Arrangement support apparatus, arrangement support method, and program

Abstract

To appropriately propose an installation destination of a load facility to a power network including a power generation facility of renewable energy power generation.SOLUTION: An arrangement support device 50 is provided with a similarity evaluation part 58 for calculating similarity between time series data of a power demand amount of a load facility that can be added to any node belonging to a power network and time series data of an output suppression amount of renewable energy power generation in each node, and a display control part 62 for displaying the node and the similarity on a display 70 in association with each other.SELECTED DRAWING: Figure 9

Description

[Technical Field]

[0001] The present invention relates to a placement assistance device, a placement assistance method, and a program. [Background technology]

[0002] As background art in this technical field, the abstract of Patent Document 1 listed below states, "[Problem] To obtain a power management server that can adjust the supply and demand of power between multiple areas. [Solution] Power management server 1 includes welcome zone candidate acquisition unit 11 that acquires candidate information for welcome zones, which are first areas where there is a surplus of power generated in the power grid or second areas where there is a shortage of power, welcome zone information generation unit 12 that generates welcome zone information by solving an optimization problem for the welcome zone based on the candidate information, and welcome zone information disclosure unit 13 that discloses the welcome zone information to users on the web, and the welcome zone information includes the fee for charging power in the first area and the fee for discharging power in the second area." [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2023-175405 Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the above-mentioned technology, there is a demand for more appropriate proposal of the installation location of the load equipment. The present invention has been made in view of the above-mentioned circumstances, and has an object to provide a layout support device, a layout support method, and a program that can appropriately suggest installation locations for load equipment. [Means for solving the problem]

[0005] In order to solve the above problem, the placement assistance device of the present invention is characterized by comprising a similarity evaluation unit that calculates the similarity between time series data of the power demand of load equipment that can be added to any node belonging to the power network and time series data of the output suppression amount of renewable energy power generation at each of the nodes, and a display control unit that associates the node with the similarity and displays it on a display. [Effects of the Invention]

[0006] According to the present invention, it is possible to appropriately propose the installation location of the load equipment. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 2 is a block diagram of a power grid and the like applied to the first embodiment. [Figure 2] FIG. 10 is a diagram illustrating an example of a power supply and demand analysis result. [Figure 3] FIG. 10 is a diagram showing another example of the power supply and demand analysis result. [Figure 4] FIG. 10 is a diagram illustrating an example of the amount of power demand of a load facility to be added. [Figure 5] FIG. 10 is a diagram showing an example of an analysis result of power supply and demand according to a comparative example. [Figure 6] FIG. 10 is a diagram showing another example of the power supply and demand analysis result according to the comparative example. [Figure 7] FIG. 10 is a diagram showing yet another example of the power supply and demand analysis result according to the comparative example. [Figure 8] FIG. 10 is a diagram showing yet another example of the power supply and demand analysis result according to the comparative example. [Figure 9] 1 is a block diagram of a placement assistance device according to a first embodiment. [Figure 10] FIG. 10 is a schematic diagram illustrating an example of processing in a similarity evaluation unit. [Figure 11] FIG. 10 is a diagram illustrating an example of a display screen. [Figure 12] FIG. 1 is a block diagram of a computer. [Figure 13] 4 is a flowchart of an analysis routine in the first embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0008] [Outline of the embodiment] In Japan, the rules for connecting renewable energy power generation facilities to the grid are shifting from farm-type connections to non-farm-type connections. Non-farm-type connections differ from the previous farm-type connections in that they are grid connection rules that assume output suppression when necessary. Non-farm-type connections allow renewable energy power generation facilities to connect to the grid without waiting for the power grid to be reinforced, but they now have to accept output suppression. One way to reduce output suppression is to install load equipment near the power generation facility to increase electricity demand. In recent years, some transmission and distribution companies have published welcome zone maps. Welcome zones are locations where the power grid has capacity and can provide electricity relatively quickly and at low cost. Publishing welcome zone maps can help guide the placement of load equipment.

[0009] The technology applying the above-mentioned Patent Document 1 is believed to be capable of predicting grid congestion and charging electric vehicle batteries in areas with excess power and discharging electric vehicle batteries in areas with a power shortage. However, Patent Document 1 does not specifically mention cases where load equipment other than electric vehicles is connected to the power grid. Furthermore, when new user selection information is received, the welcome zone information is recalculated and updated, which may require resolving the optimization problem each time conditions change. Therefore, the embodiment described below is applicable to various types of load equipment and enables quick and appropriate suggestions for zones in which to install the load equipment.

[0010] [First embodiment] <Power grid configuration> FIG. 1 is a block diagram of a power grid and the like applied to the first embodiment. In FIG. 1, a power grid 10 is divided into multiple nodes 12-A, 12-B, 12-C, 12-D, 12-E, etc., and each node is connected by a power transmission line 14. In the following description, multiple components, physical quantities, information, etc. having the same or similar functions or significance may be represented by the same reference numeral with a "-" and alphanumeric characters added, such as "nodes 12-A and 12-B." However, when it is not necessary to distinguish between these multiple components, etc., they may be represented by omitting the "-" and alphanumeric characters, such as "node 12."

