation of the solar radiation intensity data, and sorts the plurality of solar radiation intensity data sorted using the k-means method. Classify into multiple groups.

  Here, the solar radiation intensity extraction unit 120 calculates the solar mean value of the solar radiation intensity data as the magnitude of the solar radiation intensity data, and calculates the integrated value of the power spectral density of the solar radiation intensity data in a predetermined cycle as the magnitude of the fluctuation of the solar radiation intensity data. By calculating as above, a plurality of solar radiation intensity data in a plurality of periods are classified into a plurality of groups. That is, the solar radiation intensity extracting unit 120 sorts a plurality of solar radiation intensity data for each integration value in a predetermined period of the solar mean value and power spectrum density of the solar radiation intensity data, and sorts the plurality of solar radiation intensity data using the k-means method. The solar radiation intensity data is classified into multiple groups.

  In addition, the solar radiation intensity extracting unit 120 re-establishes the plurality of groups by calculating entropy between the two groups and determining the boundary between the two groups in the plurality of groups classified by the k-means method. Classify. And the solar radiation intensity extraction part 120 extracts the solar radiation intensity data in two corresponding periods within the same reclassified group.

  The decomposition component acquisition unit 130 decomposes the solar radiation intensity data acquired by the solar radiation intensity acquisition unit 110 into a trend component represented by a polynomial and a residual component obtained by subtracting the trend component from the solar radiation intensity data. Get components and residual components.

  Specifically, the decomposition component acquisition unit 130 determines the trend component in the two periods from the solar radiation intensity data in the corresponding two periods among the plurality of solar radiation intensity data in the plurality of periods acquired by the solar radiation intensity acquisition unit 110. To get. In addition, the decomposition component acquisition unit 130 acquires residual components in the two periods from the solar radiation intensity data in two corresponding periods among the plurality of solar radiation intensity data in the plurality of periods acquired by the solar radiation intensity acquisition unit 110. To do.

  More specifically, the decomposition component acquisition unit 130 acquires the trend component and the residual component in the two periods from the solar radiation intensity data in the corresponding two periods in the same group extracted by the solar radiation intensity extraction unit 120. To do. That is, the decomposition component acquisition unit 130 determines the trend component in the two periods and the residual component in the two periods from the solar intensity data in the corresponding two periods in the same group extracted by the solar intensity extraction unit 120. To get.

  The performance degradation state estimation unit 140 estimates the degradation state of the measurement performance of the pyranometer 200 from the trend component change and the residual component change acquired by the decomposition component acquisition unit 130. In other words, the performance degradation state estimation unit 140 determines whether or not the pyrometer 200 is based on the trend component change in the corresponding two periods in the same group acquired by the decomposition component acquisition unit 130 and the residual component change in the two periods. Estimate the state of measurement performance degradation.

  Specifically, the performance degradation state estimation unit 140 estimates the degradation state of the sensitivity performance of the pyranometer 200 by comparing the trend components in the two periods acquired by the decomposition component acquisition unit 130. Moreover, the performance degradation state estimation part 140 compares the time constant of the step response obtained from the residual component in the said 2 period which the decomposition | disassembly component acquisition part 130 acquired, and shows the degradation state of the response performance of the pyranometer 200. presume.

  The storage unit 150 is a memory that stores data and the like for estimating a deterioration state of the measurement performance of the pyranometer 200. Specifically, the storage unit 150 acquires, extracts, and estimates data input from the pyranometer 200, the solar radiation intensity acquisition unit 110, the solar radiation intensity extraction unit 120, the decomposition component acquisition unit 130, or the performance degradation state estimation unit 140. Alternatively, the estimation data 151 including the calculated data is stored.

  In addition, although not shown in figure, the pyranometer performance-reduced state estimation apparatus 100 may be provided with input parts, such as a keyboard and a mouse | mouth, and display parts, such as a liquid crystal display.

  Next, the process performed by the pyranometer performance degradation state estimation device 100 will be described.

  FIG. 3 is a flowchart showing an example of a process (a pyranometer performance degradation state estimation method) performed by the pyranometer performance degradation state estimation apparatus 100 according to the embodiment of the present invention.

  As shown in the figure, first, as a solar radiation intensity acquisition step, the solar radiation intensity acquisition unit 110 acquires solar radiation intensity data (S102). The process by which the solar radiation intensity acquisition unit 110 acquires solar radiation intensity data will be described in detail below.

  FIG. 4 is a flowchart illustrating an example of processing in which the solar radiation intensity acquisition unit 110 according to the embodiment of the present invention acquires solar radiation intensity data.

  As shown in the figure, first, the solar radiation intensity acquisition unit 110 acquires time series data of solar radiation intensity measured by the solar radiation meter 200 (S202).

  Specifically, the time series data of the solar radiation intensity measured by the solar radiation meter 200 is stored and accumulated in the estimation data 151 of the storage unit 150, and the solar radiation intensity acquisition unit 110 obtains the necessary data from the estimation data 151. Acquired by reading time series data of solar radiation intensity.

  The solar radiation intensity acquisition unit 110 may acquire the solar radiation intensity time-series data directly from the solar radiation meter 200, or acquire the solar radiation intensity time-series data from an external device or user input. You may decide.

  Then, the solar radiation intensity obtaining unit 110 converts the time series data of the solar radiation intensity into a clear sky index (S204).

