CN115225560A - Route planning method in power communication service - Google Patents
Route planning method in power communication service Download PDFInfo
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- CN115225560A CN115225560A CN202210837342.3A CN202210837342A CN115225560A CN 115225560 A CN115225560 A CN 115225560A CN 202210837342 A CN202210837342 A CN 202210837342A CN 115225560 A CN115225560 A CN 115225560A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/02—Topology update or discovery
- H04L45/08—Learning-based routing, e.g. using neural networks or artificial intelligence
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/147—Network analysis or design for predicting network behaviour
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/12—Shortest path evaluation
- H04L45/121—Shortest path evaluation by minimising delays
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L45/00—Routing or path finding of packets in data switching networks
- H04L45/12—Shortest path evaluation
- H04L45/124—Shortest path evaluation using a combination of metrics
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The invention provides a route planning method in electric power communication service, which belongs to the technical field of electric power system communication and specifically comprises the following steps: performing flow prediction by adopting a prediction model based on a PSO-GBDT algorithm based on a data set to obtain predicted flow, wherein the data set comprises service flow data of the last 24 hours and service flow data of the same time in one week; based on the predicted flow, planning a path by adopting a routing planning algorithm based on CA-Q-Learning to obtain a planning result, and performing time delay evaluation based on the planning result to obtain an evaluation result; and selecting a planning result meeting the time delay limit value according to the evaluation result, and selecting a planning result with the minimum time delay property of which the balance degree is smaller than a first threshold value from the planning results meeting the time delay property limit value, so that the requirement of the balance degree is ensured, and the minimum time delay property of the final planning result can be realized.
Description
Technical Field
The invention belongs to the technical field of power system communication, and particularly relates to a route planning method in a power communication service.
Background
The power communication network serves as an important infrastructure for bearing information interaction between power systems, serves all links of production and management of the power systems, and effectively guarantees safe, stable, economic and efficient operation of the power network. With the continuous deepening of the construction of the smart power grid, more and more services are carried by the power communication network, once the power communication network fails, the safe and stable operation of the large power grid is directly influenced, and therefore how to reasonably distribute service routes is an important content in the current power communication research field. Due to the randomness of the faults, if the mode of the common shortest route is selected, a large amount of traffic is concentrated in some links, so that the links become high-risk links. Therefore, the balanced distribution of the services is set as an optimization target of a power communication routing mode, and a corresponding routing optimization algorithm is provided, so that the operation risk of a power communication network can be reduced, the reliability of the communication network and the utilization rate of communication resources are improved, and the method has practical significance for ensuring the safe, stable and reliable operation of a large power grid.
Authors of the thesis "intelligent routing allocation method for dynamic service demand of power internet of things" have a strong idea that service traffic can be predicted accurately in real time and bandwidth is allocated to services efficiently, and a route with the minimum comprehensive risk is allocated to services based on the predicted service traffic and the allocated bandwidth, so as to ensure reliable and stable operation of a power system effectively.
Aiming at the technical problem, the invention provides a route planning method in the electric power communication service.
Disclosure of Invention
In order to realize the purpose of the invention, the invention adopts the following technical scheme:
according to one aspect of the invention, a route planning method in electric power communication service is provided.
A method for planning a route in an electric power communication service is characterized by specifically comprising the following steps:
s11, traffic prediction is carried out on the basis of a data set by adopting a prediction model based on a PSO-GBDT algorithm to obtain predicted traffic, wherein the data set comprises traffic data of the last 24 hours and traffic data of the same time in one week.
And S12, planning a path by adopting a routing planning algorithm based on CA-Q-Learning based on the predicted flow to obtain a planning result, and performing time delay evaluation based on the planning result to obtain an evaluation result.
S13, aiming at the evaluation result, selecting a planning result meeting the time delay limit value, and selecting a planning result with the minimum time delay with the balance degree smaller than a first threshold value from the planning results meeting the time delay limit value.
