CN115841221A - Emergency aid decision-making system based on intranet - Google Patents
Emergency aid decision-making system based on intranet Download PDFInfo
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Abstract
The invention relates to the technical field of emergency repair, and provides an emergency aid decision-making system based on an intranet. The system comprises: the emergency repair system comprises a fault identification module, a topological relation module, an emergency repair guidance module and an emergency command module, wherein the fault identification module is used for acquiring fault identification information by utilizing a forward reasoning algorithm and a reverse reasoning algorithm according to original fault data; the topological relation module is used for constructing a power network topological relation graph after equipment failure based on a GIS database vectorized electrical wiring graph; the emergency repair guidance module is used for determining the emergency repair sequence of the fault points and selecting a target emergency repair line by combining the relevant data of the fault points; and the emergency command module is used for carrying out desensitization and encryption processing on data in the target emergency repair line and sharing the data to an external network. The invention realizes automatic fault identification, obtains data communication internal and external network data sharing, and improves the first-aid repair efficiency.
Description
Technical Field
The invention relates to the technical field of emergency repair, in particular to an emergency aid decision-making system based on an intranet.
Background
In recent years, a large-area power supply interruption and a serious damage to an electric power infrastructure have occurred due to natural disasters. If the ice-covered galloping tripping fault of a plurality of lines is caused by a freezing rain and snowstorm disaster, large-range power failure is caused; flood disasters cause damage to cable lines, transformers, towers and switches to different degrees. The reliability of the power grid is improved, the safe and stable operation of the power grid is guaranteed, the damage of natural disasters to the power grid is reduced, and the emergency treatment capability of the power grid is improved. At present, the management of emergency sites has certain limitation, and the application of the emergency site is limited when large-area power failure accidents caused by disasters are processed. In the traditional emergency repair work, the ideal working efficiency and precision are difficult to achieve by virtue of the experience of managers and workers.
The current emergency management system has some limitations: firstly, under the condition of large-scale power failure caused by disaster, data transmission can not be carried out through a public network, and an original monitoring system fails to accurately identify and locate faults; secondly, when the emergency repair team goes out to carry out the emergency repair task, important information related to an intranet cannot be obtained, such as load data, line data and the like, sensitive data related to a power grid cannot be shared by the intranet and the intranet, and the development of the emergency repair task is completely dependent on the experience of workers; and thirdly, no intelligent first-aid repair scheme is implemented.
Disclosure of Invention
In view of this, the invention provides an emergency aid decision-making system based on an intranet, so as to solve the technical problem that in the prior art, ideal working efficiency and accuracy cannot be achieved by virtue of experiences of managers and workers.
The invention provides an emergency aid decision-making system based on an intranet, which comprises:
a fault identification module, a topological relation module, an emergency repair guidance module and an emergency command module,
the fault identification module acquires fault identification information by utilizing a forward reasoning algorithm and a reverse reasoning algorithm according to original fault data;
the topological relation module is used for constructing a power network topological relation graph after a fault based on a GIS database vectorized electrical wiring graph, and reading a vector relation of loads in the power network topological relation graph;
the emergency repair guidance module determines an emergency repair sequence of fault points by using a vector relation of loads in the power network topological relation diagram and combining relevant data of the fault points through a topological relation module to form an emergency repair scheme, and obtains a decision of transporting emergency repair materials to the fault points through a target loss value caused by material scheduling delay based on the emergency repair scheme, and selects a target emergency repair line; the relevant data of the fault point comprise the importance degree of the power-losing load, the position information of the fault point, the distance from the emergency maintenance team to the fault point and materials required by emergency maintenance of the fault point;
and the emergency command module is connected with the emergency repair guidance module and the fault identification module through the topological relation module, desensitizes and encrypts data in the target emergency repair line, and shares the processed data to an external network.
Further, the fault identification module includes: a fault interface unit, a load interface unit, a system diagram interface unit,
the fault interface unit is used for acquiring original fault data;
the load interface unit is used for extracting fault information in the original fault data, wherein the fault information comprises the load grade and the load power of a load affected by equipment faults;
and the system diagram interface unit is used for generating fault identification information by using the fault information in the original fault data.
Further, the topological relation module comprises a quantization level unit and a constraint condition unit,
the quantization level unit is used for dividing the load into different levels according to different types of the load and determining a target level function according to the levels;
the constraint condition unit is used for constraining the loop quantity and the power limit in the topological relation graph of the power network based on an objective level function.