  Specifically, the solar radiation intensity acquisition unit 110 converts each time series data of the acquired solar radiation intensity into a clear sky index, and acquires each time series data of the clear sky index after conversion as solar radiation intensity data. Then, the solar radiation intensity acquisition unit 110 writes the acquired solar radiation intensity data in the estimation data 151 stored in the storage unit 150.

  Returning to FIG. 3, next, as a solar radiation intensity extracting step, the solar radiation intensity extracting unit 120 extracts solar radiation intensity data in two corresponding periods (S104).

  Specifically, the solar radiation intensity extracting unit 120 acquires a plurality of solar radiation intensity data in a plurality of periods acquired by the solar radiation intensity acquiring unit 110 by reading from the estimation data 151. And the solar radiation intensity extraction part 120 classify | categorizes the some solar radiation intensity data in the acquired several period into a some group by the k-means method, and extracts the solar radiation intensity data in two corresponding periods in the same group.

  Then, the solar radiation intensity extraction unit 120 writes the extracted solar radiation intensity data in the corresponding two periods into the estimation data 151 stored in the storage unit 150. The detailed description of the process of extracting the solar radiation intensity data by the solar radiation intensity extracting unit 120 will be described later.

  Next, as a decomposition component acquisition step, the decomposition component acquisition unit 130 decomposes the solar radiation intensity data in the two corresponding periods into a trend component and a residual component, so that the trend component and the remaining in the two corresponding periods are separated. The difference component is acquired (S106).

  Specifically, the decomposition component acquisition unit 130 acquires solar radiation intensity data in two corresponding periods within the same group extracted by the solar radiation intensity extraction unit 120 by reading from the estimation data 151. Then, the decomposition component acquisition unit 130 converts the acquired solar radiation intensity data in two corresponding periods in the same group into a trend component indicated by a polynomial and a residual component obtained by subtracting the trend component from the solar radiation intensity data. By decomposing, the trend component and the residual component are obtained.

  Then, the decomposition component acquisition unit 130 writes the acquired trend component and residual component in the corresponding two periods in the same group in the estimation data 151 stored in the storage unit 150. A detailed description of the process in which the decomposition component acquisition unit 130 acquires the trend component and the residual component will be described later.

  Next, as the performance degradation state estimation step, the performance degradation state estimation unit 140 estimates the degradation state of the measurement performance of the pyranometer 200 from the change in the trend component and the change in the residual component in the two corresponding periods ( S108).

  Specifically, the performance degradation state estimation unit 140 acquires the trend component and the residual component in the corresponding two periods in the same group acquired by the decomposition component acquisition unit 130 by reading them from the estimation data 151. . And the performance degradation state estimation part 140 estimates the degradation state of the measurement performance of the pyranometer 200 from the change of the trend component in the acquired said 2 period, and the change of the residual component in the said 2 period.

  Then, the performance degradation state estimation unit 140 writes the estimated degradation state of the measurement performance of the pyranometer 200 in the estimation data 151 stored in the storage unit 150. A detailed description of the process in which the performance degradation state estimation unit 140 estimates the degradation state of the measurement performance of the pyranometer 200 will be described later.

  Thus, the process performed by the pyranometer performance degradation state estimation device 100 (the pyranometer performance degradation state estimation method) ends.

  Next, the process (S104 of FIG. 3) which the solar radiation intensity extraction part 120 extracts solar radiation intensity data is demonstrated in detail.

  FIG. 5 is a flowchart showing an example of a process in which the solar radiation intensity extracting unit 120 according to the embodiment of the present invention extracts solar radiation intensity data.

  As shown in the figure, first, the solar radiation intensity extracting unit 120 classifies a plurality of solar radiation intensity data in a plurality of periods acquired by the solar radiation intensity acquiring unit 110 into a plurality of groups by the k-means method (S302). A process in which the solar radiation intensity extracting unit 120 classifies the solar radiation intensity data into a plurality of groups by the k-means method will be described in detail with reference to FIGS.

  First, a process in which the solar radiation intensity extraction unit 120 sorts the plurality of solar radiation intensity data in the plurality of periods acquired by the solar radiation intensity acquisition unit 110 according to the size of the solar radiation intensity data and the magnitude of variation will be described in detail.

  FIGS. 6 and 7 are diagrams illustrating a process in which the solar radiation intensity extracting unit 120 according to the embodiment of the present invention sorts a plurality of solar radiation intensity data according to the size of the solar radiation intensity data and the magnitude of variation.

  Here, in the present embodiment, the average value of the solar radiation intensity data is used as the size of the solar radiation intensity data, and the integration of the power spectral density of the solar radiation intensity data in a predetermined cycle is used as the magnitude of fluctuation of the solar radiation intensity data. The value is used. The solar radiation intensity data is a value obtained by converting each time series data of solar radiation intensity measured by the solar radiation meter 200 into a clear sky index.

  That is, as shown in FIGS. 6A and 6B, the solar radiation intensity extracting unit 120 acquires, as solar radiation intensity data, a value obtained by the solar radiation intensity acquiring unit 110 converting time series data of solar radiation intensity into a clear sky index. doing.

