A distribution network safe operation monitoring system and method based on cloud platform

Abstract

The present invention discloses a distribution network safe operation monitoring system and method based on a cloud platform. On the basis of the corresponding relationship of monitoring data established by the early aging test, the cloud platform server can perform online drift identification and judgment according to the identified voltage sensor model and usage time, and can realize the drift identification, processing and correction of the output data of all voltage sensors in the distribution network, greatly improving the safety of the distribution network operation. In addition, on the basis of realizing the automatic identification and correction of the voltage sensor of the distribution network safe operation monitoring system, a manual sampling verification link is added to further verify the automatic correction result, realize the training and learning of the correction coefficient, and improve the accuracy of the correction.

Description

Technical Field

[0001] The present invention relates to a cloud platform-based distribution network safe operation monitoring system and method, and in particular to a distribution network voltage sensor operation monitoring system and method. Background Art

[0002] During the operation of the distribution network, the control center implements operation monitoring based on the voltage information of each device or component collected by the voltage sensors installed at each device in the distribution network, and controls the operation and dispatch of the power grid based on the collected voltage information. Hall voltage sensors are usually used. Since the power operation environment of the distribution network is generally harsh, the voltage sensor will age with the increase of usage time, and the detection output parameters will drift, resulting in inaccurate detection data. The dispatch control based on this detection data is also prone to cause grid operation shocks, and in severe cases, it will cause the grid to paralyze. Therefore, how to identify the drift of the voltage sensor detection data and how to realize the drift correction of the voltage sensor acquisition parameters are the key prerequisites for the safe operation and monitoring of the distribution network.

[0003] In the prior art, multiple voltage sensors are often used for cross-validation to achieve abnormal monitoring of the voltage sensor. For example, the invention patent application with publication number CN116165594A provides a voltage sensor fault diagnosis method, which actually obtains the voltage data of the target auxiliary converter output in real time, and judges the voltage data according to the operating sequence and the fault judgment rule corresponding to the operating sequence, so as to diagnose whether there is a fault in the output voltage sensor; the voltage data includes three internal voltage output data and three external voltage detection data, the internal voltage sensor is used to collect the three internal voltage output data, and the external voltage sensor is used to collect the three external voltage detection data. However, this method cannot accurately identify the drift of the voltage sensor output parameters, and the use of multiple voltage sensors will increase the difficulty of system operation data processing and increase the system setting cost.

[0004] In addition, the number of voltage sensors used in various devices of the distribution network system is huge. Using only the local control center database cannot timely process and correct the data of such a large number of voltage sensors. In addition, the computing power and data storage capacity of the local control center server are limited, which cannot meet the needs of the operation and dispatching control of the power grid.

[0005] Therefore, in order to solve the above problems, it is necessary to provide a new distribution network safe operation monitoring system and method. Summary of the invention

[0006] The purpose of the present invention is to overcome the shortcomings of the prior art and propose a distribution network safe operation monitoring system and method based on a cloud platform, which can realize the drift identification, processing and correction of the output data detected by all voltage sensors in the distribution network, and can realize online real-time correction, thereby greatly improving the safety of distribution network operation.

[0007] A method for monitoring the safe operation of a distribution network based on a cloud platform of the present invention adopts the following steps:

[0008] S1: simulate the use environment of various types of voltage sensors in the distribution network, perform aging tests on various types of voltage sensors, and store the aging test monitoring data to the cloud platform server;

[0009] S2: The cloud platform server establishes a corresponding relationship between the aging coefficient and the usage time of each type of voltage sensor according to the stored aging test monitoring data;

[0010] S3: Determine the real range of the output voltage of the voltage sensor under each aging coefficient of each type of voltage sensor, and calculate the corresponding conversion correction coefficient of the voltage sensor of this type under each aging coefficient according to the ratio of the real range to the nominal range;

[0011] S4: The cloud platform server performs online identification of all voltage sensors in the distribution network, and determines whether it is necessary to correct the real-time voltage collected and output by the voltage sensor based on the model and usage time of the identified voltage sensor; if correction is required, the corresponding conversion correction coefficient is obtained according to the identification result to perform online correction on the real-time voltage collected and output by the voltage sensor; if not, continue monitoring and identification.

