Power outage resilience evaluation device, power outage resilience evaluation method, and program

Abstract

To provide a power outage resilience evaluation device, a power outage resilience evaluation method, and a program capable of quickly implementing accurate power outage resilience evaluation.SOLUTION: A power outage resilience evaluation device of an embodiment includes: a condition setting unit which sets a power outage resilience evaluation condition of a power system; a risk evaluation unit which calculates a function loss probability of the power system for each scenario; a demand-supply balance evaluation unit which calculates an amount of supply trouble power from the demand-supply balance of the power system for each scenario; and a power outage resilience evaluation unit which calculates an anticipation value of the amount of supply trouble power for each scenario by using the function loss probability and the amount of supply trouble power, and implements the power outage resilience evaluation on the basis of the anticipation value of the amount of supply trouble power.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] An embodiment of the present invention relates to a power outage resilience evaluation device, a power outage resilience evaluation method, and a program. [Background technology]

[0002] Generally, power system analysis is performed to analyze the entire power system, from the power plant where electricity is generated, through the transmission and distribution grid, and all the way to the consumer. This involves modeling power equipment in a simulator, and the analysis results are used to plan facilities or investigate the causes of abnormal events. This power system analysis has traditionally been used with the goal of ensuring a stable supply of high-quality electricity.

[0003] As a result of an abnormal event in the power system, power transmission or distribution becomes impossible, resulting in a power outage. Furthermore, there has been extensive research into predicting the occurrence of power outages caused by natural disasters and the recovery of power outages.

[0004] For example, there is a known technology for predicting typhoon damage based on typhoon forecasts and past damage information. There is also a known technology for modeling the target power distribution network, calculating the power distribution route and damage probability, and calculating the change in the power supply rate over time based on the expected value of customer demand or power supply. These technologies basically evaluate the impact of the presence or absence of a power distribution route on a power outage based on the probability of physical damage to each component of the power distribution network. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 5044243 [Patent Document 2] Japanese Patent Application Publication No. 2023-167169 [Non-patent literature]

[0006] [Non-Patent Document 1] Study on earthquake resilience evaluation method for power distribution networks with distributed generation, Journal of Earthquake Engineering, Japan, 2019, Vol. 19, No. 7, pp. 14-26 Summary of the Invention [Problem to be solved by the invention]

[0007] As mentioned above, there are methods known for evaluating or predicting power outage losses due to typhoons and evaluating the effectiveness of power outage countermeasures, but these power outage countermeasures are simple methods that do not take into account resource failures at consumers' facilities.

[0008] The present invention has been made to solve the above-mentioned problems, and aims to provide a power outage resilience evaluation device, a power outage resilience evaluation method, and a program that can quickly and accurately evaluate power outage resilience. [Means for solving the problem]

[0009] The power outage resilience evaluation device of the embodiment includes a condition setting unit that sets power outage resilience evaluation conditions for the power system, a risk evaluation unit that calculates the probability of functional loss of the power system for each scenario, a supply and demand balance evaluation unit that calculates the amount of supply disruption power from the supply and demand balance of the power system for each scenario, and a power outage resilience evaluation unit that calculates an expected value of the amount of supply disruption power for each scenario using the probability of functional loss and the amount of supply disruption power, and performs power outage resilience evaluation based on the expected value of the amount of supply disruption power. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a power outage resilience evaluation system according to an embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of power equipment management information according to the embodiment. [Figure 3] FIG. 3 is a diagram illustrating an example of a power transmission and distribution system according to the embodiment. [Figure 4]FIG. 4 is a diagram illustrating an example of the relationship between maximum instantaneous wind speed and failure probability according to the embodiment. [Figure 5] FIG. 5 is a diagram illustrating an example of resource management information according to the embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of consumer management information according to the embodiment. [Figure 7] FIG. 7 is a diagram illustrating an example of hazard management information according to the embodiment. [Figure 8] FIG. 8 is a diagram illustrating a first example of an event tree according to the embodiment. [Figure 9] FIG. 9 is a diagram illustrating a second example of an event tree according to the embodiment. [Figure 10] FIG. 10 is a diagram illustrating a third example of an event tree according to the embodiment. [Figure 11] FIG. 11 is a diagram illustrating an example of a fault tree according to the embodiment. [Figure 12] FIG. 12 is a diagram illustrating an example of a supply disruption power amount curve according to the embodiment. [Figure 13] FIG. 13 is a diagram illustrating an example of a power outage resilience evaluation according to the embodiment. [Figure 14] FIG. 14 is a diagram illustrating an example of a weather forecast of a typhoon according to the embodiment. [Figure 15] FIG. 15 is a diagram illustrating an example of a first setting of the condition setting unit according to the embodiment. [Figure 16] FIG. 16 is a diagram illustrating an example of a second setting of the condition setting unit according to the embodiment. [Figure 17] FIG. 17 is a diagram illustrating an example of a third setting of the condition setting unit according to the embodiment. [Figure 18] FIG. 18 is a diagram illustrating a fourth setting example of the condition setting unit according to the embodiment. [Figure 19] FIG. 19 is a diagram illustrating a first example of a display of a typhoon path and an amount of power supply disruption according to the embodiment. [Figure 20] FIG. 20 is a diagram illustrating an example of a second display of the typhoon path and the amount of power supply disruption according to the embodiment. [Figure 21]FIG. 21 is a diagram illustrating an example of a third display of the typhoon path and the amount of power supply disruption according to the embodiment. [Figure 22] FIG. 22 is a diagram illustrating an example of a display of additional countermeasure equipment according to the embodiment. [Figure 23] FIG. 23 is a diagram illustrating an example of displaying additional countermeasure equipment and updating the prediction result according to the embodiment. [Figure 24] FIG. 24 is a diagram illustrating an example of updating additional consumer information and prediction results according to the embodiment. [Figure 25] FIG. 25 is a diagram illustrating an example of updating the prediction result due to dispatch of additional measures according to the embodiment. [Figure 26] FIG. 26 is a diagram illustrating an example of a display of a typhoon path and a power outage cost according to the embodiment. [Figure 27] FIG. 27 is a diagram illustrating an example of displaying additional countermeasure equipment and updating the power outage cost prediction result according to the embodiment. [Figure 28] FIG. 28 is a flowchart illustrating an example of power outage resilience assessment according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] An example of a power outage resilience evaluation system 1 to which the power outage resilience evaluation device, power outage resilience evaluation method, and program according to this embodiment is applied will be described below with reference to the drawings.

