CN115719139A - Dispatching self-checking system for power grid dispatching operation management - Google Patents
Dispatching self-checking system for power grid dispatching operation management Download PDFInfo
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Abstract
The invention provides a dispatching self-checking system for dispatching operation management of a power grid. The dispatching self-checking system for the power grid dispatching operation management comprises: the system comprises a shift management function module, an electromechanical group tab management function module and a scheduling service execution condition checking function module; the shift management function module comprises a shift preparation submodule, a shift execution submodule and a shift post-analysis submodule; the machine-group option card management function module comprises an organic furnace defect submodule, a machine-group start-stop submodule, a machine-group analysis submodule and a machine-group statistic submodule. The dispatching self-checking system for the dispatching operation management of the power grid, provided by the invention, has the advantages that the dispatching self-checking function of the system is realized in real time by combining the perfect shift switching management module and the unit management module, the problems are found in time, and early warning is given out.
Description
Technical Field
The invention belongs to the technical field of dispatching self-checking systems for dispatching operation management of power grids, and particularly relates to a dispatching self-checking system for dispatching operation management of power grids.
Background
With the further deepening of the reform of the economic system in China, the power grid structure is increasingly complex, the dispatching business is increased day by day, and the information and work which need to be concerned by a dispatcher are increasingly heavy. In recent years, computer technology is mature, a power grid dispatching management system is realized, and the idea of computer-aided service dispatching is adopted, so that the digitization level of power grid dispatching operation is improved, and the safe and stable operation level of a power grid is improved.
The existing dispatching power grid operation management system needs manual execution of dispatching personnel, lacks a system self-checking function and has strong manual dependence. With the continuous development and the gradual maturity of computer and Artificial Intelligence (AI) technologies, technologies such as intelligent monitoring, artificial brain thinking decision, intelligent interaction and the like gradually move from laboratories to markets. The artificial intelligence technology is combined with the power grid dispatching service, functions of researching, developing and dispatching a robot assistant, customizing reports, automatically composing pictures, automatically responding typical services and the like are achieved, artificial intelligence treatment of simple operation regulation and control is achieved, and a system self-checking function is achieved, but the following defects exist in the actual life:
1. the information integration depends on manpower, the workload is large, and the information is not updated in time;
2. the scheduling service execution condition checking work is manually executed by a scheduler, the automatic checking of a system is lacked, and the manual dependency is strong.
Therefore, there is a need to provide a new dispatching self-checking system for dispatching operation management of power grid to solve the above technical problems.
Disclosure of Invention
The invention aims to provide a dispatching self-checking system for power grid dispatching operation management, which can realize the real-time automatic self-checking function of the system, find problems in time and send out early warning by combining and perfecting a shift switching management module and a unit management module.
In order to solve the technical problem, the dispatching self-checking system for the power grid dispatching operation management provided by the invention comprises: the system comprises a shift management function module, an electromechanical group tab management function module and a scheduling service execution condition checking function module;
the shift management function module comprises a shift preparation submodule, a shift execution submodule and a shift post-analysis submodule;
the machine-group option card management function module comprises an organic furnace defect submodule, a machine set starting and stopping submodule, a machine set analysis submodule and a machine set statistic submodule;
the scheduling service execution condition checking function module comprises a service information acquisition and preprocessing submodule, a service association analysis submodule and an automatic service propelling submodule.
As a further scheme of the invention, the shift preparation submodule is used for acquiring the current shift condition of personnel from the scheduling log system, generating a report according to the acquired shift information, generating task arrangement to be handled for related users according to the shift report, reminding the related users according to time, acquiring the shift information from the scheduling system, checking the reasonability of the personnel information, supporting the users to manually adjust the shift information, acquiring the temporary mode adjustment condition information of the current shift from the scheduling log, acquiring the execution information of the operation ticket from the operation ticket system, acquiring the execution condition of the starting scheme from the OMS, acquiring the electric quantity information from the D5000 and automatically finishing the scheduling of the shift report.
