Intelligent operation ticket generation method and device

Abstract

The present invention belongs to the technical field of power dispatching order parsing, and discloses an intelligent operation ticket generation method and device, equipment, and storage medium. The method obtains keyword information by parsing the received power dispatching control dispatching order; then determines the target interval object model matching the keyword information, determines the model element information from the keyword information, and fills it into the target interval object model to obtain the model content; finally, according to the parsing rules corresponding to the target interval object model, the model content is parsed to obtain the first five-defense operation sequence, and the first five-defense operation sequence is converted into a five-defense operation ticket, so that the power dispatching control dispatching order can be automatically parsed into the interval object model, and the problem of non-standard dispatching orders is solved, thereby realizing the automatic generation and processing from dispatching orders to five-defense operation sequences, and then the efficiency and accuracy of the finally generated five-defense operation tickets can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power dispatching order analysis, and in particular relates to a method and device for generating an intelligent operation ticket. Background Art

[0002] Electric power dispatching and control orders (hereinafter referred to as orders) are mostly written by the staff responsible for dispatching and control. The format is not unified, and there are many non-standard formats in the text, which brings difficulties to text processing and semantic analysis in the power field.

[0003] At present, in the process of parsing the transfer order into the five-defense operation ticket (i.e. the switching operation ticket), there is no function of directly and automatically converting it into the switching operation ticket. It mainly relies on the manual decomposition of the monitoring or operation personnel and compiles it into the switching operation ticket, which has the operational risk of incorrect compilation of the switching operation ticket. Moreover, the manual simulation of the five-defense system's invoicing is not strongly related to the transfer order. When the proposed invoice does not meet the requirements of the transfer order operation, it is impossible to restrict and remind the drafter to transfer the computer key operation.

[0004] It can be seen that the problem of non-standard adjustment orders leads to low efficiency and accuracy in the generation of switching operation tickets. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent operation ticket generation method and device, which can improve the generation efficiency and accuracy of the operation ticket.

[0006] A first aspect of an embodiment of the present invention discloses a method for generating an intelligent operation ticket, comprising:

[0007] Receive power dispatching control orders;

[0008] Parsing the electric power dispatching control command to obtain keyword information;

[0009] Determining a target interval object model that matches the keyword information;

[0010] According to the target interval object model, determining model element information from the keyword information;

[0011] Filling the model element information into the target interval object model to obtain model content;

[0012] According to the parsing rules corresponding to the target interval object model, the model content is parsed to obtain a first five-defense operation sequence;

[0013] The first five-defense operation sequence is converted into a five-defense operation ticket.

[0014] A second aspect of an embodiment of the present invention discloses an intelligent operation ticket generating device, comprising:

[0015] A receiving unit, used for receiving power dispatching control orders;

[0016] An order parsing unit, used to parse the power dispatching control order to obtain keyword information;

[0017] A matching unit, used to determine a target interval object model that matches the keyword information;

[0018] a determining unit, configured to determine model element information from the keyword information according to the target interval object model;

[0019] A filling unit, used for filling the model element information into the target interval object model to obtain model content;

[0020] A model parsing unit, configured to parse the model content according to a parsing rule corresponding to the target interval object model to obtain a first five-defense operation sequence;

[0021] A conversion unit is used to convert the first five-defense operation sequence into a five-defense operation ticket.

[0022] The third aspect of an embodiment of the present invention discloses an electronic device, comprising a memory storing executable program code and a processor coupled to the memory; the processor calls the executable program code stored in the memory to execute the smart operation ticket generation method disclosed in the first aspect.

[0023] The fourth aspect of an embodiment of the present invention discloses a computer-readable storage medium, which stores a computer program, wherein the computer program enables a computer to execute the intelligent operation ticket generation method disclosed in the first aspect.

[0024] The beneficial effect of the present invention lies in that the provided intelligent operation ticket generation method and device parse the received power dispatching control order to obtain keyword information; then determine the target interval object model matching the keyword information, determine the model element information from the keyword information, and fill it into the target interval object model to obtain the model content; finally, according to the parsing rules corresponding to the target interval object model, parse the model content to obtain the first five-defense operation sequence, and convert the first five-defense operation sequence into a five-defense operation ticket, so that the power dispatching control order can be automatically parsed into the interval object model, solving the problem of non-standard orders, thereby realizing the automatic generation and processing from the order to the five-defense operation sequence, and then improving the efficiency and accuracy of the finally generated five-defense operation ticket. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings herein show specific examples of the technical solutions described in the present invention, and together with the specific implementation methods, constitute a part of the specification, and are used to explain the technical solutions, principles and effects of the present invention.

[0026] Unless otherwise specified or defined, the same reference numerals in different drawings represent the same or similar technical features, and the same or similar technical features may also be represented by different reference numerals.