The method comprises the steps of firstly predicting flow by adopting a prediction model based on a PSO-GBDT algorithm, simultaneously predicting the flow by adopting a data set at the moment, wherein the data set at the moment comprises service flow data of the past 24 hours and service flow data at the same time in a week, so that the problem of inaccurate prediction result caused by only depending on the service flow data of the past 24 hours is solved, the prediction precision and reliability are further improved by combining the service flow data at the same time in a week, optimizing the initial value of the GBDT algorithm by adopting the PSO algorithm, solving the problem of low calculation efficiency caused by the fact that the initial value is not optimized by adopting the original prediction model based on a single algorithm, further improving the calculation efficiency and precision, improving the convergence speed, obtaining a planning result by adopting a route planning algorithm optimized based on a CA algorithm after obtaining the predicted flow, performing time delay evaluation on the planning result by adopting a time delay formula, obtaining an evaluation result, selecting a ductility planning result meeting the time delay requirement, obtaining the ductility planning result meeting the time delay requirement after obtaining the balancing degree after the planning result is obtained, setting a first threshold, meeting the best ductility requirement on the best ductility planning result, and obtaining a ductility planning scheme which can meet the best balance requirement on the best balance requirement when the best balance requirement, thereby not only obtaining a mixed scheme which is possible.
By adopting the PSO algorithm to optimize the initial value of the GBDT algorithm, the problem that the calculation efficiency is low because the initial value of the algorithm is not optimized by adopting a single algorithm-based prediction model in the prior art is solved, the calculation efficiency and precision are further improved, and the convergence speed is improved. The accuracy and reliability of prediction are further improved and the robustness of the whole model is improved by the aid of service flow data based on the past 24 hours and service flow data at the same time in a week, planning of a path is performed by the aid of a route planning algorithm based on CA algorithm optimization to obtain a planning result, the prediction efficiency and accuracy of the algorithm are improved, the overall efficiency is further improved, the planning result meeting the ductility limit is selected firstly, and the planning result with the minimum delay performance and the balance degree smaller than a first threshold is selected on the basis of the planning result, so that the final planning result meets the requirement of the balance degree, and the overall delay performance is minimized.
A further technical solution is characterized in that the data set includes past 24-hour traffic data, past 24-hour average traffic data, same-time-of-week traffic data, past 24-hour power load data, and temperature.
The influence on the service flow data is not only the conventional service flow data but also the size of the power load data and the fluctuation of the power load data caused by the temperature, so that the above quantity is added into the data set, the overall prediction accuracy and robustness are further improved, in addition, the average flow data and the average service flow data in the past 24 hours are added by not only adopting the service flow data in the past 24 hours, and the stability and reliability of the prediction of the service flow data are further improved, and the influence of the problem of inaccurate prediction caused by the huge fluctuation of the service flow in a single day is reduced.
A further technical means is characterized in that the past 24-hour traffic flow data is past 24-hour traffic flow data, and the past 24-hour power load data is past 24-hour power load data.
The method is characterized in that principal component analysis is carried out on the data set by adopting a principal component analysis method based on PCA, dimensionality reduction is carried out on the data set to obtain a dimensionality reduction data set, and flow prediction is carried out based on the dimensionality reduction data set.
The principal component analysis is carried out by adopting a Principal Component Analysis (PCA) method, so that the data set is further reduced, and the prediction precision is further improved on the basis of ensuring the prediction precision.
The further technical scheme is that the PSO-GBDT algorithm optimizes the learning rate of the GBDT algorithm and the number of basic models by adopting the PSO algorithm.
A further technical solution is characterized in that the planning result satisfying the time-ductility limit is a planning result in which the time-delay property is smaller than a first time-delay threshold.
The further technical scheme is that the first time delay threshold value is determined according to the importance degree of the predicted flow and the scale of the predicted flow.
By setting the first time delay threshold, the planning result can be accurately ensured to meet the time delay requirement from the data perspective, and the first time delay threshold is determined by taking the importance degree of the predicted flow and the scale of the predicted flow as the reference, so that the reliability and the accuracy of the threshold are also ensured.
The further technical scheme is that the evaluation process of the balance degree comprises the following steps:
s21, extracting the planning result meeting the time delay limit value;
s22, endowing the importance degree of the predicted flow in different lines in the planning result with a balance weight value;
s23, calculating the balance degree based on the balance degree weight and the planning result, and extracting all the planning results with the balance degree smaller than a first threshold value.
The balance degree weight is given according to the importance degree of the predicted flow, so that the balance degree does not only consider the balance problem of single flow in the evaluation process, but the more important the flow data is, for example, the importance of the transmission of the flow data of different data centers is definitely inconsistent with the importance of the flow transmission of a transformer substation and the data center, and further the balance degree obtained by the evaluation becomes more reliable and effective.