[0011] The power grid 10 includes various power generation facilities and load facilities. When analyzing the power supply and demand of these power generation facilities and load facilities, it is preferable to be able to express a certain degree of "group" as a unit from the viewpoint of the amount of calculation and data. Therefore, in this embodiment, these groups are defined as nodes 12. Note that the nodes 12 are virtually defined, and the range of each node 12 can be changed as necessary. The nodes 12 are, for example, power generation facilities, load facilities, substations, switchyards, etc., or a combination of these.

[0012] 1, node 12-A includes a substation 22-A, a power generation facility 24-A, and a load facility 26-A. Similarly, node 12-B includes a substation 22-B, a power generation facility 24-B, and a load facility 26-B. These power generation facilities 24-A and 24-B are renewable energy power generation facilities (hereinafter, sometimes referred to as renewable energy power generation facilities).

[0013] However, the configuration of each node 12 is different. For example, since thermal power generation facilities and the like have a large power generation output per unit, one node 12 may be configured with only one thermal power generation facility. On the other hand, renewable energy power generation facilities have a smaller power generation output per unit compared to thermal power generation facilities and therefore have a larger number of power generation facilities 24. Therefore, it is preferable to consider a single node 12 to include a substation 22 and the multiple power generation facilities 24 connected to its low-voltage side (the lower side in FIG. 1). Therefore, each of power generation facilities 24-A and 24-B shown in FIG. 1 is not limited to a single renewable energy power generation facility, but may also be a collection of multiple renewable energy power generation facilities of the same type.

[0014] The load facilities 26-A and 26-B are not limited to a single load facility each, and may be a collection of multiple load facilities connected to the low-voltage side of the substations 22-A and 22-B. However, it is not necessary to link all renewable energy power generation facilities to a substation. For example, since offshore wind power plants are larger in scale than onshore wind power plants, one node 12 may consist of only one power plant. The nodes 12 can exchange power with each other via transmission lines 14.

[0015] Fig. 2 is a diagram showing an example of the power supply and demand analysis result. The power supply and demand analysis result AD-A shown in Fig. 2 shows an example of the transition of various types of power at node 12-A from 0:00 to 24:00 on a certain day. In Fig. 2, the horizontal axis represents time and the vertical axis represents power. First, the power demand Pdem-A is the power consumed by the load equipment 26-A. Furthermore, the power generation output Pgen-A is the power output by the power generation equipment 24-A. Furthermore, the reverse power flow rate Prev-A is the power obtained by subtracting the power demand Pdem-A from the power generation output Pgen-A.

[0016] That is, when the reverse power flow rate Prev-A is a positive value, it means that power is being supplied to another node, and when it is a negative value, it means that power is being received from another node. However, the reverse power flow rate Prev-A is limited by the ratings of the power transmission line 14, substation 22-A, etc. Therefore, the maximum power allowed as the reverse power flow rate Prev-A is called the transmittable power capacity Pth-A. When the reverse power flow rate Prev-A reaches the transmittable power capacity Pth-A, the power generation facility 24-A must suppress its power output Pgen-A so that the reverse power flow rate Prev-A does not exceed the transmittable power capacity Pth-A. Note that the ideal reverse power flow rate Pir-A is the reverse power flow rate Prev-A that would occur if there were no limit on the transmittable power capacity Pth-A.

[0017] The maximum value of the power generation output Pgen-A that can be achieved based on the performance of the power generation equipment 24-A is called the pre-suppression power generation output Pps-A. The power obtained by subtracting the power generation output Pgen-A from the pre-suppression power generation output Pps-A is called the output suppression amount Psup-A. If the power generation equipment 24-A is a renewable energy power generation equipment, effective energy use can be achieved by making this output suppression amount Psup-A as small as possible.

[0018] The power generation equipment 24-A is, for example, a solar power generation equipment, and its power generation output Pgen-A is high mainly during the daytime. Furthermore, the power demand amount Pdem-A by the load equipment 26-A is a value that changes smoothly throughout the day. Therefore, the output suppression amount Psup-A is a positive value mainly in the time period around 12:00. In other words, the output of the power generation equipment 24-A is suppressed during this time period. The ratio of the time integration result of the pre-suppression power generation output Pps-A to the time integration result of the output suppression amount Psup-A is called the output suppression rate of the power generation equipment 24-A. In the illustrated example, the output suppression rate of the power generation equipment 24-A is approximately 10%.

[0019] Fig. 3 is a diagram showing another example of the power supply and demand analysis result. The power supply and demand analysis result AD-B shown in Fig. 3 shows an example of transition of various types of power at node 12-B from 0:00 to 24:00 on a certain day. The horizontal and vertical axes in Fig. 3 have the same meanings as those in Fig. 2. Furthermore, the power demand Pdem-B, pre-suppression power generation output Pps-B, power generation output Pgen-B, reverse power flow rate Prev-B, ideal reverse power flow rate Pir-B, available power transmission capacity Pth-B, and output suppression amount Psup-B in Fig. 3 correspond to Pdem-A, Pps-A, Pgen-A, Prev-A, Pir-A, Pth-A, and Psup-A shown in Fig. 2, respectively.

[0020] The power generation facility 24-B is, for example, a wind power generation facility, and its power output Pgen-B tends to increase and decrease randomly throughout the day. The ratio of the time integration result of the pre-suppression power output Pps-B to the time integration result of the output suppression amount Psup-B is called the output suppression rate of the power generation facility 24-B. In the illustrated example, the output suppression rate of the power generation facility 24-B is approximately 11%.

