JP2016139270A - Photovoltaic power generation output estimation device, photovoltaic power generation output estimation system and photovoltaic power generation output estimation method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a photovoltaic power generation output estimation device capable of estimating power generation output of a photovoltaic power generation facility without installing the device in individual users.SOLUTION: A photovoltaic power generation output estimation device 100 estimates photovoltaic power generation output to be power generation output at a predetermined point in a photovoltaic power generation facility for supplying power to a load connected to a power system. The photovoltaic power generation output estimation device includes a power generation output estimation unit 130 that estimates photovoltaic power generation output with solar radiation intensity at the predetermined point and effective power of the power system, in a period that is a period before the predetermined point and within a predetermined range from a culmination altitude with the culmination attitude of the sun as the predetermined point.SELECTED DRAWING: Figure 2

Description

  The present invention relates to a solar power generation output estimation device, a solar power generation output estimation system, and a solar power generation output estimation method for estimating a power generation output of a solar power generation facility that supplies power to a load connected to an electric power system.

  In recent years, an increasing number of consumers have installed a distributed power source such as a solar power generation facility, and supply power from the solar power generation facility to a load connected to a commercial power system (hereinafter simply referred to as a power system). . For this reason, the apparatus which estimates the electric power generation output of the solar power generation installation which each consumer installed is proposed (for example, refer patent document 1).

JP 2014-95941 A

  Here, if a large number of photovoltaic power generation facilities are introduced, various problems occur in power system operation. In other words, although the load on the apparent power system taking into account the power generation output of the photovoltaic power generation facility can be measured with a measuring instrument, the power generation output of the solar power generation facility is unknown, so the actual load (actual load) is grasped. I can't. For this reason, if a large number of photovoltaic power generation facilities are introduced, the risk in demand and supply control that the error in demand assumption will increase will increase, and the risk in system control that will hinder recovery work in the event of an accident increases. To do.

  For this reason, it is necessary to estimate the power generation output of the solar power generation facility. However, since the conventional device is a device for estimating the power generation output of the solar power generation facility installed by each consumer, the solar power generation facility If a large amount is introduced, it becomes necessary to install the device in all consumers. However, introducing the device to all consumers has technical and cost problems.

  Therefore, the present invention has been made in view of such problems, and a photovoltaic power generation output estimation device capable of estimating the power generation output of photovoltaic power generation equipment without installing a device at each consumer. An object of the present invention is to provide a photovoltaic power generation output estimation system and a photovoltaic power generation output estimation method.

  In order to achieve the above object, a photovoltaic power generation output estimation device according to an aspect of the present invention is a solar power generation output at a predetermined time of a photovoltaic power generation facility that supplies power to a load connected to a power system. A photovoltaic power generation output estimation device for estimating a power generation output, wherein the predetermined point is a period before the predetermined time point and the solar south-middle altitude is within a predetermined range from the south-middle altitude at the predetermined time point. The solar power generation output is estimated using the solar radiation intensity and the active power of the electric power system.

  According to this, the solar power generation output estimation device uses the solar radiation intensity at the predetermined point and the active power of the power system in the period before the predetermined time point and the solar south-middle altitude is within the predetermined range. To estimate the solar power output. In other words, for example, by using data in a period in which the solar south-middle altitude is about 1 to 2 weeks before a predetermined time, the solar power output can be estimated more accurately, and the solar radiation intensity and power system It is possible to easily estimate the photovoltaic power generation output by using the effective power. Here, the estimated photovoltaic power generation output is the power generation output at a predetermined time of the solar power generation facility that supplies power to the load connected to the power system, that is, the power generation of the entire solar power generation facility connected to the power system. Is the output. For this reason, according to the photovoltaic power generation output estimation device, the power generation output of the entire photovoltaic power generation facility connected to the power system can be estimated accurately and simply, so that the device is installed at each consumer. In addition, the power generation output of the solar power generation facility can be estimated.

  Further, the power generation output estimation unit may estimate the solar power generation output using the time series data of the solar radiation intensity and the time series data of the active power in a short time within the period. .

  According to this, the photovoltaic power generation output estimation device estimates the photovoltaic power generation output using time series data of the solar radiation intensity and the active power of the power system in a short time. That is, for example, the photovoltaic power generation output can be estimated using data in a short period of about 30 minutes to 2 hours. For this reason, according to the solar power generation output estimation apparatus, since it is not necessary to acquire time-series data for a long time, the power generation output of the solar power generation facility can be estimated easily and quickly.

  Further, the power generation output estimation unit is configured to calculate the solar radiation intensity and the effective power during a period in which a total installed capacity of the photovoltaic power generation facility linked to the power system is within a predetermined range from the total installed capacity at the predetermined time point. The solar power generation output may be estimated using electric power.

  According to this, the solar power generation output estimation device uses the solar radiation intensity and the active power of the power system in a period in which the total facility capacity of the solar power generation facilities linked to the power system is within a predetermined range, Estimate photovoltaic power output. That is, the photovoltaic power generation output estimation apparatus can estimate the power generation output of the photovoltaic power generation facility more accurately by using data in a period in which the total facility capacity of the photovoltaic power generation facility is equivalent.

  Furthermore, a first covariance acquisition unit that acquires a first covariance that is a covariance of time series data of the solar radiation intensity and the active power, and two time series data of the solar radiation intensity that are shifted in delay time. A second covariance acquisition unit that acquires a second covariance that is self-covariance, and the power generation output estimation unit uses the acquired first covariance and the second covariance, and The photovoltaic power output may be estimated.

  According to this, the solar power generation output estimation device is capable of the first covariance that is the covariance of the time series data of the solar radiation intensity and the active power of the power system, and the time series data of the two solar radiation intensity that are shifted in delay time. The solar power output is estimated using the second covariance that is self-covariance. For this reason, the photovoltaic power generation output estimation device can easily estimate the power generation output of the photovoltaic power generation facility using the first covariance and the second covariance.

  In addition, the power generation output estimation unit calculates the solar power generation output by multiplying the coefficient obtained by using the first covariance and the second covariance by the solar radiation intensity at the predetermined point. May be.

  According to this, the photovoltaic power generation output estimation device can calculate the photovoltaic power generation output by multiplying the coefficient obtained by using the first covariance and the second covariance by the solar radiation intensity at a predetermined point. Therefore, the power generation output of the photovoltaic power generation facility can be estimated with a simple calculation.

  The power generation output estimation unit may calculate the solar power generation output using the coefficient obtained by dividing the first covariance by the second covariance and multiplying the negative covariance by the coefficient.

  According to this, since the photovoltaic power generation output estimation device can calculate the photovoltaic power generation output by using the value obtained by dividing the first covariance by the second covariance and multiplying by the above-mentioned coefficient, The power generation output of the photovoltaic power generation facility can be estimated with a simple calculation.

  In addition, the second covariance acquisition unit acquires the second covariance using the time during which the solar radiation intensity moves between the solar radiation intensity measurement point and the installation point of the photovoltaic power generation facility as the delay time. You may decide.

  According to this, the photovoltaic power generation output estimation device calculates the second covariance using the time during which the solar radiation intensity moves between the solar radiation intensity measurement point and the installation point of the solar power generation facility as a delay time, The power generation output of the solar power generation facility can be estimated.

  Further, the first covariance acquisition unit acquires the first covariance that is a covariance of time series data of the solar radiation intensity and the active power in a predetermined period, and the second covariance acquisition unit The second covariance may be acquired using a lag when the covariance function of the time series data of the solar radiation intensity and the active power in a predetermined period takes a minimum value as the delay time.

  According to this, the photovoltaic power generation output estimating apparatus uses the second covariance as a delay time with a lag when the covariance function of the time series data of the solar radiation intensity and the active power of the power system in the predetermined period takes a minimum value. By calculating, the second covariance can be easily obtained.

  The first covariance acquisition unit acquires the time series data of the solar radiation intensity and the time series data of the active power in the first period, and the time series data of the solar radiation intensity and the time series data of the active power Is calculated as the first covariance, and the second covariance acquisition unit is a time-series data of the solar radiation intensity in the first period, and a period shifted by the delay time from the first period. Obtaining the time series data of the solar radiation intensity in the second period, calculating the self-covariance of the time series data of the two solar radiation intensity as the second covariance, and the power generation output estimating unit The photovoltaic power generation output may be calculated by multiplying the coefficient obtained by using the variance and the second covariance by the solar radiation intensity at the time when the delay time is shifted from the predetermined time.