As a further scheme of the present invention, the shift execution sub-module supports a user to check a shift report and shift completion conditions, automatically analyzes work completion conditions on shift, automatically analyzes information of equipment and the like related to each specific content of the shift, hooks each specific content with the equipment as a main line, and graphically performs 3D draggable display on the equipment, including abnormal equipment conditions on a time section, and accurately displays abnormal points.
As a further aspect of the present invention, the after-shift analysis submodule may analyze the shift deviation time, mark the deviation greater than half an hour, and count the number of people on duty according to the time period.
As a further scheme of the invention, the machine furnace defect sub-module acquires the machine furnace information from an OMS system, supports a user to input the machine furnace defect information, performs rationality check on the input information, and uses a TF-IDF (Term Frequency-Inverse Document Frequency) keyword extraction algorithm to extract keywords, automatically generates a machine furnace defect circulation prompt, automatically pushes the machine furnace defect circulation prompt to a dispatching operation assistant and a network plant platform, records a machine furnace defect circulation log and supports the user to inquire the log aiming at the input machine furnace defect information.
As a further scheme of the invention, the unit start-stop submodule supports a user to input the unit start-stop information condition, checks the rationality of the input information, extracts and records the unit start-stop recording information keywords by using a TF-IDF algorithm, automatically generates unit start-stop circulation reminding information, and outputs the information to a scheduling operation assistant and a network plant platform.
As a further scheme of the present invention, the unit analysis submodule supports analysis of a unit trial operation section and dynamic calculation of a stopped unit section, and the unit statistics submodule can perform analysis statistics according to a unit state and a unit history situation, perform visual display, perform statistics on the unit state on each section according to a time section, support checking of the unit state, perform statistics according to a monthly unit section situation, support statistics according to unit start-stop times, stop time, unit category, and the like, and perform grouping according to a power plant.
As a further scheme of the invention, the service information acquisition and preprocessing submodule supports information butt joint with multiple systems, checks whether records such as electrical defects, mode adjustment, stability limit and the like of a scheduling log are closed and newly added, and checks whether an oms system application form, a bus arrangement, a starting scheme and the stability limit are correctly started and closed.
As a further scheme of the invention, the service correlation analysis submodule analyzes and self-checks the power grid scheduling service by utilizing personnel and typesetting information collected by the shift management function and unit equipment information collected by the unit option card management function, analyzes and self-checks the operation time line of certain equipment, performs correlation analysis on various operations according to the operation time range of the equipment, counts the operation quantity of the equipment on the day and performs comparison analysis, analyzes the time line of equipment defects, hooks all various service information according to the equipment to form equipment defect processing affairs of the power grid, counts the number of the equipment defects on the day and performs comparison analysis, analyzes the equipment information, the operation and fault information of the equipment through a DeepAR algorithm, predicts the fault rate of the equipment, performs early warning, models the network structure of the whole power grid, performs real-time dynamic network abnormal information detection by using a NetWalk algorithm, and sends out early warning in time.
As a further scheme of the present invention, the automated service propelling sub-module intelligently propels the circulation of the associated services according to the association between the operation ticket and the scheduling log and the maintenance ticket, maintains and corrects the automatically recorded content, pushes the important automatically recorded information to the scheduling operation assistant, analyzes the content and the handling condition to be processed according to the association relationship of the services, and notifies the corresponding personnel.
Compared with the related technology, the dispatching self-checking system for the dispatching operation management of the power grid has the following beneficial effects:
1. the invention realizes the real-time automatic self-checking function of the system by combining the perfect shift switching management module and the unit management module, finds problems in time and sends out early warning.
Drawings
To facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a block diagram of the system of the present invention;
FIG. 2 is a functional diagram of a shift-to-shift report according to the present invention;
FIG. 3 is a functional schematic diagram of a defect in a furnace according to the present invention;
FIG. 4 is a schematic diagram of a DeepaR network structure introduced by the present invention;
fig. 5 is a schematic structural diagram of a NetWalk embedded model introduced by the present invention.
