CN113159443A - Optimal path selection method and system suitable for operation order - Google Patents

Optimal path selection method and system suitable for operation order Download PDF

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CN113159443A
CN113159443A CN202110485323.4A CN202110485323A CN113159443A CN 113159443 A CN113159443 A CN 113159443A CN 202110485323 A CN202110485323 A CN 202110485323A CN 113159443 A CN113159443 A CN 113159443A
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罗磊
张鸿
虢韬
肖林
晏鹏
汪适
石鹏昌
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Guizhou Power Grid Co Ltd
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Abstract

The invention discloses an optimal path selection method and system suitable for an operation ticket, which comprises the steps of collecting the billing type and operation task information and selecting the ticket sample type; judging whether an optimal path needs to be calculated, if so, determining an initial topological structure of the power grid according to the power data in the database and the switch state in the knowledge rule base; analyzing the initial topological structure of the power grid by using graph theory and a genetic algorithm, and calculating and selecting an optimal power supply path; performing load flow calculation on the optimal power supply path scheme, and judging whether load flow distribution meets the requirement of system reliability; if not, continuously searching an optimal power supply path; if the optimal path is met, generating an operation ticket according to the operation rule, automatically printing a ticket sample, and completing the selection of the optimal path. The invention can realize minimum switching times, reduce scheduling time and economic loss, and simultaneously can judge whether the power flow distribution of the minimum path meets the reliability requirement, thereby achieving the advantage of combining economy and reliability.

Description

Optimal path selection method and system suitable for operation order
Technical Field
The invention relates to the technical field of power grid operation application systems, in particular to an optimal path selection method and system suitable for an operation order.
Background
The intelligent dispatching management system of the power system is mainly used for organizing, guiding and coordinating the operation of the power system to the operation of the power grid. The intelligent management and operation of the electric power system are a development trend, the dispatching operation ticket system is widely applied to electric power departments and electric power enterprises, the former method that electric power dispatching personnel manually operate to issue tickets is changed, the efficiency of the electric power enterprises is improved, the accuracy of the operation tickets is improved, the electric power operation ticket system is an effective safety measure for preventing the misoperation of dispatching operation management of the electric power system in China, and the dispatching operation ticket system is a basis for completing dispatching tasks with high quality and high efficiency.
With the increase of the total number of users and the continuous expansion of the scale of a power grid, the defects of the conventional scheduling operation ticket system are exposed, mainly because the intelligent reasoning function is not strong, the self-adaptive learning capability is poor, and the operation of the power database is lack of flexibility on the whole; the electric power service and the power grid construction are auxiliary works of urban and rural basic construction, and along with the enlargement of urban scale and the adjustment of development direction, the power grid needs to be regularly reconstructed and expanded, which puts higher requirements on the intelligent level of the power grid dispatching operation ticket generating system.
The most important thing in the electric power system is reliability, and every switching operation generates expenses including equipment depreciation expense, labor expense and the like, and by reducing the switching operation times, the relay protection misoperation caused by multiple switching operations can be avoided, and the service life of the switch can be prolonged. The existing scheduling operation ticket system does not consider the selection of an optimal path, the number of times of actions of switch equipment is large in the actual scheduling process, the action time is increased, the switching loss is increased, and timeliness and economy are not achieved.
Disclosure of Invention
This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.
The present invention has been made in view of the above-mentioned conventional problems.
Therefore, the technical problem solved by the invention is as follows: the prior art has poor reliability, no timeliness and economy and low intelligent level.
In order to solve the technical problems, the invention provides the following technical scheme: collecting the billing type and the operation task information and selecting the ticket sample type; judging whether an optimal path needs to be calculated, if so, determining an initial topological structure of the power grid according to the power data in the database and the switch state in the knowledge rule base; analyzing the initial topological structure of the power grid by using graph theory and a genetic algorithm, and calculating and selecting an optimal power supply path; performing load flow calculation on the optimal power supply path scheme, and judging whether load flow distribution meets the requirement of system reliability; if not, continuously searching an optimal power supply path; if the optimal path is met, generating an operation ticket according to the operation rule, automatically printing a ticket sample, and completing the selection of the optimal path.
