Big data-based intelligent operation and maintenance system and method for transformer substation

Abstract

The invention discloses a transformer substation intelligent operation and maintenance system and method based on big data, and relates to the technical field of big data intelligent operation and maintenance, the transformer substation intelligent operation and maintenance system comprises an environment sensing module, a central processing module, an environment monitoring model building module, an environment evaluation module and an intelligent operation and maintenance execution module, acquiring substation environment data by utilizing acquisition equipment; the environment monitoring model construction module adopts a neural network algorithm to construct a substation environment monitoring model; the environment evaluation module is combined with the substation environment monitoring model to evaluate the influence degree of substation environment factors on substation intelligent operation and maintenance, and the environment perception technology, the database technology, the neural network algorithm technology and the modern information technology are tightly combined, so that the substation environment is comprehensively monitored in real time; and the intelligent degree in the intelligent operation and maintenance process of the transformer substation is obviously enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of big data intelligent operation and maintenance, and particularly relates to a substation intelligent operation and maintenance system and method based on big data. Background Art

[0002] With the rapid development of the power industry, as a key hub of the power system, the safe and stable operation of substations is of vital importance. The traditional substation operation and maintenance mode faces many challenges. On the one hand, manual inspection depends on the experience and subjective judgment of operation and maintenance personnel, with low efficiency and easy omission of potential faults, and it is impossible to detect the subtle abnormalities of equipment in a timely manner. On the other hand, the amount of data generated by equipment is increasing day by day, and traditional data processing methods are difficult to effectively analyze and mine the massive data, and cannot provide accurate support for operation and maintenance decisions. In the era of big data, the development of the Internet of Things and sensors has brought new opportunities to substation operation and maintenance. At the same time, the maturity of cloud computing and artificial intelligence technologies facilitates the storage, processing, and analysis of massive data. Through in-depth mining and analysis of these data, the abnormal behaviors and potential faults of equipment can be discovered in a timely manner, realizing the status monitoring and fault warning of substation equipment. The substation intelligent operation and maintenance technology based on big data has emerged as the times require. By integrating advanced technical means, it improves the intelligent level of substation operation and maintenance, improves operation and maintenance efficiency, reduces operation and maintenance costs, and ensures the reliable operation of the power system;

[0003] Although there have been great progress in the direction of big data intelligent operation and maintenance in the existing technology, there are still some problems to be optimized. In the case of a complex substation environment with many environmental influencing factors, the existing substation intelligent operation and maintenance system and method based on big data cannot evaluate the influence degree of various environmental factors on substation intelligent operation and maintenance and take corresponding measures, resulting in a decline in the efficiency of substation intelligent operation and maintenance. Summary of the Invention

[0004] The purpose of the present invention is to provide a substation intelligent operation and maintenance system and method based on big data to solve the problems raised in the above background art.

[0005] To solve the above technical problems, the technical solution adopted by the present invention is: on the first aspect, a substation intelligent operation and maintenance system based on big data, including an environmental perception module, a central processing module, an environmental monitoring model construction module, an environmental evaluation module, and an intelligent operation and maintenance execution module, wherein each module is communicatively connected;

[0006] The environmental perception module uses acquisition devices to collect substation environmental data, provides data support for monitoring and analyzing the influence of environmental factors on substation intelligent operation and maintenance, and ensures the safety and stability of power facilities;

[0007] The central processing module is divided into a temperature processing unit, a rainfall processing unit, and a lightning processing unit. Among them, the temperature processing unit is used to obtain the degree of influence of temperature on substation equipment; the rainfall processing unit is used to obtain the degree of influence of rainfall on the cable tray of the substation; the lightning processing unit is used to obtain the degree of influence of lightning on the communication equipment of the substation;

[0008] The environmental monitoring model construction module uses a neural network algorithm to construct a substation environmental monitoring model, laying a foundation for realizing the intelligent evaluation of the substation environmental state;

[0009] The environmental evaluation module combines the substation environmental monitoring model to evaluate the degree of influence of substation environmental factors on the intelligent operation and maintenance of the substation, providing decision-making support for optimizing the operation and maintenance strategy;

[0010] The intelligent operation and maintenance execution module takes corresponding measures according to the evaluation results and issues an alarm to the client to deal with the substation environment, so as to respond to the changes in the substation environment and ensure the safe and stable operation of the power system.

