JP2016200454A - Meteorological data estimation method and power generation amount estimation method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a meteorological data estimation method that can estimate meteorological data while restraining the amount of necessary information, and a power generation amount estimation method that estimates the amount of power generation of an electric power plant using natural energy by using the estimated meteorological data.SOLUTION: A data computation system 1 performs meteorological data estimation computation processing, and thereby estimates meteorological data (temperature from sunrise time to sunset time) at an estimation object spot on the basis of past meteorological data (highest temperature TH, lowest temperature TL, sunrise time Tsr, and sunset time Tss of a day). The meteorological data estimation computation processing executes a series of processes (S110 to S180) and can estimate "temperature from sunrise time to sunset time" (temperature change waveform) as shown in Figure 3.SELECTED DRAWING: Figure 3

Description

  The present invention relates to a meteorological data estimation method for estimating meteorological data at an estimation target point, and a power generation amount estimation method for estimating a power generation amount of a power plant using natural energy.

As means for detecting actual weather data, an air temperature sensor or the like for detecting air temperature is used.
However, if an abnormality occurs in the temperature sensor, it becomes impossible to detect actual weather data. On the other hand, a meteorological data estimation method for estimating meteorological data (temperature) using a predetermined arithmetic expression when an abnormality occurs in the temperature sensor has been proposed (Patent Document 1).

  In this meteorological data estimation method, for example, when estimating the temperature, the maximum daily maximum temperature, the minimum daily maximum temperature, the number of days in the monitoring day, the slope of change, the number of years in which the daily maximum temperature is the maximum, the maximum The minimum temperature difference, the constant of the change gradient, and the constant of the maximum temperature time are used as input values for the arithmetic expression.

  Also, a weather data estimation method (outside air temperature prediction method) for predicting the outside air temperature using the outside air temperature data for 24 hours measured by the temperature sensor and the past outside air temperature data over a long period (for example, 30 months). Has been proposed (Patent Document 2).

  Furthermore, a meteorological data estimation method (temperature prediction method) has been proposed that predicts the temperature at each time of the next day or the current day using data on the maximum temperature and the minimum temperature of each day in the past (patent document). 3).

JP 09-264966 A JP 04-348296 A Japanese Patent Laid-Open No. 08-320383

However, in the above meteorological data estimation method, there is a problem that a lot of information necessary for the work of estimating the weather data becomes complicated, and the work of preparing such a lot of information becomes complicated.
For example, when there are many constants used in the arithmetic expression, the constant setting operation becomes complicated. In addition, when using past outside air temperature data over a long period (for example, 30 months) and data on the maximum temperature and the minimum temperature on each day in the past, it is complicated to collect the data. Become.

On the other hand, the meteorological data can be used in a power generation amount estimation method for estimating the power generation amount of a power plant using natural energy.
Therefore, the present invention provides a meteorological data estimation method capable of estimating meteorological data while suppressing the amount of necessary information, and uses the estimated meteorological data to generate power generated by a power plant using natural energy. An object of the present invention is to provide a power generation amount estimation method for estimating the power generation amount.

  The meteorological data estimation method according to the first aspect of the present invention is a method of estimating meteorological data at an estimation target point based on past meteorological data, and the estimated meteorological data is from sunrise time to sunset time. The past weather data includes at least a maximum temperature, a minimum temperature, a sunrise time, and a sunset time of the day.

In the first step of the meteorological data estimation method, the minimum temperature is set as the estimated temperature at the sunrise time on the temperature coordinate plane with the horizontal axis representing time and the vertical axis representing temperature.
In the second step, the sunrise time and sunset time are used to calculate the south / intermediate time, and in the temperature coordinate plane, the highest temperature is estimated as the highest temperature at which a predetermined delay time has elapsed from the south / intermediate time. Set as estimated temperature at time. The south-central time is obtained by calculating the middle time (central time) between the sunrise time and the sunset time.

  In the third step, on the temperature coordinate plane, a waveform obtained by connecting the estimated temperature at the sunrise time and the estimated temperature at the maximum temperature estimated time with a predetermined curve or straight line is defined as a temperature waveform from the sunrise time to the maximum temperature estimated time. Set.

  In the fourth step, using the temperature change information determined based on the past meteorological data at the point related to the estimation target point among the past meteorological data, the amount of temperature decrease from the maximum temperature estimated time to the sunset time is calculated. Calculate. The temperature change information includes temperature change information in which the correlation between the daytime from sunrise time to sunset time and the temperature change amount is defined, or the elapsed time from the highest temperature observation time and the temperature change amount. The temperature change information for which the correlation is determined is used.

  In addition, as "a point related to the estimation target point", for example, a point closest to the estimation target point or a point whose temperature change is similar to the estimation target point among the points where the past weather data exists And a plurality of points whose distance from the estimation target point is within a predetermined range. Among these, when using “a plurality of points whose distance from the estimation target point is within a predetermined range” as “the point related to the estimation target point”, the average value of past weather data at each point is It may be used as “past weather data at a point related to the target point”. In addition, when there is past weather data at the estimation target point, the estimation target point may be handled as “a point related to the estimation target point” and the temperature change amount information may be determined.

