CN117833236A - Intelligent power distribution network control method based on digital twin technology - Google Patents
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Abstract
The invention discloses a control method of an intelligent power distribution network based on a digital twin technology, relates to the technical field of intelligent power distribution networks, and aims to solve the problems of inaccurate data processing and inaccurate control and adjustment parameters of the power distribution network. The method for creating the image is presented to a user, so that the data controlled in the power distribution network can be better understood and interpreted, the accuracy and efficiency of decision making can be improved through data visualization, the cognition and understanding of the user on the digital twin technology can be improved, the optimized parameters are subjected to model construction, the essence and connotation of the data can be better reflected through the parameter data, the subsequent data processing and analysis are facilitated, the constructed curves and standard model curves are overlapped, the change trend and difference of the constructed curves and the standard model curves can be intuitively compared, the difference between different data can be highlighted, and the relative change among the different data can be found, so that the control effect and efficiency of the power distribution network can be improved.
Description
Technical Field
The invention relates to the technical field of intelligent power distribution networks, in particular to a control method of an intelligent power distribution network based on a digital twin technology.
Background
The intelligent power distribution network is based on the traditional power distribution network, and introduces advanced technical means such as intellectualization, informatization, internetworking and the like.
The Chinese patent with publication number of CN113807705A discloses a power distribution network planning method, device and terminal, mainly by utilizing the characteristic that a digital twin power distribution network is an accurate mirror image of a physical power distribution network in a digital space, real-time data are obtained from a digital twin power distribution network data layer, a digital twin power distribution network planning scheme set and an operation scene data set are constructed, a load evaluation objective function, a line loss evaluation objective function, an economic evaluation objective function and constraint conditions of the digital twin power distribution network operation are constructed, and according to the load evaluation objective function, the line loss evaluation objective function, the economic evaluation objective function and the constraint conditions, a digital twin power distribution network planning scheme evaluation result is given, and an optimal scheme is optimized, wherein the patent solves the problem of applying digital twin technology in the power distribution network, but has the following problems in actual operation:
1. the acquired power distribution network data is not subjected to fine parameter comparison with standard power distribution network data, so that power distribution network control and adjustment optimization are incomplete.
2. The data before control and the data after control are not compared in a more visual image, so that the power distribution network cannot be controlled in measures.
3. The data acquired in the power distribution network are not subjected to further data processing, so that the control accuracy is reduced due to inaccurate data acquisition quality.
Disclosure of Invention
The invention aims to provide an intelligent power distribution network control method based on a digital twin technology, wherein an image creation mode is presented to a user, so that control data in a power distribution network can be better understood and interpreted, the accuracy and efficiency of decision making can be improved through data visualization, meanwhile, the cognition and understanding of the user on the digital twin technology can be improved, the optimized parameters are subjected to model construction, the essence and connotation of the data can be better reflected through parameter data, the subsequent data processing and analysis are convenient, the constructed curves are overlapped with standard model curves, the change trend and difference of the curves can be intuitively compared, the difference between different data can be highlighted, the relative change among the different data can be found, the control effect and efficiency of the power distribution network can be improved, and the problems in the prior art can be solved.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a control method of an intelligent power distribution network based on a digital twin technology comprises the following steps:
s1: data to be processed by the digital twin technology in the power distribution network are received, wherein the received data comprise voltage data, tide data, monitoring data, energy saving data, load data and energy data, and the received data are standardized as power distribution network source data;
s2: respectively carrying out data processing on the power distribution network source data, wherein the data processing comprises data cleaning, data checking and data integrity detection, and marking the processed data as target power distribution network data;
s3: constructing a model of target power distribution network data, performing data simulation analysis on the constructed model, and optimizing and adjusting the data in the power distribution network according to the data subjected to the simulation analysis;
s4: and visually presenting the optimized and adjusted power distribution network data in a text and image mode, and transmitting the presented data to a display terminal.
Preferably, for the received data processed by the digital twin technique in S1, the method is used for:
the voltage data is obtained by measuring the voltage value of each measuring point in the power distribution network through an intelligent voltmeter, leading the measured voltage value into a data reader, and obtaining the voltage data of each measuring point from the data reader;
the power flow data is obtained by monitoring power flow data of each node in the power distribution network through a current detector, and transmitting the monitored power flow data through a sensor and a data acquisition device;
the monitoring data is to monitor the equipment state and the running condition in the power distribution network in real time and transmit the content of the real-time monitoring to a monitoring center through a communication network.
