Information processing device, information processing method, and program

Abstract

This information processing device for calculating a share ratio of a plurality of renewable energy power generation sources at a consumer that uses the plurality of renewable energy power generation sources includes a calculation unit for calculating the share ratio so that a magnitude of the difference between demand at the consumer and an amount of power generated by the plurality of renewable energy power generation sources meets prescribed conditions.

Description

Information processing device, information processing method, and program

[0001] The present invention relates to a technology for meeting demand using renewable energy power generation.

[0002] There are known attempts to develop zero-emission data centers (DCs) that use 100% renewable energy for the electricity they consume without purchasing non-fossil fuel certificates. For example, in the Ishikari Port area, construction of a DC is underway, as it is expected to utilize wind power (WG) in addition to photovoltaics (PV) (Non-Patent Document 1).

[0003] In planning a zero-emission data center that is premised on making maximum use of renewable energy, the characteristics of PV and WG power generation differ depending on the region, and so it is necessary to design a system that takes these characteristics into account. Energy storage equipment is required to absorb fluctuations in PV and WG output, but as the capacity of energy storage equipment increases, the cost of installing the storage batteries, securing space, and the burden of maintenance also increase, so it is also necessary to minimize the amount of energy storage equipment.

[0004] The conventional technology disclosed in Non-Patent Document 1 is based on the premise that the supply and demand balance will be adjusted using a large-capacity storage battery installed at the DC, and that local renewable energy generation such as biomass will be added in addition to PV and WG, and the system design does not take advantage of the mutually complementary relationship created by the hybrid of PV and WG.

[0005] "Introduction to the Zero-Emission Data Center Plan," https: / / hokkaido.env.go.jp / content / 000066909.pdf, accessed May 7, 2024

[0006] In a DC system that is premised on maximizing the use of renewable energy, in order to minimize the need for storage facilities, it is necessary to determine the ratio of PV to WG power generation so that the mutually complementary relationship between PV and WG is maximized, for example, by supplementing with WG power generation when PV power generation is insufficient at night. However, with conventional technology, it was not possible to appropriately determine the ratio of PV to WG power generation.

[0007] The multiple renewable energies that are mutually complementary are not limited to PV and WG. Furthermore, consumers who make the most of renewable energy are not limited to DC.

[0008] The present invention has been made in consideration of the above points, and aims to provide a technology for determining an appropriate sharing ratio between multiple renewable energy power generation sources for a consumer that utilizes multiple renewable energy sources.

[0009] According to the disclosed technology, there is provided an information processing device that calculates the share ratio of a consumer that uses multiple renewable energy power generation sources, the information processing device including: a calculation unit that calculates the share ratio so that the magnitude of the difference between the demand of the consumer and the amount of power generated by the multiple renewable energy power generation sources meets a predetermined condition.

[0010] The disclosed technology provides a technology for determining an appropriate sharing ratio between multiple renewable energy power generation sources in a consumer that utilizes multiple renewable energy sources.

[0011] It is a block diagram of an information processing device 100. It is a flowchart for explaining the operation of the information processing device 100. It is a diagram for explaining an example of an allocation ratio calculation unit 170. It is a block diagram of an information processing device 200. It is a diagram for showing an example of the hardware configuration of an information processing device.

[0012] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. The embodiment described below is merely an example, and the embodiment to which the present invention is applied is not limited to the following embodiment.

[0013] In the following description of the embodiment, the consumer is assumed to be a DC and the renewable energy power generation used is assumed to be photovoltaic (PV) power generation and wind power generation (WG), but these are examples and are not limited to these. The technology according to the present invention can be applied to consumers in general who utilize renewable energy. Furthermore, the multiple renewable energy power generation used may be other than "PV and WG" (e.g., wave power generation, hydroelectric power generation, geothermal power generation, etc.).

[0014] In this embodiment, an information processing device 100 (described later) calculates an optimal power generation share ratio for a certain demand based on past time-series data, and estimates the installed capacity of power generation from the calculated value. By obtaining an estimated value of the installed capacity in this way, the estimated value can be used in designing a data center that aims to make maximum use of renewable energy.

[0015] For example, since the power generation potential of renewable energy varies by region, this technology can be used to select potential construction sites while minimizing equipment costs.

