JP2024157412A - Power outage risk assessment system, power outage risk assessment method, and program - Google Patents

Abstract

To provide a technique of evaluating the risk of a blackout which can contribute to considering rational measures to reduce the risk of a blackout.SOLUTION: A blackout risk evaluation system according to an embodiment of the present invention includes: a blackout probability evaluation unit for forming a model of a power system by a graph or a list and evaluating the probability of a blackout of the power system; and a demand balance evaluation unit for evaluating the power supply rate of the power system on the basis of the probability of a blackout.SELECTED DRAWING: Figure 1

Description

Embodiments of the present invention relate to a power outage risk assessment system, a power outage risk assessment method, and a program.

Power system analysis is generally performed to analyze phenomena that occur in a series of power systems from upstream to downstream, from the power plant where electricity is generated, through the transmission system and distribution network, to the consumer. This power system analysis has traditionally been used with the aim of providing a stable supply of high-quality electricity. Here, as a result of an abnormal event in the power system, power transmission or distribution becomes impossible, resulting in a power outage. There are multiple factors that cause power outages, but the impact of natural disasters has been widely studied as it relates to predicting the occurrence of power outages and restoring power after a power outage.

For example, there is a known technique for predicting typhoon damage based on typhoon forecasts and past damage information. There is also a known technique for predicting the number of households that will lose power based on equipment resilience and weather forecast data. There is also a known technique for calculating the average power outage duration for consumers, the amount of power outage damage, and the cost-effectiveness of countermeasures based on data on past natural disasters and the number of power outages. There is also a known technique for modeling the target power distribution network into nodes and links, calculating the power distribution route and damage probability, and using an event tree to calculate the expected value of consumer demand or power supply, and calculating changes in the power supply rate over time. These techniques basically evaluate the impact on power outages based on the presence or absence of a power distribution route, based on the probability of physical damage to each component of the power distribution network.

Patent No. 5044243 Patent No. 5931830 Patent No. 5088628

Toshiaki Matsumoto et al., Study on earthquake resilience evaluation method for power distribution grids with distributed power sources, Journal of the Japan Association for Earthquake Engineering, Vol. 19, No. 7, 2019

Power outages are caused by natural disasters such as earthquakes, typhoons, lightning strikes, and floods, or by other factors. If the risk of power outages due to various disasters could be quantitatively understood in advance, electricity consumers could take rational and effective measures based on that information. For example, as a measure to reduce the risk of power outages, power outages can be avoided by installing storage batteries, fuel cells, private power generation equipment, etc., and supplying power from these facilities when the supply from the power distribution network is cut off. In addition, there are power distribution automation systems that monitor the power distribution network or control system switching using various devices via a communication network, with the aim of maintaining and improving the power quality or supply reliability of the power distribution network.

Figure 17 shows a schematic diagram of a conventional power distribution automation system. This schematic diagram shows the flow of recovery by the power distribution automation system when an accident occurs in the power distribution network. For example, a power distribution line extending from a substation is divided into multiple sections (1) to (6) by automatic switches. Under normal circumstances, power is transmitted through this power distribution line. Now, assume that an accident that affects the power distribution line occurs in a specific section (3). When an accident occurs, the automatic switch relay operates and the automatic switch is opened. Furthermore, the substation stops transmitting power. When the circuit is reclosed, power transmission from the substation is resumed, and each automatic switch is closed in sequence, transmitting power to the accident point. At this time, the specific section (3) is identified as the accident section. The automatic switch on the power supply side of this accident section (3) is locked. Power is transmitted to sections (1) to (2) on the power supply side of the accident section (3). However, power is not transmitted to the accident section (3) because the automatic switch is locked. In this case, sections (4) to (6) on the load side of the fault section (3) experience a power outage, even though no fault has occurred. These sections (4) to (6) are called healthy power outage sections. When a power outage occurs, the distribution automation system aims to minimize the scale of the outage by detecting the accident, identifying the fault section, and transmitting power backwards. Here, reverse transmission means supplying power from a different route to healthy power outage sections (4) to (6) on the load side of the fault section (3). This reverse transmission can reduce the number of power outages.

Figure 18 shows a schematic diagram of a power outage automation system and power interchange. Unlike Figure 17, this schematic diagram is an example of a distribution line without redundancy. In other words, reverse transmission is not possible. In this case, consumers connected to the fault section (3) will not be supplied with power and will therefore experience a power outage. However, if each consumer has its own distributed power source, power will be supplied from the distributed power source, reducing losses due to the power outage. On the other hand, sections (4) to (6) on the load side of the fault section (3) are healthy power outage sections. Consumers connected to these sections will also experience a power outage as they will not be supplied with power. However, because the distribution line is healthy, it is possible to share the resources of the distributed power sources held within the section and use them according to priority.