[0021] Returning to FIG. 1, the load equipment 26-X, 26-Y is equipment that has not yet been connected to the power grid 10. When these load equipment 26-X, 26-Y are connected to the power grid 10, they will be included in one of the nodes 12. If the load equipment 26-X, 26-Y are to be included in the nodes 12-A, 12-B, it is conceivable to connect the load equipment 26-X, 26-Y to the connection positions PA, PB shown by dashed lines in FIG. 1. The node 12 that includes the load equipment 26-X, 26-Y is preferably selected from the nodes 12 that can significantly reduce the output suppression rate, for example.

[0022] 4 is a diagram showing an example of power demands Pdem-X and Pdem-Y of the added load facilities 26-X and 26-Y. The horizontal and vertical axes in FIG. 4 have the same meanings as those in FIG. The load equipment 26-X is, for example, a commercial facility or an office building, and its power demand Pdem-X increases during the day and decreases at night. On the other hand, the load equipment 26-Y is, for example, an electric vehicle charging facility, and its power demand Pdem-Y increases from night to early morning and decreases during the day.

[0023] Comparative Example Next, in order to clarify the effect of this embodiment, an algorithm according to a comparative example for determining the destination of the load equipment 26-X and 26-Y will be described. In the comparative example, when load equipment 26-X, 26-Y is assigned to each node 12, the extent to which the output suppression rate can be reduced is calculated at each node 12, and the assignment destination of load equipment 26-X, 26-Y is determined based on the results.

[0024] Fig. 5 is a diagram illustrating an example of a power supply and demand analysis result according to a comparative example. That is, Fig. 5 is a diagram illustrating an example of a power supply and demand analysis result AD-AX of node 12-A when it is assumed that load equipment 26-X belongs to node 12-A. The power demand Pdem-AX, pre-suppression power generation output Pps-AX, power generation output Pgen-AX, reverse power flow rate Prev-AX, ideal reverse power flow rate Pir-AX, available power transmission capacity Pth-AX, and output suppression amount Psup-AX in Figure 5 correspond to Pdem-A, Pps-A, Pgen-A, Prev-A, Pir-A, Pth-A, and Psup-A shown in Figure 2, respectively.

[0025] That is, the power demand Pdem-AX is equal to the sum of the power demand Pdem-A (see FIG. 2) and the power demand Pdem-X (see FIG. 4). At node 12-A, the increase in power demand during the daytime extends the time during which the ideal reverse power flow rate Pir-AX is equal to or less than the available power transmission capacity Pth-AX. As a result, the reverse power flow rate Prev-AX is significantly reduced compared to the reverse power flow rate Prev-A (see FIG. 2). Accordingly, in the illustrated example, the output suppression rate of power generation facility 24-A is approximately 2%, which is a sufficiently lower value than the output suppression rate (approximately 10%) in the example of FIG. 2.

[0026] Fig. 6 is a diagram showing another example of the power supply and demand analysis result according to the comparative example. That is, Fig. 6 is a diagram showing an example of the power supply and demand analysis result AD-BX of node 12-B when it is assumed that load equipment 26-X belongs to node 12-B. The power demand Pdem-BX, pre-suppression power generation output Pps-BX, power generation output Pgen-BX, reverse power flow rate Prev-BX, ideal reverse power flow rate Pir-BX, available power transmission capacity Pth-BX, and output suppression amount Psup-BX in Figure 6 correspond to Pdem-B, Pps-B, Pgen-B, Prev-B, Pir-B, Pth-B, and Psup-B shown in Figure 3, respectively.

[0027] That is, the power demand Pdem-BX is equal to the sum of the power demand Pdem-B (see FIG. 3) and the power demand Pdem-X (see FIG. 4). Compared with the reverse power flow rate Prev-B (see FIG. 3), the reverse power flow rate Prev-BX is slightly reduced. Accordingly, in the illustrated example, the output curtailment rate of the power generation facility 24-B is approximately 9%. Although this value is slightly lower than the output curtailment rate in the example of FIG. 3 (approximately 11%), it is not a significant improvement. Thus, from the perspective of reducing the output curtailment rate, it can be seen that it is preferable to assign the load facility 26-X to node 12-A rather than to node 12-B.

[0028] Fig. 7 is a diagram showing yet another example of the power supply and demand analysis result according to the comparative example. That is, Fig. 7 is a diagram showing an example of the power supply and demand analysis result AD-AY of node 12-A when it is assumed that load equipment 26-Y belongs to node 12-A. The power demand Pdem-AY, pre-suppression power generation output Pps-AY, power generation output Pgen-AY, reverse power flow rate Prev-AY, ideal reverse power flow rate Pir-AY, available power transmission capacity Pth-AY, and output suppression amount Psup-AY in Figure 7 correspond to Pdem-A, Pps-A, Pgen-A, Prev-A, Pir-A, Pth-A, and Psup-A shown in Figure 2, respectively.

[0029] That is, the power demand amount Pdem-AY is equal to the sum of the power demand amount Pdem-A (see FIG. 2) and the power demand amount Pdem-Y (see FIG. 4). Compared to the reverse power flow amount Prev-A (see FIG. 2), the reverse power flow amount Prev-AY is slightly reduced. However, at node 12-A, output suppression is concentrated in the daytime. Therefore, even if load equipment 26-Y is added, the reduction in the output suppression amount Psup-AY is slight. In the example shown, the output suppression rate of power generation equipment 24-A is approximately 9%. This value is a small change compared to the output suppression rate (approximately 10%) in the example of FIG. 2.

