JP2023096837A - Data collection system during disaster, and method of collecting data during disaster - Google Patents

Abstract

To support that a restoration plan for restoring a mechanism concerning power supplied to a power distribution system, facilities and so forth after disaster occurrence is quickly prepared without imposing any load thereon.SOLUTION: A data collection system during disaster comprises a first processing unit for collecting data comprising power distribution information including a position of a power distribution system and/or equipment, and a power application state of the power distribution system and/or the equipment; a second processing unit for calculating an area restored from a power failure state, based on the position and the power application state of the power distribution system and/or the equipment included in the data; and a third processing unit for determining execution timing of application of preparing a restoration plan with respect to the area, based on a typhoon-elapsing situation of the area obtained using meteorological information about the area, an occurrence state at a fault point indicating a power failure state place in the area, and a collection situation of the data including the power distribution information.SELECTED DRAWING: Figure 7

Description

The present invention relates to a disaster data collection system and a disaster data collection method.

An initial restoration plan creation simulation step for simulating the operation of a computer comprising a CPU and a memory for sequentially updating the initial restoration plan for the affected area each time usable information is obtained based on the advance prediction of the damage situation. and an initial placement simulation step that simulates the work of arranging the restoration workers who perform the recovery work and the equipment and materials necessary for the recovery work based on the initial recovery plan created by simulating the work in the initial recovery plan creation simulation step. , Simulating the work of restoring the disaster-stricken area by the restoration workers deployed by simulating the work in the initial placement simulating step, associating identifiers that identify equipment with failure information that indicates the failure status of equipment for each equipment An information processing method (see Japanese Patent Laid-Open No. 2002-100001), etc., characterized by executing a restoration work simulating step of updating the equipment information stored in the memory has been proposed.

JP 2014-2783 A

In the event of a disaster such as a typhoon, when grasping the damage situation, restoring the power distribution system and resuming operation as the initial response, a restoration plan must be prepared quickly for quick restoration. When a disaster strikes, data related to the disaster situation is transmitted from the system that manages the area where the disaster occurred, and data may be lost or changed due to interruptions in communication lines that accompany the disaster. Under such circumstances, it is required to provide effective data for recovery plan creation to a recovery plan creation application that uses the data, and to support execution at an early and appropriate timing.

In the technique disclosed in Patent Document 1, whether or not the information can be used for creating a recovery plan is determined by an application or by a person based on the information obtained. For this reason, a load is imposed due to the successive determination of the information content. Further, if the information is delayed or difficult to obtain, it is difficult to determine whether or not to create a recovery plan for the information and the execution timing, and the user will have to wait until the information can be obtained. Therefore, it may lead to a delay in creating a recovery plan.

The present invention provides a technology capable of assisting the creation of a recovery plan for recovering a mechanism related to power supply such as a distribution system and facilities after a disaster occurs, without imposing a load. for the purpose.

A disaster data collection system according to the present invention is a disaster data collection system for creating a recovery plan in the event of a disaster, which is performed by a computer having a calculation unit and a storage unit, and comprises a power distribution system and / or equipment a first processing unit that collects data having power distribution information including the position of the power distribution system and/or the energized state of the power distribution system and/or equipment; a second processing unit that calculates an area to be restored from a power failure state based on the state, a typhoon progress situation in the area obtained using the weather information of the area, and the location of the power failure state in the area. a third processing unit that determines execution timing of the recovery plan creation application for the area based on the occurrence status of the accident point and the collection status of the data including the power distribution information. Configured as a data collection system.

According to the present invention, it is possible to create a recovery plan for recovering a system related to power supply such as a distribution system and equipment after a disaster occurs, and to ensure the effectiveness of the plan by effective data utilization and load it. can help you do it quickly without

1 is a diagram showing an example of a system configuration to which a disaster data collection system and a disaster data collection method according to an embodiment are applied; FIG. FIG. 2 is a diagram showing an example of a computer schematic; It is a figure which shows an example of implementation of data collection at the time of a disaster, and restoration plan preparation. FIG. 2 is a conceptual diagram for explaining the range of an islanding operation area; It is a figure which shows the module structure of the data-collection server at the time of a disaster in a present Example. It is a figure which shows an example of the collection data table at the time of a disaster in a present Example. It is a figure which shows an example of the area information table in a present Example. It is a figure which shows an example of the data catalog table in a present Example. FIG. 10 is a diagram showing an example of a provided data list in the embodiment; FIG. 4 is a flow chart showing the flow of processing for determining execution start timing of creation of a recovery plan for each area in this embodiment. 10 is a flow chart showing the flow of processing for judging whether or not a fault point has occurred for each area in order to judge the execution start timing of creating a recovery plan for each area in this embodiment. FIG. 10 is a flow chart showing the flow of processing for judging the execution start timing of recovery plan creation for each area based on the data collection status for each area in this embodiment. FIG. FIG. 4 is a diagram showing an example of an application data definition related to data requested by a recovery plan creation application and an example of permissible condition items for the data in the embodiment; FIG. 4 is a diagram showing an example of a message format for providing data to applications in this system; FIG. 4 is a diagram for explaining the concept of judging the execution start timing of an application in this system (in the case of judging based on the typhoon passing situation); FIG. 4 is a diagram for explaining the concept of judging the execution start timing of an application in this system (case 1 where judgment is made based on whether or not a fault point has occurred); FIG. 2 is a diagram for explaining the concept of judging the execution start timing of an application in this system (case 2 where judgment is made based on whether or not an accident point has occurred); FIG. 4 is a diagram for explaining the concept of judging the execution start timing of an application in this system (judgment based on data collection status 1); FIG. 4 is a diagram for explaining the concept of judging the execution start timing of an application in this system (judgment based on data collection status 2);

Embodiments of the present invention will be described below with reference to the drawings. The following description and drawings are examples for explaining the present invention, and are appropriately omitted and simplified for clarity of explanation. The present invention can also be implemented in various other forms. Unless otherwise specified, each component may be singular or plural.

The position, size, shape, range, etc. of each component shown in the drawings may not represent the actual position, size, shape, range, etc., in order to facilitate understanding of the invention. As such, the present invention is not necessarily limited to the locations, sizes, shapes, extents, etc., disclosed in the drawings.

In the following description, various types of information may be described using expressions such as "database", "table", and "list", but various types of information may be expressed in data structures other than these. "XX table", "XX list", etc. are sometimes referred to as "XX information" to indicate that they do not depend on the data structure. When the identification information is described, expressions such as "identification information", "identifier", "name", "ID", and "number" are interchangeable.

When there are a plurality of components having the same or similar functions, they may be described with the same reference numerals and different suffixes. However, if there is no need to distinguish between these multiple constituent elements, the subscripts may be omitted in the description.

In addition, in the following description, there are cases where processing performed by executing a program is described. A processor may be the subject of the processing to perform the processing while appropriately using storage resources (eg, memory) and/or interface devices (eg, communication ports). Similarly, a main body of processing executed by executing a program may be a controller having a processor, a device, a system, a computer, or a node. The main body of the processing performed by executing the program may be an arithmetic unit, and may include a dedicated circuit (for example, FPGA (Field-Programmable Gate Array) or ASIC (Application Specific Integrated Circuit)) that performs specific processing. .

A program may be installed on a device, such as a computer, from a program source. The program source may be, for example, a program distribution server or a computer-readable storage medium. When the program source is a program distribution server, the program distribution server may include a processor and storage resources for storing the distribution target program, and the processor of the program distribution server may distribute the distribution target program to other computers. Also, in the following description, two or more programs may be implemented as one program, and one program may be implemented as two or more programs.

FIG. 1 is a diagram showing an example of a system configuration to which a disaster data collection system and a disaster data collection method according to this embodiment are applied.
The main components are disaster data that collects and manages data from distribution systems, IoT (Internet of Things) sensors, consumer smart meters, other infrastructure systems, etc. in the event of a disaster, and processes related to initial recovery plan creation. A collection server 101, a distribution automation system server 102 of a distribution automation system 171 where a distribution company operates and manages a distribution system, is installed in a region and environment, performs wireless communication with IoT sensors, etc., and collects and relays sensor data. base station servers (105, 106), consumer server 107 that collects and manages consumer data such as smart meters or IoT sensors at individual consumers, infrastructure other than power distribution constructed by local governments, etc. Other infrastructure system servers (108, 109) that operate and manage facilities.

