JP2024060369A - Photovoltaic power generation output estimation device, grid control system, supply and demand control system, facility formation support system, photovoltaic power generation output estimation method, and photovoltaic power generation output estimation program - Google Patents

Abstract

[Problem] To provide a photovoltaic power output estimation device capable of improving the estimation accuracy of the power output of a photovoltaic power generation facility. [Solution] The device includes an estimation unit 150 that estimates the target photovoltaic power output, which is the power output of the photovoltaic power generation facility to be estimated, using solar irradiance data indicating solar irradiance and residual demand, which is the sum of the power consumption and the photovoltaic power output of the consumer where the photovoltaic power generation facility is installed, and an estimation accuracy verification unit 140 that determines whether the estimation accuracy of the target photovoltaic power output satisfies a set accuracy using correlation information indicating the correlation between the solar irradiance data and the residual demand. [Selected Figure] Figure 2

Description

This disclosure relates to a photovoltaic power generation output estimation device that estimates the power generation output of a photovoltaic power generation facility, a grid control system, a supply and demand control system, a facility formation support system, a photovoltaic power generation output estimation method, and a photovoltaic power generation output estimation program.

In recent years, the importance of expanding the use of renewable energy has been increasing, and an increasing number of consumers are installing distributed power sources such as solar power generation facilities and supplying electricity to the power transmission system or the power distribution system (hereinafter, these are referred to as the power system). On the other hand, while electric power companies that operate the power system are aware of the power output of some solar power generation facilities, they are unable to grasp the power output of many solar power generation facilities. For this reason, a device that estimates the power output of solar power generation facilities installed by each consumer has been proposed (see, for example, Patent Document 1). Note that the above-mentioned solar power generation facilities that can grasp the power output are solar power generation facilities that are subject to a contract under the full amount purchase system (hereinafter, also referred to as a full amount purchase contract), and the solar power generation facilities that cannot grasp the power output are solar power generation facilities that are subject to a contract under the surplus power purchase system (hereinafter, also referred to as a surplus purchase contract). This is because consumers who own solar power generation facilities that are subject to full purchase agreements are equipped with separate smart meters that measure the amount of electricity generated by the solar power generation facilities and the amount of electricity consumed by the load within the consumer's facility, whereas consumers who own solar power generation facilities that are subject to surplus purchase agreements are equipped with only a smart meter that measures the combined amount of electricity generated by the solar power generation facilities and the amount of electricity consumed by the load.

Patent Document 1 discloses a technology for estimating the power generation output of a solar power generation facility of a consumer (hereinafter also referred to as a surplus purchase consumer) who owns solar power generation equipment that is the subject of a surplus purchase contract. The solar power generation output estimation device described in Patent Document 1 estimates the power generation output of the surplus purchase consumer's power generation facility using the measurement value of a smart meter that measures the power consumption of the surplus purchase consumer's load and the measurement value of a smart meter that measures the power generation amount of the solar power generation facility that is the subject of a full purchase contract and is installed within a predetermined distance from the surplus purchase consumer's solar power generation facility.

JP 2020-191764 A

When a large number of solar power generation facilities are introduced in a situation where electric power companies and other parties are unable to grasp the power generation output of many solar power generation facilities, various problems arise in the operation of the power system. Although electric power companies and other parties can measure the power consumption of the apparent power system load (hereinafter referred to as the apparent load) that takes into account the power generation output of the solar power generation facilities at substations under their jurisdiction using meters, etc., they cannot accurately grasp the power consumption of the actual load (hereinafter referred to as the actual load) because the total power generation output of all solar power generation facilities connected to the power system is unknown. For this reason, when a large number of solar power generation facilities are introduced, there is an increased risk in supply and demand control, such as a large prediction error in the power consumption of the actual load, which is predicted using multiple regression analysis, etc., and an increased risk in system control, such as an impediment to recovery operations after a system accident.

For this reason, it is necessary to accurately estimate the power generation output of the solar power generation facility. However, according to the solar power generation output estimation device of Patent Document 1, the estimation is performed under the assumption that the power generation output of the solar power generation facility of the surplus purchase consumer being estimated is directly proportional to the power generation output of the solar power generation facility of the full purchase consumer. Therefore, under conditions where this assumption does not hold, there is a problem that the estimation error of the power generation output may become large.

The present disclosure has been made in consideration of the above, and aims to provide a photovoltaic power generation output estimation device that can improve the accuracy of estimating the power generation output of a photovoltaic power generation facility.

In order to solve the above-mentioned problems and achieve the objective, the photovoltaic power generation output estimation device according to the present disclosure includes an estimation unit that estimates the target photovoltaic power generation output, which is the power generation output of the photovoltaic power generation facility to be estimated, using solar irradiance data indicating solar irradiance and residual demand, which is the sum of the power consumption and the photovoltaic power generation output at the consumer where the photovoltaic power generation facility is installed, and an estimation accuracy verification unit that determines whether the estimation accuracy of the target photovoltaic power generation output satisfies a specified accuracy using correlation information indicating the correlation between the solar irradiance data and the residual demand.

The photovoltaic power generation output estimation device disclosed herein has the effect of improving the accuracy of estimating the power generation output of a photovoltaic power generation facility.

FIG. 1 is a diagram showing a configuration example of a power system control system according to a first embodiment; FIG. 1 is a block diagram showing an example of a functional configuration of a system control system according to a first embodiment. FIG. 1 is a diagram showing an example of the configuration of a computer system that realizes a photovoltaic power generation output estimation device according to a first embodiment. A flowchart showing an example of a procedure for estimating a power generation output by the photovoltaic power generation output estimating device according to the first embodiment. FIG. 1 is a diagram showing an example of a ratio for each combination of photovoltaic power generation facilities stored in a storage unit according to the first embodiment; A flowchart showing an example of a ratio calculation process according to the first embodiment. A flowchart showing an example of a process for estimating a photovoltaic power generation output of a second photovoltaic power generation facility according to the first embodiment. FIG. 1 is a diagram showing an example of a verification result of the power generation output estimation method according to the first embodiment. FIG. 13 is a diagram showing an example of a verification result of the power generation output estimation method according to the first embodiment when the estimation accuracy is not verified. FIG. 13 is a diagram showing an example of a scatter diagram of correlation coefficients and estimation errors of second photovoltaic power generation output. A flowchart showing an example of a procedure for estimating a power generation output by a photovoltaic power generation output estimating device according to a second embodiment. FIG. 13 is a diagram showing a configuration example of a system control system according to a third embodiment. A flowchart showing an example of a procedure for estimating a power generation output by a photovoltaic power generation output estimating device according to a third embodiment. A flowchart showing an example of a ratio calculation process according to the third embodiment. A flowchart showing an example of a process for estimating a photovoltaic power generation output of a second photovoltaic power generation facility according to a third embodiment. A flowchart showing an example of a procedure for estimating a power generation output by a photovoltaic power generation output estimating device according to a fourth embodiment.

The solar power generation output estimation device, grid control system, supply and demand control system, facility formation support system, solar power generation output estimation method, and solar power generation output estimation program according to the embodiments are described in detail below with reference to the drawings.

Embodiment 1.
Fig. 1 is a diagram showing a configuration example of a grid control system according to a first embodiment. A grid control system 10 of the present embodiment includes a photovoltaic power generation output estimation device 100, a control device 300, and smart meters (abbreviated as SM (Smart Meter) in the figure) 203-205, which are various measuring instruments installed under a plurality of consumers, and a measuring instrument 206. The photovoltaic power generation output estimation device 100, the smart meters 203-205, and the measuring instrument 206 are connected via a communication network 50. In Fig. 1, solid lines represent the flow of power, and dashed lines represent the flow of information.

1 illustrates a plurality of consumers, consumer 200-1, consumer 200-2, consumer 200-3, consumer 200-4, ..., consumer 200-m, ..., consumer 200-n. A load 201 and a photovoltaic power generation facility (abbreviated as PV (PhotoVoltaic) in the figure) 202 are connected to each of the consumers 200-1 to 200-n. In the example illustrated in FIG. 1, n is an integer of 6 or more, and m is an integer of 5 or more and less than n, but the values of n and m are not limited to the example illustrated in FIG. 1. In addition, the load 201 of each consumer 200-1 to 200-n indicates one or more facilities that consume power, and the specific facilities that constitute the load 201 do not have to be the same for all consumers 200-1 to 200-n. Similarly, the specific specifications of the photovoltaic power generation facility 202 do not have to be the same for all consumers 200-1 to 200-n.

The solar power generation facility 202 installed at consumer 200-1 is a solar power generation facility that is the subject of a full purchase contract. The solar power generation facilities 202 installed at consumers 200-2 to 200-n are solar power generation facilities that are the subject of surplus purchase contracts.

The photovoltaic power generation equipment 202 is, for example, photovoltaic power generation equipment installed on the roofs of buildings owned by the consumers 200-1 to 200-n, and includes not only small-scale photovoltaic power generation equipment but also large-scale photovoltaic power plants such as so-called mega solar power plants. The photovoltaic power generation equipment 202 is connected to the power system 20 that is connected to the higher-level system 30, and supplies the generated power to the power system 20. In addition, as shown in FIG. 1, the loads 201 of the consumers 200-1 to 200-n are connected to the power system 20. The loads 201 receive power from the power system 20 and consume the power. The power generated by the photovoltaic power generation equipment 202 may also be consumed by the loads 201 in the consumers 200-1 to 200-n that have the photovoltaic power generation equipment 202.

The consumers 200-1 to 200-n, which are provided with a load 201 and a solar power generation facility 202, receive power from the power grid 20 and supply power generated by the solar power generation facility 202 to the power grid 20. Therefore, the apparent power consumption of each consumer 200-1 to 200-n as viewed from the power grid 20 depends on both the actual power consumption of the load 201 and the power output of the solar power generation facility 202. If the power consumption of the load 201 is exceeded by the power output of the solar power generation facility 202, the power output of the consumer is supplied to the power grid 20 as viewed from the power grid 20, and the apparent power consumption is a negative value. Hereinafter, the apparent power consumption of each consumer 200-1 to 200-n as viewed from the power grid 20 is referred to as residual demand.

The smart meter 205 is installed in the consumer 200-2 to 200-n that has concluded a surplus purchase contract. Assuming that i is an arbitrary integer from 2 to n, the smart meter 205 of the consumer 200-i measures the sum of the power generation output P _PVi (t) of the photovoltaic power generation facility 202 of the consumer 200-i and the power consumption P _Li (t) by the load 201 when time is t. That is, the power measured by the smart meter 205 is the above-mentioned residual demand, and is the amount obtained by subtracting the power generation output of the photovoltaic power generation facility 202 from the power consumption of the load 201 for each of the consumers 200-2 to 200-n. The measurement data of the residual demand measured by the smart meter 205 is sent to the photovoltaic power generation output estimation device 100 via the communication network 25 and the communication network 50.

For example, in the consumer 200-2, the smart meter 205 measures and records the sum of the power generation output P _PV2 (t) of the photovoltaic power generation facility 202 and the power consumption P _L2 (t) by the load 201 as the residual demand. Then, the smart meter 205 transmits the measurement data of the residual demand of the consumer 200-2 to the photovoltaic power generation output estimation device 100 via the communication network 25 and the communication network 50. In this manner, the photovoltaic power generation output estimation device 100 acquires the measurement data of the residual demand, which is the measurement value of the smart meter 205 installed in the consumers 200-2 to 200-n that own the photovoltaic power generation facility 202 that is the subject of the surplus purchase contract. Hereinafter, the measurement value of the smart meter 205 is also referred to as the SM metered value.

The consumer 200-3 is also provided with a meter 206 that measures the power generation output P _PV3 (t) of the photovoltaic power generation facility 202 provided in the consumer 200-3. The meter 206 may be part of a device such as a power conditioner that controls the photovoltaic power generation facility 202, or may be a separately provided meter. The meter 206 transmits measurement data of the measured power generation output P _PV3 (t) to the photovoltaic power generation output estimation device 100 via the communication network 25 and the communication network 50. Note that, although an example in which the meter 206 is provided in the consumer 200-3 will be described here, the number of consumers provided with the meter 206 among the consumers 200-2 to 200-n may be zero or more.

