Forecasting Method

Abstract

To provide a technique of suppressing a load of simulation processing while securing a prediction accuracy.SOLUTION: A prediction device for predicting the change of a voltage of a power system, comprises: a simulation processing part that executes simulation processing for predicting the change of a voltage in each first division region preset by a predetermined first operation period; an extraction part that extracts an unstable portion that the change of the predicted voltage is deviated from a predetermined acceptable range; and a setting part of resetting a plurality of second division regions obtained by finely dividing a second operation period obtained by finely dividing the first operation period or the first division region to the first division region corresponded to the unstable portion. The simulation processing part executes the simulation processing in the second operation period or the second division region, reset to the first division region corresponded to the unstable portion, and predicts the change of the voltage.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a technique for predicting voltage changes in a power system. [Background technology]

[0002] Patent Document 1 discloses a renewable energy system stabilization system having an operational limit value management unit that manages operational limit values ​​related to the flow power of system equipment, and a determination unit that calculates the flow state of the power system for each future set time based on power supply information including power generation plan values, output forecast values, and power demand forecast values, compares it with the operational limit values, and determines whether each flow state is stable or not. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-100325 Summary of the Invention [Problem to be solved by the invention]

[0004] With the spread of renewable energy generation and rechargeable vehicles, the amount of electricity supply and demand is prone to change significantly in a short period of time. On the other hand, if prediction simulations are performed frequently to accurately predict electricity supply and demand, the processing load will increase.

[0005] An object of the present invention is to provide a technique for reducing the load of simulation processing while ensuring prediction accuracy. [Means for solving the problem]

[0006] In order to solve the above problem, one aspect of the present invention is a prediction method for predicting the supply and demand of a power system and predicting locations where the power system will become unstable, comprising: a first step of executing a simulation process for predicting the power supply and demand for each preset first divided area in a predetermined first calculation period; a second step of extracting locations where the voltage of the power system is unstable, derived based on the predicted power supply and demand; a third step of re-setting a second calculation period obtained by subdividing the first calculation period or a plurality of second divided areas obtained by subdividing the first divided area for the first divided area corresponding to the unstable locations; and a fourth step of executing a simulation process in the second calculation period or the second divided areas re-set for the first divided area corresponding to the unstable locations. a fifth step of extracting unstable points in the power system from the power supply and power demand predicted in the fourth step; a sixth step of setting a plurality of second partitioned areas by subdividing the first partitioned area corresponding to the unstable points; a seventh step of executing a simulation process for each second calculation period and each of the plurality of second partitioned areas set for the first partitioned area corresponding to the unstable points; and an eighth step of extracting unstable points in the power system from the power supply and power demand predicted in the seventh step. Includes. [Effects of the Invention]

[0008] According to the present invention, it is possible to provide a technique for reducing the load of simulation processing while ensuring prediction accuracy. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram for explaining the scale of an electric power network. [Figure 2] Figure 2(a) is a diagram showing the amount of power supply from solar power generation devices located in a town-wide network, Figure 2(b) is a diagram showing the amount of power consumption from consumers located in the town-wide network, and Figure 2(c) is a diagram showing the amount of power consumption from vehicle charging devices located in the town-wide network. [Figure 3] FIG. 1 is a diagram for explaining prediction of unstable points in a power network. [Figure 4] FIG. 1 is a diagram illustrating a functional configuration of an energy state prediction device according to an embodiment. [Figure 5] 10A and 10B are diagrams for explaining the subdivided setting process of the setting unit when an unstable portion is extracted. [Figure 6] 1 is a flowchart of a process for controlling the voltage of a power system in a power network. [Figure 7] 10 is a flowchart of a simulation process for predicting a change in voltage of a power system. [Figure 8] 8 is a flowchart of the load handling process of S40 in FIG. 7. DETAILED DESCRIPTION OF THE INVENTION

[0010] FIG. 1 is a diagram illustrating the scale of a power network 1. The power network 1 is monitored by an energy state prediction device of the embodiment to determine whether a stable power supply is possible. That is, the energy state prediction device predicts the power supply and demand of the power network 1, and predicts unstable points that may occur in the voltage of the power system of the power network 1.

