JP2015089196A - Estimate power generation amount calculation device, program, and method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a power demand peak cut program, method, and device capable of estimating battery capacity.SOLUTION: A relative sunshine duration calculation unit 101 calculates estimate relative sunshine duration by using transition matrix data 111. A sunshine amount calculation unit 102 calculates an estimate sunshine amount on the basis of estimate relative sunshine duration data 112 and relative sunshine duration/sunshine amount conversion coefficient data 113. A discharge amount calculation unit 103 calculates a discharge power amount on the basis of estimate PV power generation amount data 115 obtained by multiplying estimate sunshine amount data 114 by a conversion coefficient, power consumption data 116, and a peak power amount. A danger degree calculation unit 104 calculates, for each estimation method, a maximum insufficient power amount and total insufficient power amount on the basis of estimate PV power generation amount/discharge power amount data 117.

Description

  The present invention relates to an estimated power generation amount calculation device, a program, and a method.

  With the introduction of storage batteries and solar panels in many homes, attention has been paid to peak cuts in power consumption using both discharge from storage batteries and solar power generation. The peak cut of power consumption means that when the amount of power consumed by a consumer exceeds a certain peak power amount, the normal amount of power supplied from the customer's external system is peaked by power supply by storage battery discharge or solar power generation. It means keeping within the amount of electric power.

  Specifically, a predetermined peak power amount is set for each time, and when the power demand exceeds the peak power amount, power is replenished with PV power from solar power generation and discharged power from the storage battery. Power peak cut is made. The peak cut of power consumption can be used to reduce the amount of normal power supplied during the time period when the normal power amount supplied from the grid to each consumer is large, which is useful for the problem of insufficient power supply in the entire region.

  In addition, by charging the storage battery with low-cost power at midnight hours and using this power during the day, the solar power can be used to generate electricity by using solar panels during solar power. Reduce the corresponding power consumption. Thereby, a consumer can save an electricity bill.

  By the way, the PV power generation amount and the discharge power amount in each time zone have a complementary relationship. For example, there are cases where the amount of power consumed by the consumer is large, or the amount of sunlight is not sufficient because the sunlight is weak. Thus, when the value obtained by subtracting the PV power generation amount from the power consumption amount of the consumer exceeds the peak power amount, the shortage is compensated by the discharge power amount by the storage battery. Therefore, the consumer estimates the storage battery capacity for the purpose of avoiding insufficient discharge from the storage battery for peak cutting of power consumption. Hereinafter, a method for estimating the storage battery capacity will be described with a specific example.

The total discharge amount A is obtained by counting the discharge amount of the storage battery at each time of a certain day. Based on the total discharge amount A, the storage battery capacity is obtained. Since the total discharge amount, that is, the storage battery capacity A has never been small, the following linear programming problems, equations (1) to (3), are used to calculate the discharge amount of the storage battery at each time. In the formulas (1) to (3), the daily peak power amount is Z, the power consumption amount is Di, the PV power generation amount is Mi, the discharge amount at each time is Xi, and the storage battery capacity is A.
min (A) (1)
Z ≧ D1-M1-X1,..., Z ≧ Dn-Mn-Xn (2)
X1 + X2 + ... + Xn = A (3)
In addition, instead of the storage battery capacity A regarding the said Formula (2), you may use the storage battery total charge amount a which shows the total charge amount in a storage battery.

  In order to appropriately estimate the storage battery capacity, the PV power generation amount at each time is estimated. However, since the amount of sunlight changes greatly depending on the weather of the day, the PV power generation amount is usually not stable. Therefore, in order to estimate the PV power generation amount, for example, a Monte Carlo simulation that considers all the possibilities are used. In the Monte Carlo simulation, a probability is allocated to each PV power generation amount by the PV power generation amount by solar power generation at each time, and the PV power generation amount at each time is calculated by using a random number to obtain the PV power generation amount per day. The storage battery capacity is estimated from the result.

JP 2009-284586 A JP-A-5-252671

  There is a problem that there is no method for obtaining the PV power generation amount by solar power generation in a short time when performing peak cut of power consumption using both storage battery discharge and solar power generation.

  For example, when the storage battery capacity is estimated using Monte Carlo simulation, simulations of 100,000 and million are performed to increase the reliability of the estimated value. As a result of increasing the number of simulations, the amount of calculation becomes enormous and the simulation takes a lot of time.

  On the other hand, if the estimated PV power generation amount at each time is set as the minimum power generation amount at each time, the probability that the actual power generation amount is lower than that is extremely low, and the safety is enhanced. However, it is easy to overestimate the storage battery discharge amount at each time, and as a result, the storage battery capacity is overestimated.

  On the other hand, if the estimation of the power generation amount at each time is the average power generation amount at each time, it is rare to overestimate the storage battery discharge amount at each time. However, when the PV power generation amount by solar power generation is small, the storage battery capacity may be insufficient.

  In other words, when estimating the PV power generation amount at each time, the uncertainty of the PV power generation amount is not sufficiently considered, the PV power generation amount is excessively estimated, or the storage battery capacity is insufficient, or conversely, the PV power generation amount is excessively low In some cases, the storage battery capacity is too large. Moreover, even if the estimation accuracy of the PV power generation amount is high, the estimation method in which the calculation amount is enormous takes a long time for calculation and is not realistic.

  The disclosed technology has been made in view of the above, and an object thereof is to provide an estimated power generation amount calculation device, program, and method that can accurately estimate the PV power generation amount in a short time.

  In the first plan, the estimated sunshine rate at one fixed time and the estimated sunshine rate at another time calculated using a transition matrix based on the estimated sunshine rate at one fixed time are all A probability q that is equal to or less than the average sunshine rate is calculated. A process of fixing the estimated sunshine rate at the one time to the maximum sunshine rate within a range where the probability q is equal to or greater than the guarantee probability p. Further, the computer is caused to execute a process of calculating an estimated sunshine rate at another time using a transition matrix based on the estimated sunshine rate at the fixed one time.

  According to the embodiment of the disclosed technology, there is an effect that the PV power generation amount can be estimated accurately in a short time.

FIG. 1 is a functional block diagram illustrating a configuration of a storage battery capacity estimation apparatus according to the first embodiment. FIG. 2 is a diagram illustrating an example of the transition matrix data of the sunshine rate. FIG. 3 is a diagram showing an example of estimated sunshine rate data. FIG. 4 is a diagram showing an example of the sunshine rate / sunshine amount conversion coefficient data. FIG. 5 is a diagram showing an example of estimated sunshine amount data. FIG. 6 is a diagram illustrating an example of estimated PV power generation amount data. FIG. 7 is a diagram illustrating an example of power consumption data. FIG. 8 is a diagram illustrating an example of PV power generation amount / discharge power amount data. FIG. 9 is a diagram showing an example of estimated risk data. FIG. 10 is a flowchart showing a processing procedure for calculating the sunlight rate in the sunlight rate calculating unit. FIG. 11 is a diagram illustrating a first example regarding the transition of the estimated sunshine rate and the average sunshine rate. FIG. 12 is a diagram illustrating a second example regarding the transition of the estimated sunshine rate and the average sunshine rate. FIG. 13 is a diagram showing the sunshine rate at a fixed point at each time set in a range satisfying the condition according to step S25. FIG. 14 is a diagram illustrating a third example regarding the transition of the estimated sunshine rate and the average sunshine rate. FIG. 15 is a flowchart showing a procedure for calculating the estimated storage battery capacity and the degree of risk for each estimation method. FIG. 16 is a diagram illustrating an example of transition matrix data of the PV power generation amount. FIG. 17 is a flowchart illustrating a processing procedure for calculating the PV power generation amount in the discharge amount calculation unit. FIG. 18 is a functional block diagram illustrating the configuration of the storage battery capacity estimation device according to the third embodiment. FIG. 19 is a diagram illustrating an example of estimated PV power generation amount data according to the third embodiment. FIG. 20 is a flowchart illustrating the procedure for calculating the PV power generation amount according to the third embodiment. FIG. 21 is a functional block diagram illustrating the configuration of the storage battery capacity estimation device according to the fourth embodiment. FIG. 22 is a diagram illustrating an example of estimated PV power generation amount data according to the fourth embodiment. FIG. 23 is a flowchart illustrating the procedure for calculating the PV power generation amount according to the fourth embodiment. FIG. 24 is a flowchart showing a processing procedure when the risk A and the demand peak are calculated for each day. FIG. 25 is a diagram illustrating an example of a computer that executes an estimated storage battery capacity calculation program.

  Embodiments of an estimated power generation amount calculation apparatus, program, and method disclosed in the present application will be described below in detail with reference to the drawings. Note that the present invention is not limited to the embodiments. Each embodiment can be appropriately combined within a range in which processing contents do not contradict each other.