Further, the objective level function includes the following expression:
wherein λ is i Representing the load importance level associated with the failed node i;
represents the sum of the loads of the nodes i;
the loop number in the power network topological relation graph comprises the following expressions:
L＝0
wherein, L is the loop number in the topological relation graph of the power network;
the power limit includes the following expression:
S l ≤S lmax
S l is the power flowing on the tie line; s. the lmax Is the power limit of the tie line.
Further, the emergency repair guidance module comprises a dispatching path unit and an emergency repair fault unit,
the dispatching path unit is used for determining the emergency repair sequence of the fault points by utilizing the vector relation of the loads in the topological relation graph of the power network and combining the relevant data of the fault points to form an emergency repair scheme;
and the emergency repair fault unit is used for obtaining a decision of emergency repair material transportation to a fault point through a target loss value caused by material scheduling delay based on the emergency repair scheme and selecting a target path.
Further, the target loss value is obtained based on a target loss function, and the calculation of the target loss function includes the following expression:
F＝min∑(t il +t ir )
wherein, t il The distance time from the fault point i to the fault point i +1 is the first-aid repair team; t is t ir The repair time is the failure point i.
Further, the target pathway is selected by ant colony algorithm in combination with pheromone concentration.
Furthermore, the emergency command module is used for specifying sensitive data in the power data through manual specification and automatic identification technologies, desensitizing encryption is carried out on the sensitive data through a desensitization correlation algorithm, and then communication of internal and external network data is achieved through an SQL proxy isolation device technology, wherein the desensitization correlation algorithm comprises k-anonymity, L diversity, data suppression, data disturbance and differential privacy.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the invention, through intelligently identifying important information in the fault alarm system and carrying out extraction and analysis, manual identification is replaced, automatic fault identification is realized, and fault information is provided for the emergency aid decision-making system.
2. According to the invention, the traditional electrical wiring diagram is converted into a network topological diagram and combined with GIS data, so that the electrical primary wiring diagram is simplified, and the fault position and fault point data are more intuitively known.
3. The invention establishes an emergency repair model, integrates the factors such as load grade, road conditions, materials and the like, adopts the particle swarm algorithm, seeks an optimal emergency repair scheme, replaces the original emergency repair scheme obtained by artificial experience, and leads the emergency repair work to be carried out more scientifically and efficiently.
4. According to the emergency repair scheme formed based on the intranet data and the method for sharing the relevant data of the fault point and the extranet, data communication is achieved on the premise that data safety is guaranteed, and repair efficiency is improved.
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In order to more clearly illustrate the technical solutions of the present invention, the drawings used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a block diagram of an emergency aid decision-making system based on an intranet according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a principle of an emergency aid decision-making system based on an intranet according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
An emergency aid decision system based on an intranet according to the present invention will be described in detail with reference to the accompanying drawings.
Fig. 1 is a block diagram of an emergency aid decision system based on an intranet according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a principle of an emergency aid decision-making system based on an intranet according to an embodiment of the present invention.
As shown in fig. 1, the system includes:
a fault identification module, a topological relation module, an emergency repair guidance module and an emergency command module,
the fault identification module acquires fault identification information by utilizing a forward reasoning algorithm and a reverse reasoning algorithm according to original fault data;
the fault information of the power grid has the characteristics of layering, redundancy, non-standardization and non-timeliness, the fault identification information is obtained from a large amount of text information by using an artificial intelligence technology, the equipment fault information characteristic words are extracted, the equipment fault type is further identified, and a basis is provided for auxiliary decision making. And based on the equipment fault association + words, performing association analysis on the equipment fault information characteristic words by using an optimized association analysis algorithm, extracting an equipment association failure rule, and establishing an equipment association failure model. Based on the equipment association failure model, a fault identification method based on the fuzzy fault petri net is provided by utilizing a petri net theory, a fault petri net, a fuzzy petri net theory and a fuzzy inference rule, the fuzzy fault petri net fault identification model of the system is constructed by combining the association failure model, intelligent inference on fault propagation is obtained by utilizing a forward inference algorithm and a reverse inference algorithm, and fault identification information is obtained quickly and accurately.
The fault identification module includes: a fault interface unit, a load interface unit, a system diagram interface unit,
the fault interface unit is used for acquiring original fault data;
the load interface unit is used for extracting fault information in the original fault data, wherein the fault information comprises the load grade and the load power of a load affected by equipment faults;
based on the audit relationship between the electrical components and the loads, all possibly affected loads are quickly identified, and the visualization is realized in a multi-dimensional mode. The load curve generally changes periodically, and the type and the generation reason of load data of power abnormity are analyzed by analyzing the periodicity presented by the conventional load curve. And (3) utilizing the relation between the load power data of the selected sample and the expected output by data mining, analyzing the load data based on PFCM clustering, and extracting the relevant data information of the fault point in the fault identification information.