[0011] Demand-side devices and supply-side devices are connected to the power grid of the power network 1. The demand-side devices include consumers such as businesses and households, as well as charging devices that supply energy to plug-in hybrid electric vehicles, fuel cell electric vehicles, and battery electric vehicles. The supply-side devices include power generation devices such as solar power generation and thermoelectric power generation, and storage battery devices. The supply-side devices may also include hydrogen fuel cells. These demand-side devices and supply-side devices have sensors that detect the amount of discharge and the amount of stored power, and are connected to the energy state prediction device via the network. The amount of power demand can be predicted based on the detection results of the demand-side devices, and the amount of power supply can be predicted based on the detection results of the supply-side devices.

[0012] The power network 1 can be understood as a hierarchical structure consisting of an entire town network 10, a backbone network 12 that divides the entire town network 10, and sectioned networks 14 that further divide the backbone network 12, with the scale decreasing in this order. The larger the scale, the less load the energy state prediction device can perform state prediction simulations, but the prediction accuracy decreases. On the other hand, if the energy state prediction device performs simulations on a small scale for each sectioned network 14, the prediction accuracy increases, but the load increases because simulations are performed for each sectioned network 14 for the entire town. It is preferable to invest energy and costs in response to increased loads in order to reduce processing load and energy and costs in line with the SDGs (Sustainable Development Goals).

[0013] Fig. 2(a) is a diagram showing the amount of power supplied by solar power generation devices arranged in the entire town network 10, Fig. 2(b) is a diagram showing the amount of power used by consumers arranged in the entire town network 10, and Fig. 2(c) is a diagram showing the amount of power used by vehicle charging devices arranged in the entire town network 10. The horizontal axis of Fig. 2(a) to Fig. 2(c) represents one day from 0:00 to 24:00, and the vertical axis represents the amount of power supplied or the amount of power used.

[0014] The power supply of the solar power generation system shown in Figure 2(a) increases with sunrise and decreases from midday to sunset. The power supply of the solar power generation system also temporarily decreases during the day due to cloudy weather or rain.

[0015] The power consumption of consumers shown in Figure 2(b) increases from morning to evening and decreases toward midnight. The power consumption of vehicle charging devices shown in Figure 2(c) increases during the morning and evening rush hours.

[0016] The amount of power supplied by a solar power generation system varies greatly depending on the weather. As such, the amount of power supplied by renewable energy sources is unstable. Furthermore, vehicle charging systems can also vary greatly in a short period of time. As a result, large fluctuations in supply and demand in localized areas can cause supply-demand gaps, potentially leading to unstable voltage in the power grid. Because supply and demand can vary significantly in a short period of time, shortening the calculation cycle can improve prediction accuracy. However, shortening the calculation cycle increases the processing load. Therefore, the energy status prediction device of the embodiment sets the scale and calculation cycle according to the situation, and executes simulation processing while reducing the processing load to suit the SDGs.

[0017] 3 is a diagram for explaining prediction of unstable points in the power network 1. In the power system of the power network 1, a battery device 16 is arranged as a supply-side device, and a charging device 18 and a consumer 20 are arranged as demand-side devices. The supply-side devices may include a fuel cell that uses hydrogen fuel, a power generation device that recovers exhaust heat, and the like.

[0018] The battery device 16 transmits the remaining battery charge SOC to the energy state prediction device via a network. The remaining battery charge SOC of the multiple battery devices 16 shown in FIG. 3 increases during the day due to supply from the solar power generation device, and decreases according to the power demand of the charging device 18 and consumers 20 such as homes and businesses. The charging device 18 and consumers 20 transmit their power demands to the energy state prediction device via a network. The supply-side device and the demand-side device transmit detection results related to power at every measurement period, for example, every 10 seconds. Note that the supply-side device and the demand-side device are not limited to the devices shown in FIG. 3. For example, the supply-side device may include a switch installed in a substation or on a utility pole, or may include a fuel cell.