  According to this, the photovoltaic power generation output estimating device calculates the covariance between the time series data of the solar radiation intensity in the first period and the time series data of the active power of the power system as the first covariance, The self-covariance between the time series data of the solar radiation intensity and the time series data of the solar radiation intensity in the second period shifted from the first period is calculated as the second covariance. Then, the photovoltaic power generation output estimation device multiplies the coefficient obtained by using the calculated first covariance and second covariance by the solar radiation intensity at the time deviated from the predetermined time by the solar power output Is calculated. Thereby, the solar power generation output estimation apparatus can estimate the power generation output of solar power generation equipment.

  In addition, the first covariance acquisition unit calculates the first covariance, and the second covariance acquisition unit calculates the first covariance as a period in which the solar radiation intensity is strong and the fluctuation of the solar radiation intensity is large. Bicovariance may be calculated.

  According to this, the solar power generation output estimation device calculates the first covariance and the second covariance with a period in which the solar radiation intensity is strong and the fluctuation of the solar radiation intensity is large as the first period. In other words, the photovoltaic power generation output estimation device calculates the first covariance and the second covariance more accurately by calculating the first covariance as the first period in which the characteristics of the period for estimating the photovoltaic power generation are prominent. The power generation output of the solar power generation facility can be estimated.

  In addition, the present invention can be realized not only as such a photovoltaic power generation output estimation apparatus, but also with the photovoltaic power generation output estimation apparatus, a solar radiation meter that measures solar radiation intensity at a predetermined point, and an effective power system. It can also be realized as a photovoltaic power generation output estimation system including a measuring instrument for measuring electric power.

  Moreover, this invention is realizable also as a solar power generation output estimation method which uses the characteristic process which the process part contained in said solar power generation output estimation apparatus performs as a step. In addition, it can be realized as a program or an integrated circuit that causes a computer to execute characteristic processing included in the photovoltaic power generation output estimation method. 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 solar power generation output estimation apparatus which can estimate the power generation output of a solar power generation installation can be provided, without installing an apparatus in each consumer.

It is a figure which shows the structure of a photovoltaic power generation output estimation system provided with the photovoltaic power generation output estimation apparatus which concerns on embodiment of this invention. It is a block diagram which shows the functional structure of the photovoltaic power generation output estimation apparatus which concerns on embodiment of this invention. It is a flowchart which shows an example of the process (solar power generation output estimation method) which the solar power generation output estimation apparatus which concerns on embodiment of this invention estimates a solar power generation output. It is a flowchart which shows an example of the process in which the 1st covariance acquisition part which concerns on embodiment of this invention acquires 1st covariance. It is a graph which shows transition of the change of the south-middle altitude in one year and the difference of the south-middle altitude in the day 1 week and two weeks away. It is a flowchart which shows an example of the process in which the 2nd covariance acquisition part which concerns on embodiment of this invention acquires 2nd covariance. It is a flowchart which shows an example of the process in which the electric power generation output estimation part which concerns on embodiment of this invention estimates a solar power generation output. It is a figure explaining that there is no correlation between load and solar radiation intensity. It is a figure explaining that there is no correlation between load and solar radiation intensity. It is a figure explaining that there is no correlation between load and solar radiation intensity. It is a figure explaining that there is no correlation between load and solar radiation intensity. It is a figure explaining the process in which the 2nd covariance acquisition part which concerns on embodiment of this invention acquires delay time. It is a figure which shows the structure at the time of explaining the effect which the photovoltaic power generation output estimation apparatus which concerns on embodiment of this invention show | plays. It is a graph which shows the time series data of the solar radiation intensity and electric power flow in winter weekdays. It is a graph which shows the covariance of the solar radiation intensity and electric power flow in a winter weekday. It is a graph which shows the estimated value and true value of the power generation output of the solar power generation equipment of the day which measured the solar radiation intensity and the power flow on the weekday of winter. It is a graph which shows the estimated value and true value of the power generation output of the photovoltaic power generation equipment on the next day which measured the solar radiation intensity and the power flow on the weekday of winter. It is a histogram which shows the difference | error from the true value of the estimated value of the power generation output of the solar power generation equipment of the day which measured the solar radiation intensity and the power flow on the weekday of winter. It is a histogram which shows the difference | error from the true value of the estimated value of the power generation output of the photovoltaic power generation equipment of the next day which measured the solar radiation intensity and electric power flow on the weekday of winter. It is a graph which shows the time series data of the solar radiation intensity and electric power flow in winter Saturday and Sunday. It is a graph which shows the covariance of the solar radiation intensity and electric power flow in winter Saturday and Sunday. It is a graph which shows the estimated value and true value of the power generation output of the solar power generation equipment of the day which measured the solar radiation intensity and electric power flow on winter Saturday and Sunday. It is a graph which shows the estimated value and true value of the power generation output of the photovoltaic power generation equipment of the next day which measured solar radiation intensity and electric power flow on the weekend of winter. It is a histogram which shows the difference | error from the true value of the estimated value of the power generation output of the solar power generation equipment of the day which measured the solar radiation intensity and electric power flow on the weekend of winter. It is a histogram which shows the difference | error from the true value of the estimated value of the power generation output of the photovoltaic power generation equipment of the next day which measured the solar radiation intensity and electric power flow on the winter Saturday and Sunday. It is a graph which shows the estimated value and true value of the electric power generation output of the solar power generation equipment of the day which measured the solar radiation intensity and electric power flow on the spring Saturday and Sunday. It is a graph which shows the estimated value and true value of the power generation output of the photovoltaic power generation equipment on the next day which measured the solar radiation intensity and the power flow on the spring Saturday and Sunday. It is a histogram which shows the difference | error from the true value of the estimated value of the power generation output of the solar power generation equipment of the day which measured the solar radiation intensity and electric power flow on the spring Saturday and Sunday. It is a histogram which shows the difference | error from the true value of the estimated value of the power generation output of the photovoltaic power generation equipment of the next day which measured the solar radiation intensity | strength and electric power flow on the weekend of spring. It is a graph which shows the estimated value and true value of the electric power generation output of the solar power generation equipment of the day which measured the solar radiation intensity and electric power flow on a spring weekday. It is a graph which shows the estimated value and true value of the power generation output of the photovoltaic power generation equipment of the next day which measured the solar radiation intensity and the power flow on the weekday of spring. It is a histogram which shows the difference | error from the true value of the estimated value of the electric power generation output of the solar power generation equipment of the day which measured the solar radiation intensity and electric power flow on the weekday of spring. It is a histogram which shows the difference | error from the true value of the estimated value of the power generation output of the photovoltaic power generation equipment on the next day which measured the solar radiation intensity and the power flow on the weekday of spring.

  Hereinafter, a photovoltaic power generation estimation apparatus and a photovoltaic power generation output estimation system according to embodiments 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 illustrating a configuration of a photovoltaic power generation output estimation system 10 including a photovoltaic power generation output estimation device 100 according to an embodiment of the present invention.

  As shown in the figure, the photovoltaic power generation output estimation system 10 includes a photovoltaic power generation output estimation device 100, a pyranometer 200, and a measuring instrument 300.

  The photovoltaic power generation output estimation device 100 is a computer that estimates a photovoltaic power generation output that is a power generation output at a predetermined time of a photovoltaic power generation facility that supplies power to a load connected to an electric power system. Here, the predetermined time point includes not only the current time point but also a past or future time point. The photovoltaic power generation output 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. The detailed configuration of the photovoltaic power generation output estimation apparatus 100 will be described later.

  The solar radiation meter 200 is a solar radiation meter that measures the solar radiation intensity at a predetermined point. That is, the solar radiation meter 200 is arranged at a predetermined point, measures the solar radiation intensity at regular time intervals, and outputs the measured solar radiation intensity to the photovoltaic power generation output estimating apparatus 100. In addition, the point where the pyranometer 200 is arranged is arbitrarily determined by the user.