And the system diagram interface unit is used for generating fault identification information by using the fault information in the original fault data.
Specifically, various devices such as a generator, a load feeder, a transformer, a transmission line and the like are connected into a power grid according to the switch state, a plurality of subsystems which are mutually isolated are formed and identified, and a charged subsystem and a stopped subsystem are identified according to whether the subsystems are injected with power supply or not. The fault area is necessarily in the live subsystem before the fault, and is necessarily in the power failure subsystem after the fault, namely, the newly-added power failure subsystem. And obtaining a fault area according to the difference of the topology analysis results before and after the fault.
The topological relation module is used for constructing a power network topological relation graph after a fault based on a GIS database vectorized electrical wiring graph, and reading a vector relation of loads in the power network topological relation graph;
and the vector relation of important loads in the electrical wiring diagram is read, and a GIS database-based vectorized power network topological diagram is constructed. After an emergency happens, corresponding fault information is displayed on a fault element wiring diagram interface, the emergency repair sequence of each area is determined according to the influence level of the load, and required material allocation, vehicle allocation and personnel allocation data are mapped to a GIS platform and displayed in an icon mode.
And establishing a GIS related retrieval mode, and automatically retrieving the electrical wiring diagram of the fault element based on the GIS geographic position information data and the electrical wiring diagram. And constructing the electrical wiring diagram by using the geographic position information data acquired by the interface. And converting the known power system network shown by the electrical wiring diagram into a topological network structure which can be identified by a computer. The electric power topological structure analysis is to analyze and judge the connection structure of the electric network according to the primary connection relation and the switch state of the electric power elements of the electric network.
The related retrieval mode comprises geographic position information data and electric element information.
Wherein, GIS intelligence route formation step includes:
and reading the fault information acquired by the fault module and a subsystem model obtained by analyzing the system diagram to form a power grid topology structure diagram and load grade information after the fault. The GIS system contains geographical position information, and the distance time is estimated according to the distance between the nodes and the road condition. And materials required for rush repair of the fault point can be known from the fault information of the equipment. When the actual repair task was carried out, salvageed the team and sent out from the dispatch point, carried a quantitative salvage goods and materials, followed certain route and visited the node of damage one by one, used the salvage goods and materials that carry, like cable, equipment replacement spare part and reinforcement etc. maintain damage user and node, go to next damage point after the maintenance was accomplished. If the first-aid repair materials are used up, the first-aid repair materials are supplied to material supply points, and then the first-aid repair materials are continuously supplied to the next damaged point until all the damaged points are repaired. After the fault point to be rush-repaired is coded, calculating and planning a rush-repair line and calculating rush-repair time according to the method, performing optimization solution by using a particle swarm algorithm, and finally generating the target rush-repair line.
The analysis of the power network topological relation diagram comprises the following steps:
(1) Reading the primary wiring diagram data and reorganizing the primary wiring diagram data into a topological structure;
the primary wiring diagram comprises complex information such as a main wiring form, a voltage grade, a power plant, a transformer substation, a switch and the like, and is not beneficial to problem analysis, so that the primary wiring diagram is simplified and reorganized into the power network topological relation diagram. The distribution network is a topological network formed by connecting various electrical devices by transmission lines and connecting nodes by branches.
(2) According to the connection relation between the interconnection lines between the stations or the connection relation between the transformer and the nodes in the stations, carrying out network connection analysis on the node-branch model, and dividing the regional power grid into a plurality of subsystems to form a subsystem model;
after a disaster occurs, faults of a transformer substation, a line, a tower and the like may occur, so that the topological structure of the power grid changes, and the information of the power loss node and the power loss branch is obtained through fault module data, so as to obtain the power network topological relation diagram after the faults occur. Due to a fault causing a loss of power to the line, the complete regional power grid is split into several subsystems.
Wherein, other power sources comprise a distributed power source and an emergency power supply vehicle.
(3) And dividing a subsystem model according to the connection relation between the plant stations, and positioning a fault area.
In emergency, other power supplies except a power plant supply power in a small range, the activity of each subsystem is judged according to the position of the power supply and the connectivity among the subsystems, elements of the passive subsystem are classified into a power failure element set, and the area is a fault area. And a load data processing step: the loads are classified according to different requirements of different loads on power supply reliability, each power loss node is weighted, and the higher the numerical value is, the higher the load grade is, and the higher the requirement on the power supply reliability is.
