Anti-interference optimization method in power communication network of networking SVG (Static Var Generator)

Abstract

The invention relates to the technical field of data processing, in particular to an anti-interference optimization method in a power communication network of a networking SVG, and the method comprises the steps: S1, carrying out the real-time collection of power communication state data, and S2, outputting an optimal anti-interference strategy, according to the method, strategy adjustment is carried out on the optimal anti-interference strategy through the step S3, and strategy updating and strategy optimization are carried out through the step S4. According to the method, the electric power communication state data is collected in real time, and the optimal anti-interference strategy is obtained, updated and optimized in real time, so that the anti-interference process in the communication network is optimized in real time, and the anti-interference accuracy and efficiency in the communication network are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to an anti-interference optimization method for a networked SVG power communication network. BACKGROUND

[0002] Under the background of the wide access of networked new energy power stations, the power communication network has become the core hub supporting the real-time perception, accurate control and stable operation of the power grid. However, with the evolution of power business from traditional production control to source-grid-load-storage coordination interaction, the communication network is facing increasingly severe interference challenges. On the one hand, the existing anti-interference technology has obvious problems of insufficient accuracy and efficiency. In terms of accuracy, the traditional interference discrimination method based on fixed threshold cannot dynamically adapt to complex time-varying interference characteristics, resulting in frequent misjudgment and omission, which cannot realize accurate identification and positioning of interference, and directly threatens the stable operation of the power grid.

[0003] The Chinese patent application file with publication number CN102573432A discloses a video anti-interference method in a satellite communication network system. 1) Electrostatic shielding is adopted for space radiation interference: that is, metal mesh grounding shielding is used to prevent the influence of high-frequency electromagnetic fields; the grounding of the shielding mainly has two types: floating with the signal ground and connecting to the ground; 2) Pulse anti-interference method for power supply voltage: suppression through AC voltage stabilizer and DC voltage stabilizer; anti-interference method for pulsating change of power supply: AC voltage stabilizer or UPS power supply in parallel mode is adopted; anti-interference method for I / O port line: digital filtering mode is adopted; interference to input and output switching quantity is anti-interfered by increasing the input and output amplitude of the switching quantity; for the interference of superimposing a series of discrete sharp pulses on the effective signal of the control quantity, the input is improved by software repeated detection. It can be seen that this scheme still has the problems of insufficient accuracy and low efficiency of anti-interference in the power communication network due to the lack of simulation and real-time optimization of the anti-interference process in the communication network. SUMMARY

[0004] Therefore, the present application provides an anti-interference optimization method for a networked SVG power communication network, which overcomes the problem of insufficient accuracy and low efficiency of anti-interference in the power communication network due to the lack of simulation and real-time optimization of the anti-interference process in the communication network in the prior art.

[0005] To achieve the above-mentioned purpose, the present application provides an anti-interference optimization method for a networked SVG power communication network, which comprises: Step S1, real-time collection of power communication state data is performed to obtain power communication state data; In step S2, the data interference index is obtained according to the power communication state data, the interference type is obtained according to the data interference index, the packet loss rate is calculated according to the power communication state data, the process of obtaining the interference type is adjusted according to the packet loss rate, and the optimal anti-interference strategy is obtained according to the data interference index through the optimal anti-interference strategy obtaining method. In step S3, the optimal anti-interference strategy is adjusted according to the power communication state data. In step S4, the power communication interference SVG map is constructed according to the power communication state data, the interference optimization result is output according to the power communication interference SVG map and the optimal anti-interference strategy, the process of strategy adjustment is updated according to the interference optimization result, and the process of strategy updating is optimized according to the number of interference optimization failures in the period.

[0006] Further, in step S2, the data interference index is obtained according to the power communication state data, the state data features are obtained by performing feature transformation on the power communication state data, the state data features are input into the interference analysis model, and the data interference index output by the interference analysis model is obtained. In step S2, the data interference index is obtained according to the data interference index, the data interference index Gs is compared with the first preset data interference index Gs1 and the second preset data interference index Gs2, Gs1 < Gs2, the state of the data interference index is judged according to the comparison result, and the interference type is output according to the judgment result, wherein: When Gs ≤ Gs1, it is determined that the state of the data interference index is low, and the mild interference is output as the interference type; When Gs1 < Gs ≤ Gs2, it is determined that the state of the data interference index is moderate, and the moderate interference is output as the interference type; When Gs > Gs2, it is determined that the state of the data interference index is high, and the severe interference is output as the interference type.

[0007] Further, in step S2, the packet loss rate is calculated according to the power communication state data, the packet loss rate Ls is calculated according to the total data packet number Zs and the received data packet number Js, and Ls = [(Zs-Js) / Zs]×100% is set to obtain the packet loss rate Ls. In step S2, the process of obtaining the interference type is adjusted according to the packet loss rate, the packet loss rate Ls is compared with the preset packet loss rate Ls0, the compliance of the packet loss rate is judged according to the comparison result, and the process of obtaining the interference type is adjusted according to the judgment result, wherein: When Ls≤Ls0, it is determined that the compliance of the packet loss rate is up to standard, and the type adjustment is not performed on the acquisition process of the interference type; When Ls>Ls0, it is determined that the compliance of the packet loss rate is not up to standard, and the type adjustment is performed on the acquisition process of the interference type: the type adjustment is performed on the first preset data interference index Gs1 and the second preset data interference index Gs2 according to the type adjustment coefficient tz, and tz=0.7+0.21×e -（Ls-Ls0） , the adjusted first preset data interference index is Gs1', the adjusted second preset data interference index is Gs2', Gs1'=Gs1×tz, Gs2'=Gs2×tz, the adjusted first preset data interference index Gs1' is output as the first preset data interference index Gs1, the adjusted second preset data interference index Gs2' is output as the second preset data interference index Gs2, and the data interference index Gs is compared with the first preset data interference index Gs1 and the second preset data interference index Gs2 again.