  And the solar radiation intensity extraction part 120 calculates the daily average value of the acquired solar radiation intensity data. For example, the solar radiation intensity extraction unit 120 calculates the average value of the clear sky index from 8 o'clock to 16 o'clock in FIG. The daily average value of intensity data.

  Further, as shown in FIG. 6C, the solar radiation intensity extraction unit 120 calculates an integral value in a predetermined cycle of the power spectral density (PSD) of the solar radiation intensity data. For example, assuming that the target period is 2 sec to 600 sec, the solar radiation intensity extracting unit 120 calculates an integrated value of the power spectrum density of the clear sky index in the target period of 2 sec to 600 sec, and the integrated value of the power spectral density of the solar radiation intensity data in the predetermined period To do. Note that the integral value of the power spectral density in a predetermined cycle may be simply calculated using a trapezoidal formula.

  Then, as shown in FIG. 6D, the solar radiation intensity extracting unit 120 calculates the daily average value of the calculated solar radiation intensity data (the daily average value of the clear sky index) and the solar radiation for each day for which the solar radiation intensity was measured. The integral value (hereinafter also referred to as the power of the clear sky index) of the power spectrum density of the intensity data in a predetermined cycle is plotted on a graph.

  FIG. 7 shows the power spectrum density of the target period of 2 sec to 600 sec on each day of 2012. The solar radiation intensity extracting unit 120 calculates an integral value (power of a clear sky index) in a predetermined period of the power spectral density of the solar radiation intensity data by calculating the power spectral density in each period as shown in FIG. Can do.

  Next, the solar radiation intensity extracting unit 120 classifies the plurality of sorted solar radiation intensity data into a plurality of groups by using the k-means method.

  FIG. 8 is a diagram illustrating a process in which the solar radiation intensity extracting unit 120 according to the embodiment of the present invention classifies a plurality of solar radiation intensity data into a plurality of groups by the k-means method.

  As shown in the figure, first, the solar radiation intensity extracting unit 120 classifies solar radiation intensity data on a day that has a low daily average value of the clear sky index and that is clearly cloudy into Category 1. And the solar radiation intensity extraction part 120 classifies the solar radiation intensity data of the remaining day into a some group (category) using the k-means method.

  Here, the k-means method (k average method) is the following method. In other words, k initial centers are randomly set from among a plurality of elements, and each element is associated with the center having the closest distance and is classified into k groups. Then, the center (center of gravity) of each linked group is calculated to obtain a new center. Then, the new center is reclassified, and these operations are repeated until convergence (until there is no change in the center). Each group when the center converges is the final classification result.

  In the present embodiment, the solar radiation intensity extracting unit 120 classifies solar radiation intensity data of a day that has not been classified into category 1 into two groups (categories) with k = 2. Specifically, the solar radiation intensity extracting unit 120 classifies a group having a low clear sky index power as category 2, and classifies a group having a high clear sky index power as category 3. In the present embodiment, the value of the power spectral density for each period is considered as an n-dimensional (14353 dimension in this case) value, and the k-means method is applied.

  Returning to FIG. 5, next, the solar radiation intensity extracting unit 120 calculates entropy between two groups in a plurality of groups classified by the k-means method, and determines a boundary between the two groups (S304). ).

  That is, in the graph of FIG. 8 classified by the solar radiation intensity extraction unit 120 by the k-means method, the power of the clear sky index is around 0.006, and category 2 and category 3 are mixedly distributed. For this reason, the solar radiation intensity extraction part 120 determines the power value of the clear sky index used as the boundary of the category 2 and the category 3 by calculating entropy. The process in which this solar radiation intensity extraction part 120 calculates entropy and determines the boundary between two groups is demonstrated in detail using FIG.

  FIG. 9 is a diagram illustrating a process in which the solar radiation intensity extraction unit 120 according to the embodiment of the present invention calculates entropy and determines the boundary between two groups.

  First, the solar radiation intensity extraction unit 120 calculates entropy from the number of plots of category 2 and category 3 by changing the power value of the clear sky index. Hereinafter, a method for calculating entropy will be described.

First, the following four probabilities are defined. The probability that what is classified into category 1 by a certain boundary line is clustered into category A by the k-means method is defined as P _1A . In addition, the probability that what is classified into category 1 by a certain boundary line is clustered into category B by the k-means method is defined as P _1B . In addition, the probability that what is classified into category 2 by a certain boundary line is clustered into category A by the k-means method is defined as _P2A . In addition, the probability that what is classified into category 2 by a certain boundary line is clustered into category B by the k-means method is defined as _P2B .

  Next, the entropy E is defined by the following equation based on these probabilities.

E = -P _1A logP _1A -P _1B logP _1B -P _2A logP _2A -P _2B logP _2B

For example, as shown in (a) of the figure, with respect to the power value of a predetermined clear sky index, among the three plots on the lower side, there are two categories 2, one category 3, and five upper plots. Of these, when there is one category 2 and four categories 3, the solar radiation intensity extracting unit 120 calculates entropy E = 0.494 in the power value of the predetermined clear sky index. In other words, the solar radiation intensity extraction unit 120 sets P _1A = 2/3, P _1B = 1/3, P _2A = 1/5, and P _2B = 4/5, and substitutes these into the above formula to obtain the entropy E = 0.494. The categories 1 and 2 in the above formula correspond to the lower category and the upper category in (a) in the figure, and the categories A and B in the above formula are in (a) in the figure. Corresponds to categories 2 and 3.