The consumer 200-1 that has concluded a full purchase contract is equipped with a smart meter 203 and a smart meter 204. The smart meter 203 measures and records the power consumption P _L1 (t) of the load 201 of the consumer 200-1. The smart meter 204 measures and records the power generation output P _PV1 (t) of the photovoltaic power generation facility 202 of the consumer 200-1. The measurement data of the power generation output of the photovoltaic power generation facility 202 of the consumer 200-1 measured by the smart meter 204 is sent to the photovoltaic power generation output estimation device 100 via the communication network 25 and the communication network 50. In this way, the photovoltaic power generation output estimation device 100 acquires the measurement data of the power generation output P _PV1 (t) of the photovoltaic power generation facility 202 of the consumer 200-1. The measurement data of the smart meter 203 is also sent to the photovoltaic power generation output estimation device 100 via the communication network 25 and the communication network 50. At least one of the smart meter 203 and the smart meter 204, or a device not shown in place of these devices, may measure (or calculate) the apparent power consumption, which is the sum of the measurement data of the smart meter 203 and the measurement data of the smart meter 204, that is, the residual demand, and transmit the measured (or calculated) residual demand to the photovoltaic power generation output estimation device 100. It is not essential that the photovoltaic power generation output estimation device 100 obtains the measurement (calculation) data of the residual demand of the consumer 200-1 with whom a full purchase contract has been concluded, but by obtaining this measurement (calculation) data, this measurement (calculation) data can be used to optimize the value of the threshold value u, which will be described later.

As described above, among the consumers 200-1 to 200-n, the consumers 200-1 and 200-3 can obtain measurement data of the power generation output of the photovoltaic power generation facility 202 by the smart meter 204 or the meter 206. Since the smart meter 204 can also be considered as part of the meter, both the consumers 200-1 and 200-3 are consumers who can obtain measurement data of the power generation output of the photovoltaic power generation facility 202. On the other hand, among the consumers 200-1 to 200-n, in the consumers that do not have either the smart meter 204 or the meter 206, although the residual demand added to the power consumption is measured, the power generation output of the photovoltaic power generation facility 202 is not directly measured, so it is difficult to accurately obtain the power generation output. In this embodiment, a method is described in which the photovoltaic power generation output estimation device 100 accurately estimates the power generation output of the consumers that do not have either the smart meter 204 or the meter 206 by using at least one of the consumers 200-1 and 200-3. Hereinafter, the solar power generation equipment of consumers 200-1, 200-3 used as a reference for estimating power generation output will also be referred to as the first solar power generation equipment, and the solar power generation equipment for which power generation output is estimated will also be referred to as the second solar power generation equipment.

The photovoltaic power generation output estimation device 100 uses the first photovoltaic power generation output, which is the power generation output of the first photovoltaic power generation facility, to estimate the second photovoltaic power generation output, which is the photovoltaic power generation output of the second photovoltaic power generation facility at a predetermined time point (hereinafter referred to as the estimation time point). The estimation time point includes not only the present time point but also past or future time points. The photovoltaic power generation output estimation device 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 device 100 will be described later. Note that the combination of the first photovoltaic power generation facility and the second photovoltaic power generation facility may be determined so that the distance between the first photovoltaic power generation facility and the second photovoltaic power generation facility is equal to or less than a predetermined value, or there may be no restriction on the distance between the first photovoltaic power generation facility and the second photovoltaic power generation facility. The above-mentioned predetermined value is, for example, several km, but is not limited thereto.

The photovoltaic power generation output estimation device 100 transmits the estimated photovoltaic power generation output to the control device 300. The control device 300 uses the power generation output estimated by the photovoltaic power generation output estimation device 100 to control the current and voltage, for example, using a power system control device or a distributed power source.

In FIG. 1, an example is shown in which the power generation output estimated by the photovoltaic power generation output estimation device 100 is used for system control, but the power generation output estimated by the photovoltaic power generation output estimation device 100 may be used for, for example, supply and demand control, facility formation, etc. Furthermore, the power generation output estimated by the photovoltaic power generation output estimation device 100 may be used for the control of a VPP (Virtual Power Plant) or DR (Demand Response), or may be used for energy management at the consumer's facility.

When the power generation output estimated by the photovoltaic power generation output estimation device 100 is used for supply and demand control, the supply and demand control system including the photovoltaic power generation output estimation device 100 includes a supply and demand control device instead of the control device 300 shown in FIG. 1. The supply and demand control device controls the supply and demand of electricity using the power generation output estimated by the photovoltaic power generation output estimation device 100. When the power generation output estimated by the photovoltaic power generation output estimation device 100 is used to support facility formation, the facility formation support system including the photovoltaic power generation output estimation device 100 includes a state management device that manages the state of the power system instead of the control device 300. The state management device manages the state of the power system using the power generation output estimated by the photovoltaic power generation output estimation device 100 and supports facility formation by presenting the state of the power system to the operator.

Next, the function of the photovoltaic power generation output estimation device 100 will be described. The photovoltaic power generation output estimation device 100 estimates the second photovoltaic power generation output, which is the power generation output of the photovoltaic power generation facility 202 of the consumer to be estimated, using the first photovoltaic power generation output as a reference and the residual demand of the consumer to be estimated. The first photovoltaic power generation output is the power generation output of the first photovoltaic power generation facility. The second photovoltaic power generation output is the power generation output of the second photovoltaic power generation facility, which is the power generation output of the photovoltaic power generation facility 202 to be estimated. Hereinafter, the consumer in which the first photovoltaic power generation facility is installed is referred to as the first consumer, and the consumer in which the second photovoltaic power generation facility is installed is referred to as the second consumer. Note that the power generation output of the photovoltaic power generation facility 202 and the power consumption of the load 201 include active power and reactive power. Since general photovoltaic power generation facilities, particularly household photovoltaic power generation facilities, are operated with a constant power factor, it is possible to easily estimate the reactive power by estimating the active power. For this reason, the power generation output of the photovoltaic power generation facility 202 and the power consumption of the load 201 described below refer to active power.

Here, an overview of the method for estimating the power generation output of the photovoltaic power generation facility 202 in the photovoltaic power generation output estimation device 100 will be described. Here, the photovoltaic power generation facility 202 of the consumer 200-2 will be used as an example of the power generation output to be estimated, and the power generation output of the photovoltaic power generation facility 202 of the consumer 200-1 will be used as the photovoltaic power generation output used as a reference in the estimation. That is, in this example, the first photovoltaic power generation output is the power generation output of the photovoltaic power generation facility 202 of the consumer 200-1, and the second photovoltaic power generation output to be estimated is the power generation output of the photovoltaic power generation facility 202 of the consumer 200-2. Note that when the estimation target is the power generation output of each of the photovoltaic power generation facilities 202 of the consumers 200-4 to 200-n, that is, when the second photovoltaic power generation output is the power generation output of each of the photovoltaic power generation facilities 202 of the consumers 200-4 to 200-n, the power generation output of the photovoltaic power generation facility 202 can be similarly estimated by using the value corresponding to each consumer as the residual demand. In addition, the second solar power generation output can be estimated in the same manner when the power generation output of the solar power generation facility 202 of the consumer 200-3, i.e., the power generation output measured by the meter 206, is used as the first solar power generation output, which is the solar power generation output used as a reference, instead of the power generation output of the solar power generation facility 202 of the consumer 200-1.

The residual demand of consumer 200-2, the second consumer, is P ₂ (t), the power consumption of load 201 of consumer 200-2 is P _L2 (t), and the power generation output of photovoltaic power generation facility 202 of consumer 200-2, which is the second photovoltaic power generation output, is P _PV2 (t). Furthermore, the power generation output of photovoltaic power generation facility 202 of consumer 200-1, the first consumer, i.e., the first photovoltaic power generation output, is P _PV1 (t). In this case, an equation related to P ₂ (t) holds as in the following equation (1), and further, an equation related to P _PV2 (t) can be assumed as in equation (2).

Here, α is the ratio between the first photovoltaic power generation output and the second photovoltaic power generation output, and is a coefficient for converting the first photovoltaic power generation output to the second photovoltaic power generation output. ε ₁₂ (t) is a time disturbance. _{τ s} is a delay time, i.e., the time it takes for a solar radiation fluctuation to propagate between the installation point of the second photovoltaic power generation facility and the installation point of the first photovoltaic power generation facility.

Then, assuming that the fluctuations in P _L2 (t) and ε ₁₂ (t) are not correlated with the fluctuations in P _PV1 (t), and assuming that temporal stationarity holds in the above equations (1) and (2), the following equation (3) can be derived from the above equations (1) and (2).

Here, Cov _t [ ] means an operator that calculates the covariance function of two quantities, and Cov _t [P _PV1 (t), P _PV1 (t + τ + τ _s )] in the above formula (3) is maximized when τ = -τ _s . Therefore, the delay time τ s is the value obtained by multiplying the time lag when the covariance function Cov _t [P _PV1 (t), P ₂ (t + τ)] of the time series data of the first photovoltaic power generation output and the second consumer's residual demand is minimized (the sign is "-" and the absolute value is maximized) _by -1.

Furthermore, by substituting τ = 0 into the above equation (3), we obtain the following equation (4).

Then, by transforming the above equation (4) into the following equation (5), we can obtain an estimate of the ratio α.

Cov _t [P _PV1 (t), P ₂ (t)] is the covariance between the first photovoltaic power generation output P _PV1 (t) and the residual demand P ₂ (t), and this covariance is called the first covariance. _{Cov t} [P _PV1 (t), P _PV1 (t + τ _s ) _] is the autocovariance between the two first photovoltaic power generation outputs P _PV1 (t) and P _PV1 (t + τ _s ), which are shifted by a delay time τ s, and this autocovariance is called the second covariance. And α is a ratio obtained by dividing the first covariance Cov _t [P _PV1 (t), P ₂ (t)] by the second covariance Cov _t [P _PV1 (t), P _PV1 (t + τ _s )] and multiplying it by -1.

Furthermore, if it is assumed that ε ₁₂ (t) is minute and can be ignored, the following equation (6), which is an approximation equation relating to the second photovoltaic power generation output, can be obtained from the above equation (2).

The photovoltaic power generation output estimation device 100 of this embodiment estimates the second photovoltaic power generation output using the estimation method described above. That is, the photovoltaic power generation output estimation device 100 calculates the above-mentioned first covariance and second covariance, and calculates an estimate of the ratio α by using the calculated first covariance and second covariance according to formula (5). The process of calculating the ratio α may be performed before the estimation time point, which is the time to be estimated for the second photovoltaic power generation output. However, if the estimation time point is in the past, the process may be performed from the estimation time point, which is in the future of the estimation time point, to the present. As described above, the calculation of the ratio α uses time-series data of each measurement data, so that measurement data for a certain period of time is required. This period is set to a range before the estimation time point and not too far away in time from the estimation time point. For example, this period is any period between the estimation time point at which the second photovoltaic power generation output is estimated and a period going back about one or two weeks. For example, the process of calculating the estimate of the ratio α is performed on the day before the day at which the second photovoltaic power generation output is estimated, but the timing of the process of calculating the estimate of the ratio α is not limited to this example. The photovoltaic power generation output estimation device 100 can then calculate an estimate of the second photovoltaic power generation output P _{PV2 (t) by multiplying the estimated value of the ratio α by the first photovoltaic power generation output P PV1} (t+τ _s ) at a time point that is shifted by a delay time τ _s from the _estimation time point t.

The delay time _τs may be approximated to 0. In this case, the photovoltaic power generation output estimation device 100 can calculate an estimate of the second photovoltaic power generation output P _PV2 (t) by multiplying the estimate of the ratio α by the first photovoltaic power generation output P _PV1 (t).

In the above calculation method, it is assumed that the above formula (2) is satisfied, but there are cases where this assumption does not hold. For example, the above assumption may not hold when there is a mountain between the first photovoltaic power generation equipment and the second photovoltaic power generation equipment, when a temporary shadow is cast on at least one of the first photovoltaic power generation equipment and the second photovoltaic power generation equipment, or when the photovoltaic power generation outputs of the first photovoltaic power generation equipment and the second photovoltaic power generation equipment are not proportional to each other due to changes in clouds or wind direction. In such cases, the estimation accuracy of the ratio α decreases, and therefore the estimation accuracy of the second photovoltaic power generation output P _PV2 (t) also decreases. Therefore, when the above assumption does not hold, it is expected that the estimation accuracy of the second photovoltaic power generation output P _PV2 (t) decreases, and it can be said that the conditions are not suitable for estimating the ratio α.

In this embodiment, in order to avoid using the estimated value of α under conditions in which the estimation accuracy of the ratio α decreases, for estimating the second photovoltaic power generation output P _PV2 (t), the photovoltaic power generation output estimation device 100 verifies the estimation accuracy of the ratio α, and does not adopt the estimated ratio α if it is determined that the estimation accuracy will decrease. For example, as described later, an initial value of the ratio α is determined in advance, and when a process for obtaining the ratio α is performed, the ratio α is updated with the value of the ratio α estimated by the process, but if it is determined that the period is not suitable for estimating the ratio α, the process for obtaining the ratio α is not performed or the ratio α is not updated with the value calculated by the process for obtaining the ratio α.