[0027] Figure 1 It is a flow chart of a method for generating an intelligent operation ticket;

[0028] Figure 2 It is a flow chart of another intelligent operation ticket generation method;

[0029] Figure 3 It is a structural schematic diagram of an intelligent operation ticket generating device;

[0030] Figure 4 It is a structural diagram of an electronic device.

[0031] Description of reference numerals:

[0032] 301, receiving unit; 302, command parsing unit; 303, matching unit; 304, determining unit; 305, filling unit; 306, model parsing unit; 307, converting unit; 401, memory; 402, processor. DETAILED DESCRIPTION

[0033] In order to facilitate the understanding of the present invention, specific embodiments of the present invention will be described in more detail below with reference to the accompanying drawings.

[0034] Unless otherwise specified or defined, all technical and scientific terms used herein have the same meaning as those generally understood by those skilled in the art. In the case of combining the technical solution of the present invention with realistic scenarios, all technical and scientific terms used herein may also have meanings corresponding to the purpose of implementing the technical solution of the present invention. The "first, second..." used herein is only used to distinguish the names and does not represent a specific quantity or order. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0035] It should be noted that when a component is considered to be "fixed to" another component, it can be directly fixed to the other component or there can be a central component; when an component is considered to be "connected to" another component, it can be directly connected to the other component or there can be a central component at the same time; when an component is considered to be "installed on" another component, it can be directly installed on the other component or there can be a central component at the same time. When an component is considered to be "set on" another component, it can be directly set on the other component or there can be a central component at the same time.

[0036] Unless otherwise specified or defined, the “said” and “the” used in this document refer to the technical features or technical contents mentioned or described before the corresponding position, and the technical features or technical contents may be the same as or similar to the technical features or technical contents mentioned therein.

[0037] Undoubtedly, technical contents or technical features that are contrary to the purpose of the present invention or are obviously contradictory should be excluded.

[0038] like Figure 1 As shown, an embodiment of the present invention discloses a method for generating an intelligent operation ticket, including the following steps 101 to 107.

[0039] 101. Receive power dispatching control orders.

[0040] 102. Analyze the electric power dispatching control order to obtain keyword information.

[0041] In an embodiment of the present invention, a set of corpus in the field of power system control can be pre-defined. First, several command samples are analyzed to extract corresponding corpus words, including voltage level, equipment type, equipment status or operation action, etc., to form a corpus.

[0042] Among them, the voltage levels generally use fixed voltage values, which are relatively easy to identify, including:

[0043] 36V, 220V, 380V, 6kV, 10kV, 35kV, 66kV, 110kV, 220kV, 330kV, 500kV, 750kV, 800kV, 1000kV.

[0044] Among them, the equipment type is established according to the scheduling standard name, and the following are some reference types:

[0045] Main transformer, coupling transformer, station transformer, busbar, bypass busbar, switch, busbar switch, line switch, transformer switch, generator switch, grounding switch, neutral grounding switch, lightning arrester switch, voltage transformer switch, PT switch, switch, line switch, bus coupling switch, bypass switch, bypass-bus switch, bus branch switch, line, phase-changing switch, bus coupling, bypass, bypass-bus, bus branch, circuit breaker, protection device (line protection device, bus differential protection device, transformer protection device, circuit breaker protection device, non-electrical protection device), secondary equipment (pressure plate, circuit breaker, handle), etc.

[0046] Among them, regarding the device status or operation action, the status in the call command is mainly represented by the source status and target status of the operation object. Relevant corpus words can be extracted based on a large number of call commands:

[0047] Operation, hot standby, cold standby, maintenance, direct trip, signal, tripping, closing, tripping via reclosing, via single tripping, via triple tripping, adaptive reclosing, tripping via adaptive reclosing, out of service, put into operation, etc.

[0048] Then, when executing step 101, the dispatch order decomposition algorithm can be used to segment, annotate and extract keywords from the dispatch order according to the power system control domain corpus. The dispatch order decomposition algorithm includes but is not limited to the following algorithms:

[0049] 1) Word graph scanning is implemented based on the prefix dictionary to generate a directed acyclic graph (DAG) consisting of all possible word formation situations of Chinese characters in the sentence. Dynamic programming is used to find the maximum probability path and the maximum segmentation combination based on word frequency, so as to perform word segmentation;

[0050] 2) For non-dictionary words, the Hidden Markov Model (HMM model) and Viterbi algorithm based on the word-forming ability of Chinese characters are used for calculation; the Viterbi algorithm is a decoding algorithm for many natural language processing;

[0051] 3) Part-of-speech tagging based on the Viterbi algorithm;

[0052] 4) Extract keywords based on TF-IDF and textrank models respectively.