As a preferable aspect of the optimal path selection method for an operation ticket according to the present invention, wherein: analyzing the power grid initial topological structure by using a genetic algorithm comprises the steps of obtaining the power grid initial topological structure, forming a node branch incidence matrix A and obtaining the connection relation of the node branches; forming an initial switch state vector according to the real-time switch state, and indicating whether the corresponding switch is closed or open; forming a population by the switching state codes of each individual, comparing the population with the initial switching state vector to obtain switching times S, and determining a selection factor, a cross factor and a variation factor by taking the minimum switching times as an adaptive function to form a new population; obtaining a node admittance matrix Y according to the node branch incidence matrix A and system parameters; selecting individuals in the previous generation population to enter the next generation population according to the selection factors, selecting individuals through the cross factors to perform cross coding to enter a new population, and selecting individuals through the variation factors to perform coding change to enter the new population; and judging whether the number of inheritance times is reached, if so, carrying out the next step, and if not, returning to the previous step.
As a preferable aspect of the optimal path selection method for an operation ticket according to the present invention, wherein: performing load flow calculation on the optimal power supply path scheme comprises the following steps of performing load flow calculation by adopting a Newton-Raphson strategy: and carrying out load flow calculation on the obtained individuals, and judging whether the power, the voltage and the current are out of limit or not.
As a preferable aspect of the optimal path selection method for an operation ticket according to the present invention, wherein: the optimal switch path is judged by setting the genetic times to be 0 again when the power, the voltage and the current are out of limit, carrying out selection, crossing and mutation operations, eliminating individuals with fitness function values equal to the maximum value, namely the individuals which cannot meet the load flow calculation verification, obtaining a new optimal path scheme after the genetic times reach the specified times, and calculating the load flow distribution; and when the power, the voltage and the current are not out of limit, outputting an optimal switching path, and finishing the algorithm.
The invention solves another technical problem that: a fiber network resource digital verification system is provided, and the method is realized by depending on the system.
In order to solve the technical problems, the invention provides the following technical scheme: the human-computer interaction interface is used for inputting a program and an operation instruction for judging the optimal path and updating the contents of the knowledge rule base module and the database module according to the program and the instruction; the database module is used for providing power data and historical operation tickets required by the reasoning module, and the rule base module is used for providing states of all components and operation ticket generation rules; the inference module comprises an optimal path selection module and a power flow calculation module, the optimal path selection module is used for processing the power data provided by the database module to generate an operation order of an optimal path, and the power flow calculation module is connected with the optimal path selection module and used for judging whether the power flow distribution under the optimal path meets the system requirement.
As a preferable aspect of the optimal path selection system for an operation ticket according to the present invention, wherein: the system also comprises an operating system which is used for realizing the comprehensive management of each module.
As a preferable aspect of the optimal path selection system for an operation ticket according to the present invention, wherein: the human-computer interaction interface provides a visual operation interface, an operator can conveniently manage the system and each module, and the human-computer interaction interface indirectly controls each module through the operation system to update the contents of the database module and the knowledge rule base module.
As a preferable aspect of the optimal path selection system for an operation ticket according to the present invention, wherein: the human-computer interaction interface guides a genetic algorithm program which is manually input into the optimal path selection module, guides an operation instruction which needs to be completed into the reasoning module, and displays an optimal path operation ticket obtained by the reasoning module on the interface to realize the automatic ticket issuing function.
As a preferable aspect of the optimal path selection system for an operation ticket according to the present invention, wherein: the knowledge rule base module stores various logic rules required by the state of the equipment and the generation of the operation ticket, and the logic rules are controlled by the program of the operation system and are managed, added and modified as required.
As a preferable aspect of the optimal path selection system for an operation ticket according to the present invention, wherein: the optimal path selection module generates an optimal path operation ticket through a genetic algorithm, the load flow calculation module performs load flow calculation on the power system under the optimal path, judges whether load flow distribution under the optimal path meets system requirements, transmits the generated operation ticket to the operation system if the load flow distribution under the optimal path meets the system requirements, takes the path as a rejected individual of the genetic algorithm if the load flow distribution does not meet the requirements, and returns to the optimal path selection module to recalculate the optimal path.