Detailed Description
Please refer to fig. 1, fig. 2, fig. 3, fig. 4 and fig. 5 in combination, wherein fig. 1 is a system structure diagram of the present invention; FIG. 2 is a functional diagram of a shift-over report according to the present invention; FIG. 3 is a functional schematic diagram of a defect in a furnace according to the present invention; FIG. 4 is a schematic diagram of a DeepAR network structure introduced by the present invention; fig. 5 is a schematic structural diagram of a NetWalk embedded model introduced by the present invention. The dispatching self-checking system for the dispatching operation management of the power grid comprises: the system comprises a shift management function module, an electromechanical group tab management function module and a scheduling service execution condition checking function module;
the shift management function module comprises a shift preparation submodule, a shift execution submodule and a shift post-analysis submodule;
the machine-group option card management function module comprises an organic furnace defect submodule, a machine set starting and stopping submodule, a machine set analysis submodule and a machine set statistic submodule;
the scheduling service execution condition checking function module comprises a service information acquisition and preprocessing submodule, a service association analysis submodule and an automatic service propelling submodule.
The shift preparation submodule is used for acquiring the current shift condition of personnel from a scheduling log system, generating a report according to the acquired shift information, generating a task arrangement to be handled for a relevant user according to the shift report, reminding the relevant user according to time, acquiring the information of the shift personnel from the scheduling and scheduling system, checking the reasonability of the information of the personnel, supporting the user to manually adjust the information of the shift personnel, acquiring the temporary mode adjustment condition information of the current shift from the scheduling log, acquiring the execution information of an operation ticket from the operation ticket system, acquiring the execution condition of a starting scheme from an OMS, acquiring the electric quantity information from a D5000, and automatically finishing the establishment of the shift report.
The shift preparation submodule comprises the following three steps:
the method comprises the following steps: and generating a shift task, namely acquiring the current shift condition of personnel from a scheduling log system, generating a report according to the acquired shift information, generating a task arrangement to be handled for a related user according to the shift report, reminding the related user according to time, providing a shift task query list for querying a shift group to which the current user belongs, and supporting the user to query the shift report according to name, time and task.
Step two: and scheduling the work attendance personnel, acquiring the information of the work attendance personnel from the scheduling and scheduling system, checking the reasonability of the information of the work attendance personnel, supporting the manual adjustment of the information of the work attendance personnel by a user, providing a function of inquiring the information of the work attendance personnel, and reminding the work attendance of related users according to time.
Step three: the method comprises the steps of compiling a shift report, acquiring temporary mode adjustment condition information of a current shift from a scheduling log, acquiring operation ticket execution information from an operation ticket system, acquiring execution conditions of a starting scheme from an OMS, acquiring electric quantity information from a D5000, performing data interval inspection, data item inspection and data relevance inspection, supporting a user to manually maintain shift contents, automatically completing the shift report compilation according to the acquired information, performing visual display, and supporting the user to screen and query a historical shift report according to time periods and personnel as shown in FIG. 2.
The shift execution sub-module supports a user to check shift reports and shift completion conditions, automatically analyzes work completion conditions on duty, automatically analyzes information of equipment and the like related to each specific content of the shift, hooks each specific content by taking the equipment as a main line, and carries out 3D draggable display on the equipment on graphs, wherein the condition of the equipment with abnormal state on a time section is included, and abnormal points are accurately displayed.
The shift switching execution submodule comprises the following steps:
the method comprises the following steps: and checking the work of shift change, namely supporting a user to check a work of shift change report and the work of shift change completion condition, automatically analyzing the work of shift change completion condition, outputting an analysis result, performing grouping display on the work of shift change according to the work completion state, and sequencing the work of shift change of the work according to the generation time.
Step two: and (4) performing shift-to-shift execution, namely outputting a shift-to-shift execution result to a scheduling log, providing a shift-to-shift execution result query function, and supporting a user to sort according to time.
Step three: the method comprises the steps of displaying graphical shift execution conditions, automatically analyzing information of equipment and the like related to each specific content of the shift, hanging each specific content by taking the equipment as a main line, carrying out 3D draggable display on the equipment on graphs, including abnormal equipment conditions on a time section, accurately displaying abnormal points, visually displaying shift arrangement and execution conditions, and supporting a user to group the shift according to log classification.
