CN113806705A - Method, device, terminal and medium for automatically issuing operation order based on artificial intelligence - Google Patents
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Abstract
The invention discloses an artificial intelligence-based automatic ordering method, an artificial intelligence-based automatic ordering device, an artificial intelligence-based automatic ordering terminal and an artificial intelligence-based automatic ordering medium, wherein the method comprises the following steps of: acquiring a scheduling operation command ticket of the power scheduling system; an identity authentication model is built based on a BP neural network, and the identity of a dispatcher is authenticated through the identity authentication model; enabling the authenticated dispatcher to receive the dispatching operation command ticket and a pre-issued order of the dispatching operation command ticket; judging whether the scheduling operation command ticket meets all automatic ordering conditions or not; if so, issuing a scheduling instruction to the authenticated dispatcher according to the pre-issued instruction; if not, the scheduling instruction is not issued. The identity authentication method based on the neural network establishes the identity authentication model, and improves the accuracy of identity authentication by setting the number of nodes of the input layer, the output layer and the hidden layer. Meanwhile, the order issuing condition is set through the DMIS system, so that the automatic issuing of the dispatching operation order instruction is realized, and the method has the advantages of short time consumption, high accuracy and strong safety.
Description
Technical Field
The invention relates to the technical field of electric power operation tickets, in particular to an artificial intelligence-based automatic operation ticket ordering method, an artificial intelligence-based automatic operation ticket ordering device, an artificial intelligence-based automatic operation ticket ordering terminal and an artificial intelligence-based automatic operation ticket ordering medium.
Background
With the continuous expansion of the power grid scale, the operation tasks of dispatchers are greatly increased. The traditional telephone command mode can not meet the development requirement of the modern power grid dispatching operation. At present, electric power system's operation mode is more complicated changeable, and power equipment also mostly operates under the level that is close safety limit, because the switching operation of equipment is more frequent, write the loss that complexity, frequent degree and the maloperation of correct operation ticket brought all than greatly increased in the past, if still order the mode based on traditional manual work, not only can make the executive task degree of difficulty increase, consume time for a long time, can lead to the error rate of executive task to increase simultaneously, and the security descends.
Disclosure of Invention
The invention aims to provide an artificial intelligence-based automatic operation order issuing method, an artificial intelligence-based automatic operation order issuing device, an artificial intelligence-based automatic operation order issuing terminal and an artificial intelligence-based automatic operation order issuing medium, so that the problems of long time consumption, high error rate and low safety caused by the fact that the conventional operation order depends on manual telephone order issuing are solved.
In order to overcome the defects in the prior art, the invention provides an artificial intelligence-based automatic operation order issuing method, which comprises the following steps:
acquiring a scheduling operation command ticket of the power scheduling system;
establishing an identity authentication model based on a BP neural network, and authenticating the identity of a dispatcher through the identity authentication model;
enabling the authenticated dispatcher to receive the dispatching operation command ticket and a pre-issued order of the dispatching operation command ticket;
judging whether the scheduling operation command ticket meets all automatic ordering conditions or not; if so, issuing a scheduling instruction to the authenticated dispatcher according to the pre-issue instruction; if not, the scheduling instruction is not issued.
Further, the authenticated dispatcher receives the dispatching operation command ticket by utilizing a safety isolation device; and judging whether the scheduling operation command ticket meets all automatic ordering conditions through the DMIS system.
Further, the building of an identity authentication model based on the BP neural network and the authentication of the dispatcher identity through the identity authentication model include:
collecting the signature of a dispatcher to be authenticated;
preprocessing the signature;
extracting features of the signature using markov;
inputting the characteristics into an identity authentication model to be trained for training, and authenticating the identity of the dispatcher to be authenticated by using the trained identity authentication model.
Further, the identity authentication model to be trained comprises an input layer, an output layer and a hidden layer; wherein,
the number of nodes of the input layer is 5, the number of nodes of the output layer is 3, and the number of nodes of the hidden layer is 17.
Further, the preprocessing the signature includes:
carrying out normalization processing on the position of the signature by adopting a coordinate translation method;
and smoothing the signature subjected to the normalization processing by adopting Gaussian filtering.
Further, the extracting the signature using markov includes: a Markov state interval is determined, and a Markov state transition probability matrix is calculated.
Further, the identity authentication model to be trained is trained by using a gradient descent method.