Specifically, the photovoltaic power generation output estimation device 100 calculates a correlation coefficient ρ between the value obtained by multiplying the first photovoltaic power generation output P _PV1 (t) by −1 (minus one) and the residual demand of the second consumer P ₂ (t). The correlation coefficient ρ is an example of correlation information indicating the correlation between the first photovoltaic power generation output P _PV1 (t) and the residual demand P ₂ (t+τ _s ). That is, the photovoltaic power generation output estimation device 100 calculates the correlation coefficient ρ by the following formula (7). Then, the photovoltaic power generation output estimation device 100 evaluates the estimation accuracy of the ratio α depending on whether the calculated correlation coefficient ρ is equal to or greater than a threshold value. In detail, when the correlation coefficient ρ is equal to or greater than a threshold value, the photovoltaic power generation output estimation device 100 determines that the estimation accuracy of the second photovoltaic power generation output, which is the photovoltaic power generation output to be estimated, satisfies the specified accuracy, and when the correlation coefficient ρ is less than the threshold value, determines that the estimation accuracy of the photovoltaic power generation output to be estimated does not satisfy the specified accuracy. The threshold may be set to a value that is generally considered to have a high correlation, for example, 0.95, or may be set by a user based on data acquired for verification, or may be determined by machine learning, etc. Details of the threshold will be described later.

Also, as described above, the combination of the first solar power generation facility and the second solar power generation facility itself may not be appropriate, such as when there is a mountain between the first solar power generation facility and the second solar power generation facility. The above-mentioned determination result of the estimation accuracy can also be used to determine whether the combination of the first solar power generation facility and the second solar power generation facility is appropriate. In other words, the above-mentioned determination result of the estimation accuracy can also be used to select an appropriate combination of the first solar power generation facility and the second solar power generation facility.

For example, when it is assumed that the above formula (2) holds, the closer the distance between the first and second photovoltaic power generation facilities, the more likely the above assumption holds. For this reason, as described above, a method of determining a combination of the first and second photovoltaic power generation facilities so that the distance between the first and second photovoltaic power generation facilities is within a predetermined distance is conceivable. On the other hand, by using the determination result of the estimation accuracy of the ratio α and not adopting the ratio α when the correlation coefficient ρ is less than a threshold value, an appropriate combination of the first and second photovoltaic power generation facilities is selected without considering the distance between the first and second photovoltaic power generation facilities. In the case where the distance between the first photovoltaic power generation facility and the second photovoltaic power generation facility is not taken into consideration, for example, for each second photovoltaic power generation facility to be estimated, at least one of the photovoltaic power generation facilities 202 that are the subject of the full purchase contract and the photovoltaic power generation facility 202 that is measured by the measuring instrument 206 is determined as a candidate for the first photovoltaic power generation facility, and a correlation coefficient ρ is calculated for each candidate, and a candidate whose correlation coefficient ρ is equal to or greater than a threshold value is selected as the first photovoltaic power generation facility. This makes it possible to realize a highly accurate estimation of the second photovoltaic power generation output P _PV2 (t) without taking into consideration the distance between the first photovoltaic power generation facility and the second photovoltaic power generation facility. In the case where there are multiple candidates whose correlation coefficient ρ is equal to or greater than a threshold value, the candidate whose correlation coefficient ρ is the highest may be determined as the first photovoltaic power generation facility. In addition, in the case where there are multiple candidates whose correlation coefficient ρ is equal to or greater than a threshold value, the sum, average, median, or the like of the photovoltaic power generation outputs of the multiple candidates may be used as the first photovoltaic power generation output.

The first photovoltaic power generation facility corresponding to the second photovoltaic power generation facility may also be determined based on both the distance and the correlation coefficient ρ. For example, the photovoltaic power generation output estimation device 100 may determine, as the first photovoltaic power generation facility corresponding to the second photovoltaic power generation facility, the photovoltaic power generation facility 202 that is the subject of a full purchase contract and whose distance from the second photovoltaic power generation facility is within a predetermined distance, and the photovoltaic power generation facility 202 that has the highest correlation coefficient ρ among the photovoltaic power generation facilities 202 measured by the measuring device 206.

Next, an example of the functional configuration of the photovoltaic power generation output estimation device 100 will be described. FIG. 2 is a block diagram showing an example of the functional configuration of the grid control system 10 according to the present embodiment. The photovoltaic power generation output estimation device 100 is a device that estimates a second photovoltaic power generation output, which is the power generation output of the photovoltaic power generation facility 202 at the time of estimation. As shown in FIG. 2, the photovoltaic power generation output estimation device 100 includes a data acquisition unit 110, a first covariance calculation unit 120, a second covariance calculation unit 130, an estimation accuracy verification unit 140, an estimation unit 150, a display unit 160, an input reception unit 170, a storage unit 180, and an output unit 190.

The data acquisition unit 110 receives measurement data from the smart meters 203 to 205 and the measuring instrument 206 via the communication network 25 and the communication network 50, and stores the received measurement data in the memory unit 180. In detail, the measurement data received from the smart meter 204 and the measuring instrument 206 is stored in the memory unit 180 as photovoltaic power generation output data 182, and the measurement data received from the smart meter 205 is stored in the memory unit 180 as residual demand data 183. These measurement data are associated with a time for each measurement value. The time intervals between each measurement value of these measurement data stored in the memory unit 180 are, for example, 1 second, 10 seconds, 1 minute, 30 minutes, or 1 hour, but are not limited to these, and an appropriate value is determined by the user. In addition, these measurement data are stored together with the identification information of the consumers 200-1 to 200-n or the identification information of the photovoltaic power generation facility 202. Furthermore, when the data acquisition unit 110 receives measurement data from the smart meter 203 and the smart meter 204 of the consumer 200-1, it uses these measurement data to calculate the residual demand of the consumer 200-1 and stores it in the memory unit 180 as residual demand data 183.

Here, an example is shown in which the photovoltaic power output estimation device 100 acquires measurement data from the smart meters 203-205 and the measuring instrument 206 via the communication network 25 and the communication network 50, but the measurement data of the smart meters 203-205 may be collected by a so-called aggregation device or a head-end system, and transmitted from the collecting device to the photovoltaic power output estimation device 100. That is, a device that collects measurement data may exist in the communication network 25 and the communication network 50, and the photovoltaic power output estimation device 100 may acquire the measurement data from the device. In addition, the communication route between the photovoltaic power output estimation device 100 and the smart meters 203-205 and the measuring instrument 206 is not limited to the example shown in FIG. 1 and FIG. 2, and the communication route through which the photovoltaic power output estimation device 100 receives the measuring instrument 206 may be different from the communication route through which the photovoltaic power output estimation device 100 receives the measurement data of the smart meters 203-205. In addition, the communication network between the photovoltaic power generation output estimation device 100 and the smart meters 203-205 and the measuring device 206 does not have to be separated into the communication network 25 and the communication network 50. In addition, the photovoltaic power generation output estimation device 100 may receive measurement data from the smart meters 203-205 via multiple communication routes.

The memory unit 180 stores the above-mentioned photovoltaic power generation output data 182 and residual demand data 183, and also stores various data calculated in the photovoltaic power generation output estimation device 100 as calculation data 185. The memory unit 180 also stores, for example, location information data 181 and ratio initial value data 184 input by a user via the input reception unit 170. Note that the location information data 181 and ratio initial value data 184 may be transmitted from another device instead of being input via the input reception unit 170, acquired by the data acquisition unit 110, and stored in the memory unit 180. The location information data 181 is location information data such as the addresses or latitude and longitude of the consumers 200-1 to 200-n that own the photovoltaic power generation facilities 202.

The first covariance calculation unit 120 refers to the location information data 181 of the storage unit 180 and selects a first consumer whose distance from the second consumer, whose power generation output is to be estimated, is within a predetermined distance and has a solar power generation facility 202 that serves as a reference for the estimation. As described above, the first consumer is the consumer 200-1 whose solar power generation facility 202 is the subject of a full purchase contract, or the consumer 200-3 whose power generation output of the solar power generation facility 202 is measured by a measuring instrument 206. As described above, the first solar power generation facility corresponding to the second solar power generation facility, that is, the first consumer corresponding to the second consumer, may be determined using the correlation coefficient ρ without taking the distance into consideration. The first covariance calculation unit 120 calculates a first covariance that is the covariance between the first solar power generation output, which is the power generation output of the solar power generation facility 202 of the first consumer, and the residual demand of the second consumer, and stores the calculated first covariance in the storage unit 180 as calculation data 185. The consumer whose power output is to be estimated is, for example, consumer 200-2 as described above, but it may also be consumers 200-4 to 200-n. All of consumers 200-2, 200-4 to 200-n may be subject to estimation in sequence, and estimation may be performed for each of consumers 200-2, 200-4 to 200-n, or if a total value is required, the total value may be estimated all at once.

Further, the first covariance calculation unit 120 extracts and reads out the first photovoltaic power generation output in the first period from the photovoltaic power generation output data 182 in the storage unit 180, and extracts and reads out the residual demand of the second consumer in the first period from the residual demand data 183 in the storage unit 180. The first period is, for example, a period of about 6 to 10 hours, preferably 8 hours, within a period going back about 1 or 2 weeks from the estimation time point. The first period is preferably a period in which the solar radiation intensity is strong and the fluctuation of the solar radiation intensity is large. However, in this embodiment, in order to determine whether the first period is a period suitable for calculating the ratio α, even if the first period is selected regardless of the solar radiation intensity, even if a period in which the solar radiation intensity is weak or the fluctuation of the solar radiation intensity is small is set as the first period, the ratio α corresponding to the first period is not used, so that the deterioration of the estimation accuracy of the ratio α can be suppressed. Therefore, the solar radiation intensity does not need to be taken into consideration when setting the first period. The first covariance calculation unit 120 calculates a first covariance, which is the covariance of the first photovoltaic power generation output and the residual demand of the second consumer in the first period, using the read-out first photovoltaic power generation output and the read-out residual demand of the second consumer, and stores the first covariance in the storage unit 180 as calculated data 185. Furthermore, the first covariance calculation unit 120 calculates a delay time τ _s in the first period, using the read-out first photovoltaic power generation output and the similarly read-out residual demand of the second consumer, and stores the delay time τ s in the storage unit 180 as calculated data 185. Note that the first covariance calculation unit 120 may approximate the delay time τ _s to 0 without calculating it.

The second covariance calculation unit 130 extracts and reads out the delay time τ _s from the calculation data 185 in the storage unit 180, and extracts and reads out the first photovoltaic power generation output in the first period and the first photovoltaic power generation output in the second period shifted from the first period by the delay time τ _s from the photovoltaic power generation output data 182 in the storage unit 180. Then, the second covariance calculation unit 130 calculates a second covariance which is the autocovariance of the two first photovoltaic power generation outputs shifted from the first period by the delay time τ _s , and stores the calculated second covariance in the storage unit 180 as the calculation data 185. In detail, the second covariance calculation unit 130 reads out, from the photovoltaic power generation output data 182 in the storage unit 180, the time series data of the first photovoltaic power generation output in the first period and the time series data of the first photovoltaic power generation output in the second period shifted from the first period by the delay time τ _s . Then, the second covariance calculation unit 130 calculates a second covariance which is the autocovariance of the time series data of the first photovoltaic power generation output in the first period and the time series data of the first photovoltaic power generation output in the second period, and stores the calculated second covariance in the storage unit 180 as calculated data 185. Note that, when the delay time τ _s is approximated to 0, the second covariance calculation unit 130 calculates the variance of the time series data of the first photovoltaic power generation output in the first period as the second covariance.