The invention has the beneficial effects that: the invention combines the automatic ticket issuing function of the traditional operation ticket system, adds the function of optimal path selection, can realize the minimum switching times and reduce the scheduling time and the economic loss, has the function of load flow calculation and verification, realizes the load flow distribution judgment of the minimum path to meet the reliability requirement and achieves the advantage of economic and reliable combination.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced 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 to obtain other drawings based on these drawings without inventive exercise. Wherein:
fig. 1 is a basic flowchart of a method and a system for selecting an optimal path for an operation ticket according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a genetic algorithm and a load flow calculation process of an optimal path selection method and system for operation tickets according to an embodiment of the present invention;
fig. 3 is a schematic block diagram of an optimal path selection method and system for an operation ticket according to an embodiment of the present invention;
fig. 4 is a system structural diagram of an optimal path selection method and system for an operation ticket according to an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, specific embodiments accompanied with figures are described in detail below, and it is apparent that the described embodiments are a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present invention, shall fall within the protection scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described and will be readily apparent to those of ordinary skill in the art without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Furthermore, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
The present invention will be described in detail with reference to the drawings, wherein the cross-sectional views illustrating the structure of the device are not enlarged partially in general scale for convenience of illustration, and the drawings are only exemplary and should not be construed as limiting the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
Meanwhile, in the description of the present invention, it should be noted that the terms "upper, lower, inner and outer" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation and operate, and thus, cannot be construed as limiting the present invention. Furthermore, the terms first, second, or third are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected and connected" in the present invention are to be understood broadly, unless otherwise explicitly specified or limited, for example: can be fixedly connected, detachably connected or integrally connected; they may be mechanically, electrically, or directly connected, or indirectly connected through intervening media, or may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Example 1
Referring to fig. 1 to 2, an embodiment of the present invention provides an optimal path selection method for an operation ticket, including:
s1: collecting the billing type and the operation task information and selecting the ticket sample type;
s2: judging whether an optimal path needs to be calculated, if so, determining an initial topological structure of the power grid according to the power data in the database and the switch state in the knowledge rule base;
s3: analyzing the initial topological structure of the power grid by using graph theory and a genetic algorithm, and calculating and selecting an optimal power supply path;
s4: performing load flow calculation on the optimal power supply path scheme, and judging whether load flow distribution meets the requirement of system reliability;
if not, continuously searching an optimal power supply path;
if the optimal path is met, generating an operation ticket according to the operation rule, automatically printing a ticket sample, and completing the selection of the optimal path.
Specifically, as shown in fig. 2, analyzing the initial topology of the power grid by using a genetic algorithm includes: acquiring an initial topological structure of a power grid, forming a node branch incidence matrix A, and acquiring a connection relation of node branches;
forming an initial switch state vector according to the real-time switch state, wherein the initial switch state vector represents whether a corresponding switch is closed or opened, 1 represents closed, and 0 represents opened;
the switching state codes of each individual form a population, the population is compared with the initial switching state vector to obtain switching times S, the minimum switching times is taken as an adaptive function, namely the adaptive function is the sum of the switching times of each switch, and selection factors, cross factors and variation factors are determined to form a new population;
obtaining a node admittance matrix Y according to the node branch incidence matrix A and the system parameters;
selecting individuals in the previous generation population to enter the next generation population according to selection factors, selecting individuals through cross factors to perform cross coding to enter a new population, and selecting individuals through variation factors to perform coding change to enter the new population;
judging whether the number of inheritance times is reached, if so, carrying out the next step, and if not, returning to the previous step, namely returning to the selection, crossing and mutation operations;
further, the performing of the power flow calculation on the optimal power supply path scheme includes:
and (3) carrying out load flow calculation by adopting a Newton Raphson strategy:
carrying out load flow calculation on the obtained individuals (the optimal switch path scheme), and judging whether the power, the voltage and the current are out of limit or not;
further, the determination of the optimal switching path includes,
when the power, the voltage and the current are out of limit, setting the genetic times as 0 again, carrying out selection, crossing and mutation operations, eliminating the individuals of which fitness function values are equal to the maximum value, namely the individuals which cannot meet the power flow calculation verification, immediately eliminating the individuals once the individuals appear, obtaining a new optimal path scheme after the genetic times reach the specified times, calculating the power flow distribution, and executing the program according to the scheme;
and when the power, the voltage and the current are not out of limit, outputting an optimal switching path, and ending the algorithm.