Preferably, for the received data processed by the digital twin technique in S1, the method is further used for:
the energy-saving data is obtained by acquiring energy consumption data of all nodes and equipment in the power distribution network, and the obtained energy consumption data is obtained by a sensor and a data acquisition device;
the load data is obtained by carrying out load data acquisition on electric load data in the power distribution network through the intelligent ammeter;
the energy data are obtained from electric power data, gas data and water energy data in the power distribution network, wherein the electric power data, the gas data and the water energy data are obtained from the intelligent ammeter, the intelligent water meter and the gas meter.
Preferably, the data cleaning for the power distribution network source data in the power distribution network in S2 is used for:
filling the obtained power distribution network source data with missing values, wherein the missing value filling is carried out by adopting a median statistical method;
repeating data removal is carried out after filling of the power distribution network source data missing values is completed;
performing abnormal value correction after removing the repeated data, wherein the abnormal value judgment is performed on the power distribution network source data from which the repeated data are removed, and the judged abnormal value is corrected;
the data format is unified after the abnormal value of the power distribution network source data is corrected;
and labeling the power distribution network source data with uniform format as first processing data.
Preferably, the data verification after data cleaning is performed on the power distribution network source data in the S2 is used for:
performing data verification on the first processed data through a CRC (cyclic redundancy check) method;
wherein the CRC check is a cyclic redundancy check;
the CRC checking flow is as follows:
dividing the first processing data by CRC codes;
the CRC code is a code formed by a binary bit string and polynomial data with coefficients of 0 and 1;
if the first processing data is divided by the CRC code, the operation result is a divisor, the first processing data is check qualified data, and the check qualified data is marked as second processing data;
if the first processing data is divided by the CRC code, the operation result is a division failure result, the first processing data is check failure data, the check failure data are obtained independently, and the check failure data are transmitted to a display terminal for manual checking.
Preferably, the data integrity detection after data verification is performed on the power distribution network source data in the S2 is used for:
the second processing data is subjected to integrity detection according to a checksum method;
dividing the second processing data into a plurality of data segments, and performing checksum calculation on each data segment;
comparing the data calculated by the checksum with the power distribution network source data, and confirming the comparison result;
data detection is carried out on the comparison result and a standard integrity rule, wherein the standard integrity rule is called from a database;
if the value of the comparison result is within the threshold range of the standard integrity rule, the comparison result accords with the integrity detection, and the second processing data which accords with the integrity detection is marked as the target power distribution network data;
if the value of the comparison result is not in the threshold range of the standard integrity rule, the comparison result does not accord with the integrity detection, the integrity detection is independently called, and the comparison result is transmitted to a display terminal for manual verification.
Preferably, the modeling for the target power distribution network data in S3 is used for:
respectively acquiring data parameters of voltage data, tide data, monitoring data, energy saving data, load data and energy data in target power distribution network data;
forward propagating the acquired data parameters, wherein each parameter data is propagated from a low level to a high level;
when the data result obtained by the propagation does not accord with the standard propagation result, performing back propagation, wherein the back propagation is to perform propagation training on the error of each parameter data from a high level to a bottom level;
preferably, the modeling for the target power distribution network data in S3 is further configured to:
the process of the back propagation training is as follows:
firstly, initializing and setting the weight of the parameter, and after the setting is completed, forward transmitting each parameter data through a convolution layer, a downsampling layer and a full-connection layer to obtain an output value;
when the error is larger than the expected value, the error is transmitted back to the network, and the errors of the full-connection layer, the downsampling layer and the convolution layer are obtained in sequence;
wherein the errors of each layer are the total errors of the network; when the error is equal to or smaller than the expected value, training is completed;
and constructing a model according to parameters of the data and marking the constructed model as target model data.