The estimation accuracy verification unit 140 uses correlation information indicating the correlation between the first photovoltaic power generation output and the residual demand of the second consumer to determine whether the estimation accuracy of the second photovoltaic power generation output, which is the photovoltaic power generation output to be estimated, satisfies the specified accuracy. In detail, the estimation accuracy verification unit 140 extracts and reads out the first photovoltaic power generation output in the first period from the photovoltaic power generation output data 182 in the storage unit 180, and extracts and reads out the residual demand of the second consumer in the first period from the residual demand data 183 in the storage unit 180. Then, the estimation accuracy verification unit 140 calculates a correlation coefficient ρ by multiplying the correlation coefficient between the read out first photovoltaic power generation output and the read out residual demand of the second consumer by -1, and determines whether the estimation accuracy satisfies the specified accuracy based on whether the correlation coefficient ρ is equal to or greater than a threshold value. The correlation coefficient ρ is an example of correlation information indicating the correlation between the first photovoltaic power generation output and the residual demand of the second consumer. The reason why the estimation accuracy can be determined using the correlation coefficient ρ is as follows. The residual demand of the second consumer is the sum (subtraction) of the second photovoltaic power generation output from the power consumption of the load 201 of the second consumer, and when the correlation between the first photovoltaic power generation output and the second photovoltaic power generation output is strong, the correlation between the first photovoltaic power generation output and the residual demand of the second consumer is also strong. In addition, in calculating the correlation coefficient ρ, the correlation between the first photovoltaic power generation output and the residual demand of the second consumer is multiplied by -1 because, as described above, the residual demand of the second consumer is the power consumption of the load of the second consumer minus the second photovoltaic power generation output, and the positive and negative signs of the residual demand of the second consumer and the second photovoltaic power generation output are opposite. From the above, when the correlation coefficient ρ is close to 1, a high estimation accuracy can be achieved by the estimation method assuming that the above formula (2) is established.

The estimation unit 150 estimates the estimation target photovoltaic power generation output, which is the power generation output of the photovoltaic power generation facility 202 to be estimated, that is, the power generation output of the second photovoltaic power generation facility, by using the first photovoltaic power generation output and the residual demand, which is the apparent power consumption of the second consumer in which the second photovoltaic power generation facility is installed (the sum of the power consumption and the photovoltaic power generation output of the second consumer). The first photovoltaic power generation output is an example of solar radiation intensity data indicating solar radiation intensity. The solar radiation intensity data is, for example, data indicating the solar radiation intensity at a reference point, which is a point different from the installation position of the second photovoltaic power generation facility, but is not limited thereto. In this embodiment, the reference point is the installation position of the first photovoltaic power generation facility. In detail, the estimation unit 150 calculates a ratio α, which is an estimate of the ratio between the first photovoltaic power generation output and the second photovoltaic power generation output, by using the first covariance and the second covariance, and estimates the second photovoltaic power generation output by multiplying the ratio α by the first photovoltaic power generation output shifted by a delay time from the estimation time point. In detail, the estimation unit 150 reads out the first covariance and the second covariance stored in the storage unit 180 as the calculation data 185, and estimates the ratio α for each consumer whose power output is to be estimated by using the read out first covariance and second covariance according to the above formula (5). The estimation unit 150 updates the value of the ratio α stored as the calculation data 185 with the value estimated above. The estimation unit 150 also extracts and reads out the first photovoltaic power generation output at a time point shifted by the delay time τ _s from the estimation time point from the photovoltaic power generation output data 182 in the storage unit 180, and estimates the second photovoltaic power generation output, which is the photovoltaic power generation output of the consumer whose power output is to be estimated, by multiplying the first photovoltaic power generation output by the ratio α, and stores the estimation result in the storage unit 180 as the calculation data 185. Note that while the ratio α is unlikely to change in a short period of time such as one or two weeks, the delay time τ _s is likely to change in a short period of time due to changes in the wind direction or wind speed. Therefore, it is preferable that the delay time τ _s used when estimating the second photovoltaic power generation output is changed in real time taking into account meteorological data and the like.

The display unit 160 displays various data stored in the memory unit 180. The input reception unit 170 receives input from the user.

The output unit 190 reads out the estimated result of the second photovoltaic power generation output from the calculation data 185 stored in the memory unit 180, and transmits the read out estimated result to the control device 300. The output unit 190 may also display the read out estimated result.

Next, the hardware configuration of the photovoltaic power generation output estimation device 100 will be described. In the present embodiment, the photovoltaic power generation output estimation program, which is a program describing the processing in the photovoltaic power generation output estimation device 100, is executed on a computer system, so that the computer system functions as the photovoltaic power generation output estimation device 100. FIG. 3 is a diagram showing an example of the configuration of a computer system that realizes the photovoltaic power generation output estimation device 100 of the present embodiment. As shown in FIG. 3, this computer system includes a control unit 101, an input unit 102, a memory unit 103, a display unit 104, a communication unit 105, and an output unit 106, which are connected via a system bus 107.

In FIG. 3, the control unit 101 is a processor such as a CPU (Central Processing Unit), and executes a photovoltaic power generation output estimation program in which the processing in the photovoltaic power generation output estimation device 100 of this embodiment is described. The input unit 102 is composed of, for example, a keyboard, a mouse, etc., and is used by the user of the computer system to input various information. The storage unit 103 includes various memories such as a RAM (Random Access Memory) and a ROM (Read Only Memory) and a storage device such as a hard disk, and stores the program to be executed by the control unit 101, necessary data obtained in the process of processing, etc. The storage unit 103 is also used as a temporary storage area for the program. The display unit 104 is composed of a display, an LCD (Liquid Crystal Display Panel), etc., and displays various screens to the user of the computer system. The communication unit 105 is a receiver and a transmitter that perform communication processing. The output unit 106 is a printer, etc. Note that FIG. 3 is an example, and the configuration of the computer system is not limited to the example of FIG. 3.

Here, an example of the operation of the computer system until the photovoltaic power output estimation program of this embodiment is in a state where it can be executed will be described. In the computer system having the above-mentioned configuration, for example, the photovoltaic power output estimation program is installed in an auxiliary storage device that is part of the storage unit 103 from a CD-ROM or DVD-ROM set in a CD (Compact Disc)-ROM drive or DVD (Digital Versatile Disc)-ROM drive (not shown). Then, when the photovoltaic power output estimation program is executed, the photovoltaic power output estimation program read from the auxiliary storage device of the storage unit 103 is stored in the main storage area of the storage unit 103. In this state, the control unit 101 executes the processing as the photovoltaic power output estimation device 100 of this embodiment according to the program stored in the storage unit 103.

In the above description, a program describing the processing in the photovoltaic power generation output estimation device 100 is provided on a CD-ROM or DVD-ROM as a recording medium. However, this is not limiting, and depending on the configuration of the computer system and the capacity of the program provided, for example, a program provided via a transmission medium such as the Internet via the communication unit 105 may be used.

The first covariance calculation unit 120, the second covariance calculation unit 130, the estimation accuracy verification unit 140, and the estimation unit 150 shown in FIG. 2 are realized by the control unit 101 shown in FIG. 3 executing the photovoltaic power generation output estimation program stored in the storage unit 103 shown in FIG. 3. The storage unit 180 shown in FIG. 2 is a part of the storage unit 103 shown in FIG. 3. The data acquisition unit 110 shown in FIG. 2 is realized by the communication unit 105 and the control unit 101 shown in FIG. 3. The display unit 160 shown in FIG. 2 is realized by the display unit 104 shown in FIG. 3, and the input reception unit 170 shown in FIG. 2 is realized by the input unit 102 shown in FIG. 3. The photovoltaic power generation output estimation device 100 may be realized by multiple computer systems. The output unit 190 shown in FIG. 2 is realized by at least one of the communication unit 105 and the display unit 104 shown in FIG. 3.

The photovoltaic power generation output estimation program of this embodiment causes a computer to execute, for example, a step of estimating the target photovoltaic power generation output, which is the power generation output of the photovoltaic power generation facility 202 to be estimated, using solar radiation intensity data indicating solar radiation intensity and residual demand, which is the sum of the power consumption and photovoltaic power generation output of the consumer in which the photovoltaic power generation facility is installed, and a step of determining whether the estimation accuracy of the target photovoltaic power generation output satisfies a predetermined accuracy using correlation information indicating the correlation between the solar radiation intensity data and the residual demand in which the photovoltaic power generation facility is installed.

Next, the details of the operation of the photovoltaic power generation output estimation device 100 of this embodiment will be described. FIG. 4 is a flowchart showing an example of a processing procedure for estimating the power generation output by the photovoltaic power generation output estimation device 100 of this embodiment. Below, the processing of estimating the second photovoltaic power generation output by the photovoltaic power generation output estimation device 100 will be described along the flow of FIG. 4. The processing shown in FIG. 4 is performed, for example, for each second photovoltaic power generation facility to be estimated for the power generation output, and it is assumed that the photovoltaic power generation facility 202 (hereinafter also referred to as the surplus purchase PV) that is the second photovoltaic power generation facility and the photovoltaic power generation facility 202 (hereinafter also referred to as the full purchase PV) that is the first photovoltaic power generation facility corresponding to the second photovoltaic power generation facility are selected before this processing. That is, it is assumed that the second consumer having the second photovoltaic power generation facility and the first consumer having the first photovoltaic power generation facility are selected. In the following, an example will be described in which the first solar power generation facility is a full-amount buyback PV, but the first solar power generation facility may be a solar power generation facility 202 whose power generation output is measured by a meter 206 as described above, that is, a surplus buyback PV, and does not depend on the contract type. The selection of the first solar power generation facility may be based on the distance between the solar power generation facilities 202 as described above, may be based on the correlation coefficient ρ, or may be based on both the distance and the correlation coefficient ρ.

As shown in FIG. 4, first, the estimation accuracy verification unit 140 sets the first period (step S1). In detail, the estimation accuracy verification unit 140 refers to the time series data of the first photovoltaic power generation output, which is the power generation output of the photovoltaic power generation facility 202 of the first consumer in the photovoltaic power generation output data 182 stored in the storage unit 180, and searches for a period in which the solar radiation intensity is strong and the solar radiation intensity fluctuates greatly. For example, the estimation accuracy verification unit 140 searches for a period of about 6 to 10 hours in which the first photovoltaic power generation output is large and the fluctuation of the first photovoltaic power generation output is large on the day before the day on which the second photovoltaic power generation output is estimated. Then, the estimation accuracy verification unit 140 sets the searched period as the first period. Note that the estimation accuracy verification unit 140 may search for the above period itself and then search for the first period from the period, rather than searching for the first period from the above period (for example, the day before the day on which the second photovoltaic power generation output is estimated). As described above, the first period may be set in any manner without searching for a period of about 6 to 10 hours during which the first photovoltaic power generation output is large and the fluctuation of the first photovoltaic power generation output is large. Since the hours of sunlight vary depending on the season, the first period may be set according to the season. For example, the first period may be set to 6:00 a.m. to 6:00 p.m. in the summer and shorter in the winter.

Next, the estimation accuracy verification unit 140 acquires P _PV1 (t), which is the SM metering value of the full-amount purchase PV (step S2). In detail, the estimation accuracy verification unit 140 reads P _PV1 (t), which is the power generation output of the first photovoltaic power generation facility in the first period, from the photovoltaic power generation output data 182 stored in the storage unit 180.

Next, the estimation accuracy verification unit 140 acquires _P2 (t), which is the SM metric value of the surplus purchasing consumer (step S3). In detail, the estimation accuracy verification unit 140 reads _P2 (t), which is the residual demand of the second consumer in the first period, from the residual demand data 183 stored in the memory unit 180.

Next, the first covariance calculation unit 120 calculates the delay time τ _s (step S4). In detail, the first covariance calculation unit 120 reads P _PV1 (t), which is the power generation output of the first photovoltaic power generation facility in the first period, and the residual demand P ₂ (t+τ) of the second consumer shifted by the time lag τ from the photovoltaic power generation output data 182 and the residual demand data 183 stored in the storage unit 180, and calculates a covariance function Cov _t [P _PV1 (t), P ₂ (t+τ)] using the read P _PV1 (t) and the residual demand P ₂ (t+τ). Then, the first covariance calculation section 120 calculates the covariance function Cov _t [P _PV1 (t), P ₂ (t + τ)] for multiple time lags τ, and calculates the delay time τ s by multiplying the time lag when the covariance function Cov _t [P _PV1 (t), P ₂ (t + τ)] is at its minimum value (the sign is "-" and the absolute value is the maximum value) by -1. The first covariance calculation section 120 stores _{the calculated delay time τ s in} the storage section 180 as calculated data 185.

Next, the estimation accuracy verification unit 140 calculates the correlation coefficient ρ (step S5). In detail, the estimation accuracy verification unit 140 reads out the delay time _τs from the calculation data 185 stored in the memory unit 180, calculates the correlation coefficient ρ by using P _PV1 (t), P ₂ (t) and the delay time _τs according to the above-mentioned formula (7), and stores it in the memory unit 180 as the calculation data 185.

Next, the estimation accuracy verification unit 140 determines whether the correlation coefficient ρ is equal to or greater than the threshold value u (ρ≧u) (step S6). If the correlation coefficient ρ is equal to or greater than the threshold value u (step S6 Yes), the photovoltaic power generation output estimation device 100 calculates and updates the ratio α (step S7), estimates the photovoltaic power generation output of the surplus purchase PV, i.e., the second photovoltaic power generation output (step S8), and ends the process. Details of steps S7 and S8 will be described later.