The invention combines the automatic ticket issuing function of the traditional operation ticket system, adds the function of optimal path selection, can realize the minimum switching times and reduce the scheduling time and the economic loss, has the function of load flow calculation and verification, realizes the load flow distribution judgment of the minimum path to meet the reliability requirement and achieves the advantage of economic and reliable combination.
Example 2
Referring to fig. 3 to 4, for the optimal path selection system for the operation ticket provided in this embodiment, the optimal path selection method for the operation ticket provided in the above embodiment can be implemented by depending on the system.
As shown in fig. 3 to 4, the optimal path selection system for operation tickets includes: the human-computer interaction interface 100 is used for inputting a program and an operation instruction for judging the optimal path and updating the contents of the knowledge rule base module 200 and the database module 300 according to the program and the instruction; the database module 300 is used for providing power data and historical operation tickets required by the reasoning module 400, and the knowledge rule base module 200 is used for providing states of all components and operation ticket generation rules; the inference module 400 includes an optimal path selection module 401 and a power flow calculation module 402, where the optimal path selection module 401 is configured to process the power data provided by the database module 200 to generate an operation ticket of an optimal path, and the power flow calculation module 402 is connected to the optimal path selection module 401 to determine whether power flow distribution in the optimal path meets system requirements.
The system further includes an operating system 500, configured to implement comprehensive management of the modules.
Specifically, the human-computer interaction interface 100 provides a visual operation interface, the control management of the operation system 500, the database module 300, the knowledge rule base module 200 and the inference module 400 is presented in a visual form, so that an operator can conveniently manage the system and each module, and the human-computer interaction interface 100 indirectly controls each module through the operation system 500 to update the contents of the database module 300 and the knowledge rule base module 200; the human-computer interaction interface 100 guides a genetic algorithm program input manually into the optimal path selection module 401, guides an operation instruction to be completed into the inference module 400, and displays an optimal path operation ticket obtained by the inference module 400 on the interface to realize an automatic ticket issuing function; in addition, the human-computer interaction interface 100 can also conduct import, export and modification maintenance operations on the power data and the historical operation tickets of the database module 300, conduct import, export and modification maintenance operations on the equipment state information of the knowledge rule base module 200, and input a logic control program to control the generation rule of the operation tickets; the inference module 400 inputs a genetic algorithm and a procedure of load flow calculation to realize selection of an optimal path and load flow calculation verification; and for the operating system 500, displaying the finally obtained optimal path operation ticket on an interface, and automatically printing the operation ticket.
The knowledge rule base module 200 stores various logic rules required by the state of the equipment and the generation of an operation ticket, the logic rules are controlled by an operation system 500 program and are managed, added and modified as required, the management of the knowledge rules needs to verify the identity of an operator on a human-computer interaction interface, the knowledge rule base adopts a management method of hierarchical rules, namely, a plurality of secondary rules are arranged below a primary rule, the secondary rules comprise a plurality of tertiary rules, and when the upper-level rules are changed, all the lower-level rules need to be changed, and the lower-level rules do not need to be changed; the database module 300 stores data and historical operation tickets of the power system, provides power system data for reasoning of the reasoning module 400 and historical operation tickets for the same scheduling situation, realizes importing and exporting of the power system data through operation of an operator on a human-computer interaction interface, and imports and exports the historical operation tickets according to operating system instructions, and the database module 300 has an automatic learning function and can realize a function of automatically updating the historical operation tickets.
The inference module 400 firstly judges whether the optimal path selection is needed according to an operation ticket instruction input by the human-computer interaction interface, directly calls a historical operation ticket in the database module for the operation ticket instruction which is already generated, returns the result to the human-computer interaction interface, generates an operation ticket of the optimal path by combining the power system data in the database and the operation ticket generation rule in the knowledge rule base for the condition that the optimal path selection is needed, and returns the result to the human-computer interaction interface.
The inference module 400 is divided into an optimal path selection module 401 and a power flow calculation module 402, the algorithm program in the optimal path selection module 401 is input by a human-computer interaction interface, the generation of the operation ticket of the optimal path is realized through a genetic algorithm, the load flow calculation module 402 realizes the load flow calculation of the power system under the optimal path, judges whether the load flow distribution under the optimal path meets the system requirements, the result generated by the optimal path selection module 401 is verified to ensure the reliability of the system operation, and can also prevent the system from misoperation, and if the current calculation result meets the requirement, the generated operation ticket is transmitted to the operation system 500, if the current calculation result does not meet the requirement, the path is used as a eliminated individual of the genetic algorithm, the optimal path is returned to the optimal path selection module 401 to recalculate the optimal path, and if the current calculation result meets the requirement, the generated operation ticket is transmitted to the operation system 500.