The off-duty analysis submodule can analyze the off-duty deviation time, mark the deviation more than half an hour and count the number of people on duty according to the time period.
The off-duty analysis sub-module analyzes the off-duty deviation time, marks the deviation larger than half an hour, counts the number of people on duty according to the time period, supports the user to inquire off-duty records and off-duty historical statistics, supports the screening according to the people and supports the sorting according to the time.
The machine furnace defect submodule acquires machine furnace information from an OMS (operation management system), supports a user to input the machine furnace defect information, performs rationality check on the input information, extracts keywords by using a TF-IDF (Term Frequency-Inverse Document detail Frequency) keyword extraction algorithm according to the input machine furnace defect information, automatically generates a machine furnace defect circulation prompt, automatically pushes the machine furnace defect circulation prompt to a scheduling operation assistant and a network factory platform, records a machine furnace defect circulation log, and supports the user to inquire the log.
The machine furnace defect submodule comprises the following two steps:
the method comprises the following steps: the machine furnace defect record is, as shown in fig. 3, obtained from the OMS system, supports the user to enter the machine furnace defect information, performs rationality check on the entered information, and extracts a keyword by using a TF-IDF (Term-Inverse Document function) keyword extraction algorithm with respect to the entered machine furnace defect information.
A word is considered to have a good category distinction capability if it appears more frequently in a class of business knowledge, i.e., TF (Term Frequency) is higher, and it appears less frequently in other documents in the business information base, i.e., DF (Document Frequency) is low, i.e., IDF (Inverse Document Frequency) is higher. The calculation formula is as follows:
TF (Term Frequency), i.e. word t i On-business knowledge information d j The probability of occurrence of (1):
wherein n is i,j Is the word t i Business knowledge d j The number of occurrences in (1), and the denominator is in the business knowledge d j The sum of the number of occurrences of all words in (b).
IDF (Inverse Document Frequency), i.e. the word t is contained in the service knowledge base i The reciprocal of the number of documents of (1):
wherein | D | represents the total number of documents in the business knowledge base, | j: t i ∈d j The expression, | denotes the inclusion of the word t i The amount of business knowledge.
TF-IDF is in practice mainly a multiplication of the two above, i.e. TF x IDF, and the calculation formula is as follows:
TF-IDF i,j ＝tf i,j ×idf i
and filtering common words and retaining important words through a TF-IDF algorithm, and analyzing and recording the machine furnace defect information keywords after acquiring the keywords.
Step two: and (4) machine furnace defect circulation, automatically generating a machine furnace defect circulation prompt according to the machine furnace defect information and the keywords input in the step one, automatically pushing the machine furnace defect circulation prompt to a dispatching operation assistant and a network factory platform, recording a machine furnace defect circulation log, and supporting a user to inquire the log.
The unit start-stop submodule supports a user to input the unit start-stop information condition, checks the rationality of the input information, extracts and records unit start-stop record information keywords by using a TF-IDF algorithm, automatically generates unit start-stop circulation reminding information, and outputs the unit start-stop circulation reminding information to a scheduling operation assistant and a network plant platform.
The unit start-stop submodule comprises the following two steps:
the method comprises the following steps: and the unit start-stop record supports a user to input the unit start-stop information condition, checks the rationality of the input information, and extracts and records the unit start-stop record information keywords by using the TF-IDF algorithm.
Step two: and (4) unit start-stop circulation, outputting a unit start-stop information next circulatable object inspection result according to the unit start-stop information condition input in the step one, automatically generating unit start-stop circulation reminding information according to the information and the keywords input in the step one, outputting the unit start-stop circulation reminding information to a scheduling operation assistant and a network plant platform, supporting a user to inquire unit start-stop circulation logs, supporting sequencing according to time, and supporting grouping of units according to a power plant.
The unit analysis submodule supports analysis of a unit trial operation section and dynamic calculation of a stopped unit section, the unit statistics submodule can perform analysis statistics according to a unit state and a unit historical situation and perform visual display, statistics is performed on the unit state on each section according to a time section, checking of the unit state is supported, statistics is performed according to a monthly unit section situation, statistics is performed according to unit start-stop times, stop time, unit types and the like, and grouping is performed according to a power plant.