[0012] Preferably, in step S4, determining whether the real-time voltage collected and output by the voltage sensor needs to be corrected specifically includes:

[0013] According to the model and usage time of the identified voltage sensor, the corresponding relationship between the aging coefficient and usage time of each model of voltage sensor established in step S2 is queried, and the aging coefficient value corresponding to the model of voltage sensor under the usage time is obtained, and it is determined whether the aging coefficient value is greater than the first preset aging coefficient threshold value. If so, correction is required; if not, no correction is required.

[0014] Preferably, in step S4, determining whether it is necessary to calibrate the real-time voltage collected and output by the voltage sensor specifically includes:

[0015] S41: The cloud platform server analyzes the stored historical operation data of the distribution network and establishes a corresponding relationship curve between the voltage change and the current change of each device in the distribution network;

[0016] S42: collecting and storing the current value and voltage value of each device in real time, and calculating the current change and voltage change of each device at a preset time interval and the device voltage terminal value corresponding to the current change interval;

[0017] S43: judging whether it is necessary to correct the real-time voltage collected and output by the voltage sensor according to the calculated current change and voltage change of each device and the device voltage terminal value corresponding to the current change interval.

[0018] Preferably, in step S43, judging whether it is necessary to correct the real-time voltage collected and output by the voltage sensor according to the calculated current change amount and voltage change amount of each device and the device voltage terminal value corresponding to the current change amount interval specifically includes:

[0019] S431: Draw a corresponding relationship curve between the current change and the voltage change of each device according to the calculated current change and voltage change of each device, and compare the drawn corresponding relationship curve with the corresponding relationship curve between the voltage change and the current change of each device established in step S41 to obtain a corresponding relationship curve deviation value;

[0020] S432: If the deviation value of the corresponding relationship curve is greater than a preset threshold, and the device voltage terminal value corresponding to the current variation interval exceeds the preset range of the device normal voltage terminal value corresponding to the current variation interval, correction is required; if not, no correction is required.

[0021] Preferably, S5: the cloud platform server regularly notifies the inspection personnel to verify the calibration results of the randomly sampled voltage sensors. If the calibration results are not within the expected range, the conversion correction coefficient is modified and adjusted, and the modified conversion correction coefficient is used for calibration; if the calibration results are within the expected range, the monitoring operation continues.

[0022] Preferably, the step S4 further includes: determining whether the aging coefficient value is greater than a second preset aging coefficient threshold value, and if so, replacing the voltage sensor; wherein the second preset aging coefficient threshold value is greater than the first preset aging coefficient threshold value.

[0023] The present invention also includes a cloud platform-based distribution network safe operation monitoring system, characterized in that: the monitoring system includes an aging test module, a cloud platform server and a measurement calculation module;

[0024] The aging test module can simulate the use environment of various types of voltage sensors in the distribution network, perform aging tests on various types of voltage sensors, and upload the aging test monitoring data to the cloud platform server for storage;

[0025] The cloud platform server filters the received aging test monitoring data, and establishes a corresponding relationship between the aging coefficient of each type of voltage sensor and the usage time according to the stored aging test monitoring data; and then sends each aging coefficient of each type of voltage sensor to the measurement and calculation module;

[0026] The determination and calculation module determines the real range of the output voltage of the voltage sensor under each aging coefficient according to the received aging coefficients of each type of voltage sensor, calculates the corresponding conversion correction coefficient of the voltage sensor of this type under each aging coefficient according to the ratio of the real range to the nominal range, and sends the conversion correction coefficient to the cloud platform server for storage;

[0027] The cloud platform server also performs online identification of all voltage sensors in the distribution network, and determines whether it is necessary to correct the real-time voltage collected and output by the voltage sensor based on the model and usage time of the identified voltage sensor; if correction is required, the corresponding conversion correction coefficient is obtained according to the identification result to perform online correction on the real-time voltage collected and output by the voltage sensor; if not, monitoring and identification continue.

[0028] Preferably, the cloud platform server determines whether it is necessary to correct the real-time voltage collected and output by the voltage sensor, specifically including: according to the identified model and usage time of the voltage sensor, query the correspondence between the aging coefficient and usage time of each model of voltage sensor established in step S2, obtain the aging coefficient value corresponding to the model of voltage sensor under the usage time, and determine whether the aging coefficient value is greater than a first preset aging coefficient threshold value. If so, correction is required; if not, no correction is required.