[0019] The energy state prediction device predicts the amount of power supply and demand in, for example, region 22a and region 22b, and estimates the future voltage value V of the power grid 22 based on the supply-demand gap. In region 22b, the predicted voltage value V (22b) is within an allowable range from the reference voltage value and is stable. In region 22a, the voltage value V (22a) predicted at time t0 falls outside the allowable range from the reference voltage value around time t1 and becomes unstable. The energy state prediction device predicts the future energy state of the power grid 22, i.e., the voltage value V of the power grid 22, and extracts unstable points 24 from the predicted energy state.

[0020] 4 is a diagram showing the functional configuration of the energy state prediction device 30 of the embodiment. The various functions of the energy state prediction device 30 can be configured in hardware using circuit blocks, memory, and other LSIs, and can be realized in software using programs loaded into memory, etc. Therefore, it will be understood by those skilled in the art that the various functions of the energy state prediction device 30 can be realized in various forms using only hardware, only software, or a combination thereof, and are not limited to any one of them.

[0021] The energy state prediction device 30 includes an acquisition unit 32, a simulation processing unit 34, an extraction unit 36, a setting unit 38, a load response unit 40, and a control unit 42. The acquisition unit 32 acquires information indicating the available power supply from supply-side devices arranged in the energy network 1, and acquires information indicating the demanded power from demand-side devices.

[0022] The simulation processing unit 34 executes a simulation process that predicts the amount of power supply and the amount of power demand for each preset divisional area at a predetermined calculation cycle, and predicts changes in the voltage of the power grid 22 based on the predicted supply-demand gap. The simulation processing unit 34 predicts the amount of power supply based on information indicating the available power supply from the supply-side devices, predicts the amount of power demand based on information indicating the power demand from the demand-side devices, calculates the supply-demand gap for each divisional area from the predicted amount of power supply and the amount of power demand, and predicts changes in the voltage value of the power grid 22 based on the calculated supply-demand gap. A larger supply-demand gap results in a larger change in the voltage value from the reference voltage value. The supply-demand gap may include the remaining fuel in the fuel cell converted into power, and the energy state of the power grid 22 is indicated by a voltage value.

[0023] The predetermined calculation period is, for example, a first calculation period of every minute or a second calculation period of every 10 seconds. The simulation processing unit 34 executes the simulation process at the first calculation period or the second calculation period according to the setting by the setting unit 38. The preset divided areas are, for example, first divided areas such as the areas 22a and 22b shown in FIG. 3, or second divided areas obtained by further subdividing the first divided areas. That is, the simulation processing unit 34 executes the simulation process for each first divided area or each second divided area at the first calculation period or the second calculation period. The second calculation period is a subdivision of the first calculation period, and the second divided area is a subdivision of the first divided area. An ID is assigned to each of the first divided area and the second divided area. A second divided area included in a first divided area is associated with the first divided area. When the first calculation period and the second calculation period are not distinguished, they are simply referred to as the calculation period, and when the first divided area and the second divided area are not distinguished, they are simply referred to as the divided area.

[0024] When the extraction unit 36 ​​determines that there is an unstable point in the voltage value of the power system 22 in the divided area, the simulation processing unit 34 executes the simulation processing in the second calculation period or the second divided area. In other words, when there is an unstable point in the predicted voltage value, the calculation period or the divided area is subdivided and the simulation processing is executed. This makes it possible to predict the unstable point with high accuracy. Details of this subdivision processing will be described later.

[0025] The extraction unit 36 ​​determines whether the voltage value of the power grid 22 predicted by the simulation processing unit 34 is within a predetermined tolerance range from a reference voltage value, and extracts voltage values ​​outside the tolerance range from the reference voltage value as unstable locations. For example, the reference voltage value is set to 350V (volts) and the tolerance range is set to ±50V. The extraction unit 36 ​​calculates the ID of the divided area in which it was determined that an unstable location exists and the time at which this occurred. The extraction unit 36 ​​may extract unstable locations based on the power supply and demand gap predicted by the simulation processing unit 34.