FIG. 5 is a diagram showing an example of the ratio α for each combination of photovoltaic power generation facilities 202 stored in the storage unit 180 of the present embodiment. For example, in the example shown in FIG. 5, the power generation output of PV2, which is the photovoltaic power generation facility 202 of the customer 200-2, is estimated using the power generation output of PV1, which is the photovoltaic power generation facility 202 of the customer 200-1, and the estimated value of the ratio α used for the estimation is _α1 . In this way, the ratio α is stored in the storage unit 180 for each combination of the photovoltaic power generation facilities 202 (combination of the second photovoltaic power generation facility and the first photovoltaic power generation facility). When the ratio α is calculated in step S7, the estimated value of the ratio α is stored as the calculation data 185 in the storage unit 180 for each combination of the photovoltaic power generation facility 202 (second photovoltaic power generation facility) to be estimated and the photovoltaic power generation facility 202 (first photovoltaic power generation facility) used for the estimation. If the ratio α has already been stored in the storage unit 180, when the ratio α is calculated in step S7, the ratio α stored in the storage unit 180 is updated with the calculated ratio α.

Returning to the explanation of FIG. 4, if the correlation coefficient ρ is less than the threshold u (step S6 No), the photovoltaic power generation output estimation device 100 calls the ratio α without updating it (step S9) and performs the process of step S8. In detail, the estimation accuracy verification unit 140 notifies the estimation unit 150 of the judgment result of step S6, and in step S9, the estimation unit 150 calls the ratio α by reading the ratio α stored as the calculation data 185 in the storage unit 180. Note that, if the judgment in the above-mentioned step S6 is No when the estimation of the ratio α has never been performed, in step S9, the corresponding initial value in the ratio initial value data 184 is read and stored in the storage unit 180 as the calculation data 185.

The ratio initial value data 184 is an initial value of the ratio α for each second consumer. When a first consumer corresponding to each second consumer is predefined, the initial value of the ratio α may be the ratio of the rated capacity between the photovoltaic power generation equipment 202 of the second consumer and the photovoltaic power generation equipment 202 of the first consumer. When a first consumer corresponding to each second consumer is not predefined, the ratio of the rated capacity between the photovoltaic power generation equipment 202 of the second consumer and the photovoltaic power generation equipment 202 of the candidate first consumer may be stored as the initial value for all consumers that are candidates for the first consumer. In addition, the initial value of the ratio α may be a value that reflects the difference in efficiency by multiplying the above-mentioned rated capacity ratio by a coefficient indicating the efficiency ratio between the first photovoltaic power generation equipment and the second photovoltaic power generation equipment.

Next, the process of step S7 in FIG. 4, that is, the calculation process of the ratio α, will be described in detail. FIG. 6 is a flowchart showing an example of the calculation process of the ratio α in this embodiment. As shown in FIG. 6, the first covariance C ₁ = Cov _t [P _PV1 (t), P ₂ (t)] is calculated (step S11). In detail, the first covariance calculation unit 120 extracts and reads P _PV1 (t), which is the first photovoltaic power generation output in the first period, from the photovoltaic power generation output data 182 in the storage unit 180, extracts and reads P ₂ (t), which is the residual demand of the second consumer in the first period, from the residual demand data 183 in the storage unit 180, and calculates the first covariance C ₁ using the read P _PV1 (t) and P ₂ (t). The first covariance calculation unit 120 stores the calculated first covariance C ₁ in the storage unit 180 as calculation data 185. Since the first covariance _C1 = _Covt [ _PPV1 (t), _P2 (t)] is also calculated in step S4 described above, the first covariance calculation section 120 may store the first covariance _C1 = _Covt [ _PPV1 (t), _P2 (t)] calculated in step S4 in the storage section 180 as the calculated data 185. In other words, step S11 may be performed within the processing of step S4.

Next, the second covariance calculation unit 130 calculates the second covariance _C2 = _Covt [ _PPV1 (t), _PPV1 (t + _τs )] (step S12). In detail, the second covariance calculation unit 130 reads out the delay time _τs from the calculation data 185 in the storage unit 180, extracts and reads out _PPV1 (t) which is the first photovoltaic power generation output in the first period and _PPV1 (t + _τs ) which is the first photovoltaic power generation output in the second period shifted by the delay time _τs from the first period from the photovoltaic power generation output data 182 in the storage unit 180, and calculates the second covariance _C2 = _Covt [ _PPV1 (t), _PPV1 (t + _τs )] which corresponds to the denominator of the formula (5) using _PPV1 (t) and _PPV1 (t + _τs ). The second covariance calculation unit 130 stores the calculated second covariance _C2 in the storage unit 180 as calculation data 185. When the delay time _τs is approximated to 0, no processing related to the delay time _τs is necessary, and the second covariance calculation unit 130 extracts and reads out P _PV1 (t), which is the first photovoltaic power generation output in the first period, from the photovoltaic power generation output data 182 in the storage unit 180, and calculates the second covariance _C2 = Cov _t [P _PV1 (t), P _PV1 (t)] using P _PV1 (t).

Next, the estimation unit 150 calculates the ratio α= _-C1 / _C2 (step S13). In detail, the estimation unit 150 reads out the first covariance _C1 and the second covariance _C2 stored in the storage unit 180 as the calculated data 185, calculates the ratio α by dividing the first covariance _C1 by the second covariance _C2 and adding a negative value to the result, and stores the calculated ratio α in the storage unit 180 as the calculated data 185. As a result, the ratio α stored in the storage unit 180 is updated.

Next, the details of the process of step S8 in FIG. 4, that is, the estimation process of the photovoltaic power generation output of the surplus purchase PV, which is the second photovoltaic power generation facility, will be described. FIG. 7 is a flowchart showing an example of the estimation process of the photovoltaic power generation output of the second photovoltaic power generation facility of this embodiment. As shown in FIG. 7, the estimation unit 150 calculates P _PV2 (t), which is the photovoltaic power generation output (second photovoltaic power generation output) to be estimated, by multiplying P _PV1 (t+τ _s ), which is the first photovoltaic power generation output at a time point shifted by the delay time τ _s from the estimation target time point, by the ratio α (step S21). The estimation unit 150 may use the delay time _{τ s stored} in the storage unit 180 as the calculation data 185 as the delay time τ s at the estimation time point, or may update the delay time τ _s by reflecting weather data at the estimation time point. For example, the estimation unit 150 may update the delay time using a value obtained by calculating the time it takes for clouds to pass from wind direction and wind speed data included in the weather data, may update the delay time τ _s using a satellite image or the like, or may update using weather data by a method other than these. When the delay time τ _s is approximated to 0, the estimation unit 150 calculates the estimation target P _PV2 (t) by multiplying P _PV1 (t) by the ratio α.

4 are performed before step S8, i.e., the estimation process of the second photovoltaic power generation output. For example, they may be performed by the day before the estimation target time. In step S8, the estimation unit 150 estimates the photovoltaic power generation output P _PV2 (t) of the second photovoltaic power generation facility using P _PV1 (t), which is the first photovoltaic power generation output at the estimation target time.

The photovoltaic power generation output data 182 is measurement data measured by the smart meter 204 and the measuring device 206 as described above, but estimated values may be used instead of these measurement data. For example, the photovoltaic power generation output estimation device 100 may estimate the photovoltaic power generation output using the method of this embodiment or another method, and store the estimated photovoltaic power generation output as the photovoltaic power generation output data 182. Alternatively, an estimated value or an actual measurement value of the photovoltaic power generation output may be input by a user, and the input estimated value or actual measurement value may be stored as the photovoltaic power generation output data 182.

The photovoltaic power generation output estimation device 100 of this embodiment is capable of estimating the photovoltaic power generation output of other desired photovoltaic power generation facilities individually by using the power generation output of at least one photovoltaic power generation facility that can acquire the photovoltaic power generation output through the above processing, without installing an actinometer or a measuring instrument with high time resolution. Furthermore, in this embodiment, as described above, the correlation coefficient ρ is used to verify the ratio α, thereby preventing a decrease in the estimation accuracy of the ratio α, and therefore the second photovoltaic power generation output can be estimated with high accuracy.

Although an example has been described in which the power generation output of the second solar power generation equipment of one second consumer is estimated using the power generation output of the first solar power generation equipment of one first consumer, the total amount (combined value) of the power generation output of multiple second solar power generation equipment may be estimated using the power generation output of the first solar power generation equipment of one first consumer. Also, the total amount (combined value) of the power generation output of multiple second solar power generation equipment may be estimated using the total amount (combined value) of the power generation output of the first solar power generation equipment of multiple first consumers. For example, when it is necessary to estimate the total amount of power generation output of solar power generation equipment of multiple consumers, such as by distribution section unit such as a pole-mounted transformer unit, by distribution line unit, or by transmission line unit, the total amount of power generation output of consumers whose power generation output has not been measured can be estimated in a similar manner.

When the power generation output of the second photovoltaic power generation facilities is estimated using the power generation output of the first photovoltaic power generation facilities of the first consumers, the ratio α is calculated for each combination of the photovoltaic power generation facilities. In this case, when the delay time τ _s is taken into consideration, the delay time τ _s is the time it takes for the solar radiation fluctuation to propagate between the center position of the installation point of the second photovoltaic power generation facility and the center position of the installation point of the first photovoltaic power generation facility.

Next, the verification result of the effect of the photovoltaic power generation output estimation device 100 will be described. FIG. 8 is a diagram showing an example of the verification result of the estimation method of the power generation output of this embodiment. In FIG. 8, the horizontal axis indicates time, and the vertical axis indicates the second photovoltaic power generation output (active power). The dashed line indicates the estimated value of the second photovoltaic power generation output estimated by the estimation method described in this embodiment, and the solid line indicates the actual measured value. In the example shown in FIG. 8, the photovoltaic power generation equipment of a customer who is the subject of a full amount purchase contract of multiple houses is set as the first photovoltaic power generation equipment, and the photovoltaic power generation equipment of a customer who is the subject of a surplus purchase contract of multiple houses is set as the second photovoltaic power generation equipment, and the result of estimating the total amount of power generation output of the second photovoltaic power generation equipment is shown. In addition, in the example shown in FIG. 8, 16 points in 30-minute units from 8:00 to 16:00 on a certain day in the past were set as estimation time points, and the ratio α was obtained on the day before the estimation time point, and the second photovoltaic power generation output was estimated using the measurement data of the first photovoltaic power generation output on the day of the estimation time point. In this verification, the power generation output of the second solar power generation facility was measured separately and the measured value is shown as an actual measurement value in Figure 8. As can be seen from Figure 8, it was confirmed that the power generation output estimation method of this embodiment can estimate the second solar power generation output with high accuracy.

Figure 9 is a diagram showing an example of a verification result of the power generation output estimation method of this embodiment when the estimation accuracy is not verified. In Figure 9, as in Figure 8, the dashed line indicates the estimated value of the second photovoltaic power generation output estimated by the estimation method described in this embodiment, and the solid line indicates the actual measured value. In the example shown in Figure 9, the same verification as the example shown in Figure 8 is performed on a different day. However, in the example shown in Figure 9, the verification of the estimation accuracy using the correlation coefficient ρ is omitted. That is, in the example shown in Figure 9, steps S6 and S9 shown in Figure 4 are not performed, and step S7 is performed after step S5. If the verification of the estimation accuracy using the correlation coefficient ρ is not performed, the estimation accuracy of the second photovoltaic power generation output may decrease as shown in Figure 9.

Here, factors that can cause a decrease in the estimation accuracy include, for example, a sudden shadow appearing on either the first or second solar power generation equipment, the presence of a mountain between the first and second solar power generation equipment, or cloud changes or wind direction causing different clouds to pass overhead at the first and second solar power generation equipment, which causes the solar power generation output of the two equipment to be non-proportional, which causes equation (2) to no longer hold. By verifying the estimation accuracy using the correlation coefficient ρ and not adopting the ratio α if the estimation accuracy decreases, it is possible to prevent a decrease in the estimation accuracy of the second solar power generation output.