In this way, when damage or a failure occurs at a specific point in the power distribution network and the power supply route is cut off, the point of the accident is identified, power is transmitted from an alternative route, and measures are taken to minimize the blackout section. In order to take measures against blackouts in advance, it is necessary to evaluate the return on investment of the measures, such as whether the measures are effective for the investment. Because there are various disasters that can cause blackouts and the scale and form of blackouts, it is necessary to consider the components of the power system and their respective relationships and roles, quantitatively evaluate the blackout risk, and then evaluate the risk reduction of the measures to be introduced.

In the case of damage to the distribution network in a specific section, the distribution automation system identifies that section and performs operations to transmit power from a detour route. However, even if a route for transmitting power is secured, the functions of the equipment required for this series of operations may be lost due to a disaster. Conventional technology does not consider the impact of power outage damage according to the role of each device in the distribution network in the system. In addition, it is difficult to grasp what functions of the distribution network should be strengthened to efficiently reduce the risk of power outages. In addition, the reduction of power outage damage by distributed power sources installed by consumers as a power outage countermeasure is not considered, or even if it is considered, it is evaluated based on the simple assumption that it will function without exception in the event of a disaster, and the risk of loss of function of the power outage countermeasure itself is not considered. For example, even in a healthy power outage section, if the configuration does not allow reverse transmission by the distribution automation system, there is a possibility that the consumer can exchange power to other consumers using his/her own distributed power source, but this is not subject to evaluation. Furthermore, when calculating risk using an event tree, it is necessary to express the health and failure of the power system as branches. Therefore, when the scale of a power system is large or when the granularity is fine, the number of possible scenario patterns (such as combinations of equipment failures) increases. As a result, the analysis load increases, and there may be limits to the modeling that can be evaluated. As such, conventional technology cannot contribute to the consideration of rational measures to reduce the risk of power outages.

The purpose of an embodiment of the present invention is to provide a power outage risk assessment technology that can contribute to the consideration of rational measures to reduce the risk of power outages.

The power outage risk assessment system according to one embodiment includes a power outage probability assessment unit that models a power system using a graph or list and assesses the probability of a power outage in the power system, and a supply and demand balance assessment unit that assesses the power supply rate of the power system based on the power outage probability.

This embodiment makes it possible to provide a power outage risk assessment technology that can help consider rational measures to reduce the risk of power outages.

1 is a block diagram showing a configuration of a power outage risk assessment system according to one embodiment. FIG. FIG. 2 is a block diagram showing a configuration of a main control unit. FIG. 2 is a diagram illustrating an example of a configuration of a power system stored in a power system configuration database. FIG. 2 is a diagram illustrating an example of a system configuration management table. FIG. 2 is a diagram illustrating an example of a demander configuration management table. FIG. 11 is a diagram illustrating an example of a first device management table. FIG. 11 illustrates an example of a second device management table. 1 is a graph showing an example of the relationship between the intensity of a disaster and the probability of damage to equipment. FIG. 13 illustrates an example of a hazard management table. 1 is a graph showing an example of the relationship between disaster intensity and annual exceedance frequency. FIG. 2 is a diagram showing an example of a hazard map stored in a disaster hazard database. FIG. 1 is a diagram illustrating an example of a power distribution line and a consumer; FIG. 13 is a diagram showing an example of a power outage risk curve presentation. FIG. 13 is a diagram showing an example of a presentation of an additional countermeasure menu. FIG. 1 is a diagram showing an example of a change in electricity demand. 1 is a flowchart illustrating an example of a method for assessing a risk of a power outage. FIG. 1 is a diagram showing a flow of restoration in a conventional power distribution automation system. FIG. 1 is a diagram showing an automated power distribution system and aspects of power interchange.

The following describes an embodiment of the present invention with reference to the drawings. The following embodiment does not limit the present invention.

Figure 1 is a block diagram showing the configuration of a power outage risk assessment system according to one embodiment. This power outage risk assessment system 1 assesses the power outage risk of a power system. In this embodiment, an example of a mode used to calculate the power outage risk of a power system is shown.

The power system that is the subject of evaluation by power outage risk assessment system 1 is a system that includes the generation of electricity (power generation), the transportation of electricity (transmission and transformation), the supply of electricity (distribution), and the demand for electricity (consumption). This power system is very large-scale, including everything from power generation to consumption, and is a highly controlled system that keeps the overall voltage and frequency within certain ranges. The equipment that makes up this power system includes equipment installed by the power company and equipment installed by consumers.

In a power system, electricity generated at power plants is supplied to consumers (homes, factories, businesses, etc.) via a power transmission network and a power distribution network. This series of power supply routes from upstream to downstream differs depending on the region. Power outage risk assessment system 1 quantifies the power outage risk in a region to accurately grasp that risk. This allows for more effective and necessary capital investments to be made.

The components of the power system according to this embodiment include substations, distribution lines (transmission lines), distribution poles, switches, and other pole-mounted equipment. In addition, they also include power-receiving equipment of consumers who use the power system, and equipment (distributed power sources) that may be introduced as a countermeasure against power outages. Specific examples include storage batteries, solar power generation systems, fuel cells, emergency diesel generators, gas engines, and electric vehicles.