In the fifth step, the temperature obtained by subtracting the amount of decrease in temperature from the maximum temperature is set as the estimated temperature at sunset time on the temperature coordinate plane.
In the sixth step, on the temperature coordinate plane, a waveform obtained by connecting the estimated temperature at the highest temperature estimated time and the estimated temperature at the sunset time with a predetermined curve or straight line is represented as the temperature from the highest temperature estimated time to the sunset time. Set as waveform.

  According to this weather data estimation method, the sunrise time is based on past weather data (specifically, past weather data including at least the highest temperature, the lowest temperature, the sunrise time, and the sunset time of the day). Temperature from sunset to sunset time can be estimated.

In particular, since the past meteorological data necessary for estimating the temperature is four (maximum temperature, minimum temperature, sunrise time, sunset time of the day), the necessary amount of information can be suppressed.
Therefore, according to the present invention, the weather data can be estimated while suppressing the amount of information necessary for estimating the weather data of the estimation target point.

  Next, in the above meteorological data estimation method, the temperature change amount information includes the daytime time and the decrease on the temperature decrease rate coordinate plane in which the horizontal axis is the daytime time and the vertical axis is the decrease rate from the maximum temperature. You may comprise by the waveform data which shows the correlation with a rate, and the variation | change_quantity calculation formula which calculates the said temperature variation | change_quantity using the said fall rate. Alternatively, the temperature change amount information is a waveform indicating the correlation between the elapsed time from the highest temperature observation time and the temperature change amount on the temperature change amount coordinate plane with the horizontal axis as the elapsed time and the vertical axis as the temperature change amount. It may consist of data.

  That is, as the temperature change amount information, the waveform data drawn on the temperature decrease rate coordinate plane and the change amount calculation formula are used, or the waveform data drawn on the temperature change amount coordinate plane is used, and the weather data of the estimation target point is used. May be estimated.

  Next, in the above meteorological data estimation method, in the third step, the estimated temperature at the sunrise time and the estimated temperature at the maximum temperature estimated time are connected by a curve corresponding to a part of the sine wave waveform on the temperature coordinate plane. The waveform may be set as a temperature waveform from the sunrise time to the maximum temperature estimation time. Further, in the sixth step, on the temperature coordinate plane, a waveform obtained by connecting the estimated temperature at the highest temperature estimated time and the estimated temperature at the sunset time with a curve corresponding to a part of the sine wave waveform is obtained from the highest temperature estimated time. It may be set as a temperature waveform up to sunset time.

  That is, the temperature waveform from the sunrise time to the maximum temperature estimation time and the temperature waveform from the maximum temperature estimation time to the sunset time may be realized using, for example, a curve corresponding to a part of the sine wave waveform.

  Next, in the meteorological data estimation method described above, in the third step, the estimated temperature at the sunrise time and the estimated temperature at the maximum temperature estimation time are calculated from the minimum value to the maximum value in the sine wave waveform on the temperature coordinate plane. A waveform connected by a curve corresponding to a half cycle may be set as a temperature waveform from the sunrise time to the maximum temperature estimation time. In the sixth step, on the temperature coordinate plane, the estimated temperature at the highest estimated temperature time and the estimated temperature at the sunset time are connected by a curve corresponding to the lapse of a quarter cycle from the maximum value of the sine wave waveform. The waveform may be set as a temperature waveform from the maximum temperature estimation time to the sunset time.

  In other words, as a curve corresponding to a part of the sine wave waveform, using a curve corresponding to a half cycle from the minimum value to the maximum value and a curve corresponding to a period from the maximum value to a quarter cycle, You may estimate the temperature waveform to the highest temperature estimation time, and the temperature waveform from the highest temperature estimation time to the sunset time.

  A power generation amount estimation method according to another aspect of the present invention is a power generation amount estimation method of a power plant using natural energy, wherein the power plant is a solar power plant, and the power plant is based on weather data at the power plant. A power generation amount calculating step for calculating the estimated power generation amount. In this power generation amount estimation method, the estimated power generation amount is calculated using the weather data estimated by the above-described weather data estimation method.

  According to this power generation amount estimation method, the meteorological data estimated while suppressing the required amount of information is used, and the amount of information necessary for estimating the power generation amount of the power plant using natural energy can be suppressed. .

  Further, according to this power generation amount estimation method, weather data estimated based on past weather data is used in estimating the power generation amount of a power plant using natural energy. Since this estimated weather data is calculated based on past weather data, it becomes highly reliable estimated data reflecting the trend of past weather data.

  By calculating the estimated power generation amount based on such estimated weather data, it is possible to obtain a highly reliable estimated power generation amount while suppressing the required information amount.

According to the meteorological data estimation method of the present invention, it is possible to estimate meteorological data while suppressing the amount of information required when estimating meteorological data at a point to be estimated.
In addition, according to the power generation amount estimation method of the present invention, by calculating the estimated power generation amount based on the estimated weather data obtained by the weather data estimation method described above, it is possible to reduce the amount of information that is required and A high estimated power generation amount can be obtained.