[0053] For example, assuming that the transfer order is "route the 10kV F1 financial line from operation to maintenance", the keyword information obtained after parsing includes multiple segmented words and the element type to which each segmented word belongs, as listed in Table 1 below:

[0054] Table 1 Keyword information

[0055] Participle Feature Type Will Keywords 10kV Voltage F1 serial number Financial Lines noun line type Depend on Keywords run Source Status change Keywords Maintenance Target state

[0056] 103. Determine a target interval object model that matches the keyword information.

[0057] In an embodiment of the present invention, a group of interval object models can be pre-set, including but not limited to the following types of basic models, such as object operation model A1, object state transition model A2, object power supply transition model A3, object state transition and power supply model A4, bus object state transition model after bus reverse operation A5, bus object state transition and recovery to normal operation mode model A6, ground wire hanging model A7, ground wire removal model A8, object grounding change model A9.

[0058] In addition to individual basic models, composite models may also be included. The composite model is composed of the above nine basic models. The split sub-models calculate the corresponding five-defense operation sequences separately. The repeated five-defense operation sequences between models take the first position of occurrence as the deduplication standard. Specifically, it includes but is not limited to the following types of composite models, such as a combination of multiple basic models A2, a combination of basic models A3, A2 and A1, a combination of basic models A4 and A1, a combination of basic models A2, A3 and A1, a combination of basic models A3 and A2, and a combination of basic models A2 and A3.

[0059] Based on this, in step 103, the closest interval object model can be matched as the target interval object model according to the key words, voltage, name, type, state and other element types decomposed and parsed from the command.

[0060] Specifically, multiple element types in the keyword information can be retrieved one by one to obtain multiple interval object models matching each element type, and finally the interval object model with the most matching element types, that is, the interval object model with the most element types identical to the keyword information, is determined as the target interval object model.

[0061] 104. According to the target interval object model, determine model element information from the keyword information.

[0062] Step 104 includes: determining a target element type that matches the target interval object model from the element type to which each segment belongs; and determining the target segment belonging to the target element type as model element information.

[0063] 105. Fill the model element information into the target interval object model to obtain the model content.

[0064] Each interval object model has a one-to-one correspondence model structure, which includes multiple target element types arranged in a certain order. Similar to the object operation model A1, its model structure is: [action][object]. This model A1 is generally used to solve the dispatching structure of "action" and "object".

[0065] For example, if the command is "Close the 10kV F1 financial line 701 switch", it can be determined that the target element types that match the object operation model A1 include [action][object], so the target participle "close" of [action] and the target participle "10kV F1 financial line 701 switch" of [object] are determined as model element information. Fill in the target interval object model, and the output model content is: Close the 10kV F1 financial line 701 switch, and the model ID is A1.

[0066] Considering that the dispatch order is written manually, the equipment name in the dispatch order may not be standardized and there are multiple ways of writing. For example: "10kVF6 Training Line II 706 Switch", "10kVF6 Spare Six Line 706 Switch", "110kV Longpan Station 10kVF6 Training Line II 706 Switch", "10kVF6 Training Line II 706 Switch", etc., their standard names are all "10kV F6 Training Line II 706 Switch". Therefore, in an embodiment of the present invention, each equipment name can be mapped to its corresponding regular standard name by pre-setting a device name normalization mapping table. The device name normalization mapping table stores multiple standard names, and each standard name corresponds to multiple non-standard names.

[0067] Based on this, after executing step 105, the target standard name corresponding to the device name in the model content can also be determined from the multiple standard names in the device name normalization mapping table, and then it can be determined whether the device name in the model content is the same as its corresponding target standard name; if they are not the same, it means that the device name in the model content is not written in a standard way, and the device name in the model content is replaced with the target standard name; if they are the same, it means that the device name in the model content is written in a standard way and no modification is required.

[0068] Through the above implementation, the device names can be normalized to solve the problem of non-standard device names in the dispatch order, thereby realizing automatic parsing of the dispatch order.

[0069] 106. According to the parsing rules corresponding to the target interval object model, the model content is parsed to obtain the first five defense operation sequence.

[0070] Each interval object model may be provided with different parsing rules, which are stored in one-to-one correspondence with the interval object model, so that when executing step 106, the parsing rule corresponding to the target interval object model may be determined for parsing according to the target interval object model.

[0071] 107. Convert the first five-defense operation sequence into a five-defense operation ticket.

[0072] Step 107 may include the following steps 1071 to 1074:

[0073] 1071. Determine the device information from the first five-defense operation sequence, the device information including the device station number, device number, action initial state, and action target state.

[0074] For example, in the device information obtained from the first five-defense operation sequence, the device station number is 1, the device number is 102, the action initial state is 0, and the action target state is 1.

[0075] 1072. Query the equipment ledger according to the equipment station number and equipment number to obtain the equipment type and equipment double number.

[0076] First, query the equipment ledger through the equipment station number "1" and the equipment number "102", and you can get the corresponding equipment type as "switch" and the equipment double number as "#2 main transformer 110kV side 102 switch".