[0011] A further improvement of the technical solution of the present invention is that the process of the environmental perception module collecting substation environmental data includes:

[0012] The collection equipment includes a temperature sensor, a tipping rain gauge, a Rogowski coil, a Pearson current transformer, and an oscilloscope; the substation environmental data includes the temperature of substation equipment, the rainfall around the cable tray of the substation, the lightning current amplitude, and the lightning current steepness;

[0013] The substation equipment has an internal winding, and a temperature sensor is embedded in the winding of the substation equipment to collect the temperature of the substation equipment;

[0014] The tipping rain gauge is installed near the cable tray. The tipping rain gauge includes a rain receiving port, a tipping bucket, and a counting device. When the rain enters the rain receiving port and reaches a certain amount, the tipping bucket rotates. Each rotation represents a rainfall of 0.1 mm, and the counting device records the number of rotations of the tipping bucket, and the rainfall around the cable tray of the substation is obtained by calculation.

[0015] A further improvement of the technical solution of the present invention is that the process of the environmental perception module collecting the lightning current amplitude and the lightning current steepness includes:

[0016] According to Faraday's law of electromagnetic induction, the magnetic field generated by the lightning current passes through the Rogowski coil, inducing an electromotive force in the Rogowski coil. Integrating this induced electromotive force over time to obtain a voltage signal, the greater the voltage signal, the greater the lightning current amplitude. By measuring the output signals of the Rogowski coil at different current amplitudes, the proportional relationship between the output voltage signal and the lightning current amplitude is determined. Using the collected voltage signal and the proportional relationship between the output voltage signal and the lightning current amplitude, the lightning current amplitude is calculated;

[0017] The Pearson current transformer has a primary winding and a secondary winding built-in. Based on the principle of electromagnetic induction, the lightning current generates a changing magnetic field around the primary winding of the Pearson current transformer. Through the electromagnetic coupling between the primary winding and the secondary winding, the changing magnetic field around the primary winding generates an induced voltage signal in the secondary winding. Set the parameters of the oscilloscope, and transmit the induced voltage signal to the oscilloscope probe through a wire. The oscilloscope displays the waveform of the induced voltage signal corresponding to the lightning current. Select two points on the rising edge of the waveform displayed on the oscilloscope. By measuring the voltage change and time interval between the selected two points, and using the turns ratio of the Pearson current transformer, the process of calculating the lightning current steepness is as follows:

[0018]

[0019] Among them, is the lightning current steepness, K is the turns ratio of the Pearson current transformer, ΔV is the voltage change between the selected two points, and ΔT is the time interval between the selected two points.

[0020] A further improvement of the technical solution of the present invention lies in: the process of the temperature processing unit obtaining the influence degree of temperature on substation equipment includes:

[0021] Preprocess the temperature data of the substation equipment, select the MySQL database, design the MySQL database table, and insert the preprocessed temperature data of the substation equipment into the MySQL database table to store the temperature data of the substation equipment;

[0022] Set the lower threshold value and upper threshold value of the ambient temperature for the operation of the substation equipment. The influence degree of temperature on the substation equipment includes the influence degree of low temperature on the substation equipment and the influence degree of high temperature on the substation equipment;

[0023] When the temperature of the substation equipment collected is lower than the lower threshold value of the ambient temperature for the operation of the substation equipment, the process of obtaining the influence degree of low temperature on the substation equipment is as follows:

[0024]

[0025] Among them, PDDI is the influence degree of low temperature on the substation equipment, Tmin is the lower limit threshold of the ambient temperature for the operation of substation equipment, T e is the temperature data of substation equipment, k 1 is the low-temperature influence coefficient;

[0026] When the temperature of the substation equipment collected is higher than the upper limit threshold of the ambient temperature for the operation of substation equipment, the process of obtaining the influence degree of high temperature on substation equipment is as follows:

[0027]

[0028] where OHRI is the influence degree of high temperature on substation equipment, T max is the upper limit threshold of the ambient temperature for the operation of substation equipment, T e is the temperature data of substation equipment, k 2 is the high-temperature influence coefficient.