1 is an explanatory diagram showing a schematic configuration of a data operation system 1. FIG. It is a flowchart showing the processing content of the weather data estimation calculation processing. It is explanatory drawing showing "the temperature from the sunrise time to the sunset time" in the temperature coordinate plane which makes time on a horizontal axis and temperature on a vertical axis. It is explanatory drawing of the waveform data showing the delay time Td of each month in each measurement point (points ag). It is explanatory drawing of the waveform data showing the correlation of daytime time in each measurement point (points ag) and the fall rate Rd from the highest temperature. The flowchart showing the processing content of the electric power generation amount estimation calculation process is shown. It is explanatory drawing of the waveform data as the curve CL showing the correlation with daytime time and the fall rate Rd from highest temperature.

Embodiments to which the present invention is applied will be described below with reference to the drawings.
In addition, this invention is not limited to the following embodiment at all, and it cannot be overemphasized that various forms may be taken as long as it belongs to the technical scope of this invention.

[1. First Embodiment]
[1-1. overall structure]
FIG. 1 is an explanatory diagram showing a schematic configuration of a data operation system 1 according to the first embodiment.

  The data calculation system 1 is configured to be able to execute various calculation processes including a weather data estimation calculation process and a power generation amount estimation calculation process. The data calculation system 1 includes a calculation device 11, an input device 31, an output device 33, and a storage device 35.

  The calculation device 11 includes a calculation unit 13, a storage unit 15, a memory 17, a communication unit 19, and an interface unit 21. The arithmetic device 11 can be configured using a computer, for example.

  The calculation unit 13 executes calculation processing using various data based on a predetermined program. The storage unit 15 stores initial data used for various types of arithmetic processing, a program indicating the content of arithmetic processing, and the like. The memory 17 temporarily stores programs and data executed by the calculation unit 13. The communication unit 19 transmits and receives various data and command signals to and from an external device (not shown) connected to the arithmetic device 11. The interface unit 21 performs data input / output with the input device 31, the output device 33, and the storage device 35.

And the calculating part 13 reads initial data, a program, etc. from the memory | storage part 15, and performs various arithmetic processing including a weather data estimation calculation process and a power generation amount estimation calculation process.
The input device 31 includes a keyboard, a mouse (pointing device), and the like, and is used by an operator to input commands and the like to the data calculation system 1.

The output device 33 includes a display, a printer, and the like, and is used for outputting (displaying, printing, etc.) a calculation result by the calculation device 11.
The storage device 35 includes a hard disk drive (HDD), a flexible disk drive, a CD drive, a DVD drive, a Blu-ray disk drive, and the like, and is used as an external storage device that stores data and programs stored in the storage unit 15. It is done. Note that the storage device 35 can also be used as an alternative means of the storage unit 15.

[1-2. Weather data estimation calculation processing]
The data calculation system 1 is configured to perform weather data estimation calculation processing as one of various calculation processing.

The meteorological data estimation calculation process is a calculation process for estimating meteorological data at an estimation target point based on past meteorological data at a point related to the estimation target point.
Specifically, it is a calculation process for estimating “temperature from sunrise time to sunset time” in the weather data. This weather data estimation calculation process uses the temperature change information determined based on the past meteorological data at the point related to the estimated target point out of the past meteorological data, and uses the “sunrise time to sunset time” of the estimated target point. Estimate the temperature until.

  In addition, as "a point related to the estimation target point", for example, a point closest to the estimation target point or a point whose temperature change is similar to the estimation target point among the points where the past weather data exists And a plurality of points whose distance from the estimation target point is within a predetermined range. Further, when past weather data exists at the estimation target point, the estimation target point may be handled as “a point related to the estimation target point” and the temperature change amount information may be determined. In the present embodiment, as a “point related to the estimation target point”, a point closest to the estimation target point among the points where past weather data exists is set.

  In the data calculation system 1, the meteorological data estimation calculation process is executed by the calculation device 11 (specifically, the calculation unit 13) to estimate “temperature from sunrise time to sunset time” at the estimation target point. To do.

  When the execution instruction of the weather data estimation calculation process is input from the user via the input device 31, the calculation unit 13 reads a program related to the weather data estimation calculation process from the storage unit 15, and the weather data estimation calculation process To start.

FIG. 2 is a flowchart showing the contents of the weather data estimation calculation process.
When the meteorological data estimation calculation process is started, first, in S110 (S represents a step), initial setting is performed. Specifically, the estimation target point and the estimation target date are set based on the execution command from the user.

  Note that the execution command input from the user via the input device 31 includes the command content indicating “what temperature and what day“ temperature from sunrise time to sunset time ”is calculated at which point”. It is.

  In the next S120, the process reads the past weather data on the estimation target date from the storage unit 15 or the storage device 35 among the past weather data at the point related to the estimation target point designated by the user.

  In this embodiment, the maximum temperature TH, the minimum temperature TL, the sunrise time Tsr, and the sunset time Tss of the day are read from the storage unit 15 or the storage device 35 as past weather data. At least one of the storage unit 15 and the storage device 35 stores past weather data at a plurality of points. In this step, information on the latitude and longitude of each point is used to extract the point closest to the estimation target point from the points where past weather data exists, Set as “Point to do”.

  In the next S130, the lowest temperature TL read in S120 is set as the estimated temperature at the sunrise time Tsr read in S120 on the temperature coordinate plane with the horizontal axis as time and the vertical axis as temperature.