  Further, the time interval at which the solar radiation meter 200 measures the solar radiation intensity is not particularly limited, such as 1 second, 10 seconds, 1 minute, and the like, and an appropriate numerical value is determined by the user. Further, the solar radiation meter 200 may measure the solar radiation intensity at a timing arbitrarily determined by the user, instead of measuring the solar radiation intensity at regular time intervals. Moreover, it does not specifically limit about the timing which outputs the solar radiation intensity which the solar radiation meter 200 measured to the solar power generation output estimation apparatus 100, You may output whenever solar radiation intensity is measured, The predetermined | prescribed predetermined by the user You may decide to output at a timing.

  The measuring instrument 300 is a measuring instrument that measures the active power of the power system 400. That is, the measuring instrument 300 measures at least the active power of the power system 400 among the active power and reactive power of the power system 400. Specifically, the measuring instrument 300 is installed in the vicinity of the electric power system 400, measures the effective electric power of the electric power system 400 at a constant time interval, and supplies the measured effective electric power to the photovoltaic power generation output estimating apparatus 100. Output.

  The time interval at which the measuring device 300 measures the effective power is not particularly limited, such as 1 second, 10 seconds, 1 minute, and an appropriate numerical value is determined by the user. The measuring device 300 may measure the active power at a timing arbitrarily determined by the user, instead of measuring the active power at regular time intervals. Further, the timing at which the active power measured by the measuring instrument 300 is output to the photovoltaic power generation output estimating apparatus 100 is not particularly limited, and may be output every time the active power is measured or determined by the user. It may be output at a predetermined timing.

  As the measuring instrument 300, for example, a PQVF recording device (for example, a PQVF recording device installed in a substation for the purpose of recording fluctuations in active power (P), reactive power (Q), voltage (V) and frequency (F). A system information recording device), a remote monitoring control system (telecon) that transmits a telemeter to a power supply control station, a sensor-equipped section switch (VS) installed on a utility pole, or the like can be used.

  Here, the power system 400 is a commercial power system to which power is supplied from a power generation facility 500 such as an electric power company via a substation (S / S). In addition, a plurality of loads 410 are connected to the power system 400, and a plurality of photovoltaic power generation facilities 420 are interconnected.

  The load 410 is a power load consumed by a consumer, for example, power consumption of home appliances such as an air conditioner, power consumption for operating a machine in a factory, and the like. The load 410 may be any load as long as it is a power load connected to the power system 400.

  The photovoltaic power generation facility 420 is, for example, a photovoltaic power generation (PV) facility installed on the roof of a building owned by a consumer, and is not only a small-scale photovoltaic power generation facility but also a large-scale photovoltaic power plant. (So-called mega solar) is also included. The photovoltaic power generation facility 420 supplies the generated power to the load 410 connected to the power system 400 or supplies the power system 400 with the generated power. That is, the solar power generation facility 420 is a power generation facility that is directly or indirectly linked to the power system 400.

  Thus, the apparent appearance of the power system 400 depends on the size of all the loads 410 connected to the power system 400 and the size of the power generation output of all the photovoltaic power generation facilities 420 connected to the power system 400. The load of will fluctuate. It should be noted that the apparent load of the power system 400 can also be referred to as a power flow (or line power flow), and hereinafter referred to as a power flow.

  Next, a detailed functional configuration of the photovoltaic power generation output estimation apparatus 100 will be described.

  FIG. 2 is a block diagram showing a functional configuration of the photovoltaic power generation output estimation apparatus 100 according to the embodiment of the present invention.

  The photovoltaic power generation output estimation device 100 is a device that estimates a photovoltaic power generation output that is a power generation output at a predetermined time of a photovoltaic power generation facility 420 that supplies power to a load 410 connected to the power system 400. As shown in the figure, the photovoltaic power generation output estimation apparatus 100 includes a first covariance acquisition unit 110, a second covariance acquisition unit 120, a power generation output estimation unit 130, and a storage unit 140.

  The storage unit 140 is a memory that stores data for estimating the power generation output of the photovoltaic power generation facility 420 at a predetermined time. Specifically, the storage unit 140 is data input from the pyranometer 200 or the measuring instrument 300, data calculated by the first covariance acquisition unit 110, the second covariance acquisition unit 120, or the power generation output estimation unit 130, etc. The estimation data 141 including is stored.

  Although not shown, the photovoltaic power generation output estimation apparatus 100 may include an input unit such as a keyboard and a mouse and a display unit such as a liquid crystal display.

  The power generation output estimating unit 130 is a period before the predetermined time point, and the solar radiation intensity at the predetermined point and the validity of the power system 400 in the period in which the solar south-middle altitude is within the predetermined range from the south-middle altitude at the predetermined time point. The solar power generation output is estimated using the power (hereinafter referred to as the active power of the power flow). Here, the solar power generation output is a power generation output at a predetermined time of the solar power generation facility 420 that supplies power to the load 410 connected to the power system 400.

  In addition, although the active power and the reactive power exist in the power generation output of the solar power generation equipment 420, the solar power generation equipment 420 (especially for home use) is generally operated at a power factor of 1, Many have only active power. For this reason, hereinafter, the power generation output of the solar power generation facility 420 refers to the effective power of the power generation output of the solar power generation facility 420.

  Moreover, it is preferable that said period is a period in which the total installation capacity of the photovoltaic power generation equipment 420 is within a predetermined range from the total installation capacity at a predetermined point in time. That is, the power generation output estimation unit 130 determines the solar radiation intensity and the power flow in a period in which the total installed capacity of the photovoltaic power generation equipment 420 linked to the power system 400 is within a predetermined range from the total installed capacity at a predetermined time. The photovoltaic power generation output is estimated using the effective power of. Note that the total installed capacity of the photovoltaic power generation equipment 420 that is linked to the power system 400 at a certain time is, in other words, the total installed capacity of the photovoltaic power generation equipment 420 that is installed in the power system 400 at that time. is there.

  Thus, the period is a period before the predetermined time point for estimating the photovoltaic power output, and the solar south-middle altitude is within a predetermined range from the south-middle altitude at the predetermined time point, and The total installation capacity of the photovoltaic power generation equipment 420 is a period within a predetermined range from the total installation capacity at a predetermined time point. For example, the period is a period of about one to two weeks retroactive from a predetermined time point when the solar power output is estimated, and specifically, the day before the day when the solar power output is estimated.

  More specifically, the power generation output estimation unit 130 uses the time series data of the solar radiation intensity and the time series data of the active power of the power flow in a short time within the period to generate the solar power output. presume. Here, the said short time is a short period of about 30 minutes-2 hours, for example, Preferably it is 1 hour. That is, the power generation output estimation unit 130 reflects the solar radiation intensity and the power flow in a short period of about 30 minutes to 2 hours within a period of about 1 to 2 weeks retroactive from a predetermined time point for estimating the photovoltaic power generation output. The solar power generation output is estimated using time series data of active power. The short time corresponds to the following first period.

  Here, the power generation output estimation unit 130 uses the first covariance and the second covariance acquired by the first covariance acquisition unit 110 and the second covariance acquisition unit 120 described below, to Estimate power generation output.

  The first covariance acquisition unit 110 acquires the first covariance that is the covariance of time-series data between the solar radiation intensity at a predetermined point and the effective power of the power flow. Specifically, the first covariance acquisition unit 110 acquires time series data of the solar radiation intensity in the first period and time series data of the active power of the power flow, and the time series data of the solar radiation intensity and the The covariance of the power flow with the time series data of the active power is calculated as the first covariance.

  For example, the time series data of the solar radiation intensity measured by the solar radiation meter 200 installed at a predetermined point is stored in the estimation data 141 of the storage unit 140, and the first covariance acquisition unit 110 refers to the estimation data 141. By doing so, time series data of the solar radiation intensity in the first period is acquired. In addition, time series data of active power (effective power of power flow) measured by the measuring instrument 300 is stored in the estimation data 141 of the storage unit 140, and the first covariance acquisition unit 110 estimates By referring to the use data 141, the time series data of the active power of the power flow in the first period is acquired. Then, the first covariance acquisition unit 110 calculates the first covariance that is the covariance between the acquired time series data of the solar radiation intensity and the time series data of the active power of the power flow.

