CN116633011B - Urban power distribution network-oriented power equipment fault influence analysis method - Google Patents

Urban power distribution network-oriented power equipment fault influence analysis method Download PDF

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CN116633011B
CN116633011B CN202310538313.1A CN202310538313A CN116633011B CN 116633011 B CN116633011 B CN 116633011B CN 202310538313 A CN202310538313 A CN 202310538313A CN 116633011 B CN116633011 B CN 116633011B
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equipment
vertex
dispatch
fault
power
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CN116633011A (en
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侯丽钢
王思怡
沈凌男
张雅舟
殷怀宇
陶雪
邵淋晶
沈人洁
李平文
陆天豪
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Nantong Power Supply Co Of State Grid Jiangsu Electric Power Co
Nantong Power Supply Co of State Grid Jiangsu Electric Power Co Ltd
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Nantong Power Supply Co Of State Grid Jiangsu Electric Power Co
Nantong Power Supply Co of State Grid Jiangsu Electric Power Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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    • H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
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Abstract

The invention discloses a power equipment fault influence analysis method for an urban power distribution network, which comprises the steps of acquiring operation state data of power distribution network equipment in an analysis target area from a power dispatching control system, acquiring equipment foundation management data of the power distribution network from a production management system, matching the two system data, constructing a unified fusion data model, generating a new electrical topology, analyzing the electrical topology of the power distribution network in a complete target area based on a connectivity analysis algorithm, searching corresponding peaks in the electrical topology according to marketing stop work orders or fault positioning key node data, judging by utilizing a topology traversal algorithm in combination with switch state information, and finally generating an equipment topology graph in combination with geographic information to provide decision support for an electric power fault management department. Compared with the existing topology method, the method reduces the number of edges and greatly improves the topology traversal efficiency.

Description

Urban power distribution network-oriented power equipment fault influence analysis method
Technical Field
The invention relates to the technical field of power equipment, in particular to an urban power distribution network-oriented power equipment fault influence analysis method.
Background
Today, the number of devices in urban distribution networks is large and the devices are very complex to communicate due to the dense distribution of the electrical loads in the cities. Therefore, the power equipment in the urban power distribution network fails, and huge analysis pressure is caused for fault investigation and fault influence condition judgment. In an urban power distribution network, taking a low-voltage residential power consumption area as an example, the phenomenon that cross-households occur in the low-voltage power consumption area in the urban power distribution network is very common, and usually the whole area is powered off, but a small number of power consumption clients still exist in the geographic range of the area. The method brings great challenges to the analysis of the influence of the power faults, but the current analysis of the power equipment faults of the urban power distribution network lacks effective technical means, and has the following problems: the traditional fault influence analysis takes fault positioning as a guide, analyzes where the source of the power failure is, guides a first-line worker to maintain, but lacks a global information report, needs a detailed fault analysis report, and gives out which devices in the power failure area are powered off and which devices are not powered off; in the existing urban power distribution network fault information acquisition, the fault condition is usually researched and judged by combining power dispatching information analysis feedback data and 95598 customer service repair feedback order data, and a unified fault information acquisition channel is lacked; the existing intelligent fault analysis method of the power distribution network is realized only by relying on electrical topology analysis; the condition that power supply areas are crossed frequently occurs in each power supply area in the urban power distribution network, and an electric power management department cannot accurately and effectively provide effective information support for other social management departments only by means of a traditional electric topological graph; real-time and historical operation data of each device of the power distribution network are recorded in the power dispatching control system, basic management data of the devices in the power distribution network, including power geographic information, are recorded in the power production management system, but at present, the two systems cannot be communicated, and more powerful support cannot be provided for device fault analysis in the power distribution network.
In order to solve the above problems, for example, chinese patent publication No. CN105139278B discloses a method for analyzing the influence of human factors on cascading failures of a power grid, which includes the following steps: 1. according to the current running state requirement of the power grid, analyzing the dispatching operation of a power grid dispatcher, and decomposing to obtain the included cognitive behaviors; 2. analyzing failure modes contained in the cognitive behaviors; 3. solving a probability basic value HEP of occurrence of artificial failure; 4. analyzing the operation task situation, and determining the level of the behavior influence factor to obtain a failure probability correction coefficient; 5. solving the artificial failure probability under the specific operation situation; 6. and taking the N-1 fault as an initial condition, and carrying out reliability evaluation on the system. The invention improves the running reliability of the power grid.