  Here, FIG. 3 is an explanatory diagram showing “temperature from sunrise time to sunset time” on the temperature coordinate plane with time on the horizontal axis and temperature on the vertical axis. In S130, processing for setting a point indicated by an arrow A on the temperature coordinate plane of FIG. 3 is performed.

  In the next step S140, the south / intermediate time Tc is calculated using the sunrise time Tsr and the sunset time Tss, and the highest temperature TH on the temperature coordinate plane is set to the highest delay time Td from the south / intermediate time Tc. Set as the estimated temperature at the estimated temperature time Tce. In S140, processing for setting a point indicated by an arrow B on the temperature coordinate plane of FIG. 3 is performed. The south-central time Tc is obtained by calculating the middle time (central time) between the sunrise time Tsr and the sunset time Tss.

  Here, FIG. 4 is explanatory drawing of the waveform data showing the delay time Td of each month in each measurement point (points ag). In S140, the delay time of the month to which the estimation target date belongs at the point related to the estimation target point is read from the waveform data, and the maximum temperature estimation time Tce is set using the read delay time Td.

  FIG. 4 also shows waveform data as an average value of the delay time Td of each month at each measurement point (points a to g). The processing content in S140 is not limited to the method using different waveform data depending on the estimation target point, but the waveform data determined regardless of the estimation target point (in other words, the delay time Td as an average value). A method of setting the maximum temperature estimation time Tce using the waveform data shown in FIG.

  In the next step S150, on the temperature coordinate plane, a waveform obtained by connecting the estimated temperature at the sunrise time Tsr and the estimated temperature at the maximum temperature estimated time Tce with a predetermined curve or straight line from the sunrise time Tsr to the maximum temperature estimated time Tce. Set as the temperature waveform.

  In the present embodiment, a curve corresponding to a part of the sine wave waveform is set as the temperature waveform from the sunrise time Tsr to the maximum temperature estimation time Tce. More specifically, a curve corresponding to a half cycle from the minimum value to the maximum value of the sine wave waveform is used. In S150, a process for setting a curve indicated by an arrow C is performed on the temperature coordinate plane of FIG.

  In next S160, the temperature decrease amount TR from the maximum temperature estimation time Tce to the sunset time Tss is calculated using the temperature change amount information determined based on the past weather data at the point related to the estimation target point.

  In the present embodiment, as the temperature change amount information, the temperature decrease amount TR is calculated by using the waveform data indicating the correlation between the daytime time from the sunrise time to the sunset time and the decrease rate Rd from the maximum temperature, and the decrease rate Rd. Temperature change amount information including a change amount calculation formula to be calculated is used.

  Here, FIG. 5 is explanatory drawing of the waveform data showing the correlation between the daytime time at each measurement point (points a to g) and the rate of decrease Rd from the maximum temperature. In FIG. 5, waveform data representing the correlation between daytime time and the rate of decrease Rd from the maximum temperature on the temperature change coordinate plane with the horizontal axis as the daytime and the vertical axis as the rate of decrease Rd from the maximum temperature. (Decrease rate information representing the correlation between the daytime time and the rate of decrease Rd from the maximum temperature).

  In addition, Equation (1) shown in [Equation 1] is an arithmetic expression for calculating the temperature decrease amount TR using the decrease rate Rd.

  That is, in S160, the temperature decrease amount TR is calculated by substituting the decrease rate Rd obtained by calculation using the waveform data shown in FIG. In S160, a process of calculating a numerical value (temperature decrease amount TR) indicated by an arrow D on the temperature coordinate plane of FIG. 3 is performed.

  At this time, the waveform data and [Equation 1] shown in FIG. 5 correspond to an example of the temperature change amount information in which the correlation between the daytime from the sunrise time Tsr to the sunset time Tss and the temperature change amount TR is determined. .

  FIG. 5 also shows waveform data as an approximate line (a straight line corresponding to a linear function) of the correlation between the daytime time at each measurement point (points a to g) and the rate of decrease Rd from the maximum temperature. The processing content in S160 is not limited to the method using different waveform data depending on the estimation target point, but is waveform data determined regardless of the estimation target point (waveform data indicating the decrease rate Rd as an approximate line). A method of calculating the temperature decrease amount TR using the decrease rate Rd obtained based on the above may be adopted.

  Further, as the temperature change amount information, temperature change amount information in which a correlation between the elapsed time from the maximum temperature observation time and the temperature change amount is defined may be used. When such temperature change information is used, the temperature change TR can be obtained based on the elapsed time from the maximum temperature estimation time Tce to the sunset time Tss. Specific examples of temperature change information include, for example, waveform data (not shown) drawn on a coordinate plane with the horizontal axis as the elapsed time from the maximum temperature observation time and the vertical axis as the temperature change amount, and the maximum temperature observation For example, a calculation formula for calculating a temperature change amount by using an elapsed time from the time as an input value.

  In next S170, a numerical value (temperature) obtained by subtracting the temperature decrease amount TR from the maximum temperature TH on the temperature coordinate plane is set as the estimated temperature TE (= TH-TR) at the sunset time Tss. In S170, the process which sets the point shown by the arrow E in the temperature coordinate plane of FIG. 3 is performed.