  An example of a functional configuration of the estimation apparatus according to the first embodiment will be described. FIG. 1 is a functional block diagram illustrating a configuration of a storage battery capacity estimation apparatus according to the first embodiment. As illustrated in FIG. 1, the estimation device 10 includes an input unit 21, an output unit 22, a control unit 100, and a storage unit 110. The control unit 100 includes a sunshine rate calculation unit 101, a sunshine amount calculation unit 102, a discharge amount calculation unit 103, and a risk level calculation unit 104. The storage unit 110 includes transition matrix data 111, estimated sunshine rate data 112, sunshine rate / sunshine amount conversion coefficient data 113, estimated sunshine amount data 114, and estimated PV power generation amount data 115. Further, the storage unit 110 includes power consumption data 116, estimated PV power generation / discharge power data 117, and estimated risk data 118. In the first embodiment, the sunshine rate calculation unit 101 is an example of a specification unit and an estimation unit. The risk level calculation unit 104 is an example of an acquisition unit and a calculation unit.

  Each function of the control unit 100 can be realized, for example, by a CPU (Central Processing Unit) executing a predetermined program. The storage unit 110 corresponds to, for example, a semiconductor memory device such as a random access memory (RAM), a read only memory (ROM), and a flash memory, and a storage device such as a hard disk or an optical disk.

  The transition matrix data 111 represents the probability that the sunshine rate at the current time changes to a predetermined sunshine rate at the next time in a matrix format. FIG. 2 is a diagram showing an example of the sunshine rate transition matrix data 111. In the transition matrix data 111, the column 111a indicates the sunshine rate at the current time, the row 111b indicates the sunshine rate at the next time, and the matrix 111c indicates the probability that the sunshine rate at the current time transitions to a predetermined sunshine rate at the next time. Show.

  For example, when the sunshine rate at 6:00 at the current time is 0.1, the probability that the sunshine rate at 7:00 at the next time will decrease by 0.1 and become 0 is 0.20. When the sunshine rate at 6 o'clock at the current time is 0.1, the rate of sunshine at 7 o'clock at the next time does not change, and the probability of being 0.1 is 0.50. If the sunshine rate at 6 o'clock at the current time is 0.1, the probability of sunshine increase at 7 o'clock at the next time increases by 0.9 and is 1.0. The sunshine rate calculation unit 101 obtains an estimated sunshine rate at each time using the transition matrix data 111.

  The estimated sunshine rate data 112 is a list of estimated sunshine rate data at each time obtained using the transition matrix data 111. FIG. 3 is a diagram illustrating an example of the estimated sunshine rate data 112. In FIG. 3, the time is associated with the estimated sunshine rate. Details of the method for calculating the estimated sunshine rate will be described later.

  The sunshine rate / sunshine amount conversion coefficient data 113 is obtained by associating each coefficient of the conversion formula used when converting the estimated sunshine rate into the estimated sunshine amount for each time. FIG. 4 is a diagram showing an example of the sunshine rate / sunshine amount conversion coefficient data 113. In FIG. 4, time is associated with coefficient a and coefficient b. A formula for converting the estimated sunshine rate into the estimated amount of sunshine will be described later.

  The estimated sunshine amount data 114 lists the estimated sunshine amount at each time calculated based on the estimated sunshine rate data 112. FIG. 5 is a diagram illustrating an example of the estimated sunshine amount data 114. In FIG. 5, the time is associated with the amount of sunlight. The details of the calculation method for converting the estimated sunshine rate into the estimated sunshine amount will be described later.

  The estimated PV power generation amount data 115 lists the estimated PV power generation amount at each time calculated from the estimated sunshine amount data 114. FIG. 6 is a diagram illustrating an example of the estimated PV power generation amount data 115. In FIG. 6, the time is associated with the estimated PV power generation amount.

  The power consumption data 116 is an enumeration of average power consumption for each consumer at each time. FIG. 7 is a diagram illustrating an example of the power consumption data 116. In FIG. 7, time and power consumption are associated with each other. The average power consumption for each time is obtained, for example, by measuring the power consumption for each time from a switchboard over several days and calculating the average value.

  The estimated PV power generation amount / discharge power amount data 117 corresponds to the estimated PV power generation amount and the discharge power amount at each time. FIG. 8 is a diagram illustrating an example of the estimated PV power generation amount / discharge power amount data 117. In FIG. 8, the time is associated with the estimated PV power generation amount and the discharge power amount. The details of the calculation method of the discharge power amount will be described later.

  The estimated risk data 118 lists the maximum insufficient power amount and the total insufficient power amount obtained for each estimation method. FIG. 9 is a diagram showing an example of the estimated risk data 118. In FIG. 9, the estimation method is associated with the maximum insufficient power amount and the total unexpected power amount. The maximum power shortage and the total power shortage are used as an index indicating the degree of risk when the estimation method is adopted. The details of the method for calculating the maximum power shortage and the total power shortage will be described later.

(Estimated sunshine rate calculation procedure)
The sunshine rate calculation unit 101 creates estimated sunshine rate data 112 based on the average sunshine rate input from the input unit 21 of FIG. 1 and the transition matrix data 111. In addition, an average sunshine rate shows the average value of the sunshine rate of each time measured in several days.

  The sunshine rate calculation unit 101 calculates the sunshine rate at one time so that the probability q that the estimated sunshine rate becomes equal to or less than the average sunshine rate at all times is maximized in a range that is equal to or greater than a preset guarantee probability p. Set. The sunshine rate calculation unit 101 obtains an estimated sunshine rate at each time using the transition matrix data 111 with the sunshine rate at this one time as a starting point. The sunshine rate calculation unit 101 obtains a plurality of combinations of estimated sunshine rates at each time by the following method, for example.

  The sunshine rate calculation unit 101 represents the sunshine rate at each time as a discrete value in 11 steps every 0.1 from 0.0 to 1.0. Note that the number of discrete values may be greater or less than this.

  First, the sunshine rate calculation unit 101 substitutes the initial value 0.0 for all times. Next, the sunshine rate calculation unit 101 adds 0.1 to k (1) indicating the sunshine rate at time 1, and fixes the sunshine rate at time 1 to 0.1. Hereinafter, the sunshine rate at a fixed predetermined time will be referred to as a fixed point.

  Next, the sunshine rate calculation unit 101 calculates k (2) to k (n) excluding k (1) using the transition matrix data 111. These k (2) to k (n) are not uniquely determined, and the route from k (1) to k (n) branches, so there are a plurality of routes. The sunshine rate calculation unit 101 selects all routes having an estimated sunshine rate equal to or less than the average sunshine rate at all times from among a plurality of routes.

  The sunshine rate calculation unit 101 adds the probability of taking one or more selected routes to the probability q. When the calculated probability q is equal to or greater than the guarantee probability p, the sunshine rate calculation unit 101 increases the fixed point at time 1 by 0.1 to 0.2.

  Similarly, the sunshine ratio calculation unit 101 sets a route from k (1) to k (n), calculates the probability q, and compares it with the guarantee probability p. The sunshine ratio calculation unit 101 performs the operation of increasing the fixed point by 0.1 and obtaining the probability q until the probability q becomes smaller than the guarantee probability p.

  On the other hand, when the probability q becomes smaller than the guarantee probability p, the sunshine rate calculation unit 101 decrements k (1), which is a fixed point at time 1, by 0.1. The sunshine rate calculation unit 101 sets this as the estimated sunshine rate of k (1). And the sunshine rate calculation part 101 is calculated by step S24 shown by FIG. 10 about the estimated sunshine rate which concerns on k (2)-k (n), k (2)-k corresponding to the said fixed point. Set the estimated sunshine rate for (n). Details of the calculation procedure of the estimated sunshine rate at the time excluding the fixed point will be described later.

  Also, the sunshine rate calculation unit 101 sets a fixed point by the above process at times 2 to n and similarly performs a process of calculating an estimated sunshine rate at a time other than the time at which the fixed point is set. For this reason, the sunshine rate calculation unit 101 calculates n estimated sunshine rates for each time.

  Next, the process procedure in the sunshine rate calculation part 101 which concerns on Example 1 is demonstrated concretely. FIG. 10 is a flowchart showing the procedure for calculating the sunlight rate in the sunlight rate calculating unit 101. The sunshine rate calculation unit 101 obtains an estimated sunshine rate at each time using the transition matrix data 111.

  The sunshine rate calculation unit 101 first inserts 1 into a variable t indicating time (step S21). Here, time 1 indicates the start time for obtaining the estimated sunshine rate, and time n indicates the end time. For example, if time 1 is 6 o'clock start time and time n is 18 o'clock end time, time 2 is 7 o'clock, time 3 is 8 o'clock, and time 13 is 18 o'clock end time.

  Next, the sunshine rate calculation unit 101 inserts an initial value 0.0 into variables k (1) to k (n) indicating the estimated sunshine rate at each time (step S22). Next, the sunshine rate calculation unit 101 increases the estimated sunshine rate by one level by adding 0.1 to k (1) (step S23).

  The sunshine rate calculation unit 101 calculates k (2) to k (n) indicating the estimated sunshine rate at each time excluding k (1) using the transition matrix (step S24). In addition, the detail of the calculation method of the estimated sunlight rate at each time is mentioned later.

  The sunshine rate calculation unit 101 compares the estimated sunshine rate with the average sunshine rate at each time, and calculates a probability q that the estimated sunshine rate is equal to or less than the average sunshine rate at all times (step S25). Specifically, the sunshine rate calculation unit 101 sets the estimated sunshine rate at time t as k (t) and the average sunshine rate as SRR (t), and q = Prob {SRR (1) ≧ k (1), SRR. (2) ≧ k (2),..., SRR (n) ≧ k (n)}, the probability q is calculated. Details of the calculation method of the probability q will be described later.