Figure 10 is a diagram showing an example of a scatter diagram of the correlation coefficient ρ and the estimated error of the second photovoltaic power generation output. In Figure 10, the horizontal axis shows the correlation coefficient ρ, and the vertical axis shows the root mean squared error (RMSE) of the estimated value of the second photovoltaic power generation output. The RMSE shown in Figure 10 is calculated using the photovoltaic power generation output on the next day (estimated target time point) estimated using the ratio α, without verifying the estimation accuracy using the correlation coefficient ρ on the previous day, and the actual measured value measured for verification, calculated using the ratio α. The correlation coefficient ρ shown in Figure 10 is calculated when the ratio α is calculated. Each point in the scatter diagram shown in Figure 10 shows the result of calculating the RMSE of the estimated value for each estimated time point with respect to the actual measured value of the estimated value for each estimated time point, with multiple days as the estimated time points. The correlation coefficient ρ and the ratio α are calculated on the day before each estimated time point. Area 401 is an area where the correlation coefficient ρ is small and the error is large, and it can be seen that by identifying points where the correlation coefficient ρ is small, it is possible to identify estimated days where the error will be large. Area 402 is an area where the correlation coefficient ρ is large and the estimation accuracy is high, and it can be seen that the estimation accuracy is high when the correlation coefficient ρ is sufficiently large (for example, 0.95 or more).

The threshold value u for the correlation coefficient ρ may be preset to a value indicating a high correlation, such as 0.95, or may be determined using data obtained by verification. For example, the estimation accuracy verification unit 140 stores in the storage unit 180 a plurality of sets of data, each set consisting of the RMSE and the correlation coefficient ρ obtained by verification, as illustrated in FIG. 10, and the display unit 160 displays these as a scatter diagram. That is, the display unit 160 displays the scatter diagram illustrated in FIG. 10. Note that the RMSE at this time is the result obtained by estimating the power generation output by updating the ratio α in all cases regardless of the value of the correlation coefficient ρ, without verifying the estimation accuracy using the correlation coefficient ρ. Then, while checking this scatter diagram, the user determines the threshold value u so that a group with a large RMSE, which is the estimation error, can be appropriately separated from a group with a small RMSE, and inputs the determined threshold value u via the input reception unit 170. For example, the user adjusts the threshold value u by moving the line of the threshold value u shown in FIG. 10 left and right with a mouse, which is an example of the input reception unit 170. For example, a confirmation button may be displayed on the scatter diagram illustrated in FIG. 10, and the user may set the threshold value u by moving the straight line indicating the threshold value u to a desired position and pressing the confirmation button. In addition, in the verification for determining the threshold value u, the first consumer having the all-purchase PV may be set as the second consumer, and another all-purchase PV may be used as the first solar power generation facility to estimate the power generation output of the all-purchase PV of the second consumer. In this case, the measurement value of the smart meter 204 of the second consumer may be used as the actual measurement value for verification. In addition, a measuring instrument may be temporarily installed in the second consumer having the surplus purchase PV described above to measure the solar power generation output. Furthermore, an estimated value of the solar power generation output installed in the second consumer may be used. In addition, the threshold value u may be determined using a simulation result instead of the verification result.

The threshold value u may be calculated by the photovoltaic power generation output estimation device 100 or another device by calculation such as machine learning. For example, the estimation accuracy verification unit 140 may determine the threshold value u by machine learning using the RMSE and correlation coefficient ρ obtained by the verification. That is, the estimation accuracy verification unit 140 may obtain multiple errors (RMSE) of the estimated value of the second photovoltaic power generation output estimated by the estimation unit 150 with respect to the actual measured value of the second photovoltaic power generation output, and may use multiple data sets consisting of the errors and the correlation coefficient ρ corresponding to the errors to calculate the threshold value by machine learning so that the error when the correlation coefficient ρ is less than the threshold value u is equal to or less than a specified value. As the machine learning, the maximum entropy method, decision tree, etc. may be used, or the threshold value u may be obtained by classifying the results by a clustering method, and any method may be used. The display unit 160 may display the above-mentioned scatter diagram, that is, a scatter diagram showing the relationship between the error of the estimated value of the second photovoltaic power generation output estimated by the estimation unit 150 with respect to the actual measured value of the second photovoltaic power generation output. Furthermore, the display unit 160 may display the calculated threshold value u superimposed on this scatter diagram. This allows the user to check whether the threshold value u is set correctly. The user may also be allowed to change the calculated threshold value u. For example, the user may be allowed to change the threshold value u by shifting the straight line indicating the calculated threshold value u to the left or right, in the same way as when the user sets the threshold value u.

In the above example, the second photovoltaic power generation output is estimated using the first photovoltaic power generation output, which is the measurement data. However, after estimating the second photovoltaic power generation output, the estimated second photovoltaic power generation output may be used as the first photovoltaic power generation output to estimate the power generation output of another photovoltaic power generation facility. By repeating this, for example, even if there is no photovoltaic power generation facility 202 whose power generation output has been measured within a predetermined distance from the photovoltaic power generation facility 202 to be estimated, the power generation output of the photovoltaic power generation facility 202 to be estimated can be estimated.

As described above, the photovoltaic power generation output estimation device 100 of the first embodiment estimates the second photovoltaic power generation output, which is the power generation output of the second photovoltaic power generation facility, using the first photovoltaic power generation output, which is the power generation output of the first photovoltaic power generation facility, and the residual demand of the consumer in which the second photovoltaic power generation facility is installed. Furthermore, the photovoltaic power generation output estimation device 100 includes an estimation accuracy verification unit 140 that determines whether the estimation accuracy of the second photovoltaic power generation output satisfies a specified accuracy using a correlation coefficient ρ between the first photovoltaic power generation output and the residual demand of the consumer in which the second photovoltaic power generation facility is installed. Therefore, if it is determined that the estimation accuracy does not satisfy the specified accuracy, measures can be taken. One example of this measure is to use an initial value or a previously calculated ratio α without adopting the calculated ratio α, but the measure is not limited to this. For example, if it is determined that the estimation accuracy does not satisfy the specified accuracy, the second photovoltaic power generation output may be estimated by another estimation method. Alternatively, the first photovoltaic power generation equipment corresponding to the second photovoltaic power generation equipment may be changed sequentially, and if a first photovoltaic power generation equipment with a high correlation coefficient ρ is found, the ratio α may be calculated using the power generation output of the first photovoltaic power generation equipment. If it is determined that the estimation accuracy does not satisfy the specified accuracy, measures may be taken to improve the estimation accuracy of the second photovoltaic power generation output.

Embodiment 2.
Next, a photovoltaic power generation output estimating apparatus 100 according to a second embodiment will be described. The functional configuration and hardware configuration of the photovoltaic power generation output estimating apparatus 100 of this embodiment are similar to those of the photovoltaic power generation output estimating apparatus 100 of the first embodiment. Components having the same functions as those of the first embodiment will be described with the same reference numerals as those of the first embodiment, and descriptions that overlap with those of the first embodiment will be omitted. Below, differences from the first embodiment will be mainly described.

FIG. 11 is a flowchart showing an example of a procedure for estimating the power generation output by the photovoltaic power generation output estimation device 100 of this embodiment. First, the estimation accuracy verification unit 140 sets a plurality of first periods (step S31). Then, for one of the plurality of first periods, steps S2 to S6 are performed in the same manner as in embodiment 1. If step S6 is Yes, step S32 is performed. In step S32, the ratio α is calculated in the same manner as in embodiment 1, but the calculated ratio α is temporarily stored in the estimation unit 150 or the storage unit 180, and the ratio α in the calculation data 185 of the storage unit 180 is not updated at this point. After step S32, the estimation accuracy verification unit 140 determines whether the ratio α for all first periods has been calculated (step S33), and if there is a first period for which the ratio α has not been calculated (step S33 No), selects one of the first periods for which the ratio α has not been calculated. Thereafter, the process from step S2 is repeated for the selected first period. If the answer is No in step S6, step S32 is not performed and step S33 is performed.

When the ratios α for all first periods have been calculated (step S33 Yes), the estimation accuracy verification unit 140 instructs the estimation unit 150 to calculate a representative value, and the estimation unit 150 calculates a representative value of the multiple ratios α and updates the stored ratio α with the calculated value (step S34). In detail, the estimation unit 150 calculates a representative value of the ratio α using the ratio α for each first period that is temporarily stored. The representative value of the ratio α is, for example, the median value of the multiple ratios α that are temporarily stored, but may also be a statistical value such as the average value or the mode. Step S8 is the same as in the first embodiment.

As described in this embodiment, multiple first periods may be set, or one first period may be set as described in embodiment 1. In other words, it is sufficient that at least one first period is set.

In this embodiment, the photovoltaic power generation output estimation device 100 sets a plurality of first periods, calculates the ratio α for the first periods in which the correlation coefficient ρ is equal to or greater than the threshold value u, and estimates the second photovoltaic power generation output using a representative value of the calculated ratio α. This makes it possible to improve the estimation accuracy of the second photovoltaic power generation output compared to embodiment 1.

Embodiment 3.
12 is a diagram showing a configuration example of a system control system according to a third embodiment. A system control system 10a according to this embodiment includes a photovoltaic power generation output estimating device 100a, a control device 300, smart meters 203 to 205, a measuring instrument 206, and a solar radiation intensity measuring network 60. Components having the same functions as those in the first embodiment are described with the same reference numerals as those in the first embodiment, and descriptions that overlap with those in the first embodiment will be omitted. Below, differences from the first embodiment will be mainly described.

The solar radiation intensity measurement network 60, for example, includes multiple pyranometers that measure solar radiation intensity, and provides measured values of solar radiation intensity at multiple locations as data indicating solar radiation intensity. The data indicating solar radiation intensity is provided together with information indicating the corresponding date and time and location, i.e., information indicating the corresponding date and time and location. The solar radiation intensity measurement network 60 may also provide both measured values of solar radiation intensity and estimated values of solar radiation intensity. The estimated values of solar radiation intensity may be, for example, highly accurate estimates estimated using satellite images, but are not limited to this. Also, instead of the solar radiation intensity measurement network 60, an estimation system that obtains estimated values of solar radiation intensity may be used.

In the first embodiment, the photovoltaic power generation output estimation device 100 in FIG. 2 estimates the second photovoltaic power generation output using measurement data of the first photovoltaic power generation output (measurement data of the power generation output of the full-amount purchase PV, or measurement data of the power generation output of the surplus purchase PV measured by the measuring instrument 206). In the present embodiment, the second photovoltaic power generation output is estimated using an actual or estimated value of solar radiation intensity instead of the measurement data of the first photovoltaic power generation output.

As shown in FIG. 12, the photovoltaic power generation output estimation device 100a is similar to the photovoltaic power generation output estimation device 100 of the first embodiment, except that, instead of the first covariance calculation unit 120, the second covariance calculation unit 130, and the estimation accuracy verification unit 140, the device includes a first covariance calculation unit 120a, a second covariance calculation unit 130a, and an estimation accuracy verification unit 140a, and that solar radiation intensity data 186 is stored in the memory unit 180 instead of the photovoltaic power generation output data 182.

In this embodiment, the data acquisition unit 110 acquires data indicating solar radiation intensity from the solar radiation intensity measurement network 60, and stores the acquired data in the memory unit 180 as solar radiation intensity data 186. Note that the solar radiation intensity data 186 may be an estimated value of solar radiation intensity, or may be a mixture of both measured values of solar radiation intensity and estimated values of solar radiation intensity.

The first covariance calculation unit 120a, the second covariance calculation unit 130a, and the estimation accuracy verification unit 140a perform the same processing as in embodiment 1 using the solar radiation intensity data 186 instead of the measurement data of the first solar power generation output.

Figure 13 is a flowchart showing an example of a processing procedure for estimating power generation output by the photovoltaic power generation output estimation device 100a of this embodiment. Note that, before the processing shown in Figure 13, a reference point that is a point corresponding to the second photovoltaic power generation facility is selected from among the points for which data indicating solar radiation intensity is provided. The method of selecting the reference point is the same as the method of selecting the combination of the second photovoltaic power generation facility and the first photovoltaic power generation facility in embodiment 1, and may be selected based on distance, may be selected based on the correlation coefficient ρ of this embodiment described later, or may be selected based on both distance and correlation coefficient ρ.

In step S1 shown in FIG. 13, similar to the first embodiment, the estimation accuracy verification unit 140a sets the first period by searching for a period in which the irradiance is strong and the irradiance fluctuates greatly, for example, by referring to the irradiance intensity data 186 instead of the photovoltaic power generation output data 182. After step S1, the estimation accuracy verification unit 140a acquires the irradiance intensity SR(t) (step S41). In detail, the estimation accuracy verification unit 140a reads out the irradiance intensity SR(t) at the reference point for the first period from the irradiance intensity data 186 stored in the memory unit 180.

The estimation accuracy verification unit 140a performs step S3 in the same manner as in the first embodiment. Thereafter, the first covariance calculation unit 120 calculates the delay time τ _s (step S4), and the estimation accuracy verification unit 140a calculates the correlation coefficient ρ (step S42). In step S4, the delay time τ _s is calculated in the same manner as in the first embodiment, using the irradiance instead of the first photovoltaic power generation output. In step S42, the estimation accuracy verification unit 140a calculates the correlation coefficient ρ by -Cor _t [SR(t), P ₂ (t+τ _s )] using SR(t) and P ₂ (t). The correlation coefficient ρ is an example of correlation information indicating the correlation between the irradiance data and the residual demand of the second consumer. The estimation accuracy verification unit 140a stores the calculated correlation coefficient ρ in the storage unit 180 as calculation data 185.