  In the next step S180, on the temperature coordinate plane, a waveform obtained by connecting the estimated temperature at the highest temperature estimated time Tce and the estimated temperature at the sunset time Tss with a predetermined curve or straight line from the highest temperature estimated time Tce to the sunset time. Set as temperature waveform up to Tss.

  In the present embodiment, a curve corresponding to a part of the sine wave waveform is set as the temperature waveform from the maximum temperature estimation time Tce to the sunset time Tss. More specifically, a curve corresponding to the period from the maximum value to the lapse of a quarter period is used in the sine wave waveform. In S180, processing for setting a curve indicated by an arrow F on the temperature coordinate plane in FIG. 3 is performed.

As a result, an estimation result of “temperature from sunrise time Tsr to sunset time Tss” as shown in FIG. 3 can be obtained.
In the next S190, the calculation result (“estimation result of“ temperature from sunrise time Tsr to sunset time Tss ”)” is stored in at least one of the storage unit 15 and the storage device 35 and output (displayed) to the output device 33. Or print).

When S190 ends, the weather data estimation calculation process ends.
By executing the weather data estimation calculation process in this way, it is possible to estimate “the temperature from the sunrise time Tsr to the sunset time Tss”.

[1-3. Power generation amount estimation calculation process]
The data calculation system 1 is configured to execute a power generation amount calculation calculation process as one of various calculation processes.

The power generation amount estimation calculation process uses the “temperature from the sunrise time Tsr to the sunset time Tss” obtained in the weather data estimation calculation process to generate the power generation amount E (n) [ kWh · hour ⁻¹ ] is estimated. The power generation amount E (n) represents the power generation amount in one hour from n hour to (n + 1) hour.

In the data calculation system 1, the power generation amount estimation calculation process is executed by the calculation device 11 (specifically, the calculation unit 13), so that the estimated power generation amount of the solar power plant can be obtained.
When an execution command of the power generation amount estimation calculation process is input from the user via the input device 31, the calculation unit 13 reads a program related to the power generation amount estimation calculation process from the storage unit 15 and generates the power generation amount estimation calculation process. To start.

FIG. 6 is a flowchart showing the processing contents of the power generation amount estimation calculation process.
When the power generation amount estimation calculation process is started, first, initial setting is performed in S210. Specifically, based on the execution command from the user, the power generation amount per hour starting from what time ((power generation amount E (n) in one hour from n hour to (n + 1) hour) is calculated. Set whether or not.

  Note that the execution command input from the user via the input device 31 includes a command content indicating “how much power is generated per hour starting from what month / day / month at which point”. It is.

  In the next S220, the calculation result in the weather data estimation calculation process (estimation result of “temperature from sunrise time to sunset time” on the date determined based on the execution command from the user) from the storage unit 15 or the storage device 35. ) Is read.

  In addition, when the estimation result of “the temperature from the sunrise time to the sunset time” on the corresponding date is not stored in the storage unit 15 or the storage device 35, the meteorological data estimation calculation process is executed to cope with it. An estimation result of “temperature from sunrise time to sunset time” on the date is calculated, and the calculation result is read.

In the next S230, the power generation amount E (n) is calculated using the temperature T (n) at n o'clock among the estimation results of “temperature from sunrise time to sunset time” read in S220.
In S230, first, the estimation coefficient K is calculated using Equation (2) shown in [Equation 2].

K ′ is a basic design coefficient, α _Pmax is a maximum output temperature coefficient, T (n) is an air temperature at n hours (target time air temperature), and ΔT is a weighted average solar module temperature increase value. is there. The basic design coefficient K ′ is a value determined based on the solar radiation annual variation correction coefficient, aging correction coefficient, array load matching correction coefficient, battery contribution ratio, battery charge / discharge efficiency, inverter effective efficiency, DC conditioner effective efficiency, etc. is there. The maximum output temperature coefficient α _Pmax is a value determined based on the characteristics of the solar panel, and normally indicates a negative value. The target time temperature T (n) is the temperature at n hours among the estimation results of “temperature from sunrise time to sunset time” on the corresponding date. The weighted average solar module temperature increase value ΔT is a difference between the temperature and the temperature of the solar cell module weighted and averaged by the solar radiation intensity, and is a measure of the array temperature increase as an average value.

  Formula (2) is determined based on Formula (3) shown in [Formula 3], Formula (4) shown in [Formula 4], and Formula (5) shown in [Formula 5].

Among these, _KPT is a temperature correction coefficient, and _TCR is a weighted average solar module temperature. The temperature correction coefficient _KPT is a coefficient for correcting the influence of the temperature on the power generation amount. The weighted average solar module temperature _TCR is a temperature of the solar cell module weighted and averaged by the solar radiation intensity.

  Then, the power generation amount E (n) is calculated using Equation (6) shown in [Equation 6]. Note that Equation (6) is an equation including the estimation coefficient K.

K is a correction coefficient, Pas is the standard solar cell array output [kW], Gs is the solar radiation intensity [kW · m ⁻² ] under the standard test conditions, and R (n) is from (n + 1) to (n + 1) ) Integrated solar radiation amount [kWh · hour ⁻¹ ] in one hour until the hour. Of these, the integrated solar radiation amount R (n) is calculated using a separately provided calculation formula or map data (waveform data).