  When the probability q is equal to or greater than the guaranteed probability p and k (t) is equal to or less than 1.0 (Yes at Step S25), the sunshine rate calculating unit 101 returns to Step S23 and adds 0.1 to k (1). 0.2, and the process of step S24 and step S25 is repeated.

  When the probability q becomes smaller than the guarantee probability p or when k (t) becomes larger than 1.0 (No in step S25), the sunshine ratio calculating unit 101 exits the loop and changes from 0 (0) to 0. 1 is subtracted (step S26).

  Further, the sunshine rate calculation unit 101 adds 1 to the variable t indicating the time (step S27), and compares the variable t with the variable n indicating the final time (step S28). When the variable t is equal to or less than the variable n (No at Step S28), the sunshine rate calculating unit 101 returns to Step S22 and performs the same process. On the other hand, if the variable t is larger than the variable n (Yes in step S28), the sunshine rate calculation unit 101 ends the process.

  For example, if t is 1 at the time of step S26, the sunshine rate calculation unit 101 adds 1 to t in step S27 and sets t to 2. In this case, the sunshine rate calculation unit 101 does not satisfy the conditional expression t> n in step S28, and returns the process to step S22. Thereafter, the sunshine rate calculation unit 101 performs the process for k (2) in the same manner as k (1), and repeats the process until the conditional expression related to step S28 is satisfied.

  It should be noted that the sunshine rate calculation unit 101 assigns each estimated sunshine rate from k (1) to k (n) excluding k (t) in step S24 to, for example, a LIFO (Last In First Out) format may be stored in the storage unit 110. Alternatively, the sunshine rate calculation unit 101 omits step S24, holds only the estimated sunshine rate at k (t) as a fixed point in the list, and after the process is finished, excluding k (t) afterwards Each estimated sunshine rate from (1) to k (n) may be calculated. Thereby, the sunshine rate calculation part 101 can save the temporary storage area which memorize | stores an estimated sunshine rate.

(Procedure for calculating probability q)
Next, the calculation method of the probability q performed in step S25 of FIG. 10 will be described with a specific example.

  FIG. 11 is a diagram illustrating a first example regarding the transition of the estimated sunshine rate and the average sunshine rate. The vertical axis indicates the sunshine rate at each time, and the horizontal axis indicates the time. In FIG. 11, the time is limited to three of 1 to 3 in order to simplify the description.

  In FIG. 11, the solid line indicates the transition of the estimated sunshine rate, and the first route 302 and the second route 303 are exemplified, but there are actually other routes. The sunshine rate calculation unit 101 sets the fixed point at the position of the sunshine rate 0.1 at time 1. A dotted line 301 indicates the transition of the average sunshine rate. The fixed point indicates k (t) set in step S23 in FIG. 10, and is the starting point of all routes.

  The sunshine rate calculation unit 101 acquires, from the transition matrix data 111, the probability of transition from the sunshine rate at the previous time to the sunshine rate at the current time. For example, in the first route 302, the sunshine rate calculation unit 101 acquires from the transition matrix data 111 a probability 0.50 of transition from the fixed point at time 1 to the sunshine rate 0.1 at time 2, and the sunshine at time 2 Similarly, a probability 0.25 of transition from a rate of 0.1 to a sunshine rate of 0.2 at time 3 is acquired. The sunshine ratio calculation unit 101 calculates the probability of taking the route of the first route 302 by multiplying 0.50 by 0.25.

  And the sunshine rate calculation part 101 adds the probability 0.125 which takes the path | route of the 1st route 302 to the probability q because the sunshine rate is below an average sunshine rate at all times in the 1st route 302. To do.

  On the other hand, the sunshine rate calculation unit 101 acquires, from the transition matrix data 111, the probability 0.04 of transition from the fixed point at time 1 to the sunshine rate 0.3 at time 2 in the second route 303, and the sunshine at time 2 Similarly, a probability of 0.1 changing from a rate of 0.3 to a sunshine rate of 0.4 at time 3 is acquired. The sunshine ratio calculation unit 101 calculates a probability 0.004 of taking the route of the second route 303 by multiplying 0.04 by 0.1.

  However, the sunshine rate calculation unit 101 does not add the probability 0.004 of taking the route of the second route 303 to the probability q because the sunshine rate is equal to or higher than the average sunshine rate at the time 3 in the second route 303. .

  That is, the sunshine rate calculation unit 101 calculates the probability of taking the route for all routes in which the sunshine rate at each time of times 1 to 3 changes below the average sunshine rate, and adds them to the probability q. Then, if the calculated probability q is greater than or equal to the guaranteed probability p, the sunshine rate calculating unit 101 raises the fixed point at time 1 by one step to 0.2. The sunshine rate calculation unit 101 calculates the probability q in the same manner even when the fixed point is set to 0.2. On the other hand, when the probability q is smaller than the guarantee probability p, the sunshine rate calculation unit 101 ends the calculation process of the probability q at time 1 and sets a fixed point at time 2.

  FIG. 12 is a diagram illustrating a second example regarding the transition of the estimated sunshine rate and the average sunshine rate. The sunshine rate calculation unit 101 sets a fixed point at time 2 in the second example. When a fixed point is set at time 2, the sunshine ratio calculation unit 101 includes not only the transition to time 3 but also the transition from time 1 which is the time before time 2 to the route, and the probability of taking each route. calculate.

  The sunshine rate calculation unit 101 has a sunshine rate of 0.1, 0.2, and 0.1 in order from the first route 402 to times 1 to 3, respectively, and the sunshine rate is less than or equal to the average sunshine rate 401 at any time. Therefore, the probability that the first route 402 can be taken is added to the probability q. On the other hand, the sunlight rate calculation unit 101 determines that the second route 403 has a sunlight rate of 0.3, 0.2, and 0.3 in order from time 1 to 3, respectively, and the sunlight rate at time 1 is based on the average sunlight rate 401. Since it is large, the probability that the second route 403 can be taken is not added to the probability q.

  That is, the sunshine rate calculation unit 101 calculates the probability of taking the route for all routes whose sunshine rates at all times of the times 1 to 3 are equal to or less than the average sunshine rate 401, and adds them to the probability q. Then, when the probability q is equal to or greater than the guarantee probability p, the sunshine rate calculating unit 101 calculates the probability q in the same manner by setting the fixed point at time 2 as 0.3 by one step. On the other hand, if the probability q is smaller than the guarantee probability p, the sunshine rate calculation unit 101 finishes the calculation process of the probability q at time 2 and sets the fixed point to 0.2 at time 3.

(Calculation of estimated sunshine rate by time)
FIG. 13 is a diagram showing the sunshine rate at a fixed point at each time set in a range satisfying the condition according to step S25. As shown in FIG. 13, as a result of setting a fixed point in a range where the probability q is equal to or greater than the guarantee probability p at each time, the fixed point at each time is calculated. Based on a fixed point at each time, an estimated sunshine rate at another time is calculated. For example, the sunshine rate calculation unit 101 calculates the expected value of the estimated sunshine rate at times 2 to n by setting a fixed point 0.1 at time 1 and sets a fixed point 0.2 at time 2 Thus, the expected value of the estimated sunshine rate at time 1 and time 3 to n is calculated. Hereinafter, specifically, the calculation procedure of the estimated sunshine rate other than the time at which the fixed point is set in step S24 by the sunshine rate calculation unit 101 will be described in more detail.

  The sunshine rate calculation unit 101 determines the maximum value of the sunshine rate at the fixed point by increasing the sunshine rate at the fixed point by 0.1 in a range where the probability q is equal to or greater than the guarantee probability p. Furthermore, the sunshine rate calculation part 101 calculates | requires the average value of the sunshine rate of time other than a fixed point. The sunshine rate calculation unit 101 may calculate the sunshine rate at times other than the fixed point every time the sunshine rate at the fixed point is increased by 0.1, or when the fixed point is the maximum value of the sunshine rate. Only may be calculated.

  Here, the procedure for calculating the average value of the sunshine rates at times 2 and 3 when the fixed point is set to 0.1 at time 1 will be described using the example of FIG. Here, it is assumed that the route from the fixed point to time 3 is only the first route 302 and the second route 303.

  First, the procedure for calculating the average value of the sunshine rate at time 2 will be described. The sunshine rate calculation unit 101 calculates a probability 0.125 of taking the first route 302. Also, the sunshine rate calculation unit 101 calculates a probability 0.004 of taking the second route 303. The sunshine rate calculation unit 101 takes a value 0.0125 obtained by multiplying the probability 0.125 of taking the first route 302 by the sunshine rate 0.1 at time 2 of the first route 302 and the second route 303. An expected value 0.0137 of the sunshine rate at time 2 is calculated by adding a value 0.0012 obtained by multiplying the probability 0.004 by the sunshine rate 0.3. Then, the sunshine rate calculation unit 101 sets this to the estimated sunshine rate at time 2.