  Here, the said 1st period is a period corresponded to said short time, for example, as mentioned above, 30 minutes in the period in about 1 to 2 weeks retroactively from the predetermined time point which estimates a photovoltaic power generation output. It is about 2 hours. Moreover, it is preferable that the said 1st period is a period when the said solar radiation intensity is strong and the fluctuation | variation of the said solar radiation intensity is large. In general, since the load tends to temporarily decrease from 12:00 to 13:00, the first period is more preferably a period excluding 12:00 to 13:00. As described above, the first covariance acquisition unit 110 calculates the first covariance using the period in which the solar radiation intensity is strong and the fluctuation of the solar radiation intensity is large as the first period.

  Then, the first covariance acquisition unit 110 stores the calculated first covariance by writing it in the estimation data 141 of the storage unit 140.

  The second covariance acquisition unit 120 acquires a second covariance that is self-covariance of time series data of two solar radiation intensities that are shifted in delay time. Specifically, the second covariance acquisition unit 120 includes the time series data of the solar radiation intensity in the first period and the time series data of the solar radiation intensity in the second period which is a period shifted from the first period by a delay time. And the autocovariance of the time series data of the two solar radiation intensities is calculated as the second covariance.

  For example, the time series data of the solar radiation intensity measured by the pyranometer 200 installed at a predetermined point is stored in the estimation data 141 of the storage unit 140, and the second covariance acquisition unit 120 refers to the estimation data 141. By doing so, the time series data of the solar radiation intensity in the first period and the second period are acquired. Then, the second covariance acquisition unit 120 calculates a second covariance that is self-covariance of the acquired time series data of the two solar radiation intensities. When the delay time is zero, the first period and the second period are the same period, so the second covariance acquisition unit 120 determines the variance of the time series data of the solar radiation intensity in the first period. Calculated as bicovariance.

  Here, the delay time is the time during which the solar radiation intensity moves between the solar radiation intensity measurement point (installation point of the solar radiation meter 200) and the solar power generation facility 420, specifically, the solar radiation intensity. This is a period until the cloud existing at the measurement point reaches the installation point of the photovoltaic power generation equipment 420. For example, the second covariance acquisition unit 120 can calculate, as the delay time, a lag when the covariance function of the time series data of the solar radiation intensity and the active power of the power flow takes a minimum value. Note that the second covariance acquisition unit 120 can also acquire the delay time by referring to weather data or the like.

  As described above, the second covariance acquisition unit 120 acquires the second covariance using the time during which the solar radiation intensity moves between the solar radiation intensity measurement point and the installation point of the solar power generation facility 420 as the delay time. . At this time, the second covariance acquisition unit 120 acquires, as the delay time, a lag when the covariance function of the time series data of the solar radiation intensity and the active power of the power flow in the predetermined period takes a minimum value. Can do. Here, the predetermined period is preferably the same period as the first period.

  Then, the second covariance acquisition unit 120 stores the calculated second covariance by writing it in the estimation data 141 of the storage unit 140.

  Then, the power generation output estimation unit 130 reads out the first covariance and the second covariance acquired by the first covariance acquisition unit 110 and the second covariance acquisition unit 120 from the estimation data 141, Estimate power generation output. Specifically, the power generation output estimation unit 130 uses the first covariance and the second covariance as a coefficient of solar radiation intensity at a predetermined point at a time point that is shifted from the predetermined time point. The solar power output is calculated by multiplying the solar radiation intensity.

  Here, the coefficient is a value obtained by dividing the first covariance by the second covariance and multiplying by minus. That is, the power generation output estimation unit 130 calculates the solar power generation output by using a value obtained by dividing the first covariance by the second covariance and multiplying by the coefficient. Although the coefficient is unlikely to change in a short period, the delay time is likely to change in a short period due to changes in wind direction and wind speed. It is preferable to use the one changed in real time in consideration of the above.

  Then, the power generation output estimation unit 130 stores the calculated solar power generation output by writing it in the estimation data 141 of the storage unit 140.

  Next, the process in which the photovoltaic power generation output estimation apparatus 100 estimates the photovoltaic power generation output will be described.

  FIG. 3 is a flowchart showing an example of a process (solar power generation output estimation method) in which the solar power generation output estimation apparatus 100 according to the embodiment of the present invention estimates the solar power generation output.

  As shown in the figure, first, the first covariance acquisition unit 110 acquires the first covariance that is the covariance of time-series data between the solar radiation intensity at a predetermined point and the effective power of the power flow (S102). . Specifically, the first covariance acquisition unit 110 acquires the first covariance acquired by calculating the first covariance, and writes the acquired (calculated) first covariance in the estimation data 141 of the storage unit 140. A detailed description of the process in which the first covariance acquisition unit 110 acquires the first covariance will be described later.

  And the 2nd covariance acquisition part 120 acquires the 2nd covariance which is the autocovariance of the time series data of two solar radiation intensity which shifted | deviated the delay time (S104). Specifically, the second covariance acquisition unit 120 acquires the second covariance acquired by calculating the second covariance and writes the acquired (calculated) second covariance in the estimation data 141 of the storage unit 140. The detailed description of the process in which the second covariance acquisition unit 120 acquires the second covariance will be described later.

  Then, the power generation output estimation unit 130 is a period before the predetermined time point, and the solar radiation intensity and power flow at a predetermined point in a period in which the solar south-middle altitude is within a predetermined range from the south-middle altitude at the predetermined time point. A photovoltaic power generation output is estimated using active power (S106). Specifically, the power generation output estimation unit 130 reads the first covariance acquired by the first covariance acquisition unit 110 and the second covariance acquired by the second covariance acquisition unit 120 from the estimation data 141. The solar power generation output is estimated by using the first covariance and the second covariance. The detailed description of the process in which the power generation output estimation unit 130 estimates the solar power generation output will be described later.

  As described above, the processing (solar power generation output estimation method) in which the solar power generation output estimation device 100 estimates the solar power generation output ends.

  Next, the process in which the first covariance acquisition unit 110 acquires the first covariance (S102 in FIG. 3) will be described in detail.

  FIG. 4 is a flowchart showing an example of processing in which the first covariance acquisition unit 110 according to the embodiment of the present invention acquires the first covariance.

  As shown in the figure, first, the first covariance acquisition unit 110 acquires time series data of solar radiation intensity (S202). Specifically, the time series data of the solar radiation intensity measured by the pyranometer 200 installed at a predetermined point is stored in the estimation data 141 of the storage unit 140, and the first covariance acquisition unit 110 performs the estimation data From 141, it acquires by reading the time series data of the said solar radiation intensity.

  Note that the first covariance acquisition unit 110 may acquire an estimated value of time series data of solar radiation intensity instead of an actual measurement value of time series data of solar radiation intensity. In this case, the first covariance acquisition unit 110, for example, when the pyranometer 200 is a pyranometer group composed of a plurality of pyranometers, information on any one of the plural pyranometers (past and present). The estimated value can be acquired by estimating the surrounding solar radiation intensity using the solar radiation intensity value). Note that, from the viewpoint of improving estimation accuracy, the first covariance acquisition unit 110 preferably acquires the estimated value in consideration of the distribution form of the photovoltaic power generation equipment 420.

  More specifically, the first covariance acquisition unit 110 is a period before a predetermined time point for estimating the solar power generation output, and the solar south-middle altitude is within a predetermined range from the south-middle altitude at the predetermined time point. It is a period, and the time series data of the solar radiation intensity in the period within the predetermined range from the total installed capacity of the photovoltaic power generation equipment 420 at the predetermined time point is acquired.

  Here, as a period in which the southern middle altitude of the sun is within a predetermined range from the southern middle altitude at a predetermined time, for example, the southern middle altitude is within ± about 6 ° from the south middle altitude at the predetermined time (or ± Within about 12%), and more preferably within about ± 3 ° (or within about ± 6%).

  In this case, as shown in FIG. 5, the difference between the altitudes in the south and the middle on a day two weeks away changes between −about 6 ° and + about 6 ° (between −about 12% and + about 12%). The difference in altitude between the south and the middle on a day one week away is between -about 3 ° and + about 3 ° (between -about 6% and + about 6%). For this reason, as the said period, the period from a predetermined time to two weeks ago is preferable, and the period from a predetermined time to one week ago is further more preferable. FIG. 5 is a graph showing the transition of the south-middle altitude over the course of one year and the transition of the difference between the south-middle altitudes for one week and two weeks away.