[0029] A further improvement of the technical solution of the present invention lies in that: the process of the rainfall processing unit obtaining the influence degree of rainfall on the substation cable tray includes:

[0030] Preprocess the rainfall data around the substation cable tray, select the MySQL database, design the MySQL database table, insert the preprocessed rainfall data around the substation cable tray into the MySQL database table, and store the rainfall data around the substation cable tray;

[0031] Set the rainfall threshold around the substation cable tray. When the rainfall around the substation cable tray collected is higher than the rainfall threshold around the substation cable tray, the process of obtaining the influence degree of rainfall on the substation cable tray is as follows:

[0032]

[0033] where FRI is the influence degree of rainfall on the substation cable tray, R 0 is the rainfall threshold around the substation cable tray, R e is the rainfall around the substation cable tray.

[0034] A further improvement of the technical solution of the present invention lies in that: the process of the lightning processing unit obtaining the influence degree of lightning on the substation communication equipment includes:

[0035] Preprocess the lightning current amplitude data and lightning current steepness data, select the MySQL database, design the MySQL database table, insert the preprocessed lightning current amplitude data and lightning current steepness data into the MySQL database table, and store the lightning current amplitude data and lightning current steepness data;

[0036] The influencing degree of lightning on substation communication equipment includes the influencing degree of lightning current amplitude on substation communication equipment and the influencing degree of lightning current steepness on substation communication equipment;

[0037] Set the lightning current amplitude threshold and its weight. When the collected lightning current amplitude is higher than the lightning current amplitude threshold, the acquisition process of the influencing degree of lightning current amplitude on substation communication equipment is as follows:

[0038]

[0039] CI = w 1 ×C m

[0040] where CI is the influencing degree of lightning current amplitude on substation communication equipment, C m is the lightning current amplitude influence coefficient, I 0 is the lightning current amplitude threshold, I e is the lightning current amplitude, w 1 is the lightning current amplitude weight;

[0041] Set the lightning current steepness threshold and its weight. When the collected lightning current steepness is higher than the lightning current steepness threshold, the acquisition process of the influencing degree of lightning current steepness on substation communication equipment is as follows:

[0042]

[0043] CS = w 2 ×C n

[0044] where CS is the influencing degree of lightning current steepness on substation communication equipment, C n is the lightning current steepness influence coefficient, S 0 is the lightning current steepness threshold, S e is the lightning current steepness, w 2 is the lightning current steepness weight;

[0045] Combining the influencing degree of lightning current amplitude on substation communication equipment and the influencing degree of lightning current steepness on substation communication equipment, the process of obtaining the influencing degree of lightning on substation communication equipment includes:

[0046] CQ = CI + CS

[0047] where CQ is the influencing degree of lightning on substation communication equipment, CI is the influencing degree of lightning current amplitude on substation communication equipment, and CS is the influencing degree of lightning current steepness on substation communication equipment.