As shown in FIG. 1, the power outage risk assessment system 1 according to this embodiment includes a main control unit 2, an input unit 3, an output unit 4, a storage unit 5, and a communication unit 6. Furthermore, this power outage risk assessment system 1 includes a system configuration database 7, an equipment database 8, and a disaster hazard database 9. These databases are stored in memory, a HDD, or cloud storage capacity, and are collections of information organized so that they can be searched or accumulated.

The power outage risk assessment system 1 of this embodiment is configured as a computer having hardware resources such as a CPU, ROM, RAM, and HDD, and in which software-based information processing is realized using the hardware resources as the CPU executes various programs. Furthermore, the power outage risk assessment method of this embodiment is realized by having the computer execute various programs.

Each component of the power outage risk assessment system 1 does not necessarily have to be provided on a single computer. For example, a single power outage risk assessment system 1 may be realized using multiple computers connected to each other via a network. For example, the various databases 7 to 9 may each be installed on a separate computer.

Prescribed information is input to the input unit 3 in response to operations by a user using the power outage risk assessment system 1. For example, various information such as the system configuration of the region or area where the power outage risk assessment is to be carried out, equipment fragility information, and disaster hazard information is input to the input unit 3.

The input unit 3 includes input devices such as a mouse or a keyboard. In other words, 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 system configuration and equipment information. 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.

The output unit 4 outputs predetermined information. For example, the output unit 4 outputs the evaluation results of the main control unit 2 and the information stored in the databases 7 to 9. The power outage risk assessment system 1 according to 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. Note that the display may be separate from the computer main body, or may be integrated with it.

The power outage risk assessment system 1 according to this embodiment may 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 assessment results derived by the main control unit 2.

In addition, in this embodiment, a display is exemplified as a device that displays images, but other configurations are also possible. For example, information may be displayed using a projector. 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.

The memory unit 5 stores various information required to evaluate the risk of power outages based on the information stored in each of the databases 7 to 9.

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

The system configuration database 7 stores information indicating the configuration or connection status of the power system. This information includes geographical information about the power system, the relative positions of various pieces of equipment, and the distances between various pieces of equipment. For example, the system configuration database 7 stores information indicating the configuration of the power system shown in FIG. 3, the system configuration management table shown in FIG. 4, and the consumer configuration management table shown in FIG. 5.

Figure 3 is an example of an image showing the configuration of a power system. Information showing the configuration of the power system can be displayed two-dimensionally on a display or the like, as in image 300 shown in Figure 3. This allows the user to understand the relative positions or configuration of various facilities in the power system. Note that image 300 shows the configuration of the equipment installed downstream of a distribution substation in the power system. However, image 300 may also show the configuration of a local system installed upstream of the distribution substation. This local system is composed of, for example, a primary substation that transforms the power supplied from a power plant, and a secondary substation that transforms the output power of the primary substation.

The output unit 4 also has the function of displaying the system configuration and overlaying it on an actual map. Each system configuration is managed by a unique system configuration ID.

Figure 4 is an example of a system configuration management table. Information on equipment related to each system configuration is registered in the system configuration management table 400 shown in Figure 4. In addition, various information is registered in the system configuration management table 400 using the system configuration ID as a primary key. For example, an equipment ID, equipment detail ID, equipment name, and coordinates/altitude are registered in association with the system configuration ID.

Here, the system configuration ID is identification information capable of individually identifying each system configuration. The equipment ID is identification information capable of individually identifying each piece of equipment. The equipment detail ID is identification information capable of individually identifying each piece of data that records detailed information about the equipment. Based on this equipment detail ID, detailed data about the equipment stored in other areas of the system configuration database 7 can be read out. The equipment name is a name indicating the type of equipment. The coordinates/altitude are the coordinates and altitude of the location where the equipment is installed. These coordinates/altitude are specific information capable of identifying whether or not the equipment will lose its function due to a disaster.

Figure 5 is an example of a consumer configuration management table. Information about consumers who receive power from each system is registered in the consumer configuration management table 500 shown in Figure 5. In addition, various information is registered in the consumer configuration management table 500 using the system configuration ID as a primary key. For example, a consumer ID, coordinates/altitude, industry, consumer name, contracted power capacity, normal power demand, emergency power demand, countermeasure equipment, and countermeasure equipment capacity are registered in association with the system configuration ID.

Here, the consumer ID is identification information that can identify each consumer individually. The coordinates and altitude are the coordinates and altitude of the consumer's location. These coordinates and altitude are specific information that can identify whether the consumer will lose functionality due to a disaster. The industry is the industry of the consumer. For example, the type of consumer is a home, a medical institution, an office building, a government office, etc. The consumer name is a name that can identify the consumer. The contracted power capacity is the power capacity that the power company has contracted with the consumer.