[0016] (Device Configuration) Fig. 1 shows an example of the configuration of an information processing device 100 according to this embodiment. As shown in Fig. 1, the information processing device 100 according to this embodiment includes an area input unit 110, a weather data acquisition unit 120, a power generation data calculation unit 130, a demand data acquisition unit 140, a data division unit 150, a variable determination unit 160, a sharing ratio calculation unit 170, an installed capacity estimation unit 180, and an estimation result output unit 190. The functions of each unit are as follows:

[0017] The area input unit 110 inputs an area that is a candidate for installing a consumer (here, a DC). The meteorological data acquisition unit 120 acquires time-series data of meteorological data (e.g., solar radiation, wind speed) for the selected area that is necessary for calculating the amount of power generation.

[0018] The power generation data calculation unit 130 calculates the amount of power generation from the weather data acquired by the weather data acquisition unit 120. For the calculation, a general formula for calculating the amount of power generation from weather data may be used, or AI may be used. As AI, for example, a neural network model that inputs weather data and outputs the amount of power generation may be used.

[0019] The demand data acquisition unit 140 acquires time-series demand data of a target consumer. The data division unit 150 aligns the granularity of the power generation data calculated by the power generation data calculation unit 130 and the demand data acquired by the demand data acquisition unit 140, and divides the time-series data of power generation and demand by period as necessary. Calculations may be performed using data divided by period by the data division unit 150.

[0020] The divided period (unit) is not limited to a specific period, and may be divided into daytime and nighttime periods, or into seasons (e.g., spring, summer, fall, winter), or into other periods.

[0021] The parameter determination unit 160 standardizes the data on power generation and demand using statistical information such as average values.

[0022] The sharing ratio calculation unit 170 performs calculations to optimize the sharing ratio of the amount of power generation between the PV and the WG so as to minimize the magnitude of the difference (adjustment amount) between demand (required amount of power) and supply (amount of power generation). The method of optimization calculation is not limited to a specific method, and for example, a general optimization problem solution method may be applied to solve an optimization problem that minimizes the difference (adjustment amount) between demand and supply. Note that calculating the sharing ratio so as to minimize the difference (adjustment amount) between demand and supply is merely an example. The sharing ratio may also be calculated so that the difference (adjustment amount) between demand and supply meets a predetermined condition. "Minimum" is merely an example of a "predetermined condition."

[0023] The installed capacity estimation unit 180 estimates the installed capacity of power generation based on the share ratio of the power generation amount calculated by the share ratio calculation unit 170.

[0024] The estimation result output unit 190 outputs the estimation result of the installed capacity estimated by the installed capacity estimation unit 180. In this embodiment, the above-described processing is performed for each of a plurality of areas (candidate areas for DC installation).

[0025] (Example of Processing Flow) The processing flow of the information processing device 100 will be described with reference to Fig. 2. Here, the information processing device 100 calculates the distribution ratio between PV and WG based on past weather data for a certain area and demand data of a consumer (assuming DC in this case), and estimates the installed capacity of power generation for the consumer.

[0026] <S1 (Step 1)> In S1, the power generation data calculation unit 130 calculates time-series data on the amount of power generation from weather data for the target area. As described above, the time-series data on the amount of power generation may be calculated using a general estimation formula or may be estimated using machine learning (AI, etc.). In addition, the power generation data calculation unit 130 extracts data of an appropriate granularity from the calculated (estimated) time-series data on the amount of power generation.

[0027] <S2> In S2, the demand data acquisition unit 140 acquires time-series data of the power demand of the target consumer (here, DC).

[0028] <S3> In S3, for example, the data dividing unit 150 aligns the granularity of the time-series data of the power generation amount extracted in S1 and the time-series data of the demand extracted in S2 and records them in a storage device (for example, a memory device) in the information processing device 100. As described above, the time-series data of power generation and demand may be divided into periods.

[0029] <S4> In S4, the variable determination unit 160 standardizes the time-series data of the power generation amount and the time-series data of the demand based on statistical information, and uses the standardized values ​​as variables. For example, the values ​​are made dimensionless by standardizing them with an annual average value. Note that standardization may not be performed.

[0030] <S5> In S5, the sharing ratio calculation unit 170 uses the standardized time-series data to determine the sharing ratio between the PV and the WG so as to minimize the fluctuation range (=adjustment amount by a storage battery, etc.) of the difference between demand and supply (amount of power generation). For example, the sharing ratio is determined by solving an optimization problem. As a more specific example, the coefficient a in the evaluation function described below is determined.