[0008] Further, in the step S2, when the optimal anti-interference strategy is acquired by the optimal anti-interference strategy acquisition method according to the data interference index, the optimal anti-interference strategy acquisition method comprises: Step A01, constructing an interference strategy library, the interference strategy library comprising preset data interference indexes as indexes and optimal anti-interference strategies corresponding to the data interference indexes as associated contents; Step A02, comparing the data interference index with the preset data interference index, and outputting the optimal anti-interference strategy according to the comparison result, wherein: When the data interference index is consistent with the preset data interference index, the optimal anti-interference strategy corresponding to the preset data interference index is outputted; When the data interference index is inconsistent with the preset data interference index, the artificial setting is performed to obtain an artificial optimal anti-interference strategy, the artificial optimal anti-interference strategy is outputted as the optimal anti-interference strategy, and the preset data interference index and the optimal anti-interference strategy are added to the interference strategy library.

[0009] Further, in the step S3, when the acquisition process of the optimal anti-interference strategy is adjusted according to the power communication state data, the acquisition process of the optimal anti-interference strategy is adjusted according to the power communication state data by a strategy adjustment method; The strategy adjustment method comprises: Step S31, constructing a communication digital twin model according to the power communication state data, and performing simulation execution on the optimal anti-interference strategy according to the communication digital twin model to obtain target execution data; Step S32, according to the target execution data, the execution result deviation is obtained, and the optimal anti-interference strategy is adjusted according to the execution result deviation.

[0010] Further, in the step S31, when the communication digital twin model is constructed according to the power communication state data, the communication digital twin model is constructed according to the communication digital twin model construction method; The communication digital twin model construction method comprises: Step B01, according to the communication network point cloud data in the power communication state data, the communication network geometry model is geometrically constructed by 3D scanning technology, and the communication network geometry model is obtained; Step B02, the communication network geometry model is physically simulated by physical simulation software, and the communication network physical model is obtained; Step B02, the power communication state data is input into the communication network physical model to label the communication network physical model, and the labeled communication network simulation model is obtained, and the communication network simulation model is output as a communication digital twin model; In the step S31, the optimal anti-interference strategy is simulated and executed according to the communication digital twin model, and the target execution data is obtained.

[0011] Further, in the step S32, when the target execution data is input into the result deviation comparison model, the result deviation Sy output by the result deviation comparison model is obtained; In the step S32, the acquisition process of the optimal anti-interference strategy is adjusted according to the execution result deviation, the execution result deviation Sy is compared with the preset execution result deviation Sy0, the state of the execution result deviation is judged according to the comparison result, and the acquisition process of the optimal anti-interference strategy is adjusted according to the judgment result, wherein: When Sy≤Sy0, it is determined that the state of the execution result deviation is normal, and the acquisition process of the optimal anti-interference strategy is not adjusted; When Sy>Sy0, it is determined that the state of the execution result deviation is abnormal, and the optimal anti-interference strategy is adjusted: the target execution data is input into the interference analysis model, the data interference index output by the interference analysis model is obtained, and the optimal anti-interference strategy is output again according to the data interference index.

[0012] Further, in the step S4, when the power communication interference SVG map is constructed according to the power communication state data, the power communication interference SVG map is constructed according to the power communication state data by the power communication interference SVG map construction method; The communication interference SVG map construction method comprises: Step C01, vector graph conversion is performed on the power communication state data to obtain a power communication state vector graph; Step C02, initial construction is performed on an initial communication interference SVG map according to the power communication state vector graph to obtain the initial communication interference SVG map; Step C03, state visualization processing is performed on the initial communication interference SVG map to obtain a processed communication interference SVG map; Step C04, process visualization processing is performed on the processed communication interference SVG map to obtain the communication interference SVG map.

[0013] Further, in the step S4, when the power communication interference SVG map and the optimal anti-interference strategy are used to output the interference optimization result, the optimal anti-interference strategy is graphically simulated in the power communication interference SVG map to obtain target graphic data, rasterization processing is performed on the target graphic data to obtain target bitmap data, the target bitmap data is input into a graphic interference judgment model to obtain an interference optimization index Gv output by the graphic interference judgment model, the interference optimization index Gv is compared with a preset interference optimization index Gv0, the state of the interference optimization index is judged according to the comparison result, and the interference optimization result is output according to the judgment result, wherein: When Gv is greater than or equal to Gv0, it is determined that the state of the interference optimization index is up to the standard, and the success of the interference optimization is output as the interference optimization result; When Gv is less than Gv0, it is determined that the state of the interference optimization index is not up to the standard, and the failure of the interference optimization is output as the interference optimization result, and the process of strategy adjustment is updated; In the step S4, when the process of strategy adjustment is updated according to the interference optimization result, the preset execution result deviation Sy0 is updated according to a strategy update coefficient cz, and cz is set to 0.72+0.21×e -（Gv0-Gv） , wherein e is the base of natural logarithm, the updated preset execution result deviation is set to Sy0', and Sy0'=Sy0×cz, the updated preset execution result deviation Sy0' is output as the preset execution result deviation Sy0, and the execution result deviation Sy is compared with the preset execution result deviation Sy0 again.