[0077] 1073. According to the device type, the action initial state and the action target state, the expert term with wildcard is searched in the preset expert term list.

[0078] Then, according to the device type "switch", the initial state of the action "0", and the target state of the action "1", the expert term list is queried to obtain the corresponding expert terms including pre-action terms, action terms, and post-action terms, as follows: the pre-action term is check {SBSBH} in the open position; the action term is close {SBSBH}; the post-action term is check {SBSBH} in the closed position. Among them, {SBSBH} is a wildcard.

[0079] 1074. Replace the wildcard in the expert terminology with the double number of the equipment to obtain the five-prevention operation ticket.

[0080] Finally, replace the wildcard {SBSBH} with the equipment double number "#2 main transformer 110kV side 102 switch" to get the five-protection operation ticket, which reads: Check that the #2 main transformer 110kV side 102 switch is in the open position; close the #2 main transformer 110kV side 102 switch; check that the #2 main transformer 110kV side 102 switch is in the closed position.

[0081] In the embodiment of the present invention, step 106 mainly generates the first five-prevention operation sequence according to certain rules based on information such as model type, interval (device) type, source state, target state, etc. The first five-prevention operation sequence is a collection of multiple operation sequences of device number, device initial state, device target state, sequence number and special identification structure. In order to meet various complex situations, the analysis rules corresponding to each interval object model are set, and the specific situation will be reflected in the analysis examples of the following nine models.

[0082] (1) Model A1: Object Operation Model

[0083] Model structure: [action][object]

[0084] There are two types of target elements, namely [action] and [object]. In this model, an object refers to a single device, such as a switch or a knife switch, and an action is a verb such as close or open.

[0085] This model A1 is generally used to solve the command structure of "action" and "object".

[0086] For example, the command is: Close the 10kV F1 financial line 701 switch

[0087] Model content output: Action: Close; Object: 10kVF1 Financial Line 701 Switch; Model ID: Model: A1.

[0088] Parsing rules: When parsing this model, you can get the device number based on [Object] and get the device initial state and device target state based on [Action].

[0089] (2) Model A2: Object State Transition Model

[0090] Model structure: <Transform> [object] from [source state] to [target state]

[0091] The object in this model is an interval object, and the source state and target state are adjectives such as running, hot standby, cold standby, and maintenance that describe the state of the interval object.

[0092] This model A2 is generally used to solve the command structure of an "object" changing from a "source state" to a "target state".

[0093] For example, the transfer order is: 110kV Peixinlong line is switched from hot standby to maintenance

[0094] Model content output: object group: 110kV Peixinlong line; source state: hot standby; target state: maintenance; model ID: A2.

[0095] Parsing rules: When parsing this model, the interval objects can be divided into multiple types of interval objects according to a series of attributes such as the voltage level, equipment topology type, and wiring method of the interval objects. A device topology type operation sequence is generated for each type of interval object and each transition state. Then, a specific five-defense operation sequence is generated from the interval object and the equipment topology type operation sequence of the interval type to which the interval object belongs.

[0096] Specifically, the parsing process may include: judging whether the object is a busbar interval object according to the interval alias, source state, and target state in the model content; if it is a busbar interval object, generating an operation sequence of "decomposing the source state and target state, and transitioning the interval objects on the bus in order and according to the decomposed source state and target state"; if it is not a busbar interval object, judging whether the object is multiple interval objects; if it is multiple interval objects, generating an operation sequence of "decomposing the source state and target state, and transitioning the multiple interval objects according to the decomposed source state and target state"; if it is not multiple interval objects, generating an operation sequence of "converting the source state of the interval object to the standard state".

[0097] (3) Model A3: Object power supply conversion model

[0098] Model structure: <Change> [supply object] from [pre-transfer object] to [post-transfer object] [power supply action]

[0099] The object in this model is the busbar, the object before and after the transfer is the main transformer, and the power supply action is the keyword.

[0100] The model A3 is generally used to solve the conversion of bus power supply objects, where the bus is powered by a certain main transformer and then switched to another main transformer.

[0101] For example, the order is: transfer the 10kV 2A M and 2B M busbars from #2 main transformer to #1 main transformer for power supply

[0102] Model content output: transfer object: 10kV 2AM, 2BM busbars; object before transfer: #2 main transformer; object after transfer: #1 main transformer; model ID: A3.

[0103] Analysis rules: When analyzing this model, you can find the connection device between the bus and the main transformer according to the bus and the main transformer. The main transformer disconnects this device before the transfer, and the object connects this device after the transfer. In addition, it is necessary to implicitly derive the grounding transformer and the bus interval to ensure that there is only one grounding transformer running on the running bus and no grounding transformer running on the non-running bus.