[0030] Fig. 8 is a diagram showing yet another example of the power supply and demand analysis result according to the comparative example. That is, Fig. 8 is a diagram showing an example of the power supply and demand analysis result AD-BY of node 12-B when it is assumed that load equipment 26-Y is assigned to node 12-B. The power demand Pdem-BY, pre-suppression power generation output Pps-BY, power generation output Pgen-BY, reverse power flow rate Prev-BY, ideal reverse power flow rate Pir-BY, available power transmission capacity Pth-BY, and output suppression amount Psup-BY in Figure 8 correspond to Pdem-B, Pps-B, Pgen-B, Prev-B, Pir-B, Pth-B, and Psup-B shown in Figure 3, respectively.

[0031] That is, the power demand Pdem-BY is equal to the sum of the power demand Pdem-B (see FIG. 3) and the power demand Pdem-Y (see FIG. 4). The output suppression amount Psup-BY is reduced compared to the output suppression amount Psup-B (see FIG. 3), especially at night. Therefore, in the illustrated example, the output suppression rate of the power generation equipment 24-B is approximately 6%. This value is sufficiently smaller than the output suppression rate (approximately 11%) in the example of FIG. 2. Thus, from the perspective of reducing the output suppression rate, it can be seen that it is preferable to assign the load equipment 26-Y to node 12-B rather than to node 12-A.

[0032] In the examples shown in Figures 5 to 8 described above, it is possible to determine to which of the nodes 12-A and 12-B the added load facilities 26-X and 26-Y should preferably be assigned. However, this method has the problem that, for example, the contents of the power supply and demand analysis results AD shown in Figures 5 to 8 must be calculated, resulting in a large amount of calculation. Although Figure 1 shows five nodes 12-A to 12-E, the number of nodes 12 included in an actual power grid 10 is much larger. If the power supply and demand analysis results AD shown in Figures 5 to 8 are calculated for each of these many nodes, the amount of calculation becomes enormous.

[0033] Therefore, in this embodiment, the similarity between the time series data of the power demand Pdem of the load equipment 26 to be added and the time series data of the output suppression amount Psup of each node 12 is evaluated, and the destination of the load equipment 26 to be added is proposed based on the similarity.

[0034] Overall Configuration of First Embodiment FIG. 9 is a block diagram of a placement assistance device 50 (computer) in the first embodiment. In Figure 9, the placement assistance device 50 includes a power system information database 52, a power supply and demand analysis result database 54, a power supply and demand analysis unit 56, a similarity evaluation unit 58 (similarity evaluation process, similarity evaluation means), an input unit 60, and a display control unit 62 (display control means, display control process).

[0035] (Power System Information Database 52) The power system information database 52 is a database that stores settings and data necessary for power supply and demand analysis, and stores, for example, the following data: Thermal power generation information: This is information indicating the maximum output, minimum output, fuel type (oil, coal, natural gas), maintenance schedule, location, etc. of the power generation facility 24, which is a thermal power plant. Note that "location" includes not only the geographical location but also the node 12 to which it belongs.

[0036] · Fuel unit price information: This is information showing the unit price of fuel (oil, coal, natural gas) at thermal power plants. Nuclear and hydroelectric power generation information: This is information indicating the maximum output, minimum output, maintenance schedule, location, etc. of power generation facilities 24 such as nuclear power plants, run-of-river hydroelectric plants, and pumped storage power plants.

[0037] Renewable energy power generation information: This is information indicating the time series data of the power generation output Pgen (see Figure 2), the maximum value of the power generation output Pgen, the maximum value of the power generation output Pps before suppression, the location of the power generation equipment 24, etc., for the power generation equipment 24, which is a renewable energy power generation equipment. Weather data: This is weather data for the location where the power generation facility 24, which is a renewable energy power generation facility, is installed. The weather data includes time-series data such as wind direction, wind speed, and solar radiation. The weather data can be actual measurement data published by meteorological organizations or long-term reanalysis data.

[0038] Load equipment information: This is information indicating time-series data of the power demand Pdem of the load equipment 26 (see FIG. 2), the location of the load equipment 26, and the like. Power line information: This is information indicating the capacity, location, etc. of the power line 14. Substation information: This is information indicating the capacity, location, etc. of the substation 22.

[0039] (Electricity Supply and Demand Analysis Section 56) The power supply and demand analysis unit 56 calculates the power supply and demand analysis results AD of each node 12 (for example, the power supply and demand analysis results AD-A and AD-B shown in FIGS. 2 and 3) based on the contents of the power system information database 52 described above.

[0040] Typical renewable energy power generation facilities are solar power generation facilities and wind power generation facilities. The pre-suppression power output Pps of a renewable energy power generation facility can be obtained based on the maximum pre-suppression power output Pps and meteorological data. For example, the pre-suppression power output Pps of a solar power generation facility (e.g., Pps-A shown in FIG. 2) can be calculated based on the amount of solar radiation included in the meteorological data. Also, the pre-suppression power output Pps of a wind power generation facility (e.g., Pps-B shown in FIG. 3) can be calculated based on the wind speed.