  Next, a procedure for calculating the average value of the sunshine rate at time 3 will be described. The sunshine rate calculation unit 101 takes a value 0.025 obtained by multiplying the probability 0.125 of taking the first route 302 by the sunshine rate 0.2 at time 3 of the first route 302, and the second route 303. The value 0.0016, which is obtained by multiplying the probability 0.004 by the sunshine rate 0.4, is added. Accordingly, the sunshine rate calculation unit 101 calculates the expected value of sunshine rate 0.0266 at time 3. Then, the sunshine rate calculation unit 101 sets this to the estimated sunshine rate at time 3.

  The sunshine rate calculation unit 101 sets the estimated sunshine rate at each time in this way, and creates estimated sunshine rate data 112.

(Calculation of estimated amount of sunshine by time)
The sunshine amount calculation unit 102 creates estimated sunshine amount data 114 based on the estimated sunshine rate data 112 and the sunshine rate / sunshine amount conversion coefficient data 113. For example, the sunshine amount calculation unit 102 calculates the estimated sunshine amount Vi at the time i by calculating each coefficient of the sunshine rate / sunshine amount conversion coefficient data 113 corresponding to the time i and the estimated sunshine rate Ni at the time i as follows: It is calculated by applying to (4).
Vi = aNi + b (4)

  For example, according to FIG. 4, when calculating the estimated amount of sunshine at time 1, the sunshine amount calculation unit 102 has a coefficient a = 13.3, a coefficient b = 0.14, and Ni at 6 o'clock at time 1 is 0.30. = 13.3 × 0.30 + 0.14 = 4.13. The sunshine amount calculation unit 102 calculates the sunshine amount at each time in this way.

(Calculation of estimated PV power generation by time)
The discharge amount calculation unit 103 creates estimated PV power generation amount data 115 based on the estimated sunshine amount data 114. The discharge amount calculation unit 103 calculates the estimated PV power generation amount at each time by multiplying the estimated sunshine amount by a conversion factor 0.75.

(Calculation of estimated discharge energy by time)
The discharge amount calculation unit 103 creates estimated PV power generation amount / discharge power amount data 117 based on the peak power, the estimated PV power generation amount data 115, and the power consumption amount data 116. The discharge amount calculation unit 103 sets Z as the peak power amount, Di as the power consumption amount at the time i, Mi as the PV power generation amount at the time i, and Xi as the discharge power amount at the time i, and applies the following equation (5). Thus, the amount of discharge power at each time is calculated.
Xi = Di-Mi-Z (5)

  The discharge amount calculation part 103 totals the discharge electric energy of each time, and estimates storage battery capacity. The discharge amount calculation unit 103 calculates an estimated value of the same number of storage battery capacities as the number of times for setting a fixed point.

  As described above, the sunshine rate calculation unit 101 calculates the combination of the estimated sunshine rates at each time for the time at which a fixed point is set. For example, when a fixed point is set up to time 7 as shown in FIG. 13, the sunshine rate calculation unit 101 calculates combinations of estimated sunshine rates at seven different times.

  Therefore, the sunshine rate calculation unit 101, the sunshine amount calculation unit 102, and the discharge amount calculation unit 103 calculate a combination of the estimated PV power generation amount and the estimated discharge power amount for the number of times at which fixed points are set. Here, a case where a fixed point is set at time 1 is an estimation method a, and a case where a fixed point is set at time 2 is an estimation method b. A case where a fixed point is set at time 13 is set as an estimation method m.

(Calculation of maximum power shortage and total power shortage by estimation method)
Based on the transition matrix data 111, the risk level calculation unit 104 calculates the maximum power shortage and the total power shortage for each estimation method. The maximum power shortage and the total power shortage are indicators of the risk level by selecting each estimation method.

(Calculation of maximum power shortage)
The risk level calculation unit 104 shifts the estimated PV power generation amount at time i to Mi, the average power generation amount at time i to Yi, and the estimated PV power generation amount Mt-1 at time t-1 to the estimated PV power generation amount Mt at time t. Let p (Mt−1, Mt) be the probability of performing, and p be the guarantee probability. At this time, the risk level calculation unit 104 can obtain the maximum power shortage amount by applying the following equation (6).

  The procedure for calculating the maximum power shortage will be described in more detail. The risk level calculation unit 104 selects a route that is larger than the average sunshine rate at a certain time among the routes that show the transition of the estimated sunshine rate in step S25 of FIG. The degree-of-risk calculation unit 104 calculates a difference value when the difference value obtained by subtracting the average sunshine rate from the estimated sunshine rate among the times in this route is maximized.

  The risk level calculation unit 104 calculates the PV power generation amount corresponding to the difference value based on the difference value of the estimated sunshine rate to obtain the maximum difference PV power generation amount.

  The risk level calculation unit 104 calculates the probability p (M1, M2) p (M2, M3)... P (Mn-1, Mn) that the maximum difference PV power generation amount takes the route. The risk level calculation unit 104 multiplies the probability of taking this route by the maximum difference PV power generation amount.

  The risk level calculation unit 104 performs the operation of multiplying the PV power generation amount by the probability of taking the route for other routes in which the estimated PV power generation amount becomes larger than the average PV power generation amount at a certain time, and adds these. Calculate the total value. The average PV power generation amount is an average value of the PV power generation amount at each time measured during a predetermined number of days.

  The risk level calculation unit 104 divides this total value by the probability 1-p that a certain estimated PV power generation amount is larger than the average PV power generation amount. The risk level calculation unit 104 may use the probability 1-q instead of the probability 1-p that is greater than the average sunshine rate at a certain time. Note that q indicates q calculated in step S25 of FIG.

  Next, a specific example will be described. FIG. 14 is a diagram illustrating a third example regarding the transition of the estimated sunshine rate and the average sunshine rate. The degree-of-risk calculation unit 104 compares the first route 501 that shows the change in the average sunshine rate with a dotted line and the second route 502 that shows the change in the estimated sunshine rate with a solid line. At time 2 and time 3, the risk level calculation unit 104 exceeds the sunshine rate of the first route 501, and the difference value at time 3 is larger. The difference value 1.6 in 3 is acquired. Then, the risk level calculation unit 104 sets the difference value 1.6 at time 3 to the maximum difference value.

  The risk level calculation unit 104 converts the maximum difference value 1.6 into the PV power generation amount, and obtains the maximum difference PV power generation amount. The degree-of-risk calculation unit 104 multiplies this maximum differential PV power generation amount by a probability 0.02 of taking the second route 502. The degree-of-risk calculation unit 104 performs an operation of multiplying the maximum difference PV power generation amount by the probability of taking the route in other routes that are larger than the average sunshine rate at a certain time, and calculates each of the calculated maximum difference values. To get the total value. Further, the risk level calculation unit 104 divides this total value by a probability of 0.1 obtained by subtracting a guarantee probability of 0.9 from 1. Thereby, the maximum power shortage can be calculated.

(Calculation of total power shortage)
The risk level calculation unit 104 shifts the estimated PV power generation amount at time i to Mi, the average power generation amount at time i to Yi, and the estimated PV power generation amount Mt-1 at time t-1 to the estimated PV power generation amount Mt at time t. Let p (Mt−1, Mt) be the probability of performing, and p be the guarantee probability. At this time, the risk level calculation unit 104 can obtain the total power shortage amount by applying the following equation (7).

  This will be specifically described with reference to FIG. The degree-of-risk calculation unit 104 acquires the difference value 0.8 at time 2 when the estimated sunshine rate exceeds the average sunshine rate, and the difference value 1.6 at time 3, and converts them into PV power generation amounts. The risk degree calculation unit 104 adds the PV power generation amounts at time 2 and time 3 to obtain a total value. If the risk level calculation unit 104 regards this total value as the maximum difference PV power generation amount when calculating the maximum shortage power amount, and subsequently calculates in the same manner, the total shortage power amount can be calculated.

(Storage battery capacity estimation processing procedure)
Next, the procedure of the storage battery capacity estimation process according to the first embodiment will be described. FIG. 15 is a flowchart showing a procedure for calculating the estimated storage battery capacity and the degree of risk for each estimation method.

  The sunshine rate calculating unit 101 calculates the estimated sunshine rate using the transition matrix data 111 (step S11). The calculated estimated sunshine rate is stored in the storage area of the estimated sunshine rate data 112 in the storage unit 110.

  The sunshine amount calculation unit 102 calculates the estimated sunshine amount based on the estimated sunshine rate data 112 and the sunshine rate / sunshine amount conversion coefficient data 113 (step S12). The calculated estimated sunshine amount is stored in the storage area of the estimated sunshine amount data 114 in the storage unit 110.

  In the discharge amount calculation unit 103, the discharge power amount is calculated based on the estimated PV power generation amount data 115 obtained by multiplying the estimated sunshine amount data 114 by the conversion factor, the power consumption amount data 116, and the peak power amount ( Step S13). The calculated discharge power amount is stored in the storage area of the estimated PV power generation amount / discharge power amount data 117 in the storage unit 110 together with the estimated PV power generation amount.

  Based on the estimated PV power generation amount / discharge power amount data 117, the risk level calculation unit 104 calculates the maximum insufficient power amount and the total insufficient power amount for each estimation method (step S14). The calculated maximum power shortage and total power shortage are stored in the storage area of the estimated risk data 118 in the storage unit 110.