  Note that the difference between the south and middle altitudes tends to be small in summer and winter and large in spring and autumn. Therefore, different periods may be used as the above period. In addition, since the difference between the south and middle altitudes varies depending on the observation point of the south and middle altitudes, the period corresponding to the observation point may be used.

  In addition, for a period in which the total installed capacity of the photovoltaic power generation equipment 420 is within a predetermined range from the total installed capacity at a predetermined time, for example, the total installed capacity is within ± 5% from the total installed capacity at the predetermined time Etc., as appropriate.

  Note that the above period may be determined in advance and may be input in advance to the first covariance acquisition unit 110 or may be changed as appropriate by the user, or the first covariance acquisition unit 110 may calculate the period. It may be determined as follows. In this Embodiment, the 1st covariance acquisition part 110 makes the said period the day before the day which estimates photovoltaic power generation output, for example, and acquires the time series data of the solar radiation intensity in the said day.

  Returning to FIG. 4, the first covariance acquisition unit 110 searches for the first period (S204). Specifically, the first covariance acquisition unit 110 refers to the acquired time series data of the solar radiation intensity and searches for a period in which the solar radiation intensity is strong and the fluctuation of the solar radiation intensity is large. For example, the first covariance acquisition unit 110 searches for a short period of about 30 minutes to 2 hours, in which the solar radiation intensity is strong and the fluctuation of the solar radiation intensity is large, on the day before the day on which the solar power generation output is estimated. Then, the first covariance acquisition unit 110 determines the searched period as the first period. Note that the first covariance acquisition unit 110 preferably searches for the first period from a period excluding 12:00 to 13:00.

  Note that the first covariance acquisition unit 110 does not search for the first period from the above period (for example, the day before the day when the solar power generation output is estimated), but searches for the above period itself. Therefore, the first period may be searched from the period.

  And the 1st covariance acquisition part 110 acquires the time series data of the solar radiation intensity in the said 1st period, and the time series data of the active power of an electric power flow (S206). Specifically, the first covariance acquisition unit 110 reads the time series data of the solar radiation intensity in the first period and the time series data of the active power of the power flow in the first period from the estimation data 141. By that, get.

  Then, the first covariance acquisition unit 110 calculates the covariance between the time series data of the solar radiation intensity and the time series data of the active power of the power flow as the first covariance (S208). Then, the first covariance acquisition unit 110 writes the calculated first covariance in the estimation data 141.

  As described above, the process in which the first covariance acquisition unit 110 acquires the first covariance (S102 in FIG. 3) ends.

  Next, the process in which the second covariance acquisition unit 120 acquires the second covariance (S104 in FIG. 3) will be described in detail.

  FIG. 6 is a flowchart illustrating an example of processing in which the second covariance acquisition unit 120 according to the embodiment of the present invention acquires the second covariance.

  As shown in the figure, first, the second covariance acquisition unit 120 acquires a delay time between the solar radiation intensity measurement point and the installation point of the solar power generation equipment 420 (S302). Since a plurality of photovoltaic power generation facilities 420 are connected to the power system 400, there are a plurality of installation points of the photovoltaic power generation facilities 420. The installation point is a point that becomes the center position of the plurality of photovoltaic power generation facilities 420.

  Specifically, the second covariance acquisition unit 120 determines the lag when the covariance function of the time series data of the solar radiation intensity and the active power of the power flow in the first period has a minimum value as the delay time. Get as. Then, the second covariance acquisition unit 120 writes the acquired delay time in the estimation data 141. A specific description of the process in which the second covariance acquisition unit 120 acquires the delay time will be described later.

  Then, the second covariance acquisition unit 120 acquires time series data of two solar radiation intensities that are shifted in delay time (S304). That is, the second covariance acquisition unit 120 acquires the time series data of the solar radiation intensity in the first period and the time series data of the solar radiation intensity in the second period that is delayed from the first period. Specifically, the second covariance acquisition unit 120 reads time series data of the solar radiation intensity in the first period and the second period from the estimation data 141.

  Then, the second covariance acquisition unit 120 calculates the second covariance that is the self-covariance of the time series data of the two solar radiation intensities that are delayed in time (S306). Specifically, the second covariance acquisition unit 120 calculates self-covariance between the time series data of the solar radiation intensity in the first period and the time series data of the solar radiation intensity in the second period. Then, the second covariance acquisition unit 120 writes the calculated second covariance in the estimation data 141.

  As described above, the process in which the second covariance acquisition unit 120 acquires the second covariance (S104 in FIG. 3) ends.

  Next, the process (S106 in FIG. 3) in which the power generation output estimation unit 130 estimates the solar power generation output will be described in detail.

  FIG. 7 is a flowchart illustrating an example of processing in which the power generation output estimation unit 130 according to the embodiment of the present invention estimates the solar power generation output.

  As shown in the figure, first, the power generation output estimation unit 130 acquires the first covariance, the second covariance, and the delay time (S402). Specifically, the power generation output estimation unit 130 reads the first covariance, the second covariance, and the delay time from the estimation data 141.

  Then, the power generation output estimation unit 130 calculates a coefficient using the first covariance and the second covariance (S404). Specifically, the power generation output estimation unit 130 calculates the coefficient by dividing the first covariance by the second covariance and multiplying by the minus.

  Then, the power generation output estimation unit 130 calculates the solar power generation output by multiplying the calculated coefficient by the solar radiation intensity at the predetermined point and the solar radiation intensity at the time when the delay time is shifted from the predetermined time (S406). ). In addition, as above-mentioned, it is preferable to use what was changed in real time as delay time at the time of calculating this solar power generation output. For this reason, it is preferable that the power generation output estimation unit 130 calculates the solar power generation output using the delay time changed in real time in consideration of weather data and the like. Then, the power generation output estimation unit 130 writes the calculated solar power generation output in the estimation data 141.

  As described above, the process in which the power generation output estimation unit 130 estimates the solar power generation output (S106 in FIG. 3) ends.

  Here, the method by which the power generation output estimation unit 130 calculates the solar power generation output will be specifically described below.

First, the active power of the power flow (apparent load) of the power system 400 is P (t), the total value (actual load) of the load 410 connected to the power system 400 is P _L (t), solar power generation Assuming that the total value of the power generation output of the facility 420 is P _PV (t) and the solar radiation intensity at a predetermined point is SR (t), the following formula 1 holds, and P _PV (t ) Can be assumed.

Here, w is a coefficient (coefficient for converting the solar radiation intensity into the power generation output of the photovoltaic power generation equipment 420), ε (t) is fluctuation (noise), and τ _s is a delay time (installation point of the solar radiation meter 200). And the time when the solar radiation fluctuation moves between the installation point of the solar power generation equipment 420).

  From the above formula 1, the following formula 2 can be derived.

  For this reason, the covariance between SR (t) and P (t) can be calculated as in Equation 3 below.

Here, when t is a short time of about 30 minutes to 2 hours, it can be assumed that P _L (t), SR (t), and ε (t) have no correlation. The coefficient w can be obtained by transforming Expression 3 into Expression 4 below.

That is, Cov [SR (t), P (t)], which is a covariance between the solar radiation intensity SR (t) and the effective power P (t) of the power flow, is the first covariance and is shifted by the delay time τ _s . Cov [SR (t), SR (t−τ _s )], which is an autocovariance between two solar radiation intensities SR (t) and SR (t−τ _s ), is the second covariance. The coefficient w is obtained by dividing the first covariance Cov [SR (t), P (t)] by the second covariance Cov [SR (t), SR (t−τ _s )] and multiplying by the minus. Is.

  If it is assumed that ε (t) is very small and can be ignored, the following approximate expression of Expression 6 can be obtained from Expression 1 above.

As described above, the power generation output estimation unit 130 divides the first covariance by the second covariance and multiplies the minus by the solar radiation at the time when the delay time τ _s deviates from the predetermined time t. By multiplying the strength SR (t−τ _s ), the photovoltaic power generation output P _PV (t) can be calculated.

In calculating the coefficient w, when t is a short time, it is assumed that there is no correlation between the load P _L (t) and the solar radiation intensity SR (t). This will be described with reference to FIG. 9C. 8 to 9C are diagrams for explaining that there is no correlation between the load P _L (t) and the solar radiation intensity SR (t).