In the following, the above-mentioned power distribution system is exemplified as an example of a mechanism related to power supply such as a power distribution system and equipment after a disaster. It is possible to apply various systems, equipment, etc.

Disaster data collection server 101 and power distribution automation system server 102 are interconnected via network 111 and network 112 . Disaster data collection server 101 and base station servers ( 105 , 106 ) are interconnected via network 111 and network 113 . Disaster data collection server 101 and customer server 107 are interconnected via network 111 and network 114 . The disaster data collection server 101 and other infrastructure system servers ( 108 , 109 ) are interconnected via networks 111 and 115 . However, the distribution automation system server 102, base station servers (105, 106), consumer server 107, and other infrastructure system servers (108, 109) provide data to the disaster data collection server 101 via the network (111, 112, 113, 114, 115), as well as when storing data manually in the disaster data collection server 101 without going through the network (111, 112, 113, 114, 115) There is also

Servers and equipment (103, 104, 163) in the distribution automation system 171 are used to control the distribution system 161. An IoT sensor is installed on a utility pole 162 or the like included in the power distribution system 161 . A consumer facility in the consumer 172 receives and receives electric power from the power distribution system 161 .

The disaster data collection server 101, power distribution automation system server 102, base station servers (105, 106), consumer server 107, and other infrastructure system servers (108, 109) shown in FIG. ), information is stored in a CPU 1601, a memory 1602, an external storage device 1603 such as a HDD (Hard Disk Drive), and a portable storage medium 1608 such as a CD (Compact Disk) or USB memory. A reading device 1607 for reading and writing, an input device 1606 such as a scanner, keyboard, and mouse, an output device 1605 such as a display, and a communication device 1604 such as a NIC (Network Interface Card) for connecting to a communication network are connected. It can be realized by a general computer 1600 having an internal communication line (called system bus) 1609 such as a system bus.

Various data stored in these servers or used for processing can be realized by the CPU 1601 reading from the memory 1602 or the external storage device 1603 and using them. In addition, each function unit of each server (for example, data collection unit 311, collected data management unit 312, data catalog management unit 313, application data definition management unit 314, other system cooperation of disaster data collection server 101 shown in FIG. 5) unit 315, execution timing determination unit 321, accident point state determination unit 322, data collection status determination unit 323, notification provision unit 331, and data communication unit 332). It can be implemented by loading it into the memory 1602 and executing it.

The predetermined program described above is stored (downloaded) in the external storage device 1603 from the storage medium 1608 via the reading device 1607 or from the network via the communication device 1604, and then loaded onto the memory 1602, It may be executed by the CPU 1601 . It may also be directly loaded into the memory 1602 and executed by the CPU 1601 from the storage medium 1608 via the reading device 1607 or from the network via the communication device 1604 .

In the following, a case where these servers are configured by a single computer will be exemplified, but all or part of these functions are provided distributed in one or more computers such as a cloud, and a network is used. may achieve similar functionality by communicating with each other via. Specific processing performed by each server will be described later using a flowchart.

FIG. 3 is a diagram showing an example of data collection and restoration plan creation at the time of a disaster.
In Fig. 3, in this system, when a typhoon 211 passes through a certain area 201 and damages the equipment of the power distribution system, etc., and damage such as power failure occurs, the damage situation is grasped as the initial response after the typhoon passes. , create a restoration plan and implement restoration work for the distribution system based on the plan. In this example, recovery means implementing islanding operation in which power is supplied only from distributed power sources in a separate isolated system in order to quickly resume operation of the distribution system and eliminate power outages. mention things.

Islanding operation is to supply power to minimize power failure damage to consumers, for example, by using distributed power sources such as storage batteries and photovoltaic power generation, and power supply cars. Also, the islanding operation area is a target range in which electric power can be supplied by performing the islanding operation.

Moreover, it is assumed that creating a recovery plan is to create a plan for implementing the islanding operation. An area 212 is a range divided so that power can be supplied from a distributed power source or the like in a divided power distribution system for carrying out the islanding operation. That is, in FIG. 3, the area 212 corresponds to the single area.

FIG. 4 is a conceptual diagram for explaining the range of the individual operation area. FIG. 4 shows an example of a power distribution system in a certain area 201 shown in FIG. As shown in FIG. 4, the area 201 includes a plurality of individual operation areas 212 (in this example, four individual operation areas 212a, 212b, 212c, and 212d). Now, due to a disaster caused by the passage of a typhoon or the like, damage to the power distribution system and facilities in the isolated operation area 212a has caused accident points X (four points X1 to X4 in this example), resulting in power outage damage. A fault point represents a location where current cannot flow, such as a collapsed utility pole or a broken wire.

If there is no accident point due to damage to the distribution system or equipment, the distribution system in the area 201 is composed of these four islanding operation areas. The system is damaged and cannot be operated independently. Therefore, the isolated operation areas targeted by this system are three isolated operation areas 212b, 212c, and 212d. In this example, the islanding operation area 212b is in a state of being energized as in normal times, the islanding operation area 212c is in a state of being able to secure energization by the distributed power supply, and the islanding operation area 212d is in a state where power supply cars It is assumed that the energization can be secured by As to which range is to be defined as one single operation area 212, for example, blackout information (for example, blackout date and time, blackout area, blackout time period, etc.) about the accident point managed by the power distribution automation system server 102 of the power distribution automation system 171 information) and predetermined distribution information in which a distribution system or facility is associated with a geographical position where the distribution system or facility is installed. A method of specifying the area will be described later with reference to FIG.

In FIG. 3, as the typhoon 211 passes, in each area 212, the power distribution automation system 171 and the environmental Data from the IoT sensor installed inside, the smart meter of the customer 172, etc. (for example, the current measurement value, the error code indicating power failure or no power supply) is frequently detected from before the typhoon to during the passage of the typhoon. Collected. FIG. 3 shows that data are collected twice before the typhoon passes, nine times during the typhoon, and four times after the typhoon passes.

In order to quickly implement initial restoration, as the typhoon passes, after the typhoon passes, grasp the damage situation based on data 221, create a restoration plan, and restore the power distribution system based on the plan. 222 to be implemented.

Here, delays in planning also lead to delays in recovery. On the other hand, prematurely creating an imprecise plan with insufficient data can hinder the smooth implementation of recovery. In particular, when creating a plan for implementing the islanding operation, if there is an accident point where the distribution system is disconnected or equipment is damaged, the distribution system cannot be operated in the area containing the accident point. It is also not possible to create a plan for the area containing the accident point. In other words, the islanding operation plan is a plan for supplying power from the islanding operation area to the area where the power failure occurred and performing the above restoration. is not included in the single area. In addition, if an area that has been planned and operated once is changed, there will be a delay in recovery due to re-planning for the changed area. Therefore, you want to avoid recreating the plan.

For this reason, the range in which power can be supplied is expanded by gradually expanding the area in which individual operation is possible. It is difficult to estimate in advance the occurrence of accident points, etc., and they may occur simultaneously. For this reason, the processing load related to grasping the damage situation and creating a recovery plan should be minimized. Although the data required by the recovery plan creation application is specified, there may be an allowable range of reliability required for the data.

FIG. 5 is a diagram showing the module configuration of the disaster data collection server in this embodiment.
Disaster data collection middleware 301 that collects and manages data from power distribution systems, IoT sensors, consumer smart meters, other infrastructure systems, etc. in the event of a disaster to the disaster data collection server 101, and executes processing related to data provision to applications. Then, recovery plan creation applications (302, 303) are introduced to execute processing related to initial recovery plan creation.