The invention also provides an automatic ordering device based on the artificial intelligence, which comprises:
the operation command ticket acquiring unit is used for acquiring a scheduling operation command ticket of the power scheduling system;
the dispatcher identity authentication unit is used for building an identity authentication model based on a BP neural network and authenticating the identity of the dispatcher through the identity authentication model;
a pre-issue receiving unit for receiving the scheduling operation command ticket and the pre-issue order of the scheduling operation command ticket by the authenticated dispatcher;
the automatic order-issuing judging unit is used for judging whether the scheduling operation command ticket meets all automatic order-issuing conditions; if so, issuing a scheduling instruction to the authenticated dispatcher according to the pre-issue instruction; if not, the scheduling instruction is not issued.
The present invention also provides a terminal device, including:
one or more processors;
a memory coupled to the processor for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the artificial intelligence based operation ticket automated ordering method of any one of the above.
The invention also provides a computer-readable storage medium, on which a computer program is stored, the computer program being executed by a processor to implement the artificial intelligence based operation ticket automatic ordering method as described in any one of the above.
Compared with the prior art, the invention has the beneficial effects that:
the invention discloses an artificial intelligence-based automatic ordering method for operation tickets, which comprises the following steps: acquiring a scheduling operation command ticket of the power scheduling system; establishing an identity authentication model based on a BP neural network, and authenticating the identity of a dispatcher through the identity authentication model; enabling the authenticated dispatcher to receive the dispatching operation command ticket and a pre-issued order of the dispatching operation command ticket; judging whether the scheduling operation command ticket meets all automatic ordering conditions or not; if so, issuing a scheduling instruction to the authenticated dispatcher according to the pre-issue instruction; if not, the scheduling instruction is not issued.
The identity authentication method based on the neural network establishes the identity authentication model, and improves the accuracy of identity authentication by setting the number of nodes of the input layer, the output layer and the hidden layer. Meanwhile, the order issuing condition is set through the DMIS system, so that the automatic issuing of the dispatching operation order instruction is realized, and the method has the advantages of short time consumption, high accuracy and strong safety.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of an artificial intelligence-based operation order automatic ordering method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an operation order automatic issuing device based on artificial intelligence according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be understood that the step numbers used herein are for convenience of description only and are not used as limitations on the order in which the steps are performed.
It is to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The terms "comprises" and "comprising" indicate the presence of the described features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The term "and/or" refers to and includes any and all possible combinations of one or more of the associated listed items.
In a first aspect:
referring to fig. 1, an embodiment of the present invention provides an artificial intelligence-based automatic operation order issuing method, including:
and S10, acquiring a scheduling operation command ticket of the power scheduling system.
It should be noted that in this step, a power generation task, an operation mode, and an operation plan are mainly formulated by the power scheduling system, and according to a predicted load curve and an economic scheduling principle, power generation tasks of each power plant (including load distribution of a hydropower station and a thermal power plant) are allocated to generate a scheduling operation order ticket.
S20, building an identity authentication model based on the BP neural network, and authenticating the identity of the dispatcher through the identity authentication model.
In one embodiment, step S20 further includes the following steps:
1) collecting the signature of a dispatcher to be authenticated;
specifically, a handwritten signature of a dispatcher to be authenticated is collected through a handwritten touch screen;
2) preprocessing the signature;
in one embodiment, the steps of the preprocessing operation are as follows:
2.1) adopting a coordinate translation method to carry out normalization processing on the position of the signature:
wherein x and y are respectively the horizontal and vertical coordinates after normalization processing, x0And y0Respectively are the horizontal and vertical coordinates before normalization processing,
and
respectively are the mean values of the horizontal and vertical coordinates before normalization processing.
2.2) determining the size of the normalized signature:
where i represents the number of coordinates that need to be normalized.
2.3) adopting Gaussian filtering to carry out smoothing treatment on the handwritten signature, and eliminating noise:
wherein, h (x)2,y2) For smoothed handwritten signatures, D (x)1,y1) Is a pixel (x) on the spatial domain image1,y1) The distance from the center, σ, is the number of convolutions.
3) Extracting features of the signature using markov;
in one embodiment, the step 3) further comprises:
3.1) determining a Markov state interval;
specifically, the design state interval is [ -5, 5 ].