[0029] Preferably, the cloud platform server includes: an analysis module, a calculation module and a correction judgment module; the cloud platform server judges whether it is necessary to correct the real-time voltage collected and output by the voltage sensor, specifically including:

[0030] The analysis module analyzes the stored historical operation data of the distribution network, establishes and stores the corresponding relationship curve between the voltage change and current change of each device in the distribution network;

[0031] The calculation module collects and stores the current and voltage values ​​of each device in real time, calculates the current change and voltage change of each device at a preset interval, and the device voltage terminal value corresponding to the current change interval, and sends them to the correction judgment module;

[0032] The correction judgment module judges whether it is necessary to correct the real-time voltage collected and output by the voltage sensor according to the received current change amount and voltage change amount of each device and the device voltage terminal value corresponding to the current change amount interval.

[0033] Preferably, the correction judgment module judges whether it is necessary to correct the real-time voltage collected and output by the voltage sensor according to the received current change amount, voltage change amount of each device and the device voltage terminal value corresponding to the current change amount interval, specifically including:

[0034] The correction judgment module draws a corresponding relationship curve between the current change and the voltage change of each device according to the calculated current change and the voltage change of each device, and compares the drawn corresponding relationship curve with the established corresponding relationship curve between the voltage change and the current change of each device to obtain the corresponding relationship curve deviation value;

[0035] If the deviation value of the corresponding relationship curve is greater than the preset threshold value, and the device voltage terminal value corresponding to the current change interval exceeds the preset range of the device normal voltage terminal value corresponding to the current change interval, correction is required; otherwise, no correction is required.

[0036] The beneficial effects of the present invention are as follows: 1. Based on the corresponding relationship of monitoring data established in the early aging test, the cloud platform server can perform drift identification and judgment according to the identified voltage sensor model and usage time. The online identification process is simple and convenient, and corresponding conversion correction coefficients are set for the aging coefficients of the voltage sensors at each stage, so as to realize the real-time correction of each voltage sensor in the distribution network, reduce the operation risk of the distribution network, and improve the safety of the operation and dispatching of the distribution network;

[0037] 2. The voltage sensor can also make drift judgment based on the calculated current change and voltage change of each device and the device voltage terminal value corresponding to the current change interval, further improving the accuracy of the voltage sensor in detecting output parameter drift;

[0038] 3. The voltage sensor sets the correction coefficient according to the degree of aging, realizes the monitoring and correction of the voltage sensor throughout its life cycle, improves the accuracy of the voltage sensor detection data, and improves the safety of distribution network operation and dispatching;

[0039] 4. The cloud platform server is used to realize the identification and monitoring of all voltage sensors in the distribution network, which improves the data processing speed and capacity of the distribution network safety operation monitoring system and provides guarantee for the safe operation of the distribution network;

[0040] 5. On the basis of realizing automatic identification and correction of voltage sensors in the distribution network safe operation monitoring system, a manual sampling verification link is added to further verify the automatic correction results, realize the training and learning of correction coefficients, and improve the accuracy of correction. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A step diagram of a method for monitoring the safe operation of a distribution network based on a cloud platform;

[0042] Figure 2 A flow chart for judging and correcting based on the aging coefficient;

[0043] Figure 3 A diagram showing the steps for making judgments and corrections based on the corresponding relationship between the current change and the voltage change. DETAILED DESCRIPTION

[0044] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings, but the protection scope of the present invention is not limited to the following.

[0045] A method for monitoring the safe operation of a distribution network based on a cloud platform of the present invention is as follows: Figure 1 As shown, the following steps are taken:

[0046] S1: simulate the use environment of various types of voltage sensors in the distribution network, perform aging tests on various types of voltage sensors, and store the aging test monitoring data to the cloud platform server;

[0047] S2: The cloud platform server establishes a corresponding relationship between the aging coefficient and the usage time of each type of voltage sensor according to the stored aging test monitoring data;

[0048] S3: Determine the real range of the output voltage of the voltage sensor under each aging coefficient of each type of voltage sensor, and calculate the corresponding conversion correction coefficient of the voltage sensor of this type under each aging coefficient according to the ratio of the real range to the nominal range;

[0049] S4: The cloud platform server performs online identification of all voltage sensors in the distribution network, and determines whether it is necessary to correct the real-time voltage collected and output by the voltage sensor based on the model and usage time of the identified voltage sensor; if correction is required, the corresponding conversion correction coefficient is obtained according to the identification result to perform online correction on the real-time voltage collected and output by the voltage sensor; if not, continue monitoring and identification.