[0041] If the pre-suppression power output Pps can be calculated, the output suppression amount Psup can be calculated by subtracting the time series data of the power output Pgen from the time series data. For example, in Figure 2, the output suppression amount Psup-A can be calculated by subtracting the power output Pgen-A from the pre-suppression power output Pps-A.

[0042] Furthermore, as time series data of the power demand Pdem due to existing load equipment 26, for example, the power demand Pdem-A in Figure 2, actual measurement data published by the electric power company or data calculated based on temperature and weekday / holiday divisions can be applied.

[0043] The power supply and demand analysis in the power supply and demand analysis unit 56 can be reduced to a fuel cost minimization problem with the power generation output Pgen of each power generation facility 24 as a variable. Constraints include a supply and demand balance constraint that matches supply and demand in the power grid 10, and a transmission capacity constraint that prevents the power passing through the transmission line 14 from exceeding the capacity of the transmission line 14. The power supply and demand analysis can be implemented as a mixed integer linear programming problem, with the start and stop of the power generation facility 24 represented as a binary variable (a variable that takes the value 0 or 1).

[0044] (Electricity supply and demand analysis results database 54) The power demand and supply analysis result database 54 stores the calculation results obtained by the power demand and supply analysis unit 56, that is, the power demand and supply analysis results AD.

[0045] (Similarity evaluation unit 58) The similarity evaluation unit 58 calculates and evaluates the similarity between the time series data of the output suppression amount Psup at each node 12 and the time series data of the power demand Pdem at the load equipment 26 that can be added (for example, the load equipment 26-X, 26-Y in Figure 1).

[0046] FIG. 10 is a schematic diagram showing an example of processing in the similarity evaluation unit 58. The similarity between the time series data of the output suppression amount Psup-A at node 12-A and the time series data of the power demand Pdem-X of load equipment 26-X is defined as Sim(A,X). Also, the similarity between the time series data of the output suppression amount Psup-B at node 12-B and the time series data of the power demand Pdem-X is defined as Sim(B,X). If it is evaluated that the power demand Pdem-X is more similar to the output suppression amount Psup-A than to the output suppression amount Psup-B based on the similarities Sim(A,X) and Sim(B,X), it can be determined that it is preferable to assign load equipment 26-X to node 12-A rather than to node 12-B.

[0047] Similarly, the similarity between the time series data of the output suppression amount Psup-A and the time series data of the power demand Pdem-Y of the load equipment 26-Y is defined as Sim(A,Y). Also, the similarity between the time series data of the output suppression amount Psup-B and the time series data of the power demand Pdem-Y is defined as Sim(B,Y). If it is evaluated that the power demand Pdem-Y is more similar to the output suppression amount Psup-B than to the output suppression amount Psup-A based on the similarities Sim(A,Y) and Sim(B,Y), it can be determined that it is preferable to assign the load equipment 26-Y to node 12-B rather than to node 12-A.

[0048] There are various possible methods for calculating similarity, but here we will explain an example in which RMSE (Root Mean Squared Error) is applied. When RMSE is applied, the similarity Sim(A,X) between the output suppression amount Psup-A and the power demand amount Pdem-X is "313". Also, the similarity Sim(B,X) between the output suppression amount Psup-B and the power demand amount Pdem-X is "524". Since the smaller the RMSE value, the higher the similarity, it can be seen that it is preferable to assign load equipment 26-X to node 12-A rather than node 12-B.

[0049] Furthermore, when RMSE was applied, the similarity Sim(A,Y) between the output suppression amount Psup-A and the power demand amount Pdem-Y was "407." Furthermore, the similarity Sim(B,Y) between the output suppression amount Psup-B and the power demand amount Pdem-Y was "383." As described above, the smaller the RMSE value, the higher the similarity, so it can be seen that it is preferable for load equipment 26-Y to be assigned to node 12-B rather than node 12-A.

[0050] As described above, in this embodiment, by focusing on the similarity between the output suppression amount Psup and the power demand amount Pdem of the load equipment 26 to be added, it is possible to determine to which node 12 the load equipment 26 should be assigned in terms of reducing the output suppression of renewable energy, even if only one power supply and demand analysis is performed. This method can significantly reduce the calculation load because it is sufficient to perform a power supply and demand analysis in a state where the load equipment 26 to be added is not included in the node 12. That is, in the example shown in FIGS. 2 to 8, it is sufficient to perform the power supply and demand analysis shown in FIGS. 2 and 3, and the power supply and demand analysis shown in FIGS. 5 to 8 is not necessary.

[0051] (input unit 60) The input unit 60 inputs time-series data of the power demand Pdem of the load equipment 26 to be added (for example, the power demands Pdem-X and Pdem-Y shown in FIG. 4). Examples of the input time-series data include "hourly values ​​for one year" (data in which 8,760 values ​​excluding leap years are arranged) and "hourly values ​​for a representative day for each season or day of the week" (data in which 24 values ​​are arranged). However, these time-series data are not limited to hourly values, and other time granularities, such as 30-minute values, may also be used. Furthermore, to facilitate the execution of power supply and demand analysis in various settings, the input unit 60 can input data to and update data in the power system information database 52.

[0052] (Display control unit 62) The display control unit 62 causes the display 70 to display a display screen 100 (see FIG. 11) showing the evaluation result by the similarity evaluation unit 58. 11 is a diagram showing an example of a display screen 100. The display screen 100 includes a map display field 110 and a legend display field 120. The map display field 110 displays squares (without symbols) across its entirety, and includes a plurality of node images 112-A to 112-E, a plurality of power line images 114, and a similarity display image 116.