3.2) calculating a Markov state transition probability matrix;
Pij(m,m+n)＝Pij(n)；
where m and n are Markov state transition matrix dimensions, i is the number of state samples, j is the time interval, and P (n) is PijAnd (n) is an n-step transition probability matrix.
4) Inputting the characteristics into an identity authentication model to be trained for training, and authenticating the identity of the dispatcher to be authenticated by using the trained identity authentication model.
In one embodiment, the identity authentication model to be trained comprises an input layer, an output layer and a hidden layer, the characteristics are input into the input layer, then the model is trained, and finally the identity of the dispatcher to be authenticated is authenticated through the trained identity authentication model.
In this embodiment, the number of nodes in the input layer is 5, the number of nodes in the output layer is 3, and the number of nodes in the hidden layer is 17. Meanwhile, the dimension of the Markov state transition matrix is set to 320, a gradient descent method is adopted for training during parameter training of the model, the iteration frequency is set to 1000, the learning rate is 0.01, and experiments prove that the recognition rate of 98.7 percent can be obtained through the setting of the parameters, so that the accuracy and the safety of the operation ticket are greatly improved.
And S30, enabling the authenticated dispatcher to receive the dispatching operation command ticket and the pre-issued order of the dispatching operation command ticket.
It should be noted that, when scheduling the pre-issue command, the operation task needs to be accepted and repeated without errors.
S40, judging whether the scheduling operation command ticket meets all automatic ordering conditions; if so, issuing a scheduling instruction to the authenticated dispatcher according to the pre-issue instruction; if not, the scheduling instruction is not issued.
In one embodiment, the automatic ordering conditions include the following 7:
(1) the state of the scheduling operation command ticket is converted into an executing state;
(2) the order time of the scheduling operation command ticket is null;
(3) the field operator is in place (report on the arrival at the field);
(4) the ordered people are not empty (in design, the ordered people can be automatically placed on the site to report the personnel);
(5) the scheduled operation time is not empty and the current time has reached (exceeded) the scheduled operation time; (when the time is empty, automatic ordering is started, namely the time for reaching the planned operation meets the condition);
(6) the operator is not empty (the operator can automatically set up the starting automatic scheduling order-issuing personnel in design);
(7) if the operation order is associated with a maintenance order or a power conversion order, the state of the maintenance order or the mode order must be a state to be executed or a state in the middle of execution;
it is emphasized that the automatic ordering is only issued when the comprehensive order of the scheduling operation order meets all the conditions; otherwise, the order is not automatically issued.
The method for automatically issuing the operation order based on the artificial intelligence, provided by the embodiment of the invention, is used for establishing an identity authentication model based on the neural network and improving the accuracy of identity authentication by setting the number of nodes of the input layer, the output layer and the hidden layer. Meanwhile, the order issuing condition is set through the DMIS system, so that the automatic issuing of the dispatching operation order instruction is realized, and the method has the advantages of short time consumption, high accuracy and strong safety.
In a second aspect:
referring to fig. 2, an embodiment of the present invention further provides an automatic instruction issuing device based on artificial intelligence, including:
an operation command ticket acquiring unit 01, configured to acquire a scheduling operation command ticket of the power scheduling system;
the dispatcher identity authentication unit 02 is used for building an identity authentication model based on a BP neural network and authenticating the identity of the dispatcher through the identity authentication model;
a pre-issue receiving unit 03 for receiving the scheduling operation command ticket and a pre-issue order of the scheduling operation command ticket by an authenticated dispatcher;
an automatic ordering judgment unit 04, configured to judge whether the scheduling operation command ticket satisfies all automatic ordering conditions; if so, issuing a scheduling instruction to the authenticated dispatcher according to the pre-issue instruction; if not, the scheduling instruction is not issued.
It should be noted that the operation ticket automatic ordering apparatus based on artificial intelligence provided in the embodiment of the present invention is configured to execute the operation ticket automatic ordering method based on artificial intelligence according to the first aspect.
The device provided by the embodiment of the invention establishes the identity authentication model based on the neural network, and improves the accuracy of identity authentication by setting the number of nodes of the input layer, the output layer and the hidden layer. Meanwhile, the order issuing condition is set through the DMIS system, so that the automatic issuing of the dispatching operation order instruction is realized, and the method has the advantages of short time consumption, high accuracy and strong safety.
In a third aspect:
in an embodiment, there is further provided a terminal device, including:
one or more processors;
a memory coupled to the processor for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the artificial intelligence based operation ticket automated ordering method as described above.