  The maximum power shortage and the total power shortage can be an index indicating the degree of risk due to the adoption of each estimation method. The user appropriately selects whether to select an estimation method based on the maximum insufficient power amount or to select an estimation method based on the total unexpected power amount.

  In the first embodiment, the estimated sunshine rate at each time is calculated using the transition matrix of the sunshine rate and converted into the PV power generation amount at each time. However, the transition matrix of the sunshine rate is converted into the transition matrix of the PV power generation amount. It may be converted. First, the amount of sunlight calculation part 102 converts the transition matrix of the sunlight rate which concerns on the transition matrix data 111 into the transition matrix of the amount of sunlight. At this time, as shown in FIG. 4, the sunshine amount calculation unit 102 calculates a transition matrix for each time because the coefficient for converting the sunshine rate into the sunshine amount differs for each time. For this reason, the amount of sunlight calculation part 102 produces | generates the same number of transition matrices as the time number n. And the discharge amount calculation part 103 converts the transition matrix of each sunshine amount into the transition matrix of PV power generation amount. In the second embodiment, the discharge amount calculation unit 103 is an example of a specifying unit and an estimation unit.

  A procedure for converting the transition matrix of the sunshine rate into the transition matrix of the PV power generation amount will be described using a specific example. FIG. 16 is a diagram illustrating an example of transition matrix data of the PV power generation amount. The sunshine amount calculation unit 102 and the discharge amount calculation unit 103 convert 111a indicating the sunshine rate before the transition in FIG. 2 into 211a indicating the PV power generation amount at time 1 before the transition in FIG. Moreover, the sunshine amount calculation part 102 and the discharge amount calculation part 103 convert 111b which shows the sunshine rate after the transition of FIG. 2 into 211b which shows the PV power generation amount of the time 1 after the transition of FIG. Further, 211c indicating the probability of the PV power generation amount transition in FIG. 16 may be the same value as 111c in FIG.

  For example, the sunshine amount calculation unit 102 applies the sunshine rate 0 to Equation (2) to calculate the sunshine amount 0.14. The discharge amount calculation unit 103 calculates the PV power generation amount 0.105 by multiplying the sunlight amount 0.14 by the conversion factor 0.75, and sets it to 211a. Further, the sunshine amount calculation unit 102 calculates the sunshine amount 1.47 by applying the sunshine rate 0.1 to the equation (2). The discharge amount calculation unit 103 calculates the PV power generation amount 1.1 by multiplying the sunshine amount 1.47 by the conversion factor 0.75, and sets it to 211a. In this way, the estimating apparatus 10 calculates the PV power generation amount at a certain time corresponding to each sunshine rate from 0 to 1.0 and sets it to 211a. Similarly, the estimating apparatus 10 calculates the PV power generation amount at the next time and sets it to 211b.

  The discharge amount calculation unit 103 obtains the estimated PV power generation amount at each time by using the transition matrix data 111 converted into the transition matrix of the PV power generation amount. The calculation procedure of the estimated PV power generation amount at each time will be specifically described with reference to FIG. FIG. 17 is a flowchart illustrating a processing procedure for calculating the PV power generation amount in the discharge amount calculation unit 103.

  First, the discharge amount calculation unit 103 inserts 1 into a variable t indicating time and 1 into a variable m indicating a stage of the estimated PV power generation amount (step S31). Since 1 is set in the variable t, a fixed point is set at time 1. Here, time 1 indicates the start time for obtaining the estimated PV power generation amount, and time n indicates the end time. The variable m corresponds to the estimated PV power generation amounts 211a and 211b in FIG. For example, when m is 1, the estimated PV power generation amount is 0.105, and when m is 2, the estimated PV power generation amount is 1.1.

  As shown in FIG. 17, the discharge amount calculation unit 103 next calculates the estimated PV power generation amount 0.105 when m is 1 in variables lm (1) to lm (n) indicating the estimated PV power generation amount at each time. Is inserted (step S32). Here, the variable lm (t) indicates the m-th estimated PV power generation amount at time t. For example, the estimated PV power generation amount at the second stage at time 1 is represented by l 2 (1), and the estimated PV power generation amount can be obtained from 211a and becomes 1.1.

  Next, the discharge amount calculation unit 103 adds 1 to m indicating the stage of the estimated PV power generation amount, thereby obtaining l2 (1). As shown in FIG. (1) = 1.1 (step S33).

  The discharge amount calculation unit 103 calculates l2 (2) to l2 (n) indicating the estimated PV power generation amount at each time excluding l2 (1) using the transition matrix (step S34).

  The discharge amount calculation unit 103 compares the estimated PV power generation amount with the average PV power generation amount at each time, and calculates a probability q that the estimated PV power generation amount is equal to or less than the average PV power generation amount at all times (step S35). Specifically, the discharge amount calculation unit 103 sets the estimated PV power generation amount at the m-th stage at time t as lm (t) and the average PV power generation amount as L (t), and q = Prob {L (1) ≧ The probability q is calculated from lm (1), L (2) ≧ lm (2),..., L (n) ≧ lm (n)}.

  If the probability q is equal to or greater than the guaranteed probability p and m is equal to or less than 1.0 (Yes in step S35), the discharge amount calculation unit 103 returns to step S33 to add 1 to m to obtain l3 (1). The process of S34 and step S35 is repeated.

  When the probability q is smaller than the guaranteed probability p or when m is larger than 1.0 (No in step S35), the discharge amount calculation unit 103 exits the loop and subtracts 1 from m (step S36).

  Furthermore, the discharge amount calculation unit 103 adds 1 to the variable t indicating time (step S37), and compares the variable t with the variable n indicating the final time (step S38). When the variable t is equal to or less than the variable n (No at Step S38), the discharge amount calculation unit 103 returns to Step S32 and performs the same process. On the other hand, when the variable t is larger than the variable n (Yes in step S38), the discharge amount calculation unit 103 ends the process.

  For example, if t is 1 at the time of step S36, the discharge amount calculation unit 103 adds 1 to t in step S37 and sets t to 2. In this case, since the discharge amount calculation unit 103 does not satisfy the conditional expression t> n in step S38, the process returns to step S32. Thereafter, the discharge amount calculation unit 103 performs the process for lm (2) similarly to lm (1), and repeats the process until the conditional expression related to step S38 is satisfied. As described above, the estimated PV power generation amount at the fixed point set at each time is calculated.

  Based on the estimated PV power generation amount at a fixed point set at a certain time, the estimated PV power generation amount at a time other than the fixed point is calculated. Can be calculated.

  In the transition matrix data 111, 111c indicating the probability that the sunshine rate changes or 211c indicating the probability that the PV power generation amount changes may be changed for each time. For example, the transition matrix from 12:00 to 14:00 may set the probability of transition at a high sunshine rate higher than other times. Thereby, the sunshine rate calculation part 101 and the discharge amount calculation part 103 can make the transition matrix data 111 more suitable for the transition of the actual sunshine rate or the PV power generation amount.

  Further, the degree of danger such as the maximum power shortage and the total power shortage may be calculated on the basis of the estimated PV generation amount, on the basis of the estimated amount of sunlight, on the basis of the estimated amount of sunlight. The start time and end time for calculating the estimated sunshine rate can be arbitrarily selected.

  An example of a functional configuration of the estimation apparatus according to the third embodiment will be described. FIG. 18 is a functional block diagram illustrating the configuration of the storage battery capacity estimation device according to the third embodiment. As illustrated in FIG. 18, the estimation device 20 includes an input unit 31, an output unit 32, a control unit 200, and a storage unit 210. The control unit 200 includes a sunshine rate calculation unit 201, a sunshine amount calculation unit 202, a discharge amount calculation unit 203, a risk level calculation unit 204, and a comparison unit 205. The storage unit 210 includes transition matrix data 211, estimated sunshine rate data 212, sunshine rate / sunshine amount conversion coefficient data 213, estimated sunshine amount data 214, and estimated PV power generation amount data 215. Further, the storage unit 210 includes power consumption data 216, estimated PV power generation / discharge power data 217, and estimated risk data 218. In the first embodiment, the sunshine rate calculating unit 201 is an example of a specifying unit and an estimating unit. The risk level calculation unit 204 is an example of an acquisition unit and a calculation unit.

  Next, estimated PV power generation amount data according to the third embodiment will be described with reference to FIG. FIG. 19 is a diagram illustrating an example of estimated PV power generation amount data according to the third embodiment. According to the example shown in FIG. 19, the estimated PV power generation amount data 214 associates the guarantee probability (p) with the power generation amount at each time from the start time ts to the end time te. The estimation device 20 holds the estimated PV power generation amount at each time corresponding to each security probability in the estimated PV power generation data 214 for each security probability (p) set in a range that satisfies the conditions described later. For example, in FIG. 19, the estimation device 20 satisfies the conditions described later in the range of 1.0 to 0.6, and the guarantee probabilities are 1.0, 0.9, 0.8, 0.7, The estimated PV power generation amount at each time corresponding to each of 0.6 is held in the estimated PV power generation amount data 214.