[0012] Fig. 1 is a diagram showing an example of the configuration of a power outage resilience evaluation system 1 according to this embodiment. As shown in Fig. 1, the power outage resilience evaluation system 1 evaluates the power outage resilience performance of a power transmission and distribution system having a wide area, the power resources connected thereto, and a power system such as consumers. In this embodiment, an example is shown in which the system is used to evaluate the power outage resilience when a typhoon strikes a certain power transmission and distribution system as an example of a natural disaster.

[0013] Power outage resilience assessment involves calculating and assessing the extent to which power supply will be insufficient due to, for example, a natural disaster, etc. That is, examples include calculating the amount of power supply disruption, and then calculating the cost of a power outage from the amount of power supply disruption, or calculating the cost of additional power generation facilities to be prepared.

[0014] A power transmission and distribution system is connected to multiple power resources and power consumers. When a balance is achieved between the power supply of the power resources and the power demand of the consumers, power can be used normally without power outages. However, during disasters such as typhoons, there is a possibility that the equipment (power equipment) and power resources that make up the power transmission and distribution system may fail. In such cases, consumers will not be able to obtain the power they need, resulting in a power outage, and there is a need to evaluate the resilience performance against such power outages.

[0015] Examples of power facilities include substations, transmission towers, overhead power distribution lines (including utility poles), and underground power distribution lines.

[0016] Examples of power resources include energy generating devices and facilities, energy storing devices and facilities, and load devices and facilities.

[0017] Examples of energy generation equipment and facilities include private (emergency) generators, cogeneration systems, renewable energy generators, etc. Examples of energy storage equipment and facilities include storage batteries, heat pumps, thermal storage, etc. Examples of load equipment and facilities include air conditioners, fans, chillers, etc.

[0018] As shown in FIG. 1, the power outage resilience evaluation system 1 includes a main control unit 2, an input unit 3, an output unit 4, a storage unit 5, and a communication unit 6.

[0019] Furthermore, the power outage resilience evaluation system 1 includes a power facility database 7, a resource database 8, a consumer database 9, and a hazard database 10. These databases are stored in memory, a hard disk drive, or cloud storage capacity, and are collections of information organized so that they can be searched or accumulated.

[0020] The power outage resilience evaluation system 1 of this embodiment can have a hardware configuration using a normal computer, including, for example, a control device such as a CPU, a storage device such as a ROM (Read Only Memory) or RAM, and an external storage device such as a HDD. The system is configured as a computer in which software-based information processing is realized using hardware resources as the CPU executes various programs. Furthermore, the power outage resilience evaluation method of this embodiment is realized by having the computer execute various programs.

[0021] Each component of the power outage resilience evaluation system 1 does not necessarily have to be installed on a single computer. For example, a single power outage resilience evaluation system 1 may be realized using multiple computers connected to each other via a network. For example, the various databases 7 to 10 may each be installed on a separate computer. Also, for example, the main control unit 2 may be installed on a cloud-based computer, and the input unit 3, output unit 4, storage unit 5, and communication unit 6 may be installed on a user-side computer.

[0022] The program executed by the power outage resilience evaluation system 1 of this embodiment may be provided as an installable or executable file recorded on a computer-readable recording medium such as a USB memory, a semiconductor storage device such as an SSD (Solid State Drive), or a DVD (Digital Versatile Disk).The program may also be configured to be provided or distributed via a network such as the Internet.

[0023] Predetermined information is input to the input unit 3 in response to operations by a user of the power outage resilience evaluation system 1. For example, various types of information such as information on power facilities, resources, and consumers in the region or area where the power outage resilience evaluation is to be carried out, as well as disaster hazard information, are input to the input unit 3.

[0024] The input unit 3 includes input devices such as a mouse or a keyboard. That is, predetermined information is input to the input unit 3 in response to the operation of these input devices. When inputting information, the user assigns a unique ID to each piece of information such as the system configuration and equipment. An ID is identification information required to individually identify the corresponding information, and a unique ID is assigned in association with each piece of information. Furthermore, information indicating a change decision on the evaluation conditions is input in real time during a disaster.

[0025] The output unit 4 outputs predetermined information. For example, the output unit 4 outputs the evaluation results of the main control unit 2 and information stored in the databases 7 to 10. The power outage resilience evaluation system 1 of this embodiment includes a device for displaying images, such as a display that outputs the analysis results. In other words, the output unit 4 controls the images displayed on the display. The display may be separate from the computer main body or may be integrated with it. The output unit 4 displays the image on a display unit such as a display. The output unit 4 may be integrated with the display unit or may be separate from it.

[0026] The power outage resilience evaluation system 1 of this embodiment may also control images displayed on a display of another computer connected via a network. In this case, the output unit 4 of the other computer may control the output of the evaluation results derived by the main control unit 2.

[0027] In this embodiment, a display is used as an example of a device for displaying images, but other modes are also possible. For example, a projector may be used to display information. Furthermore, a printer that prints information on paper media may be used instead of a display. In other words, the objects controlled by the output unit 4 may include a projector or a printer.

[0028] The storage unit 5 stores various information required for performing a power outage resilience evaluation based on the information stored in the respective databases 7 to 10.

[0029] The communication unit 6 communicates with other computers via a communication line such as the Internet. In this embodiment, the power outage resilience evaluation system 1 and the other computers are connected to each other via the Internet, but other modes are also possible. For example, they may be connected to each other via a communication line such as a LAN (Local Area Network), a WAN (Wide Area Network), or a mobile communication network.