[0026] The setting unit 38 sets the calculation period and the division area of ​​the simulation process depending on whether or not there is an unstable part. If there is no unstable part, the setting unit 38 sets the first calculation period and the first division area. As a result, the simulation processing unit 34 predicts voltage changes in the voltage system for each first division area in the first calculation period. If there is an unstable part, the setting unit 38 sets the second calculation period and / or the second division area. This subdivision setting process will be explained with reference to new drawings.

[0027] FIG. 5 is a diagram illustrating the subdivision setting process of the setting unit 38 when an unstable location is extracted. In FIG. 5(a), the simulation processing unit 34 executes a simulation process at time t0, which is the current time of 6:00:00, and predicts a voltage change in the power system for each first segmented region. The extraction unit 36 ​​extracts an unstable location based on the predicted voltage change and determines that the unstable location is located at time t1, which is approximately three minutes after time t0. In response to the extraction of the unstable location, the setting unit 38 first subdivides and resets the calculation cycle for the first segmented region corresponding to the unstable location. That is, the setting unit 38 resets the first calculation cycle, which is every minute, to a second calculation cycle, which is every 10 seconds. Therefore, the next simulation process will be at 6:00:10, not 6:01:00.

[0028] In FIG. 5(b), the simulation processing unit 34 predicts voltage changes in the power system for each first partitioned area at the current time, 6:00:10, which is time t2. The extraction unit 36 ​​extracts unstable areas around time t1 from the simulation results at time t2. This allows the calculation cycle to be shortened when an unstable area is extracted for the first time, allowing the unstable area to be quickly reconfirmed. Furthermore, by increasing the time resolution, the unstable area can be predicted with high accuracy.

[0029] In response to the extraction of two consecutive unstable portions, the setting unit 38 subdivides the first segmented region 22a corresponding to the unstable portions and resets each of the first segmented regions 22a into second segmented regions 50. For example, in FIG. 5, the second segmented region 50 is formed by subdividing the six squares that make up the first segmented region 22a into individual squares. The first segmented region may be subdivided into second segmented regions at a predetermined division ratio, or may be subdivided into preset second segmented regions.

[0030] In Figure 5(c), the simulation processing unit 34 predicts voltage changes in the power system for each second sectional area at time t3, which is the current time of 6:00:20. When two consecutive unstable areas are extracted in this way, the simulation processing unit 34 predicts voltage changes in the power system for each second sectional area in the second calculation cycle. In this way, the setting unit 38 first subdivides only the calculation cycle, and then subdivides the sectional areas in the next calculation cycle.

[0031] 5(c), the extraction unit 36 ​​extracts an unstable portion around time t1 from the simulation result at time t3. At this time, since the accuracy of the simulation has increased, the extraction unit 36 ​​calculates the period of the unstable portion with higher accuracy than in the previous simulation.

[0032] If three consecutive unstable locations are detected, the control unit 42 executes suppression control to suppress power usage for demand-side devices located in the second segment where the unstable location is predicted to occur. In other words, the control unit 42 initiates suppression control only if an unstable location is found even after simulations are performed by subdividing the calculation cycle and segment. For example, the control unit 42 prohibits the use of demand-side devices in a predetermined order of priority during suppression control. For example, the priority may be set so that business, home, and vehicle charging devices are given the highest priority and are protected in this order. This allows appropriate measures to be taken for unstable locations that are ultimately detected with high accuracy. Furthermore, even if the simulation processing unit 34 performs a simulation by suppressing the load in the first calculation cycle, if an unstable location is detected, the unstable location can be accurately reconfirmed without waiting for the next first calculation cycle.

[0033] Returning to FIG. 4, the first calculation period set by the setting unit 38 may be, for example, four or more times the second calculation period, or ten or less times the second calculation period. By making the first calculation period four or more times the second calculation period, if an unstable portion is extracted, it can be reconfirmed with high accuracy before the next first calculation period. Furthermore, by making the first calculation period ten or less times the second calculation period, the processing load can be reduced.