[0014] Further, in the step S4, when the strategy optimization is performed on the process of strategy updating according to the number of intra-period interference optimization failures, the number of intra-period interference optimization failures Sz is obtained through the system local log, the number of intra-period interference optimization failures Sz is compared with the preset number of intra-period interference optimization failures Sz0, the state of the number of intra-period interference optimization failures is judged according to the comparison result, and the strategy optimization is performed on the process of strategy updating according to the judgment result, wherein: When Sz≤Sz0, it is determined that the state of the number of intra-period interference optimization failures is acceptable, and the strategy optimization is not performed on the process of strategy updating; When Sz>Sz0, it is determined that the state of the number of intra-period interference optimization failures is unacceptable, and the strategy optimization is performed on the process of strategy updating: the preset interference optimization index Gv0 is optimized according to the strategy optimization coefficient cm, cm=1.42-0.21×e is set, the optimized preset interference optimization index Gv0' is set, and Gv0'=Gv0×cm, the optimized preset interference optimization index Gv0' is output as the preset interference optimization index Gv0, and the interference optimization index Gv is compared with the preset interference optimization index Gv0 again. -（Sz-Sz0）

[0015] Compared with the prior art, the method has the beneficial effects that: the power communication state data is collected in real time through the step S1, so that the communication network can be anti-interference according to the power communication state data, the optimal anti-interference strategy is output through the step S2, so that the optimal anti-interference strategy can be matched under different data interference degrees, the accuracy of anti-interference in the communication power grid is improved, the optimal anti-interference strategy is adjusted through the step S3, the optimal anti-interference strategy is re-acquired according to the target execution data output by the communication digital twin model in time, so that the optimal anti-interference strategy can be calibrated in real time through simulation, and the strategy is updated and optimized through the step S4, so that the optimal anti-interference strategy can be updated in time according to the state of interference optimization, and the accuracy and efficiency of anti-interference in the communication network are improved. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 The flowchart of the anti-interference optimization method of the power communication network of the network SVG of the embodiment is shown; Figure 2 The flowchart of the strategy adjustment method of the embodiment is shown; Figure 3 The flowchart of the communication digital twin model construction method of the embodiment is shown; Figure 4 The flowchart of the communication interference SVG map construction method of the embodiment is shown.​ Detailed Implementation

[0017] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0018] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0019] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0020] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0021] Please see Figure 1 As shown, it is a flowchart illustrating the anti-interference optimization method in the power communication network of the SVG network in this embodiment. The method includes: Step S1: Real-time acquisition of power communication status data to obtain power communication status data; Step S2: Obtain the data interference index based on the power communication status data, obtain the interference type based on the data interference index, calculate the packet loss rate based on the power communication status data, adjust the interference type acquisition process based on the packet loss rate, and obtain the optimal anti-interference strategy based on the data interference index using the optimal anti-interference strategy acquisition method. Step S3: Adjust the optimal anti-interference strategy based on the power communication status data; In step S4, the power communication interference SVG map is constructed according to the power communication state data, the interference optimization result is output according to the power communication interference SVG map and the optimal anti-interference strategy, the strategy adjustment process is updated according to the interference optimization result, and the strategy updating process is optimized according to the number of interference optimization failures in the period.

[0022] Specifically, the network SVG power communication network anti-interference optimization method is applied to anti-interference terminals in the power communication network, such as power line carrier machines. The method collects power communication state data in real time, and acquires and updates and optimizes the optimal anti-interference strategy in real time, so as to simulate and optimize the anti-interference process in the communication network in real time, thereby improving the accuracy and efficiency of anti-interference in the communication network. The method collects power communication state data in real time through step S1, so as to facilitate subsequent anti-interference of the communication network according to the power communication state data. The method also outputs the optimal anti-interference strategy through step S2, so as to match the optimal anti-interference strategy under different data interference degrees, thereby improving the accuracy of anti-interference in the communication network. The method also adjusts the optimal anti-interference strategy through step S3, and reacquires the optimal anti-interference strategy according to the target execution data output by the communication digital twin model in time, so as to real-time calibrate the optimal anti-interference strategy through simulation. The method also updates and optimizes the strategy through step S4, so as to update the optimal anti-interference strategy in time according to the interference optimization state, thereby improving the accuracy and efficiency of anti-interference in the communication network.

[0023] Specifically, in step S1, the power communication state data is collected in real time, and the power communication state data includes the total number of data packets, the number of received data packets, the communication network point cloud data, the signal-to-noise ratio, the real-time traffic, and the bit error rate.

[0024] Specifically, the total number of data packets refers to the total number of data packets sent by the sending end in the communication network, and the received number of data packets refers to the total number of data packets received by the receiving end in the communication network. The embodiment does not limit the specific acquisition manner of the total number of data packets and the received number of data packets, and a person skilled in the related art can freely select according to actual needs, such as acquiring the total number of data packets and the received number of data packets by querying the interface counter of the network device. The communication network point cloud data refers to the point cloud data set of the morphology, texture and topological relationship between the devices and network lines in the communication network obtained by the laser radar. The signal-to-noise ratio refers to the ratio of the average power of the useful signal received in the communication network to the average power of the noise. The bit error rate refers to the ratio of the number of error bits to the total number of transmission bits in the process of transmitting data in the communication network. The embodiment does not limit the specific acquisition manner of the signal-to-noise ratio and the bit error rate, and a person skilled in the related art can freely select according to actual needs, such as acquiring through the management system of the communication network device. The real-time traffic refers to the amount of data passing through the network device port obtained by the network management system polling the network device port in a unit of time. The embodiment does not limit the specific time length of the unit of time, and a person skilled in the related art can freely select according to actual needs, such as setting the unit of time to 5 minutes in the embodiment.

[0025] Specifically, in the step S1, the power communication state data is collected in real time, so as to subsequently resist interference on the communication network according to the power communication state data.