Normal power usage is the power that a consumer uses under normal circumstances. Emergency power demand is the power that a consumer needs during a power outage. Note that multiple patterns may be registered in the items for normal power demand and emergency power demand. Multiple patterns include, for example, summer and winter patterns, day and night patterns, weekday and holiday patterns, etc.

Countermeasure equipment is equipment for continuing the supply of power during a power outage. For example, it is an emergency diesel generator. This countermeasure equipment includes off-grid equipment that supplies power not only in emergencies but also during normal times. Off-grid refers to a state in which electricity is self-sufficient without relying on a power company. Note that information indicating the presence or absence of countermeasure equipment may be registered in the countermeasure equipment item. Countermeasure equipment capacity is the amount of power that can be supplied from the countermeasure equipment to consumers.

The equipment database 8 stores information indicating the strength information (fragility) or failure probability of the equipment that is a component of the power system. For example, the equipment database 8 stores the first equipment management table shown in FIG. 6, the second equipment management table shown in FIG. 7, and information indicating the relationship between earthquake acceleration and equipment damage probability shown in FIG. 8.

Figure 6 is an example of a first equipment management table. Information about equipment required for power supply from the power plant is registered in the first equipment management table 600 shown in Figure 6. In addition, various information is registered in the first equipment management table 600 using the equipment ID as the primary key. For example, the equipment use, equipment name, equipment strength, and design criteria are registered in association with the equipment ID.

Figure 7 is an example of a second equipment management table. Information related to countermeasure equipment is mainly registered in the second equipment management table 700 shown in Figure 7. In addition, various information is registered in the second equipment management table 700 using the equipment ID as the primary key. For example, the equipment name, facility capacity, equipment strength, and design criteria are registered in association with the equipment ID.

Here, equipment use is information indicating the use of the equipment. Equipment resistance is information indicating the durability of equipment against the intensity of the disaster. If the disaster is an earthquake, the intensity of the disaster is seismic acceleration, and the equipment resistance is information indicating the durability of equipment against seismic acceleration. If the disaster is a typhoon, the intensity of the disaster is wind speed, and the equipment resistance is information indicating the durability of equipment against wind speed. If the disaster is a lightning strike, the intensity of the disaster is lightning current value, and the equipment resistance is information indicating the durability of equipment against lightning current value. If the disaster is a flood, the intensity of the disaster is flood depth, and the equipment resistance is information indicating the durability of equipment against flood depth. Design criteria is information indicating the design standard value that equipment can withstand against the intensity of the disaster. If the disaster is an earthquake, the intensity of the disaster is seismic acceleration, and the design criteria is information indicating the design standard value that equipment can withstand against seismic acceleration. If the disaster is a typhoon, the intensity of the disaster is the wind speed, and the design standards are information indicating the design standard value that equipment can withstand against the wind speed. If the disaster is a lightning strike, the intensity of the disaster is the lightning current value, and the design standards are information indicating the design standard value that equipment can withstand against the lightning current value. If the disaster is a flood, the intensity of the disaster is the flood depth, and the design standards are information indicating the design standard value that equipment can withstand against the flood depth. These equipment resistance strength and design standards are specific information that can identify whether or not equipment will lose its function due to a disaster. Facility capacity is the amount of power that can be supplied from the equipment to consumers.

In addition, equipment resistance is information that indicates the relationship between the intensity of a disaster and the probability of equipment damage. For example, equipment resistance may be shown as in the graph in Figure 8.

Figure 8 is a graph showing an example of the relationship between disaster intensity and equipment damage probability. As shown in Figure 8, even if the design criteria for three types of equipment are the same, the equipment resistance may differ for each piece of equipment. The graph in Figure 8 illustrates the case where the disaster is an earthquake, as an example of information showing the relationship between disaster intensity and equipment damage probability. The horizontal axis of this graph shows earthquake acceleration as the intensity of the disaster. Note that this horizontal axis shows wind speed if the disaster is a typhoon, shows lightning current value if the disaster is a lightning strike, and shows flood depth if the disaster is a flood. For other disasters as well, the horizontal axis shows disaster intensity, and the vertical axis shows equipment damage probability.

The disaster hazard database 9 stores information on the hazards of various natural disasters and information on the annual exceedance frequency. This information includes hazard maps published by the national government, local governments, and other organizations.

The power outage risk assessment system 1 can also extract necessary points from the hazard map stored in the disaster hazard database 9. For example, the disaster hazard database 9 stores the hazard management table shown in FIG. 9, information showing the relationship between disaster intensity and annual exceedance frequency (disaster hazard) shown in FIG. 10, and information showing the hazard map stored in the disaster hazard database 9 shown in FIG. 11. The graph in FIG. 10 illustrates the information showing the relationship between disaster intensity and annual exceedance frequency (disaster hazard) when the disaster is an earthquake. The horizontal axis of this graph indicates earthquake acceleration as an example of disaster intensity. Note that the horizontal axis of this graph indicates wind speed when the disaster is a typhoon, lightning current value when the disaster is a lightning strike, and flood depth when the disaster is a flood. For other disasters, the horizontal axis also indicates disaster intensity, and the vertical axis indicates annual exceedance frequency.