[0030] The electric power equipment database 7 stores information indicating the ID, name, location, fragility, etc. of the equipment that constitutes the power transmission and distribution system. For example, the electric power equipment database 7 stores an electric power equipment management table as shown in Fig. 2 and information indicating the configuration of the power transmission and distribution system as shown in Fig. 3.

[0031] The main control unit 2, the resource database 8, the customer database 9, and the hazard database 10 will be described later.

[0032] FIG. 2 is a diagram showing an example of power equipment management information according to an embodiment, and shows a power equipment management table as an example. Information about each piece of power equipment is registered in this power equipment management table. Various information is registered in this power equipment management table using a grid ID as a primary key. For example, a grid detail ID, a facility ID, a facility name (resource name), coordinates, elevation, and fragility are registered in association with the grid ID.

[0033] Here, the system ID is identification information that can individually identify each system. The system detail ID is identification information that can individually identify each data that records detailed information about the system. The equipment ID is identification information that can individually identify each power equipment. The equipment name is a name that indicates the type of equipment and information that can individually identify it. Examples include substations, transmission towers, and utility poles. The coordinates and elevation are the coordinates and elevation of the location where the equipment is installed. For example, the coordinates are expressed as E:○ and N:○. Furthermore, the elevation is expressed as H:○m. These coordinates and elevation are an example of specific information that can identify whether or not equipment will fail (lose function) due to a disaster. Fragility is information that indicates the relationship between the severity of a disaster and the probability of equipment failure.

[0034] FIG. 3 is a diagram showing an example of the configuration of a power transmission and distribution system according to an embodiment. As shown in FIG. 3, for example, information indicating the configuration of the power transmission and distribution system can be displayed in two or three dimensions on a display or the like. In addition, consumer information can also be displayed additionally. This allows the user to understand the relative positions or configuration of various facilities in the power transmission and distribution system. This makes it possible to evaluate power outages caused by failures. In other words, it is possible to evaluate the amount of power supply disruption calculated by calculating the amount of power supply shortage caused by a power outage due to failures of various facilities, etc.

[0035] Furthermore, as shown in Figure 3, the power outage resilience evaluation system 1 can display the configuration of the power transmission and distribution system. In addition, it has a function to display the configuration of the power transmission and distribution system overlaid on an actual map. The configuration of each power transmission and distribution system is managed by a unique ID.

[0036] Figure 3 shows, for example, that a substation is connected to a steel tower or utility pole by a power transmission line. It also shows that a steel tower is connected to a solar power generation system, a utility pole (1) is connected to a power storage facility, and a utility pole (4) is connected to a wind power generation system.

[0037] Fig. 4 is a diagram showing an example of the relationship between maximum instantaneous wind speed [m / s] and failure probability according to the embodiment. For example, the fragility shown in the power equipment management table in Fig. 2 may be shown as a graph in Fig. 4 instead of the median and uncertainty.

[0038] As shown in Figure 4, information showing the relationship between disaster intensity and failure probability is provided by taking the case of strong winds caused by a typhoon as an example, with the horizontal axis representing the disaster intensity as the maximum instantaneous wind speed. If the disaster is an earthquake, the horizontal axis of the graph in Figure 4 represents the disaster intensity, which is the maximum acceleration or maximum speed. If the disaster is a lightning strike, it represents the lightning current value. If the disaster is a flood, it represents the flood depth. For other disasters, the horizontal axis should also represent the disaster intensity, and the vertical axis should represent the failure probability.

[0039] 1, the resource database 8 stores information on power resources in a power transmission and distribution system, information indicating fragility, etc. For example, the resource database 8 stores a resource management table as shown in FIG.

[0040] 5 is a diagram showing an example of resource management information according to an embodiment, illustrating a resource management table as an example. Information about each resource is registered in this resource management table. For example, a grid detail ID, a resource ID, a resource name, a rated output, an amount of power, coordinates, altitude, and fragility are registered in association with a grid ID.

[0041] Here, the grid ID and grid detail ID are as shown in Figure 2 above. The resource ID is identification information that can individually identify each resource. The resource name is a name that indicates the type of resource. Examples include solar power generation, storage batteries, emergency power supplies, and wind power generation. The rated output indicates the power generation capacity of the resource. If this rated output varies depending on the time or weather, time series data may be used. The power amount indicates the power amount of the resource. The coordinates and elevation are the coordinates and elevation of the location where the resource is installed. These coordinates and elevation are specific information that can identify whether the resource will lose its function due to a disaster. The fragility is information that indicates the relationship between the severity of the disaster and the probability of equipment failure. Fragility may be displayed in a graph such as Figure 4, similar to the power equipment management table.

[0042] 1, information about consumers connected to the power transmission and distribution system is stored in the consumer database 9. For example, the consumer database 9 stores a consumer management table as shown in FIG.

[0043] FIG. 6 is a diagram showing an example of consumer management information according to the embodiment, illustrating a consumer management table as an example. Information about each consumer is registered in this consumer management table. For example, a detailed grid ID, a consumer ID, a consumer name, a contracted power, demand data, coordinates and elevation, fragility, and a power outage cost unit price are registered in association with a grid ID.

[0044] The grid ID and grid detail ID are as shown in Figure 2 above. The customer ID is identification information that can individually identify each customer. The customer name is the name that indicates the type of customer. Examples include city hall, hospital, school, and building. The contracted power indicates the customer's contracted power. The demand data indicates the customer's past power demand. This data may be saved as time-series data. The coordinates and elevation are the coordinates and elevation of the customer's location. These coordinates and elevation are specific information that can identify whether the customer will lose functionality due to a disaster. Fragility is information that indicates the relationship between the severity of the disaster and the customer's failure probability. Fragility may be displayed as a graph, as in the power equipment management table, as shown in Figure 4. The power outage cost unit indicates the unit cost of damage caused to the customer when a power outage occurs. If the power outage cost unit varies depending on the time and weather, time-series data may be used.

[0045] 1, disaster information is stored in the hazard database 10. For example, the hazard database 10 stores a hazard management table as shown in FIG.