The operating system 500 directly controls each module, maintains and updates the database module 300 and the knowledge rule base module 400, imports an operation order instruction and exports an optimal path operation order to a human-computer interaction interface, the operating system 500 is used as a communication core of the human-computer interaction interface and each module, and all instructions and results are controlled by the operating system 500.
The working principle is as follows: determining the billing type and the operation task on the human-computer interaction interface 100, selecting the ticket type by an operator, judging whether an optimal path needs to be calculated by the operation system 500, if not, searching a historical operation ticket meeting the requirement in the database, if so, determining the initial topological structure of the power grid by the power data in the database and the switch state in the knowledge rule base, analyzing the topological structure by the inference module 400 by using graph theory and genetic algorithm, calculating the scheme of the optimal path by the optimal path selection module 401, verifying whether the scheme meets the system reliability by the power flow calculation module 402, otherwise, returning to the optimal path calculation module to recalculate the optimal path until the system reliability requirement is met, generating the operation ticket by the operation rule, and returning to the human-computer interaction interface to automatically print the ticket.
It should be recognized that embodiments of the present invention can be realized and implemented by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer readable memory. The methods may be implemented in a computer program using standard programming techniques, including a non-transitory computer-readable storage medium configured with the computer program, where the storage medium so configured causes a computer to operate in a specific and predefined manner, according to the methods and figures described in the detailed description. Each program may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.
Further, the operations of processes described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes described herein (or variations and/or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) collectively executed on one or more processors, by hardware, or combinations thereof. The computer program includes a plurality of instructions executable by one or more processors.
Further, the method may be implemented in any type of computing platform operatively connected to a suitable interface, including but not limited to a personal computer, mini computer, mainframe, workstation, networked or distributed computing environment, separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, and the like. Aspects of the invention may be embodied in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, optically read and/or write storage medium, RAM, ROM, or the like, such that it may be read by a programmable computer, which when read by the storage medium or device, is operative to configure and operate the computer to perform the procedures described herein. Further, the machine-readable code, or portions thereof, may be transmitted over a wired or wireless network. The invention described herein includes these and other different types of non-transitory computer-readable storage media when such media include instructions or programs that implement the steps described above in conjunction with a microprocessor or other data processor. The invention also includes the computer itself when programmed according to the methods and techniques described herein. A computer program can be applied to input data to perform the functions described herein to transform the input data to generate output data that is stored to non-volatile memory. The output information may also be applied to one or more output devices, such as a display. In a preferred embodiment of the invention, the transformed data represents physical and tangible objects, including particular visual depictions of physical and tangible objects produced on a display.
As used in this application, the terms "component," "module," "system," and the like are intended to refer to a computer-related entity, either hardware, firmware, a combination of hardware and software, or software in execution. For example, a component may be, but is not limited to being: a process running on a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of example, both an application running on a computing device and the computing device can be a component. One or more components can reside within a process and/or thread of execution and a component can be localized on one computer and/or distributed between two or more computers. In addition, these components can execute from various computer readable media having various data structures thereon. The components may communicate by way of local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from one component interacting with another component in a local system, distributed system, and/or across a network such as the internet with other systems by way of the signal).
It should be noted that the above-mentioned embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.

Claims (10)

1. An optimal path selection method suitable for operation tickets, characterized by comprising:
collecting the billing type and the operation task information and selecting the ticket sample type;
judging whether an optimal path needs to be calculated, if so, determining an initial topological structure of the power grid according to the power data in the database and the switch state in the knowledge rule base;
analyzing the initial topological structure of the power grid by using graph theory and a genetic algorithm, and calculating and selecting an optimal power supply path;
performing load flow calculation on the optimal power supply path scheme, and judging whether load flow distribution meets the requirement of system reliability;
if not, continuously searching an optimal power supply path;
if the optimal path is met, generating an operation ticket according to the operation rule, automatically printing a ticket sample, and completing the selection of the optimal path.