Figure 9 is an example of a hazard management table. In the hazard management table 900 shown in Figure 9, information about various hazards is registered using a hazard ID as a primary key. For example, a hazard type, disaster hazard, and reference source are registered in association with a hazard ID.

Here, the hazard ID is identification information that can individually identify each type of hazard. The hazard type is information that indicates the type of hazard. The hazard details are detailed information about each type of hazard. The reference source is information that indicates the reference source from which the information about the hazard was obtained.

Hazard details are information that indicates the relationship between the intensity of a disaster and the annual exceedance frequency. For example, hazard details may be displayed as in the graph in Figure 10.

Figure 10 is a graph showing an example of the relationship between disaster intensity and annual exceedance frequency. As shown in Figure 10, the annual exceedance frequency may differ at each of the three points A, B, and C. The graph in Figure 10 illustrates the case where the disaster is an earthquake as an example of information showing the relationship between disaster intensity and annual exceedance frequency (disaster hazard). The horizontal axis of this graph shows earthquake acceleration as the intensity of the disaster. This horizontal axis shows wind speed if the disaster is a typhoon, lightning current value if the disaster is a lightning strike, and flood depth if the disaster is a flood. For other disasters as well, the horizontal axis shows disaster intensity and the vertical axis shows annual exceedance frequency.

The hazard details may also include a hazard details ID, which is identification information that can individually identify each piece of data that records information about the hazard details. Based on this hazard details ID, detailed hazard data stored in other areas of the disaster hazard database 9 can be read out. For example, the hazard map shown in FIG. 11 may be linked to the hazard management table 900 shown in FIG. 9.

The configuration of the main control unit 2 will now be described with reference to FIG. 2. FIG. 2 is a block diagram showing an example of the configuration of the main control unit 2. The main control unit 2 performs overall control of the power outage risk assessment system 1. As shown in FIG. 2, the main control unit 2 has a power outage risk assessment unit 10, a supply and demand balance assessment unit 11, and a risk curve assessment unit 12. Each assessment unit is realized by the CPU executing a program stored in the memory or HDD.

The power outage risk assessment unit 10 has a model creation unit 13 and a power outage probability assessment unit 14. The model creation unit 13 models the power system using graphs and lists. In this embodiment, the equipment to be evaluated includes equipment installed by consumers who receive power supply.

The power outage probability evaluation unit 14 evaluates power outage patterns that combine the health and failure of the power system, the power outage probability, losses during a power outage, and the power outage risk obtained by multiplying the power outage probability and losses, based on the graphs and lists modeled by the model creation unit 13. In this embodiment, the evaluation methods used by the power outage probability evaluation unit 14 include a method using graph theory and a method using a simulation model. Each method will be described below.

Graph theory represents power lines, consumers, etc. as directed graphs consisting of vertices and edges, and analyzes them using graph algorithms.

First, the connections and elements of the distribution line are treated as a directed graph. For example, a data structure can be created in which transmission towers and switches are represented as vertices, and distribution lines are represented as edges. At this time, the probability of failure and losses during a power outage are set on the edges. A path search algorithm is then used on the directed graph to find the probability of a power outage. At this time, if there is a connection from the transmission tower to the distribution line to which the consumer is connected, there will be no power outage and the system is healthy, and if there is no connection, there will be a power outage. Under these conditions, the power outage pattern (the combination of healthy/faulty to be evaluated), losses, and occurrence probability are calculated. Since the failure probability of the power system and consumers changes depending on the severity of the disaster, an evaluation is performed for each severity of the disaster. Below, an explanation is given using the distribution line shown in Figure 12.

Fig. 12 is a diagram showing an example of a power distribution line and consumers. Referring to Fig. 12, for example, the power system can be described by the following model formula.
graph={“C0”:{“L0”:20},“C1”:{“L1”:15},“C2”:{“L2”:10},“C3”:{“L3”:25},“L0”:{“L1”:0},“L1”:{“L2”:0},“L2”:{“L3”:0}}

In this example, four consumers C0, C1, C2, and C3 and four distribution lines L0, L1, L2, and L3 are included in the power system. Each consumer is connected to one distribution line, and each distribution line is connected to other distribution lines or consumers. First, the connection between the distribution lines and the consumers will be explained. For example, the element "C0":{"L0":20}" indicates that consumer C0 is connected to distribution line L0, and that consumer C0 is connected to distribution line L0, and in this case, a numerical value of 20 can be obtained. This numerical value may be the amount of power, or the amount of loss or damage to the consumer. Similarly, numerical values are assigned to other consumers. In this example, consumer C1 is assigned the numerical value 15, consumer C2 is assigned the numerical value 10, and consumer C3 is assigned the numerical value 25. Next, the connection between distribution lines will be explained. For example, the element "L0":{"L1":0} indicates that distribution line L0 is connected to distribution line L1, and the numerical value between these connections is obtained.