[0050] Preferably, since the new voltage sensor has high accuracy, no calibration is required. If the calibration is performed from the time the new voltage sensor is used, a large amount of processor computing resources will be occupied. Therefore, the calibration process needs to be started from the time when the output parameter of the voltage sensor is identified to drift.

[0051] Therefore, in step S4, determining whether it is necessary to correct the real-time voltage collected and output by the voltage sensor specifically includes:

[0052] According to the model and usage time of the identified voltage sensor, the corresponding relationship between the aging coefficient and usage time of each model of voltage sensor established in step S2 is queried, and the aging coefficient value corresponding to the model of voltage sensor under the usage time is obtained, and it is determined whether the aging coefficient value is greater than the first preset aging coefficient threshold value. If so, correction is required; if not, no correction is required.

[0053] Preferably, in step S4, determining whether the real-time voltage collected and output by the voltage sensor needs to be corrected may further specifically include:

[0054] S41: The cloud platform server analyzes the stored historical operation data of the distribution network and establishes a corresponding relationship curve between the voltage change and the current change of each device in the distribution network;

[0055] S42: collecting and storing the current value and voltage value of each device in real time, and calculating the current change and voltage change of each device at a preset time interval and the device voltage terminal value corresponding to the current change interval;

[0056] S43: judging whether it is necessary to correct the real-time voltage collected and output by the voltage sensor according to the calculated current change and voltage change of each device and the device voltage terminal value corresponding to the current change interval.

[0057] Preferably, in step S43, judging whether it is necessary to correct the real-time voltage collected and output by the voltage sensor according to the calculated current change amount and voltage change amount of each device and the device voltage terminal value corresponding to the current change amount interval specifically includes:

[0058] S431: Draw a corresponding relationship curve between the current change and the voltage change of each device according to the calculated current change and voltage change of each device, and compare the drawn corresponding relationship curve with the corresponding relationship curve between the voltage change and the current change of each device established in step S41 to obtain a corresponding relationship curve deviation value;

[0059] S432: If the deviation value of the corresponding relationship curve is greater than a preset threshold, and the device voltage terminal value corresponding to the current variation interval exceeds the preset range of the device normal voltage terminal value corresponding to the current variation interval, correction is required; if not, no correction is required.

[0060] Preferably, in step S4, a judgment model may also be used to judge whether the real-time voltage collected and output by the voltage sensor needs to be corrected, and the judgment model specifically includes:

[0061] According to the identified voltage sensor model and usage time, query the corresponding relationship between the aging coefficient and usage time of each model of voltage sensor established in step S2, and obtain the difference Δa between the aging coefficient value corresponding to the model of voltage sensor at the usage time and the first preset aging coefficient threshold;

[0062] At the same time, the difference Δb between the device voltage terminal value corresponding to the current variation interval in the aforementioned step S42 and the preset range of the device normal voltage terminal value corresponding to the current variation interval, and the difference Δc between the corresponding relationship curve deviation value and the preset threshold value in step S431 are obtained;

[0063] The judgment model z=α*Δa+β*Δb+δ*Δc; if z>z0, the real-time voltage collected and output by the voltage sensor needs to be corrected; where z is the calculated deviation value; z0 is the preset correction threshold; α is the weight of the difference Δa; β is the weight of the difference Δb; δ is the weight of the difference Δc.

[0064] Preferably, S5: the cloud platform server regularly notifies the inspection personnel to verify the calibration results of the randomly sampled voltage sensors. If the calibration results are not within the expected range, the conversion correction coefficient is modified and adjusted, and the modified conversion correction coefficient is used for calibration; if the calibration results are within the expected range, the monitoring operation continues.

[0065] Specifically, X 修折 =X 折 +η; where X 修折 is the modified conversion correction coefficient; X 折 is the conversion correction coefficient before modification, η is the manual calibration factor;

[0066] Preferably, the step S4 further includes: determining whether the aging coefficient value is greater than a second preset aging coefficient threshold value, and if so, replacing the voltage sensor; wherein the second preset aging coefficient threshold value is greater than the first preset aging coefficient threshold value.