The topological relation module comprises a quantization level unit and a constraint condition unit,
the quantization level unit is used for dividing the load into different levels according to different types of the load and determining a target level function according to the levels;
and the constraint condition unit is used for constraining the loop quantity and the power limit in the topological relation diagram of the power network based on an objective level function.
The objective level function includes the following expression:
wherein λ is i Representing the load importance level associated with the failed node i;
represents the sum of the loads of the nodes i;
the loop number in the power network topological relation graph comprises the following expressions:
L＝0
wherein, L is the loop number in the topological relation graph of the power network;
the power limit includes the following expression:
S l ≤S lmax
S l is the power flowing on the tie line; s lmax Is the power limit of the tie line.
The emergency repair guidance module determines the emergency repair sequence of the fault points by using the vector relation of the loads in the power network topological relation diagram and combining the relevant data of the fault points through the topological relation module to form an emergency repair scheme, and obtains a decision of transporting emergency repair materials to the fault points through a target loss value caused by material scheduling delay based on the emergency repair scheme, and selects a target emergency repair line; the relevant data of the fault point comprise the importance degree of the power-losing load, the position information of the fault point, the distance from the emergency maintenance team to the fault point and materials required by emergency maintenance of the fault point;
the emergency assistant decision needs to plan a load transfer route and provides a scientific basis for making an emergency repair plan. When the system recommends to form an emergency repair route, path selection is involved, the shortest path is considered according to the obtained electrical fault information, load data and information in the GIS system, and meanwhile, the influence of load priority is also considered, a target emergency repair line is finally formed, and the target emergency repair line is used for an emergency repair decision maker to refer to so as to improve emergency repair efficiency.
Salvage guide module includes: a dispatch path unit and a repair failure unit,
the dispatching path unit is used for determining the emergency repair sequence of the fault points by utilizing the vector relation of the loads in the topological relation graph of the power network and combining the relevant data of the fault points to form an emergency repair scheme;
and quantifying the importance level of the fault point by combining indexes such as line data, load loss severity of the line and the like, establishing a fault recovery priority model, and further determining the emergency repair sequence of the fault point. Meanwhile, the expected time of material transportation is calculated based on a three-point estimation method, and an optimal scheduling path, namely a target emergency repair line, is found by using a Dixtera algorithm. And finally, based on an effectiveness theory method, considering the priority factor of fault recovery, and providing the consequence severity of material scheduling delay.
And the emergency repair fault unit is used for obtaining a decision of transporting emergency repair materials to a fault point through a target loss value caused by material scheduling delay based on the emergency repair scheme and selecting a target path.
Based on the first-aid repair scheme, an electric power emergency material scheduling model is established by taking the minimum comprehensive loss value caused by material scheduling delay as a target, and a proper algorithm is adopted for solving, so that the decision of which material warehouse transports which quantity of material to which fault point via which path is realized, the main power grid is enabled to recover operation and the important user recovers power supply as soon as possible, and the power failure loss is reduced to the maximum extent.
The target loss value is obtained based on a target loss function, and the calculation of the target loss function includes the following expression:
F＝min∑(t il +t ir )
wherein, t il The distance time from the fault point i to the fault point i +1 is the first-aid repair team; t is t ir The repair time is the failure point i.
The target pathway is selected by an ant colony algorithm in combination with pheromone concentration.
And the emergency command module is connected with the emergency repair guidance module and the fault identification module through the topological relation module, desensitizes and encrypts data in the target emergency repair line, and shares the processed data to an external network.
The emergency command module is used for appointing sensitive data in the electric power data through manual appointing and automatic identification technologies, desensitizing encryption is carried out on the sensitive data through a desensitizing correlation algorithm, and then communication between the internal network data and the external network data is achieved through the SQL agent isolation device technology.
The desensitization correlation algorithm comprises k-anonymity, L diversity, data suppression, data disturbance and differential privacy.
And constructing a secure channel between the SG-JDBC driver and the isolation device based on an encryption communication protocol to realize database proxy access.
The SQL proxy isolation device is deployed at the network boundary of the internal network and the external network, only necessary service data between the internal network and the external network are allowed to interact in a controllable database communication mode, and any connection between an internal network host and the internet is cut off.