[0104] Specifically, if the target interval object model is the object power supply conversion model A3, the parsing process in step 106 may specifically include:

[0105] Determine whether the transfer object, the object before transfer, and the object after transfer in the model content are powered by the same side;

[0106] If the power supply is on the same side, an operation sequence of "closing the main transformer switch on the transfer object side, switching on the grounding system of the transfer object, and disconnecting the busbar switch between the transfer object and the transfer object" is generated;

[0107] If the power supply is not on the same side, an operation sequence of "closing the busbar switch between the object before transfer and the object after transfer, and then exiting the grounding system of the transfer object" is generated.

[0108] (4) Model A4: Object state transition and power supply model

[0109] Model structure: <Change> [object] from [source state] to [target state], [power supply action] [power supply object]

[0110] In this model, the object is the main transformer bay, and the source and target states are operation, hot standby, cold standby, and maintenance, which are adjectives describing the bay object state. The power supply object is the busbar.

[0111] When parsing this model, the first half of the sentence can be processed in the same way as model A2, and the second half of the sentence requires implicit reasoning about the interval between the grounding transformer and the busbar, to ensure that there is only one grounding transformer in operation on the busbar in operation, that is, there cannot be two grounding transformers running in parallel for a long time on the busbar, and they can only be in parallel for a short time during the transfer process. Based on this, when the busbar is switched to the main transformer on the non-same side, the grounding wire must be withdrawn immediately after the busbar is closed and separated. In addition, the busbar that is not in operation does not need to have a grounding transformer in operation, but the busbar in operation must have a grounding transformer in operation. Based on this, when the main transformer on the same side of the busbar switches to operation and power supply, after the main transformer switches to operation, the grounding transformer must be put into operation first and then the busbar switch must be disconnected. The busbar switch cannot be disconnected first and then the grounding transformer must be put into operation, which will result in the busbar being without a grounding transformer. At the same time, when the main transformer has not switched to operation, the grounding transformer cannot be put into operation in advance, which will result in two grounding transformers running on the running busbar for a long time.

[0112] Specifically, if the target interval object model is object state transition and power supply A4, the parsing process in step 106 may specifically include:

[0113] Determine whether the target state is running. If it is running, generate an operation sequence of "converting the source state of the object to the target state, connecting the grounding system on the power supply object side, and disconnecting the busbar interval between the object and the power supply object"; if it is not running, generate an operation sequence of "converting the source state of the object to the target state".

[0114] (5) Model A5: State transition model after bus object inversion operation

[0115] Model structure: <Change> [bus object 1] <on or all or running> equipment to [bus object 2] [running target state], <Change> [bus object 1] from [source state] to [target state]

[0116] In this model, busbar object 1 is busbar, up or all or operation are keywords, busbar object 2 is busbar, operation target state, source state, target state are adjectives describing the state of bay object such as operation, hot standby, cold standby, and maintenance. This model is applied to the double busbar connection situation.

[0117] When analyzing this model, the mother operation is performed first. First, the status of all bays is determined. When the bay is in operation, hot switching is performed, and when it is in hot standby, cold switching is performed. A hot switching sequence is generated first, followed by a cold switching sequence.

[0118] Specifically, if the target interval object model is the state transition model A5 of the bus object after the bus inversion operation, the parsing process in step 106 may specifically include:

[0119] Obtain bus object 1, bus object 2, operation target state, source state, target state in the model content, and obtain all intervals of bus object 1, determine whether the interval is a line or a main transformer && the interval is running in bus object 1; if it is running, generate an operation sequence of "warming the interval, changing the PT interval of bus object 1 from the source state to the target state, and changing the bus coupler and bus sub-interval of bus object 1 from operation to cold standby"; if it is not running, determine whether the interval is a line or a main transformer && the interval is in hot standby in bus object 1, if it is hot standby, generate an operation sequence of "colding the interval, changing the PT interval of bus object 1 from the source state to the target state, and changing the bus coupler and bus sub-interval of bus object 1 from operation to cold standby"; if it is not hot standby, generate an operation sequence of "changing the PT interval of bus object 1 from the source state to the target state, and changing the bus coupler and bus sub-interval of bus object 1 from operation to cold standby".

[0120] (6) Model A6: Busbar object state conversion and recovery to normal operation model

[0121] Model structure: <Change> [busbar object] from [source state] to [target state], [busbar object] restores [normal operation state]

[0122] In this model, the normal operating state consists of all the bays running on the bus object. When the bus resumes normal operating mode, the bays linked to the bus are switched to normal operating mode.

[0123] When analyzing this model, you can first perform the bus state conversion operation, that is, the bus PT interval, the bus corresponding bus coupling interval operation to the target state, that is, the operating state. Then use the bus inversion operation mode to invert all the line intervals and main transformer intervals and bus split intervals running on the bus in the normal operation mode to the bus, and restore the normal operation mode of the bus.