[0026] Specifically, in the step S2, when the data interference index is acquired according to the power communication state data, the power communication state data is feature-transformed to obtain state data features, the state data features are input into the interference analysis model, and the data interference index output by the interference analysis model is obtained. In the step S2, when the interference type is acquired according to the data interference index, the data interference index Gs is compared with the first preset data interference index Gs1 and the second preset data interference index Gs2, Gs1 < Gs2, the state of the data interference index is judged according to the comparison result, and the interference type is output according to the judgment result, wherein: When Gs ≤ Gs1, it is determined that the state of the data interference index is low, and the mild interference is output as the interference type; When Gs1 < Gs ≤ Gs2, it is determined that the state of the data interference index is moderate, and the moderate interference is output as the interference type; When Gs > Gs2, it is determined that the state of the data interference index is high, and the severe interference is output as the interference type.

[0027] Specifically, the feature conversion refers to a process of converting power communication state data into a feature vector, and the embodiment does not limit the specific implementation manner of the feature conversion, and a person skilled in the art can freely choose according to actual needs, such as performing feature conversion through paython, the state data feature refers to a vector value obtained after feature conversion and describing the feature of power communication state data, the interference analysis model refers to a recurrent neural network model taking the state data feature as input data and taking a data interference index as output data, and the embodiment does not limit the specific construction manner of the interference analysis model, and a person skilled in the art can freely choose according to actual needs, such as taking the state data feature and the corresponding data interference index occurring in history as a training set to train the recurrent neural network model to obtain the interference analysis model, the data interference index refers to a degree of interference existing in the state data feature according to the interference analysis model, the first preset data interference index refers to a lower limit of a preset value for judging the state of the data interference index, and the second preset data interference index refers to an upper limit of a preset value for judging the state of the data interference index, and the embodiment does not limit the specific numerical value of the first preset data interference index Gs1 and the second preset data interference index Gs2, and a person skilled in the art can freely choose according to actual needs, such as setting Gs1=0.3 and Gs2=0.6 in the embodiment, the state of the data interference index refers to the degree of the data interference index, and the state of the data interference index includes low, medium and high.

[0028] Specifically, in the step S2, the type of interference is outputted so as to enable the staff to master the situation of data interference in the communication network in real time.

[0029] Specifically, in the step S2, the packet loss rate is calculated according to the power communication state data, the total data packet number Zs and the received data packet number Js are used to calculate the packet loss rate Ls, Ls=[(Zs-Js) / Zs]×100% is set, and the packet loss rate Ls is obtained. In the step S2, the type adjustment of the interference type acquisition process is performed according to the packet loss rate, the packet loss rate Ls is compared with a preset packet loss rate Ls0, the compliance of the packet loss rate is judged according to the comparison result, and the type adjustment of the interference type acquisition process is performed according to the judgment result, wherein: When Ls≤Ls0, it is determined that the compliance of the packet loss rate is up to the standard, and the type adjustment of the interference type acquisition process is not performed; When Ls>Ls0, it is determined that the packet loss rate does not meet the standard, and the type adjustment is performed on the interference type acquisition process: the type adjustment is performed on the first preset data interference index Gs1 and the second preset data interference index Gs2 according to the type adjustment coefficient tz, and tz=0.7+0.21×e -（Ls-Ls0） Gs1’=Gs1×tz, Gs2’=Gs2×tz, the adjusted first preset data interference index Gs1’ is output as the first preset data interference index Gs1, the adjusted second preset data interference index Gs2’ is output as the second preset data interference index Gs2, and the data interference index Gs is compared with the first preset data interference index Gs1 and the second preset data interference index Gs2 again.

[0030] Specifically, the preset packet loss rate refers to the preset value for judging the packet loss rate, and the specific value of the preset packet loss rate Ls0 is not limited in the embodiment, and can be freely selected by a person skilled in the art according to actual needs. For example, Ls0=1% is set in the embodiment. The packet loss rate meeting the standard refers to the meeting degree of the packet loss rate judged according to the packet loss rate and the preset packet loss rate. The packet loss rate meeting the standard includes meeting the standard and not meeting the standard. The constant term 0.7 of the type adjustment coefficient represents the minimum value of the type adjustment coefficient. The constant coefficient 0.21 of the type adjustment coefficient represents the variation range of the type adjustment coefficient. The variation trend of the type adjustment coefficient is to decrease from 0.91 to 0.7 and maintain constant.

[0031] Specifically, in the step S2, when the packet loss rate does not meet the standard, the first preset data interference index and the second preset data interference index are reduced in time to balance the influence of the packet loss rate on the interference type, so as to improve the identification accuracy of the interference type.

[0032] Specifically, in the step S2, when the optimal anti-interference strategy is acquired by the optimal anti-interference strategy acquisition method according to the data interference index, the optimal anti-interference strategy acquisition method comprises: Step A01, constructing an interference strategy library, the interference strategy library comprising preset data interference indexes as indexes and optimal anti-interference strategies corresponding to the data interference indexes as associated contents; Step A02, comparing the data interference index with the preset data interference index, and outputting the optimal anti-interference strategy according to the comparison result, wherein: When the data interference index is consistent with the preset data interference index, the optimal anti-interference strategy corresponding to the preset data interference index is output. When the data interference index is inconsistent with the preset data interference index, manual setting is performed to obtain a manually optimal anti-interference strategy, the manually optimal anti-interference strategy is output as an optimal anti-interference strategy, and the preset data interference index and the optimal anti-interference strategy are added to the interference strategy library.