[0034] When an unstable portion is extracted and the second calculation cycle or the second partitioned region is reset, the load management unit 40 determines whether extraction of the unstable portion can be completed by the next calculation cycle. If it is determined that extraction of the unstable portion cannot be completed by the next calculation cycle, the load management unit 40 adds a processing unit (CPU). The added CPU may be, for example, a cloud server, and the load management unit 40 recognizes the processing capacity of the added CPU in advance. Furthermore, if it is determined that extraction of the unstable portion cannot be completed by the next calculation cycle even after adding a processing unit, the load management unit 40 decides to simplify the simulation process. The simplification of the simulation process is performed, for example, by thinning out the data used in the simulation process. The demand-side device and the supply-side device transmit information related to power to the energy status prediction device 30, for example, every 10 seconds. For example, the simulation processing unit 34 thins out the information related to power by half and uses information related to power every 20 seconds. In this way, when the load of the simulation process is high, the simulation processing unit 34 thins out and simplifies the data used in the simulation process.

[0035] Furthermore, the simulation processing unit 34 may thin out the data used in the simulation process until an unstable portion is extracted. For example, the simulation process in the first calculation cycle until an unstable portion is extracted is performed using half of the information related to the power transmitted every 10 seconds. After an unstable portion is extracted, the simulation process in the second calculation cycle is performed using all of the information related to the power transmitted every 10 seconds. In this way, the amount of data used in the simulation process may be varied depending on whether or not an unstable portion is extracted, and if no unstable portion is extracted, the amount of data used in the simulation process may be reduced. This reduces the processing load until an unstable portion is extracted.

[0036] Fig. 6 is a flowchart of a process for controlling the voltage of the power grid 22 of the power network 1. The process shown in Fig. 6 is repeatedly executed at a calculation cycle by the simulation processing unit 34. The simulation processing unit 34 executes a simulation process for predicting a voltage change in the power grid 22 for each divided area, and calculates a change in the voltage value for, for example, 10 minutes later (S10).

[0037] The extraction unit 36 ​​determines whether there is an unstable voltage change point in each divided region predicted by the simulation processing unit 34 (S12). That is, the extraction unit 36 ​​extracts, from the voltage change in each divided region predicted by the simulation processing unit 34, a voltage value that is outside a predetermined allowable range from the reference voltage as an unstable point. The extraction unit 36 ​​stores the divided region and time of the extracted unstable point in memory. If the extraction unit 36 ​​does not extract an unstable point (N in S12), the first flag and the second flag are all turned off, and this process ends.

[0038] If the extraction unit 36 ​​extracts an unstable portion (Y in S12), the setting unit 38 determines whether the first flag is on (S14). If the first flag is not on (N in S14), the setting unit 38 turns on the first flag and ends this process (S18). The first flag and the second flag are used in the simulation process shown in S10.

[0039] If the first flag is on (Y in S14), the setting unit 38 determines whether the second flag is on (S20). If the second flag is not on (N in S20), the setting unit 38 turns on the second flag and ends this process (S22).

[0040] If the second flag is on (Y in S20), the control unit 42 executes suppression control to suppress the use of power in the second divided area including the unstable portion (S24). In this way, measures can be taken to stabilize the power supply for the unstable portion that has been finally extracted with high accuracy.

[0041] Fig. 7 is a flowchart of a simulation process for predicting a change in voltage in a power system. Fig. 7 shows the simulation process of S10 in Fig. 6. The setting unit 38 determines whether the first flag is on (S30). If the first flag is not on (N in S30), the setting unit 38 sets the simulation process to be performed for the first calculation cycle and for each first partitioned region, and completes the setting (S38).

[0042] If the first flag is on (Y in S30), the setting unit 38 subdivides the first calculation cycle and sets it to a second calculation cycle (S32). Note that if the first calculation cycle has already been set to the second calculation cycle, the setting unit 38 sets it to the second calculation cycle as is.