  In next S240, the calculation result (power generation amount E (n)) in S230 is stored in at least one of the storage unit 15 and the storage device 35, and is output (displayed or printed) to the output device 33.

When S240 ends, the power generation amount estimation calculation process ends.
By executing the power generation amount estimation calculation process in this way, it is possible to estimate the power generation amount E (n) in one hour from n o'clock to (n + 1) o'clock.

[1-4. effect]
As described above, the data calculation system 1 according to the present embodiment executes the weather data estimation calculation process, so that past weather data (the highest temperature TH, the lowest temperature TL, the sunrise time Tsr, the day of the day) Based on the dead time (Tss), the meteorological data of the estimation target point (temperature from the sunrise time to the sunset time) is estimated. Specifically, based on the execution command from the user, “the temperature from the sunrise time to the sunset time” (temperature change waveform) of the estimation target date at the estimation target point is estimated.

  In the meteorological data estimation calculation process, by executing the above-described series of processes (S110 to S180), “temperature from sunrise time to sunset time” (temperature change waveform) as shown in FIG. 3 is estimated. be able to.

  In particular, since the past meteorological data necessary for estimating the temperature is four (maximum temperature TH, minimum temperature TL, sunrise time Tsr, sunset time Tss of the day), the necessary amount of information can be suppressed. .

  Therefore, according to the data calculation system 1 of the present embodiment, it is possible to estimate meteorological data while suppressing the amount of information necessary for estimating meteorological data (temperature from sunrise time to sunset time) at the estimation target point. .

  Further, the data calculation system 1 has waveform data (FIG. 5) representing the correlation between the daytime time and the rate of decrease Rd from the maximum temperature as the temperature change amount information used in the process of S160 of the weather data estimation calculation process, An arithmetic expression (Formula (1)) for calculating the temperature decrease amount TR using the decrease rate Rd is used.

  As described above, by using the waveform data and the calculation formula as the temperature change amount information, the data calculation system 1 can estimate the meteorological data (temperature from the sunrise time to the sunset time) of the estimation target point.

  Further, in S150 of the weather data estimation calculation process, the data calculation system 1 sets a curve corresponding to a part of the sine wave waveform as a temperature waveform from the sunrise time Tsr to the maximum temperature estimated time Tce. More specifically, a curve corresponding to a half cycle from the minimum value to the maximum value of the sine wave waveform is used.

Thereby, the data calculation system 1 can estimate the temperature waveform from the sunrise time Tsr to the maximum temperature estimation time Tce.
In S180 of the weather data estimation calculation process, the data calculation system 1 sets a curve corresponding to a part of the sine wave waveform as a temperature waveform from the maximum temperature estimated time Tce to the sunset time Tss. More specifically, a curve corresponding to the period from the maximum value to the lapse of a quarter period is used in the sine wave waveform.

Thereby, the data calculation system 1 can estimate the temperature waveform from the maximum temperature estimation time Tce to the sunset time Tss.
In addition, the data calculation system 1 of the present embodiment performs natural power generation using the “temperature from sunrise time to sunset time” obtained by the meteorological data estimation calculation process by executing the power generation amount estimation calculation process. The power generation amount E (n) per hour at the used power plant is calculated.

  Since “temperature from sunrise time to sunset time” is calculated based on past weather data, it is highly reliable estimation data reflecting the tendency of past weather data. Further, as described above, the data calculation system 1 can estimate meteorological data while suppressing the amount of information necessary for estimating meteorological data (temperature from the sunrise time to the sunset time) of the estimation target point.

  By calculating the power generation amount E (n) using such estimated weather data (the temperature from the sunrise time to the sunset time), a highly reliable estimated power generation amount can be obtained while suppressing the amount of information required. Can be obtained.

[1-5. Correspondence with Claims]
Here, the correspondence of the words in the claims and the present embodiment will be described.
The calculation method of “temperature from sunrise time to sunset time” by the weather data estimation calculation process corresponds to an example of the weather data estimation method, S130 corresponds to an example of the first step, and S140 corresponds to an example of the second step. S150 corresponds to an example of the third step, S160 corresponds to an example of the fourth step, S170 corresponds to an example of the fifth step, and S180 corresponds to an example of the sixth step.

  The maximum temperature TH corresponds to an example of the maximum temperature of the day, the minimum temperature TL corresponds to an example of the minimum temperature of the day, the sunrise time Tsr corresponds to an example of the sunrise time, and the sunset time Tss Corresponds to an example of sunset time, south-intermediate time Tc corresponds to an example of south-intermediate time, and delay time Td corresponds to an example of delay time. The waveform data and the mathematical formula (1) shown in FIG. 5 correspond to an example of temperature change amount information.

The calculation method of the power generation amount by the power generation amount estimation calculation process corresponds to an example of the power generation amount estimation method, and S230 in the power generation amount estimation calculation process corresponds to an example of the power generation amount calculation step.
[2. Other Embodiments]
As mentioned above, although embodiment of this invention was described, this invention is not limited to the said embodiment, In the range which does not deviate from the summary of this invention, it is possible to implement in various aspects.