[0033] Specifically, the interference strategy library refers to a data retrieval library with a preset data interference index as an index and an optimal anti-interference strategy corresponding to the preset data interference index as associated content. The preset data interference index refers to a preset index in the interference strategy library for retrieving the optimal anti-interference strategy corresponding to the preset data interference index. The optimal anti-interference strategy corresponding to the preset data interference index refers to the corresponding optimal anti-interference strategy in the interference strategy library that is retrieved according to the preset data interference index. This embodiment does not limit the specific acquisition method of the preset data interference index and the optimal anti-interference strategy corresponding to the preset data interference index, and a person skilled in the art can freely choose according to actual needs. For example, the data interference index and the corresponding optimal anti-interference strategy that have historically occurred can be input into the interference strategy library by the staff in advance. The optimal anti-interference strategy refers to an anti-interference strategy adopted in the power communication network for the data interference index, such as switching routes and enabling backup channels. The data interference index consistent with the preset data interference index refers to the case that the data interference index is exactly the same as the preset data interference index. The data interference index inconsistent with the preset data interference index refers to the case that the data interference index is not the same as the preset data interference index. The manual setting refers to the process of setting the optimal anti-interference strategy by a person skilled in the art.

[0034] Specifically, in the step S2, the optimal anti-interference strategy is output so as to match the optimal anti-interference strategy under different data interference degrees, thereby improving the accuracy and efficiency of anti-interference in the communication network.

[0035] Specifically, in the step S3, when the acquisition process of the optimal anti-interference strategy is adjusted according to the power communication state data, the acquisition process of the optimal anti-interference strategy is adjusted according to the power communication state data by the strategy adjustment method.

[0036] Please refer to Figure 2 Fig. 1 shows a flowchart of the strategy adjustment method of this embodiment, and the strategy adjustment method comprises: Step S31, constructing a communication digital twin model according to the power communication state data, and performing simulation execution of the optimal anti-interference strategy according to the communication digital twin model to obtain target execution data; Step S32, acquiring an execution result deviation according to the target execution data, and adjusting the optimal anti-interference strategy according to the execution result deviation.

[0037] Specifically, in the step S31, the communication digital twin model is constructed according to the power communication state data.

[0038] Please refer to Figure 3 The communication digital twin model construction method includes: Step B01, constructing a communication network geometric model according to communication network point cloud data in the power communication state data by a 3D scanning technology to obtain a communication network geometric model; Step B02, performing physical simulation on the communication network geometric model by a physical simulation software to obtain a communication network physical model; Step B02, inputting the power communication state data into the communication network physical model to perform data labeling on the communication network physical model to obtain a labeled communication network simulation model, and outputting the communication network simulation model as a communication digital twin model; In the step S31, the optimal anti-interference strategy is simulated and executed according to the communication digital twin model to obtain target execution data.

[0039] Specifically, the 3D scanning technology refers to an existing technology for creating a digital three-dimensional model identical to the real communication network in a computer according to the communication network point cloud data, the geometric construction refers to a process of constructing a communication network geometric model according to the geometric shape of the communication network by the 3D scanning technology, the physical simulation software refers to software for simulating physical phenomena and laws of the real communication network in a computer, such as ANSYS, the physical simulation refers to a process of adding physical properties and behavior rules to the communication network geometric model by the physical simulation software, the data labeling refers to a process of inputting the power communication state data into the communication network physical model for labeling, the simulation execution refers to a process of executing the optimal anti-interference strategy in the communication digital twin model, and the target execution data refers to the power communication state data reacquired after the simulation execution.

[0040] Specifically, in the step S31, the communication digital twin model is constructed to facilitate subsequent simulation and execution of the optimal anti-interference strategy according to the communication digital twin model, thereby saving simulation costs while improving the effectiveness of the optimal anti-interference strategy.

[0041] Specifically, in the step S32, when the execution result deviation is obtained according to the target execution data, the target execution data and the real execution data are input into a result deviation comparison model to obtain an execution result deviation Sy output by the result deviation comparison model. In the step S32, the execution result deviation Sy is compared with a preset execution result deviation Sy0, the state of the execution result deviation is judged according to the comparison result, and the process of obtaining the optimal anti-interference strategy is adjusted according to the judgment result, wherein: When Sy≤Sy0, it is determined that the state of the execution result deviation is normal, and the process of obtaining the optimal anti-interference strategy is not adjusted; When Sy> Sy0, it is determined that the state of the execution result deviation is abnormal, and the optimal anti-interference strategy is adjusted: the target execution data is input into the interference analysis model to obtain a data interference index output by the interference analysis model, and the optimal anti-interference strategy is output again according to the data interference index.

[0042] Specifically, the result deviation comparison model refers to a decision tree model taking the target execution data and the real execution data as input data and taking the execution result deviation as output data. The specific construction method of the result deviation comparison model is not limited in the embodiment, and can be freely selected by a person skilled in the art according to actual needs. For example, the historical target execution data is taken as category 1, the historical real execution data is taken as category 2, and the target execution data and the real execution data-category-execution result deviation is taken as the path of the decision tree model to train the decision tree model to obtain the result deviation comparison model. The execution result deviation refers to a numerical value measuring the difference between the target execution data and the real execution data according to the result deviation comparison model. The real execution data refers to the power communication state data obtained by executing the optimal anti-interference strategy in the real communication network. The preset execution result deviation refers to a preset value for judging the state of the execution result deviation. The specific numerical value of the preset execution result deviation Sy0 is not limited in the embodiment, and can be freely selected by a person skilled in the art according to actual needs. For example, Sy0=0.17 is set in the embodiment. The state of the execution result deviation refers to the normal degree of the execution result deviation according to the judgment of the execution result deviation and the preset execution result deviation. The state of the execution result deviation includes normal and abnormal.

[0043] Specifically, in the step S32, when the state of the execution result deviation is abnormal, the optimal anti-interference strategy is re-obtained according to the target execution data in time to calibrate the optimal anti-interference strategy in real time, so as to improve the effectiveness and timeliness of the optimal anti-interference strategy.

[0044] Specifically, in the step S4, the power communication interference SVG map is constructed according to the power communication state data.