  In the third embodiment, the estimation device 20 may calculate the estimated PV power generation amount based on, for example, the minimum guaranteed probability p set in a range where the maximum insufficient power amount and the total insufficient power amount satisfy predetermined conditions. Good. Specifically, the estimation device 20 may calculate the estimated PV power generation amount by the following procedure. The sunshine rate calculation unit 201 calculates an estimated sunshine rate when the guarantee probability is 1.0 according to the method of the first embodiment. The sunshine amount calculation unit 202 calculates an estimated sunshine amount based on the calculated estimated sunshine rate. Then, the discharge amount calculation unit 203 calculates an estimated PV power generation amount based on the calculated estimated amount of sunshine.

  Furthermore, the risk level calculation unit 204 calculates the maximum power shortage amount and the total power shortage amount based on the difference between the calculated estimated PV power generation amount and the average PV power generation amount. At this time, the comparison unit 205 determines whether or not each of the calculated maximum power shortage and total power shortage is within a preset threshold value.

  The estimation device 20 stores the calculated estimated PV power generation amount 214 in the estimated PV power generation amount data 214 when both the maximum insufficient power amount and the total insufficient power amount are equal to or less than the threshold value. Then, the estimation device 20 calculates the estimated PV power generation amount, the maximum insufficient power amount, and the total insufficient power amount when the guarantee probability is 0.9 in the same procedure as described above. Further, the comparison unit 205 determines whether each of the calculated maximum power shortage and total power shortage is within a preset threshold value. As described above, the estimation device 20 reduces the guaranteed probability by 0.1 and reduces the estimated PV power generation amount, the maximum shortage power amount, and the total shortage power amount as long as each of the maximum shortage power amount and the total shortage power amount is within the threshold. Is calculated. Then, the estimation device 20 holds the estimated PV power generation amount calculated within the range satisfying the above condition in the estimated PV power generation amount data 214.

  Then, the comparison unit 205 selects the estimated PV power generation calculated most recently when either the maximum power shortage or the total power shortage is greater than the threshold. That is, the comparison unit 205 selects the estimated PV power generation amount corresponding to the minimum guarantee probability p set within the range where the maximum insufficient power amount and the total insufficient power amount are within the threshold. Then, the discharge amount calculation unit 203 calculates the storage battery capacity based on the selected estimated PV power generation amount. Thereby, the estimation apparatus 20 can calculate the maximum storage battery capacity in the range of the allowable maximum insufficient power amount and the total insufficient power amount. Note that the estimation device 20 may calculate the estimated PV power generation amount by the method of the second embodiment.

(Processing flow in Example 3)
Next, the procedure for calculating the PV power generation amount according to the third embodiment will be specifically described with reference to FIG. FIG. 20 is a flowchart illustrating the procedure for calculating the PV power generation amount according to the third embodiment. First, the estimating apparatus 20 substitutes “1.0” for the guarantee probability p (step S40). The estimating apparatus 20 substitutes the threshold value of the risk A indicating the maximum insufficient power amount into KA (step S41). Further, the estimating device 20 substitutes the threshold value of the risk level B indicating the total insufficient power amount into KB (step S42). Hereinafter, the maximum power shortage amount is referred to as a risk level A, and the total power shortage amount is referred to as a risk level B.

  The estimation device 20 calculates the estimated PV power generation amount M (p) corresponding to the guarantee probability p in the same procedure as in the first embodiment (step S43). The risk level calculation unit 204 calculates the maximum power shortage amount, that is, the risk level kA (p) of the estimated PV power generation amount based on the difference between the estimated sunshine rate and the average sunshine rate in the same procedure as in the first embodiment. (Step S44). Further, the risk level calculation unit 204 calculates the total power shortage amount, that is, the risk level kB (p) of the estimated PV power generation amount in the same procedure as in the first embodiment based on the difference between the estimated sunshine rate and the average sunshine rate. Calculate (step S45).

  The comparison unit 205 determines whether or not the degree of risk kA (p) is less than or equal to the threshold KA (step S46). When the degree of risk kA (p) is greater than the threshold value KA (step S46 No), the comparison unit 205 adds the reduction probability Δp to the security probability p (step S49) and ends the process. On the other hand, when the degree of risk kA (p) is equal to or less than the threshold value KA (step S46 Yes), the comparison unit 205 proceeds to the process of step S47.

  The comparison unit 205 determines whether or not the degree of risk kB (p) is less than or equal to the threshold KB (step S47). When the degree of risk kB (p) is larger than the threshold KB (step S47 No), the comparison unit 205 adds the reduction probability Δp to the security probability p (step S49) and ends the process. On the other hand, when the degree of risk kB (p) is less than or equal to the threshold KB (step S47 Yes), the comparison unit 205 subtracts the reduction probability Δp from the guarantee probability p (step S48), and returns to the process of step S43. That is, the comparison unit 205 sets a lower guarantee probability p−Δp and causes the estimation device 20 to perform the above processing (steps S43 to S45).

  In addition, although the estimation apparatus 20 set the threshold value to both the risk A and the risk B, it is not limited to this. For example, a threshold value may be set for either the risk level A or the risk level B.

  An example of a functional configuration of the estimation apparatus according to the fourth embodiment will be described. FIG. 21 is a functional block diagram illustrating the configuration of the storage battery capacity estimation device according to the fourth embodiment. As illustrated in FIG. 21, the estimation device 30 includes an input unit 41, an output unit 42, a control unit 300, and a storage unit 310. The control unit 300 includes a sunshine rate calculation unit 301, a sunshine amount calculation unit 302, a discharge amount calculation unit 303, a risk level calculation unit 304, and an update unit 306. The storage unit 310 includes transition matrix data 311, estimated sunshine rate data 312, sunshine rate / sunshine amount conversion coefficient data 313, estimated sunshine amount data 314, estimated PV power generation amount data 315, and estimated risk level data 318. Have Furthermore, the storage unit 310 includes power demand data 319, charge / discharge plan data 320, optimal charge / discharge plan data 321, and weather data 322. In the fourth embodiment, the sunshine rate calculation unit 301 is an example of a specifying unit and an estimation unit. The risk level calculation unit 304 is an example of an acquisition unit and a calculation unit.

  Next, estimated PV power generation amount data according to the fourth embodiment will be described with reference to FIG. FIG. 22 is a diagram illustrating an example of estimated PV power generation amount data according to the fourth embodiment. According to the example shown in FIG. 22, the estimated PV power generation amount data 315 associates the guarantee probability (p) with the power generation amount at each time from the start time ts to the end time te. The estimated PV power generation amount data 314 according to the fourth embodiment is different from the estimated PV power generation amount data 215 of the third embodiment in that the security probability of the entire range is maintained from 1.0 to 0.1.

In the fourth embodiment, for example, the estimation device 30 calculates a demand peak and a maximum insufficient power amount from an estimated PV power generation amount related to each guarantee probability, and adds the calculated demand peak and the maximum insufficient power amount. You may select the estimated PV electric power generation amount when the addition value becomes the minimum. Specifically, the estimation device 30 may select the estimated PV power generation amount by the following procedure. First, the estimation device 30 sets the guarantee probability p to 1.0, the peak value Zmin including the minimum risk level to 10 ¹⁰ , and 1 at time t. Note that estimation device 30 has been set to Zmin to 10 ^10, not limited thereto, Zmin may use other values if higher than the value of Zmin that can be assumed value. Further, the minimum risk-included peak value indicates a minimum value among the total values of the risk A and the demand peak calculated for each guarantee probability.

  The estimation device 30 calculates the estimated PV power generation amount when the guarantee probability is 1.0 by the method of the first embodiment. Further, the risk level calculation unit 204 calculates the risk level A, that is, the maximum insufficient power amount kA (p). On the other hand, the estimation device 30 calculates a demand peak Z (p) corresponding to the guarantee probability p based on the demand power data and the charge / discharge plan data. Note that the demand peak Z (p) indicates the peak power at the time when the maximum value is reached among the peak powers calculated by cutting the power consumption amount at each time when the guarantee probability is p. In the fourth embodiment, the average value of the risk level A and the demand peak is calculated based on the risk level A and the demand peak calculated each day. Details regarding the processing will be described later.

  The updating unit 306 determines whether or not the total value of the calculated maximum power shortage kA (p) and the demand peak Z (p) is smaller than the minimum risk-included peak value Zmin. The update unit 306 updates Zmin to the total value when the total value of the maximum insufficient power kA (p) and the demand peak Z (p) is smaller than Zmin.

  In the same manner as described above, the estimating apparatus 30 calculates the total value of the risk A and the demand peak when the guarantee probability is 0.9. If the calculated total value is smaller than Zmin, the updating unit 306 updates Zmin to the total value. And the estimation apparatus 30 performs the said process about all the guarantee probabilities from 0.8 to 0.1.

  In other words, the estimation device 30 calculates a total value for all guarantee probabilities from 1.0 to 0.1. The updating unit 306 sets the minimum total value among the total values calculated with each guarantee probability as Zmin. And the estimation apparatus 30 selects the estimated PV electric power generation amount corresponding to the guarantee probability p at the time of taking the minimum total value.