The unit analysis submodule supports analysis of a unit trial operation section, judges unit real-time operation section information, dynamically calculates a stopped unit section, supports a user to inquire the unit real-time operation section, and supports grouping of the units according to a power plant.
The unit counting submodule comprises two subfunctions of unit state counting and unit historical condition counting;
the unit state counting function counts the number of the units according to different states, counts the unit states on each section according to time sections, supports checking the unit states, visually displays the unit state counting results, and groups the unit states according to unit shutdown time intervals.
The unit historical condition statistics function is used for carrying out statistics according to the monthly unit section condition, statistics according to the unit start-stop times, the unit stop time length, the unit category and the like is supported, grouping is carried out according to the power plant, and the statistics result can be displayed in a replaceable mode.
The service information acquisition and preprocessing submodule supports information butt joint with multiple systems, checks whether records such as electrical defects, mode adjustment, stability limit and the like of a scheduling log are closed-loop or newly added, and checks whether an oms system application form, a bus bar arrangement, a starting scheme and the stability limit are correctly started or closed-loop.
The service information acquisition and preprocessing submodule acquires scheduling service real-time information from each subsystem, and comprises the following steps:
the method comprises the following steps: acquiring and preprocessing electrical defect information, acquiring the electrical defect information from a scheduling log, analyzing the equipment condition of the electrical defect, analyzing the content of the electrical defect to form a power grid operation event, extracting electrical defect keywords by using a TF-IDF algorithm, and visually displaying the electrical defect information.
Step two: and preprocessing the mode adjustment condition, acquiring mode adjustment information from a scheduling log, acquiring equipment model information from D5000, analyzing associated equipment information of mode adjustment, outputting the mode adjustment information to the scheduling log, visually displaying the mode adjustment information, supporting sequencing according to time and supporting grouping according to adjustment types.
Step three: and (3) preprocessing the power grid fault information, acquiring the power grid fault information from the dispatching log, analyzing the equipment condition in the fault, extracting keywords by using a TF-IDF algorithm, and supporting the query of the fault condition.
Step four: and (4) stable quota preprocessing, namely acquiring stable quota information from a stable quota module, analyzing equipment information related in the stable quota, marking out overrun and overload records in the stable quota, and supporting the visual display of the stable quota information.
Step five: and (3) preprocessing the application form, acquiring a maintenance application from the maintenance application form, analyzing maintenance equipment information related in the maintenance form, extracting keywords from maintenance contents by using a TF-IDF algorithm, outputting information of execution conditions to a scheduling log after the application form is executed, displaying detailed information of the maintenance application form, supporting sequencing according to application time and supporting grouping according to the state of the application form.
Step six: and (3) bus arrangement preprocessing, namely acquiring bus arrangement information from the OMS, analyzing equipment information related to a bus arrangement module, outputting execution information to a scheduling log after bus arrangement execution, and performing list display on the bus arrangement information.
Step seven: and starting scheme preprocessing, namely acquiring a starting scheme from an OMS (operation management system), analyzing equipment information related to the starting scheme, extracting keywords of the scheme by using a TF-IDF (Transflash-IDF) algorithm, automatically generating a scheme execution reminder, outputting the execution information of the starting scheme to a scheduling log, outputting the execution reminder of the starting scheme to a scheduling operation assistant, displaying detailed information of the starting scheme, and supporting sequencing according to starting time.
The business correlation analysis submodule analyzes and self-checks the power grid dispatching business by utilizing personnel and typesetting information collected by the shift management function and unit equipment information collected by the unit option card management function, analyzes the time line of certain equipment operation, performs correlation analysis on various operations according to the equipment operation time range, counts the equipment operation quantity of the current day and performs the homonymy analysis, analyzes the time line of equipment defects, hooks all various kinds of business information according to the equipment to form equipment defect processing affairs of the power grid, counts the equipment defect quantity of the current day, performs the homonymy analysis, analyzes the equipment information, the equipment operation and the fault information by a DeepAR algorithm, predicts the equipment fault rate, performs early warning, models the whole power grid network structure, performs real-time dynamic network abnormal information detection by using a NetWalk algorithm, and sends out early warning in time.