[0053] Each node image 112 is a circular image corresponding to each node 12 shown in FIG. 1. Each power transmission line image 114 is a linear image corresponding to each power transmission line 14. The similarity display image 116 is an image arranged around the node image 112. The similarity display image 116 indicates the level of similarity between the time-series data of the power demand Pdem of the load equipment 26 to be added (e.g., load equipment 26-X) and the time-series data of the output suppression amount Psup at each node 12, according to the criteria indicated in the legend display field 120. In the illustrated example, the similarity display image 116 indicates the level of similarity with the shade of dots. This allows the area around the node image 112 with high similarity to be highlighted as a location that will lead to a reduction in the output suppression of renewable energy.

[0054] However, the level of similarity may be expressed by color instead of the shade of the dots. Also, in Fig. 11, squares are displayed throughout the map display field 110, but a map may be displayed instead of the squares so that real place names can be associated with them. Note that in Fig. 11, the similarity display image 116 is not displayed around the node image 112-D. This indicates that the corresponding node 12-D (see Fig. 1) does not include any renewable energy power generation facilities, and therefore the similarity Sim has not been calculated.

[0055] <Computer Configuration> 12 is a block diagram of the computer 980. The placement assistance device 50 shown in FIG. 9 includes one or more computers 980 shown in FIG. 12, a computer 980 includes a CPU 981, a storage unit 982, a communication I / F (interface) 983, an input / output I / F 984, and a media I / F 985. Here, the storage unit 982 includes a RAM 982a, a ROM 982b, and an SSD (Solid State Drive) 982c. The communication I / F 983 is connected to a communication circuit 986. The input / output I / F 984 is connected to an input / output device 987. The media I / F 985 reads and writes data from a recording medium 988. The ROM 982b stores an IPL (Initial Program Loader) executed by the CPU, etc. The SSD 982c stores application programs, various data, etc. The CPU 981 executes application programs, etc. loaded from the SSD 982c to the RAM 982a, thereby realizing various functions. The interior of the placement assistance device 50 shown in FIG. 9 is primarily a block diagram of functions realized by application programs and the like.

[0056] <Operation of the First Embodiment> Next, the operation of the first embodiment will be described. 13 is a flowchart of the analysis routine in the first embodiment. This routine is executed by the placement assistance device 50 (see FIG. 9). 13, when the process proceeds to step S2, the similarity evaluation unit 58 acquires various data. That is, the similarity evaluation unit 58 acquires the power supply and demand analysis results AD (see FIGS. 2 and 3) of each node 12 from the power supply and demand analysis result database 54. The similarity evaluation unit 58 also acquires the power demand Pdem of the load equipment to be added (for example, the power demands Pdem-X and Pdem-Y shown in FIG. 4) via the input unit 60. Here, the load equipment to be added is referred to as load equipment 26-k (not shown), and its power demand is referred to as Pdem-k (not shown).

[0057] Next, when the process proceeds to step S4, the similarity evaluation unit 58 selects one node that has not yet undergone the process of step S6, which will be described later, from among all nodes 12 including the power generation facility 24, which is a renewable energy power generation facility. The selected node is referred to as node 12-i, and its output suppression amount is referred to as Psup-i (not shown). Next, when the process proceeds to step S6, the similarity evaluation unit 58 calculates and evaluates the similarity Sim(i,k) between the time series data of the output suppression amount Psup-i and the time series data of the power demand Pdem-k.

[0058] Next, when the process proceeds to step S8, the similarity evaluation unit 58 determines whether or not the process of step S6 has been executed for all nodes 12 including the power generation facility 24, which is a renewable energy power generation facility. If the determination result is negative, the process returns to step S4, and if the determination result is positive, the process proceeds to step S10.

[0059] Next, when the process proceeds to step S10, the similarity evaluation unit 58 causes the display 70 to display a display screen 100 (see FIG. 11) in which each node 12 is associated with the similarity Sim(i, k) via the display control unit 62. This completes the process of this routine.

[0060] [Variations] The present invention is not limited to the above-described embodiment, and various modifications are possible. The above-described embodiment is an example for explaining the present invention in an easy-to-understand manner, and is not necessarily limited to an embodiment having all of the described configurations. Furthermore, other configurations may be added to the configurations of the above-described embodiment, and some of the configurations may be replaced with other configurations. Furthermore, the control lines and information lines shown in the figures are those considered necessary for explanation, and do not necessarily represent all control lines and information lines necessary in the product. In reality, it can be assumed that almost all configurations are interconnected. Possible modifications of the above-described embodiment include, for example, the following.

[0061] 1. Modifications of the Similarity Evaluation Unit 58 First, various modifications of the similarity evaluation unit 58 will be described. (1) In the above example, the RMSE (Root Mean Squared Error) was used as an index for evaluating the similarity in the similarity evaluation unit 58. However, various other indices can be used. For example, correlation coefficient, MSE (Mean Squared Error), MAE (Mean Absolute Error), and Max Error may be used. Furthermore, indices for evaluating the similarity of time series, such as Euclidean distance, Manhattan distance, and DTW (Dynamic Time Warping), may also be used.