Preferably, the data simulation analysis for the model constructed in S3 is used for:
confirming each data parameter in the target model data, and constructing a curve for each confirmed data parameter;
performing curve overlapping on the constructed curve and standard model curve data;
after the curves are overlapped, the constructed curves are obtained independently without overlapping the standard model curves;
performing parameter conversion on a part where the independently obtained construction curve and the standard model curve are not overlapped;
taking the data with the converted parameters as optimized parameters;
and corresponding the optimized parameters to data attributes in the power distribution network, and carrying out parameter adjustment through each device in the power distribution network.
Preferably, for the presentation of the text and image modes of the power distribution network data in S4, the method is used for:
after optimizing and adjusting equipment in the power distribution network, monitoring the equipment and data in the power distribution network;
respectively acquiring the monitored data parameters and the data parameters before optimization adjustment, and respectively marking the parameters as the optimized parameters and the original parameters;
and respectively creating the optimized parameters and the original parameters, and respectively labeling the text attribute of each parameter in the created image.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the intelligent power distribution network control method based on the digital twin technology, the quality and the accuracy of data can be improved by data cleaning, so that the data analysis result is more reliable, the accuracy and the consistency of the data can be improved by correcting the abnormal value, the division operation is carried out through the CRC code, the checking flow is simpler, the checking error and the correcting capability are stronger, the error control is easier to realize in the power distribution network source data, the input error, the system fault and the network problem can be effectively found by carrying out the integrity detection, the problems can be corrected, the error is reduced, and the accuracy of the data is improved.
2. According to the intelligent power distribution network control method based on the digital twin technology, the parameter data can be subjected to forward propagation and backward propagation, the parameters can be optimized, the optimized parameters are subjected to model construction, the parameter data can better reflect the essence and meaning of the data, subsequent data processing and analysis are facilitated, the constructed curves and standard model curves are overlapped, the change trend and difference of the constructed curves and the standard model curves can be intuitively compared, the difference between different data can be highlighted, and the relative change between the different data can be found, so that the control effect and efficiency of the power distribution network can be improved.
3. The intelligent power distribution network control method based on the digital twin technology provided by the invention is presented to a user in a mode of image creation, so that the data controlled in the power distribution network can be better understood and interpreted, the accuracy and efficiency of decision making can be improved through data visualization, and the cognition and understanding of the user on the digital twin technology can be improved.
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FIG. 1 is a schematic diagram of the overall process of the present invention;
fig. 2 is a schematic overall flow chart of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to solve the problem that in the prior art, data to be controlled in a power distribution network is not obtained widely, so that data control of a later power distribution network is inaccurate, please refer to fig. 1 and 2, the present embodiment provides the following technical scheme:
a control method of an intelligent power distribution network based on a digital twin technology comprises the following steps:
s1: data to be processed by the digital twin technology in the power distribution network are received, wherein the received data comprise voltage data, tide data, monitoring data, energy saving data, load data and energy data, and the received data are standardized as power distribution network source data;
s2: respectively carrying out data processing on the power distribution network source data, wherein the data processing comprises data cleaning, data checking and data integrity detection, and marking the processed data as target power distribution network data;
the data cleaning can improve the quality and accuracy of the data, so that the data analysis result is more reliable, the data verification can enable the error detection and correction capability of the data to be stronger, the error control can be realized in the power distribution network source data more easily, the integrity detection can be carried out on the data, the abnormality and error in the data can be found and corrected, and the accuracy and the reliability of the data are improved;
s3: constructing a model of target power distribution network data, performing data simulation analysis on the constructed model, and optimizing and adjusting the data in the power distribution network according to the data subjected to the simulation analysis;
the model construction can enable the parameter data to better reflect the essence and meaning of the data, the follow-up data processing and analysis are facilitated, and the optimization adjustment can enable the power distribution network to acquire the data parameters to be controlled more accurately, so that the control effect and efficiency of the power distribution network can be improved;
s4: the optimized and adjusted power distribution network data are visually presented in a text and image mode, and the presented data are transmitted to a display terminal;
the data visualization can improve the accuracy and efficiency of decision making, and can also improve the cognition and understanding of users on digital twin technology.