[0124] Specifically, if the target bay object model is the busbar object state transition and recovery to normal operation mode model A6, the parsing process in step 106 may specifically include:

[0125] Obtain bus object 1, source state, target state, bus object 2, and normal operation state in the model content, and generate an operation sequence of "changing the PT bay of bus object 1 from the source state to the target state, and changing the bus-division and bus-coupling bay equipment of bus object 1 to operation"; then determine whether bus object 1 or the main transformer bay && bay is in the operating state, if so, generate an operation sequence of "bay hot failure"; if not, generate an operation sequence of "bay cold failure".

[0126] (7) Model A7: Ground wire model

[0127] Model structure: In [object] [action] a group of ground wires

[0128] When parsing this model, the corresponding grounding point can be found according to the object name, and the operation sequence of "hanging the ground wire" can be generated.

[0129] (8) Model A8: Ground wire removal model

[0130] Model structure: Remove a set of ground wires

[0131] When parsing this model, the corresponding grounding point can be found according to the object name, and the operation sequence of "removing the ground wire" can be generated.

[0132] (9) Model A9: Object grounding change model

[0133] Model structure: <Change> [object] from [original grounding object] to [target grounding object]

[0134] In this model, the grounding objects include small reactance grounding and direct grounding. This model explains the changes in the grounding methods of the neutral grounding point of the main transformer. Direct grounding means closing the neutral grounding point switch, and small reactance grounding means dividing the neutral grounding point switch.

[0135] When parsing this model, the corresponding neutral grounding point switch can be found according to the object name, and then it can be determined whether the target grounding object is directly grounded. If it is directly grounded, an operation sequence of "closing the neutral grounding point switch" is generated; if it is not directly grounded, an operation sequence of "opening the neutral grounding point switch" is generated.

[0136] In addition, the composite model is composed of the above nine basic models. The split sub-models calculate the corresponding five-defense operation sequences separately. The repeated five-defense operation sequences between models take the first position of occurrence as the deduplication standard. The specific situation is reflected in the analysis of the following six composite models.

[0137] (10) Composite model B1: Combination of multiple basic models A2

[0138] Model structure: Model A2, Model A2

[0139] The composite model B1 is generally used to solve the order structure of transferring power to the busbar before the main transformer is powered off (the busbar switches to non-conventional power supply), the main transformer is powered off (i.e. the main transformer state changes) and the grounding transformer corresponding to the busbar is exited. The most common is the comprehensive order.

[0140] (11) Composite model B2: Combination of model A3, model A2, and model A1 (busbar transfer to non-colateral main transformer power supply, clear main transformer state transition)

[0141] Model structure: Model A3, Model A2, Model A1

[0142] This model B2 is generally used to solve the order structure of transferring power to the busbar before the main transformer is powered off (the busbar switches to non-conventional power supply), the main transformer is powered off (i.e. the main transformer state changes) and the grounding transformer corresponding to the busbar is exited. The most common is the comprehensive order. For example:

[0143]

[0144] (12) Composite model B3: Combination of model A4 and model A1

[0145] Model structure: <Change> [object] from [source state] to [target state], [power supply action] [power supply object], [grounding action] [grounding object]

[0146] The composite model B3 is generally used to solve the order structure of transferring power to the busbar before the main transformer is powered off (the busbar switches to non-conventional power supply), the main transformer is powered off (i.e. the main transformer state changes) and the grounding transformer corresponding to the busbar is exited. The most common is the comprehensive order. For example:

[0147]

[0148]

[0149] (13) Composite model B4: Combination of model A2, model A3, and model A1 (switching power supply to the main transformer on the same side and clarifying the state transition of the main transformer)

[0150] Model structure: Model A2, Model A3, Model A1

[0151] The composite model B4 is generally used to solve the problem of main transformer power restoration, corresponding to the main transformer transferring normal power to the busbar, and putting into operation the command structure of the grounding transformer corresponding to the main transformer normal power supply busbar. The most common is the comprehensive command.

[0152] For example:

[0153]

[0154]

[0155] (14) Composite model B5: Combination of model A3 and model A2 (busbar transfer to non-colateral main transformer for power supply, first close the busbar and then disconnect the ground transformer, and then disconnect the colateral main transformer)

[0156] Model structure: Model A3, Model A2

[0157] The composite model B5 of this model is generally used to solve the problem of abnormal power supply of the corresponding busbar, and the command structure of switching the grounding transformer corresponding to the busbar from operation to cold standby. Or after the busbar is switched to abnormal power supply, the main transformer is powered off or powered off and switched to maintenance; a common command is a comprehensive command. For example:

[0158]

[0159] (15) Composite model B6: Combination of model A2 and model A3

[0160] Model structure: Model A2, Model A3

[0161] The compound model B6 is generally used to solve the problem of switching the corresponding busbar to normal power supply and switching the corresponding grounding transformer of the busbar from cold standby to operation. It corresponds to the compound model eight just operation. It is commonly used as a comprehensive command. For example:

[0162]

[0163] like Figure 2 As shown, an embodiment of the present invention discloses another intelligent operation ticket generation method, which includes the following steps 201 to 209.