[0046] FIG. 7 is a diagram showing an example of hazard management information according to an embodiment, illustrating a disaster hazard management table as an example. This disaster hazard management table stores information about hazards of various natural disasters. This information includes hazard maps published by the national government, local governments, and other organizations. The data may be a graph with time-series information. Past disaster information may be saved and used as an evaluation criterion.

[0047] As shown in FIG. 7, for example, the type of hazard, data, and reference source are registered in association with a hazard ID. Here, the hazard ID is identification information that can individually identify each hazard. The hazard type is a name that indicates the type of hazard. Examples include earthquakes, strong winds, heavy rain, flooding, mudslides, heavy snowfall, and typhoons. The data indicates disaster intensity, such as hazard maps and graphs with time-series information.

[0048] As shown in Fig. 1, a main control unit 2 comprehensively controls the power outage resilience evaluation system 1. This main control unit 2 includes a condition setting unit 11, a risk assessment unit 12, a supply and demand balance assessment unit 13, and a power outage resilience assessment unit 14. These are realized by the CPU executing programs stored in memory or a HDD.

[0049] The condition setting unit 11 includes an evaluation target setting unit 15 and an additional condition setting unit 16. The condition setting unit 11 sets an evaluation target for which a power outage resilience evaluation is to be performed. The set evaluation target is then used as an evaluation condition for the risk assessment unit 12 and the supply and demand balance assessment unit 13.

[0050] The evaluation target setting unit 15 sets, for example, the target scope of the power outage resilience evaluation and the evaluation target such as facilities and equipment.

[0051] The additional condition setting unit 16 selects conditions such as additional countermeasure equipment for the evaluation target for which the power outage resilience evaluation is performed, and sets them as evaluation conditions. Also, the additional condition setting unit 16 sets and updates the evaluation conditions based on the information input by the input unit 3. For example, if a shortage of power supply occurs in the power outage resilience evaluation, the additional countermeasure equipment is selected as an evaluation condition.

[0052] Next, the risk assessment unit 12 includes an event tree analysis unit 17 and a fault tree analysis unit 18. The risk assessment unit 12 calculates and evaluates the probability of function loss (failure probability) of the assessment target for the disaster progression scenario of the event tree, for example. In this way, the occurrence probability of the disaster progression scenario is calculated and evaluated.

[0053] As shown in FIG. 1, the event tree analysis unit 17 evaluates the occurrence probability of a disaster progression scenario (scenario).

[0054] FIG. 8 is a diagram showing a first example of an event tree according to an embodiment. In this embodiment, a natural disaster such as a typhoon progresses, and therefore, as an example, each time can be set as a branch in the event tree. In FIG. 8, one branch is set at each time, but by setting multiple branches and failure probabilities for power facilities, power resources, consumers, etc. as necessary, it is possible to calculate the occurrence probability of each scenario resulting from the event tree. By registering a scenario ID for each scenario, it is possible to link it to the evaluation result of the supply and demand balance evaluation unit 13.

[0055] As shown in Figure 8, for example, consider a case where the disaster intensity of a natural disaster changes over time. That is, in the case of a typhoon, wind speed changes over time. Here, as an example, if the evaluation target is a power line failure, in scenario SA, the power line failure probability is set to A based on the wind speed forecast at 6:00, and the occurrence probability of a power line failure at 6:00 is calculated as A. Similarly, for other time periods after 7:00, the power line failure probability set from the wind speed forecast for each scenario and the occurrence probability for each time change are shown.

[0056] Next, Fig. 9 is a diagram showing a second example of an event tree according to an embodiment. In Fig. 8, one branch is set at each time, but in the second example, as shown in Fig. 9, multiple branches and failure probabilities are set at each time. This makes it possible to calculate the occurrence probability of each scenario resulting from the event tree.

[0057] As shown in Figure 9, for example, if the evaluation targets are transmission tower failure and PV (Photovoltaic Power Generation) failure, scenario S-AB calculates the occurrence probability of a transmission tower failure at 6:00 as A*B, based on the transmission tower failure probability A set from the wind speed at 6:00.

[0058] For scenario SA, the probability of PV failure at 6:00 is calculated as A*(1-B) from the PV failure probability B, which is set from the wind speed at 6:00. Similarly, for other time periods after 7:00, the occurrence probability for each time change is expressed from the failure probability of the evaluation target, which is set from the wind speed for each scenario.

[0059] Next, Fig. 10 is a diagram showing a third example of an event tree according to an embodiment. Fig. 9 shows multiple branches at each time and the failure probability of one evaluation object for each branch. As shown in Fig. 10, the third example shows an example in which multiple branches and failure probabilities of multiple evaluation objects are set at each time.

[0060] As shown in Figure 10, for example, if the evaluation targets are transmission tower failure and PV failure, scenario SA calculates the occurrence probability of a transmission tower failure at 6:00 as A*(1-P) based on the transmission tower failure probability A and PV failure probability P, which are set based on the wind speed at 6:00.

[0061] In addition, in scenario S-AP, the occurrence probability of a transmission tower and PV failure at 6:00 is calculated as A*P from the transmission tower failure probability A and PV failure probability P, which are set from the wind speed at 6:00. Similarly, for other time periods, the occurrence probability of failure of multiple evaluation objects over time is expressed from the failure probability set from the wind speed for each time period. Note that the natural disasters, evaluation objects, scenario branches, etc. shown in Figures 8, 9, and 10 are examples. Note that the function loss probability (failure probability) used in the risk assessment unit 12 is an example of occurrence probability, but failure probability may also be used.

[0062] As shown in FIG. 1, the fault tree analysis unit 18 creates a function loss probability (failure probability) of the evaluation target.

[0063] 11 is a diagram showing an example of a fault tree according to an embodiment. In the fault tree of this embodiment, facilities and devices that constitute resources are registered as lower-level items. These lower-level items are associated with logic gates (AND gates, OR gates) to construct a fault tree.

[0064] In addition, events that occur in relation to the occurrence of events in lower-level items are registered in the middle-level items in the fault tree, and events that occur in relation to the occurrence of events in middle-level items are registered in the upper-level items in the fault tree.