  Thus, as shown in (b) of the figure, the solar radiation intensity extracting unit 120 changes the value of the power of the clear sky index by 0.00001, for example, between 0 and 0.022, and each clear sky index. The entropy at the power value of is calculated. Then, the solar radiation intensity extraction unit 120 searches for the value of the power of the clear sky index when the entropy is minimum, and determines the value as the boundary between the category 2 and the category 3.

  In the present embodiment, the solar radiation intensity extracting unit 120 determines that the boundary between the category 2 and the category 3 is 0.0062 because the entropy is minimized when the power of the clear sky index is 0.0062.

  Returning to FIG. 5, next, the solar radiation intensity extracting unit 120 reclassifies the plurality of groups (S306).

  Specifically, as shown in FIG. 10, the solar radiation intensity extracting unit 120 divides the category 2 and the category 3 at the determined boundary (the power of the clear sky index is 0.0062), so that the category 2 and the category 3 Reclassify. FIG. 10 is a diagram illustrating a process in which the solar radiation intensity extracting unit 120 according to the embodiment of the present invention reclassifies a plurality of groups.

  Thus, the category 1 is classified as cloudy (rainy) day, the category 2 is classified as the day when the fluctuation of the solar radiation intensity is small even if there are many clouds, and the fluctuation of the solar radiation intensity is very high in the category 3. Larger days are classified.

  Returning to FIG. 5, next, the solar radiation intensity extraction unit 120 extracts solar radiation intensity data in two corresponding periods within the same reclassified group (S308).

  Specifically, the solar radiation intensity extraction unit 120 extracts, for example, solar radiation intensity data on a similar day (two nearby points) in the category 2 shown in FIG. In other words, the two corresponding periods in this case are two days with similar daily average values and powers of the clear sky index. For example, the two periods are two days of the same weather (for example, clear weather).

  The graph shown in FIG. 10 is plotted on a daily basis for one year, but the plotting period is not limited to one year, and may be for several months or multiple years, for example. Moreover, it is not limited to plotting by a day unit, You may be a unit of several hours or a month unit.

  In addition, the graph for one year shown in FIG. 10 is created for two years, and the solar radiation intensity data of all the days classified into categories 1 to 3 in each graph is averaged, and then the solar radiation of the same category for two years. You may decide to extract intensity data. In other words, the two corresponding periods in this case refer to two categories (groups consisting of a plurality of days) having similar daily average values and powers of the clear sky index.

  Thus, the process of extracting the solar radiation intensity data by the solar radiation intensity extracting unit 120 (S104 in FIG. 3) ends.

  Next, the process (S106 in FIG. 3) in which the decomposition component acquisition unit 130 acquires the trend component and the residual component will be described in detail.

  FIG. 11 is a flowchart illustrating an example of processing in which the decomposition component acquisition unit 130 according to the embodiment of the present invention acquires a trend component and a residual component.

  As shown in the figure, the decomposition component acquisition unit 130 decomposes the solar radiation intensity data in two corresponding periods within the same group extracted by the solar radiation intensity extraction unit 120 into a trend component and a residual component (S402). . Here, the process in which the decomposition component acquisition unit 130 decomposes the solar radiation intensity data into the trend component and the residual component will be described in detail.

  12 and 13 are diagrams for describing processing in which the decomposition component acquisition unit 130 according to the embodiment of the present invention separates the trend component and the residual component.

  As shown in these drawings, the decomposition component acquisition unit 130 decomposes the solar radiation intensity data A into a trend component B and a residual component C in each of the two periods. Note that FIG. 12 shows a diagram in which the solar radiation intensity is decomposed in order to explain the state of decomposition in an easy-to-understand manner. However, in this embodiment, the clear sky index is decomposed in FIG. The figure which decomposes | disassembles is shown.

  Specifically, as shown in FIG. 13, the decomposition component acquisition unit 130 calculates the waveform of the trend component B by applying the waveform of the solar radiation intensity data A to a polynomial model. That is, the decomposition component acquisition unit 130 approximates the graph of the clear sky index (solar intensity data A) to a polynomial (L-order function), and sets the approximated polynomial as the trend component B.

  In addition, the decomposition component acquisition unit 130 calculates a residual component C by subtracting the trend component B from the clear sky index (solar intensity data A).

  Returning to FIG. 11, the decomposition component acquisition unit 130 acquires the trend component of the solar radiation intensity data in each of the two corresponding periods in the same group extracted by the solar radiation intensity extraction unit 120 (S404). That is, the decomposition component acquisition unit 130 acquires the trend component B shown in FIG. 13 in each of the two periods.

  Returning to FIG. 11, the decomposition component acquisition unit 130 acquires the residual component of the solar radiation intensity data in each of the two corresponding periods in the same group extracted by the solar radiation intensity extraction unit 120 (S406). That is, the decomposition component acquisition unit 130 acquires the residual component C shown in FIG. 13 in each of the two periods.

  Thus, the process (S106 in FIG. 3) in which the decomposition component acquisition unit 130 acquires the trend component and the residual component ends.

  Next, the process in which the performance degradation state estimation unit 140 estimates the degradation state of the measurement performance of the pyranometer 200 (S108 in FIG. 3) will be described in detail.