Another example is that chinese patent with publication number CN103473712a discloses a method for establishing a fault impact analysis table of a power distribution network, which is technically characterized in that: the method comprises the following steps: 1. analyzing the fault influence of the non-switching element according to the power distribution network code; 2. analyzing the fault influence of the switching element according to the power distribution network code; 3. and collecting the power failure conditions of all load points of the power distribution network after all the elements are failed, and uniformly storing the power failure conditions to form a power distribution network failure influence analysis table. The method is simple, convenient, quick and efficient, and can be applied to the reliability evaluation method of the power system, so that the quick reliability evaluation of the power system can be realized, and the method is used for guiding the construction and maintenance of the power system.
At present, the existing power equipment technology of the power distribution network has the following defects: both patents improve the reliability of the operation of the power grid to a certain extent, but do not combine the state information of electrical equipment, especially switch equipment, to comprehensively judge the fault condition of the circuit, and can not accurately acquire the fault data of the circuit in the power distribution network, and the power dispatching control system is not communicated with the power production management system, so that decision support can not be provided for the follow-up influence analysis of the high-order fault. The prior art remains to be improved.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an analysis method for the fault influence of power equipment facing an urban power distribution network, which aims to solve the problems.
In order to achieve the above purpose, the invention is realized by the following technical scheme: the utility model provides a power equipment fault influence analysis method towards urban distribution network, fuses electric topology, equipment running state and geographic information, carries out the analysis to the fault influence based on the graph topology traversal algorithm, obtains complete comprehensive fault analysis result, supports the power management decision, includes following steps:
s1, fusing data in a power dispatching control system and power production management, and then carrying out fault analysis according to a data fusion result to assist a power management decision by an analysis result;
s2: extracting and comparing the equipment types, the voltage levels and the number of the connecting terminals of all the equipment in the power dispatching control system and the power production management system, and taking the comparison result as a judgment whether the equipment descriptions in the two systems correspond to the same equipment or not;
s3: selecting a certain device in the power dispatching system, assuming that the device is 'dispatching system device 1', extracting the device type dispatch_type of the device from the attribute information of the device 1 Voltage class dispatch_voltage 1 Terminal number information dispatch_count 1 And acquires device type dispatch_type of all neighbor devices 'neighbor device 2', 'neighbor device 3' directly connected to the device 2 ,dispatch_type 3 Voltage class dispatch_voltage 2 ,dispatch_voltage 3 Terminal number information dispatch_count 2 ,dispatch_count 3 Comparing it with corresponding information of devices in the production management system, if there are k devices "production device 1, production device 2,..once, device type of production device k", voltage class, voltage, terminal number, and number of terminals satisfy:
for(i＝1；i<＝k；i++)
{
(dispatch_type 1 ＝manage_type i &dispatch_voltage 1 ＝manage_voltage i &dispatch_count 1 ＝manage_count i )
}
then the device's neighboring device is looked up if the three properties of the neighboring device 2, 3 connected to it also satisfy:
(dispatch_type 2 ＝manage_type 2 &dispatch_voltage 2 ＝manage_voltage 2 &dispatch_count 2 ＝manage_count 2 )
(dispatch_type 3 ＝manage_type 3 &dispatch_voltage 3 ＝manage_voltage 3 &dispatch_count 3 ＝manage_count 3 )
judging that the scheduling system equipment 1 and the production system equipment i are the same equipment, and successfully matching;
s4: for the devices which are not successfully matched, the address information of the devices is respectively extracted from the two systems, and the address of the dispatch system device 1 is defined as dispatch_address 1 The addresses of the k production devices in S3 are: [ message_address ] 1 ,manage_address 2 ,...,manage_address k ]；
S5: respectively calculating the similarity between k production equipment addresses and the addresses of the dispatching system equipment 1, wherein m is the address of the dispatching system equipment 1 1 The production system has n characters 1 The characters are compared in sequence character by character, and the same character quantity eq is counted 1 The similarity coefficients of the k production device addresses and the addresses of the dispatch system device 1 are then respectively:
s6: finding the device with the highest similarity coefficient from k devices as an associated target of the device, sim 1,j ＝max(sim 1,1 ,sim 1,2 ,...,sim 1,k )；
S7: the equipment in the two systems are correspondingly and correlatively combined according to the steps S1-S6, so that fusion of the data of the two systems is realized, and the fused data structure is shown in a table 3;
s8: generating a new electrical topological graph according to the fused data, as shown in fig. 3;
s9: setting a timing update program, reading a switch state from a power dispatching control system at fixed time, and assigning the latest switch state to the attribute of the edge;
s10: giving out the source of equipment failure according to the power failure information returned by the customer service system or the dispatching system, and searching for corresponding equipment nodes in the system;
s11: traversing from the equipment fault positioning root node, searching all subordinate equipment, traversing layer by adopting a depth-first traversing method, and obtaining the result shown in figure 4Defining a traversal result set fault_result, namely, vertex 1 Starting traversing, and converting vertex 1 Storing fault_result, and inquiring vertex 1 Is defined as all subsequent vertices of the graph;
s12: traversing the whole topological graph according to the traversing mode of the step S9 to finally obtain a traversing result fault_result;
s13: and generating a new topology from the traversing result, and pushing the topology to a fault analysis manager in the form of a geographical graph according to the geographical information attribute data of each device in the topology.
Further, in S1, a target area to be subjected to fault analysis is first selected, and equipment and topology related data corresponding to the target area are respectively extracted and stored in a graph database in a power dispatching control system and a power production management system.
Further, in S3, if the "dispatch system device 1" and the "production system device i" are the same device, all the successfully matched devices are taken out, and the rest are the devices which are not successfully matched.
Further, in S3, if the three attributes of the adjacent device 2 and the adjacent device 3 connected thereto do not satisfy the condition in S3, the process proceeds to step S4.
Further, in S6, the data of the production equipment system and the data of the dispatching system corresponding to the production equipment j and the dispatching system equipment 1 are respectively corresponding and associated;
further, in S8, the non-switching type device is defined as vertex, the switching type device is defined as side, and a new electrical topology is generated.
Further, in S8, the non-switching device 1 and the non-switching device 2 are connected by a wire, and there is a certain switching device, so in the corresponding new electrical topology diagram, the non-switching device 1 and the non-switching device 2 are two adjacent vertices, and the edge between the two vertices is the switch;
further, in S8, the attribute data properties of each vertex include a device number, a device type, a voltage class, and longitude and latitude coordinates; the attribute data of the edge includes a device number, a switch state, a voltage class, a device type, and a historical state set.
Further, step-by-step traversal in S11, vertex 1 Only one subsequent vertex 2 And vertex 1 And vertex 2 The connection switch between them is closed, thus the vertex 2 And storing fault_result.
Further, vertex in S11 2 After the fault_result is stored, the vertex is continuously traversed 1 Is traversed through the vertexes next to the vertex 3 ，vertex 2 And vertex 3 The connection switch of (2) is also closed, and the vertex is 3 Also fault_result is stored.
Further, in S11, vertex 3 After the fault_result is stored, the vertex is continuously traversed 3 Is followed by vertex of (2) 4 And vertex 10 But vertex 3 And vertex 4 The running state of the connecting edges between them is disconnected, thus giving up vertex 4 Continue traversing vertex 10 。
Compared with the prior art, the invention has the beneficial effects that: acquiring operation state data of power distribution network equipment in an analysis target area from a power dispatching control system, acquiring equipment foundation management data of the power distribution network from a production management system, matching the two system data, constructing a unified fusion data model, generating a new electric topology, analyzing the electric topology of the power distribution network in a complete target area based on a connectivity analysis algorithm, searching corresponding peaks in the electric topology graph according to marketing outage sheets or key node data of fault location, judging by utilizing a topology traversal algorithm and combining switch state information, acquiring basic management data and geographic information data of all equipment in a complete fault influence range, finally generating an equipment topology graph combining geographic information, and providing decision support for a power fault management department. Compared with the existing topology method, the method reduces the number of edges and greatly improves the topology traversal efficiency.