The further technical scheme is that the specific calculation formula of the balance degree is as follows:
wherein N is i For the predicted traffic passing on the ith link, k i Is the weight on the predicted traffic passing on the ith link, W is the total number of links, P is the degree of balance,
is the average of the predicted flow.
In another aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed in a computer, the computer program causes the computer to execute the method for route planning in power communication service described above.
In another aspect, a computer program product is provided in an embodiment of the present application, where the computer program product stores instructions that, when executed by a computer, cause the computer to implement the method for route planning in electric power communication service described above. .
Drawings
The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.
Fig. 1 is a flowchart of a route planning method in an electric power communication service according to embodiment 1.
Fig. 2 is a flowchart of an evaluation process of the degree of equalization according to embodiment 1.
Fig. 3 is a structural diagram of a computer-readable storage medium according to embodiment 2.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and thus a detailed description thereof will be omitted.
The terms "a," "an," "the," "said" are used to indicate the presence of one or more elements/components/etc.; the terms "comprising" and "having" are intended to be inclusive and mean that there may be additional elements/components/etc. other than the listed elements/components/etc.
The power communication network is used as an important infrastructure for bearing information interaction between power systems, serves all links of production and management of the power systems, and effectively guarantees safe, stable, economical and efficient operation of a power grid. With the continuous deepening of the construction of the smart power grid, more and more services are carried by the power communication network, once the power communication network fails, the safe and stable operation of the large power grid is directly influenced, and therefore how to reasonably distribute service routes is an important content in the current power communication research field. Due to the randomness of the faults, if the mode of the common shortest route is selected, a large amount of traffic is concentrated in some links, so that the links become high-risk links. Therefore, the balanced distribution of the services is set as an optimization target of a power communication routing mode, a corresponding routing optimization algorithm is provided, the operation risk of a power communication network can be reduced, the reliability of the communication network and the utilization rate of communication resources are improved, and the method has practical significance for guaranteeing safe, stable and reliable operation of a large power grid.
The authors of the thesis, "intelligent routing allocation method for dynamic service demand of power internet of things," widely spread the fact that service traffic can be accurately predicted in real time, bandwidth is efficiently allocated to services, and a route with the minimum comprehensive risk is allocated to services based on the predicted service traffic and the allocated bandwidth, so as to effectively guarantee reliable and stable operation of a power system, but only after the time delay in the path planning in the communication service demand of the power system meets the requirement, the equalization degree can be evaluated, if the two are mixed, a possibly obtained scheme cannot obtain an optimal time-lapse scheme, and when service traffic prediction is performed, service traffic data at a time when a contract is not finished is predicted, only service traffic data in the past 24 hours is used for low prediction accuracy, and a prediction model based on a single algorithm is used for not performing initial value optimization on the algorithm, so that the calculation efficiency is not high.
Example 1
To solve the above problem, according to an aspect of the present invention, as shown in fig. 1, a method for route planning in power communication service is provided.
A method for planning a route in an electric power communication service is characterized by specifically comprising the following steps:
s11, traffic prediction is carried out on the basis of a data set by adopting a prediction model based on a PSO-GBDT algorithm to obtain predicted traffic, wherein the data set comprises traffic data of the last 24 hours and traffic data of the same time in one week.
And S12, planning a path by adopting a routing planning algorithm based on CA-Q-Learning based on the predicted flow to obtain a planning result, and performing time delay evaluation based on the planning result to obtain an evaluation result.
S13, aiming at the evaluation result, selecting a planning result meeting the time delay limit value, and selecting a planning result with the minimum time delay with the balance degree smaller than a first threshold value from the planning results meeting the time delay limit value.
For example, in all the planning results, the time delay property in the first planning result is 20ms, the equalization degree is 0.8, the time delay property in the second planning result is 10ms, the equalization degree is 0.9, the time delay property in the third planning result is 5ms, the equalization degree is 0.95, and the first threshold value is 0.91, then the selected result is the second planning result.
