JP7357586B2 - Solar power generation prediction device - Google Patents

Description

The present application relates to a solar power generation amount prediction device.

When snow accumulates on solar power generation panels, the amount of power generated decreases to nearly zero, resulting in excessive prediction errors in normal power generation forecasts. In order to avoid this, there are known techniques for predicting and calculating the amount of electricity during snowfall using forecast information regarding the weather, etc. (see Patent Document 1), and for correcting the amount of electricity based on information on the average number of days of snowfall. (See Patent Document 2).

Unexamined Japanese Patent Publication No. 2017-163632 Japanese Patent Application Publication No. 11-65686

When large-scale snowfall occurs and snow accumulates on solar panels for several days or more, it is difficult to accurately predict the amount of solar power generated during snowfall by simply using snowfall forecast information. There was a problem with it being bad.

This application was made in order to solve the above-mentioned problem, and even when large-scale snowfall occurs and the snow accumulates on the solar power generation panels for several days or more, it is possible to accurately calculate power generation prediction. The purpose is to provide a solar power generation amount prediction device that can predict the amount of solar power generated.

The solar power generation amount prediction device disclosed in the present application includes a data receiving unit that receives the actual power generation amount measured value, snowfall amount forecast value, and solar radiation amount forecast value of the solar power generation panel, and a data receiving unit that receives the solar radiation amount forecast value from the solar power generation panel. A solar radiation conversion unit that converts the predicted power generation amount to the corresponding predicted power generation amount, and a snow cover that estimates the snow depth from now on based on the current snow depth calculated by comparing the predicted power generation amount and the actual power generation amount measurement value, and the snowfall forecast value. The power generation amount prediction correction section corrects the predicted power generation amount based on the snow depth estimated by the estimation section and the snow accumulation estimation section.

According to the solar power generation amount prediction device disclosed in the present application, even when snow falls on the solar power generation panels for several days or more, it is possible to accurately predict the amount of power generation.

1 is a configuration diagram of a solar power generation amount prediction device according to Embodiment 1. FIG. 3 is a flowchart illustrating the operation of the solar power generation amount prediction device according to the first embodiment. 2 is a flowchart illustrating an algorithm for estimating snow depth by the solar power generation amount prediction device according to the first embodiment. 1 is a hardware configuration diagram of a solar power generation amount prediction device according to Embodiment 1. FIG.

Hereinafter, preferred embodiments of the solar power generation amount prediction device according to the present application will be described with reference to the drawings. Note that the same content and corresponding parts are designated by the same reference numerals, and detailed explanation thereof will be omitted. Similarly, in the embodiments that follow, redundant explanations will be omitted for the components denoted by the same reference numerals.

Embodiment 1.
FIG. 1 is a schematic configuration diagram of a solar power generation amount prediction device 100 according to the first embodiment. The solar power generation amount prediction device 100 includes a data receiving section 101 , a solar radiation amount conversion section 102 , a power generation amount equipment database 103 , a snow accumulation estimation section 104 , a power generation amount prediction correction section 105 , a prediction result accumulation section 106 , and a display section 107 .

The data receiving unit 101 inputs the measured value of the power generation amount of the solar power generation panel 10, the predicted value of snowfall amount, and the predicted value of solar radiation amount.

The measured value of the power generation amount of the solar power generation panel 10 is measured in the solar power generation system 1. As shown in FIG. 1, the solar power generation system 1 is roughly composed of a solar power generation panel 10, a measuring device 11, and a power conditioner 12. Measure. The actual power generation amount measurement value may be transmitted to the solar power generation amount prediction device 100 in real time, or may be stored by dividing it by time, date, etc., and transmitted at regular intervals.

For the snowfall forecast value and solar radiation forecast value, forecast values provided by a weather company via the network 2 or the like are input.

The actual power generation amount measurement value, snowfall amount forecast value, and solar radiation amount forecast value input into the data receiving unit 101 are used in the solar power generation amount prediction device 100 as follows according to the flowchart shown in FIG. .
(1) The solar radiation forecast value is converted into a predicted power generation amount in the solar radiation conversion unit 102 (step S1). At this time, a power generation equipment database 103 that stores equipment information of the solar power generation system 1 for converting solar radiation into power generation output is used.
(2) Compare the converted predicted power generation amount with the current actual power generation amount measurement value, and if the predicted power generation amount has not been reached even after considering the error (step S2), snow has fallen on the solar power generation panel 10. The snow estimation unit 104 estimates the current depth of snow on the solar power generation panel 10 according to the difference between the measured power generation amount and the predicted power generation amount (step S3).
(3) If the actual power generation amount measured value is equal to but greater than the predicted power generation amount taking into account the error, it is determined that there is no snowfall (step S4).
(4) Based on the snow depth estimated by the snow accumulation estimation unit 104 and the snowfall forecast value, the snow accumulation depth from now onwards is further estimated, and the predicted power generation amount converted by the solar radiation conversion unit 102 is estimated. The amount of power generated in the future is predicted by making corrections based on the depth of future snowfall (step S5).
(5) The prediction result is stored in the prediction result storage unit 106 (step S6). The stored prediction results may be displayed on the display unit, if necessary. Furthermore, this prediction result may be used as a trigger for performing another operation, such as calculating the start time of snow melting.