  FIG. 14 is a flowchart showing an example of a process in which the performance degradation state estimation unit 140 according to the embodiment of the present invention estimates the degradation state of the measurement performance of the pyranometer 200.

  As shown in the figure, the performance degradation state estimation unit 140 estimates the degradation state of the sensitivity performance of the pyranometer 200 by comparing the trend components in the two corresponding periods acquired by the decomposition component acquisition unit 130 ( S502). The process in which this performance degradation state estimation part 140 estimates the degradation state of the sensitivity performance of the pyranometer 200 is demonstrated in detail below.

  FIG. 15 is a diagram illustrating processing in which the performance degradation state estimation unit 140 according to the embodiment of the present invention estimates the sensitivity performance degradation state of the pyranometer 200.

  As shown in the figure, it is assumed that the trend component in the two corresponding periods has changed from the trend component B1 to the trend component B2 (or trend component B3). That is, since the trend component is an index for evaluating the magnitude of the output signal with respect to the input signal to the pyranometer 200, the magnitude of the output signal with respect to the input signal has changed due to a decrease in measurement performance such as deterioration or failure. It is shown that.

  In this case, the performance degradation state estimation unit 140 compares the trend component B1 and the trend component B2 (or the trend component B3), which are trend components in the two corresponding periods, to thereby reduce the sensitivity performance degradation state of the pyranometer 200. Is estimated. For example, when the difference between the trend component B1 and the trend component B2 (or the trend component B3) exceeds a predetermined value, the performance deterioration state estimation unit 140 decreases the sensitivity performance of the pyranometer 200 (deterioration or failure). Judge that you are doing.

  Further, the performance degradation state estimation unit 140 compares the time constant of the step response obtained from the residual components in the two corresponding periods acquired by the decomposition component acquisition unit 130, thereby reducing the response performance degradation state of the pyranometer 200. Is estimated (S504). The process in which this performance degradation state estimation part 140 estimates the degradation state of the response performance of the pyranometer 200 is demonstrated in detail below.

  FIG.16 and FIG.17 is a figure explaining the process in which the performance fall state estimation part 140 which concerns on embodiment of this invention estimates the fall state of the response performance of the pyranometer 200. FIG.

First, as shown in FIG. 16A, the performance degradation state estimation unit 140 uses the autoregressive (AR) indicated by the mathematical expression in the figure as the residual component acquired by the decomposition component acquisition unit 130. Applying the model, the autoregressive coefficient a _i is calculated. Incidentally, v _n in the formula indicates the white noise.

Then, as shown in (b) of FIG. 16, reduced performance state estimation unit 140 obtains an impulse response _{g n} from autoregressive coefficients _{a i.} Furthermore, as shown in (c) of FIG. 16, reduced performance state estimating unit 140, by integrating the impulse response g _n, determine the step response.

  Then, it is assumed that the step response obtained in this way changes from the step response C1 to the step response C2 (or step response C3) as shown in FIG. That is, since the residual component is an index for evaluating the delay time of the output signal when the step signal is input to the pyranometer 200, it indicates that the delay time has changed due to deterioration in measurement performance such as deterioration or failure. ing.

  In this case, the performance degradation state estimation unit 140 compares the time constant T between the step response C1 and the step response C2 (or step response C3), which are step responses obtained from the residual components in the two corresponding periods. By this, the deterioration state of the response performance of the pyranometer 200 is estimated. For example, when the difference between the time constant of the step response C1 and the time constant of the step response C2 (or the step response C3) exceeds a predetermined value, the performance deterioration state estimation unit 140 decreases the response performance of the pyranometer 200. Judge that it is (degraded or broken).

  Thus, the process (S108 in FIG. 3) in which the performance degradation state estimation unit 140 estimates the degradation state of the measurement performance of the pyranometer 200 ends.

  As described above, according to the solar radiation performance degradation state estimating device 100 according to the embodiment of the present invention, the solar radiation intensity data obtained from the solar radiation meter 200 is converted into a trend component represented by a polynomial and the trend component from the solar radiation intensity data. And the degradation state of the measurement performance of the pyranometer 200 is estimated from the change in the trend component and the change in the residual component. Here, the inventor of the present application, as a result of diligent research and examination, decomposes the solar radiation intensity data measured by the solar radiation meter 200 into the trend component and the residual component, and evaluates the change of each component, It has been found that it is possible to easily estimate the state of decrease in measurement performance of the pyranometer 200. In other words, the trend component can be generated by applying the solar radiation intensity data to the polynomial model, and the residual component can be generated by subtracting the trend component from the solar radiation intensity data. It can be easily broken down into components. Thereby, according to the pyranometer performance fall state estimation apparatus 100, the fall state of the measurement performance of the pyranometer 200 can be estimated.

  Further, the solar radiation performance degradation state estimation device 100 acquires, as solar radiation intensity data, values obtained by converting each time series data of solar radiation intensity measured by the solar radiation meter 200 into a clear sky index. Here, the solar radiation intensity input from sunlight varies greatly depending on the time (season), time, place (latitude, longitude), and the like. For this reason, the solar radiation performance degradation state estimation apparatus 100 can handle the solar radiation intensity equivalently by converting the solar radiation intensity measured by the solar radiation meter 200 into a clear sky index and normalizing it.