[0043] If the second calculation cycle is set, the setting unit 38 determines whether the second flag is on (S34). If the second flag is not on (N in S34), the setting is completed (S38). If the second flag is on (Y in S34), the first segmented area is divided into second segmented areas (S36), and the setting is completed (S38).

[0044] When the second calculation cycle or the second partitioned region is reset and extraction of the unstable portion cannot be completed by the next calculation cycle, the load handling unit 40 adds a CPU or simplifies the processing (S40).

[0045] The simulation processing unit 34 executes a simulation process to predict voltage changes in the power system 22 for each set division area at a calculation period set by the setting unit 38 (S42), and stores the voltage changes for each division area in memory (S44).

[0046] Fig. 8 is a flowchart of the load handling process of S40 in Fig. 7. The load handling unit 40 first sets CPU=1 (S50). A larger number of CPUs indicates a higher processing speed, and CPU=1 indicates a normal number of CPUs. CPU=2 is not limited to being twice the processing speed of CPU=1, and indicates that the processing speed is increased by adding a CPU.

[0047] The load management unit 40 calculates the calculation time from the simulation processing by the simulation processing unit 34 to the extraction of unstable parts by the extraction unit 36 ​​(S52). The load management unit 40 determines whether the calculation time is within the set calculation period, i.e., whether it will be in time for the next calculation period (S54). If the calculation time is not within the calculation period (N in S54), the load management unit 40 adds one CPU (S56) and recalculates the calculation time (S52).

[0048] If the calculation time is within the calculation period (Y in S54), the load handling unit 40 determines whether the number of CPUs is within the upper limit (S58). If the number of CPUs is within the preset upper limit (Y in S58), this process ends. The upper limit indicates the number of CPUs that can be used.

[0049] If the number of CPUs is not within the upper limit (N in S58), the load handling unit 40 sets the number of CPUs to the upper limit (S60) and simplifies the simulation process (S62). This allows the simulation process to be executed without delay even if the processing load increases due to the calculation cycle and subdivision of the partitioned areas.

[0050] It should be understood by those skilled in the art that the embodiments are merely illustrative and that various modifications are possible in the combination of the components, and that such modifications are also within the scope of the present invention. [Explanation of symbols]

[0051] 1 Power network, 10 Town-wide network, 12 Backbone network, 14 Sectional network, 16 Battery device, 18 Charging device, 20 Consumer, 22 Power system, 24 Unstable location, 30 Energy state prediction device, 32 Acquisition unit, 34 Simulation processing unit, 36 Extraction unit, 38 Setting unit, 40 Load response unit, 42 Control unit.

Claims

1. A prediction method for predicting supply and demand in a power system and predicting locations where the power system will become unstable, comprising: a first step of executing a simulation process for predicting the amount of power supply and the amount of power demand for each preset first divided area in a predetermined first calculation period; A second step of extracting voltage unstable points in the power system derived based on the predicted power supply amount and power demand amount; a third step of resetting a second calculation period obtained by subdividing the first calculation period or a plurality of second divisional regions obtained by subdividing the first divisional region for the first divisional region corresponding to the unstable portion; a fourth step of executing a simulation process in the second calculation period or the second partitioned region reset for the first partitioned region corresponding to the unstable portion; a fifth step of extracting unstable points in the power system from the power supply amount and power demand amount predicted in the fourth step; a sixth step of setting a plurality of second segmented regions by subdividing the first segmented region corresponding to the unstable portion; a seventh step of executing a simulation process for each of the second calculation cycles set for the first divided regions corresponding to the unstable locations and for each of the second divided regions; an eighth step of extracting unstable points in the power system from the power supply and power demand predicted in the seventh step.

2. In the third step, a second calculation period obtained by subdividing the first calculation period is set for a first divided region corresponding to an unstable portion; 2. The prediction method according to claim 1, wherein in the fourth step, a simulation process is executed at a second calculation period set for a first divided region corresponding to an unstable portion.

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