Drawings
FIG. 1 is a schematic diagram of analysis of distribution network faults by superimposing scheduling system and production management system data in an analysis method of power equipment fault influence for an urban distribution network;
FIG. 2 is a schematic diagram of a common attribute of equipment in scheduling control data and production management data in an analysis method for power equipment fault influence of an urban distribution network;
FIG. 3 is a schematic diagram of a description model of non-switching equipment and switching equipment data of an electric power equipment fault influence analysis method for an urban distribution network;
fig. 4 is a schematic diagram of a topology vertex-edge description model converted from a method for analyzing the fault influence of power equipment for an urban distribution network;
FIG. 5 is a schematic diagram of a result set of fault impact analysis of the method for analyzing the fault impact of power equipment for an urban power distribution network;
FIG. 6 is a flowchart of a method for analyzing the fault impact of power equipment on an urban distribution network;
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
The invention provides a technical scheme that: according to the method, power dispatching control system data and power production management data are fused, related data of corresponding target areas are extracted from the two systems according to fault analysis requirements, and then equipment data of the two systems are matched to construct a unified fusion data model. And then, constructing and generating a new electrical topology by taking the non-switching equipment as a vertex and the switching equipment as an edge according to the new data model, and superposing equipment running state data and equipment geographic information data. And then, judging by using a topology traversal algorithm and combining the switch state information to obtain the electrical topology of the fault influencing equipment. And finally, combining the geographic coordinate information to generate a complete electrical topology and geographic information diagram, and outputting a result. The implementation steps of the invention are as follows:
s1: as shown in fig. 1, the method fuses data in a power dispatching control system and power production management, and then performs fault analysis according to a data fusion result, and the analysis result assists in power management decision. Therefore, a target area to be subjected to fault analysis is first selected, and equipment and topology related data corresponding to the target area are respectively extracted and stored in a graph database in a power dispatching control system and a power production management system.
Table 1 power schedule control data summary table
Device numbering Device name Device type Voltage class Terminal set Operating state Historical state set Others
D_no 1 D_name 1 Type1 Vol_lv 1 Intf 1 Status 1 His 1 ...
D_no 2 D_name 2 Type2 Vol_lv 2 Intf 2 Status 2 His 2 ...
D_no 3 D_name 3 Type3 Vol_lv 3 Intf 3 Status 3 His 3 ...
D_no 4 D_name 4 Type4 Vol_lv 4 Intf 4 Status 4 His 4 ...
D_no 5 D_name 5 Type5 Vol_lv 5 Intf 5 Status 5 His 5 ...
D_no 6 D_name 6 Type6 Vol_lv 6 Intf 6 Status 6 His 6 ...
D_no 7 D_name 7 Type7 Vol_lv 7 Intf 7 Status 7 His 7 ...
D_no 8 D_name 8 Type8 Vol_lv 8 Intf 8 Status 8 His 8 ...
D_no 9 D_name 9 Type9 Vol_lv 9 Intf 9 Status 9 His 9 ...
D_no 10 D_name 10 Type10 Vol_lv 10 Intf 10 Status 10 His 10 ...
... ... ... ... ... ... ... ...
Table 2 power production management data summary table
S2: tables 1 and 2 are device description field information summaries in the power dispatch control system and the power production management system, but although devices of both systems have device numbers, association cannot be directly made by the device numbers due to the difference in device number rules between data in both systems. But the basic device description is identical for the same device, e.g. the device type, voltage class, number of connection terminals, etc. Therefore, the method extracts and compares the equipment types, the voltage levels and the number of the connecting terminals of all the equipment in the two systems, and uses the comparison result as a judgment whether the equipment descriptions in the two systems correspond to the same equipment.