The business correlation analysis sub-module comprises two sub-functions of equipment operation and defect analysis and daily monitoring analysis;
the equipment operation and defect analysis function analyzes the time line of certain equipment operation, performs correlation analysis on various operations according to the equipment operation time range, counts the equipment operation number of the current day and performs the same-proportion analysis, analyzes the time line of equipment defects, hooks all various service information according to equipment to form equipment defect processing affairs of a power grid, counts the equipment defect number of the current day, performs the same-proportion analysis, supports visual display of equipment operation and defect related content modules, and supports sequencing according to the time line.
The equipment operation and defect analysis function adopts a DeepAR model to evaluate and predict the current state parameters of the equipment, an early warning prompt is generated, and the DeepAR model outputs a predicted equipment fault probability distribution.
Defining a first time series in timeThe values are represented by equipment information and operation and defect data, representing the prediction start time, the probability distribution predicted by Deepar based on the autoregressive recurrent neural network, namely the equipment failure probability, and the likelihood function l (z) i,t |θ i,t ) And (4) showing.
The DeepAR structure is shown in FIG. 3, where the training process is on the left and the prediction process is on the right.
During training, at each time step t, the input of the network comprises the characteristic x i,t The value z of the last time step i, State of last time step
First, the current state is calculated
Further, a parameter of likelihood l (z | θ) is calculated
Finally, the network parameters are learned by maximizing the log-likelihood, and the formula is as follows:
wherein, the first and the second end of the pipe are connected with each other,
with a Gaussian distribution, i.e. θ = (μ, σ), then:
after training is finished, t is less than t 0 The historical data of the network is input into the network to obtain the initial state
The ancestor samples are used to obtain a series of samples from which the failure rate of the device is calculated.
The daily monitoring analysis function supports a user preset value service association rule, dynamic graph network modeling is carried out according to a power grid network structure, a NetWalk algorithm is introduced to carry out abnormity detection in a dynamically changing network in real time, and the relation between power grid dispatching operation data and the preset value rule is analyzed and compared.
The structure of the clique embedded model of NetWalk is shown in FIG. 5, vector representation is learned by using Deep Autoencoder Neural Network, firstly, the latest Network representation is learned by using a large amount of random walks led out from the initial Network, vertex coordinates learned in multi-dimensional Euclidean space can realize local fitting and global regularization, furthermore, the learned representation can be easily updated by using a reservior sampling strategy, and then, abnormal vertices or edges are marked by using a dynamic clustering model based on the learned vertex or edge representation, namely, devices or lines with possible abnormality exist in the whole power grid structure.
The function also supports classification of daily monitoring contents, visual display, analysis of reasonability between a power grid operation process and a power grid equipment state, reminding of an abnormal state, and output of a reasonability check result of a business association rule input content.
The automatic business propelling sub-module intelligently pushes the related business to circulate according to the relevance between the operation ticket, the scheduling log and the overhaul ticket, maintains and corrects the automatically recorded content, pushes the important automatically recorded information to a scheduling operation assistant, analyzes the content and the handling condition which need to be processed according to the relevance of the business, and informs corresponding personnel.
The automatic business propelling submodule intelligently pushes related business circulation according to the relevance among the operation ticket, the scheduling log and the overhaul ticket, maintains and corrects the automatic recording content, pushes important automatic recording information to a scheduling operation assistant, analyzes the content and the handling condition which need to be processed according to the relevance relation of the business, informs corresponding personnel, counts the number of the automatic circulation in a time period, compares the number of the automatic circulation in the time period according to the business type, supports the inquiry of the automatic recording log and the automatic circulation record, and supports the sequencing according to the time.