[0031] <S6> In S6, the installed capacity estimation unit 180 calculates the total power generation amount of the PV and the total power generation amount of the WG, for example, for one year, using the sharing ratio determined in S5. As an example, if the total power demand for one year is 100 and the sharing ratio of the PV and the WG is "PV:WG = 7:3", the total power generation amount of the PV can be calculated as 70 and the total power generation amount of the WG as 30.

[0032] <S7> In S7, the installed capacity estimation unit 180 records the calculation result in S6 in the storage device of the information processing device 100.

[0033] <S8> In S8, the installed capacity estimation unit 180 estimates the installed capacity of the PVs based on the total power generation amount of the PVs calculated in S6, and estimates the installed capacity of the WG based on the total power generation amount of the WG calculated in S6. The estimation result output unit 190 outputs the estimated installed capacity.

[0034] <S9> By performing the processes of S1 to S8 for multiple areas, it is possible to obtain an estimated result of the installed capacity for each of the multiple areas. For example, a person can select an area suitable for installing a data center based on the estimation result for each area. Alternatively, the information processing device 100 (e.g., the installed capacity estimation unit 180) can calculate the installed cost for each area from the installed capacity of the PV and WG for each area, and select the area with the lowest installed cost as the area suitable for installing a data center.

[0035] <Effects of the above process> In this embodiment, the installed capacity is estimated using the total power generation amount based on the optimal sharing ratio, so that it is possible to avoid excessive installed capacity for each of the PV and WG, and to minimize the cost of power generation equipment. Furthermore, since the sharing ratio is determined so as to minimize the fluctuation range (= adjustment amount by storage batteries, etc.) of the difference between demand and supply (power generation amount), the cost of the power storage equipment required to adjust the fluctuation range can also be minimized.

[0036] (Example of Sharing Ratio Calculation) A specific example of the sharing ratio calculation executed by the sharing ratio calculation unit 170 will be described. In this example, the sharing ratio between the PV and the WG is calculated using the following evaluation function.

[0037] Evaluation function: L(t) = a × S(t) + (1-a) × W(t) + δ(t) In the above formula, L(t) is the DC power demand, S(t) is the PV power generation amount, W(t) is the WG power generation amount, and δ(t) is the fluctuation range of supply and demand (= adjustment amount by storage batteries, etc.). In these variables, t is time, and these variables are each a function of time (i.e., time series data). Also, a is a coefficient (0≦a≦1) representing the sharing ratio. In this embodiment, since it is assumed that DC power demand is met only by hybrid power generation of PV and WG, when the PV ratio is a, the WG ratio is set to 1-a.

[0038] The sharing ratio calculation unit 170 determines a so that the magnitude of δ(t) in the evaluation function (evaluation formula) is minimized using time series data S(t) of the amount of power generated by PV, time series data W(t) of the amount of power generated by WG, and time series data L(t) of power demand from DC, for example, for one year. The magnitude of δ(t) being minimized means that, for example, when considering one year, the total amount (= one-year integrated value) of the magnitude of δ(t) (absolute value of δ(t)) for one year is minimized.

[0039] Alternatively, a may be determined using a scatter diagram such as that shown in Figure 3. The value x on the horizontal axis in Figure 3 is x = S(t) - W(t), and the value y on the vertical axis is y = L(t) - W(t). In this way, the evaluation function above becomes y = a x + δ(t).

[0040] The scatter diagram in FIG. 3 is a diagram in which the values ​​of (x, y) at each time are plotted. The slope p of the approximation formula "y = p x + q" of the straight line that approximates the set of plotted points in the scatter diagram corresponds to a. The accuracy of the approximation (R ２ Among the approximate expressions "y = p x + q" where the value of q (the absolute value of q) is equal to or greater than a threshold, p is found where the magnitude of q (the absolute value of q) is minimum.

[0041] The installed capacity estimation unit 180 can estimate the installed capacity of each of the PV and WG as described above using the value a obtained as described above. The capacity of the storage battery can be estimated, for example, as follows.

[0042] The installed capacity estimation unit 180 calculates δ(t) at each time (for example, every hour) using the value of a obtained as described above and the time series data of the PV and WG. That is, it calculates "δ(t) = L(t) - a × S(t) - (1 - a) × W(t)" at each time.

[0043] For example, the installed capacity estimation unit 180 determines the capacity of the storage battery based on |δ(t)| at the time when |δ(t)| is maximum among the magnitude (|δ(t)|) of δ(t) at each time during a certain period. For example, if |δ(t)| is large, the amount of adjustment of the fluctuation range becomes large, so the capacity of the storage battery is increased, and if |δ(t)| is small, the amount of adjustment of the fluctuation range becomes small, so the capacity of the storage battery is decreased.