[0045] Referring to Figure 4 As shown in the figure, it is a flowchart of the communication interference SVG map construction method of the embodiment, which includes: Step C01, vector graphics conversion is performed on the power communication state data to obtain a power communication state vector graph; Step C02, initial construction is performed on the initial communication interference SVG map according to the power communication state vector graph to obtain an initial communication interference SVG map; Step C03, state visualization processing is performed on the initial communication interference SVG map to obtain a processed communication interference SVG map; Step C04, process visualization processing is performed on the processed communication interference SVG map to obtain a communication interference SVG map.

[0046] Specifically, the vector graphics conversion refers to a process of representing data in the power communication state data with vector graphics, such as mathematical symbols, the initial construction refers to a process of combining the power communication state vector graph to obtain a vector graph representing the association between the power communication state data and the data in the power communication state data, the state visualization processing refers to a process of superimposedly displaying the link state on the processed communication interference SVG map in the form of color, animation and chart, such as representing the link state as unblocked with green, interrupted with red and warned with yellow, and the process visualization processing refers to a process of displaying the action of the execution layer in the form of animation, such as displaying the route switching path and the spectrum hopping process in the form of animation.

[0047] Specifically, in the step S4, the power communication interference SVG map is constructed to facilitate subsequent policy updating and policy optimization, thereby improving the accuracy and efficiency of the anti-interference in the communication network.

[0048] Specifically, in the step S4, when the optimal anti-interference strategy is output according to the power communication interference SVG map and the optimal anti-interference strategy, the optimal anti-interference strategy is graphically simulated in the power communication interference SVG map to obtain target graphic data, the target graphic data is rasterized to obtain target bitmap data, the target bitmap data is input into the graphic interference judgment model to obtain the interference optimization index Gv output by the graphic interference judgment model, the interference optimization index Gv is compared with the preset interference optimization index Gv0, the state of the interference optimization index is judged according to the comparison result, and the interference optimization result is output according to the judgment result, wherein: When Gv≥Gv0, it is determined that the state of the interference optimization index is up to standard, and the interference optimization success is output as the interference optimization result; When Gv<Gv0, it is determined that the state of the interference optimization index is not up to standard, and the interference optimization failure is output as the interference optimization result, and the strategy updating process of the strategy adjustment is performed.

[0049] In the step S4, when the strategy updating process of the strategy adjustment is performed according to the interference optimization result, the preset execution result deviation Sy0 is updated according to the strategy updating coefficient cz, cz=0.72+0.21×e is set, where e is the base of natural logarithm, the updated preset execution result deviation is set as Sy0', and Sy0'=Sy0×cz, the updated preset execution result deviation Sy0' is output as the preset execution result deviation Sy0, and the execution result deviation Sy is compared with the preset execution result deviation Sy0 again. -（Gv0-Gv）

[0050] ​Specifically, the graphic simulation refers to a process of executing the optimal anti-interference strategy in the communication interference SVG map, the target graphic data refers to the digital graphic changed in the communication interference SVG map obtained after the graphic simulation, the rasterization processing refers to a process of rendering the target graphic data in the memory into a fixed size, such as a 224x224 pixel bitmap, the graphic interference judgment model refers to a convolutional neural network model taking the target bitmap data as input data and taking the interference optimization index as output data, and the specific construction manner of the graphic interference judgment model is not limited in the embodiment, and the related technicians in the field can freely select according to actual needs, such as taking the historical target bitmap data and the corresponding interference optimization index as a training set to train the convolutional neural network model to obtain the graphic interference judgment model, the interference optimization index refers to a numerical value measuring the optimization degree of the interference after the graphic simulation, the preset interference optimization index refers to a preset value for judging the state of the interference optimization index, and the specific numerical value of the preset interference optimization index Gv0 is not limited in the embodiment, and the related technicians in the field can freely select according to actual needs, such as setting Gv0=0.9 in the embodiment, the state of the interference optimization index refers to the up-to-standard degree of the interference optimization index according to the judgment of the interference optimization index and the preset interference optimization index, the state of the interference optimization index includes up-to-standard and not up-to-standard, the constant term 0.72 of the strategy update coefficient represents the minimum value that the strategy update coefficient can reach, the constant coefficient 0.21 of the strategy update coefficient represents the change range of the strategy update coefficient, and the change trend of the strategy update coefficient is to decrease from 0.93 to 0.72 and maintain constant.

[0051] Specifically, in the step S4, by judging the state of the interference optimization index, when the state of the interference optimization index is not up-to-standard, the preset execution result deviation is reduced by the strategy update coefficient, so as to update the optimal anti-interference strategy in time according to the state of the interference optimization, thereby improving the accuracy and efficiency of the anti-interference in the communication network.

[0052] Specifically, in the step S4, when the strategy update process is optimized according to the number of interference optimization failures in the period, the number of interference optimization failures in the period Sz is obtained through the system local log, the number of interference optimization failures in the period Sz is compared with the preset number of interference optimization failures in the period Sz0, the state of the number of interference optimization failures in the period is judged according to the comparison result, and the strategy update process is optimized according to the judgment result, wherein: when Sz≤Sz0, it is determined that the state of the number of interference optimization failures in the period is acceptable, and the strategy update process is not optimized; When Sz > Sz0, the state of the number of failures of the interference optimization in the period is determined to be unacceptable, and the process of the strategy updating is subjected to strategy optimization: the preset interference optimization index Gv0 is subjected to strategy optimization according to a strategy optimization coefficient cm, and cm = 1.42 - 0.21 × e is set -（Sz-Sz0） wherein e is the base of the natural logarithm, the preset interference optimization index Gv0' after the optimization is set as Gv0' = Gv0 × cm, the preset interference optimization index Gv0' after the optimization is output as the preset interference optimization index Gv0, and the interference optimization index Gv is compared with the preset interference optimization index Gv0 again.