In the above example, the directed graph is set based on the configuration of the equipment installed downstream of the distribution substation in the power system. However, this directed graph may also be set based on the configuration of a local system installed upstream of the distribution substation. This local system is composed of, for example, a primary substation that transforms the power supplied from a power plant, and a secondary substation that transforms the output power of the primary substation.

The simulation model is explained below. The simulation model represents and evaluates distribution lines and consumers in lists and graphs. A graph is created that shows the relationship between distribution lines and consumers. The consumers to which each distribution line supplies are expressed in a list or similar, and the parent-child relationship of the distribution lines is described in a model formula. Next, a function is defined that determines whether power will be supplied to a consumer. Based on these conditions, the power outage pattern, loss, and occurrence probability are calculated. Since the probability of failure of the power system and consumers changes depending on the severity of the disaster, an evaluation is performed for each severity of the disaster.

In the simulation model, for example, the power system can be described by the following model formula:
Line_consumer = [[0], [1], [2], [3]]
Line_parents = [-1, 0, 1, 2]

"Line_consumers" indicates a list of consumers supplied by each distribution line. For example, "Line_consumers[0]" contains a list of consumers supplied by distribution line L0. Here, it indicates that it is connected to one consumer (consumer C0). Also, "Line_parents" indicates the parent distribution line of each distribution line. For example, "Line_parents[1]" indicates that the parent distribution line of distribution line L1 is distribution line L0. The most upstream distribution line is "Line_parents[0]", which is assigned "-1". In this example, the list is set based on the configuration of the equipment installed downstream of the distribution substation in the power system. This list may also be set based on the configuration of the local system installed upstream of the distribution substation, as in the directed graph described above.

Below, an example of the evaluation process for calculating the power outage pattern and the power outage probability is described. For the model created above, parameters are set, and a simulation is performed the set number of times. For example, if an upper limit on the number of simultaneous failures is set, a distribution line is randomly selected to determine whether it will fail when the number of simultaneous failures is equal to or less than the upper limit. Next, the power outage probability evaluation unit 14 calculates the power outage probability based on the failure probability of each distribution line and the failure probability of each consumer for each disaster severity. If the generated random number is lower than the preset failure probability, the power outage probability evaluation unit 14 determines that a failure has occurred. Depending on this pattern, the power outage probability evaluation unit 14 calculates the failure probability by multiplying the disaster occurrence frequency by the preset failure probabilities of the distribution line and consumer.

In the event of a power outage, the loss of pre-specified consumers can also be calculated. When calculating the loss, not only will the distribution line or consumer fail, but if the upstream of the distribution line is not healthy, power will not be distributed and a power outage will occur. For this reason, a function is introduced that determines whether power can be supplied to a specified consumer if the distribution line is not faulty, based on a graph and list of distribution lines and consumers. In graph theory, a breadth-first search or other method is used to determine whether power can be supplied to a consumer from the upstream of the distribution line. If there is a faulty distribution line, power cannot be supplied because it cannot pass through that distribution line. In an evaluation using a simulation model, if a given distribution line is faulty, it fails, if it is not faulty and directly connected to the consumer, it is successful, and if there is no direct connection, power can be supplied only if the parent distribution line of that distribution line is traced and not faulty.

In this way, the power outage pattern, power outage probability, losses, etc. are calculated for all simulations. Finally, the power outage risk is calculated by multiplying the power outage probability and loss for each power outage pattern, and by sorting the patterns in order of the highest power outage risk, it is possible to present power outage patterns that are important in assessing the power outage risk. This makes it possible to reduce the number of power outage patterns to be evaluated in the next supply and demand balance evaluation unit 11.

Returning to FIG. 2, the supply and demand balance evaluation unit 11 has a model creation unit 15 and a power supply rate evaluation unit 16. The model creation unit 15 creates a model for evaluating the power supply rate by solving a linear programming problem or the like between the demand of consumers and the supply from distributed power sources or the like. The created model corresponds to the power outage pattern output by the power outage probability evaluation unit 14. The power supply rate evaluation unit 16 calculates the power supply rate corresponding to the power outage pattern by analyzing the linear programming problem or the like created by the model creation unit 15. At this time, the evaluation period may be set assuming that the recovery time from a power outage varies depending on the disaster level.