The main components of the disaster data collection middleware 301 are the power distribution automation system server 102, the base station servers (105, 106), the data collection unit 311 that collects data from the consumer server 107, and the disaster data collection unit that stores the collected data. A collected data management unit 312 that manages collected data 341, a data catalog management unit 313 that manages a data catalog storing catalog information of data handled by the disaster data collection server 101, and an application data definition 345 that is a data definition by an application. Application data definition management unit 314 to be managed, other system cooperation unit 315 that performs cooperative processing for collecting data from other infrastructure system servers (108, 109), and determination of execution timing of recovery plan creation applications (302, 303) An execution timing determination unit 321, a fault point state determination unit 322 that determines the fault point occurrence state in the area by referring to the disaster time collection data 341 and the area information 342, and an area A data collection status determination unit 323 that determines the data collection status in the recovery plan creation application (302, 303), a notification providing unit 331 that notifies the recovery plan creation application (302, 303) of execution timing and provides data, network (111, 112, 113, 114 , 115) with the distribution automation system server 102, base station servers (105, 106), consumer server 107, and other infrastructure system servers (108, 109). The catalog information is information that defines what kind of data (type of data, etc.) is to be processed by the disaster data collection server 101 .

6A to 6D are diagrams showing configurations of tables used in the disaster data collection method and system according to this embodiment.

FIG. 6A shows an example of a disaster collection data table 341 that stores information related to data collected from power distribution systems, IoT sensors, consumer smart meters, other infrastructure systems, etc. at the time of a disaster, managed by the disaster data collection server 101. FIG. 4 is a diagram showing; FIG. 6B is a diagram showing an example of the area information table 342 that stores information about areas. FIG. 6C is a diagram showing an example of the data catalog table 343 that stores catalog information of data handled by the disaster data collection server 101. As shown in FIG. FIG. 6D is a diagram showing an example of the provided data list 344 that stores data provided to the planning application running on the disaster data collection server 101 and information about the data.

As shown in FIG. 6A, the main components of the disaster collection data table 341 are data identification information 411, area identification information 412, measurement position 413, temporal characteristics 414, latest occurrence time 415, latest collection time 416, record number 417, data 418, and update date/time 419.

The data identification information 411 stores information for identifying data collected in the event of a disaster. The area identification information 412 stores information for identifying the area corresponding to the origin of the data identified by the data identification information 411 . The measurement position 413 stores information about the measurement position of the data specified by the data identification information 411 . The temporal property 414 stores information about the temporal property of the data specified by the data identification information 411 (for example, at what point in time the data is current value, predicted value, historical value, etc.). The latest occurrence time 415 stores the time when the latest data value among the data specified by the data identification information 411 occurred (that is, the latest time when the data occurred at the data collection source). The latest collection time 416 stores the time when the latest data value among the data specified by the data identification information 411 was collected (that is, the latest time when the server collected data from the collection source). The number of records 417 stores the number of records of the data specified by the data identification information 411 already stored in the table. The data 418 stores the body of the data specified by the data identification information 411 or pointer information to the body of the data. By reading the pointer information, the specific contents of the data body can be accessed. The updated date and time 419 stores the date and time when the records 411 to 418 were last updated.

For example, in FIG. 6A, the data identified by the data identification information "accident point_1010000121" is data indicating the current value, and the measurement position "(N35°39' 20”,E135°58'00”)” indicates that the data is collected from the distribution system, IoT sensors, consumer smart meters, and other infrastructure systems. In addition, the time when the data was generated at the collection source is "2021-10-10 11:57:53", and the time when the server collected the data is "2021-10-10 11:59:03". showing. Furthermore, the number of records of the collected data is 1, the reference destination of the actually stored data is "DataPointer00000501", and the record is the latest information at "2021-10-10 12:00:10" indicates that it has been updated to In this way, the disaster time collection data table 341 stores various data transmitted from the data collection source.

As shown in FIG. 6B, the main components of the area information table 342 are area identification information 421, area position information 422, area system information 423, typhoon progress status 424, typhoon passage time 425, accident point status 426, and equipment restoration. 427, executability (application 1) 428, executability (application 2) 429, executability (application N) 420, update date 441.

The area identification information 421 stores information for identifying areas targeted for data collection and restoration plan creation. The area location information 422 stores information about the location of the area identified by the area identification information 421. FIG. The area system information 423 stores information about the distribution system corresponding to the area specified by the area identification information 421. FIG. Typhoon progress information in the area specified by the area identification information 421 is stored in the typhoon progress status 424 . Information such as "before passage", "during passage", and "after passage" is stored here. The typhoon passing time 425 stores the time when the typhoon has completed passing through the area identified by the area identification information 421 or the estimated time when the typhoon will complete passing. The accident point state 426 stores information regarding the occurrence state of the accident point in the area specified by the area identification information 421. FIG. The facility recovery 427 stores information as to whether or not the facility recovery after the occurrence of the fault in the area identified by the area identification information 421 has been completed. Executability (application 1) 428, executability (application 2) 429, and executability (application N) 420 store information about the execution propriety of the application. Here, any one of "executable", "waiting for execution", and "executable" is stored. The updated date and time 441 stores the date and time when the records 421 to 420 were last updated.

For example, in FIG. 6B, the area identified by the area identification information "Area_00000053" shown in FIG. 6A is located in the range identified by "Mesh No.0012, 0013, 0014, ,,," indicates that the distribution system and facilities identified by "distribution line No. 12, 13, 15, ,,," are included. In addition, a typhoon is passing through the area, and the expected completion time is 2021-10-10 12:15:00. It indicates that it is in the (incomplete) state. The recovery plan creation applications (302, 303) (for example, application 1 and pre-2) are respectively in the execution standby state, and the record is updated to the latest information at "2021-10-10 12:02:30". Indicates that it has been updated. In this way, the area information table 342 stores various data relating to the state of the disaster in the area from which the collected data is collected.

As shown in FIG. 6C, the main components of the data catalog table 343 are data identification information 431, data source information 432, data type information 433, data collection timing 434, data I/F information 435, system operation information 436, The update date is 437.

The data identification information 431 stores information for identifying data to be collected by the disaster data collection server 101 . The data source information 432 stores information about the data source of the data specified by the data identification information 431. FIG. The data type information 433 stores information about the data type specified by the data identification information 431 . The data collection timing 434 stores information regarding the collection timing of the data specified by the data identification information 431 . Here, information related to the cycle of execution of collection processing or an event that triggers the start of execution of collection processing is stored. Data I/F information 435 stores information relating to an interface for accessing data specified by data identification information 431 . The system operation information 436 stores information about the operation of the system that generated the data identified by the data identification information 431 . The updated date and time 437 stores the date and time when the records 431 to 436 were last updated.

For example, in FIG. 6C, data identified by the data identification information “fault point_1010000121” shown in FIG. This indicates that the data is It also indicates that the data is collected by accessing the power distribution automation system, which is the data source, using the interface information indicated by "MQTT, topic=xxxx". Furthermore, it indicates that the system from which the data was collected is currently in operation, and the record was updated to the latest information at "2021-10-10 00:00:00". Thus, the data catalog table 343 stores various catalog information of collected data. The data catalog table 343 is stored in advance by an administrator or the like of this system.

As shown in FIG. 6D, the main components of the provided data list 344 are data identification information 441, permissible condition matching status 442, available time 443, provision status 444, data 445, and update date/time 446.

The data identification information 441 stores information for identifying data to be provided to the application. The permissible condition matching status 442 stores information about the permissible condition matching status of the data specified by the data identification information 441 with respect to the data defined by the application. Details of the acceptance conditions for the data are shown in FIG. The provisionable time 443 stores the time when the data specified by the data identification information 441 can be provided to the application. The provision state 444 stores information regarding the provision state of the data specified by the data identification information 441 . Information such as "already provided" and "not yet provided" is stored here. Data 445 stores pointer information to data specified by data identification information 441 . The updated date and time 446 stores the date and time when the records 441 to 445 were last updated.

For example, in FIG. 6D, the data identified by the data identification information "accident point_1010000121" shown in FIG. 10 12:00:10” indicates that the data can be provided to recovery plan creation applications (302, 303) (eg, application 1, pre 2) for recovery plan creation. Also, at this time, the data identified by "DataPointer00000501" has not been provided, and the record has been updated to the latest information at "2021-10-10 12:02:30". there is Thus, the provided data list 344 stores information indicating under what conditions the collected data is provided.

FIG. 7 is a flow chart showing the flow of processing for determining the execution start timing of plan creation for each area in the disaster data collection system and disaster data collection method according to the present embodiment.

At step 501, the data collection unit 311 determines whether or not it is possible to acquire the state of the distribution system. Whether or not the state of the power distribution system can be acquired may be determined by, for example, whether or not the power distribution information has been acquired from the power distribution automation system server 102 of the power distribution automation system 171 .