According to the invention, through intelligently identifying important information in the fault alarm system and carrying out extraction and analysis, manual identification is replaced, automatic fault identification is realized, and fault information is provided for an emergency aid decision-making system; the traditional electrical wiring diagram is converted into a network topological diagram and combined with GIS data, so that the electrical primary wiring diagram is simplified, and the fault position and fault point data are more intuitively known; by establishing an emergency repair model, integrating factors such as load grade, road conditions, materials and the like, adopting a particle swarm algorithm, obtaining an optimal emergency repair scheme, replacing the original emergency repair scheme obtained by artificial experience, and enabling emergency repair work to be carried out more scientifically and efficiently; according to the emergency repair scheme formed based on the intranet data and the method for sharing the relevant data of the fault point with the extranet, data communication is achieved on the premise that data safety is guaranteed, and repair efficiency is improved.
All the above optional technical solutions may be combined arbitrarily to form optional embodiments of the present application, and are not described herein again.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (8)
1. An emergency aid decision-making system based on an intranet, comprising: a fault identification module, a topological relation module, an emergency repair guidance module and an emergency command module,
the fault identification module acquires fault identification information by utilizing a forward reasoning algorithm and a reverse reasoning algorithm according to original fault data;
the topological relation module is used for constructing a power network topological relation graph after a fault based on a GIS database vectorized electrical wiring graph, and reading a vector relation of loads in the power network topological relation graph;
the emergency repair guidance module determines the emergency repair sequence of the fault points by using the vector relation of the loads in the power network topological relation diagram and combining the relevant data of the fault points through the topological relation module to form an emergency repair scheme, and obtains a decision of transporting emergency repair materials to the fault points through a target loss value caused by material scheduling delay based on the emergency repair scheme, and selects a target emergency repair line; the relevant data of the fault point comprise the importance degree of the power-losing load, the position information of the fault point, the distance from the emergency maintenance team to the fault point and materials required by emergency maintenance of the fault point;
and the emergency command module is connected with the emergency repair guidance module and the fault identification module through the topological relation module, desensitizes and encrypts data in the target emergency repair line, and shares the processed data to an external network.
2. The emergency aid decision system according to claim 1, wherein the fault identification module comprises: a fault interface unit, a load interface unit, a system diagram interface unit,
the fault interface unit is used for acquiring original fault data;
the load interface unit is used for extracting fault information in the original fault data, wherein the fault information comprises the load grade and the load power of a load affected by equipment faults;
and the system diagram interface unit is used for generating fault identification information by using the fault information in the original fault data.
3. The emergency aid decision system according to claim 1, wherein the topological relation module comprises a quantization scale unit and a constraint condition unit,
the quantization level unit is used for dividing the load into different levels according to different types of the load and determining a target level function according to the levels;
the constraint condition unit is used for constraining the loop quantity and the power limit in the topological relation graph of the power network based on an objective level function.
4. The emergency aid decision system of claim 3, wherein the objective level function comprises the expression:
wherein λ is i Representing the load importance level associated with the failed node i;
represents the sum of the loads of the nodes i;
the loop number in the power network topological relation graph comprises the following expressions:
L＝0
wherein, L is the loop number in the topological relation graph of the power network;
the power limit includes the following expression:
S l ≤S lmax
S l is the power flowing on the tie line; s lmax Is the power limit of the tie line.
5. The emergency aid decision system according to claim 1, wherein the emergency repair guidance module comprises a dispatch path unit and an emergency repair failure unit,
the dispatching path unit is used for determining the emergency repair sequence of the fault points by utilizing the vector relationship of the loads in the power network topological relation diagram and combining the relevant data of the fault points to form an emergency repair scheme;
and the emergency repair fault unit is used for obtaining a decision of transporting emergency repair materials to a fault point through a target loss value caused by material scheduling delay based on the emergency repair scheme and selecting a target path.
6. The emergency aid decision system according to claim 5, wherein the target loss value is obtained based on a target loss function, the calculation of which includes the expression:
F＝min∑(t il +t ir )
wherein, t il The distance time from the fault point i to the fault point i +1 is the first-aid repair team; t is t ir The repair time is the failure point i.
7. The emergency aid decision system according to claim 5, wherein the target pathway is selected by an ant colony algorithm in combination with pheromone concentration.
8. The emergency aid decision-making system according to claim 1, wherein the emergency command module is configured to specify sensitive data in the power data through manual specification and automatic identification technologies, perform desensitization encryption on the sensitive data by using a desensitization correlation algorithm, and then achieve communication between the internal network data and the external network data by using an SQL proxy isolation device technology, wherein the desensitization correlation algorithm includes k-anonymity, L diversity, data suppression, data disturbance, and differential privacy.
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