[0062] (2) Furthermore, the time series data of the power demand Pdem of the load equipment 26 to be added and the output suppression amount Psup of each node 12 can be regarded as a high-dimensional vector. For example, the 24 values ​​constituting one hour of a certain day can be regarded as a 24-dimensional vector. Therefore, by clustering the vectors related to the power demand Pdem and the output suppression amount Psup, it can be determined that the vectors of the power demand Pdem that belong to the same class as the vector related to the output suppression amount Psup have a high similarity, and the vectors of the power demand Pdem that belong to other classes have a low similarity. For example, the K-means method can be used as an algorithm for clustering the vectors.

[0063] (3) The scale of the power demand Pdem of the load equipment 26 to be added and the output suppression amount Psup of each node 12 may differ significantly. In this case, even if the shapes of the time-series data of both are similar, applying the RMSE or the like described above as the similarity Sim may result in a judgment that the similarity between the two is low. Therefore, it is advisable to evaluate the similarity Sim between the two after normalizing or standardizing the power demand Pdem and the output suppression amount Psup. Here, "normalization" refers to the result of dividing the power demand Pdem and the output suppression amount Psup by their respective maximum values, and these amounts can be converted to values ​​between "0" and "1." Furthermore, "standardization" refers to the value obtained by subtracting the average value from the power demand Pdem and the output suppression amount Psup and dividing the result by the standard deviation.

[0064] The normalized similarities Sim(A,X), Sim(A,Y), Sim(B,X), and Sim(B,Y) shown in FIG. 10 are referred to as normalized similarities NSim(A,X), NSim(A,Y), NSim(B,X), and NSim(B,Y), respectively (not shown). The normalized similarity NSim(A,X) based on RMSE was 0.62, and the normalized similarity NSim(B,X) was 0.75. This indicates that it is preferable to assign load equipment 26-X (see FIG. 1) to node 12-A rather than node 12-B. Furthermore, the normalized similarity NSim(A,Y) based on RMSE was 0.76, and the normalized similarity NSim(B,Y) was 0.61. This shows that it is preferable to assign the load equipment 26-Y (see FIG. 1) to the node 12-B rather than to the node 12-A.

[0065] (4) In the above example, the power system information database 52 stores the output suppression amount Psup for each node 12. However, instead, it may store time-series binary data indicating whether or not output suppression has occurred. This time-series data may be, for example, "1" at the time when output suppression has occurred and "0" at the time when output suppression has not occurred.

[0066] (5) In the above example, the similarity Sim between the time-series data of the power demand Pdem of the load equipment 26 to be added and the output suppression amount Psup of each node 12 was calculated and evaluated using time-series data for all time periods. However, the similarity Sim may be calculated and evaluated using time-series data only for the time periods when output suppression occurs. This method is particularly suitable for nodes 12 with a large amount of solar power generation, where output suppression is concentrated during the daytime.

[0067] 2. Modified Examples of Placement Support Device 50 The configuration of the placement assistance device 50 shown in FIG. 9 is not limited to the one shown in the figure, and various modifications are possible, for example, as follows. (1) The power system information database 52 and the power supply and demand analysis result database 54 may be stored in a database server (not shown) located outside the layout assistance device 50.

[0068] (2) The power system information database 52 and the power supply and demand analysis unit 56 may be provided outside the allocation support device 50, and the power supply and demand analysis results AD may be input to the power supply and demand analysis results database 54 of the allocation support device 50 by these.

[0069] (3) The placement assistance device 50 may be implemented on a web server, and the input unit 60 and the display control unit 62 may be realized by a computer used by a user. In this case, the input unit 60 and the display control unit 62 are realized by the computer executing a script delivered from a web page. This may allow a user who is an electricity consumer to input, from the input unit 60, the electricity demand Pdem of a load facility 26 that the user intends to newly add.

[0070] (4) Furthermore, the placement assistance device 50 may be a system having a three-tiered web structure, in which the power system information database 52 and the power supply and demand analysis result database 54 are a data layer, the power supply and demand analysis unit 56 and the similarity evaluation unit 58 are an application layer, and the input unit 60 and the display control unit 62 are a presentation layer.

[0071] 3. Application of the Placement Support Device 50 (1) As described above, the layout assistance device 50 can propose the allocation of load equipment 26 from the perspective of reducing output curtailment of renewable energy. Furthermore, the layout assistance device 50 can also be used as a tool for visualizing values ​​obtained from power supply and demand analysis. For example, the amount of output curtailment for each node can be visualized. A node 12 with a high amount of output curtailment can be interpreted as needing to charge during times of output curtailment and discharge during times of no output curtailment. Therefore, by visualizing nodes with a high amount of output curtailment, it is possible to efficiently search for locations where output curtailment can be reduced by installing a grid storage battery.

[0072] (2) The placement assistance device 50 may also be used to efficiently search for a node 12 for which increasing the power demand Pdem will not worsen power transmission congestion. The similarity between the time series data of the power demand Pdem of the load equipment 26 to be added and the time series data of the residual demand (the amount obtained by subtracting the renewable energy power generation output Pgen from the power demand Pdem) of each node 12 is evaluated. If the time series data of the power demand Pdem to be added and the time series data of the residual demand are highly similar, the peak of the power demand Pdem at the node 12 will become even larger. If the peak of the power demand Pdem exceeds the power receiving capacity of the node 12, the node 12 will experience a supply shortage, i.e., the power transmission congestion will worsen. Conversely, if the similarity between the time series data of the power demand Pdem to be added and the time series data of the residual demand is low, it is easier to avoid peak overlap and worsening power transmission congestion.