  In addition, the pyranometer performance degradation state estimation device 100 acquires and compares trend components in the two periods from the solar radiation intensity data in the corresponding two periods of the plurality of solar radiation intensity data in the plurality of periods. The deterioration state of the sensitivity performance of the pyranometer 200 is estimated. Here, as a result of intensive studies and examinations, the inventors of the present application have found that it is possible to estimate a state in which the sensitivity performance of the pyranometer 200 is deteriorated from a change in the trend component of the solar radiation intensity data. That is, the trend component is an index for evaluating the magnitude of the output signal with respect to the input signal to the pyranometer 200. Thereby, according to the pyranometer performance degradation state estimation apparatus 100, the degradation state of the sensitivity performance of the pyranometer 200 can be easily estimated by comparing the trend component of the solar radiation intensity data in two corresponding periods. .

  In addition, the pyranometer performance degradation state estimation device 100 acquires residual components in the two periods from the solar radiation intensity data in the two corresponding periods among the plurality of solar radiation intensity data in the plurality of periods, By comparing the time constants of the step response obtained from the difference component, the deterioration state of the response performance of the pyranometer 200 is estimated. Here, as a result of intensive studies and examinations, the inventor of the present application can estimate the deterioration of the response performance of the pyranometer 200 from the change in the time constant of the step response obtained from the residual component of the solar radiation intensity data. I found it. That is, the residual component is an index for evaluating the delay time of the output signal when the step signal is input to the pyranometer 200. Thereby, according to the pyranometer performance degradation state estimation apparatus 100, the response performance of the pyranometer 200 is degraded by comparing the time constants of the step responses obtained from the residual components of the solar radiation intensity data in the two corresponding periods. The state can be estimated easily.

  Moreover, the solar radiation performance degradation state estimation apparatus 100 classifies solar radiation intensity data into a plurality of groups by the k-means method, extracts solar radiation intensity data in two corresponding periods within the same group, and extracts the two periods. From the change in the trend component of the solar radiation intensity data and the change in the residual component, the deterioration state of the measurement performance of the solar radiation meter 200 is estimated. Here, as a result of earnest research and examination, the inventor of the present application uses the k-means method to accurately classify solar radiation intensity data into groups having similar conditions (statistical features) that can be compared. I found that I can do it. For this reason, according to the pyranometer performance degradation state estimation apparatus 100, the change of the trend component and residual component of the solar radiation intensity data in the corresponding two periods within the same group classified by the k-means method is used. It is possible to accurately estimate the degradation state of the measurement performance. By using this method, natural sunlight can be used as input light (test light) without being conscious of fluctuations in sunlight due to clouds, etc., so test light is input to the pyranometer. Field work is not required.

  The pyranometer performance degradation state estimation apparatus 100 reclassifies a plurality of groups by calculating entropy between two groups classified by the k-means method and determining a boundary between the two groups. Thus, the solar radiation intensity data in two corresponding periods in the same group are extracted. Here, the inventor of the present application has made it possible to improve the accuracy of group classification by calculating entropy between two groups and determining the boundary between the two groups as a result of intensive research and examination. I found it. For this reason, according to the pyranometer performance degradation state estimation apparatus 100, the degradation state of the measurement performance of the pyranometer 200 can be accurately estimated by calculating the entropy and reclassifying the group.

  Moreover, the solar radiation performance degradation state estimation apparatus 100 classifies the solar radiation intensity data into a plurality of groups according to the magnitude of the solar radiation intensity data and the magnitude of fluctuation of the solar radiation intensity data. For this reason, since the solar radiation performance degradation state estimation apparatus 100 can easily classify the solar radiation intensity data into a plurality of groups, the degradation state of the measurement performance of the solar radiation meter 200 can be easily estimated.

  Further, the solar radiation performance degradation state estimating device 100 classifies the solar radiation intensity data into a plurality of groups based on the daily average value of the solar radiation intensity data and the integrated value of the power spectrum density of the solar radiation intensity data in a predetermined period. For this reason, since the solar radiation performance degradation state estimation apparatus 100 can accurately classify solar radiation intensity data into a plurality of groups, the degradation state of the measurement performance of the solar radiation meter 200 can be accurately estimated.

  In addition, this invention can not only be implement | achieved as such a pyranometer performance degradation state estimation apparatus 100, but also the pyranometer 200 and the pyranometer performance degradation state estimation apparatus which estimates the degradation state of the measurement performance of the pyranometer 200 It can also be realized as a psoriometer performance degradation state estimation system 10 comprising 100.

  In addition, the present invention can also be realized as a method of estimating a psoriometer performance degradation state that includes a characteristic process performed by a processing unit included in the psoriometer performance degradation state estimation apparatus 100 as a step. Further, it can be realized as a program or an integrated circuit for causing a computer to execute characteristic processing included in the method for estimating the degradation state of the pyranometer. Needless to say, such a program can be distributed via a recording medium such as a CD-ROM and a transmission medium such as the Internet.

  As mentioned above, although the pyranometer performance degradation state estimation apparatus 100 and the pyranometer performance degradation state estimation system 10 which concern on embodiment of this invention were demonstrated, this invention is not limited to this embodiment.

  That is, the embodiment disclosed this time should be considered as illustrative in all points and not restrictive. The scope of the present invention is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims. Moreover, the form built combining the component in embodiment is also contained in the scope of the present invention.