Here, (a) of FIG. 8 shows the time of load P _L (t) and solar radiation intensity SR (t) in a short period of winter weekdays (in the figure, one hour from 10:00 am to 11:00 am). It is a graph which shows series data. FIG. 8B shows the load P _L (t) and the solar radiation intensity SR (t calculated using the load P _L (t) and the solar radiation intensity SR (t) in FIG. It is a graph which shows a cross correlation coefficient with). In addition, the solar radiation intensity SR (t) is a value obtained by multiplying the actually measured solar radiation intensity by 7 times for adjusting the scale. The same applies to the following figures (FIGS. 12A and 15A).

FIG. 9A shows the load P _L (t) calculated in the same manner as in FIG. 8B, for a short period of winter Saturdays and Sundays (in the figure, 1 hour from 11:00 am to 12:00 am). It is a graph which shows a cross correlation function with solar radiation intensity SR (t). FIG. 9B is a graph showing a cross-correlation function between the load P _L (t) and the solar radiation intensity SR (t) in a short period of spring and weekend (in the figure, 1 hour from 11:00 am to 12:00 am). is there. FIG. 9C is a graph showing a cross-correlation function between the load P _L (t) and the solar radiation intensity SR (t) for a short period of spring weekdays (in the figure, one hour from 10:00 am to 11:00 am). is there.

As shown in these figures, the cross-correlation coefficient between the load P _L (t) and the solar radiation intensity SR (t) is very small during a short period of weekdays and weekends in winter and spring, and the load P _L (t) It can be said that the solar radiation intensity SR (t) has no correlation. Further, it is presumed that similar results can be obtained in other seasons (summer, autumn), and when t is short, there is no correlation between the load P _L (t) and the solar radiation intensity SR (t). It was shown that.

FIG. 8 uses data of an actual system measured in a verification test in FIGS. 12A to 14B described later. That is, the solar radiation intensity SR (t) in FIG. 8 is obtained from the solar radiation intensity SR1 in FIG. 12A, and the load P _L (t) is the power flow P1 in FIG. 12A and the photovoltaic power generation in FIG. 13A. This is obtained by adding the true value of the power generation output of the facility 420. Similarly, FIG. 9A shows actual system data measured in the verification test in FIGS. 15A to 17B described later, and FIG. 9B shows actual system data measured in the verification tests in FIGS. 18A to 19B described later. FIG. 9C uses data of an actual system measured in a verification test in FIGS. 20A to 21B described later.

  Next, the process in which the second covariance acquisition unit 120 acquires the delay time (S302 in FIG. 6) will be specifically described.

  First, when the covariance function C (τ), which is a function of the lag τ, is calculated in the same manner as the above expressions 1 to 4, the following expression 6 is obtained. Note that the covariance function C (τ) is obtained by calculating the solar radiation intensity SR (t) defined by C (τ) = Cov [SR (t), P (t + τ)] and the effective power P (t) of the power flow. Covariance function.

Here, Cov [SR (t), SR (t + τ−τ _s )] in the above equation 6 takes a maximum value when τ = τ _s . For this reason, the lag when C (τ), which is the covariance function of the time series data of the solar radiation intensity and the active power of the power flow, takes the minimum value (the maximum value of the absolute value on the minus side) is the delay time τ _s. It is.

  As described above, the second covariance acquisition unit 120 uses, as the delay time, the lag when the covariance function of the time series data of the solar radiation intensity and the active power of the power flow in the first period takes the minimum value. get. The delay time can be considered as follows. FIG. 10 is a diagram illustrating a process in which the second covariance acquisition unit 120 according to the embodiment of the present invention acquires a delay time.

As shown in the figure, the second covariance acquisition unit 120 is, for example, time series data at a solar radiation intensity measurement point as shown in (a) of the figure and as shown in (b) of the figure. When the solar radiation intensity time series data at the installation point of the solar power generation equipment 420 is acquired, the covariance function of the two solar radiation intensity time series data as shown in FIG. be able to. In this case, the second covariance acquisition unit 120 acquires a lag (τ _s seconds in the figure) when the maximum value is obtained in the covariance function as shown in FIG. be able to. That is, (c) in the figure shows a time when the solar radiation intensity is as shown in (b) of the figure, delayed by τ _s seconds from the time series data of the solar radiation intensity as shown in (a) of the figure. Indicates that the series data is being transmitted.

  Next, the result of having verified the effect which the solar power generation output estimation apparatus 100 show | plays is demonstrated below.

  FIG. 11 is a diagram showing a configuration when describing the effect produced by the photovoltaic power generation output estimating apparatus 100 according to the embodiment of the present invention. Moreover, FIG. 12A-FIG. 21B are figures which show the verification result at the time of explaining the effect which the solar power generation output estimation apparatus 100 which concerns on embodiment of this invention show | plays.

  As shown in FIG. 11, a plurality of loads 410 are connected to the power system 400 and one large-scale (about 10 MW) solar power generation facility 420 is connected to the power system 400. In addition, a measuring instrument 421 that measures the power generation output of the solar power generation facility 420 is disposed near the solar power generation facility 420. Note that the measuring instrument 421 is provided to determine the likelihood of the estimation result of the power generation output of the photovoltaic power generation equipment 420, and a PQVF recording device or the like is used as in the measuring instrument 300.

  In the equipment configured as described above, as shown in FIG. 12A, time series data SR1 of the solar radiation intensity is measured from the pyranometer 200, and time series data P1 of the active power of the power flow of the power system 400 is obtained from the measuring instrument 300. It was measured. FIG. 12A is a graph showing time-series data of solar radiation intensity and power flow on a weekday in winter. In the figure, the measurement period of solar radiation intensity and power flow is 1 second.

  Then, as a result of calculating the covariance function between the solar radiation intensity time series data SR1 and the power flow time series data P1 shown in FIG. 12A, a graph as shown in FIG. 12B was obtained. FIG. 12B is a graph showing a covariance function between solar radiation intensity and power flow on a weekday in winter.

The covariance function is obtained by using the time series data SR1 of the solar radiation intensity from 10:00 am to 11:00 am in FIG. 12A and the time series data P1 of the power flow. _s = -6 was obtained.

Then, the first covariance and the second covariance are calculated from the time series data SR1 of the solar radiation intensity from 10:00 am to 11:00 am in FIG. 12A, the time series data P1 of the power flow, and the delay time τ _s. . Thus, the first covariance and the second covariance are calculated using the delay time in the same time zone (first period: 10:00 am to 11:00 am) as in the case of calculating the delay time. That is, the first covariance is a part of the covariance function. Then, the coefficient w = 9044.525911 was calculated from the first covariance and the second covariance.

And the electric power generation output of the solar power generation equipment 420 was estimated using the coefficient w and the time series data of the solar radiation intensity which considered the delay time (tau) _s . This estimation result (estimated value) and the power generation output (true value) of the photovoltaic power generation equipment 420 measured by the measuring instrument 421 are shown in FIGS. 13A and 13B. FIG. 13A is a graph showing an estimated value and a true value of the power generation output of the solar power generation equipment 420 on the day when solar radiation intensity and power flow are measured on a weekday in winter. FIG. 13B is a graph showing an estimated value and a true value of the power generation output of the photovoltaic power generation equipment 420 on the next day when the solar radiation intensity and the power flow are measured on a weekday in winter.

Note that, in both FIG. 13A (the day of measurement) and FIG. 13B (the day after measurement), the photovoltaic power generation equipment 420 is obtained using the coefficient w (= 9044.525911) and the delay time τ _s (= −6). The power generation output was estimated.

  And about FIG. 13A (the day of measurement) and FIG. 13B (the day after measurement), the histogram of the error from the true value of the estimated value of the power generation output of the photovoltaic power generation equipment 420 was created. FIG. 14A is a histogram showing an error from the true value of the estimated value of the power generation output of the photovoltaic power generation facility 420 on the day when the solar radiation intensity and the power flow are measured on a weekday in winter. FIG. 14B is a histogram showing an error from the true value of the estimated value of the power generation output of the photovoltaic power generation equipment 420 on the next day when the solar radiation intensity and power flow are measured on a weekday in winter.

  As shown in FIG. 14A and FIG. 14B, on winter weekdays, most of the power generation output of the solar power generation equipment 420 is approximately plus or minus 10% (about 10% of the rated output (about 10 MW) of the solar power generation equipment 420. 1 MW) or less, most of which can be estimated with an error of Pla minus 5% (about 0.5 MW) or less.