[0065] The fault tree is used to determine whether the occurrence of an event in a lower-level item will cause an event (fault mode) in a higher-level item, or to calculate the probability of the event in the higher-level item occurring.

[0066] In this embodiment, the fault tree judgment result includes the probability of resource function loss. When you want to evaluate the failure probability of a resource under a certain disaster intensity, you can calculate the probability of resource function loss by inputting the failure probability of the component facilities and equipment under each disaster intensity into the created fault tree.

[0067] For example, as shown in Figure 11, taking solar power generation as an example, the probability of functional loss of solar power generation can be calculated by the probability of functional loss of the control panel or the probability of functional loss of the solar panels at each disaster intensity. The functional loss probability shown in this fault tree is an example of the failure probability of the event tree shown in Figure 10.

[0068] The risk assessment unit 12 may also calculate the function loss probability based on a fault tree. The risk assessment unit 12 may also calculate the function loss probability based on at least the power system that supplies power.

[0069] 1, the supply and demand balance evaluation unit 13 includes a model construction unit 19 and an evaluation unit 20. The supply and demand balance evaluation unit 13 predicts the demand and supply of electricity to be evaluated based on the conditions set by the condition setting unit 11, and calculates and evaluates the balance of supply and demand of electricity in the event of a disaster.

[0070] The model construction unit 19 constructs a model required for carrying out future supply and demand prediction from the data in the resource management table and the customer management table to be evaluated.

[0071] The evaluation unit 20 inputs the necessary input data into the model constructed by the model construction unit 19 and evaluates the future supply and demand balance. For supply and demand forecasting, an appropriate method such as linear programming is selected. Factors that affect supply and demand forecasting, such as weather, may be input from the information in the hazard management table. Alternatively, they may be input from the input unit 3.

[0072] FIG. 12 is an example of a supply disruption power curve for the supply and demand balance evaluation according to the embodiment. As shown in FIG. 12, the horizontal axis represents time, for example. The horizontal axis may also represent the intensity of the disaster, for example. The vertical axis represents the amount of supply disruption power, for example. The vertical axis is not limited to the amount of supply disruption power, and various display formats are possible, such as the percentage (%) of the amount of supply disruption power in the entire evaluation target, or the number of supply disruptions among consumers.

[0073] The amount of power supply disruption on the vertical axis represents the shortage of power supply, and the closer it is to 0, the better the balance between supply and demand is maintained.

[0074] For example, the graph of power supply disruption shown in Figure 12 shows an example where a failure occurs at 6:00. Therefore, the amount of power supply disruption is shown to have risen sharply at 6:00. After the sudden rise, the amount of power supply disruption fluctuates as the power demand changes over time.

[0075] The SA written on the curve is a scenario ID, and can be associated with, for example, the evaluation result of the event tree by the event tree analysis unit 17. In addition, the supply and demand balance evaluation unit 13 calculates the amount of power supply disruption when a failure occurs at multiple time intervals.

[0076] The power outage resilience evaluation unit 14 integrates the evaluation results calculated by the risk evaluation unit 12 and the supply-demand balance evaluation unit 13 to evaluate power outage resilience. That is, it calculates the expected value of the amount of power supply disruption from the occurrence probability calculated by the risk evaluation unit 12 and the amount of power supply disruption evaluated by the loss evaluation unit. The calculation is performed using the following formula. The amount of power supply disruption is calculated as x t , the occurrence probability is p t The expected value of the amount of power supply interruption when t ,The scenario of the event tree is n. This allows us to calculate the expected amount of power supply disruption in each time period.

[0077] E t =Σ n i=1 x t(i) p t(i)

[0078] Fig. 13 is a diagram showing an example of power outage resilience evaluation according to the embodiment. In the power supply disruption power amount curve in Fig. 12, the power supply disruption amount is almost constant at each time, but Fig. 13 shows that when the failure probability at each time is taken into account, the power supply disruption amount peaks between 9:00 and 10:00.

[0079] The vertical axis is not limited to the expected value of the amount of power supply disruption, and various display formats are possible, such as the percentage of power supply disruption in the entire evaluation target, or the number of power supply disruptions among consumers.

[0080] The power outage resilience evaluation system 1 includes a condition setting unit 11 that sets the power outage resilience evaluation conditions for the power system, a risk evaluation unit 12 that calculates the probability of power system function loss or occurrence probability for each scenario, a supply and demand balance evaluation unit 13 that calculates the amount of power supply disruption from the supply and demand balance of the power system for each scenario, and a power outage resilience evaluation unit 14 that calculates the expected value of the amount of power supply disruption for each scenario using the probability of function loss or occurrence probability and the amount of power supply disruption, and performs power outage resilience evaluation based on the expected value of the amount of power supply disruption.

[0081] FIG. 14 is a diagram showing an example of a typhoon weather forecast according to the embodiment. Specifically, it is an example of typhoon weather forecast information input to the hazard management table from the input unit 3. The upper part of FIG. 14 displays the predicted path of the typhoon at each time on a map. The lower part of FIG. 14 shows the transition of the maximum instantaneous wind speed at each time for point A shown in the upper part of FIG. 14. Note that the vertical axis may use average wind speed, rainfall, probability of entering a storm zone, etc. instead of the maximum instantaneous wind speed.

[0082] FIG. 15 is a diagram showing an example of a first setting of the evaluation target setting unit 15 of the condition setting unit 11 according to the embodiment. For example, by surrounding an area on a displayed map with a rectangle, the area within the rectangle can be set as the evaluation target. That is, the condition setting unit 11 can set the target of the evaluation condition from the map. As shown in FIG. 15, a power transmission and distribution system and a predicted typhoon path are shown. The black frame indicates that the range of the evaluation target has been set.

[0083] FIG. 16 is a diagram showing an example of the second setting of the evaluation target setting unit 15 of the condition setting unit 11 according to the embodiment. For example, when an area on a map is divided into grids, by selecting a grid, the area within the grid can be set as the evaluation target. A light color indicates that the area has been selected as the evaluation target. For example, in FIG. 16, the power transmission and distribution system PAP is divided into eight squares. The central four squares are selected, indicating that they are set as the evaluation range.