  For example, in the above-described embodiment, the pyranometer performance degradation state estimation device 100 includes the solar radiation intensity acquisition unit 110, the solar radiation intensity extraction unit 120, the decomposition component acquisition unit 130, the performance degradation state estimation unit 140, and the storage unit 150. It was decided to have. However, as shown in FIG. 18, the pyranometer performance degradation state estimation device 101 only needs to include a solar radiation intensity acquisition unit 110, a decomposition component acquisition unit 130, and a performance degradation state estimation unit 140. The unit 120 and the storage unit 150 may be omitted. FIG. 18 is a block diagram showing a minimum configuration of the pyranometer performance degradation state estimating apparatus according to the embodiment of the present invention.

  In this case, the pyranometer performance degradation state estimation device 101 exchanges information with, for example, an external storage unit 150 to estimate the degradation state of the pyranometer 200 measurement performance. Specifically, the solar radiation intensity acquisition unit 110 acquires solar radiation intensity data, and the decomposition component acquisition unit 130 decomposes the solar radiation intensity data into a trend component and a residual component, thereby obtaining a trend component and a residual component. Obtained, and the performance degradation state estimation unit 140 estimates the degradation state of the measurement performance of the pyranometer from the trend component change and the residual component change.

  Moreover, in the said embodiment, the solar radiation intensity acquisition part 110 decided to acquire the value obtained by converting each time series data of the solar radiation intensity which the solar radiation meter 200 measured into the clear sky index as solar radiation intensity data. However, the solar radiation intensity acquisition unit 110 may acquire each time series data of the solar radiation intensity measured by the solar radiation meter 200 as solar radiation intensity data.

  Further, in the process (S308 in FIG. 5) in which the above-described solar radiation intensity extracting unit 120 extracts solar radiation intensity data in two corresponding periods in the same group, the corresponding two periods (similarity) shown in FIG. Any pyranometer information may be used for the classification of (day). That is, as information on the pyranometer used for the classification, it is conceivable to use information on the pyranometer different from the pyranometer to be evaluated in addition to the information on the pyranometer to be evaluated.

  Here, if the above classification is performed by using the information of the pyranometer to be evaluated, a malfunction may occur if the measurement performance of the pyranometer is degraded. It is preferable to use the information of a different pyranometer.

  Specifically, it is preferable to use the information of a pyranometer that is installed in a meteorological office and accurately calibrated as the information of the pyranometer used for the classification. In addition, since there are very few meteorological offices where the pyranometer exists, information of other pyranometers may be used, such as using the average value of the neighboring pyranometers.

  In other words, the solar radiation intensity acquisition unit 110 measures the solar radiation measured by the solar radiation meter to be evaluated and the solar radiation meter that is different from the solar radiation meter to be evaluated (that is, a plurality of solar radiation meters including the solar radiation meter to be evaluated). Solar radiation intensity data indicating intensity time-series data is acquired.

  And the solar radiation intensity extraction part 120 is classified into several groups by the k-means method using the several solar radiation intensity data in the several period acquired from the solar radiation meter different from the solar radiation meter used as evaluation object. Specifically, the solar radiation intensity extracting unit 120 obtains a plurality of solar radiation intensity data for a plurality of periods acquired from a solar radiation gauge different from the solar radiation object to be evaluated. It is classified into a plurality of groups based on the average value) and the magnitude of the fluctuation of the solar radiation intensity data (the integrated value of the power spectral density of the solar radiation intensity data in a predetermined period). In addition, the solar radiation intensity extracting unit 120 re-establishes the plurality of groups by calculating entropy between the two groups and determining the boundary between the two groups in the plurality of groups classified by the k-means method. Classify.

  And the solar radiation intensity extraction part 120 classify | categorizes the several solar radiation intensity data in the several period acquired from the solar radiation meter used as evaluation object into said several group (multiple reclassified group), and is the same Extract solar radiation intensity data for two corresponding periods in the group.

  The decomposition component acquisition unit decomposes the solar radiation intensity data (the solar radiation intensity data acquired from the solar radiation meter to be evaluated) in the two periods into a trend component and a residual component, so that the trend component in the two periods And the residual component.

  For example, in the case of classifying a sunny day, it is considered that there is little possibility that a malfunction will occur even if the information of the pyranometer to be evaluated is used.

  Further, in the present embodiment, the estimation of the measurement performance degradation state is made by comparing the past value of the pyranometer to be evaluated with the current value (or time close to the present). However, it may be possible to estimate the state of deterioration of the measurement performance of the pyranometer to be evaluated by comparing the value of the pyranometer to be evaluated with the values of the surrounding pyranometers.

  In other words, the performance degradation state estimation unit 140 determines whether the trend component and the residual component of the evaluation target pyranometer from the change (difference) from the trend component and the residual component of the surrounding solar radiation meter. Alternatively, it may be estimated that the measurement performance is degraded. In this case, the performance degradation state estimation unit 140 estimates the degradation state of the sensitivity performance of the pyranometer to be evaluated from the change amount (difference amount) of the trend component, and at the time of the step response obtained from the residual component From the change amount (difference amount) of the constant, the state of decline in the response performance of the pyranometer to be evaluated is estimated.