For the received data processed by the digital twin technique in S1, the method is used for:
the voltage data is obtained by measuring the voltage value of each measuring point in the power distribution network through an intelligent voltmeter, leading the measured voltage value into a data reader, and obtaining the voltage data of each measuring point from the data reader;
the power flow data is obtained by monitoring power flow data of each node in the power distribution network through a current detector, and transmitting the monitored power flow data through a sensor and a data acquisition device;
the monitoring data is to monitor the equipment state and the running condition in the power distribution network in real time and transmit the content of the real-time monitoring to a monitoring center through a communication network.
The energy-saving data is obtained by acquiring energy consumption data of all nodes and equipment in the power distribution network, and the obtained energy consumption data is obtained by a sensor and a data acquisition device;
the load data is obtained by carrying out load data acquisition on electric load data in the power distribution network through the intelligent ammeter;
the energy data are obtained from electric power data, gas data and water energy data in the power distribution network, wherein the electric power data, the gas data and the water energy data are obtained from the intelligent ammeter, the intelligent water meter and the gas meter.
Specifically, the voltage data is obtained to effectively judge whether the voltage data used by the power distribution network needs to be subjected to voltage control, so that the safety of the voltage data in the power distribution network can be improved, the running efficiency of the power distribution network can be better optimized in the power distribution network control, the quality and stability of power supply are ensured, the monitoring data is obtained to realize remote monitoring and operation of the power distribution network in the power distribution network control, the reliability and response speed of a power system are improved, the energy-saving data is obtained to flexibly allocate and distribute power in the power distribution network control, the utilization efficiency of power resources is improved, the energy consumption and pollution are reduced, the running efficiency and the reliability of the power distribution network can be improved in the power distribution network control by obtaining the load data, the running mode and the scheduling strategy of the distributed energy are optimized in the power distribution network control by obtaining the energy data, the reliability and the economy of a power system are improved, and the accuracy of the power distribution network data control can be effectively improved by confirming the voltage data, the power flow data, the monitoring data, the energy-saving data, the load data and the energy data.
In order to solve the problem that in the prior art, data acquired in a power distribution network is not further processed, so that the quality of data acquisition is inaccurate, and the control precision is reduced, referring to fig. 1 and 2, the present embodiment provides the following technical scheme:
data cleaning for power distribution network source data in the power distribution network in S2 is used for:
filling the obtained power distribution network source data with missing values, wherein the missing value filling is carried out by adopting a median statistical method;
repeating data removal is carried out after filling of the power distribution network source data missing values is completed;
performing abnormal value correction after removing the repeated data, wherein the abnormal value judgment is performed on the power distribution network source data from which the repeated data are removed, and the judged abnormal value is corrected;
the data format is unified after the abnormal value of the power distribution network source data is corrected;
and labeling the power distribution network source data with uniform format as first processing data.
Specifically, the integrity of the data can be enhanced by filling the missing value of the power distribution network source data, so that the data analysis is more accurate and reliable, the data can be more easily understood and analyzed, abnormal fluctuation of the data caused by the missing value can be avoided, the quality and the accuracy of the data can be improved by deleting repeated, invalid or wrong data, the data analysis result is more reliable, the accuracy and the consistency of the data can be improved by correcting the abnormal value, and the data is subjected to uniform format so as to be convenient for subsequent data processing and analysis.
And (2) performing data verification after data cleaning on the power distribution network source data in the step (S2), wherein the data verification is used for:
performing data verification on the first processed data through a CRC (cyclic redundancy check) method;
wherein the CRC check is a cyclic redundancy check;
the CRC checking flow is as follows:
dividing the first processing data by CRC codes;
the CRC code is a code formed by a binary bit string and polynomial data with coefficients of 0 and 1;
if the first processing data is divided by the CRC code, the operation result is a divisor, the first processing data is check qualified data, and the check qualified data is marked as second processing data;
if the first processing data is divided by the CRC code, the operation result is a division failure result, the first processing data is check failure data, the check failure data are obtained independently, and the check failure data are transmitted to a display terminal for manual checking.
Specifically, the CRC can be used for performing faster check under the condition that the length of the information field and the check field of the power distribution network source data is not determined, meanwhile, the CRC code is used for performing division operation, the check flow is simpler, the check error detection and correction capability is stronger, and error control is easier to realize in the power distribution network source data.