[0044] <Example of Dividing a Period> A period may be divided and a calculated for each divided period. For example, the sharing ratio calculation unit 170 acquires time-series data for daytime hours and time-series data for nighttime hours for each of the PV power generation amount and the WG power generation amount, and calculates a that minimizes the fluctuation range of demand and supply for each of the daytime hours and nighttime hours in the same manner as above. Here, a corresponding to the daytime hours is designated as a1, and a corresponding to the nighttime hours is designated as a2.

[0045] In this case, the installed capacity estimation unit 180 estimates the installed capacity of each of the PV and WG using a1, and estimates the installed capacity of each of the PV and WG using a2. For example, the installed capacity estimation unit 180 outputs the larger of the installed capacity estimated using a1 and the installed capacity estimated using a2 for each of the PV and WG as the final estimation result.

[0046] <Example of using three or more renewable energies> The above example is an example of using two renewable energies, PV and WG, but even when three or more renewable energies are used, the sharing ratio can be calculated in the same manner as above. For example, a case where three renewable energies are used will be described. Here, the following formula is used as the evaluation function.

[0047] L(t) = a x E1(t) + b x E2(t) + c x E3(t) + δ(t) In the above formula, L(t) is DC power demand, E1(t) is the amount of power generated by renewable energy 1, E2(t) is the amount of power generated by renewable energy 2, E3(t) is the amount of power generated by renewable energy 3, and a, b, and c are coefficients that represent the respective sharing ratios (0≦a≦1, 0≦b≦1, 0≦c≦1, a+b+c=1).

[0048] The sharing ratio calculation unit 170 determines a, b, and c so that the magnitude of δ(t) in the above evaluation function (evaluation formula) is minimized using time series data E1(t) of the amount of power generated by renewable energy 1, time series data E2(t) of the amount of power generated by renewable energy 2, time series data E3(t) of the amount of power generated by renewable energy 3, and time series data L(t) of DC power demand, for example, over one year. The magnitude of δ(t) being minimized means that, for example, when considering one year, the total amount of |δ(t)| over one year (= the integrated value over one year) is minimized.

[0049] Once a, b, and c are determined, the installed capacity of each renewable energy source 1, 2, and 3 can be estimated, and based on these installed capacities, for example, the area with the lowest installation cost can be selected as the DC installation area.

[0050] (Other Configuration Examples of Information Processing Device) The configuration of the information processing device is not limited to the configuration of the information processing device 100 shown in Fig. 1. For example, the configuration of the information processing device 200 shown in Fig. 4 may be used. The information processing device 200 shown in Fig. 4 has a calculation unit 210 and an estimation unit 220. The calculation unit 210 has the function of the sharing ratio calculation unit 170. However, the calculation unit 210 may also include a weather data acquisition unit 120, a power generation data calculation unit 130, a demand data acquisition unit 140, etc.

[0051] The estimation unit 220 has the function of the installed capacity estimation unit 180. The estimation unit 220 may also include a function of selecting an area.

[0052] (Hardware Configuration Example) Any of the devices (information processing devices 100, 200, etc.) described in this embodiment can be realized, for example, by causing a computer to execute a program. This computer may be a physical computer or a virtual machine on the cloud.

[0053] That is, the device can be realized by executing a program corresponding to the processing performed by the device using hardware resources such as a CPU and memory built into a computer. The program can be recorded on a computer-readable recording medium (such as a portable memory) and stored or distributed. The program can also be provided via a network such as the Internet or email.

[0054] Fig. 5 is a diagram showing an example of the hardware configuration of the computer. The computer in Fig. 5 includes a drive device 1000, an auxiliary storage device 1002, a memory device 1003, a CPU 1004, an interface device 1005, a display device 1006, an input device 1007, an output device 1008, and the like, all of which are interconnected via a bus B. The computer may further include a GPU.

[0055] The program that realizes the processing on the computer is provided by a recording medium 1001, such as a CD-ROM or a memory card. When the recording medium 1001 storing the program is set in the drive device 1000, the program is installed from the recording medium 1001 to the auxiliary storage device 1002 via the drive device 1000. However, the program does not necessarily have to be installed from the recording medium 1001, but may be downloaded from another computer via a network. The auxiliary storage device 1002 stores the installed program as well as necessary files, data, etc.