  In the above embodiment, each component may be configured by dedicated hardware or may be realized by executing a software program suitable for each component. Each component may be realized by a program execution unit such as a CPU or a processor reading and executing a software program recorded on a recording medium such as a hard disk or a semiconductor memory.

  INDUSTRIAL APPLICABILITY The present invention can be applied to a pyranometer performance degradation state estimation device that can estimate a degradation state of the measurement performance of a pyranometer.

DESCRIPTION OF SYMBOLS 10 Solarimeter performance degradation state estimation system 100, 101 Solarimeter performance degradation state estimation apparatus 110 Solar radiation intensity acquisition part 120 Solar radiation intensity extraction part 130 Decomposition component acquisition part 140 Performance degradation state estimation part 150 Storage part 151 Estimation data 200, 201, 202, 203 pyranometer

Claims (11)

A psoriometer performance degradation state estimation device that estimates a degradation state of a psoriometer measurement performance,
A solar radiation intensity acquisition unit for acquiring solar radiation intensity data indicating time series data of solar radiation intensity measured by the solar radiation meter;
By decomposing the acquired solar radiation intensity data into a trend component represented by a polynomial and a residual component obtained by subtracting the trend component from the solar radiation intensity data, the trend component and the residual component are A decomposition component acquisition unit to acquire;
A pyranometer performance degradation state estimation device comprising: a performance degradation state estimation unit that estimates a degradation state of the measurement performance of the pyranometer based on the obtained change in trend component and change in the residual component. The solar radiation intensity acquisition unit is a value obtained by converting the ratio of the solar radiation intensity at the measurement point to the theoretical solar radiation intensity at the upper end of the atmosphere as a clear sky index and converting each time series data of the solar radiation intensity measured by the solar radiation meter into the clear sky index. The solar radiation performance degradation state estimation device according to claim 1, wherein the solar radiation performance data is acquired as the solar radiation intensity data. The decomposition component acquisition unit acquires the trend component in the two periods from the solar radiation intensity data in two corresponding periods among the plurality of solar radiation intensity data in the plurality of periods acquired by the solar radiation intensity acquisition unit. And
The said performance degradation state estimation part estimates the degradation state of the sensitivity performance of the said pyranometer by comparing the said trend component in the said 2 period, The solar radiation performance degradation state estimation apparatus of Claim 1 or 2. The decomposition component acquisition unit obtains the residual component in the two periods from the solar radiation intensity data in two corresponding periods among the plurality of solar radiation intensity data in the plurality of periods acquired by the solar radiation intensity acquisition unit. Acquired,
The said performance degradation state estimation part estimates the degradation state of the response performance of the said pyranometer by comparing the time constant of the step response obtained from the said residual component in the said 2 period. The insolation device performance degradation state estimation apparatus according to claim 1. further,
The solar radiation intensity for extracting the solar radiation intensity data in two corresponding periods in the same group by classifying the solar radiation intensity data in the plurality of periods acquired by the solar radiation intensity acquisition unit into a plurality of groups by the k-means method. With an extractor,
The decomposition component acquisition unit acquires the trend component and the residual component in the two periods from the solar radiation intensity data in the two periods,
The said performance degradation state estimation part estimates the degradation state of the measurement performance of the said pyranometer from the change of the said trend component in the said 2 period, and the change of the said residual component in the said 2 period. The pyranometer performance deterioration state estimation apparatus according to any one of 4. The solar radiation intensity extraction unit recalculates the plurality of groups by calculating entropy between the two groups and determining a boundary between the two groups in the plurality of groups classified by the k-means method. The insolation performance degradation state estimation device according to claim 5, wherein the insolation intensity data in two corresponding periods within the same group that has been classified and reclassified are extracted. The said solar radiation intensity extraction part classify | categorizes the several solar radiation intensity data in the said several period into the said some group by the magnitude | size of the solar radiation intensity data and the fluctuation | variation magnitude of solar radiation intensity data. A device for estimating the degradation of the pyranometer performance. The solar radiation intensity extracting unit calculates a daily average value of the solar radiation intensity data as a magnitude of the solar radiation intensity data, and an integral value of a power spectrum density of the solar radiation intensity data in a predetermined cycle is a magnitude of variation of the solar radiation intensity data. The insolation performance degradation state estimation device according to claim 7, wherein the plurality of solar radiation intensity data in the plurality of periods is classified into the plurality of groups by calculating as the length. A pyranometer,
A radiation meter performance degradation state estimation system comprising: the radiation meter performance degradation state estimation device according to any one of claims 1 to 8 that estimates a degradation state of the measurement performance of the radiation meter. A method for estimating a degradation state of a pyranometer, which estimates a degradation state of the measurement performance of the pyranometer,
A solar radiation intensity acquisition step for acquiring solar radiation intensity data indicating time series data of solar radiation intensity measured by the solar radiation meter,
By decomposing the acquired solar radiation intensity data into a trend component represented by a polynomial and a residual component obtained by subtracting the trend component from the solar radiation intensity data, the trend component and the residual component are A decomposition component acquisition step to be acquired;
A performance degradation state estimation method comprising: a performance degradation state estimation step that estimates a degradation state of the measurement performance of the pyranometer from the obtained change of the trend component and the change of the residual component.   A program for causing a computer to execute the steps included in the method for estimating a degradation state of a pyranometer according to claim 10.

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