And (2) detecting the data integrity after data verification of the power distribution network source data in the step (S2), wherein the data integrity is used for:
the second processing data is subjected to integrity detection according to a checksum method;
dividing the second processing data into a plurality of data segments, and performing checksum calculation on each data segment;
comparing the data calculated by the checksum with the power distribution network source data, and confirming the comparison result;
data detection is carried out on the comparison result and a standard integrity rule, wherein the standard integrity rule is called from a database;
if the value of the comparison result is within the threshold range of the standard integrity rule, the comparison result accords with the integrity detection, and the second processing data which accords with the integrity detection is marked as the target power distribution network data;
if the value of the comparison result is not in the threshold range of the standard integrity rule, the comparison result does not accord with the integrity detection, the integrity detection is independently called, and the comparison result is transmitted to a display terminal for manual verification.
Specifically, the integrity detection is performed after the power distribution network source data is subjected to data verification, the integrity detection is processed through a checksum method, the checksum method can adaptively process different types of data and has higher reliability, meanwhile, the integrity detection can effectively discover input errors, system faults and network problems and correct the problems, so that errors are reduced, the accuracy of the data is improved, and anomalies and errors in the data can be discovered and corrected through the integrity detection of the data, so that the accuracy and the reliability of the data are improved.
In order to solve the problem that in the prior art, the acquired power distribution network data is not subjected to fine parameter comparison with standard power distribution network data, so that the power distribution network is incomplete in control and adjustment optimization, referring to fig. 1 and 2, the following technical scheme is provided in this embodiment:
and (3) constructing a model aiming at the target power distribution network data in the step (S3), wherein the model is used for:
respectively acquiring data parameters of voltage data, tide data, monitoring data, energy saving data, load data and energy data in target power distribution network data;
forward propagating the acquired data parameters, wherein each parameter data is propagated from a low level to a high level;
when the data result obtained by the propagation does not accord with the standard propagation result, performing back propagation, wherein the back propagation is to perform propagation training on the error of each parameter data from a high level to a bottom level;
the process of the back propagation training is as follows:
firstly, initializing and setting the weight of the parameter, and after the setting is completed, forward transmitting each parameter data through a convolution layer, a downsampling layer and a full-connection layer to obtain an output value;
when the error is larger than the expected value, the error is transmitted back to the network, and the errors of the full-connection layer, the downsampling layer and the convolution layer are obtained in sequence;
wherein the errors of each layer are the total errors of the network; when the error is equal to or smaller than the expected value, training is completed;
and constructing a model according to parameters of the data and marking the constructed model as target model data.
Specifically, firstly, data with different attributes in target power distribution network data are respectively confirmed, wherein the attributes of the data are divided into attribute data of voltage data, tide data, monitoring data, energy-saving data, load data and energy data, when the parameter data in each attribute data are confirmed, each parameter data are respectively transmitted in the forward direction, when the parameter data are trained through forward transmission, the data which are finally lost can be obtained through each hidden layer when the parameter data are transmitted through the hidden layers, when the parameter data are transmitted in the backward direction, according to a gradient decreasing formula, the forward feedback is carried out layer by layer to form a backward transmission mechanism, parameters can be optimized, and when the optimized parameters are subjected to model construction, the parameter data can better reflect the essence and meaning of the data, so that the follow-up data processing and analysis are facilitated.
Data simulation analysis for the model constructed in S3 for:
confirming each data parameter in the target model data, and constructing a curve for each confirmed data parameter;
performing curve overlapping on the constructed curve and standard model curve data;
after the curves are overlapped, the constructed curves are obtained independently without overlapping the standard model curves;
performing parameter conversion on a part where the independently obtained construction curve and the standard model curve are not overlapped;
taking the data with the converted parameters as optimized parameters;
and corresponding the optimized parameters to data attributes in the power distribution network, and carrying out parameter adjustment through each device in the power distribution network.
Specifically, the parameters of each voltage data, tide data, monitoring data, energy-saving data, load data and energy data in the model data are subjected to curve construction, the constructed curve is overlapped with the standard model curve, the variation trend and the variation difference of the constructed curve and the standard model curve can be intuitively compared, the variation among different data can be highlighted, the relative variation among the different data can be found, the part without curve overlapping is obtained, the part without overlapping is used as final adjustment data, the data parameters to be controlled of the power distribution network can be more accurately obtained, and therefore the control effect and efficiency of the power distribution network can be improved.