[0053] Specifically, the number of failures of the interference optimization in the period refers to the number of times that the state of the interference optimization index is determined to be substandard in the preset period, the preset number of failures of the interference optimization in the period refers to the preset value of the number of failures of the interference optimization in the period, and the specific value of the preset number of failures of the interference optimization in the period Sz0 and the preset period is not limited in the embodiment, and can be freely selected by the person skilled in the art according to the actual demand. For example, Sz0 = 5 times and the preset period is 24 h are set in the embodiment. The state of the number of failures of the interference optimization in the period refers to the acceptable degree of the number of failures of the interference optimization in the period, which is determined according to the number of failures of the interference optimization in the period and the preset number of failures of the interference optimization in the period. The state of the number of failures of the interference optimization in the period includes acceptable and unacceptable. The constant term 1.42 of the strategy optimization coefficient represents the maximum value of the strategy optimization coefficient. The constant coefficient 0.21 of the strategy optimization coefficient represents the variation range of the strategy optimization coefficient. The variation trend of the strategy optimization coefficient is from 0.21 to 1.42 and remains constant.

[0054] Specifically, in the step S4, when the state of the number of failures of the interference optimization in the period is unacceptable, the preset interference optimization index is increased by the strategy optimization coefficient, so as to reasonably reduce the influence of the number of failures of the interference optimization in the period on the strategy updating, thereby improving the accuracy and efficiency of the anti-interference in the communication network.

[0055] So far, the technical scheme of the present application has been described in combination with the preferred embodiments shown in the drawings, but the person skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. The person skilled in the art can make equivalent changes or replacements to the related technical features without departing from the principles of the present application, and the technical scheme after the changes or replacements will fall within the protection scope of the present application.

Claims

1. A method for anti-interference optimization in a power communication network of a networked SVG, characterized in that, The method comprises: Step S1, collecting power communication state data in real time to obtain power communication state data; Step S2, obtaining a data interference index according to the power communication state data, and obtaining an interference type according to the data interference index, calculating a packet loss rate according to the power communication state data, and adjusting the type of the interference type obtaining process according to the packet loss rate, and obtaining an optimal anti-interference strategy according to the data interference index through an optimal anti-interference strategy obtaining method; Step S3, adjusting the optimal anti-interference strategy according to the power communication state data; Step S4, constructing a power communication interference SVG map according to the power communication state data, outputting an interference optimization result according to the power communication interference SVG map and the optimal anti-interference strategy, updating the strategy according to the process of strategy adjustment according to the interference optimization result, and optimizing the process of strategy updating according to the number of interference optimization failures in the cycle.

2. The method of claim 1, wherein the method further comprises: In the step S2, when the data interference index is obtained according to the power communication state data, the power communication state data is feature transformed to obtain state data features, the state data features are input into an interference analysis model to obtain a data interference index Gs output by the interference analysis model; In the step S2, when the interference type is obtained according to the data interference index, the data interference index Gs is compared with the first preset data interference index Gs1 and the second preset data interference index Gs2, and Gs1 < Gs2, the state of the data interference index is judged according to the comparison result, and the interference type is output according to the judgment result, wherein: When Gs ≤ Gs1, it is determined that the state of the data interference index is low, and the mild interference is output as the interference type; When Gs1 < Gs ≤ Gs2, it is determined that the state of the data interference index is moderate, and the moderate interference is output as the interference type; When Gs > Gs2, it is determined that the state of the data interference index is high, and the severe interference is output as the interference type.

3. The method of claim 2, wherein the method further comprises: In the step S2, the packet loss rate Ls is calculated according to the total data packet number Zs and the received data packet number Js, and Ls = [(Zs-Js) / Zs]×100% is set to obtain the packet loss rate Ls; In the step S2, the packet loss rate Ls is compared with the preset packet loss rate Ls0, the compliance of the packet loss rate is judged according to the comparison result, and the type of the interference type obtaining process is adjusted according to the judgment result, wherein: When Ls ≤ Ls0, it is determined that the compliance of the packet loss rate is up to standard, and the type of the interference type obtaining process is not adjusted; When Ls>Ls0, it is determined that the packet loss rate does not meet the standard, and the type adjustment is performed on the interference type acquisition process: the first preset data interference index Gs1 and the second preset data interference index Gs2 are adjusted according to the type adjustment coefficient tz, and tz=0.7+0.21×e -（Ls-Ls0） , the first preset data interference index after adjustment is Gs1', the second preset data interference index after adjustment is Gs2', Gs1'=Gs1×tz, Gs2'=Gs2×tz, the first preset data interference index after adjustment Gs1' is output as the first preset data interference index Gs1, the second preset data interference index after adjustment Gs2' is output as the second preset data interference index Gs2, and the data interference index Gs is compared with the first preset data interference index Gs1 and the second preset data interference index Gs2 again.

4. The method of claim 3, wherein the method further comprises: In the step S2, when the optimal anti-interference strategy is obtained according to the data interference index through the optimal anti-interference strategy obtaining method, the optimal anti-interference strategy obtaining method comprises: Step A01, constructing an interference strategy library, the interference strategy library including preset data interference indexes as indexes and optimal anti-interference strategies corresponding to the data interference indexes as associated contents; Step A02, comparing the data interference index with the preset data interference index, and outputting the optimal anti-interference strategy according to the comparison result, wherein: when the data interference index is consistent with the preset data interference index, the optimal anti-interference strategy corresponding to the preset data interference index is outputted; when the data interference index is inconsistent with the preset data interference index, the artificial optimal anti-interference strategy is obtained through artificial setting, the artificial optimal anti-interference strategy is outputted as the optimal anti-interference strategy, and the preset data interference index and the optimal anti-interference strategy are added to the interference strategy library.