The method comprises the steps of improving a shift switching management function, adding equipment as a main line, realizing comprehensive real-time mastering of scheduling personnel information and work content thereof, automatically updating electromechanical group information in real time by improving an electromechanical group option card function, realizing automatic association of the basic information, the start-stop records and the defect records of the units, performing flow display on the unit information, using collected personnel and unit information to realize a scheduling service execution condition checking function, checking whether records of electrical defects, mode adjustment, stable quota and the like of a scheduling log are closed-loop or newly added, checking an oms system application form, a bus arrangement, a starting scheme and whether the stable quota is correctly started or closed-loop, avoiding low multi-system transfer efficiency and omission of a dispatcher to cause extrusion of each system record, analyzing the equipment information, equipment operation and fault information through a DeepAR algorithm, predicting equipment fault rate, performing early warning, modeling on the whole power grid network structure, performing dynamic network exception information detection through a Net walk algorithm, and timely sending early warning.
The technique of the invention can be summarized as follows:
the method comprises the following steps: the method comprises the steps of perfecting the shift switching management function, obtaining information of scheduling personnel, managing shift switching work in a graphical mode, and automatically hooking various scheduling work contents by taking equipment as a main line.
Step two: the management function of the electromechanical set option card is perfected, electromechanical set information is automatically updated in real time, automatic association of basic information of the set, start-stop records of the set and defect records of the set is realized, and the information of the set can be displayed in a flow manner.
Step three: the method comprises the steps that the collected personnel and unit information is used for realizing a scheduling service execution condition checking function, the operation is used as a core, whether records such as electrical defects, mode adjustment and stable quota of a scheduling log are closed and newly added or not is checked, whether an oms system application form, a bus bar arrangement, a starting scheme and the stable quota are correctly started and closed or not is checked, the condition that each system record is extruded due to low multi-system transfer efficiency and omission of a dispatcher is avoided, the equipment information, the equipment operation and fault information are analyzed through a DeEPAR algorithm, the equipment fault rate is predicted, and early warning is carried out; modeling is carried out on the whole power grid network structure, real-time dynamic network abnormal information detection is carried out by applying a NetWalk algorithm, and early warning is sent out in time.
In the present specification, the embodiments are described in a progressive manner, each embodiment focuses on the differences from the other embodiments, and the same and similar parts among the embodiments are referred to each other.
The principle and embodiments of the present invention are explained herein by using specific examples, and the above description of the examples is only for the purpose of helping understanding the method and the core idea of the present invention, and the general skilled in the art can change the specific embodiments and the application scope according to the idea of the present invention. In view of the foregoing, the description is not to be taken in a limiting sense.
Claims (10)
1. A dispatching self-checking system for dispatching operation management of a power grid is characterized by comprising:
the system comprises a shift switching management function module, an electromechanical group option card management function module and a scheduling service execution condition checking function module;
the shift management function module comprises a shift preparation submodule, a shift execution submodule and a shift post-analysis submodule;
the machine-electrical group tab management function module comprises an organic furnace defect submodule, a machine set starting and stopping submodule, a machine set analysis submodule and a machine set statistic submodule;
the scheduling service execution condition checking function module comprises a service information acquisition and preprocessing submodule, a service association analysis submodule and an automatic service propelling submodule.
2. The dispatching self-checking system for power grid dispatching operation management according to claim 1, wherein: the shift preparation submodule is used for acquiring the current shift condition of personnel from the scheduling log system, generating a report according to the acquired shift information, generating task arrangement to be handled for related users according to the shift report, reminding the related users according to time, acquiring the shift receiving personnel information from the scheduling and scheduling system, checking the reasonability of the personnel information, supporting the users to manually adjust the shift receiving personnel information, acquiring the current shift temporary mode adjustment condition information from the scheduling log, acquiring the operation ticket execution information from the operation ticket system, acquiring the execution condition of the starting scheme from the OMS, acquiring the electric quantity information from the D5000, and automatically finishing the shift report formulation.
3. The dispatching self-checking system for power grid dispatching operation management according to claim 1, wherein: the shift execution sub-module supports a user to check shift reports and shift completion conditions, automatically analyzes work completion conditions on duty, automatically analyzes information of equipment and the like related to each specific content of the shift, hooks each specific content by taking the equipment as a main line, and carries out 3D draggable display on the equipment on graphs, wherein the condition of the equipment with abnormal state on a time section is included, and abnormal points are accurately displayed.