In order to solve the problem that in the prior art, the data before control and the data after control are not subjected to more visual image comparison, so that the power distribution network cannot be subjected to measure control, referring to fig. 1 and 2, the following technical scheme is provided in this embodiment:
aiming at presentation of the text and image modes of the power distribution network data in the S4, the method is used for:
after optimizing and adjusting equipment in the power distribution network, monitoring the equipment and data in the power distribution network;
respectively acquiring the monitored data parameters and the data parameters before optimization adjustment, and respectively marking the parameters as the optimized parameters and the original parameters;
and respectively creating the optimized parameters and the original parameters, and respectively labeling the text attribute of each parameter in the created image.
Specifically, the monitored data parameters and the data parameters before optimization and adjustment are respectively subjected to image creation mode and presented to a user, so that the data controlled in the power distribution network can be better understood and explained. The data visualization can improve the accuracy and efficiency of decision making, and simultaneously can improve the cognition and understanding of a user on a digital twin technology, and simultaneously, each parameter in the created image is respectively marked with a text attribute, wherein the marking of the text attribute is to judge whether the parameter attribute is the attribute data of voltage data, tide data, monitoring data, energy-saving data, load data and energy data, so that the data can be focused on in a targeted manner, and the precaution efficiency of measures in a later-stage power distribution network is effectively improved.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. The intelligent power distribution network control method based on the digital twin technology is characterized by comprising the following steps of:
s1: data to be processed by the digital twin technology in the power distribution network are received, wherein the received data comprise voltage data, tide data, monitoring data, energy saving data, load data and energy data, and the received data are standardized as power distribution network source data;
s2: respectively carrying out data processing on the power distribution network source data, wherein the data processing comprises data cleaning, data checking and data integrity detection, and marking the processed data as target power distribution network data;
s3: constructing a model of target power distribution network data, performing data simulation analysis on the constructed model, and optimizing and adjusting the data in the power distribution network according to the data subjected to the simulation analysis;
s4: and visually presenting the optimized and adjusted power distribution network data in a text and image mode, and transmitting the presented data to a display terminal.
2. The intelligent power distribution network control method based on the digital twin technology as claimed in claim 1, wherein: for the received data processed by the digital twin technique in S1, the method is used for:
the voltage data is obtained by measuring the voltage value of each measuring point in the power distribution network through an intelligent voltmeter, leading the measured voltage value into a data reader, and obtaining the voltage data of each measuring point from the data reader;
the power flow data is obtained by monitoring power flow data of each node in the power distribution network through a current detector, and transmitting the monitored power flow data through a sensor and a data acquisition device;
the monitoring data is to monitor the equipment state and the running condition in the power distribution network in real time and transmit the content of the real-time monitoring to a monitoring center through a communication network.
3. The intelligent power distribution network control method based on the digital twin technology as claimed in claim 2, wherein: for the received data processed by the digital twin technique in S1, the method is further used for:
the energy-saving data is obtained by acquiring energy consumption data of all nodes and equipment in the power distribution network, and the obtained energy consumption data is obtained by a sensor and a data acquisition device;
the load data is obtained by carrying out load data acquisition on electric load data in the power distribution network through the intelligent ammeter;
the energy data are obtained from electric power data, gas data and water energy data in the power distribution network, wherein the electric power data, the gas data and the water energy data are obtained from the intelligent ammeter, the intelligent water meter and the gas meter.
4. A method of controlling a smart distribution network based on digital twinning technology as claimed in claim 3, wherein: data cleaning for power distribution network source data in the power distribution network in S2 is used for:
filling the obtained power distribution network source data with missing values, wherein the missing value filling is carried out by adopting a median statistical method;
repeating data removal is carried out after filling of the power distribution network source data missing values is completed;
performing abnormal value correction after removing the repeated data, wherein the abnormal value judgment is performed on the power distribution network source data from which the repeated data are removed, and the judged abnormal value is corrected;
the data format is unified after the abnormal value of the power distribution network source data is corrected;
and labeling the power distribution network source data with uniform format as first processing data.