The estimation accuracy verification unit 140a performs step S6 in the same manner as in embodiment 1. If the correlation coefficient ρ is equal to or greater than the threshold u (step S6 Yes), the photovoltaic power generation output estimation device 100a calculates and updates the ratio α (step S43), estimates the photovoltaic power generation output of the surplus purchased PV, i.e., the second photovoltaic power generation output (step S44), and ends the process. If the correlation coefficient ρ is less than the threshold u (step S6 No), the photovoltaic power generation output estimation device 100a calls the ratio α without updating it (step S45), and performs the process of step S44.

Next, the details of the process of step S43 in FIG. 13, that is, the calculation process of the ratio α, will be described. FIG. 14 is a flowchart showing an example of the calculation process of the ratio α in this embodiment. As shown in FIG. 14, first, the first covariance calculation unit 120a calculates the first covariance C ₁ = Cov _t [SR(t), P ₂ (t)] (step S51). In detail, the first covariance calculation unit 120a extracts and reads SR(t), which is the solar radiation intensity at the reference point in the first period, from the solar radiation intensity data 186 in the storage unit 180, extracts and reads P ₂ (t), which is the residual demand of the second consumer in the first period, from the residual demand data 183 in the storage unit 180, and calculates the first covariance C ₁ using the read SR(t) and P ₂ (t). The first covariance calculation unit 120a stores the calculated first covariance C ₁ in the storage unit 180 as calculation data 185. Since the first covariance _C1 = _Covt [SR(t), _P2 (t)] is also calculated in step S4 described above, the first covariance calculation section 120 may store the first covariance _C1 = _Covt [SR(t), _P2 (t)] calculated in step S4 in the storage section 180 as the calculated data 185. In other words, step S51 may be performed within the processing of step S4.

Next, the second covariance calculation unit 130a calculates the second covariance C ₂ = Cov _t [SR(t), SR(t+τ _s )] (step S52). In detail, the second covariance calculation unit 130a reads out the delay time τ _s from the calculation data 185 of the storage unit 180, extracts and reads out SR(t), which is the solar radiation intensity at the reference point in the first period, and SR(t+τ _s ), which is the solar radiation intensity in the second period shifted by the delay time τ _s from the first period, from the solar radiation intensity data 186 of the storage unit 180, and calculates Cov _t [SR(t), SR(t+τ _s )], which is the second covariance C ₂ , using SR(t) and SR(t+τ _s ). The second covariance calculation unit 130a stores the calculated second covariance C ₂ in the storage unit 180 as the calculation data 185. When the delay time τ _s is approximated to 0, no processing related to the delay time τ _s is necessary, and the second covariance calculation unit 130 extracts and reads out SR(t), which is the solar radiation intensity in the first period, from the solar radiation intensity data 186 in the storage unit 180, and calculates the second covariance C ₂ Cov _t [SR(t), SR(t)] using SR(t).

Next, the estimation unit 150 calculates the ratio α=-C ₁ /C ₂ (step S53). In detail, the estimation unit 150 reads out the first covariance C ₁ and the second covariance C ₂ stored in the storage unit 180 as the calculated data 185, similar to step S13 in the first embodiment, calculates the ratio α by dividing the first covariance C ₁ by the second covariance C ₂ and adding a negative value to the result, and stores the calculated ratio α in the storage unit 180 as the calculated data 185. This updates the ratio α stored in the storage unit 180. Similar to the first embodiment, the ratio α is stored in the storage unit 180 for each combination of the second photovoltaic power generation facility and the reference point.

Next, the details of the process of step S44 in FIG. 13, that is, the estimation process of the photovoltaic power generation output of the surplus purchase PV, which is the second photovoltaic power generation facility, will be described. FIG. 15 is a flowchart showing an example of the estimation process of the photovoltaic power generation output of the second photovoltaic power generation facility of this embodiment. As shown in FIG. 15, the estimation unit 150 calculates P _PV2 (t), which is the photovoltaic power generation output (second photovoltaic power generation output) to be estimated, by multiplying the solar irradiance SR (t + τ _s ) at a time point shifted by a delay time τ _s from the estimation target time point (the solar irradiance at the reference point at a time point shifted by a delay time τ _s from the estimation target time point) by the ratio α (step S61). The estimation unit 150 may use the delay time τ _s stored as the calculation data 185 in the storage unit 180 as the delay time τ _s at the estimation time point, or may update the delay time τ _s by reflecting weather data at the estimation time point, as in the first embodiment. When the delay time τ _s is approximated to 0, the estimation unit 150 calculates P _PV2 (t) to be estimated by multiplying SR(t) by the ratio α.

The hardware configuration of the photovoltaic power generation output estimation device 100a is similar to that of the photovoltaic power generation output estimation device 100 of embodiment 1, and the photovoltaic power generation output estimation device 100a is realized, for example, by a computer system illustrated in FIG. 3.

Figure 12 shows an example in which the power generation output estimated by the photovoltaic power generation output estimation device 100a is used for system control, but as in embodiment 1, this is not limited to this, and the power generation output estimated by the photovoltaic power generation output estimation device 100a may be used, for example, for supply and demand control, facility formation, etc. In other words, the photovoltaic power generation output estimation device 100a may be used in a supply and demand control system, a facility formation system, etc.

As described above, the photovoltaic power generation output estimation device 100a of the third embodiment estimates the second photovoltaic power generation output, which is the power generation output of the second photovoltaic power generation facility, using the solar radiation intensity data at the reference point and the residual demand of the consumer in which the second photovoltaic power generation facility is installed. Furthermore, the photovoltaic power generation output estimation device 100a includes an estimation accuracy verification unit 140a that determines whether the estimation accuracy of the second photovoltaic power generation output satisfies a specified accuracy using a correlation coefficient ρ between the solar radiation intensity data and the residual demand of the consumer in which the second photovoltaic power generation facility is installed. Therefore, if it is determined that the estimation accuracy does not satisfy the specified accuracy, measures can be taken. These measures are the same as those in the first embodiment. This makes it possible to improve the estimation accuracy of the power generation output of the second photovoltaic power generation facility.

Note that the actual or estimated value of the solar radiation intensity described in this embodiment and the measurement data of the first solar power generation output described in embodiment 1 are both dependent on the solar radiation intensity. Therefore, the actual or estimated value of the solar radiation intensity described in this embodiment and the measurement data of the first solar power generation output described in embodiment 1 are both examples of solar radiation intensity data indicating the solar radiation intensity at a point different from the installation position of the solar power generation equipment to be estimated for the power generation output. For this reason, the solar power generation output estimation device 100 of embodiment 1 also estimates the second solar power generation output, which is the power generation output of the second solar power generation equipment, using the solar radiation intensity data at the reference point (the position of the first solar power generation equipment) and the residual demand of the consumer in which the second solar power generation equipment is installed, and determines whether the estimation accuracy of the second solar power generation output satisfies the specified accuracy using the correlation coefficient ρ between the solar radiation intensity data and the residual demand of the consumer in which the second solar power generation equipment is installed.

In addition, as the solar radiation intensity data, both the power generation output (measurement data) of the full-amount purchase PV and the actual or estimated value of solar radiation intensity may be used. For example, for each second solar power generation facility, it may be more accurate to use the correlation coefficient ρ using the power generation output of the full-amount purchase PV or the correlation coefficient ρ using solar radiation intensity. For this reason, it may be possible to use either the power generation output of the full-amount purchase PV or the solar radiation intensity for each second solar power generation facility.

Embodiment 4.
Next, a photovoltaic power generation output estimating device 100a according to a fourth embodiment will be described. The functional configuration and hardware configuration of the photovoltaic power generation output estimating device 100a of this embodiment are similar to those of the photovoltaic power generation output estimating device 100a of the third embodiment. Components having the same functions as those of the third embodiment will be described with the same reference numerals as those of the first embodiment, and descriptions that overlap with those of the third embodiment will be omitted. Below, differences from the third embodiment will be mainly described.

In this embodiment, similar to embodiment 2, multiple first periods are set, and the second photovoltaic power generation output is estimated using a representative value of the calculated ratio α.

FIG. 16 is a flowchart showing an example of a procedure for estimating the power generation output by the photovoltaic power generation output estimation device 100a of this embodiment. First, the estimation accuracy verification unit 140a performs step S31 in the same manner as in embodiment 2. Then, for one of the multiple first periods, steps S41, S3, S4, S42, and S6 are performed in the same manner as in embodiment 3. If step S6 is Yes, step S71 is performed. In step S71, the ratio α is calculated in the same manner as in embodiment 3, but the calculated ratio α is temporarily stored in the estimation unit 150 or the storage unit 180, and the ratio α in the calculation data 185 of the storage unit 180 is not updated at this point. After step S71, the estimation accuracy verification unit 140a performs step S33 in the same manner as in embodiment 2. If there is a first period in which the ratio α has not been calculated (step S33 No), one of the first periods in which the ratio α has not been calculated is selected. Thereafter, the process from step S41 is repeated for the selected first period. If the answer is No in step S6, step S71 is skipped and step S33 is performed.

When the ratios α for all first periods have been calculated (step S33: Yes), step S34 is performed as in embodiment 2. Step S44 is the same as in embodiment 3.

In this embodiment, the photovoltaic power generation output estimation device 100a sets a plurality of first periods, calculates the ratio α for the first periods in which the correlation coefficient ρ is equal to or greater than the threshold value u, and estimates the second photovoltaic power generation output using a representative value of the calculated ratio α. This improves the estimation accuracy of the second photovoltaic power generation output compared to embodiment 3.

The configurations shown in the above embodiments are merely examples, and may be combined with other known technologies, or the embodiments may be combined with each other. In addition, parts of the configurations may be omitted or modified without departing from the spirit of the invention.

Various aspects of this disclosure are summarized below as appendices.