[0048] A further improvement of the technical solution of the present invention lies in that: the environmental monitoring model construction module adopts a neural network algorithm, and the process of constructing a substation environmental monitoring model includes:

[0049] Taking the temperature and its influence degree on substation equipment, the rainfall and its influence degree on the substation cable tray, the lightning current amplitude, the lightning current steepness, and the influence degree of lightning on substation communication equipment as a data set, and dividing it into a training set and a test set according to a ratio of 7:3;

[0050] Selecting MLP as the neural network structure, the input layer includes four neurons, which receive temperature data, rainfall data, lightning current amplitude data, and lightning current steepness data. The hidden layer is equipped with Sigmoid function and MSE function. The output layer includes three neurons, and outputs the influence degree of temperature on substation equipment, the influence degree of rainfall on the substation cable tray, and the influence degree of lightning on substation communication equipment;

[0051] Using the training set data to train the neural network model, setting the learning rate to 0.01 and the number of iterations to 3000. Through iterative training, learn the non-linear relationship between temperature data and the influence degree of temperature on substation equipment, the non-linear relationship between rainfall data and the influence degree of rainfall on the substation cable tray, and the influence degree of lightning current amplitude data and lightning current steepness data on the influence degree of lightning on substation communication equipment. Use the Sigmoid function to map the output value of the output layer to the [0,1] interval to obtain the neural network model;

[0052] Inputting the test set data into the trained neural network model, using the MSE function to evaluate the error between the output value and the actual value of the neural network model, adjusting the parameters of the neural network model according to the evaluation result, optimizing the performance of the neural network model, and obtaining the substation environmental monitoring model.

[0053] A further improvement of the technical solution of the present invention lies in that: the environmental evaluation module, the process of evaluating the influence degree of substation environmental factors on substation intelligent operation and maintenance includes:

[0054] According to the fact that substation equipment, substation cable trays, and substation communication equipment are components in the process of substation intelligent operation and maintenance, in accordance with the standard that the influence degree of temperature on substation equipment is equivalent to the influence degree of temperature on substation intelligent operation and maintenance, the influence degree of rainfall on substation cable trays is equivalent to the influence degree of rainfall around the substation cable trays on substation intelligent operation and maintenance, and the influence degree of lightning on substation communication equipment is equivalent to the influence degree of lightning on substation intelligent operation and maintenance, combined with the substation environmental monitoring model, evaluate the influence degree of substation environmental factors on substation intelligent operation and maintenance;

[0055] When the impact degree of temperature on the intelligent operation and maintenance of the substation is less than 30%, the temperature has a low impact on the intelligent operation and maintenance of the substation; when the impact degree of temperature on the intelligent operation and maintenance of the substation is between 30% and 60%, the temperature has a medium impact on the intelligent operation and maintenance of the substation; when the impact degree of temperature on the intelligent operation and maintenance of the substation is higher than 60%, the temperature has a high impact on the intelligent operation and maintenance of the substation;

[0056] When the impact degree of rainfall on the intelligent operation and maintenance of the substation is less than 40%, the rainfall has a low impact on the intelligent operation and maintenance of the substation; when the impact degree of rainfall on the intelligent operation and maintenance of the substation is between 40% and 60%, the rainfall has a medium impact on the intelligent operation and maintenance of the substation; when the impact degree of rainfall on the intelligent operation and maintenance of the substation is higher than 60%, the rainfall has a high impact on the intelligent operation and maintenance of the substation;

[0057] When the impact degree of lightning on the intelligent operation and maintenance of the substation is less than 20%, the lightning has a low impact on the intelligent operation and maintenance of the substation; when the impact degree of lightning on the intelligent operation and maintenance of the substation is between 20% and 50%, the lightning has a medium impact on the intelligent operation and maintenance of the substation; when the impact degree of lightning on the intelligent operation and maintenance of the substation is higher than 50%, the lightning has a high impact on the intelligent operation and maintenance of the substation.