5. The method of claim 4, wherein the method further comprises: In the step S3, when the acquisition process of the optimal anti-interference strategy is adjusted according to the power communication state data, the acquisition process of the optimal anti-interference strategy is adjusted according to the power communication state data through the strategy adjustment method; The strategy adjustment method includes: Step S31, constructing a communication digital twin model according to the power communication state data, and simulating and executing the optimal anti-interference strategy according to the communication digital twin model to obtain target execution data; Step S32, acquiring an execution result deviation according to the target execution data, and adjusting the acquisition process of the optimal anti-interference strategy according to the execution result deviation.

6. The method of claim 5, wherein the method further comprises: In the step S31, the communication digital twin model is constructed according to the power communication state data, and the communication digital twin model is constructed according to the communication digital twin model construction method; The communication digital twin model construction method includes: Step B01, constructing a communication network geometric model according to communication network point cloud data in the power communication state data through a 3D scanning technology to obtain the communication network geometric model; Step B02, performing physical simulation on the communication network geometric model through a physical simulation software to obtain a communication network physical model; Step B02, inputting the power communication state data into the communication network physical model to perform data labeling on the communication network physical model to obtain a labeled communication network simulation model, and outputting the communication network simulation model as the communication digital twin model; In the step S31, the optimal anti-interference strategy is simulated and executed according to the communication digital twin model to obtain target execution data.

7. The method of claim 6, wherein the method further comprises: In the step S32, when the target execution data is inputted into the result deviation comparison model together with real execution data to obtain an execution result deviation Sy outputted by the result deviation comparison model; In the step S32, the acquisition process of the optimal anti-interference strategy is adjusted according to the execution result deviation, the execution result deviation Sy is compared with a preset execution result deviation Sy0, the state of the execution result deviation is judged according to the comparison result, and the acquisition process of the optimal anti-interference strategy is adjusted according to the judgment result, wherein: When Sy≤Sy0, it is determined that the state of the execution result deviation is normal, and no strategy adjustment is made to the process of obtaining the optimal anti-interference strategy; When Sy> Sy0, it is determined that the state of the execution result deviation is abnormal, and the optimal anti-interference strategy is adjusted: the target execution data is input into the interference analysis model to obtain a data interference index output by the interference analysis model, and the optimal anti-interference strategy is output again according to the data interference index.

8. The method of claim 7, wherein the method further comprises: In the step S4, when the power communication interference SVG map is constructed according to the power communication state data, the power communication interference SVG map is constructed according to the power communication state data by the power communication interference SVG map construction method; The communication interference SVG map construction method comprises: Step C01, vector graph conversion is performed on the power communication state data to obtain a power communication state vector graph; Step C02, initial construction is performed on an initial communication interference SVG map according to the power communication state vector graph to obtain the initial communication interference SVG map; Step C03, state visualization processing is performed on the initial communication interference SVG map to obtain a processed communication interference SVG map; Step C04, process visualization processing is performed on the processed communication interference SVG map to obtain the communication interference SVG map.

9. The method of claim 8, wherein the method further comprises: In the step S4, when the interference optimization result is output according to the power communication interference SVG map and the optimal anti-interference strategy, the optimal anti-interference strategy is graphically simulated in the power communication interference SVG map to obtain target graphic data, rasterization processing is performed on the target graphic data to obtain target bitmap data, the target bitmap data is input into a graphic interference judgment model to obtain an interference optimization index Gv output by the graphic interference judgment model, the interference optimization index Gv is compared with a preset interference optimization index Gv0, the state of the interference optimization index is judged according to the comparison result, and the interference optimization result is output according to the judgment result, wherein: When Gv≥Gv0, it is determined that the state of the interference optimization index is up to standard, and interference optimization success is output as the interference optimization result; When Gv< Gv0, it is determined that the state of the interference optimization index is not up to standard, and interference optimization failure is output as the interference optimization result, and the process of strategy adjustment is updated; In the step S4, when the policy updating is performed according to the interference optimization result and the policy adjustment process, the preset execution result deviation Sy0 is updated according to a policy updating coefficient cz, cz=0.72+0.21×e is set, e is the base of natural logarithm, the updated preset execution result deviation is set as Sy0', Sy0'=Sy0×cz, the updated preset execution result deviation Sy0' is output as the preset execution result deviation Sy0, and the execution result deviation Sy is compared with the preset execution result deviation Sy0 again. -（Gv0-Gv） wherein e is the base of natural logarithm, the updated preset execution result deviation is set as Sy0', and Sy0'=Sy0×cz, the updated preset execution result deviation Sy0' is output as the preset execution result deviation Sy0, and the execution result deviation Sy is compared with the preset execution result deviation Sy0 again.

10. The method of claim 8, wherein the method further comprises: In the step S4, when the process of strategy updating is optimized according to the number of interference optimization failures in a period, the number of interference optimization failures in a period Sz is obtained by a system local log, the number of interference optimization failures in a period Sz is compared with a preset number of interference optimization failures in a period Sz0, the state of the number of interference optimization failures in a period is judged according to the comparison result, and the process of strategy updating is optimized according to the judgment result, wherein: When Sz≤Sz0, it is determined that the state of the number of interference optimization failures in a period is acceptable, and the process of strategy updating is not optimized; When Sz>Sz0, the state of the number of times of failure of interference optimization in the cycle is determined to be unacceptable, and the process of strategy updating is subjected to strategy optimization: the preset interference optimization index Gv0 is subjected to strategy optimization according to a strategy optimization coefficient cm, and cm=1.42-0.21×e -（Sz-Sz0） wherein e is the base of natural logarithm, the preset interference optimization index after optimization is Gv0', and Gv0'=Gv0×cm, the preset interference optimization index after optimization Gv0' is output as the preset interference optimization index Gv0, and the interference optimization index Gv is compared with the preset interference optimization index Gv0 again.

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