If the data collection unit 311 determines that it is possible to acquire the state of the distribution system (501; YES), in step 502, the energized range and the blackout range are calculated from the acquired state of the distribution system. Area divisions are generated based on this. As for these ranges, for example, if the distribution system or equipment included in the distribution information and the locations of the distribution system or equipment are located close to each other to a certain degree, the data collection unit 311 treats them both as the same area. This is repeated, and when the number of locations of the distribution system and facilities in the same area reaches a predetermined threshold value, one area may be selected for determining the state of the distribution system. The data collection unit 311 can acquire the state of the distribution system for the latest area by constantly performing such processing. In other words, it is possible to determine what kind of range each area is and whether the area in the divided range is in the energized state or in the power outage state. Also, an area division is, for example, a division of an area identified by the data identification information 421 shown in FIG. 6B, and is information for identifying one area 212 shown in FIG.

On the other hand, in step 501, if the data collection unit 311 determines that the status of the distribution system cannot be obtained (501; NO), in step 503, area divisions are statically generated based on the system profile information. do. The system profile information is information that associates a distribution system or facility with a geographical position, which is the location of the distribution system or facility, for each predetermined range.

In step 504, the geographical position of the area generated in steps 502 and 503 is calculated based on the system profile information. For example, the data collection unit 311 selects a plurality of positions from the outermost positions in the area among the distribution system and equipment included in the area of the division generated in step 502 and the locations of the distribution system and equipment, Based on the relationship between these selected positions, the distribution system and equipment stored in the system profile information, and the geographical position of the distribution system and equipment, the range surrounded by these selected positions is determined. It is identified as the geographical location of the area and is referred to as area location information 422 shown in FIG. 6B. In addition, the data collection unit 311 reads the distribution system and equipment stored in the system profile information and the geographical location of the distribution system and equipment, and uses the same method as in step 501 to extract one area. is identified as the geographical location of the area, and is defined as area location information 422 shown in FIG. 6B. It is assumed that the area location information 422 (or the distribution system or equipment and the geographical position that is the location of the distribution system or equipment) and the area system information 423 are associated in advance. In addition, the data collection unit 311 adds area identification information 421 for identifying the identified area location information 422, and stores the same value as the area identification information 421 in the area identification information 412 shown in FIG. 6A. do. The data identification information 411, measurement position 413, temporal property 414, latest occurrence time 415, latest collection time 416, number of records 417, and data 418 shown in FIG. Written at the time of collection.

In step 505, the execution timing determination unit 321 compares the geographical position of the area calculated by the data collection unit 311 in step 504 with information such as the position, speed, and direction of the typhoon that is occurring, and determines the location of the area. Calculate the progress of the typhoon. For example, the data collection unit 311 acquires information such as the position, speed, and direction of the typhoon from various sites reporting the latest weather, and stores it in the typhoon progress status 424 and typhoon progress time 425 shown in FIG. 6B. Let it be.

When the execution timing determination unit 321 determines in step 506 that the typhoon progress state calculated in step 505 is "passing", in step 507, it performs the accident point presence/absence determination process. Details of the fault point presence/absence determination processing are shown in FIG. Regarding whether or not a typhoon is passing, for example, if the position on the path of the typhoon obtained from the above various sites is included in the geographical position of the area calculated above, it is determined that the typhoon is passing. good.

At step 508, the data collection status determination unit 323 performs data collection status determination processing. Details of the data collection status determination process are shown in FIG.

In step 506, when the execution timing determination unit 321 determines that the typhoon progress situation calculated in step 505 is “after passing”, the accident point state determination unit 322 determines in step 509 that the area is an accident point. Check if it is done. Regarding whether or not the typhoon has passed, for example, if the position on the path of the typhoon obtained from the various sites above is no longer included in the geographical position of the area calculated above, it is determined that the typhoon has passed. do it. As to whether or not the accident point has occurred, for example, the accident point state determination unit 322 refers to the disaster time collection data 341 shown in FIG. 6A and the area information 342 shown in FIG. If yes is stored, it can be determined that an accident point has occurred in the area. As for the method of storing "present" in the fault point state 426, for example, the fault point state determination unit 322 records the power outage information about the fault point collected by the data collection unit 311 from the distribution automation system server 102 of the distribution automation system 171. If so, it should be determined that there is an accident point in the area.

In step 510, when the fault point state determination unit 322 determines that the fault point has not occurred in the area in question as a result of the processing in step 509 (510; NO), the execution timing determination unit 321 determines in step 511 Determine that planning is "feasible" for the area.

On the other hand, in step 510, if the accident point state determination unit 322 determines that the accident point has already occurred in the area as a result of the processing in step 509 (510; YES), in step 512, the equipment in the area has been restored. It is determined whether or not. Regarding whether or not the facility has been restored in the area, for example, after it is determined that there is an accident point in the fault point presence/absence determination process described later and "present" is stored in the accident point state 426, the accident point state 426 is If the result is "None", it may be determined that the facility has been restored in the area.

If the accident point state determination unit 322 determines that the equipment has not been restored in the area (512; NO), in step 513, it determines that plan creation is "unexecutable" for the area, and are stored in execution propriety (application 1) 428 , execution propriety (application 2) 429 , and execution propriety (application N) 420 .

On the other hand, if the accident point state determination unit 322 determines in step 512 that the facility has been restored in the area (512; YES), in step 514, plan creation is “executable” for the area. Execution possibility (application 1) 428 , execution possibility (application 2) 429 , and execution possibility (application N) 420 are stored to that effect.

In step 506, when the execution timing determination unit 321 determines that the typhoon progress situation calculated in step 505 is "before passage", in step 515, plan creation is "unexecutable" for the area. Execution possibility (application 1) 428 , execution possibility (application 2) 429 , and execution possibility (application N) 420 are stored to that effect. Regarding whether the typhoon has not yet passed, for example, if the position on the typhoon's path obtained from the various sites above is not included in the geographical position of the area calculated above, it is determined that the typhoon has not yet passed. do it.

In step 516, the notification providing unit 331 determines whether execution of plan creation for the area is "executable", "execution standby", or "inexecutable" as a result of the processing up to step 515. FIG. When the notification providing unit 331 determines that the plan creation executability for the area is “executable”, in step 517, the notification providing unit 331 notifies the plan creation application of “executable”. The notification provider 331 then provides data to the planning application in step 518 . The format of the provided data will be described later with reference to FIG.

On the other hand, in step 516, when the notification providing unit 331 determines that the execution availability of plan creation for the area is “execution standby” as a result of the processing up to step 515, in step 519, the plan creation application Notify "waiting to run" and waiting time.

Further, in step 516, when the notification providing unit 331 determines that the plan creation executability for the area is “impossible” as a result of the processing up to step 515, in step 520, the plan creation application Notifies that it cannot be executed.

At step 521, the notification providing unit 331 determines whether or not data provision or notification has been completed for all areas. When the notification providing unit 331 determines that data provision or notification has not been completed for all areas (521; NO), the processing of steps 501 to 520 is repeated. On the other hand, when the notification providing unit 331 determines in step 521 that data provision or notification has been completed for all areas (521; YES), this processing ends.

FIG. 8 is a flow chart showing the flow of processing for judging whether or not an accident point has occurred for each area in order to judge the execution start timing of plan creation for each area in this embodiment.

In step 601, the accident point state determination unit 322 refers to the disaster time collection data 341, and confirms the presence or absence of an accident point up to the present time based on the occurrence history of accident points in the relevant area during the course of the current typhoon. . At step 602, the accident point state determination unit 322 confirms whether or not an accident point has occurred in the area at this time. Regarding whether or not the accident point has occurred, for example, the accident point state determination unit 322 refers to the disaster time collection data 341 shown in FIG. 6A and the area information 342 shown in FIG. 6B, as described in step 506. can be determined. Also, whether or not an accident point has occurred at the present time can be determined by referring to the latest collected data and using the method described above.

At step 603, the accident point state determination unit 322 determines whether or not there is an accident point in the area as a result of the processing at steps 601 and 602. FIG. When the accident point state determination unit 322 determines that there is no accident point in the area (603; NO), the process ends.