[0084] 17 is a diagram showing an example of the third setting of the evaluation target setting unit 15 of the condition setting unit 11 according to the embodiment. For example, when a power transmission and distribution system is displayed on a map, by selecting the power transmission and distribution system, the connected facilities, resources, and consumers can be set as the evaluation range. The power transmission and distribution system is shown with a double line indicating that it has been selected.

[0085] 18 is a diagram illustrating an example of a fourth setting of the condition setting unit 11 according to the embodiment. For example, when a consumer connected to a power transmission / distribution system is shown on a map, by selecting the consumer, the connected power transmission / distribution system and the power resources owned by the consumer can be set as the evaluation range.

[0086] FIG. 19 is an example of a display of a power outage resilience assessment according to an embodiment. Specifically, it is a diagram showing an example of a first display of a typhoon path and the amount of power supply disruption. The upper part of FIG. 19 shows the predicted path of the typhoon on a map of the power transmission and distribution system, and the lower part of FIG. 19 shows the expected value of the amount of power supply disruption by hour. The predicted path of the typhoon and the expected value of the amount of power supply disruption are then shown in correspondence with each other. In this display, typhoon information is updated over time, so the amount of power supply disruption can also be tracked and the predicted value can be updated to the actual measured value.

[0087] For example, the system further includes a display unit that displays the results of the power outage resilience assessment in association with a weather forecast of a typhoon. The display unit is controlled by the output unit 4.

[0088] Fig. 20 is an example of a display of a power outage resilience assessment according to an embodiment. Specifically, it is a diagram showing an example of a second display of a typhoon path and the amount of power supply disruption. As in Fig. 19, the predicted path of the typhoon and the expected value of the amount of power supply disruption are shown corresponding to each other, but in Fig. 20, the horizontal axis does not correspond to the predicted path of the typhoon but is shown as a time scale.

[0089] FIG. 21 is an example of a display of a power outage resilience assessment according to an embodiment. Specifically, it is a diagram showing an example of a third display of a typhoon path and the amount of power supply disruption. The typhoon path forecast is displayed in 3D, and the amount of power supply disruption is overlaid and displayed in correspondence with the typhoon path forecast. As shown in the upper part of FIG. 21, the power supply disruption for each time period may be displayed as a percentage. Specifically, it may be displayed as X% power supply disruption at 6:00 and Y% power supply disruption at 10:00.

[0090] Fig. 22 is a diagram showing an example in which a display of additional countermeasure equipment is added to the display of a power outage resilience assessment according to the embodiment. As shown in the upper part of Fig. 22, operable power resources that can be used as additional countermeasure equipment are displayed on a map of the power transmission and distribution system. The lower part of Fig. 22 shows the amount of power supply disruption.

[0091] FIG. 23 is a diagram showing an example of displaying additional countermeasure equipment and updating prediction results according to an embodiment. Specifically, it is a display example of an additional prediction in which operation of the additional countermeasure equipment in FIG. 22 is added to the evaluation conditions. The lower part of FIG. 23 shows a predicted value for the case in which the power resource of the additional countermeasure equipment is not operated, and also shows a prediction for the case in which the power resource is operated as an additional predicted value. Operating the power resource reduces the amount of power supply disruption. FIG. 23 shows an example in which a prediction of the amount of power supply disruption and an additional prediction in which the power resource of the additional countermeasure equipment is operated are displayed simultaneously.

[0092] For example, when the condition setting unit 11 changes the set power outage resilience evaluation conditions, the power outage resilience evaluation unit 14 may calculate the expected value of the amount of power supply disruption based on the changed evaluation conditions.

[0093] 24 is a diagram illustrating an example of updating of additional consumer information and prediction results according to the embodiment. Specifically, this is a display example in which consumer information is additionally input to the display of the power outage resilience assessment, and the power outage resilience assessment is updated.

[0094] While electric power companies can determine whether their customers are receiving commercial power, they do not necessarily have sufficient information on the amount of time their own power resources can supply power during a power outage. In the event of a disaster, it is necessary to accurately determine the availability of power resources, particularly for important facilities such as evacuation shelters, and to respond based on priority throughout the entire area.

[0095] The display example shown in Fig. 24 shows a case where additional information has been input stating that the power resources held by the consumer (evacuation shelter) can only operate until 8:00. As shown in the lower part of Fig. 24, the forecast shows the amount of power supply disruption that would occur if the power resources were operating until 8:00. After 8:00, the power resources cannot operate, so an additional forecast is displayed showing an increased amount of power supply disruption.

[0096] Furthermore, a power supply vehicle is shown in a remote location in the lower right corner of the upper part of Fig. 24. The power supply vehicle is shown to be in a state where it can supply power. Even when privately owned power resources are operating, commercial power sources may be included in the amount of power supply disruption, but the purpose of this embodiment is to utilize privately owned power resources to calculate and evaluate the amount of power supply disruption during a substantial power outage.

[0097] FIG. 25 is a diagram showing an example of updating the prediction results by dispatching additional measures according to the embodiment. Specifically, this is a display example in which additional measures are dispatched to a consumer in the display of the power outage resilience assessment, and the prediction results are updated. This shows a case in which the power supply vehicle shown in FIG. 24 is moved, connected to the consumer, and power is supplied. The power outage resilience assessment results are updated, and an additional prediction (after power outage measures) is displayed.

[0098] FIG. 26 is a diagram showing an example of a display of typhoon path and power outage costs according to an embodiment. Specifically, the lower part of FIG. 26 shows an example in which the vertical axis of the power outage resilience evaluation results is the power outage cost calculated from the amount of power supply disruption. The power outage cost (amount of damage) is calculated by multiplying the amount of power supply disruption by the power outage cost unit price of the consumer. The power outage cost is shown as a cumulative display for the evaluation period.