5. The intelligent power distribution network control method based on the digital twin technology as claimed in claim 4, wherein: and (2) performing data verification after data cleaning on the power distribution network source data in the step (S2), wherein the data verification is used for:
performing data verification on the first processed data through a CRC (cyclic redundancy check) method;
wherein the CRC check is a cyclic redundancy check;
the CRC checking flow is as follows:
dividing the first processing data by CRC codes;
the CRC code is a code formed by a binary bit string and polynomial data with coefficients of 0 and 1;
if the first processing data is divided by the CRC code, the operation result is a divisor, the first processing data is check qualified data, and the check qualified data is marked as second processing data;
if the first processing data is divided by the CRC code, the operation result is a division failure result, the first processing data is check failure data, the check failure data are obtained independently, and the check failure data are transmitted to a display terminal for manual checking.
6. The intelligent power distribution network control method based on the digital twin technology as claimed in claim 5, wherein: and (2) detecting the data integrity after data verification of the power distribution network source data in the step (S2), wherein the data integrity is used for:
the second processing data is subjected to integrity detection according to a checksum method;
dividing the second processing data into a plurality of data segments, and performing checksum calculation on each data segment;
comparing the data calculated by the checksum with the power distribution network source data, and confirming the comparison result;
data detection is carried out on the comparison result and a standard integrity rule, wherein the standard integrity rule is called from a database;
if the value of the comparison result is within the threshold range of the standard integrity rule, the comparison result accords with the integrity detection, and the second processing data which accords with the integrity detection is marked as the target power distribution network data;
if the value of the comparison result is not in the threshold range of the standard integrity rule, the comparison result does not accord with the integrity detection, the integrity detection is independently called, and the comparison result is transmitted to a display terminal for manual verification.
7. The intelligent power distribution network control method based on the digital twin technology as claimed in claim 6, wherein: and (3) constructing a model aiming at the target power distribution network data in the step (S3), wherein the model is used for:
respectively acquiring data parameters of voltage data, tide data, monitoring data, energy saving data, load data and energy data in target power distribution network data;
forward propagating the acquired data parameters, wherein each parameter data is propagated from a low level to a high level;
and carrying out back propagation when the data result obtained by propagation does not accord with the standard propagation result, wherein the back propagation is to carry out propagation training on the error of each parameter data from a high level to the bottom layer.
8. The intelligent power distribution network control method based on the digital twin technology as claimed in claim 7, wherein: the modeling for the target power distribution network data in the S3 is further used for:
the process of the back propagation training is as follows:
firstly, initializing and setting the weight of the parameter, and after the setting is completed, forward transmitting each parameter data through a convolution layer, a downsampling layer and a full-connection layer to obtain an output value;
when the error is larger than the expected value, the error is transmitted back to the network, and the errors of the full-connection layer, the downsampling layer and the convolution layer are obtained in sequence;
wherein the errors of each layer are the total errors of the network; when the error is equal to or smaller than the expected value, training is completed;
and constructing a model according to parameters of the data and marking the constructed model as target model data.
9. The intelligent power distribution network control method based on the digital twin technology as claimed in claim 8, wherein: data simulation analysis for the model constructed in S3 for:
confirming each data parameter in the target model data, and constructing a curve for each confirmed data parameter;
performing curve overlapping on the constructed curve and standard model curve data;
after the curves are overlapped, the constructed curves are obtained independently without overlapping the standard model curves;
performing parameter conversion on a part where the independently obtained construction curve and the standard model curve are not overlapped;
taking the data with the converted parameters as optimized parameters;
and corresponding the optimized parameters to data attributes in the power distribution network, and carrying out parameter adjustment through each device in the power distribution network.
10. The intelligent power distribution network control method based on the digital twin technology as claimed in claim 9, wherein: aiming at presentation of the text and image modes of the power distribution network data in the S4, the method is used for:
after optimizing and adjusting equipment in the power distribution network, monitoring the equipment and data in the power distribution network;
respectively acquiring the monitored data parameters and the data parameters before optimization adjustment, and respectively marking the parameters as the optimized parameters and the original parameters;
and respectively creating the optimized parameters and the original parameters, and respectively labeling the text attribute of each parameter in the created image.
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