  The estimation device 30 sets the discharge amount at each time based on the estimated PV power generation amount corresponding to the guaranteed probability p when the minimum total value is taken, and creates the optimum charge / discharge plan data 321. And the estimation apparatus 30 estimates a storage battery capacity based on the created optimal charging / discharging plan data 321. In addition, when estimating the storage battery capacity again, the estimation device 30 copies the optimum charge / discharge plan data 321 to the charge / discharge plan data 320, and again, based on the copied charge / discharge plan data 320, the optimum charge / discharge plan data 320 again. 321 may be created.

(Processing flow in Example 4)
Next, the procedure for calculating the PV power generation amount according to the fourth embodiment will be specifically described with reference to FIG. FIG. 23 is a flowchart illustrating the procedure for calculating the PV power generation amount according to the fourth embodiment. First, the estimating apparatus 30 sets the guarantee probability p to 1.0, the peak value Zmin including the minimum risk level to 10 ¹⁰ , and the time t to 1 (step S60). The risk level calculation unit 304 calculates the maximum insufficient power amount kA (p) of the estimated PV power generation amount corresponding to the guarantee probability p (step S61). The discharge amount calculation unit 303 calculates a demand peak Z (p) corresponding to the guarantee probability p (step S62). The detailed processing procedure of sub1 including step S61 and step S62 will be described with reference to another flowchart.

  The updating unit 306 determines whether or not the total value of the calculated maximum power shortage kA (p) and the demand peak Z (p) is smaller than Zmin (step S63). If the calculated total value is smaller than Zmin (step S63 Yes), the updating unit 306 updates Zmin to the total value (step S64). Furthermore, the update unit 306 updates pmin to the guarantee probability p when Zmin is updated (step S65). On the other hand, when the calculated total value is equal to or greater than Zmin (No at Step S63), the update unit 306 proceeds to the process at Step S66.

  The updating unit 306 subtracts the reduction probability Δp from the guarantee probability p (step S66). Furthermore, the update unit 306 determines whether or not the guarantee probability p is 0 or less (step S67). When the guarantee probability p is greater than 0 (No at Step S67), the update unit 306 returns to the process at Step S61. That is, the estimating apparatus 30 performs the above processing (step S61 to step S65) for the guarantee probability p−Δp. On the other hand, when the guarantee probability p is 0 or less (Yes in step S67), the update unit 306 ends the process.

  Next, processing performed in sub1 in FIG. 23 will be described with reference to FIG. FIG. 24 is a flowchart showing a processing procedure when the risk A and the demand peak are calculated for each day. In Example 1, based on the difference between the average sunshine rate and the estimated sunshine rate, the maximum power shortage, that is, the risk A was calculated. On the other hand, in Example 4, the estimation apparatus 30 calculates the maximum power shortage and the demand peak every day. Then, the estimation device 30 calculates the average value of the maximum insufficient power amount and the average value of the demand peak based on the maximum insufficient power amount and the demand peak calculated every day.

  A processing procedure in the fourth embodiment will be described. First, the estimating apparatus 30 sets 1 to the number of days d (step S70). The estimation device 30 acquires the sunshine rate R (ts) at the start time of the number of days d from the weather data 322 (step S71). The sunshine rate calculation unit 301 discretizes predicted sunshine rates R (ts + 1) to R (te) from the time t + 1 to the end time te based on the acquired sunshine rate R (ts) at the start time. Calculation is performed using a Markov process model (step S72). The sunshine rate calculation unit 301 calculates the estimated sunshine rates r (ts) to r (te) at each time (step S73). In addition, although it demonstrated that the sunshine rate calculation part 301 calculated the estimated sunshine rate of other time based on the sunshine rate R (ts) of the start time ts, it is not limited to this. For example, the weather data 322 may hold the sunshine rate at all times of the number of days d.

  The estimation device 30 calculates the maximum insufficient power amount kA (d) in the number of days d based on the difference between the calculated predicted sunshine rate and the estimated sunshine rate (step S74). Specifically, in step S74, the estimating apparatus 30 performs the following process. First, the sunshine rate calculation unit 301 calculates the estimated sunshine rate in the number of days d by the method of the first embodiment. The sunshine amount calculation unit 302 calculates the estimated sunshine amount in the number of days d based on the calculated estimated sunshine rate. Then, the discharge amount calculation unit 303 calculates an estimated PV power generation amount in days d based on the calculated estimated amount of sunshine. Further, the risk level calculation unit 304 calculates the maximum insufficient power amount kA (d) in the number of days d based on the difference between the predicted sunshine rate and the estimated sunshine rate. As described above, the estimating apparatus 30 calculates the maximum insufficient power amount kA (d) in the number of days d.

  The estimating apparatus 30 substitutes 1 at time t and 0 for the demand peak maximum value Zdmax in the number of days d (step S75). The discharge amount calculation unit 303 acquires the power consumption amount of each time in the number of days d, that is, the power demand D, from the demand power data 319 holding the daily power consumption amount for each hour. In addition, the discharge amount calculation unit 303 acquires the scheduled discharge amount X for each time from the charge / discharge plan data 320. Then, the discharge amount calculation unit 303 subtracts the estimated PV power generation amount M (t) and the scheduled discharge amount X (t) at time t from the power demand D (t) at time t to obtain a demand peak Z ( t) is calculated (step S76).

  The updating unit 306 determines whether or not the calculated demand peak Z (t) is equal to or greater than Zdmax (step S77). If the demand peak Z (t) is equal to or greater than Zdmax (step S77 Yes), the updating unit 306 updates Zdmax to the demand peak Z (t) (step S78). On the other hand, when the demand peak Z (t) is smaller than Zdmax (No at Step S77), the updating unit 306 proceeds to the process at Step S79.

  The update unit 306 adds 1 to the time t (step S79). Then, the update unit 306 determines whether t is greater than the end time te (step S80). If t is equal to or less than the end time te (step S80 No), the update unit 306 returns to the process of step S76. That is, the update unit 306 performs the above processing (step S76 to step S78) for time t + 1. On the other hand, when t is greater than the end time (step S80 Yes), the update unit 306 proceeds to the process of step S81.

  The estimation device 30 adds 1 to the number of days d (step S81). And the estimation apparatus 30 determines whether d is larger than the total number of days de (step S82). When d is equal to or less than the total number of days (step S82 No), the estimating apparatus 30 returns to the process of step S71. That is, the estimating apparatus 30 performs the above processing (step S71 to step S81) for the next day d + 1. On the other hand, when d is larger than the total number of days (step S82 Yes), the estimating apparatus 30 proceeds to the process of step S83. Then, the estimating apparatus 30 calculates the average value kA of the maximum insufficient power amount by dividing the total value ΣkA (d) of the maximum insufficient power amount for each day by the total number of days de (step S83). Further, the estimating apparatus 30 calculates the average value z of the demand peaks by dividing the total value ΣZdmax (d) of the demand peaks for each day by the total number of days de (step S84).

  Note that the average value kA of the maximum power shortage calculated by the above process and the average value z of the demand peak are used after step S63 in FIG.

  In the third embodiment, it has been described that the degree-of-risk calculation unit 204 calculates the maximum insufficient power amount and the total insufficient power amount based on the comparison between the estimated sunshine rate and the average sunshine rate. Without being limited thereto, the estimation device 20 of the third embodiment calculates the maximum power shortage and the total power shortage for each day as in the fourth embodiment, and divides each by the total number of days d. An average value may be calculated. In the same manner as in the first embodiment, the maximum power shortage and the total power shortage may be calculated every day, and the respective average values may be obtained.

  Note that the estimation device 30 according to the fourth embodiment calculates the maximum insufficient power amount and the demand peak for each day, and calculates the average value of the maximum insufficient power amount and the demand peak by dividing each by the total number of days d. explained. Without being limited thereto, the estimation device 30 according to the fourth embodiment may calculate the maximum insufficient power amount based on a comparison between the estimated sunshine rate and the average sunshine rate. Moreover, the estimation apparatus 30 may calculate a demand peak using the estimated PV power generation amount calculated using the average sunshine rate.

  In the fourth embodiment, it has been described that the weather data 322 holds the sunshine rate at the start time ts. However, the weather data 322 may hold the sunshine rate for all times.

(Computer hardware configuration)
FIG. 25 is a diagram illustrating an example of a computer that executes an estimated storage battery capacity calculation program. As illustrated in FIG. 25, the computer 600 includes a CPU 601 that executes various arithmetic processes, an input device 602 that receives data input from a user, and a monitor 603. The computer 600 includes a medium reading device 604 that reads a program or the like from a storage medium, an interface device 605 for connecting to another device, and a wireless communication device 606 for connecting to another device wirelessly. The computer 600 also includes a RAM (Random Access Memory) 607 that temporarily stores various types of information and a hard disk device 608. Each device 601 to 608 is connected to a bus 609.

  The hard disk device 608 has a degree of risk having functions similar to those of the processing units of the sunshine rate calculation unit 101, the sunshine amount calculation unit 102, the discharge amount calculation unit 103, and the risk level calculation unit 104 of the control unit 100 shown in FIG. A calculation program is stored. Further, the hard disk device 608 stores various data for realizing the risk degree calculation program.