[0099] Fig. 27 is a diagram showing an example of displaying additional countermeasure equipment and updating the power outage cost prediction results according to the embodiment. In the display example shown in Fig. 27, the power outage cost is updated as an additional prediction when the condition is set to operate additional power resources of the consumer. It can be seen that the additional power resources reduce the amount of power supply disruption, and therefore the predicted damage amount is reduced.

[0100] The power outage resilience value can be evaluated by adding conditions such as the cost of additional power resource countermeasures, the effectiveness of the countermeasures, and the amount of damage to consumers to the amount of power supply disruption and power outage costs evaluated as described above. The amount of damage can be evaluated based on the unit power outage cost set for each consumer. The cost of countermeasures is evaluated by the cost related to the power supply using other additional power resources. The effectiveness of the countermeasures can be obtained by evaluating how much the amount of power supply disruption changes due to the additional power resources.

[0101] Next, Fig. 28 is a flowchart showing an example of power outage resilience assessment according to the embodiment. The power outage resilience assessment system 1 and the power outage resilience assessment method according to the embodiment will be described using a flowchart. The above-mentioned drawings will be referenced as appropriate. The following steps are at least some of the steps included in the power outage resilience assessment method, and other steps may also be included in the power outage resilience assessment method.

[0102] First, in step S1, the evaluation target setting unit 15 of the condition setting unit 11 determines an evaluation target for the power outage resilience evaluation. The user selects the evaluation target from a map or the like by inputting an input operation. Based on this selection, the condition setting unit 11 determines the evaluation conditions (step S1).

[0103] In the next step S2, the event tree analysis unit 17 of the risk assessment unit 12 creates an event tree under the conditions set by the condition setting unit 11 (step S2).

[0104] In the next step S3, the fault tree analysis unit 18 of the risk assessment unit 12 creates a fault tree based on the branching conditions set by the event tree analysis unit 17. The risk assessment unit 12 calculates the failure probability based on the fault tree. The risk assessment unit 12 also calculates the function loss probability based on at least the power system that supplies power (step S3).

[0105] In the next step S4, the probability of occurrence of each scenario resulting from the event tree is calculated by inputting the failure probability of the fault tree created by the fault tree analysis unit 18 into the event tree created by the event tree analysis unit 17 of the risk assessment unit 12 (step S4).

[0106] In the next step S5, the model construction unit 19 of the supply and demand balance evaluation unit 13 constructs a model necessary for carrying out future supply and demand predictions from the data in the resource management table and consumer management table of the evaluation target. Then, the evaluation unit 20 performs a supply and demand balance evaluation based on the evaluation conditions set by the condition setting unit 11. Specifically, for example, the amount of power supply disruption for each scenario is calculated and a supply and demand balance evaluation is performed. Also, for example, the condition setting unit 11 sets the power outage resilience evaluation conditions using a map (step S5).

[0107] In the next step S6, the power outage resilience evaluation unit 14 uses the probability of loss of function of the power system for each scenario calculated by the risk evaluation unit 12 and the amount of power supply disruption of the power system for each scenario calculated by the supply and demand balance evaluation unit 13 to calculate an expected value curve of the amount of power supply disruption for each scenario or for each hour, and performs a power outage resilience evaluation (step S6).

[0108] In the next step S7, the amount of power supply disruption calculated in step S6 is converted into the amount of damage caused by the power outage (power outage cost), for example, from the power outage cost unit price of the amount of power supply disruption per hour. Step S7 may be omitted if necessary (step S7).

[0109] In the next step S8, it is selected whether or not to change the conditions of the evaluation target (step S8). If the conditions are to be changed (step S8: No), the process returns to step S1 where the evaluation conditions are selected via the NO branch. For example, in a case where the conditions are changed, if the calculated expected value of the amount of power supply disruption is higher than a predetermined threshold, the conditions of the evaluation target are changed in order to operate additional equipment or the like and lower the expected value of the amount of power supply disruption. In other words, if the condition setting unit 11 changes the set power outage resilience evaluation conditions, the power outage resilience evaluation unit 14 calculates the amount of power supply disruption based on the changed power outage resilience evaluation conditions.

[0110] If the conditions are not changed (step S8: Yes), the result is YES and the process proceeds to step S9. For example, an example of a case where the conditions are not changed is when the calculated expected amount of power supply disruption is lower than a predetermined threshold.

[0111] In the next step S9, the output unit 4 outputs the power outage resilience assessment results to the display unit. Then, the power outage resilience assessment method is terminated. If the conditions are changed in step S8, the predictions before and after the changes are displayed (step S9). For example, the results of the power outage resilience assessment are displayed in association with the weather forecast for typhoons.

[0112] In the flowcharts of the above-described embodiments, steps are illustrated as being executed serially, but the order of steps is not necessarily fixed, and some steps may be executed in reverse order. Also, some steps may be executed in parallel with other steps.

[0113] As described above, the power outage resilience evaluation device according to the embodiment includes a condition setting unit that sets power outage resilience evaluation conditions for the power system, a risk assessment unit that calculates the probability of functional loss of the power system for each scenario, a supply-demand balance assessment unit that calculates the amount of power supply disruption from the supply-demand balance of the power system for each scenario, and a power outage resilience assessment unit that calculates an expected value of the amount of power supply disruption for each scenario using the probability of functional loss and the amount of power supply disruption and performs power outage resilience evaluation based on the expected value of the amount of power supply disruption. Therefore, when an event affecting power supply occurs, the expected value of the amount of power supply disruption can be calculated and power outage resilience can be evaluated. This makes it possible to predict the amount of additional power required from the calculated amount of power supply disruption, allowing for consideration of additional equipment, etc. Furthermore, the amount of damage caused by a power outage can be estimated from the amount of power supply disruption. Furthermore, long-term and short-term power outage resilience evaluations can be performed.

[0114] In addition, in the power outage resilience evaluation device, the risk assessment unit calculates the function loss probability based on the fault tree. Therefore, by using the fault tree, the function loss probability can be calculated with high accuracy.

[0115] In addition, in the power outage resilience evaluation device, the risk assessment unit calculates the loss of function probability based on at least the power system that supplies power. Therefore, since it is possible to calculate at least the supply amount of the power system that supplies power, it is possible to accurately calculate the loss of function probability.