  For example, in the above-described embodiment, as the process of S150, the form in which the estimated temperature at the sunrise time Tsr and the estimated temperature at the maximum temperature estimated time Tce are connected by a curve (part of a sine wave waveform) has been described. Is not limited to such a form. For example, the form which connects the estimated temperature of sunrise time Tsr and the estimated temperature of maximum temperature estimated time Tce using a straight line instead of a curve may be sufficient. Moreover, when using a curve, it is not restricted to the curve equivalent to the half period from the minimum value to the maximum value among sine wave waveforms, and another curve may be sufficient. For example, by using a curve corresponding to a part of a half cycle from the minimum value to the maximum value of the sine wave waveform (in other words, a period shorter than the half cycle), the estimated temperature at sunrise time Tsr and The form which connects estimated temperature of maximum temperature estimated time Tce may be sufficient.

  Moreover, although the said embodiment demonstrated the form which connects the estimated temperature of the highest temperature estimated time Tce and the estimated temperature of the sunset time Tss with a curve (a part of sine wave waveform) as a process of S180, The processing is not limited to such a form. For example, the form which connects the estimated temperature of maximum temperature estimated time Tce and the estimated temperature of sunset time Tss using a straight line instead of a curve may be sufficient. Moreover, when using a curve, it is not restricted to the curve corresponding to a sine wave waveform until a quarter period passes from the maximum value, and another curve may be sufficient. For example, by using a curve corresponding to a part of a period (in other words, a period shorter than the quarter cycle) from the maximum value of the sine wave waveform until the quarter cycle elapses, the maximum temperature estimation time Tce is used. The estimated temperature and the estimated temperature at sunset time Tss may be connected.

  In the above embodiment, the waveform data shown in FIG. 5 is exemplified and described as the reduction rate information representing the correlation between the daytime time used in the processing of S160 and the reduction rate Rd from the maximum temperature. The information is not limited to the waveform data shown in FIG. For example, the waveform data represented by the curve CL as shown in FIG. 7 may be used as the rate of decline information representing the correlation between the daytime time and the rate of decline Rd from the maximum temperature. Note that the curve CL is a plurality of measurement points obtained by actual measurement on the coordinate plane shown in FIG. 7 (in other words, a plurality of correlations indicating the actual correlation between the daytime time and the rate of decrease Rd from the maximum temperature). It is an example of the approximate line drawn based on the measurement point. Further, the decrease rate information may be realized using waveform data expressed using a quadratic function, an exponential function, or a logarithmic function. Further, the decrease rate information may be an approximate line (or approximate expression) created based on past actual measurement data at a point related to the measurement target point. That is, the reduction rate information may adopt any form such as waveform data or a calculation formula as long as the reduction rate Rd is obtained by inputting daytime time.

  Moreover, although the said embodiment demonstrated the form which calculates the temperature which deducted temperature fall amount TR from maximum temperature TH as the estimated temperature TE in sunset time Tss as a process of S170, the process in S170 is such The form is not limited. For example, the estimated temperature TE at the sunset time Tss may be calculated using Equation (7) shown in [Equation 7] and Equation (8) shown in [Equation 8].

  Note that TE is an estimated temperature, TH is a maximum temperature, K1 is a first coefficient, DT is daytime, TL is a minimum temperature, and K2 is a second coefficient. Among these, the first coefficient K1 and the second coefficient K2 are predetermined constants, respectively.

  Further, Formula (9) shown in [Formula 9], Formula (10) shown in [Formula 10], Formula (11) shown in [Formula 11], Formula (12) shown in [Formula 12], [Formula 13] The estimated temperature TE at the sunset time Tss may be calculated using Equation (13).

  Note that the third coefficient K3, the fourth coefficient K4, the fifth coefficient K5, the sixth coefficient K6, and the seventh coefficient K7 are all numerical values calculated by waveform data or calculation formulas having daytime time as an input value. . Further, the third coefficient K3, the fourth coefficient K4, the fifth coefficient K5, the sixth coefficient K6, and the seventh coefficient K7 are numerical values determined in accordance with the corresponding mathematical expressions, respectively, depending on different waveform data or calculation expressions, etc. A numerical value to be calculated.

  Further, in the above embodiment, the configuration in which the weather data estimation calculation process and the power generation amount estimation calculation process are independently executed based on different execution commands has been described. However, based on one execution command, the weather data is calculated. It is good also as a structure which performs an electric power generation amount estimation calculation process, without waiting for the execution command from a user, after performing an estimation calculation process.

  Moreover, although the said embodiment demonstrated the structure which reads the past weather data from the memory | storage part 15 or the memory | storage device 35 in S120 of a weather data estimation calculation process, it is not restricted to such a structure. For example, the data calculation system 1 may take a form in which past weather data is input from the user via the input device 31.

  Furthermore, in the above-described embodiment, the configuration in which the point closest to the estimation target point is set as the “point related to the estimation target point” in S120 of the weather data estimation calculation process is described, but the configuration is limited to such a configuration. There is no.

  For example, the configuration may be such that “a point where the temperature change is similar to the estimation target point” is set as “a point related to the estimation target point”. In this case, the user selects “a point where the temperature change is similar to the estimation target point” in advance, and the execution command input from the user via the input device 31 includes the command content indicating the point. It may be configured.