[0073] (3) The location assistance device 50 can also be applied to creating a welcome zone map. For power transmission and distribution companies, a welcome zone map is a map that shows locations where electricity can be provided relatively quickly and at low cost. Power transmission and distribution companies use the welcome zone map to guide load facilities. On the other hand, for renewable energy power generation companies, a welcome zone map can be said to be a map that shows "locations where the placement of load facilities 26 will lead to a reduction in the output suppression of renewable energy." Renewable energy power generation companies can avoid output suppression by guiding new load facilities 26 near suitable locations for renewable energy power generation facilities. The location assistance device 50 can be useful in creating welcome zone maps for renewable energy power generation companies.

[0074] (4) In recent years, the installation of load facilities 26 with large power consumption, such as data centers, charging facilities for electric vehicles, hydrogen production facilities using water electrolysis, and facilities for separating and capturing carbon dioxide from the atmosphere (direct air capture), is expected. The layout support device 50 is useful when arranging these load facilities 26. It is also useful when arranging conventional load facilities such as commercial facilities, offices, residences, and factories, while taking into consideration the suppression of renewable energy output.

[0075] 4. Other Modifications (1) Since the hardware of the placement assistance device 50 in the above embodiment can be realized by a general computer, the processes corresponding to the above-mentioned block diagrams and flowcharts, as well as programs that execute the various processes described above, may be stored on a storage medium (a computer-readable storage medium on which a program is recorded) or distributed via a transmission path.

[0076] (2) In the above embodiment, the processes corresponding to the block diagrams and flowcharts, as well as the various other processes described above, are described as software processes using programs. However, some or all of these processes may be replaced with hardware processes using an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array), etc.

[0077] [Effects of the embodiment] As described above, according to the embodiment, the placement assistance device 50 includes a similarity evaluation unit 58 that calculates the similarity Sim between the time series data of the power demand Pdem-X, Pdem-Y of the load equipment 26-X, 26-Y that can be added to any of the nodes 12 belonging to the power grid 10 and the time series data of the output suppression amount Psup of the renewable energy power generation at each node 12, and a display control unit 62 that associates the node 12 with the similarity Sim and displays it on the display 70.

[0078] This allows the placement assistance device 50 to appropriately propose installation locations for load facilities. In the comparative example described above, it was necessary to calculate the power supply and demand analysis results AD-AX, AD-BX, AD-AY, and AD-BY (see FIGS. 5 to 8) that link the power demands Pdem-X and Pdem-Y of the load facilities 26-X and 26-Y that can be added, which resulted in a problem of an enormous amount of calculation. On the other hand, in the embodiment described above, such power supply and demand analysis results AD-AX, AD-BX, AD-AY, and AD-BY are unnecessary, so the amount of calculation can be reduced. This makes it possible to compare, for example, various patterns of power demand Pdem. Furthermore, because the power supply and demand analysis is performed only once, it is easy to increase the number of nodes, which is also preferable in terms of accuracy.

[0079] Furthermore, it is more preferable that the layout assistance device 50 further comprises an input unit 60 that inputs the power demand amounts Pdem-X and Pdem-Y, and a power supply and demand analysis unit 56 that calculates the output suppression amount Psup by setting the maximum value of the power generation output Pgen that can be achieved by the renewable energy power generation facility 24 included in the node 12 as the pre-suppression power generation output Pps and subtracting the actual power generation output Pgen from the pre-suppression power generation output Pps. This makes it possible to calculate the output suppression amount Psup based on the pre-suppression power generation output Pps and the power generation output Pgen. [Explanation of symbols]

[0080] 10 Power grid 12 nodes 24 Power generation facilities 26 Load equipment 50 Placement support device (computer) 56 Electric Power Supply and Demand Analysis Department 58 Similarity evaluation unit (similarity evaluation process, similarity evaluation means) 60 Input section 62 Display control unit (display control process, display control means) 70 Display Pps Power output before suppression Sim similarity Pgen power output Psup output suppression amount Pdem electricity demand

Claims

1. a similarity evaluation unit that calculates a similarity between time series data of power demand of load equipment that can be added to any node belonging to the power network and time series data of output suppression amount of renewable energy power generation at each of the nodes; a display control unit that associates the node with the similarity and displays it on a display. A placement assistance device characterized by:

2. an input unit for inputting the amount of power demand; a power supply and demand analysis unit that sets a maximum value of power output that can be realized by a power generation facility of renewable energy power generation included in the node as a pre-suppression power output, and calculates the output suppression amount by subtracting the actual power output from the pre-suppression power output.

2. The arrangement assistance device according to claim 1.

3. a similarity evaluation process for calculating a similarity between time series data of the power demand of a load facility that can be added to any node belonging to the power grid and time series data of the output suppression amount of renewable energy power generation at each of the nodes; a display control step of associating the nodes with the similarities and displaying them on a display. A placement support method characterized by:

4. Computer, a similarity evaluation means for calculating a similarity between time series data of the power demand of a load facility that can be added to any node belonging to the power grid and time series data of the output suppression amount of renewable energy power generation at each of the nodes; a display control means for displaying the nodes and the similarities on a display in association with each other; A program to function as a

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