S3: as shown in fig. 2, a certain device in the power dispatching system is selected, assuming that the device is "dispatching system device 1", and the device type dispatch_type of the device is extracted from the attribute information of the device 1 Voltage class dispatch_voltage 1 Terminal number information dispatch_count 1 And acquires device type dispatch_type of all "adjacent device 2", "adjacent device 3" directly connected to the device 2 ,dispatch_type 3 Voltage class dispatch_voltage 2 ,dispatch_voltage 3 Terminal number information dispatch_count 2 ,dispatch_count 3 Comparing it with corresponding information of devices in the production management system, if there are k devices "production device 1, production device 2,..once, device type of production device k", voltage class, voltage, terminal number, and number of terminals satisfy:
for(i＝1；i<＝k；i++)
{
(dispatch_type 1 ＝manage_type i &dispatch_voltage 1 ＝manage_voltage i &dispatch_count 1 ＝manage_count i )
}
then the device's neighboring device is looked up if the three properties of the neighboring device 2, 3 connected to it also satisfy:
(dispatch_type 2 ＝manage-type 2 &dispatch-voltage 2 ＝manage_voltage 2 &dispatch_count 2 ＝manage_count 2 )
(dispatch_type 3 ＝manage-type a &dispatch_voltage 3 ＝manage_voltage 3 &dispatch_count 3 ＝manage_count 3 )
then it is determined that both ("dispatch system device 1" and "production system device i") are the same device. And taking out all the successfully matched devices, and the rest are the devices which are not successfully matched. If the three properties of the adjacent device 2, 3 connected thereto do not meet the above conditions, step S4 is entered.
S4: for the devices which are not successfully matched, the address information of the devices is respectively extracted from the two systems, and the address of the dispatch system device 1 is defined as dispatch_address 1 The addresses of the k production devices in S3 are: [ message_address ] 1 ，manage_address 2 ，...，manage_address k ]。
S5: respectively calculating the similarity between k production equipment addresses and the addresses of the dispatching system equipment 1, wherein m is the address of the dispatching system equipment 1 1 The production system has n characters 1 The characters are compared in sequence character by character, and the same character quantity eq is counted 1 The similarity coefficients of the k production device addresses and the addresses of the dispatch system device 1 are then respectively:
s6: finding the device with the highest similarity coefficient from k devices as an associated target of the device, sim 1,j ＝max(sim 1，1 ，sim 1,2 ，...，sim 1,k ) The production equipment j and the scheduling system equipment 1 are associated with each other by associating data of the production equipment system and data of the scheduling system.
S7: and (2) corresponding and associating the equipment in the two systems according to the steps S1-S6, so as to realize the fusion of the data of the two systems. The fused data structure is shown in table 3.
TABLE 3 fused device data
New device numbering Operating state Device type Voltage class Terminal set Geographic information Historical state set Others
D_no 1 Status 1 Type1 Vol_lv 1 Intf 1 Geo 1 His 1 …
D_no 2 Status 2 Type2 Vol_lv 2 Intf 2 Geo 2 His 2 …
D_no 3 Status 3 Type3 Vol_lv 3 Intf 3 Geo 3 His 3 …
D_no 4 Status 4 Type4 Vol_lv 4 Intf 4 Geo 4 His 4 …
D_no 5 Status 5 Type5 Vol_lv 5 Intf 5 Geo 5 His 5 …
D_no 6 Status 6 Type6 Vol_lv 6 Intf 6 Geo 6 His 6 …
D_no 7 Status 7 Type7 Vol_lv 7 Intf 7 Geo 7 His 7 …
D_no 8 Status 8 Type8 Vol_lv 8 Intf 8 Geo 8 His 8 …
D_no 9 Status 9 Type9 Vol_lv 9 Intf 9 Geo 9 His 9 …
D_no 10 Status 10 Type10 Vol_lv 10 Intf 10 Geo 10 His 10 …
… … … … … … … …
S8: according to the fused data, a new electrical topology is generated, non-switch type equipment is defined as vertex, switch type equipment is defined as side, and a new electrical topology diagram is generated, as shown in fig. 3. For example, the non-switching device 1 and the non-switching device 2 are connected by a certain switching device in addition to the wires, and in the corresponding new electrical topology, the non-switching device 1 and the non-switching device 2 are two adjacent vertexes, and the edge between the two vertexes is the switch. The attribute data Property of each vertex comprises a device number, a device type, a voltage level, longitude and latitude coordinates and the like; the attribute data of the edge is a device number, a switch state, a voltage level, a device type, a historical state set, and the like.