  Moreover, the configuration may be such that “a plurality of points whose distance from the estimation target point is within a predetermined range” is set as “a point related to the estimation target point”. In this case, in S120, for example, information on the latitude and longitude of each point is used to extract “a plurality of points whose distance from the estimation target point is within a predetermined range” from points where past weather data exists. Then, it may be set as “a point related to the estimation target point”. The average value of past weather data at a plurality of extracted points may be used as “past weather data at a point related to the estimation target point”.

  Furthermore, you may produce the program for making a computer perform the weather data estimation method of this invention. By using such a program, it is possible to cause a computer to execute a weather data estimation method. Similarly, a program for causing a computer to execute the power generation amount estimation method of the present invention may be created. By using such a program, it is possible to cause the computer to execute the power generation amount estimation method.

  DESCRIPTION OF SYMBOLS 1 ... Data operation system, 11 ... Operation apparatus, 13 ... Operation part, 15 ... Memory | storage part, 17 ... Memory, 19 ... Communication part, 21 ... Interface part, 31 ... Input device, 33 ... Output device, 35 ... Memory | storage device.

Claims (5)

A meteorological data estimation method for estimating meteorological data at an estimation target point based on past meteorological data,
The weather data is the temperature from sunrise time to sunset time,
The past weather data includes at least a maximum temperature, a minimum temperature, a sunrise time, and a sunset time of the day,
A first step of setting the lowest temperature as an estimated temperature at the sunrise time on a temperature coordinate plane with time on the horizontal axis and temperature on the vertical axis;
The south / intermediate time is calculated using the sunrise time and the sunset time, and the highest temperature is estimated at the highest temperature estimated time when a predetermined delay time has elapsed from the south / central time in the temperature coordinate plane. A second step to set as
In the temperature coordinate plane, a waveform obtained by connecting the estimated temperature at the sunrise time and the estimated temperature at the maximum temperature estimated time with a predetermined curve or straight line as a temperature waveform from the sunrise time to the maximum temperature estimated time. A third step to set,
Temperature change information determined based on past meteorological data at a point related to the estimation target point among the past meteorological data, and correlation between daytime from sunrise time to sunset time and temperature change amount The temperature change information for which the relationship has been defined or the temperature change information for which the correlation between the elapsed time from the maximum temperature observation time and the temperature change has been defined, and the sunset time from the maximum temperature estimation time. A fourth step of calculating the temperature drop until
A fifth step of setting, in the temperature coordinate plane, a temperature obtained by subtracting the temperature decrease amount from the maximum temperature as an estimated temperature at the sunset time;
In the temperature coordinate plane, a temperature obtained by connecting the estimated temperature at the highest temperature estimated time and the estimated temperature at the sunset time with a predetermined curve or straight line, from the highest temperature estimated time to the sunset time. A sixth step to set as a waveform;
A meteorological data estimation method comprising: The temperature change information is
On the temperature reduction rate coordinate plane in which the horizontal axis is daytime and the vertical axis is the rate of decrease from the maximum temperature, the waveform data indicating the correlation between the daytime time and the rate of decrease, and the rate of decrease Or a change amount calculation formula for calculating the temperature change amount,
Or, it is composed of waveform data indicating the correlation between the elapsed time from the maximum temperature observation time and the temperature change amount on the temperature change amount coordinate plane with the horizontal axis as the elapsed time and the vertical axis as the temperature change amount. The
The meteorological data estimation method according to claim 1. In the third step, in the temperature coordinate plane, a waveform obtained by connecting the estimated temperature at the sunrise time and the estimated temperature at the maximum temperature estimated time with a curve corresponding to a part of a sine waveform is obtained from the sunrise time. Set as the temperature waveform up to the maximum temperature estimated time,
In the sixth step, in the temperature coordinate plane, a waveform obtained by connecting the estimated temperature at the highest temperature estimated time and the estimated temperature at the sunset time with a curve corresponding to a part of a sine wave waveform is obtained. Set as the temperature waveform from the estimated time to the sunset time,
The weather data estimation method according to claim 1 or 2. In the third step, in the temperature coordinate plane, the estimated temperature at the sunrise time and the estimated temperature at the maximum temperature estimated time are represented by a curve corresponding to a half cycle from a minimum value to a maximum value of a sine wave waveform. Set the connected waveform as the temperature waveform from the sunrise time to the maximum temperature estimation time,
In the sixth step, in the temperature coordinate plane, the estimated temperature at the maximum temperature estimated time and the estimated temperature at the sunset time are represented by a curve corresponding to a lapse of a quarter cycle from the maximum value of the sine wave waveform. Set the connected waveform as the temperature waveform from the highest temperature estimation time to the sunset time,
The meteorological data estimation method according to claim 3. A method for estimating the power generation amount of a power plant using natural energy,
The power plant is a solar power plant,
A power generation amount calculating step of calculating an estimated power generation amount at the power plant based on weather data at the power plant,
The estimated power generation amount is calculated using weather data estimated by the meteorological data estimation method according to any one of claims 1 to 4.
Power generation amount estimation method.

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