An algorithm by which the snowfall estimation unit 104 estimates the future depth of snowfall on the solar power generation panel 10 from the snowfall forecast value and the actual power generation amount measurement value will be described with reference to the flowchart shown in FIG. 3.
(1) If the current measured power generation amount is not zero (step S7), the current depth of snow on the solar power generation panel 10 is estimated in step S3 (step S8)
(2) If the current actual power generation amount measurement value is zero, if the actual power generation amount measurement value one day ago is not zero (step S9), the estimated value will be estimated before the actual power generation amount measurement value becomes zero in step S3. In addition to the estimated snow depth, the current snow depth on the solar power generation panel 10 is estimated (step S8), and in step S5, the snow depth is estimated from the snowfall amount converted from the future snowfall forecast value. Add (step S10).
(3) If the current power generation performance measurement value is zero and the power generation performance measurement value one day ago is zero, a preset amount of remaining snow (remaining snow amount setting value) is added (step S11), Furthermore, the depth of snowfall is added from the snowfall amount converted from the future snowfall forecast value (step S10).
(4) The power generation amount actual measured value in this embodiment refers to the power generation amount actual measurement value for two days, the current day and one day before, but the power generation amount actual measurement value for two or more days when the snow continues for several days. In the case where is zero, a plurality of remaining snow amount setting values may be set according to the number of days in which the actual power generation amount measurement value is zero.

An example of the hardware of the solar power generation amount prediction device 100 is shown in FIG. It is composed of a processor 50 and a storage device 60, and although not shown, the storage device 60 includes a volatile storage device such as a random access memory and a nonvolatile auxiliary storage device such as a flash memory. Further, an auxiliary storage device such as a hard disk may be provided instead of the flash memory. The processor 50 executes, for example, the flowchart of FIG. 2 or 3 by executing the program input from the storage device 60. In this case, the program is input to the processor 50 from the auxiliary storage device via the volatile storage device. Further, the processor 50 may output data such as calculation results to a volatile storage device of the storage device 60, or may store data in an auxiliary storage device via the volatile storage device. For example, the prediction result storage unit 106 may be part of the storage device 60.

As described above, the solar power generation amount prediction device of the present embodiment allows accurate power generation prediction calculations even when snow falls on the solar power generation panels for several days or more.

Although this application describes exemplary embodiments, the various features, aspects, and functions described in the embodiments are not limited to the application of particular embodiments, and may be used alone or It is applicable to the embodiments in various combinations.
Accordingly, countless variations not illustrated are envisioned within the scope of the technology disclosed herein. For example, this includes cases in which at least one component is modified, added, or omitted.

1: Solar power generation system, 2: Network, 10: Solar power generation panel, 11: Measuring instrument, 12: Power conditioner, 50: Processor, 60: Storage device, 100: Solar power generation amount prediction device, 101: Data Receiving unit, 102: Solar radiation conversion unit, 103: Power generation equipment database, 104: Snow accumulation estimation unit, 105: Power generation prediction correction unit, 106: Prediction result accumulation unit, 107: Display unit

Claims (2)

a data receiving unit that receives the measured value of the actual power generation amount, the snowfall amount forecast value, and the solar radiation amount forecast value of the solar power generation panel, and the solar radiation amount conversion that converts the solar radiation amount forecast value into the predicted power generation amount according to the said solar power generation panel. a snow depth estimating section that estimates a current snow depth calculated by comparing the predicted power generation amount and the power generation amount actual measurement value and a snow depth after the present time from the snowfall amount forecast value; A solar power generation amount prediction device including a power generation amount prediction correction section that corrects the predicted amount of power generation based on the estimated snow depth. 1 . The snow depth estimating unit estimates the snow depth by adding a preset amount of remaining snow when the measured power generation amount is zero for two or more consecutive days. The solar power generation amount prediction device described in .

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