The risk curve evaluation unit 12 has a loss evaluation unit 17 and a risk curve creation unit 18. The loss evaluation unit 17 integrates the power outage pattern and its probability evaluated by the power outage risk evaluation unit 10, and the power supply rate evaluated by the supply and demand balance evaluation unit 11. At this time, the power supply rate can be converted into a power supply shortage rate by subtracting it from "1". In this embodiment, the value of the power supply shortage rate may be the loss, but it may also be the amount of power [kWh] or the amount of damage [yen]. For example, when the loss evaluation unit 17 evaluates the amount of damage to a consumer, the amount of damage to the consumer due to a power outage can be calculated by multiplying the amount of power [kWh] by the amount of direct or indirect damage per kWh obtained using external data such as statistical data or willingness to pay according to the consumer's industry or business form. In addition, when the loss evaluation unit 17 evaluates the damage to a business operator, the amount of reduction in the power company's electricity fee income due to a power outage and the probability at that time can be calculated by multiplying the amount of power [kWh] by the average unit price of electricity per kWh in the evaluation target area. In addition, the loss of a consumer due to a power outage can also be calculated by multiplying the hourly cost of the business loss that the consumer will suffer due to a power outage by the expected hourly cost. The risk curve creation unit 18 adds up the probabilities in descending order of loss using the power outage pattern and the losses evaluated by the loss evaluation unit 17. This makes it possible to calculate the annual exceedance probability. Plotting this on a graph creates a risk curve. The expected value of loss per year can be found by calculating the area of the risk evaluation.

Figure 13 is an example of a power outage risk curve. This power outage risk curve shows the situation before and after the installation of power outage countermeasures for a certain evaluation target. As shown in Figure 13, it can be seen that the curve before the countermeasures is depicted to be higher than the curve after the countermeasures are installed. In other words, it is evaluated that the countermeasures equipment can reduce losses due to power outages, as shown in this curve.

In addition, before calculating the estimated damage amount before and after the installation of countermeasures equipment, various information must be collected and analyzed, and the probability of a power outage must be calculated. However, it is also possible to start the evaluation from the time a power outage occurs and confirm the estimated damage amount and the return on investment of countermeasures equipment.

For example, the power outage duration can be assumed in multiple forms, such as 1 hour, 5 hours, 24 hours, etc. In this case, the estimated loss and damage amount can be calculated as the minimum necessary evaluation of the failure probability of the countermeasure equipment, etc. Also, by presenting a menu of additional countermeasures to the consumer and allowing them to select one, it is possible to add it to the existing evaluation process and calculate the loss.

Figure 14 is an example of an additional countermeasure menu presentation. The customer ID, countermeasure equipment, countermeasure equipment capacity, additional countermeasure menu, etc. are presented. Here, the additional countermeasure menu shows emergency diesel generators, hydrogen power generation, solar power generation, and storage batteries. This additional countermeasure menu automatically extracts equipment that will become countermeasure equipment from the information on the equipment stored in the equipment database 8. An evaluation model is created based on the equipment strength information linked to the equipment ID, and finally a power outage risk curve is created.

In addition, when considering an actual disaster, it is possible that electricity demand will differ from normal. For example, when a factory is affected by a disaster, operations will be halted. As a result, the factory's electricity demand will drop significantly. An evaluation based on such changes in electricity demand during a disaster is also required.

Figure 15 is an example of the recovery of power demand during a disaster. The solid line shows a sudden drop in power demand and its recovery over time. By varying the power demand value using the emergency power demand value stored in the system configuration database 7 or an arbitrary disaster impact, the effectiveness of countermeasure equipment at a specified time can also be evaluated.

Next, the power outage risk assessment method of this embodiment will be explained using the flowchart in Figure 16.

Figure 16 is a flowchart showing an example of a power outage risk assessment method. Note that the steps shown in Figure 16 are at least a portion of the steps included in the power outage risk assessment method, and other steps may be included in the power outage risk assessment method.

First, in step S1, the power outage risk assessment unit 10 determines the assessment range for the power outage risk assessment. In step S1, the user specifies the assessment range by inputting data into the input unit 3. Based on this specification, the power outage probability assessment unit 14 determines the assessment range.

In the next step S2, the model creation unit 13 describes and models the power system using graphs and lists based on the evaluation range specified by the power outage probability evaluation unit 14. There are several possible methods for this modeling, and a method can be selected according to the respective purpose.

In the next step S3, the power outage probability assessment unit 14 sets input data to the power system model created by the model creation unit 13. The input data includes, for example, the probability of disaster occurrence, the probability of failure of distribution lines and consumers, and consumer losses.

In the next step S4, the power outage probability evaluation unit 14 evaluates the power outage patterns and their probabilities for the power system. At this time, the power outage probability evaluation unit 14 can also derive a loss that is set in advance for each power outage pattern. Furthermore, the power outage probability evaluation unit 14 can calculate the power outage risk by multiplying the power outage loss by the power outage probability, and can also sort the calculated power outage risks in descending order. This makes it possible to extract important power outage patterns, thereby reducing the number of power outage patterns to be evaluated in the next step S5. As a result, the evaluation can be performed efficiently. However, if the loss value is changed later, it is necessary to perform the evaluation again.

In the next step S5, the supply and demand balance evaluation unit 11 evaluates the power demand of consumers based on the power outage pattern, the operation of power outage countermeasure equipment such as distributed power sources, and, if power interchange is possible, the power supply according to priority. In step S5, the model creation unit 15 creates an optimization model based on a linear programming problem. Next, the power supply rate evaluation unit 16 evaluates the optimization model created by the model creation unit 15.