[0164] Among them, steps 201 to 206 and Figure 1 In the illustrated embodiment, steps 101 to 106 are the same, and please refer to the above description, which will not be repeated here.

[0165] 207. Obtain an artificially generated second five-defense operation sequence.

[0166] 208. According to the second five-defense operation sequence, the first five-defense operation sequence is modified to obtain a target five-defense operation sequence.

[0167] Before executing step 208, the similarity between the first five-defense operation sequence and the second five-defense operation sequence can be calculated. If the similarity reaches a specified threshold, it is determined that the automatically generated first five-defense operation sequence meets the requirements; if the similarity does not reach the specified threshold, the execution of step 208 is triggered.

[0168] Specifically, in step 208, the different contents between the first five-defense operation sequence and the second five-defense operation sequence can be determined first, and the first distinguishing content of the first five-defense operation sequence and the second distinguishing content of the second five-defense operation sequence can be obtained. Then, the second distinguishing content is used as the reference content, and the first distinguishing content in the first five-defense operation sequence is corrected to obtain the corrected five-defense operation sequence as the target five-defense operation sequence.

[0169] 209. Convert the target five-defense operation sequence into a five-defense operation ticket.

[0170] Implementation Figure 2 The intelligent operation ticket generation method shown can verify the manually generated five-defense operation sequence with the five-defense operation sequence automatically generated by the transfer order, and finally correct the five-defense operation sequence automatically generated by the transfer order before converting it into a five-defense operation ticket, thereby further improving the accuracy of intelligent operation ticket generation.

[0171] like Figure 3 As shown, the embodiment of the present invention discloses an intelligent operation ticket generation device, including a receiving unit 301, a call order parsing unit 302, a matching unit 303, a determining unit 304, a filling unit 305, a model parsing unit 306 and a conversion unit 307, wherein:

[0172] The receiving unit 301 is used to receive a power dispatching control order;

[0173] The command parsing unit 302 is used to parse the power dispatching control command to obtain keyword information;

[0174] A matching unit 303, used to determine a target interval object model that matches the keyword information;

[0175] A determination unit 304, configured to determine model element information from keyword information according to the target interval object model;

[0176] A filling unit 305 is used to fill the model element information into the target interval object model to obtain the model content;

[0177] A model parsing unit 306, configured to parse the model content according to a parsing rule corresponding to the target interval object model to obtain a first five-defense operation sequence;

[0178] The conversion unit 307 is used to convert the first five-prevention operation sequence into a five-prevention operation ticket.

[0179] In some embodiments, the intelligent operation ticket generating device may further include the following judgment unit and normalization unit (not shown), wherein:

[0180] A judging unit, configured to judge whether a device name in the model content is the same as its corresponding target standard name after the filling unit fills the model element information into the target interval object model to obtain the model content;

[0181] The normalization unit is used to replace the device name in the model content with the target standard name when the judgment unit judges that they are different.

[0182] In some embodiments, the keyword information includes multiple participles and the element type to which each participle belongs; the above-mentioned determination unit 304 is specifically used to determine the target element type that matches the target interval object model from the element type to which each participle belongs according to the target interval object model; and, determine the target participle belonging to the target element type as model element information.

[0183] In some embodiments, the conversion unit 307 may include the following sub-units not shown:

[0184] The determination subunit is used to determine the device information from the first five-defense operation sequence; the device information includes the device station number, device number, action initial state, and action target state;

[0185] The ledger query subunit is used to query the equipment ledger to obtain the equipment type and equipment double number according to the equipment station number and equipment number;

[0186] A term query subunit is used to query and obtain expert terms with wildcards in a preset expert term list according to the device type, the action initial state and the action target state;

[0187] Replacement subunit is used to replace the wildcard in the expert terminology with the double number of the equipment to obtain the five-defense operation ticket.

[0188] In some embodiments, the intelligent operation ticket generating device may further include the following units not shown in the figure:

[0189] An acquisition unit, used for acquiring an artificially generated second five-defense operation sequence before the conversion unit 307 converts the first five-defense operation sequence into a five-defense operation ticket;

[0190] A checking unit, used for correcting the first five-defense operation sequence according to the second five-defense operation sequence to obtain a target five-defense operation sequence;

[0191] The above-mentioned conversion unit 307 is specifically used to convert the target five-defense operation sequence into a five-defense operation ticket.

[0192] like Figure 4 As shown, an embodiment of the present invention discloses an electronic device, including a memory 401 storing executable program codes and a processor 402 coupled to the memory 401;

[0193] The processor 402 calls the executable program code stored in the memory 401 to execute the intelligent operation ticket generation method described in the above embodiments.