The method comprises the steps of firstly predicting flow by adopting a prediction model based on a PSO-GBDT algorithm, simultaneously predicting the flow by adopting a data set at the moment, wherein the data set at the moment comprises service flow data of the past 24 hours and service flow data at the same time in a week, so that the problem of inaccurate prediction result caused by only depending on the service flow data of the past 24 hours is solved, the prediction precision and reliability are further improved by combining the service flow data at the same time in a week, optimizing the initial value of the GBDT algorithm by adopting the PSO algorithm, solving the problem of low calculation efficiency caused by the fact that the initial value is not optimized by adopting the original prediction model based on a single algorithm, further improving the calculation efficiency and precision, improving the convergence speed, obtaining a planning result by adopting a route planning algorithm optimized based on a CA algorithm after obtaining the predicted flow, performing time delay evaluation on the planning result by adopting a time delay formula, obtaining an evaluation result, selecting a ductility planning result meeting the time delay requirement, obtaining the ductility planning result meeting the time delay requirement after obtaining the balancing degree after the planning result is obtained, setting a first threshold, meeting the best ductility requirement on the best ductility planning result, and obtaining a ductility planning scheme which can meet the best balance requirement on the best balance requirement when the best balance requirement, thereby not only obtaining a mixed scheme which is possible.
By adopting the PSO algorithm to optimize the initial value of the GBDT algorithm, the problem that the calculation efficiency is low because the initial value of the algorithm is not optimized by adopting a single algorithm-based prediction model in the prior art is solved, the calculation efficiency and precision are further improved, and the convergence speed is improved. The accuracy and reliability of prediction are further improved and the robustness of the whole model is improved by using the service flow data of the past 24 hours and the service flow data of the same time in a week, the planning result is obtained by planning the path by using the route planning algorithm of Q-Learning optimized based on the CA algorithm, the prediction efficiency and the precision of the algorithm are improved, the whole efficiency is further improved, the planning result meeting the time-delay limit value is selected firstly, and the planning result with the minimum time-delay property and the balance degree smaller than the first threshold value is selected on the basis, so that the final planning result meets the requirement of the balance degree, and the whole time-delay property is minimized.
In a further possible embodiment, the data set comprises traffic flow data over the past 24 hours, average traffic flow data over the past 24 hours, traffic flow data at the same time of the week, power load data over the past 24 hours, temperature.
The influence on the service flow data is not only the conventional service flow data but also the size of the power load data and the fluctuation of the power load data caused by the temperature, so that the above quantity is added into the data set, the overall prediction accuracy and robustness are further improved, in addition, the average flow data and the average service flow data in the past 24 hours are added by not only adopting the service flow data in the past 24 hours, and the stability and reliability of the prediction of the service flow data are further improved, and the influence of the problem of inaccurate prediction caused by the huge fluctuation of the service flow in a single day is reduced.
In another possible embodiment, the traffic data of the past 24 hours is traffic data of each hour of the past 24 hours, and the power load data of the past 24 hours is power load data of each hour of the past 24 hours.
In another possible embodiment, the principal component analysis is performed on the data set by using a principal component analysis based PCA, the dimensionality reduction is performed on the data set to obtain a dimensionality reduction data set, and the flow prediction is performed based on the dimensionality reduction data set.
The principal component analysis is carried out by adopting a Principal Component Analysis (PCA) method, so that the data set is further reduced, and the prediction precision is further improved on the basis of ensuring the prediction precision.
In another possible embodiment, the PSO-GBDT algorithm optimizes the learning rate of the GBDT algorithm and the number of base models using the PSO algorithm.
In another possible embodiment, the planning result that satisfies the time delay limit is the planning result that the time delay performance is smaller than the first time delay threshold.
In another possible embodiment, the first delay threshold is determined according to the importance of the predicted flow and the size of the predicted flow.
By setting the first time delay threshold, the planning result can be accurately ensured to meet the time delay requirement from the data perspective, and the first time delay threshold is determined by taking the importance degree of the predicted flow and the scale of the predicted flow as the reference, so that the reliability and the accuracy of the threshold are also ensured.
In another possible embodiment, as shown in fig. 2, the equalization degree evaluation process is as follows:
s21, extracting the planning result meeting the time delay limit value;
s22, endowing the importance degree of the predicted flow in different lines in the planning result with a balance weight value;
s23, calculating the balance degree based on the balance degree weight and the planning result, and extracting all the planning results with the balance degree smaller than a first threshold value.
The balance degree weight is given according to the importance degree of the predicted flow, so that the balance degree does not only consider the balance problem of single flow in the evaluation process, but the more important the flow data is, for example, the importance of the transmission of the flow data of different data centers is definitely inconsistent with the importance of the flow transmission of a transformer substation and the data center, and further the balance degree obtained by the evaluation becomes more reliable and effective.