4. The dispatching self-checking system for power grid dispatching operation management according to claim 1, wherein: the off-duty analysis submodule can analyze the off-duty deviation time, mark the deviation more than half an hour and count the number of people on duty according to the time period.
5. The dispatching self-checking system for power grid dispatching operation management according to claim 1, wherein: the machine furnace defect submodule acquires machine furnace information from an OMS (operation management system), supports a user to input the machine furnace defect information, performs rationality check on the input information, extracts keywords by using a TF-IDF (Term Frequency-Inverse Document detail Frequency) keyword extraction algorithm according to the input machine furnace defect information, automatically generates a machine furnace defect circulation prompt, automatically pushes the machine furnace defect circulation prompt to a scheduling operation assistant and a network factory platform, records a machine furnace defect circulation log, and supports the user to inquire the log.
6. The dispatching self-checking system for power grid dispatching operation management according to claim 1, wherein: the unit start-stop submodule supports a user to input the unit start-stop information condition, checks the rationality of the input information, extracts and records unit start-stop record information keywords by using a TF-IDF algorithm, automatically generates unit start-stop circulation reminding information, and outputs the unit start-stop circulation reminding information to a scheduling operation assistant and a network plant platform.
7. The dispatching self-checking system for power grid dispatching operation management according to claim 1, wherein: the unit analysis submodule supports analysis of a unit trial operation section and dynamic calculation of a stopped unit section, the unit statistics submodule can perform analysis statistics according to a unit state and a unit historical situation and perform visual display, statistics is performed on the unit state on each section according to a time section, checking of the unit state is supported, statistics is performed according to a monthly unit section situation, statistics is performed according to unit start-stop times, stop time, unit types and the like, and grouping is performed according to a power plant.
8. The dispatching self-checking system for power grid dispatching operation management according to claim 1, wherein: the service information acquisition and preprocessing submodule supports information butt joint with multiple systems, checks whether records such as electrical defects, mode adjustment, stability limit and the like of a scheduling log are closed-loop or newly added, and checks whether an oms system application form, a bus bar arrangement, a starting scheme and the stability limit are correctly started or closed-loop.
9. The dispatching self-checking system for power grid dispatching operation management according to claim 1, wherein: the business correlation analysis submodule analyzes and self-checks the power grid dispatching business by utilizing personnel and typesetting information collected by the shift management function and unit equipment information collected by the unit option card management function, analyzes the time line of certain equipment operation, performs correlation analysis on various operations according to the equipment operation time range, counts the equipment operation quantity of the current day and performs the homonymy analysis, analyzes the time line of equipment defects, hooks all various kinds of business information according to the equipment to form equipment defect processing affairs of the power grid, counts the equipment defect quantity of the current day, performs the homonymy analysis, analyzes the equipment information, the equipment operation and the fault information by a DeepAR algorithm, predicts the equipment fault rate, performs early warning, models the whole power grid network structure, performs real-time dynamic network abnormal information detection by using a NetWalk algorithm, and sends out early warning in time.
10. The dispatching self-checking system for power grid dispatching operation management according to claim 1, wherein: the automatic business propelling sub-module intelligently pushes the circulation of the related business according to the relevance between the operation ticket, the scheduling log and the overhaul ticket, maintains and corrects the automatically recorded content, pushes the important automatically recorded information to a scheduling operation assistant, analyzes the content and the handling condition to be processed according to the relevance of the business, and informs corresponding personnel.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117391357A (en) * | 2023-10-19 | 2024-01-12 | 国网安徽省电力有限公司马鞍山供电公司 | Scheduling self-checking system for power grid scheduling operation management based on big data |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117391357A (en) * | 2023-10-19 | 2024-01-12 | 国网安徽省电力有限公司马鞍山供电公司 | Scheduling self-checking system for power grid scheduling operation management based on big data |
| CN117391357B (en) * | 2023-10-19 | 2024-04-19 | 国网安徽省电力有限公司马鞍山供电公司 | Scheduling self-checking system for power grid scheduling operation management based on big data |
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