On the other hand, if the accident point state determination unit 322 determines in step 603 that there is an accident point in the area as a result of the processing of steps 601 and 602 (603; YES), It is determined whether or not many occurrences have already occurred in the

If the fault point state determination unit 322 determines that many faults have already occurred in the area (604; YES), then in step 605, the plan generation application is "unexecutable" in the area. , to that effect is stored in executability (application 1) 428 , executability (application 2) 429 , and executability (application N) 420 . Here, regarding whether or not there are many occurrences, for example, when the number of occurrences and the degree of distribution of accident points in the area are equal to or greater than a specified threshold value, it is determined that there are many occurrences.

In step 604, if the accident point state determination unit 322 determines that many accident points have not occurred in the area (604; NO), then in step 606, if the typhoon has already passed through the area, determines whether or not an accident point has occurred in the remaining area where there is no accident point and the typhoon has not yet passed. The remaining range where the typhoon has not yet passed is a range that is on the course of the future typhoon and that the typhoon has not yet passed. For the remaining areas where the typhoon has not yet passed, similar to the determination method in step 506, the following should be done. For example, the accident point state determination unit 322 determines that the position on the path of the typhoon obtained from the various sites is included in the geographical position of the calculated area, and the typhoon obtained from the various sites is included in the calculated area. The area in which the typhoon has not passed can be regarded as the remaining area in which the typhoon has not yet passed.

If the accident point state determination unit 322 determines that there is no accident point in the area where the typhoon has already passed and that there is an accident point in the remaining area where the typhoon has not yet passed (606; YES), In step 607, the area is shortened to a range in which no accident points have occurred, and it is determined that the plan creation application is “executable” ahead of schedule. 2) Stored in 429 , Execution propriety (Application N) 420 . In other words, the accident point state determination unit 322 determines that the application can be executed in order to provide the data collected in the area where the typhoon has already passed and there are no accident points other than the remaining area within the area. .

In step 606, if the accident point state determination unit 322 determines that there is no accident point in the area where the typhoon has already passed and that no accident point has occurred in the remaining area where the typhoon has not yet passed (606; NO ), the process ends.

FIG. 9 is a flow chart showing the flow of processing for judging the data collection status for each area in order to judge the execution start timing of creating a recovery plan for each area in this embodiment.

In step 701, the data collection status determination unit 323 refers to the disaster time collection data 341 and the area information 342, and compares the geographical position of the relevant area with information such as the position, speed, and direction of the typhoon that is occurring. to calculate the typhoon passage time in the area.

At step 702, the data collection status determination unit 323 refers to the data definition 345 of the application. Details of the application data definition 345 are shown in FIG.

In step 703, the data collection status determination unit 323 collates the data definition 345 of the application in step 702 with the data already collected from the area in the collected data 341 at the time of disaster.

In step 704, the data collection status determination unit 323 determines whether or not the data matches all the permissible condition items in the data definition 345 of the application as a result of the collation in step 703.

If the data collection status determination unit 323 determines that the data matches all the permissible condition items in the data definition 345 of the application (704; YES), in step 705, the data catalog 343 is referred to, and determines whether or not there is an update of the data. The presence or absence of the update may be determined by, for example, whether or not the data collection timing 434 of the data catalog 343 arrives by the typhoon passing time 425 of the area information 342 .

If the data collection status determination unit 323 determines that the data will not be updated by the typhoon passing time (705; NO), the information of the data is added to the provided data list 344 in step 706. FIG. For example, the data collection status determination unit 323 stores the collected data from the relevant area in the disaster time collection data 341 in the data 445 of the provided data list 344, the permissible condition matching status 442, the available time 443, and the provision status 444. , update date and time 446 are set, and data identification information 441 is added. For the permissible condition matching status 442, for example, the degree of matching when collated in step 703 may be calculated and stored. Further, for example, the provisionable time 443 may be set to a predetermined timing (provision time or provision cycle). As for the provision status 444 and update date/time 446, since the data has not yet been provided to the application, "not provided" may be set, and the update date/time 446 may be updated with the processing time of the step.

In step 704, if the data collection status determination unit 323 does not determine that the data matches all the permissible condition items in the data definition 345 of the application (704; NO), the process proceeds to step 707. FIG.

In step 705, the data collection status determination unit 323 refers to the data catalog 343, and if it determines that the data will be updated by the typhoon passing time (705; present), the process proceeds to step 710. FIG.

In step 707, the data collection status determination unit 323 determines whether or not the data matches the condition items for which the priority is set high in the data definition 345 of the application. The determination as to whether or not the condition item has a high priority is made, for example, by determining whether the value stored in the priority item shown in FIG. It can be determined by whether or not

If the data collection status determination unit 323 determines that the data matches the condition items set with high priority in the data definition 345 of the application (707; YES), in step 708, the data catalog 343 is referred to in the same manner as in step 705. Then, it is determined whether or not the data will be updated by the typhoon passing time. If the data collection status determination unit 323 determines that the data has not been updated by the typhoon passing time (708; no), as in step 706, the information of the data is added to the provided data list 344 in step 709. do. On the other hand, in step 708, the data collection status determination unit 323 refers to the data catalog 343 and determines that the data will be updated by the typhoon passage time (708; present). Proceed to processing.

In step 710, the data collection status determination unit 323 determines whether or not the confirmation processing of steps 702 to 709 has been performed for all data defined in the data definition 345 of the application, and determines that the processing has not been completed. If so (710; incomplete), repeat the processing of steps 702-709.

On the other hand, in step 710, if the data collection status determination unit 323 determines that all the data defined in the data definition 345 of the application have undergone the confirmation processing in steps 702 to 709 (710; completed), in step 711, It is determined whether or not there is data corresponding to a record that has not been added to the provided data list 344 among the records stored in the data definition 345 of the application.

If the data collection status determination unit 323 determines that there is no data corresponding to a record that has not yet been added to the provided data list 344 among the records stored in the data definition 345 of the application (711; none), step In 712, it is determined that planning is “executable” for the area, and this fact is stored in executability (application 1) 428, executability (application 2) 429, and executability (application N) 420. to terminate this process.

In step 711, when the data collection status determination unit 323 determines that there is data that has not been added to the provided data list 344 among the records stored in the data definition 345 of the application (711; present), step At 713, the data catalog 343 is referenced to calculate the next collection time of the data. The next collection time can be calculated from, for example, the data collection timing 434 of the data catalog table 343 and the current time.

In step 714, the data collection status determination unit 323 determines whether the next collection time of the data calculated in step 713 is not within the typhoon passage time. If it is determined not ( 714 ; NO), the process proceeds to step 721 .

In step 714, when the data collection status determination unit 323 determines that the next collection time of the data calculated in step 713 is within the typhoon passage time (714; YES), in step 715, the data catalog 343 is referred to. to determine whether the state of the collection system is normal. The collection system is, for example, each system connected to the disaster data collection server 101 via the network 111 . Further, when the status is normal, each system is connected to the disaster data collection server 101 and is in a state where the disaster collection data 341 can be collected.

When the data collection status determination unit 323 determines that the state of the collection system is normal (715; normal), in step 716, as in step 703, the data is compared with the data definition 345 of the application, and step At 717, a determination is made whether the data meets all of the allowable terms in the application's data definition 345;

If the data collection status determination unit 323 determines that the data matches all of the permissible condition items in the data definition 345 of the application (717; present), in step 718, the provided data list 344 of the data Add information.

In step 715, the data collection status determination unit 323 refers to the data catalog 343, and if it determines that the state of the collection system is abnormal (715; abnormal), the process proceeds to step 721. FIG.

In step 717, when the data collection status determination unit 323 determines that the data does not match all the permissible condition items in the data definition 345 of the application (717; none), the process proceeds to step 719.

In step 719, the data collection status determination unit 323 collates the relevant data with the application data definition 345 in the same way as in step 707, and the relevant data matches the condition items set with high priority in the application data definition 345. Determine whether or not

If the data collection status determination unit 323 determines that the data matches the condition items with a high priority set in the data definition 345 of the application (719; Yes), in 720, the corresponding Add data information.