[0067] The present invention also includes a cloud platform-based distribution network safe operation monitoring system, characterized in that: the monitoring system includes an aging test module, a cloud platform server and a measurement calculation module;

[0068] The aging test module can simulate the use environment of various types of voltage sensors in the distribution network, perform aging tests on various types of voltage sensors, and upload the aging test monitoring data to the cloud platform server for storage;

[0069] Specifically, the aging test module can simulate the environmental parameters of various types of voltage sensors in the distribution network, such as the temperature, humidity, and electromagnetic environmental parameters used by various types of voltage sensors used by all devices, to perform aging tests on the voltage sensors. The obtained monitoring data is uploaded to the cloud platform server for storage and analysis by the cloud platform server.

[0070] The cloud platform server filters the received aging test monitoring data, and establishes a corresponding relationship between the aging coefficient of each type of voltage sensor and the usage time according to the stored aging test monitoring data; and then sends each aging coefficient of each type of voltage sensor to the measurement and calculation module;

[0071] Specifically, the cloud platform server filters the stored aging test monitoring data, removes obviously abnormal monitoring data, and establishes a corresponding relationship between the aging coefficient and the usage time of each type of voltage sensor according to the stored aging test monitoring data; taking the model T voltage sensor as an example, its aging coefficient value 0-1 is divided into 10 interval values, namely corresponding to 0.1, 0.2, ..., 1.0, and then establishes the corresponding relationship between each aging coefficient value, such as 0.1 and the usage time;

[0072] The determination and calculation module determines the real range of the output voltage of the voltage sensor under each aging coefficient according to the received aging coefficients of each type of voltage sensor, calculates the corresponding conversion correction coefficient of the voltage sensor of this type under each aging coefficient according to the ratio of the real range to the nominal range, and sends the conversion correction coefficient to the cloud platform server for storage;

[0073] Specifically, the determination and calculation module determines the real range of the output voltage of the voltage sensor when the aging coefficient value is 0.1, calculates the corresponding conversion correction coefficient of the voltage sensor of this model when the aging coefficient is 0.1 according to the ratio of the real range to the nominal range, and associates and stores the aging coefficient value and the corresponding conversion correction coefficient to the cloud platform server; then repeatedly determines the corresponding conversion correction coefficient of the voltage sensor of this model when the aging coefficient value is 0.2-1.0 and associates and stores it to the cloud platform server;

[0074] The cloud platform server also performs online identification of all voltage sensors in the distribution network, and determines whether it is necessary to correct the real-time voltage collected and output by the voltage sensor based on the model and usage time of the identified voltage sensor; if correction is required, the corresponding conversion correction coefficient is obtained according to the identification result to perform online correction on the real-time voltage collected and output by the voltage sensor; if not, monitoring and identification continue.

[0075] Preferably, the cloud platform server determines whether it is necessary to correct the real-time voltage collected and output by the voltage sensor, specifically including: according to the identified model and usage time of the voltage sensor, query the correspondence between the aging coefficient and usage time of each model of voltage sensor established in step S2, obtain the aging coefficient value corresponding to the model of voltage sensor under the usage time, and determine whether the aging coefficient value is greater than a first preset aging coefficient threshold value. If so, correction is required; if not, no correction is required.

[0076] Preferably, the cloud platform server includes: an analysis module, a calculation module and a correction judgment module; the cloud platform server judges whether it is necessary to correct the real-time voltage collected and output by the voltage sensor, specifically including:

[0077] The analysis module analyzes the stored historical operation data of the distribution network, establishes and stores the corresponding relationship curve between the voltage change and current change of each device in the distribution network;

[0078] The calculation module collects and stores the current and voltage values ​​of each device in real time, calculates the current change and voltage change of each device at a preset interval, and the device voltage terminal value corresponding to the current change interval, and sends them to the correction judgment module;

[0079] The correction judgment module judges whether it is necessary to correct the real-time voltage collected and output by the voltage sensor according to the received current change amount and voltage change amount of each device and the device voltage terminal value corresponding to the current change amount interval.

[0080] Preferably, the correction judgment module judges whether it is necessary to correct the real-time voltage collected and output by the voltage sensor according to the received current change amount, voltage change amount of each device and the device voltage terminal value corresponding to the current change amount interval, specifically including:

[0081] The correction judgment module draws a corresponding relationship curve between the current change and the voltage change of each device according to the calculated current change and the voltage change of each device, and compares the drawn corresponding relationship curve with the established corresponding relationship curve between the voltage change and the current change of each device to obtain the corresponding relationship curve deviation value;

[0082] If the deviation value of the corresponding relationship curve is greater than the preset threshold value, and the device voltage terminal value corresponding to the current change interval exceeds the preset range of the device normal voltage terminal value corresponding to the current change interval, correction is required; otherwise, no correction is required.