S9: setting a timing update program, reading the switch state from the power dispatching control system at fixed time, and assigning the latest switch state to the attribute of the edge.
S10: and giving out the source of equipment failure according to the power failure information returned by the customer service system or the dispatching system, and searching for the corresponding equipment node in the system.
S11: traversing from the equipment fault positioning root node, searching all the subordinate equipment, and traversing layer by adopting a depth-first traversing method, as shown in fig. 4. Defining a traversal result set fault_result from vertex 1 Starting traversing, and converting vertex 1 Storing fault_result, and inquiring vertex 1 Is a vertex 1 Only one subsequent vertex 2 And vertex 1 And vertex 2 The connection switch between them is closed, thus the vertex 2 And storing fault_result. Continue traversing vertex 1 Is traversed through the vertexes next to the vertex 3 ，vertex 2 And vertex 3 The connection switch of (2) is also closed, and the vertex is 3 Also stores fault_result, and continues traversing the vertex 3 Is followed by vertex of (2) 4 And vertex 10 But vertex 3 And vertex 4 The running state of the connecting edges between them is disconnected, thus giving up vertex 4 Continue traversing vertex 10 。
S12: and traversing the whole topological graph according to the traversing mode of the step S9, and finally obtaining a traversing result fault_result.
S13: and generating a new topology from the traversing result, and pushing the topology to a fault analysis manager in the form of a geographical graph according to the geographical information attribute data of each device in the topology.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.

Claims (10)

1. A power equipment fault influence analysis method for an urban power distribution network is characterized by comprising the following steps of: the electrical topology, the equipment running state and the geographic information are fused, the fault influence is analyzed based on a graph topology traversal algorithm, a complete and comprehensive fault analysis result is obtained, and the power management decision is supported, and the method comprises the following steps:
s1, fusing data in a power dispatching control system and power production management, and then carrying out fault analysis according to a data fusion result to assist a power management decision by an analysis result;
s2: extracting and comparing the equipment types, the voltage levels and the number of the connecting terminals of all the equipment in the power dispatching control system and the power production management system, and taking the comparison result as a judgment whether the equipment descriptions in the two systems correspond to the same equipment or not;
s3: selecting a certain device in the power dispatching system, assuming that the device is 'dispatching system device 1', extracting the device type dispatch_type of the device from the attribute information of the device 1 Voltage class dispatch_voltage 1 Terminal number information dispatch_count 1 And acquires device type dispatch_type of all "adjacent device 2", "adjacent device 3" directly connected to the device 2 ,dispatch_type 3 Voltage class dispatch_voltage 2 ,dispatch_voltage 3 Terminal number information dispatch_count 2 ,dispatch_count 3 Comparing it with corresponding information of devices in the production management system, if there are k devices "production device 1, production device 2,..once, device type of production device k", voltage class, voltage, terminal number, and number of terminals satisfy:
for(i＝1；i<＝k；i++)
{
(dispatch_type 1 ＝manage_type i &dispatch_voltage 1 ＝manage_voltage i &dispatch_count 1 ＝manage_count i )
}
then the device's neighboring device is looked up if the three properties of the neighboring device 2, 3 connected to it also satisfy:
(dispatch_type 2 ＝manage_type 2 &dispatch_voltage 2 ＝manage_voltage 2 &dispatch_count 2 ＝manage_count 2 )
(dispatch_type 3 ＝manage_type 3 &dispatch_voltage 3 ＝manage_voltage 3 &dispatch_count 3 ＝manage_count 3 )
judging that the scheduling system equipment 1 and the production system equipment i are the same equipment, taking out all successfully matched equipment, and the rest equipment which is not successfully matched;
s4: for the devices which are not successfully matched, the address information of the devices is respectively extracted from the two systems, and the address of the dispatch system device 1 is defined as dispatch_address 1 The addresses of the k production devices in S3 are: [ message_address ] 1 ,manage_address 2 ,...,manage_address k ]；
S5: respectively calculating the similarity between k production equipment addresses and the addresses of the dispatching system equipment 1, wherein m is the address of the dispatching system equipment 1 1 The production system has n characters 1 The characters are compared in sequence character by character, and the same character quantity eq is counted 1 The similarity coefficients of the k production device addresses and the addresses of the dispatch system device 1 are then respectively:
s6: from k devicesFinding the device with the highest similarity coefficient as the associated target of the device, sim 1,j ＝max(sim 1,1 ,sim 1,2 ,...,sim 1,k )；
S7: the equipment in the two systems are corresponding and associated according to the steps S1-S6, so that fusion of the data of the two systems is realized;
s8: generating a new electrical topological graph according to the fused data;
s9: setting a timing update program, reading a switch state from a power dispatching control system at fixed time, and assigning the latest switch state to the attribute of the edge;
s10: giving out the source of equipment failure according to the power failure information returned by the customer service system or the dispatching system, and searching for corresponding equipment nodes in the system;
s11: traversing from the equipment fault positioning root node, searching all subordinate equipment, traversing layer by adopting a depth-first traversing method, defining a traversing result set fault_result, and traversing from vertex 1 Starting traversing, and converting vertex 1 Storing fault_result, and inquiring vertex 1 Is defined as all subsequent vertices of the graph;
s12: traversing the whole topological graph according to the traversing mode of S9 to finally obtain a traversing result fault_result;
s13: and generating a new topology from the traversing result, and pushing the topology to a fault analysis manager in the form of a geographical graph according to the geographical information attribute data of each device in the topology.
2. The urban power distribution network-oriented power equipment fault impact analysis method according to claim 1, wherein the method comprises the following steps of: in S1, a target area to be subjected to fault analysis is firstly selected, and equipment and topology related data corresponding to the target area are respectively extracted in a power dispatching control system and a power production management system and stored in a graph database.
3. The urban power distribution network-oriented power equipment fault impact analysis method according to claim 2, wherein the method comprises the following steps of: if the three attributes of the adjacent device 2 and the adjacent device 3 connected with the condition in S3 are not satisfied in S3, the process proceeds to step S4.
4. A method for analyzing the fault impact of power equipment on an urban distribution network according to claim 3, characterized in that: in S6, the production facility j and the scheduling system facility 1 correspond to and correlate the data of the production facility system and the data of the scheduling system, respectively.
5. The urban power distribution network-oriented power equipment fault impact analysis method according to claim 4, wherein the method comprises the following steps of: and S8, defining non-switching type equipment as vertex, defining switching type equipment as side, and generating a new electric topological graph.
6. The urban power distribution network-oriented power equipment fault impact analysis method according to claim 5, wherein the method comprises the following steps of: in S8, the non-switching device 1 and the non-switching device 2 are connected by a wire, and there is a certain switching device, so in the corresponding new electrical topology diagram, the non-switching device 1 and the non-switching device 2 are two adjacent vertexes, and the edge between the two vertexes is the switch.
7. The urban power distribution network-oriented power equipment fault impact analysis method according to claim 6, wherein the method comprises the following steps of: s8, the attribute data Property of each vertex is provided with a device number, a device type, a voltage level and longitude and latitude coordinates; the attribute data of the edge includes a device number, a switch state, a voltage class, a device type, and a historical state set.
8. The urban power distribution network-oriented power equipment fault impact analysis method according to claim 7, wherein the method comprises the following steps of: layer-by-layer traversal in S11, vertex 1 Only one subsequent vertex 2 And vertex 1 And vertex 2 The connection switch between them is closed, thus the vertex vertex 2 And storing fault_result.
9. The urban power distribution network-oriented power equipment fault impact analysis method according to claim 8, wherein the method comprises the following steps of: vertex in S11 2 After the fault_result is stored, the vertex is continuously traversed 1 Is traversed through the vertexes next to the vertex 3 ，vertex 2 And vertex 3 The connection switch of (2) is also closed, and the vertex is 3 Also fault_result is stored.
10. The urban power distribution network-oriented power equipment fault impact analysis method according to claim 9, wherein the method comprises the following steps of: in S11, vertex 3 After the fault_result is stored, the vertex is continuously traversed 3 Is followed by vertex of (2) 4 And vertex 10 But vertex 3 And vertex 4 The running state of the connecting edges between them is disconnected, thus giving up vertex 4 Continue traversing vertex 10 。
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