In step 719, the data collection status determination unit 323 collates the relevant data with the application data definition 345, and determines that the relevant data does not match the condition items set with high priority in the application data definition 345. If so (719; NO), the process proceeds to step 721;

In step 721, the data collection status determination unit 323 determines whether or not the confirmation processing of steps 714 to 720 has been performed for all remaining data defined in the data definition 345 of the application. If so (721; unfinished), the processing of steps 713-720 is repeated.

In step 721, if the data collection status determination unit 323 determines that all the remaining data defined in the data definition 345 of the application have undergone the confirmation processing in steps 702 to 709 (721; completed), in step 722, Similar to step 711, it is determined whether or not there is data corresponding to a record that has not yet been added to the provided data list 344 among the records stored in the data definition 345 of the application.

If the data collection status determination unit 323 determines that there is no data corresponding to a record that has not yet been added to the provided data list 344 among the records stored in the data definition 345 of the application (722; none), step At 733, the data catalog 343 is referenced to calculate the execution waiting time. The execution waiting time can be calculated, for example, by finding the difference between the data collection timing 434 of the data catalog table 343 and the current time.

In step 734, the data collection status determination unit 323 determines that plan creation for the area is “waiting for execution”, and notifies execution availability (application 1) 428, execution availability (application 2) 429, execution It is stored in the permission (application N) 420, and this processing ends.

In step 722, if the data collection status determination unit 323 determines that there is data that has not been added to the provided data list 344 among the records stored in the data definition 345 of the application (722; present), step At 723, the application's data definition 345 is referenced to determine if the freshness of the data (FIG. 10) is a priority item. Whether or not the item is a priority item may be determined, for example, by determining whether or not the priority 823 (FIG. 10) of the freshness of the data is smaller than a predetermined value.

If the data collection status determination unit 323 determines that the freshness of the data (FIG. 10) is a priority item, then in step 724, as in step 715, the data catalog 343 is referred to and the state of the collection system is determined to be normal. It is determined whether or not.

If the data collection status determination unit 323 determines that the state of the collection system is normal (724; normal), in step 725, as in step 716, the data in question is compared with the data definition 345 of the application, and step At 726, a determination is made as to whether the data meets all of the allowable terms in the application's data definition 345;

If the data collection status determination unit 323 determines that the data matches all the permissible condition items in the data definition 345 of the application (726; yes), as in step 717, in step 727, as in step 720, the provided data list 344 Add information about the data to

In step 723, the data collection status determination unit 323 refers to the data definition 345 of the application and determines that the freshness of the data is not a priority item (723; NO).

In step 724, the data collection status determination unit 323 refers to the data catalog 343, and if it determines that the state of the collection system is abnormal (724; abnormal), the process proceeds to step 730. FIG.

In step 725, the data collection status determination unit 323 collates the relevant data with the application data definition 345 in the same way as in step 716. determine whether or not to

If the data collection status determination unit 323 determines that the data does not match all the permissible condition items in the data definition 345 of the application (726; none), the process proceeds to 728, as in step 719.

In step 728, the data collection status determination unit 323 collates the data with the application data definition 345 to determine whether the data matches the condition items set with high priority in the application data definition 345. judge.

If the data collection status determination unit 323 determines that the data matches the condition items set with high priority in the application data definition 345 (728; yes), in step 729, the provided data list 344 Add information about the data.

In step 728, the data collection status determination unit 323 compares the data with the application data definition 345, and determines that the data does not match the condition items set with high priority in the application data definition 345. If so (728; NO), the process proceeds to step 730;

At step 730, the data collection status determination unit 323 determines whether or not the confirmation processing of steps 723 to 729 has been performed for all remaining data defined in the data definition 345 of the application. If so (730; incomplete), the processing of steps 723-729 is repeated.

In step 730, if the data collection status determination unit 323 determines that all the remaining data defined in the data definition 345 of the application have undergone the confirmation processing in steps 702 to 709 (730; completed), in step 731, Similar to step 711, it is determined whether or not there is data corresponding to a record that has not yet been added to the provided data list 344 among the records stored in the data definition 345 of the application.

If the data collection status determination unit 323 determines that there is no data corresponding to a record that has not yet been added to the provided data list 344 among the records stored in the data definition 345 of the application (731; none), step At 733, the data catalog 343 is referenced to calculate the execution waiting time.

On the other hand, when the data collection status determination unit 323 determines that there is data that has not been added to the provided data list 344 among the records stored in the data definition 345 of the application (731; present), in step 730a , it is determined that plan creation is “unexecutable” for the area, and this fact is stored in execution possibility (application 1) 428, execution possibility (application 2) 429, and execution possibility (application N) 420. End the process.

FIG. 10 is a diagram showing an example of an application data definition regarding data requested by a recovery plan creation application and an example of permissible condition items for the data in this embodiment. The application data definition 345 is information that defines various types of data input to the application. It is assumed that the application data definition 345 is defined in advance for each application by the system administrator or the like.

The main components are data identification information 811 , freshness 812 , provenance 813 , measurement location 814 and temporal nature 815 .

The data identification information 811 stores information for identifying data requested by the application.

The freshness 812 stores information about the frequency of data provision requested by the application for the freshness of the data specified by the data identification information 811 . Here, the freshness represents, for example, the degree of temporal distance between the occurrence time of the data and the time of the disaster occurrence, that is, the newness or oldness of the data. The permissible condition 821 stores information about the permissible range of freshness of the data identified by the data identification information 811. FIG. The mandatory and optional 822 stores information indicating whether the freshness 812 is “mandatory” or “optional” as the permissible condition item for the data specified by the data identification information 811 . The priority 823 stores the priority of the freshness 812 in the permissible condition item for the data specified by the data identification information 811 .

For example, in FIG. 10, for the data with the data identification information 811 of "accident point __1010000121", only the latest value can be input to the application for processing by the application, and this condition is an essential condition. showing. This condition also indicates that it is a condition (priority is "1") that has priority over other allowable condition items (source 813, measurement position 814, temporal property 815 allowable condition). Regarding whether or not the value is the latest, for example, the data collection status determination unit 323 compares the update date and time 419 included in the record of the disaster collection data 341 with the disaster collection data 341 provided at the previous timing. can be determined by comparing with the update date/time 419 included in the record.

The source 813 stores information about the reliability of the data requested by the application for the source of the data specified by the data identification information 811 . Here, the source indicates, for example, whether the source of the data is the own system or another system. The data of the own system is, for example, data provided from the power distribution automation system server 102 of the power distribution automation system 171 connected to the system or the power distribution automation system 171 connected to the system through a network in which security is ensured. Further, the data of other systems are, for example, data provided from open sites where security is not guaranteed, other than this system and the power distribution automation system server 102 described above.

The permissible condition 831 stores information about the permissible range of the source of the data specified by the data identification information 811. FIG. The mandatory optional 832 stores information indicating whether the source 813 is “mandatory” or “optional” as the permissible condition item for the data specified by the data identification information 811 . The priority 833 stores the priority of the source 813 in the permissible condition item for the data specified by the data identification information 811 .

For example, in FIG. 10, data whose data identification information 811 is "accident point __1010000121" can be input to the application only when the source of the data provided for processing by the application is the own system. This condition indicates that it is an essential condition. In addition, this condition indicates that it is a condition with a lower priority (priority is "4") than the other allowable condition items (freshness 812, measurement position 814, temporal property 815 allowable conditions). . Regarding whether or not the data provider is the own system, for example, the data collection status determination unit 323 determines that the power distribution automation system 171 is registered in the data source information 432 included in the record of the data catalog table 343. If so, it may be determined that this system or a system connected to this system via a network in which security is ensured, that is, the self system, is the provider.

The measurement position 814 stores information about the matching degree of the measurement position of the data requested by the application with respect to the measurement position of the data specified by the data identification information 811 . Here, the measurement position represents, for example, "current location only", "neighborhood possible", "similar source possible", etc., as a position measured to acquire the relevant data. Note that the permissible condition 841 stores information about the permissible range for the measurement position of the data specified by the data identification information 811. FIG. The mandatory optional 842 stores information as to whether the measurement position 814 is “mandatory” or “optional” as the allowable condition item for the data specified by the data identification information 811 . The priority 843 stores the priority of the measurement position 814 in the permissible condition item for the data specified by the data identification information 811 .