[0083] Preferably, the correction judgment module further includes a judgment model, and the judgment model judges whether it is necessary to correct the real-time voltage collected and output by the voltage sensor. The judgment model specifically includes:

[0084] According to the identified voltage sensor model and usage time, query the corresponding relationship between the aging coefficient and usage time of each model of voltage sensor established in step S2, and obtain the difference Δa between the aging coefficient value corresponding to the model of voltage sensor at the usage time and the first preset aging coefficient threshold;

[0085] At the same time, the difference Δb between the device voltage terminal value corresponding to the current variation interval in the aforementioned step S42 and the preset range of the device normal voltage terminal value corresponding to the current variation interval, and the difference Δc between the corresponding relationship curve deviation value and the preset threshold value in step S431 are obtained;

[0086] The judgment model z=α*Δa+β*Δb+δ*Δc; if z>z0, the real-time voltage collected and output by the voltage sensor needs to be corrected; where z is the calculated deviation value; z0 is the preset correction threshold; α is the weight of the difference Δa; β is the weight of the difference Δb; δ is the weight of the difference Δc.

[0087] Preferably, the monitoring system also includes a correction module, and the cloud platform server regularly notifies the inspection personnel to verify the correction results of the randomly sampled voltage sensors. The correction module receives the verification results to determine whether to modify and adjust the conversion correction coefficient; specifically, if the correction result is not within the expected range, the conversion correction coefficient is modified and adjusted, and the modified conversion correction coefficient is used for correction.

[0088] Specifically, in the correction module, X 修折 =X 折 +η; where X 修折 is the modified conversion correction coefficient; X 折 is the conversion correction coefficient before modification, η is the manual calibration factor;

[0089] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a ROM, a RAM, etc.

[0090] The above disclosure is only the preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for monitoring the safe operation of a distribution network based on a cloud platform, characterized in that: Use the following steps: S1: simulate the use environment of various types of voltage sensors in the distribution network, perform aging tests on various types of voltage sensors, and store the aging test monitoring data to the cloud platform server; S2: The cloud platform server establishes a corresponding relationship between the aging coefficient and the usage time of each type of voltage sensor according to the stored aging test monitoring data; S3: Determine the real range of the output voltage of the voltage sensor under each aging coefficient of each type of voltage sensor, and calculate the corresponding conversion correction coefficient of the voltage sensor of this type under each aging coefficient according to the ratio of the real range to the nominal range; S4: The cloud platform server performs online identification of all voltage sensors in the distribution network, and determines whether it is necessary to correct the real-time voltage collected and output by the voltage sensor according to the model and usage time of the identified voltage sensor; if correction is required, the corresponding conversion correction coefficient is obtained according to the identification result to perform online correction on the real-time voltage collected and output by the voltage sensor; if not, continue monitoring and identification; In step S4, determining whether the real-time voltage collected and output by the voltage sensor needs to be corrected specifically includes: According to the identified voltage sensor model and usage time, query the corresponding relationship between the aging coefficient and usage time of each model of voltage sensor established in step S2, obtain the aging coefficient value corresponding to the model of voltage sensor under the usage time, and determine whether the aging coefficient value is greater than a first preset aging coefficient threshold value. If so, correction is required; if not, no correction is required; In the step S4, determining whether it is necessary to correct the real-time voltage collected and output by the voltage sensor further specifically includes: S41: The cloud platform server analyzes the stored historical operation data of the distribution network and establishes a corresponding relationship curve between the voltage change and the current change of each device in the distribution network; S42: collecting and storing the current value and voltage value of each device in real time, and calculating the current change and voltage change of each device at a preset time interval and the device voltage terminal value corresponding to the current change interval; S43: judging whether it is necessary to correct the real-time voltage collected and output by the voltage sensor according to the calculated current change amount and voltage change amount of each device and the device voltage terminal value corresponding to the current change amount interval; In the step S43, judging whether it is necessary to correct the real-time voltage collected and output by the voltage sensor according to the calculated current change amount and voltage change amount of each device and the device voltage terminal value corresponding to the current change amount interval specifically includes: S431: Draw a corresponding relationship curve between the current change and the voltage change of each device according to the calculated current change and voltage change of each device, and compare the drawn corresponding relationship curve with the corresponding relationship curve between the voltage change and the current change of each device established in step S41 to obtain a corresponding relationship curve deviation value; S432: If the deviation value of the corresponding relationship curve is greater than a preset threshold, and the device voltage terminal value corresponding to the current variation interval exceeds the preset range of the device normal voltage terminal value corresponding to the current variation interval, correction is required; if not, no correction is required.