[0116] In addition, in the power outage resilience evaluation device, when the condition setting unit changes the power outage resilience evaluation conditions set by the condition setting unit, the power outage resilience evaluation unit calculates the expected value of the amount of power supply disruption based on the changed evaluation conditions. Therefore, it is possible to compare the amount of power supply disruption before and after the change and to clearly display the effect of changing the evaluation conditions.

[0117] In addition, in the power outage resilience evaluation device, the condition setting unit uses a map to set the power outage resilience evaluation conditions. This allows the user to easily set the conditions. For example, the target range of the evaluation conditions can be easily set by selecting a range from the map or by selecting a connection part.

[0118] The power outage resilience assessment device further includes a display unit that displays the results of the power outage resilience assessment in association with the typhoon weather forecast. Therefore, the results of the power outage resilience assessment and the typhoon weather forecast can be viewed, making it easier for users to take measures based on the power outage resilience assessment.

[0119] In addition, the power outage resilience evaluation method according to this embodiment is a power outage resilience evaluation method that performs power outage resilience evaluation in a power outage resilience evaluation device, and includes a condition setting step of setting power outage resilience evaluation conditions for a power system, a risk assessment step of calculating the probability of functional loss of the power system for each scenario, a supply and demand balance evaluation step of calculating the amount of supply disruption power from the supply and demand balance of the power system for each scenario, and a power outage resilience evaluation step of calculating an expected value of the amount of supply disruption power for each scenario using the functional loss probability and the amount of supply disruption power, and performing a power outage resilience evaluation using the expected value of the amount of supply disruption power.

[0120] In addition, the power outage resilience evaluation program of this embodiment causes a computer to execute a risk assessment means for calculating the probability of functional loss of the power system for each scenario, a supply and demand balance assessment means for calculating the amount of power supply disruption from the supply and demand balance of the power system for each scenario, and a power outage resilience assessment means for calculating the expected value of the amount of power supply disruption for each scenario using the probability of functional loss and the amount of power supply disruption, and for evaluating power outage resilience based on the expected value of the amount of power supply disruption.

[0121] The system of the above-described embodiment includes a control device with a highly integrated processor such as a dedicated chip, FPGA (Field Programmable Gate Array), GPU (Graphics Processing Unit), or CPU (Central Processing Unit), a storage device such as ROM (Read Only Memory) or RAM (Random Access Memory), an external storage device such as HDD (Hard Disk Drive) or SSD (Solid State Drive), a display device such as a monitor, an input device such as a mouse or keyboard, and a communication interface. This system can be realized with a hardware configuration using a normal computer.

[0122] The programs executed by the systems of the above-described embodiments are provided in advance in a ROM, etc. Alternatively, the programs may be provided in the form of installable or executable files stored on a computer-readable, non-transitory storage medium such as a CD-ROM, CD-R, memory card, DVD, or flexible disk (FD).

[0123] The programs executed by this system may be stored on a computer connected to a network such as the Internet and provided by downloading them via the network. This system may also be configured by combining separate modules that independently perform the functions of the components and interconnect them via a network or dedicated lines. [Explanation of symbols]

[0124] 1. Power outage resilience assessment system 2...Main control unit 3...Input section 4...Output section 5...Storage section 6. Communications Department 7...Electric power equipment database 8...Resource database 9...Customer database 10...Hazard database 11...Condition setting section 12. Risk Assessment Department 13...Supply and Demand Balance Evaluation Department 14...Power Outage Resilience Evaluation Section 15...Evaluation target setting section 16...Additional condition setting section 17...Event tree analysis section 18...Fault tree analysis section 19...Model Construction Department 20...Evaluation Department

Claims

1. a condition setting unit that sets conditions for evaluating the power outage resilience of the power system; a risk assessment unit that calculates a probability of loss of function of the power system for each scenario; a supply and demand balance evaluation unit that calculates an amount of power supply disruption from the supply and demand balance of the power system for each scenario; A power outage resilience evaluation unit that calculates an expected value of the supply disruption power amount for each scenario using the function loss probability and the supply disruption power amount, and performs power outage resilience evaluation using the expected value of the supply disruption power amount; A power outage resilience evaluation device comprising:

2. the risk assessment unit calculates the loss of function probability based on a fault tree. The power outage resilience evaluation device according to claim 1 .

3. the risk assessment unit calculates the loss of function probability based on at least the power system that supplies power; The power outage resilience evaluation device according to claim 1 .

4. When the condition setting unit changes the set power outage resilience evaluation condition, The power outage resilience evaluation unit calculates an expected value of the amount of power supply disruption based on the changed power outage resilience evaluation conditions, The power outage resilience evaluation device according to claim 1 .

5. The condition setting unit sets the power outage resilience evaluation conditions using a map. The power outage resilience evaluation device according to any one of claims 1 to 4.

6. Further provided is a display unit that displays the results of the power outage resilience assessment and a typhoon weather forecast in association with each other. The power outage resilience evaluation device according to any one of claims 1 to 4.

7. A power outage resilience evaluation method for performing a power outage resilience evaluation, a condition setting step of setting conditions for evaluating the power outage resilience of the power system; a risk assessment step of calculating a probability of loss of function of the power system for each scenario; a supply and demand balance evaluation step of calculating an amount of power supply disruption from the supply and demand balance of the power system for each scenario; A power outage resilience evaluation step in which an expected value of the supply disruption power amount is calculated for each scenario using the function loss probability and the supply disruption power amount, and a power outage resilience evaluation is performed using the expected value of the supply disruption power amount; Power outage resilience assessment methods, including:

8. On the computer, a risk assessment means for calculating the probability of the power system losing function for each scenario; a supply and demand balance evaluation means for calculating the amount of power supply disruption from the supply and demand balance of the power system for each scenario; A power outage resilience evaluation means for calculating an expected value of the supply disruption power amount for each scenario using the function loss probability and the supply disruption power amount, and performing a power outage resilience evaluation using the expected value of the supply disruption power amount; A program that executes the following.

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