For example, in FIG. 10, data whose data identification information 811 is "accident point __1010000121" can be input to the application only when the measurement position of the data provided for processing by the application matches the measurement position 413. , indicating that this condition is an essential condition. This condition also indicates that the condition has the second lowest priority (priority "3") after the allowable condition of the measurement position 814 among the other allowable condition items. Regarding whether or not the measurement position of the provided data matches the measurement position 413, for example, the data collection status determination unit 323 determines the measurement position 413 included in the record of the disaster collection data 341 and the provided data. The determination may be made by comparing the measured position of the data.

Temporal property 815 stores information about the temporal cycle of data that an application requests for the temporal property of data identified by data identification information 811 . Here, the temporal property indicates, for example, whether the data is a cycle of historical value, current value, or predicted value from the viewpoint of time. Note that the permissible condition 851 stores information about the permissible range of the temporal properties of the data identified by the data identification information 811. FIG. Required optional 852 stores information indicating whether the temporal property 815 is “essential” or “optional” as the permissible condition item for the data specified by the data identification information 811 . The priority 853 stores the priority of the temporal property 815 in the permissible condition item for the data specified by the data identification information 811 .

For example, in FIG. 10 , the data with the data identification information 811 of “accident point __1010000121” is sent to the application only when the temporal nature of the data provided for processing by the application matches the temporal nature 414 . It can be entered and indicates that this condition is an essential condition. This condition also indicates that the condition has the second highest priority (priority is "2") after the allowable condition of freshness 812 among the other allowable condition items. Regarding whether or not the temporal nature of the provided data matches the temporal nature 414, for example, the data collection status determination unit 323 determines whether the temporal nature 414 included in the record of the disaster collection data 341 and the above It may be determined by comparing the temporal properties of the provided data.

FIG. 11 is a diagram showing an example of a message format for providing data to applications in this system. The message format is, for example, the format of data provided by the disaster data collection middleware 301 to the recovery plan creation applications (302, 303). The notification providing unit 331 reads each table shown in FIGS. 6A to 6D and provides the application with data converted into the format shown below.

The main components of the message format are header information 901 , execution timing information 902 and data information 903 .

Header information 901 stores information necessary for transmitting and receiving the message. The main components are message identification information 911 , destination application information 912 , data count 913 and data size 914 .

The message identification information 911 stores information for identifying messages to be sent to applications. For the message identification information 911, for example, the notification providing unit 331 may assign a unique number when providing data.

Destination application information 912 stores information about the application that is the destination of the message identified by message identification information 911 . For the destination application information 912, for example, the notification providing unit 331 may read and set the destination of the application associated in advance with the recovery plan creation application (302, 303).

The number of data 913 stores information about the number of data included in the message specified by the message identification information 911 . The number of data 913 may be set by counting the number of records stored in the provided data list 344 by the notification providing unit 331, for example.

Data size 914 stores information about the total size of data included in the message identified by message identification information 911 . The data size 914 may be set by, for example, the notification providing unit 331 calculating the capacity of the data 445 stored in the provided data list 344, or the like.

The execution timing information 902 stores information about the execution timing to be presented to the application. The main components are executability 921 and execution waiting time 922 .

The executability 921 stores one of “executable”, “execution standby”, and “executable” as the execution timing of the application specified by the destination application information 912 . The executability 921 is, for example, set by the notification providing unit 331 by reading information stored in the executability (application 1) 428, the executability (application 2) 429, and the executability (application N) 420 of the area information 342. Just do it.

The execution waiting time 922 stores the waiting time until the application specified by the destination application information 912 can be executed only when the information stored in the executability 921 is "execution waiting". The execution standby time 922 may be set by, for example, the notification providing unit 331 receiving the execution standby time calculated in FIG.

The main components of the data information 903 are data 1, 2, and 3 (931, 932, and 933). Although three data are illustrated in this example, the number is arbitrary.

The main components of data 1, 2, 3 (931, 932, 933) are data identification information 941, data source information 942, status information 943, and data body 944.

The data identification information 941 stores information for identifying data (931, 932, 933). For the data identification information 941, for example, the notification providing unit 331 may assign a unique number when providing data.

The data source information 942 stores information about the data source that is the origin of the data specified by the data identification information 941 . The data source information 942 is obtained by, for example, the notification provision unit 331 identifying a record containing the same data identification information 431 as the data identification information 411 of the disaster collection data 341 from the data catalog table 343, It is sufficient to read and set the data source information 432 that is stored.

The status information 943 stores, as the status of the data specified by the data identification information 941, information on the degree of matching with the data allowance condition items (812, 813, 814, 815) specified by the application. For example, the notification providing unit 331 identifies a record including the same data identification information 441 as the data identification information 411 of the disaster collection data 341 from the provided data list 344, and the status information 943 is included in the identified record. The permissible condition matching status 442 may be read and set.

The data body 944 stores the data body specified by the data identification information 941 . For example, the notification providing unit 331 identifies a record including the same data identification information 441 as the data identification information 411 of the disaster collection data 341 from the provided data list 344, and the data body 944 is included in the identified record. The data 445 should be read and set.

Here, the concept of determining the execution start timing of an application in this system will be described.

12A to 12E are diagrams for explaining the concept of determining the execution start timing of an application in this system. 12A to 12E show an example of judging the execution timing of an application according to the situation in which a typhoon passes through an area.

FIG. 12A shows a situation in which typhoon T1 travels in the direction of course D1, passes through area 1201, and arrives at area 1202. FIG. In this case, as described in steps 506 and 509 in FIG. determines that the application is executable. For example, the execution timing determination unit 321 determines the execution timing of the application from the physical location of the area and the accident point, and the typhoon information 346 such as the position, speed, and direction. Unit 331 provides data to the application in the format shown in FIG.

FIG. 12B shows a situation in which typhoon T1 is proceeding in the direction of course D1, is passing through area 1201, and has not yet passed through the accident points (three points in this example) in area 1201. FIG. In this case, as described in steps 606 and 607 in FIG. 8, although the number of accident points equal to or greater than the predetermined threshold has not occurred in the area 1201, accident points have occurred in the course direction where the typhoon does not pass. there is In this case, the execution timing determination unit 321 advances without waiting for the typhoon to pass through the entire area 1201, and determines that the application can be executed at that time. Provide data to the application in the indicated format.

Also, in FIG. 12C, typhoon T1 is proceeding in the direction of course D1, is passing through area 1201, has passed through the accident points in area 1201 (five places in this example), and has not passed through one accident point. showing the situation. In this case, as described in steps 604 and 605 in FIG. Without waiting for the typhoon to pass through the entire 1201, it is determined that the application cannot be executed at that time, and the notification providing unit 331 notifies the application to that effect.

Also, in FIG. 12D, typhoon T1 is traveling in the direction of track D1 and is passing through area 1201, but the latest data has been acquired, and data acquisition in the next cycle will pass through area 1201 and arrive at area 1202. It shows the situation after In this case, as described in steps 705, 713, and 714 in FIG. The collection status determining unit 323 adds the data to the provided data list and determines that the application can be executed, and the notification providing unit 331 provides the data to the application in the format shown in FIG.

Also, in FIG. 12E, typhoon T1 moves in the direction of course D1, passes through area 1201 as shown in FIG. 12A, and arrives at area 1202. If the collected data is old and the latest data can be acquired in the next period, the data will be acquired in the next period. In this case, as explained in steps 705, 713, and 714 in FIG. 9, data is not provided to the application at that time, and the next update timing that arrives by the passing time of the typhoon is awaited. After that, the data collection status determination unit 323 adds the data to the provided data list, the execution timing determination unit 321 determines that the application can be executed, and the notification provision unit 331 outputs the application data in the format shown in FIG. provide data to

As described above, according to this embodiment, as described with reference to FIG. 7 and the like, a computer (for example, disaster data collection In the disaster data collection system for creating a recovery plan in the event of a disaster, performed by the server 101), distribution information including the location of the distribution system and/or equipment and the energized state of the distribution system and/or equipment (for example, the distribution information described using FIG. 4), a first processing unit (for example, the data collection unit 311) that collects data, and the location of the distribution system and/or equipment included in the data A second processing unit (for example, data collection unit 311) that calculates an area to be restored from a power failure state based on the power supply state, and the typhoon progress situation in the area obtained using weather information for the area; A third processing unit ( For example, it has an execution timing determination unit 321, an accident point state determination unit 322, and a data collection status determination unit 323). Therefore, when comprehending the damage situation in the event of a disaster such as a typhoon and creating a plan for the restoration and resumption of operation of the electric power system as an initial response, we collect data on the damage situation, The execution timing of the planning application for each area can be determined from the occurrence status of fault points in the system and the data collection implementation status compared with the data allowance condition items by the application. As a result, it is possible to guarantee the effectiveness of the plan created from the viewpoint of the input data and execute it as quickly as possible in the initial restoration after a disaster. .