2. The optimal path selection method for operation tickets according to claim 1, characterized in that: the analyzing the initial topology of the power grid using a genetic algorithm includes,
acquiring the initial topological structure of the power grid, forming a node branch incidence matrix A, and acquiring the connection relation of the node branches;
forming an initial switch state vector according to the real-time switch state, and indicating whether the corresponding switch is closed or open;
forming a population by the switching state codes of each individual, comparing the population with the initial switching state vector to obtain switching times S, and determining a selection factor, a cross factor and a variation factor by taking the minimum switching times as an adaptive function to form a new population;
obtaining a node admittance matrix Y according to the node branch incidence matrix A and system parameters;
selecting individuals in the previous generation population to enter the next generation population according to the selection factors, selecting individuals through the cross factors to perform cross coding to enter a new population, and selecting individuals through the variation factors to perform coding change to enter the new population;
and judging whether the number of inheritance times is reached, if so, carrying out the next step, and if not, returning to the previous step.
3. The optimal path selection method for operation tickets according to claim 2, characterized in that: performing a power flow calculation on the optimal power supply path plan includes,
and (3) carrying out load flow calculation by adopting a Newton Raphson strategy:
and carrying out load flow calculation on the obtained individuals, and judging whether the power, the voltage and the current are out of limit or not.
4. The optimal path selection method for operation tickets according to any one of claims 1 to 3, characterized in that: the determination of the optimal switching path may include,
when the power, the voltage and the current are out of limit, setting the genetic times as 0 again, carrying out selection, crossing and mutation operations, eliminating individuals with fitness function values equal to the maximum value, namely the individuals which cannot meet the tidal current calculation verification, obtaining a new optimal path scheme after the genetic times reach the specified times, and calculating the tidal current distribution;
and when the power, the voltage and the current are not out of limit, outputting an optimal switching path, and finishing the algorithm.
5. An optimal path selection system for operation tickets, comprising:
the human-computer interaction interface (100) is used for inputting a program and an operation instruction for judging the optimal path and updating the contents of the knowledge rule base module (200) and the database module (300) according to the program and the instruction;
the database module (300) is used for providing power data and historical operation tickets required by the reasoning module (400), and the rule base module (200) is used for providing states of all components and operation ticket generation rules;
the inference module (400) comprises an optimal path selection module (401) and a power flow calculation module (402), wherein the optimal path selection module (401) is used for processing the power data provided by the database module (200) to generate an operation order of an optimal path, and the power flow calculation module (402) is connected with the optimal path selection module (401) to judge whether the power flow distribution under the optimal path meets the system requirements.
6. The optimal path selection system for an operation ticket according to claim 5, wherein: the system also comprises an operating system (500) used for realizing the comprehensive management of each module.
7. The optimal path selection system for an operation ticket according to claim 6, wherein: the human-computer interaction interface (100) provides a visual operation interface, an operator can conveniently manage the system and each module, and the human-computer interaction interface (100) indirectly controls each module through the operation system (500) to update the contents of the database module (300) and the knowledge rule base module (200).
8. The optimal path selection system for an operation ticket according to claim 7, wherein: the human-computer interaction interface (100) guides a genetic algorithm program which is manually input into the optimal path selection module (401), guides an operation instruction which needs to be completed into the reasoning module (400), and displays an optimal path operation ticket obtained by the reasoning module (400) on the interface to realize an automatic ticket drawing function.
9. The optimal path selection system for an operation ticket according to claim 8, wherein: the knowledge rule base module (200) stores various logic rules required by the state of the equipment and the generation of the operation ticket, and the logic rules are controlled by the program of the operating system (500) and are managed, added and modified as required.
10. The optimal path selection system for an operation ticket according to claim 9, wherein: the optimal path selection module (401) generates an optimal path operation ticket through a genetic algorithm, the power flow calculation module (402) performs power flow calculation on the power system under the optimal path, judges whether power flow distribution under the optimal path meets system requirements or not, transmits the generated operation ticket to the operation system (500) if the power flow distribution under the optimal path meets the system requirements, takes the path as a eliminated individual of the genetic algorithm if the power flow distribution under the optimal path does not meet the system requirements, and returns to the optimal path selection module (401) to recalculate the optimal path.
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