[0056] The memory device 1003 reads and stores a program from the auxiliary storage device 1002 when an instruction to start the program is received. The CPU 1004 realizes functions related to the device in accordance with the program stored in the memory device 1003. The interface device 1005 is used as an interface for connecting to a network, etc. The display device 1006 displays a GUI (Graphical User Interface) or the like according to the program. The input device 1007 is composed of a keyboard, mouse, buttons, a touch panel, etc., and is used to input various operation instructions. The output device 1008 outputs the results of calculations.

[0057] As described above, the technology described in this embodiment makes it possible to determine the sharing ratio between the PV and WG so as to minimize the difference between the demand and the amount of power generated. In other words, it is possible to determine the sharing ratio between the PV and WG so as to maximize the mutually complementary relationship between the PV and WG.

[0058] Furthermore, the capacity of each PV and WG facility can be estimated from the sharing ratio.The estimated capacity can then be used to estimate the facility cost.Furthermore, since the capacity of the storage facility can be estimated based on the difference between demand and power generation, the cost of the storage facility can also be estimated.

[0059] Therefore, by using the technology described in this embodiment, for example, an area that minimizes the cost of capital investment in power generation equipment and power storage equipment can be selected as the installation area for DC.

[0060] The following additional notes are provided regarding the above-described embodiments.

[0061] <Additional Notes> (Additional Item 1) An information processing device that calculates sharing rates of a plurality of renewable energy power plants for a consumer that uses the plurality of renewable energy power plants, the information processing device comprising: a calculation unit that calculates the sharing rate so that the magnitude of the difference between the demand of the consumer and the amount of power generated by the plurality of renewable energy power plants meets a predetermined condition. (Additional Item 2) The information processing device according to Additional Item 1, wherein the calculation unit calculates the amount of power generated from weather data in a target area. (Additional Item 3) The information processing device according to Additional Item 1, further comprising: an estimation unit that estimates an installed capacity of each of the plurality of renewable energy power plants using the sharing rate. (Additional Item 4) The information processing device according to Additional Item 3, wherein the estimation unit estimates the installed capacity for each of a plurality of areas, and selects an area in which the consumer is to be installed based on the estimated installed capacity. (Supplementary Item 5) An information processing method executed by an information processing device that calculates a share ratio of a plurality of renewable energy power generation sources for a consumer that uses the plurality of renewable energy power generation sources, the information processing method calculating the share ratio so that the magnitude of the difference between the demand of the consumer and the amount of power generated by the plurality of renewable energy power generation sources meets a predetermined condition. (Supplementary Item 6) A non-transitory storage medium that stores a program for causing a computer to function as each unit in the information processing device described in any one of Supplementary Items 1 to 4.

[0062] Although the present embodiment has been described above, the present invention is not limited to such a specific embodiment, and various modifications and changes are possible within the scope of the gist of the present invention described in the claims.

[0063] REFERENCE SIGNS LIST 100 Information processing device 110 Area input unit 120 Weather data acquisition unit 130 Power generation data calculation unit 140 Demand data acquisition unit 150 Data division unit 160 Variable determination unit 170 Sharing ratio calculation unit 180 Installed capacity estimation unit 190 Estimation result output unit 200 Information processing device 210 Calculation unit 220 Estimation unit 1000 Drive device 1001 Recording medium 1002 Auxiliary storage device 1003 Memory device 1004 CPU 1005 Interface device 1006 Display device 1007 Input device 1008 Output device

Claims

1. An information processing device that calculates the share ratio of multiple renewable energy power generation sources for a consumer that uses the multiple renewable energy power generation sources, the information processing device having a calculation unit that calculates the share ratio so that the magnitude of the difference between the demand of the consumer and the amount of power generated by the multiple renewable energy power generation sources meets a predetermined condition.

2. The information processing device according to claim 1, wherein the calculation unit calculates the amount of power generation from meteorological data in a target area.

3. The information processing device according to claim 1, further comprising an estimation unit that estimates the installed capacity of each of the plurality of renewable energy power plants using the sharing ratio.

4. The information processing device according to claim 3, wherein the estimation unit estimates the installed capacity for each of a plurality of areas, and selects an area in which the customer is to be installed based on the estimated installed capacity.

5. An information processing method executed by an information processing device that calculates the share ratio of a consumer that uses multiple renewable energy power generation sources, the information processing method calculating the share ratio so that the magnitude of the difference between the demand of the consumer and the amount of power generated by the multiple renewable energy power generation sources meets a predetermined condition.

6. A program for causing a computer to function as each unit in the information processing device according to any one of claims 1 to 4.

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