In the next step S6, the loss assessment unit 17 of the risk curve assessment unit 12 converts the power supply rate of the power outage pattern assessed by the power supply rate assessment unit 16 into a loss and calculates it. Here, the loss may be damage or a damage amount.

In the next step S7, the risk curve creation unit 18 creates a risk curve using the probability of the power outage pattern and the loss calculated by the loss assessment unit 17.

In the next step S8, the output unit 4 outputs the evaluation result. This completes the power outage risk evaluation method.

The above-described flowchart of this embodiment illustrates an example in which each step is executed serially. However, in this embodiment, the order of steps is not necessarily fixed, and the order of some steps may be interchanged. Also, some steps may be executed in parallel with other steps.

The power outage risk assessment system 1 according to this embodiment also includes a control device with a highly integrated processor such as a dedicated chip, a Field Programmable Gate Array (FPGA), a Graphics Processing Unit (GPU), or a Central Processing Unit (CPU), a storage device such as a Read Only Memory (ROM) or a Random Access Memory (RAM), an external storage device such as a Hard Disk Drive (HDD) or a Solid State Drive (SSD), a display device such as a display, an input device such as a mouse or a keyboard, and a communication interface. This system can be realized with a hardware configuration that uses a normal computer.

The program executed by the power outage risk assessment system 1 according to this embodiment is provided by being pre-installed in a ROM or the like. Alternatively, this program may be provided by being stored in a non-transitory computer-readable storage medium such as a CD-ROM, CD-R, memory card, DVD, or flexible disk (FD) in the form of an installable or executable file.

The programs executed by the power outage risk assessment system 1 according to this embodiment 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 connect them to each other via a network or dedicated lines.

Furthermore, although the present embodiment illustrates an example in which a power outage occurs due to an accident in the power distribution system of the power system, other situations are also possible. For example, the risk of a power outage caused by an accident in a higher-level system of the power system may be evaluated.

According to the embodiment described above, by describing the power system using graphs and lists and providing a power outage probability evaluation unit 14 that evaluates the power outage probability of the power system and a power supply rate evaluation unit 16 that evaluates the power supply rate, it is possible to reduce the analysis load while contributing to the consideration of rational measures to reduce the risk of power outages. Furthermore, it is possible to quantitatively calculate not only the failure probability of the components of the power system but also the probability of their function loss to evaluate the risk of power outages. It is also possible to evaluate the return on investment or appropriateness of countermeasure equipment that consumers introduce to avoid damage caused by their own power outages.

Although several embodiments have been described above, these embodiments are presented only as examples and are not intended to limit the scope of the invention. The novel system described in this specification can be embodied in various other forms. Furthermore, various omissions, substitutions, and modifications can be made to the forms of the system described in this specification without departing from the spirit of the invention. The appended claims and equivalents are intended to include such forms and modifications that fall within the scope and spirit of the invention.

Reference Signs List 1: Power outage risk assessment system 2: Main control unit 3: Input unit 4: Output unit 5: Memory unit 6: Communication unit 7: System configuration database 8: Equipment database 9: Disaster hazard database 10: Power outage risk assessment unit 11: Supply and demand balance assessment unit 12: Risk curve assessment unit 13: Model creation unit 14: Power outage probability assessment unit 15: Model creation unit 16: Power supply rate assessment unit 17: Loss assessment unit 18: Risk curve creation unit

Claims (10)

a power outage probability evaluation unit that models a power system using a graph or a list and evaluates a power outage probability of the power system;
a supply and demand balance evaluation unit that evaluates a power supply rate of the power system based on the power outage probability;
A power outage risk assessment system comprising: The power outage risk assessment system of claim 1 further comprises a risk curve assessment unit that assesses a power outage risk curve using the power outage probability and the power supply rate. The power outage risk assessment system according to claim 1 or claim 2, wherein the graph or list is set based on the configuration for maintaining the power supply and the customers. The power outage risk assessment system according to claim 1 or claim 2, wherein losses in the power system are set in the graph or list. The power outage risk assessment system according to claim 1 or claim 2, wherein the graph or list is set based on the configuration of a power distribution automation system that monitors the power system or controls system switching. The power outage risk assessment system according to claim 1 or 2, wherein the graph or list is set based on the configuration upstream of a distribution substation in the power system. The power outage risk assessment system according to claim 1 or 2, wherein the graph or list is set based on a configuration downstream of a distribution substation in the power system. The power outage risk assessment system according to claim 1 or 2, further comprising a database in which specific information is stored that can identify whether or not the equipment constituting the power system will lose function due to a disaster by associating the equipment with an individually identifiable device ID. A power outage probability evaluation unit models the power system using a graph or a list, and evaluates the power outage pattern and power outage probability of the power system;
A supply and demand balance evaluation unit evaluates a power supply rate based on the power outage pattern;
A method for assessing the risk of power outages. modeling a power system using a graph or list and evaluating outage patterns and outage probabilities of the power system;
A process of evaluating a power supply rate based on the power outage pattern;
A program for causing a computer to execute the following.