In addition, as described in step 503 of FIG. 7 and the like, the second processing unit (for example, the data collection unit 311) preliminarily collects the distribution system and/or equipment and the relevant distribution system and / Or the area is calculated using the system profile information associated with the location of the facility. Therefore, the area can be calculated even for areas where the data is not collected.

Further, as described in steps 606, 607, etc. of FIG. and the above accident point occurs in the area where the typhoon has not yet passed, the above application can be executed using the above data collected in the area where the typhoon has already passed. It is determined that Therefore, even if an accident point occurs in the direction of travel in an area where a typhoon is passing, it will be possible to provide the application with rapidly collected data while maintaining a certain level of accuracy.

Also, as described in steps 705 absent, 708 absent, 712, etc. of FIG. is passing through the area and there is no update timing for the data until the typhoon passes through the area, it is determined that the application can be executed using the collected data. Therefore, when data collection is completed in an area through which a typhoon is passing, the collected data can be promptly provided to the application.

Also, as described in steps 705, 708, 713, 733, 734, etc. in FIG. If the typhoon is passing through and there is a next update timing for the above data until the typhoon passes through the above area, the above data collected at the next update timing will be used until the next update timing. After the waiting time has elapsed, it is determined that the application can be executed. Therefore, when a typhoon is passing through a certain area, it is possible to wait until the next update timing and provide updated data to the application.

Further, as described in steps 723, 733, 734, etc. of FIG. 9, the definition of the data includes at least the freshness of the data, the source of the data, the measurement position of the data, and the temporal nature of the data. Including, the third processing unit (for example, execution timing determination unit 321, data collection status determination unit 323), when the freshness of the data collected at the next update timing is a priority condition, After the waiting time has passed, it is determined that the application can be executed. Therefore, the freshness of the data is explicitly given higher priority than other items defined as data to be collected (for example, the source of the data, the measurement location of the data, the temporal nature of the data) Only if it is set will the data be available to the application. In this case, if the priority of the other items above is set higher than the freshness of the data above, the data will not be provided to the application. can be provided to the application.

Further, as explained in steps 509 to 514 and the like in FIG. 7, the third processing unit (for example, the execution timing determination unit 321 and the accident point state determination unit 322) If there is, and the distribution system and/or equipment at the point of the accident that occurred in the area has been restored, it is determined that the application can be executed using the collected data. Therefore, after the typhoon passes, if the power distribution system and facilities are restored, the collected data can be promptly provided to the application.

Also, as explained in steps 517-520 of FIG. 7, etc., the execution timing of the recovery plan creation application is notified, and based on the data definition of the recovery plan creation application and the data collected from the area, , and a fourth processing unit (for example, notification providing unit 331) that provides input data for the recovery plan creation application. Therefore, on the application side, it becomes possible to execute the application using the data collected according to the disaster situation at the timing according to the disaster situation.

Further, the fourth processing unit (for example, the notification providing unit 331) receives the input data in a predetermined format in which the information regarding the data capacity, the information regarding the execution timing of the application, and the data are associated with each other. Generate and provide the generated input data to the recovery plan creation application. Therefore, on the application side, it becomes possible to execute the application while taking into account the limitation of the data capacity. For example, when the amount of data exceeds a predetermined threshold value, the process can be executed after notifying the administrator of the possibility of overload.

101 disaster data collection server 102 power distribution automation system server 105, 106 base station server 107 consumer server 108, 109 other infrastructure system server 301 disaster data collection middleware 302, 303 recovery plan creation application 311 data collection unit 312 collection data management unit 313 Data catalog management unit 314 Application data definition management unit 315 Other system cooperation unit 321 Execution timing determination unit 322 Accident point state determination unit 323 Data collection status determination unit 331 Notification provision unit 332 Data communication unit 341 Disaster collected data 342 Area information 343 Data catalog 344 Data provision list 345 Application data definition 346 Typhoon information

Claims (11)

A disaster data collection system for creating a recovery plan in the event of a disaster, which is performed by a computer having a calculation unit and a storage unit,
a first processing unit for collecting data having distribution information including the location of a distribution system and/or equipment and the energized state of the distribution system and/or equipment;
a second processing unit that calculates an area to be restored from a power outage based on the location of the distribution system and/or equipment and the energized state included in the data;
Based on the progress of the typhoon in the area obtained using the weather information in the area, the occurrence status of the accident point indicating the location of the power outage in the area, and the collection status of the data including the power distribution information, a third processing unit that determines execution timing of the recovery plan creation application for the area;
A disaster data collection system characterized by comprising: The disaster data collection system according to claim 1,
The second processing unit calculates the area for which the data is not collected using system profile information in which the distribution system and/or equipment and the position of the distribution system and/or equipment are associated in advance. ,
A disaster data collection system characterized by: The disaster data collection system according to claim 1,
If the typhoon progress status in the area indicates that the typhoon is passing and the accident point occurs in a range in which the typhoon has not yet passed in the area, the third processing unit determines that the typhoon has passed in the area. Determining that the application can be executed using the data collected in the range of
A disaster data collection system characterized by: The disaster data collection system according to claim 1,
The third processing unit executes the application using the collected data when the progress of the typhoon in the area is passing and there is no update timing for the data until the typhoon passes through the area. determine that it is possible to
A disaster data collection system characterized by: The disaster data collection system according to claim 1,
When the typhoon progress status in the area is passing and there is a next update timing of the data until the typhoon passes through the area, the third processing unit updates the data collected at the next update timing. to determine that the application can be executed after the waiting time until the next update timing has elapsed,
A disaster data collection system characterized by: The disaster data collection system according to claim 5,
The definition of the data includes at least the freshness of the data, the source of the data, the measurement location of the data, and the temporal nature of the data;
When the freshness of the data collected at the next update timing is a priority condition, the third processing unit determines that the application can be executed after the waiting time has elapsed.
A disaster data collection system characterized by: The disaster data collection system according to claim 1,
The third processing unit, if the progress of the typhoon in the area has passed and the power distribution system and/or equipment at the accident point that occurred in the area has been restored, the collected data determining that the application can be executed using
A disaster data collection system characterized by: The disaster data collection system according to claim 1,
A fourth process of notifying execution timing of the recovery plan creation application and providing input data for the recovery plan creation application based on the data definition of the recovery plan creation application and the data collected from the area. part,
A disaster data collection system characterized by comprising: The disaster data collection system according to claim 8,
The fourth processing unit generates the input data in a predetermined format in which information about the size of the data, information about the execution timing of the application, and the data are associated with each other, and converts the generated input data to the provided to recovery planning applications,
A disaster data collection system characterized by: A disaster data collection method for creating a recovery plan in the event of a disaster, performed by a computer comprising a computing unit and a storage unit, comprising:
collecting data having distribution information including the location of the distribution system and/or equipment and the energized state of the distribution system and/or equipment;
calculating an area to be restored from a power outage based on the location of the distribution system and/or equipment and the energized state included in the data;
Based on the progress of the typhoon in the area obtained using the weather information in the area, the occurrence status of the accident point indicating the location of the power outage in the area, and the collection status of the data including the power distribution information, determining when to run a recovery planning application for the area;
A disaster data collection method characterized by: A computer comprising an arithmetic unit and a storage unit,
a process of collecting data having distribution information including the location of a distribution system and/or equipment and the energized state of the distribution system and/or equipment;
A process of calculating an area to be restored from a power failure state based on the location of the distribution system and/or equipment and the energized state included in the data;
Based on the progress of the typhoon in the area obtained using the weather information in the area, the occurrence status of the accident point indicating the location of the power outage in the area, and the collection status of the data including the power distribution information, a process of determining execution timing of a recovery plan creation application for an area;
A disaster data collection program characterized by executing

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