(Appendix 1)
an estimation unit that estimates an estimation target photovoltaic power generation output, which is a power generation output of a photovoltaic power generation facility that is an estimation target, by using solar irradiance data indicating solar irradiance and a residual demand that is a sum of a power consumption and a photovoltaic power generation output of a consumer in which the photovoltaic power generation facility is installed;
an estimation accuracy verification unit that uses correlation information indicating a correlation between the solar irradiance data and the residual demand to determine whether or not the estimation accuracy of the estimation target photovoltaic power generation output satisfies a predetermined accuracy;
A photovoltaic power generation output estimating device comprising:
(Appendix 2)
a first covariance calculation unit that calculates a first covariance that is a covariance between time series data of the solar irradiance data and time series data of the residual demand in a first period prior to an estimation time point of the photovoltaic power generation output to be estimated;
A second covariance calculation unit that calculates a second covariance that is an autocovariance between time series data of the solar irradiance data in the first period and time series data of the solar irradiance data in a second period shifted from the first period by a delay time;
Equipped with
The delay time is a time for a fluctuation in solar radiation to propagate between the solar power generation facility and a point corresponding to the solar radiation intensity data,
the estimation unit calculates a ratio that is an estimate of a ratio between the solar irradiance data and the solar power generation output to be estimated using the first covariance and the second covariance, and estimates the solar power generation output to be estimated by multiplying the solar irradiance data shifted by a delay time from the estimation time point by the ratio;
The photovoltaic power generation output estimation device according to claim 1, characterized in that the estimation accuracy verification unit determines whether the estimation accuracy of the estimation target photovoltaic power generation output for each first period satisfies a predetermined accuracy.
(Appendix 3)
The photovoltaic power generation output estimating device according to claim 2, wherein the ratio is a value obtained by dividing the first covariance by the second covariance and multiplying the result by −1.
(Appendix 4)
The correlation information is a value obtained by multiplying a correlation coefficient between the time series data of the solar irradiance data in the first period and the time series data of the residual demand in the second period shifted from the first period by a delay time by −1,
The photovoltaic power generation output estimation device according to claim 3, characterized in that the estimation accuracy verification unit determines that the estimation accuracy of the photovoltaic power generation output to be estimated meets a specified accuracy when the correlation coefficient is equal to or greater than a threshold value, and determines that the estimation accuracy of the photovoltaic power generation output to be estimated does not meet a specified accuracy when the correlation coefficient is less than the threshold value.
(Appendix 5)
A plurality of the first periods are set,
The photovoltaic power generation output estimation device according to claim 4, wherein the estimation unit calculates a representative value of the ratio using the ratio corresponding to the first period in which the correlation coefficient is determined to be equal to or greater than a threshold value, and estimates the photovoltaic power generation output to be estimated using the representative value.
(Appendix 6)
a display unit that displays a scatter diagram showing a relationship between the correlation coefficient and an error of the estimated value of the estimation target photovoltaic power generation output estimated by the estimation unit with respect to an actual measured value of the estimation target photovoltaic power generation output;
The photovoltaic power generation output estimating device according to claim 4 or 5, comprising:
(Appendix 7)
The photovoltaic power generation output estimating device according to claim 6, wherein the display unit displays the threshold value superimposed on the scatter diagram.
(Appendix 8)
The photovoltaic power generation output estimating device according to any one of appendices 2 to 7, characterized in that the delay time is approximated to zero.
(Appendix 9)
The solar power generation output estimation device described in any one of appendix 1 to 8, characterized in that the solar irradiance intensity data is measurement data or estimated values of power generation output of a solar power generation facility installed at a location corresponding to the solar irradiance intensity data.
(Appendix 10)
A photovoltaic power generation output estimation device described in any one of appendices 1 to 9, characterized in that the solar irradiance data is a measured value or an estimated value of solar irradiance measured at a point corresponding to the solar irradiance data.
(Appendix 11)
A photovoltaic power generation output estimation device that estimates the power generation output of a photovoltaic power generation facility;
a control device that controls a voltage of a power grid using the power generation output estimated by the photovoltaic power generation output estimating device;
Equipped with
The photovoltaic power generation output estimating device includes:
an estimation unit that estimates an estimation target photovoltaic power generation output, which is a power generation output of a photovoltaic power generation facility that is an estimation target, by using solar irradiance data indicating solar irradiance and a residual demand that is a sum of a power consumption and a photovoltaic power generation output of a consumer in which the photovoltaic power generation facility is installed;
an estimation accuracy verification unit that uses correlation information indicating a correlation between the solar irradiance data and the residual demand to determine whether or not the estimation accuracy of the estimation target photovoltaic power generation output satisfies a predetermined accuracy;
A system control system comprising:
(Appendix 12)
A photovoltaic power generation output estimation device that estimates the power generation output of a photovoltaic power generation facility;
a supply and demand control device that controls supply and demand of electricity using the power generation output estimated by the photovoltaic power generation output estimation device;
Equipped with
The photovoltaic power generation output estimating device includes:
an estimation unit that estimates an estimation target photovoltaic power generation output, which is a power generation output of a photovoltaic power generation facility that is an estimation target, by using solar irradiance data indicating solar irradiance and a residual demand that is a sum of a power consumption and a photovoltaic power generation output of a consumer in which the photovoltaic power generation facility is installed;
an estimation accuracy verification unit that uses correlation information indicating a correlation between the solar irradiance data and the residual demand to determine whether or not the estimation accuracy of the estimation target photovoltaic power generation output satisfies a predetermined accuracy;
A supply and demand control system comprising:
(Appendix 13)
A photovoltaic power generation output estimation device that estimates the power generation output of a photovoltaic power generation facility;
a state management device that indicates a state of a power grid using the power generation output estimated by the photovoltaic power generation output estimation device;
Equipped with
The photovoltaic power generation output estimating device includes:
an estimation unit that estimates an estimation target photovoltaic power generation output, which is a power generation output of a photovoltaic power generation facility that is an estimation target, by using solar irradiance data indicating solar irradiance and a residual demand that is a sum of a power consumption and a photovoltaic power generation output of a consumer in which the photovoltaic power generation facility is installed;
an estimation accuracy verification unit that uses correlation information indicating a correlation between the solar irradiance data and the residual demand to determine whether or not the estimation accuracy of the estimation target photovoltaic power generation output satisfies a predetermined accuracy;
A facility formation support system comprising:
(Appendix 14)
A photovoltaic power generation output estimation device estimates an estimation target photovoltaic power generation output, which is a power generation output of a photovoltaic power generation facility to be estimated, by using solar irradiance intensity data indicating solar irradiance and a residual demand, which is a sum of a power consumption and a photovoltaic power generation output at a consumer in which the photovoltaic power generation facility is installed;
A photovoltaic power generation output estimation method, characterized in that the photovoltaic power generation output estimation device determines whether the estimation accuracy of the photovoltaic power generation output to be estimated satisfies a specified accuracy using correlation information indicating the correlation between the solar irradiance data and the residual demand.
(Appendix 15)
A step of estimating an estimated photovoltaic power generation output, which is a power generation output of a photovoltaic power generation facility to be estimated, using solar irradiance data indicating solar irradiance and a residual demand, which is a sum of a power consumption and a photovoltaic power generation output of a consumer in which the photovoltaic power generation facility is installed;
determining whether or not the estimation accuracy of the estimation target photovoltaic power generation output satisfies a predetermined accuracy by using correlation information indicating a correlation between the solar irradiance data and the residual demand;
A photovoltaic power generation output estimation program characterized by causing a computer to execute the above.

10, 10a Power system control system, 60 Solar radiation intensity measurement network, 100, 100a Photovoltaic power generation output estimation device, 110 Data acquisition unit, 120, 120a First covariance calculation unit, 130, 130a Second covariance calculation unit, 140, 140a Estimation accuracy verification unit, 150 Estimation unit, 160 Display unit, 170 Input reception unit, 180 Memory unit, 190 Output unit, 200-1 to 200-4, 200-m, 200-n Consumers, 201 Load, 202 Photovoltaic power generation equipment, 203 to 205 Smart meters, 206 Measuring instrument, 300 Control device.

Claims (15)

an estimation unit that estimates an estimation target photovoltaic power generation output, which is a power generation output of a photovoltaic power generation facility that is an estimation target, by using solar irradiance data indicating solar irradiance and a residual demand that is a sum of a power consumption and a photovoltaic power generation output of a consumer in which the photovoltaic power generation facility is installed;
an estimation accuracy verification unit that uses correlation information indicating a correlation between the solar irradiance data and the residual demand to determine whether or not the estimation accuracy of the estimation target photovoltaic power generation output satisfies a predetermined accuracy;
A photovoltaic power generation output estimating device comprising: a first covariance calculation unit that calculates a first covariance that is a covariance between time series data of the solar irradiance data and time series data of the residual demand in a first period prior to an estimation time point of the photovoltaic power generation output to be estimated;
A second covariance calculation unit that calculates a second covariance that is an autocovariance between time series data of the solar irradiance intensity data in the first period and time series data of the solar irradiance intensity data in a second period shifted from the first period by a delay time;
Equipped with
The delay time is a time for a fluctuation in solar radiation to propagate between the solar power generation facility and a point corresponding to the solar radiation intensity data,
the estimation unit calculates a ratio that is an estimate of a ratio between the solar irradiance data and the solar power generation output to be estimated using the first covariance and the second covariance, and estimates the solar power generation output to be estimated by multiplying the solar irradiance data shifted by a delay time from the estimation time point by the ratio;
The photovoltaic power generation output estimating device according to claim 1 , wherein the estimation accuracy verifying unit determines whether or not the estimation accuracy of the estimation target photovoltaic power generation output satisfies a predetermined accuracy for each of the first periods. The solar power generation output estimation device according to claim 2, characterized in that the ratio is a value obtained by dividing the first covariance by the second covariance and multiplying the result by -1. The correlation information is a value obtained by multiplying a correlation coefficient between the time series data of the solar irradiance data in the first period and the time series data of the residual demand in the second period shifted from the first period by a delay time by −1,
The photovoltaic power generation output estimation device according to claim 3, characterized in that the estimation accuracy verification unit determines that the estimation accuracy of the photovoltaic power generation output to be estimated meets a predetermined accuracy when the correlation coefficient is equal to or greater than a threshold value, and determines that the estimation accuracy of the photovoltaic power generation output to be estimated does not meet a predetermined accuracy when the correlation coefficient is less than the threshold value. A plurality of the first periods are set,
The photovoltaic power generation output estimation device according to claim 4, characterized in that the estimation unit calculates a representative value of the ratio using the ratio corresponding to the first period in which the correlation coefficient is determined to be equal to or greater than a threshold value, and estimates the estimation target photovoltaic power generation output using the representative value. a display unit that displays a scatter diagram showing a relationship between the correlation coefficient and an error of the estimated value of the estimation target photovoltaic power generation output estimated by the estimation unit with respect to an actual measured value of the estimation target photovoltaic power generation output;
The photovoltaic power generation output estimating device according to claim 5, further comprising: The solar power generation output estimation device according to claim 6, characterized in that the display unit displays the threshold value superimposed on the scatter diagram. The photovoltaic power generation output estimation device according to claim 2, characterized in that the delay time is approximated to 0. The solar power generation output estimation device according to claim 1, characterized in that the solar irradiance data is measurement data or estimated values of the power generation output of a solar power generation facility installed at a location corresponding to the solar irradiance data. The solar power generation output estimation device according to claim 1, characterized in that the solar radiation intensity data is a measured or estimated value of solar radiation intensity measured at a point corresponding to the solar radiation intensity data. A photovoltaic power generation output estimation device that estimates the power generation output of a photovoltaic power generation facility;
a control device that controls a voltage of a power grid using the power generation output estimated by the photovoltaic power generation output estimation device;
Equipped with
The photovoltaic power generation output estimating device includes:
an estimation unit that estimates an estimation target photovoltaic power generation output, which is a power generation output of a photovoltaic power generation facility that is an estimation target, by using solar irradiance data indicating solar irradiance and a residual demand that is a sum of a power consumption and a photovoltaic power generation output of a consumer in which the photovoltaic power generation facility is installed;
an estimation accuracy verification unit that uses correlation information indicating a correlation between the solar irradiance data and the residual demand to determine whether or not the estimation accuracy of the estimation target photovoltaic power generation output satisfies a predetermined accuracy;
A system control system comprising: A photovoltaic power generation output estimation device that estimates the power generation output of a photovoltaic power generation facility;
a supply and demand control device that controls supply and demand of electricity using the power generation output estimated by the photovoltaic power generation output estimation device;
Equipped with
The photovoltaic power generation output estimating device includes:
an estimation unit that estimates an estimation target photovoltaic power generation output, which is a power generation output of a photovoltaic power generation facility that is an estimation target, by using solar irradiance data indicating solar irradiance and a residual demand that is a sum of a power consumption and a photovoltaic power generation output of a consumer in which the photovoltaic power generation facility is installed;
an estimation accuracy verification unit that uses correlation information indicating a correlation between the solar irradiance data and the residual demand to determine whether or not the estimation accuracy of the estimation target photovoltaic power generation output satisfies a predetermined accuracy;
A supply and demand control system comprising: A photovoltaic power generation output estimation device that estimates the power generation output of a photovoltaic power generation facility;
a state management device that indicates a state of a power grid using the power generation output estimated by the photovoltaic power generation output estimation device;
Equipped with
The photovoltaic power generation output estimating device includes:
an estimation unit that estimates an estimation target photovoltaic power generation output, which is a power generation output of a photovoltaic power generation facility that is an estimation target, by using solar irradiance data indicating solar irradiance and a residual demand that is a sum of a power consumption and a photovoltaic power generation output of a consumer in which the photovoltaic power generation facility is installed;
an estimation accuracy verification unit that uses correlation information indicating a correlation between the solar irradiance data and the residual demand to determine whether or not the estimation accuracy of the estimation target photovoltaic power generation output satisfies a predetermined accuracy;
A facility formation support system comprising: A photovoltaic power generation output estimation device estimates an estimation target photovoltaic power generation output, which is a power generation output of a photovoltaic power generation facility to be estimated, by using solar irradiance intensity data indicating solar irradiance and a residual demand, which is a sum of a power consumption and a photovoltaic power generation output at a consumer in which the photovoltaic power generation facility is installed;
A photovoltaic power generation output estimation method, characterized in that the photovoltaic power generation output estimation device determines whether the estimation accuracy of the photovoltaic power generation output to be estimated satisfies a specified accuracy using correlation information indicating the correlation between the solar irradiance data and the residual demand. A step of estimating an estimated photovoltaic power generation output, which is a power generation output of a photovoltaic power generation facility to be estimated, using solar irradiance data indicating solar irradiance and a residual demand, which is a sum of a power consumption and a photovoltaic power generation output of a consumer in which the photovoltaic power generation facility is installed;
determining whether or not the estimation accuracy of the estimation target photovoltaic power generation output satisfies a predetermined accuracy using correlation information indicating a correlation between the solar irradiance data and the residual demand;
A photovoltaic power generation output estimation program characterized by causing a computer to execute the above.

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