[0194] An embodiment of the present invention also discloses a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the intelligent operation ticket generation method described in the above embodiments.

[0195] The purpose of the above embodiments is to exemplarily reproduce and deduce the technical solution of the present invention, and to fully describe the technical solution, purpose and effect of the present invention. Its purpose is to make the public understand the disclosed content of the present invention more thoroughly and comprehensively, and it does not limit the scope of protection of the present invention.

[0196] The above embodiments are not exhaustive enumerations of the present invention, and there may be multiple other implementations not listed. Any replacement and improvement made without violating the concept of the present invention shall fall within the protection scope of the present invention.

Claims

1. Intelligent operation ticket generation method, characterized in that: include: Receive power dispatch control orders; Parsing the power dispatch control command to obtain keyword information; determining a target interval object model that matches the keyword information; determining model element information from the keyword information according to the target interval object model; Filling the model element information into the target interval object model to obtain model content; Parsing the model content according to the parsing rules corresponding to the target interval object model to obtain a first five-prevention operation sequence; Convert the first five-prevention operation sequence into a five-prevention operation ticket; Converting the first five-prevention operation sequence into a five-prevention operation ticket includes: Determine device information from the first five-prevention operation sequence; the device information includes device station number, device number, action initial state, and action target state; According to the equipment station number and the equipment number, query the equipment ledger to obtain the equipment type and equipment double number; According to the device type, the action initial state and the action target state, searching in a preset expert term list to obtain expert terms with wildcards; Replace the wildcard in the expert term with the double number of the equipment to obtain the five-prevention operation ticket.

2. The method for generating an intelligent operation ticket according to claim 1, wherein: After filling the model element information into the target interval object model to obtain model content, the method further includes: Determining whether a device name in the model content is the same as its corresponding target standard name; If they are different, replace the device name in the model content with the target standard name.

3. The method for generating an intelligent operation ticket according to claim 1, wherein: The keyword information includes multiple participles and the element type to which each participle belongs; The step of determining model element information from the keyword information according to the target interval object model includes: Determining a target element type that matches the target interval object model from the element types to which each word belongs; The target word segmentation belonging to the target element type is determined as model element information.

4. The method for generating an intelligent operation ticket according to claim 1, wherein: Before converting the first five-prevention operation sequence into a five-prevention operation ticket, the method further includes: Get the artificially generated second and fifth defense operation sequences; According to the second five-defense operation sequence, the first five-defense operation sequence is modified to obtain a target five-defense operation sequence; And, converting the first five-prevention operation sequence into a five-prevention operation ticket includes: The target five-defense operation sequence is converted into a five-defense operation ticket.

5. Intelligent operation ticket generating device, characterized in that: include: A receiving unit, configured to receive power dispatching control commands; An order parsing unit, configured to parse the power dispatching control order to obtain keyword information; a matching unit, configured to determine a target interval object model that matches the keyword information; a determining unit, configured to determine model element information from the keyword information according to the target interval object model; A filling unit, configured to fill the model element information into the target interval object model to obtain model content; a model parsing unit, configured to parse the model content according to a parsing rule corresponding to the target interval object model to obtain a first five-prevention operation sequence; A conversion unit, configured to convert the first five-prevention operation sequence into a five-prevention operation ticket; The conversion unit includes: A determination subunit, configured to determine device information from the first five-prevention operation sequence; the device information includes a device station number, a device number, an action initial state, and an action target state; The ledger query subunit is used to query the device ledger to obtain the device type and device dual number according to the device station number and the device number; A term query subunit, configured to query a preset expert term list to obtain expert terms with wildcards according to the device type, the action initial state, and the action target state; The replacement subunit is used to replace the wildcard in the expert term with the double number of the equipment to obtain the five-prevention operation ticket.

6. The intelligent operation ticket generating device according to claim 5, characterized in that: Also includes: a judging unit configured to judge whether a device name in the model content is the same as its corresponding target standard name after the filling unit fills the model element information into the target interval object model to obtain the model content; A normalization unit is configured to replace the device name in the model content with the target standard name when the determination unit determines that the device name is different from the target standard name.

7. The intelligent operation ticket generating device according to claim 5, characterized in that: The keyword information includes multiple participles and the element type to which each participle belongs; The determining unit is specifically configured to determine, according to the target interval object model, a target element type that matches the target interval object model from the element types to which each segment belongs; and determine the target segment belonging to the target element type as model element information.

8. The intelligent operation ticket generating device according to claim 5, characterized in that: Also includes: An acquiring unit, configured to acquire an artificially generated second five-prevention operation sequence before the converting unit converts the first five-prevention operation sequence into a five-prevention operation ticket; a checking unit, configured to correct the first five-defense operation sequence according to the second five-defense operation sequence to obtain a target five-defense operation sequence; The conversion unit is specifically used to convert the target five-defense operation sequence into a five-defense operation ticket.

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