In another possible embodiment, the specific calculation formula of the equalization degree is:
wherein N is i For the predicted traffic passing on the ith link, k i The weight of the predicted traffic passing through the ith link, W is the total number of links, P is the balance,
to predict the average of flowAnd (4) average value.
Example 2
As shown in fig. 3, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed in a computer, the computer program causes the computer to execute the method of routing planning in electric power communication service.
Example 3
The present invention provides a computer program product, which is characterized in that the computer program product stores instructions, and when the instructions are executed by a computer, the instructions cause the computer to implement the method for route planning in electric power communication service.
In embodiments of the present invention, the term "plurality" means two or more unless explicitly defined otherwise. The terms "mounted," "connected," "secured," and the like are to be construed broadly, and for example, "connected" may be a fixed connection, a removable connection, or an integral connection. Specific meanings of the above terms in the embodiments of the present invention may be understood by those of ordinary skill in the art according to specific situations.
In the description of the embodiments of the present invention, it should be understood that the terms "upper", "lower", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience in describing the embodiments of the present invention and simplifying the description, but do not indicate or imply that the referred devices or units must have a specific direction, be configured in a specific orientation, and operate, and thus, should not be construed as limiting the embodiments of the present invention.
In the description herein, the appearances of the phrase "one embodiment," "a preferred embodiment," or the like, are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the embodiments of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes may be made to the present embodiment by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the embodiments of the present invention should be included in the protection scope of the embodiments of the present invention.
Claims (10)
1. A route planning method in power communication service is characterized by comprising the following steps:
s11, flow prediction is carried out by adopting a prediction model based on a PSO-GBDT algorithm based on a data set to obtain predicted flow, wherein the data set comprises the service flow data of the last 24 hours and the service flow data of the same time in a week.
S12, planning a path by adopting a routing planning algorithm based on CA-Q-Learning based on the predicted flow to obtain a planning result, and performing time delay evaluation based on the planning result to obtain an evaluation result.
S13, aiming at the evaluation result, selecting a planning result meeting the time delay limit value, and selecting a planning result with the minimum time delay with the balance degree smaller than a first threshold value from the planning results meeting the time delay limit value.
2. The method according to claim 1, wherein the data set includes past 24-hour traffic data, past 24-hour average traffic data, same-time-of-week traffic data, past 24-hour power load data, and temperature.
3. The method for planning routing in electric power communication service according to claim 2, wherein the past 24-hour service traffic data is service traffic data of each hour of the past 24 hours, and the past 24-hour power load data is power load data of each hour of the past 24 hours.
4. The routing planning method for power communication service according to claim 1, wherein a principal component analysis based on PCA is adopted to perform principal component analysis on the data set, dimension reduction is performed on the data set to obtain a dimension reduction data set, and flow prediction is performed based on the dimension reduction data set.
5. The method according to claim 1, wherein the PSO-GBDT algorithm optimizes the learning rate of the GBDT algorithm and the number of basic models by using the PSO algorithm.
6. The method for planning routing in electric power communication service according to claim 1, wherein the planning result that meets the ductility limit is a planning result that the delay performance is smaller than a first delay threshold.
7. The method for planning routing in electric power communication service according to claim 6, wherein the first time delay threshold is determined according to the importance degree of the predicted traffic and the size of the predicted traffic.
8. The method for planning a route in an electric power communication service according to claim 1, wherein the evaluation process of the balance degree is as follows:
s21, extracting the planning result meeting the time delay limit value;
s22, endowing the importance degree of the predicted flow in different lines in the planning result with a balance weight value;
s23, calculating the balance degree based on the balance degree weight and the planning result, and extracting all the planning results with the balance degree smaller than a first threshold value.
9. The method for planning a route in an electric power communication service according to claim 1, wherein a specific calculation formula of the balance degree is as follows:
wherein N is i For the predicted traffic passing on the ith link, k i The weight of the predicted traffic passing through the ith link, W is the total number of links, P is the balance,
is the average of the predicted flow rates.
10. A computer-readable storage medium, on which a computer program is stored, which, when executed in a computer, causes the computer to carry out a method of route planning in an electric power communication service according to any of claims 1-9.
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