2. A method for monitoring the safe operation of a distribution network based on a cloud platform as claimed in claim 1, characterized in that: S5: The cloud platform server regularly notifies the inspection personnel to verify the calibration results of the randomly sampled voltage sensors. If the calibration results are not within the expected range, the conversion correction coefficient is modified and adjusted, and the modified conversion correction coefficient is used for calibration; if the calibration results are within the expected range, the monitoring operation continues.

3. A method for monitoring the safe operation of a distribution network based on a cloud platform as claimed in claim 2, characterized in that: The step S4 also includes: determining whether the aging coefficient value is greater than a second preset aging coefficient threshold value, and if so, replacing the voltage sensor; wherein the second preset aging coefficient threshold value is greater than the first preset aging coefficient threshold value.

4. A distribution network safe operation monitoring system based on a cloud platform, characterized in that: The monitoring system includes an aging test module, a cloud platform server and a measurement calculation module; The aging test module can simulate the use environment of various types of voltage sensors in the distribution network, perform aging tests on various types of voltage sensors, and upload the aging test monitoring data to the cloud platform server for storage; The cloud platform server filters the received aging test monitoring data, and establishes a corresponding relationship between the aging coefficient of each type of voltage sensor and the usage time according to the stored aging test monitoring data; and then sends each aging coefficient of each type of voltage sensor to the measurement and calculation module; The determination and calculation module determines the real range of the output voltage of the voltage sensor under each aging coefficient according to the received aging coefficients of each type of voltage sensor, calculates the corresponding conversion correction coefficient of the voltage sensor of this type under each aging coefficient according to the ratio of the real range to the nominal range, and sends the conversion correction coefficient to the cloud platform server for storage; The cloud platform server also performs online identification of all voltage sensors in the distribution network, and determines whether it is necessary to correct the real-time voltage collected and output by the voltage sensor according to the model and usage time of the identified voltage sensor; if correction is required, the corresponding conversion correction coefficient is obtained according to the identification result to perform online correction on the real-time voltage collected and output by the voltage sensor; if not, monitoring and identification are continued; The cloud platform server determines whether it is necessary to calibrate the real-time voltage collected and output by the voltage sensor, specifically including: according to the identified model and usage time of the voltage sensor, querying the corresponding relationship between the aging coefficient and the usage time of each model of the voltage sensor established in step S2, obtaining the aging coefficient value corresponding to the model of the voltage sensor under the usage time, and determining whether the aging coefficient value is greater than a first preset aging coefficient threshold value, if so, calibration is required; if not, calibration is not required; The cloud platform server includes: an analysis module, a calculation module and a correction judgment module; the cloud platform server determines whether it is necessary to correct the real-time voltage collected and output by the voltage sensor, and specifically includes: The analysis module analyzes the stored historical operation data of the distribution network, establishes and stores the corresponding relationship curve between the voltage change and current change of each device in the distribution network; The calculation module collects and stores the current and voltage values ​​of each device in real time, calculates the current change and voltage change of each device at a preset interval, and the device voltage terminal value corresponding to the current change interval, and sends them to the correction judgment module; The correction judgment module judges whether it is necessary to correct the real-time voltage collected and output by the voltage sensor according to the received current change and voltage change of each device and the device voltage terminal value corresponding to the current change interval; The correction judgment module judges whether it is necessary to correct the real-time voltage collected and output by the voltage sensor according to the received current change amount, voltage change amount and device voltage terminal value corresponding to the current change amount interval of each device, specifically including: The correction judgment module draws a corresponding relationship curve between the current change and the voltage change of each device according to the calculated current change and the voltage change of each device, and compares the drawn corresponding relationship curve with the established corresponding relationship curve between the voltage change and the current change of each device to obtain the corresponding relationship curve deviation value; If the deviation value of the corresponding relationship curve is greater than the preset threshold value, and the device voltage terminal value corresponding to the current change interval exceeds the preset range of the device normal voltage terminal value corresponding to the current change interval, correction is required; otherwise, no correction is required.

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