  Similarly, on winter Saturdays and Sundays, as shown in FIGS. 15A to 17B, most of the power generation output of the solar power generation facility 420 is increased with respect to the rated output (about 10 MW) of the solar power generation facility 420. It is possible to estimate with an error of minus 10% (about 1 MW) or less, and most of them can be estimated with an error of plus or minus 5% (about 0.5 MW).

  FIG. 15A is a graph showing time-series data of solar radiation intensity and power flow on a winter Saturday and Sunday. FIG. 15B is a graph showing a covariance function between solar radiation intensity and electric power flow on a winter Saturday and Sunday.

The covariance function is obtained by using the time series data SR2 of the solar radiation intensity from 11:00 am to 12:00 am and the time series data P2 of the power flow in FIG. _s = −17 and coefficient w = 9028.524401 were obtained. Here, the coefficient w is the time series data SR2 of the solar radiation intensity and the time series data of the power flow from 11:00 am to 12:00 am in FIG. This is a coefficient calculated from P2 and the delay time τ _s .

  Moreover, FIG. 16A is a graph which shows the estimated value and true value of the power generation output of the solar power generation equipment 420 of the day which measured the solar radiation intensity | strength and electric power flow on the weekend of winter. Moreover, FIG. 16B is a graph which shows the estimated value and true value of the power generation output of the photovoltaic power generation equipment 420 of the next day which measured the solar radiation intensity and the power flow on the winter Saturday and Sunday.

  FIG. 17A is a histogram showing an error from the true value of the estimated value of the power generation output of the solar power generation equipment 420 on the day when the solar radiation intensity and the power flow are measured on a winter Saturday and Sunday. FIG. 17B is a histogram showing an error from the true value of the estimated value of the power generation output of the photovoltaic power generation equipment 420 on the next day when the solar radiation intensity and the power flow are measured on a winter Saturday and Sunday.

  Similarly, on spring Saturdays and Sundays, as shown in FIGS. 18A to 19B, most of the power generation output of the solar power generation facility 420 is reduced to the rated output (about 10 MW) of the solar power generation facility 420. It can be estimated with an error of 10% (about 1 MW) or less, and most of them can be estimated with an error of Pla minus 5% (about 0.5 MW) or less.

  Here, FIG. 18A is a graph showing an estimated value and a true value of the power generation output of the solar power generation equipment 420 on the day when the solar radiation intensity and the power flow are measured on a spring Saturday and Sunday. FIG. 18B is a graph showing an estimated value and a true value of the power generation output of the solar power generation equipment 420 on the next day when the solar radiation intensity and the power flow are measured on a spring Saturday and Sunday.

The delay time τ _s is obtained using time series data of solar radiation intensity from 11:00 am to 12:00 am and time series data of power flow, and is calculated as τ _s = −2. The coefficient w is obtained using time series data of solar radiation intensity from 11:00 am to 12:00 in the same time zone (first period) as in the case of calculating the delay time and time series data of power flow. It was calculated and it was calculated as w = 7183.7720341.

  FIG. 19A is a histogram showing an error from the true value of the estimated value of the power generation output of the solar power generation equipment 420 on the day when the solar radiation intensity and the power flow are measured on the weekends of spring. FIG. 19B is a histogram showing an error from the true value of the estimated value of the power generation output of the photovoltaic power generation equipment 420 on the next day when the solar radiation intensity and the power flow are measured on a spring Saturday and Sunday.

  Similarly, on spring weekdays, as shown in FIGS. 20A to 21B, most of the power generation output of the solar power generation equipment 420 is reduced to the rated output (about 10 MW) of the solar power generation equipment 420. It can be estimated with an error of 10% (about 1 MW) or less, and most of them can be estimated with an error of Pla minus 5% (about 0.5 MW) or less.

  Here, FIG. 20A is a graph showing an estimated value and a true value of the power generation output of the solar power generation equipment 420 on the day when the solar radiation intensity and the power flow are measured on a spring weekday. FIG. 20B is a graph showing an estimated value and a true value of the power generation output of the photovoltaic power generation equipment 420 on the next day when the solar radiation intensity and the power flow are measured on a spring weekday.

The delay time τ _s is obtained using time series data of solar radiation intensity from 10:00 am to 11:00 am and time series data of power flow, and is calculated as τ _s = 14. The coefficient w is obtained using time series data of solar radiation intensity from 10:00 am to 11:00 am and time series data of power flow, which are the same time zone (first period) as in the calculation of the delay time. And was calculated to be w = 6945.5529665.

  FIG. 21A is a histogram showing an error from the true value of the estimated value of the power generation output of the solar power generation equipment 420 on the day when the solar radiation intensity and the power flow are measured on a spring weekday. FIG. 21B is a histogram showing an error from the true value of the estimated value of the power generation output of the photovoltaic power generation equipment 420 on the next day when the solar radiation intensity and the power flow are measured on a spring weekday.

  It can also be inferred that similar results can be obtained in other seasons (summer, autumn). For this reason, it turns out that the solar power generation output estimation apparatus 100 can estimate the power generation output of the solar power generation equipment 420 with high accuracy.

  As described above, according to the photovoltaic power generation output estimating apparatus 100 according to the embodiment of the present invention, it is a period before a predetermined time point, and a predetermined point in a period in which the solar south-middle altitude is within a predetermined range. The solar power generation output is estimated using the solar radiation intensity and the active power of the power system 400. In other words, for example, by using data in a period in which the solar south-middle altitude is about 1 to 2 weeks before a predetermined time, the solar power output can be estimated more accurately, and the solar radiation intensity and power system By using 400 active power, the photovoltaic power output can be easily estimated. Here, the estimated solar power generation output is the power generation output at a predetermined time of the solar power generation facility 420 that supplies power to the load 410 connected to the power system 400, that is, the solar power generation connected to the power system 400. This is the power generation output of the entire facility 420. For this reason, according to the solar power generation output estimation apparatus 100, since the power generation output of the whole solar power generation equipment 420 connected to the electric power system 400 can be estimated accurately and simply, the apparatus is provided to each consumer. The power generation output of the photovoltaic power generation facility 420 can be estimated without installation.

  Moreover, the photovoltaic power generation output estimation apparatus 100 estimates the photovoltaic power generation output using time series data of the solar radiation intensity and the active power of the power system 400 in a short time. That is, for example, the photovoltaic power generation output can be estimated using data in a short period of about 30 minutes to 2 hours. For this reason, according to the solar power generation output estimation apparatus 100, since it is not necessary to acquire long-time time series data, the power generation output of the solar power generation equipment 420 can be estimated easily and quickly.

  Moreover, the photovoltaic power generation output estimation device 100 uses the solar radiation intensity and the effective power of the power system 400 during a period in which the total installed capacity of the photovoltaic power generation equipment 420 linked to the power system 400 is within a predetermined range, Estimate solar power output. That is, the photovoltaic power generation output estimation apparatus 100 can estimate the power generation output of the photovoltaic power generation equipment 420 more accurately by using data in a period in which the total installed capacity of the photovoltaic power generation equipment 420 is equivalent.

  Moreover, the photovoltaic power generation output estimation apparatus 100 is the self-distribution of the time-series data of the first covariance that is the covariance of the time-series data between the solar radiation intensity and the active power of the power system 400, and the two solar radiation intensity time-series data that are shifted in delay time. The solar power output is estimated using the second covariance that is the covariance. For this reason, the solar power generation output estimation apparatus 100 can easily estimate the power generation output of the solar power generation facility 420 using the first covariance and the second covariance.

  Moreover, the photovoltaic power generation output estimation apparatus 100 can calculate the photovoltaic power generation output by multiplying the coefficient w obtained using the first covariance and the second covariance by the solar radiation intensity at a predetermined point. Therefore, the power generation output of the photovoltaic power generation facility 420 can be estimated by simple calculation.

  Moreover, since the photovoltaic power generation output estimation apparatus 100 can calculate the photovoltaic power generation output using the above-described coefficient w as a value obtained by dividing the first covariance by the second covariance and multiplying by minus, it is further simplified. It is possible to estimate the power generation output of the photovoltaic power generation facility 420 with a simple calculation.