  The CPU 601 reads out each program stored in the hard disk device 608, develops it in the RAM 607, and executes it to perform various processes. In addition, these programs can cause the computer 600 to perform processing in the sunshine amount calculation unit 102, the discharge amount calculation unit 103, and the risk level calculation unit 104 shown in FIG.

  Note that the estimated sunshine rate calculation program and the risk calculation program are not necessarily stored in the hard disk device 608. For example, the computer 600 may read and execute a program stored in a storage medium readable by the computer 600. As the storage medium readable by the computer 600, for example, a portable recording medium such as a CD-ROM, a DVD disk, a USB (Universal Serial Bus) memory, a semiconductor memory such as a flash memory, a hard disk drive, and the like are supported. Alternatively, the program may be stored in a device connected to a public line, the Internet, a LAN (Local Area Network), etc., and the computer 600 may read the program from the program and execute it.

  The following supplementary notes are further disclosed with respect to the embodiments including the above examples.

(Appendix 1) Estimating the probability of transition from the power generation amount before the transition to the power generation amount after the transition based on the transition matrix defined for each power generation amount before the different transition and each power generation amount after the different transition A specific unit that specifies an estimated power generation amount at one time when the power generation amount is a maximum value within a range in which the probability that the power generation amount does not exceed the predetermined power generation amount at each time is less than the guaranteed probability;
The probability of taking a route through which the power generation amount transits at each time passing through the estimated power generation amount at the specified one time is calculated for each route using the transition matrix, and the probability of taking the route, An estimated power generation amount calculation device comprising: an estimation unit that estimates an estimated power generation amount at another time based on a probability taken at another time.

(Supplementary Note 2) The estimated power generation amount at each time has a time larger than the predetermined power generation amount at each time, and the maximum power generation amount and the average power generation amount at the time of each route where the estimated power generation amount transits. An acquisition unit for acquiring each difference value;
A calculation unit that calculates the maximum underpower amount by multiplying the probability that each route can be taken and the maximum difference value corresponding to each route to calculate a multiplication value and adding the multiplication values to each other. The estimated power generation amount calculation apparatus according to appendix 1, further comprising:

(Supplementary note 3) The difference between the estimated power generation amount and the average power generation amount at the time of each route where the estimated power generation amount has a time when the estimated power generation amount at each time is larger than the predetermined power generation amount at each time. Respectively, and an acquisition unit for acquiring the total value by adding the difference values,
A calculation unit for calculating a total insufficient power amount by multiplying a probability that each route can be taken and a total value corresponding to each route to calculate a multiplication value and adding the multiplication values to each other; The estimated power generation amount calculation apparatus according to supplementary note 1, comprising:

(Additional remark 4) The comparison part which compares the threshold value set to each one of the maximum insufficient electric energy and the total insufficient electric energy with either or both of the maximum insufficient electric energy calculated by the said calculation part, or both And further having
The specifying unit specifies the estimated power generation amount at the one time based on a minimum guarantee probability within a range in which either one or both of the maximum power shortage and the total power shortage do not exceed the threshold. The estimated power generation amount calculation apparatus according to Supplementary Note 1, which is a feature.

(Supplementary Note 5) Demand peak calculated by subtracting the estimated power generation amount estimated for each guarantee probability from the power consumption amount and the discharge power amount discharged from the storage battery at each time, and calculated by the calculation unit An update unit that holds the minimum addition value among the addition values obtained by adding the maximum insufficient power amount for each guarantee probability,
The estimated power generation amount calculation apparatus according to appendix 1, wherein the specifying unit specifies the estimated power generation amount at the one time based on the guaranteed probability of the minimum addition value.

(Appendix 6) An estimated power generation amount calculation method executed by a computer,
Based on the transition matrix that defines the probability of transition from the power generation amount before the transition to the power generation amount after the transition for each power generation amount before the different transition and each power generation amount after the different transition, the estimated power generation amount at each time is Specify the estimated power generation amount at one time when the probability of transition without exceeding the predetermined power generation amount at the time is the maximum value within the range that does not fall below the guarantee probability,
The probability of taking a route through which the power generation amount transits at each time passing through the estimated power generation amount at the specified one time is calculated for each route using the transition matrix, and the probability of taking the route, An estimated power generation amount calculation method comprising: executing each process for estimating an estimated power generation amount at another time based on a probability taken at another time.

(Appendix 7)
Based on the transition matrix that defines the probability of transition from the power generation amount before the transition to the power generation amount after the transition for each power generation amount before the different transition and each power generation amount after the different transition, the estimated power generation amount at each time is Specify the estimated power generation amount at one time when the probability of transition without exceeding the predetermined power generation amount at the time is the maximum value within the range that does not fall below the guarantee probability,
The probability of taking a route through which the power generation amount transits at each time passing through the estimated power generation amount at the specified one time is calculated for each route using the transition matrix, and the probability of taking the route, An estimated power generation amount calculation program for executing each process for estimating an estimated power generation amount at another time based on a probability taken at another time.

DESCRIPTION OF SYMBOLS 10 Estimation apparatus 21 Input part 22 Output part 100 Control part 101 Sunlight rate calculation part 102 Sunlight amount calculation part 103 Discharge amount calculation part 104 Risk level calculation part 110 Storage part 111 Transition matrix data 112 Estimated sunlight rate data 113 Sunlight rate and amount of sunlight Conversion coefficient data 114 Estimated sunshine amount data 115 Estimated PV power generation amount data 116 Power consumption amount data 117 Estimated PV power generation amount / discharge power amount data 118 Estimated risk data

Claims (7)

Based on the transition matrix that defines the probability of transition from the power generation amount before the transition to the power generation amount after the transition for each power generation amount before the different transition and each power generation amount after the different transition, the estimated power generation amount at each time is A specific unit that identifies an estimated power generation amount at one time when the probability of transition without exceeding a predetermined power generation amount at a time is a maximum value within a range that does not fall below the guarantee probability;
The probability of taking a route through which the power generation amount transits at each time passing through the estimated power generation amount at the specified one time is calculated for each route using the transition matrix, and the probability of taking the route, An estimated power generation amount calculation apparatus comprising: an estimation unit that estimates an estimated power generation amount at another time based on a power generation amount taken at another time. The maximum difference value between the estimated power generation amount and the average power generation amount at the time of each route where the estimated power generation amount has a time when the estimated power generation amount at each time is larger than the predetermined power generation amount at each time. An acquisition unit to acquire;
A calculation unit that calculates the maximum underpower amount by multiplying the probability that each route can be taken and the maximum difference value corresponding to each route to calculate a multiplication value and adding the multiplication values to each other. The estimated power generation amount calculation device according to claim 1, further comprising: Obtain the difference value between the estimated power generation amount and the average power generation amount at the time of each route where the estimated power generation amount has a time when the estimated power generation amount at each time is larger than the predetermined power generation amount at each time. , An acquisition unit for adding each difference value to obtain a total value,
A calculation unit for calculating a total insufficient power amount by multiplying a probability that each route can be taken and a total value corresponding to each route to calculate a multiplication value and adding the multiplication values to each other; The estimated power generation amount calculation device according to claim 1, comprising: And a comparison unit that compares one or both of the maximum power shortage and the total power shortage calculated by the calculation unit with a threshold set for each of the maximum power shortage and the total power shortage. And
The specifying unit specifies the estimated power generation amount at the one time based on a minimum guarantee probability within a range in which either one or both of the maximum power shortage and the total power shortage do not exceed the threshold. The estimated power generation amount calculation device according to claim 1, wherein The demand peak calculated by subtracting the estimated power generation amount estimated for each guarantee probability from the power consumption amount and the discharge power amount discharged from the storage battery at each time, and the maximum insufficient power amount calculated by the calculation unit And an update unit that holds the minimum addition value among the addition values obtained by adding each guarantee probability,
The estimated generation amount calculation device according to claim 1, wherein the specifying unit specifies the estimated generation amount at the one time based on the guaranteed probability of the minimum addition value. An estimated power generation calculation method executed by a computer,
Based on the transition matrix that defines the probability of transition from the power generation amount before the transition to the power generation amount after the transition for each power generation amount before the different transition and each power generation amount after the different transition, the estimated power generation amount at each time is Specify the estimated power generation amount at one time when the probability of transition without exceeding the predetermined power generation amount at the time is the maximum value within the range that does not fall below the guarantee probability,
The probability of taking a route through which the power generation amount transits at each time passing through the estimated power generation amount at the specified one time is calculated for each route using the transition matrix, and the probability of taking the route, An estimated power generation amount calculation method comprising: executing each process for estimating an estimated power generation amount at another time based on a probability taken at another time. On the computer,
Based on the transition matrix that defines the probability of transition from the power generation amount before the transition to the power generation amount after the transition for each power generation amount before the different transition and each power generation amount after the different transition, the estimated power generation amount at each time is Specify the estimated power generation amount at one time when the probability of transition without exceeding the predetermined power generation amount at the time is the maximum value within the range that does not fall below the guarantee probability,
The probability of taking a route through which the power generation amount transits at each time passing through the estimated power generation amount at the specified one time is calculated for each route using the transition matrix, and the probability of taking the route, An estimated power generation amount calculation program for executing each process for estimating an estimated power generation amount at another time based on a probability taken at another time.

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