The processor is used for controlling the overall operation of the terminal equipment so as to complete all or part of the steps of the artificial intelligence-based operation order automatic ordering method. The memory is used to store various types of data to support operation at the terminal device, and these data may include, for example, instructions for any application or method operating on the terminal device, as well as application-related data. The Memory may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk.
The terminal Device may be implemented by one or more Application Specific 1 integrated circuits (AS 1C), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components, and is configured to perform the method for automatically issuing an operation ticket based on artificial intelligence according to any of the embodiments described above, and achieve technical effects consistent with the above methods.
In an embodiment, a computer-readable storage medium is further provided, which includes program instructions, when executed by a processor, to implement the steps of the method for automatically ordering operation tickets based on artificial intelligence according to any one of the above embodiments. For example, the computer-readable storage medium may be the above-mentioned memory including program instructions, and the above-mentioned program instructions may be executed by the processor of the terminal device to implement the method for automatically ordering the operation ticket based on artificial intelligence according to any of the above-mentioned embodiments, and achieve the technical effects consistent with the above-mentioned method.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (10)
1. An automatic operation order issuing method based on artificial intelligence is characterized by comprising the following steps:
acquiring a scheduling operation command ticket of the power scheduling system;
establishing an identity authentication model based on a BP neural network, and authenticating the identity of a dispatcher through the identity authentication model;
enabling the authenticated dispatcher to receive the dispatching operation command ticket and a pre-issued order of the dispatching operation command ticket;
judging whether the scheduling operation command ticket meets all automatic ordering conditions or not; if so, issuing a scheduling instruction to the authenticated dispatcher according to the pre-issue instruction; if not, the scheduling instruction is not issued.
2. The artificial intelligence based operation ticket automatic ordering method according to claim 1, wherein a security isolation device is used to enable an authenticated dispatcher to receive the dispatching operation command ticket; and judging whether the scheduling operation command ticket meets all automatic ordering conditions through the DMIS system.
3. The artificial intelligence-based automatic operation order issuing method according to claim 1, wherein an identity authentication model is built based on a BP neural network, and the identity of a dispatcher is authenticated through the identity authentication model, and the method comprises the following steps:
collecting the signature of a dispatcher to be authenticated;
preprocessing the signature;
extracting features of the signature using markov;
inputting the characteristics into an identity authentication model to be trained for training, and authenticating the identity of the dispatcher to be authenticated by using the trained identity authentication model.
4. The artificial intelligence based operation order automatic ordering method according to claim 3, wherein the identity authentication model to be trained comprises an input layer, an output layer and a hidden layer; wherein,
the number of nodes of the input layer is 5, the number of nodes of the output layer is 3, and the number of nodes of the hidden layer is 17.
5. The artificial intelligence based operation ticket automatic ordering method according to claim 4, wherein said preprocessing the signature comprises:
carrying out normalization processing on the position of the signature by adopting a coordinate translation method;
and smoothing the signature subjected to the normalization processing by adopting Gaussian filtering.
6. The artificial intelligence based operation ticket automatic ordering method according to claim 4, wherein said extracting the signature feature using Markov comprises: a Markov state interval is determined, and a Markov state transition probability matrix is calculated.
7. The artificial intelligence based operation order automatic ordering method according to claim 4, wherein the identity authentication model to be trained is trained by a gradient descent method.
8. The utility model provides an automatic device of ordering of operation ticket based on artificial intelligence which characterized in that includes:
the operation command ticket acquiring unit is used for acquiring a scheduling operation command ticket of the power scheduling system;
the dispatcher identity authentication unit is used for building an identity authentication model based on a BP neural network and authenticating the identity of the dispatcher through the identity authentication model;
a pre-issue receiving unit for receiving the scheduling operation command ticket and the pre-issue order of the scheduling operation command ticket by the authenticated dispatcher;
the automatic order-issuing judging unit is used for judging whether the scheduling operation command ticket meets all automatic order-issuing conditions; if so, issuing a scheduling instruction to the authenticated dispatcher according to the pre-issue instruction; if not, the scheduling instruction is not issued.
9. A terminal device, comprising:
one or more processors;
a memory coupled to the processor for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the artificial intelligence based operation ticket automated ordering method of any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, the computer program being executed by a processor to implement the artificial intelligence based operation ticket automatic ordering method according to any one of claims 1 to 7.
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