  Moreover, the solar power generation output estimation apparatus 100 calculates the second covariance by using the time during which the solar radiation intensity moves between the solar radiation intensity measurement point and the installation point of the solar power generation facility 420 as a delay time. The power generation output of the photovoltaic power generation facility 420 can be estimated.

  Moreover, the photovoltaic power generation output estimation apparatus 100 calculates the second covariance by using the lag when the covariance function of the time series data of the solar radiation intensity and the active power of the power system 400 takes the minimum value as the delay time. The second covariance can be easily obtained.

  Moreover, the solar power generation output estimation apparatus 100 calculates the covariance between the time series data of the solar radiation intensity in the first period and the time series data of the active power of the power system 400 as the first covariance, and the solar radiation in the first period. The self-covariance between the time series data of the intensity and the time series data of the solar radiation intensity in the second period shifted from the first period is calculated as the second covariance. And the solar power generation output estimation apparatus 100 multiplies the coefficient w obtained using the calculated first covariance and the second covariance by the solar radiation intensity at the time when the delay time is deviated from the predetermined time. Calculate the power generation output. Thereby, the solar power generation output estimation apparatus 100 can estimate the power generation output of the solar power generation facility 420.

  Moreover, the solar power generation output estimation apparatus 100 calculates the first covariance and the second covariance with a period in which the solar radiation intensity is strong and the fluctuation of the solar radiation intensity is large as the first period. That is, the photovoltaic power generation output estimation apparatus 100 calculates the first covariance and the second covariance by setting the period in which the characteristics of the period for estimating the photovoltaic power generation output are prominent as the first period. The power generation output of the solar power generation facility 420 can be accurately estimated.

  In addition, the present invention can be realized not only as such a photovoltaic power generation output estimation device 100, but also with the photovoltaic power generation output estimation device 100, a solarimeter 200 that measures solar radiation intensity at a predetermined point, and power It can also be realized as a photovoltaic power generation output estimation system 10 including a measuring instrument 300 that measures the active power of the system 400.

  Further, the present invention can also be realized as a photovoltaic power generation output estimation method in which a characteristic process performed by a processing unit included in the photovoltaic power generation output estimation apparatus 100 is a step. In addition, it can be realized as a program or an integrated circuit that causes a computer to execute characteristic processing included in the photovoltaic power generation output estimation method. The computer-readable non-transitory recording medium in which the program is recorded, for example, a flexible disk, a hard disk, a CD-ROM, an MO, a DVD, a DVD-ROM, a DVD-RAM, a BD (Blu-ray (registered trademark) Disc), and can be realized as a semiconductor memory. 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.

  The solar power generation output estimation apparatus 100 and the solar power generation output estimation system 10 according to the embodiment of the present invention have been described above, but the present 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. In addition, embodiments constructed by combining components in different embodiments are also included in the scope of the present invention.

  For example, in the above embodiment, the power generation output estimation unit 130 estimates the solar power generation output using time series data of the solar radiation intensity in a short time such as one hour and the active power of the power system 400. However, it is not limited to using short time-series data. For example, the power generation output estimation unit 130 may use medium- to long-term time series data such as data for 10 hours, 1 day, 1 week, and 1 month.

  Moreover, in the said embodiment, the electric power generation output estimation part 130 is the data in the period in which the total installation capacity of the photovoltaic power generation equipment 420 linked to the electric power system 400 is in the predetermined range from the said total installation capacity in the predetermined time. It was decided to estimate the solar power output. However, the power generation output estimation unit 130 may estimate the solar power generation output without considering a period during which the total capacity of the solar power generation equipment 420 is within a predetermined range.

  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.

  The present invention can be applied to a photovoltaic power generation output estimation device or the like that can estimate the power generation output of a photovoltaic power generation facility without installing a device at each individual consumer.

DESCRIPTION OF SYMBOLS 10 Solar power generation output estimation system 100 Solar power generation output estimation apparatus 110 1st covariance acquisition part 120 2nd covariance acquisition part 130 Power generation output estimation part 140 Memory | storage part 141 Estimation data 200 Solar radiation meter 300 Measuring instrument 400 Electric power system 410 Load 420 Solar power generation equipment 421 Measuring instrument 500 Power generation equipment

Claims (13)

A photovoltaic power generation output estimation device that estimates a photovoltaic power generation output that is a power generation output at a predetermined time of a photovoltaic power generation facility that supplies power to a load connected to an electric power system,
Using the solar radiation intensity at a predetermined point and the active power of the electric power system in a period before the predetermined time, in which the solar south-middle altitude is within a predetermined range from the south-middle altitude at the predetermined time A photovoltaic power generation output estimation device comprising a power generation output estimation unit that estimates the photovoltaic power generation output. The solar power generation output is estimated using the time series data of the solar radiation intensity and the time series data of the active power in a short time within the period. Photovoltaic power output estimation device. The power generation output estimation unit includes the solar radiation intensity and the active power in a period in which a total facility capacity of the photovoltaic power generation facility linked to the power system is within a predetermined range from the total facility capacity at the predetermined time point. The solar power generation output estimation apparatus according to claim 1, wherein the solar power generation output is estimated using a power generator. further,
A first covariance acquisition unit that acquires a first covariance that is a covariance of time series data of the solar radiation intensity and the active power;
A second covariance acquisition unit that acquires a second covariance that is a self-covariance of two time-series data of the solar radiation intensity shifted in delay time,
The photovoltaic power generation according to any one of claims 1 to 3, wherein the power generation output estimation unit estimates the photovoltaic power generation output using the acquired first covariance and the second covariance. Output estimation device. The power generation output estimation unit calculates the solar power generation output by multiplying a coefficient obtained by using the first covariance and the second covariance by the solar radiation intensity at the predetermined point. The solar power generation output estimation apparatus of description. The solar power generation output according to claim 5, wherein the power generation output estimation unit calculates the solar power generation output using a value obtained by dividing the first covariance by the second covariance and multiplying the negative covariance by the coefficient. Estimating device. The second covariance acquisition unit acquires the second covariance using the time during which the solar radiation intensity moves between the solar radiation intensity measurement point and the installation point of the solar power generation facility as the delay time. The solar power generation output estimation apparatus of any one of 4-6. The first covariance acquisition unit acquires the first covariance which is a covariance of time series data of the solar radiation intensity and the active power in a predetermined period,
The second covariance acquisition unit acquires the second covariance using a lag when the covariance function of the time series data of the solar radiation intensity and the active power in the predetermined period takes a minimum value as the delay time. The photovoltaic power generation output estimation device according to claim 7. The first covariance acquisition unit acquires the time series data of the solar radiation intensity and the time series data of the active power in the first period, and the time series data of the solar radiation intensity and the time series data of the active power Calculating the covariance as the first covariance;
The second covariance acquisition unit acquires time series data of the solar radiation intensity in the first period and time series data of the solar radiation intensity in a second period that is a period shifted from the first period by the delay time. And calculating the self-covariance of the time series data of the two solar radiation intensities as the second covariance,
The power generation output estimation unit multiplies the solar radiation power generation by multiplying the coefficient obtained by using the first covariance and the second covariance by the solar radiation intensity at the time shifted from the predetermined time by the delay time. The photovoltaic power generation output estimation apparatus according to any one of claims 4 to 8, wherein an output is calculated. The period when the solar radiation intensity is strong and the fluctuation of the solar radiation intensity is large is the first period,
The first covariance acquisition unit calculates the first covariance,
The solar power generation output estimation device according to claim 9, wherein the second covariance acquisition unit calculates the second covariance. The photovoltaic power generation output estimation device according to any one of claims 1 to 10,
A pyranometer that measures the intensity of solar radiation at a given point;
A photovoltaic power generation output estimation system comprising: a measuring instrument that measures active power of a power system. A photovoltaic power generation output estimation method for estimating a photovoltaic power generation output that is a power generation output at a predetermined time of a photovoltaic power generation facility that supplies power to a load connected to an electric power system,
Using the solar radiation intensity at a predetermined point and the active power of the electric power system in a period before the predetermined time, in which the solar south-middle altitude is within a predetermined range from the south-middle altitude at the predetermined time A solar power generation output estimation method including a power generation output estimation step of estimating the solar power generation output.   The program for making a computer perform the step contained in the solar power generation output estimation method of Claim 12.

Images