[0058] A further improvement of the technical solution of the present invention lies in that: the process of the intelligent operation and maintenance execution module taking corresponding measures and sending signals to the client to cope with the substation environment includes:

[0059] When the temperature has a low impact on the intelligent operation and maintenance of the substation, strengthen the monitoring frequency of the temperature, record the real-time temperature data, and predict the temperature change trend; when the temperature has a medium impact on the intelligent operation and maintenance of the substation, start the heat dissipation equipment, send a temperature warning signal to the client, and let the client formulate a solution; when the temperature has a high impact on the intelligent operation and maintenance of the substation, start the refrigeration equipment, stop the operation of the equipment with abnormal temperature, send a temperature emergency signal to the client, and let the client repair the equipment with abnormal temperature;

[0060] When the rainfall has a low impact on the intelligent operation and maintenance of the substation, continuously monitor the rainfall and the operation status of the drainage system, and record the rainfall data; when the rainfall has a medium impact on the intelligent operation and maintenance of the substation, increase the monitoring frequency of the rainfall, check the drainage pipes, and send a rainfall warning signal to the client; when the rainfall has a high impact on the intelligent operation and maintenance of the substation, start the drainage equipment, increase the waterproof sandbags, stop the operation of the equipment greatly affected by the rainfall, and send a rainfall emergency signal to the client;

[0061] When the impact of lightning on the intelligent operation and maintenance of the substation is low, increase the monitoring frequency of lightning current amplitude and lightning current steepness, record lightning activity data, send lightning prompt information to the client, and let the client check the operation status of lightning protection equipment; when the impact of lightning on the intelligent operation and maintenance of the substation is medium, check the connection of the grounding resistance of the lightning protection equipment, adjust the operation mode of the substation equipment according to the lightning impact situation, and send a lightning warning signal to the client; when the impact of lightning on the intelligent operation and maintenance of the substation is high, send a lightning emergency signal to the client, and let the client start the emergency repair work.

[0062] Second, a method for intelligent operation and maintenance of a substation based on big data is used to implement the above-mentioned intelligent operation and maintenance system of a substation based on big data, and it consists of the following steps:

[0063] Step 1: Use temperature sensors, tipping bucket rain gauges, Rogowski coils, Pearson current transformers, and oscilloscopes to collect the temperature of substation equipment, the rainfall around the substation cable tray, lightning current amplitude, and lightning current steepness respectively.

[0064] Step 2: Preprocess the substation environment data, select a MySQL database to store the substation environment data, and use the substation environment data to obtain the influence degree of temperature on substation equipment, the influence degree of rainfall on the substation cable tray, and the influence degree of lightning on substation communication equipment respectively.

[0065] Step 3: Use a neural network algorithm to construct a substation environment monitoring model.

[0066] Step 4: Combine the substation environment monitoring model to evaluate the influence degree of substation environmental factors on the intelligent operation and maintenance of the substation.

[0067] Step 5: According to the evaluation results, take corresponding measures and send an alarm to the client to deal with the substation environment.

[0068] The beneficial effects of the present invention are as follows: In the intelligent operation and maintenance system and method for substations based on big data of the present invention, compared with the traditional intelligent operation and maintenance system and method for substations based on big data, the environmental perception technology, database technology, neural network algorithm technology in the method of the present invention are closely combined with modern information technology, accurately capturing the temperature of substation equipment, rainfall around cable trays, lightning current amplitude and lightning current steepness, respectively obtaining the influence degree of temperature on substation equipment, the influence degree of rainfall on substation cable trays, and the influence degree of lightning on substation communication equipment, achieving real-time and comprehensive monitoring of the substation environment. By constructing a substation environment monitoring model, evaluating the influence degree of the environment on the intelligent operation and maintenance of substations, and taking corresponding measures according to the evaluation results, it solves the problem that in the case of complex substation environments with many environmental influencing factors, the existing intelligent operation and maintenance system and method for substations based on big data cannot evaluate the influence degree of various environmental factors on the intelligent operation and maintenance of substations, resulting in a decrease in the efficiency of substation intelligent operation and maintenance. It ensures that the method in the present invention can refine the dynamic monitoring standards for the intelligent operation and maintenance system and method for substations within a more accurate range, making the monitored data more accurate indicators under the same conditions. The research and application of this method significantly enhance the degree of intelligence in the process of substation intelligent operation and maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0070] Figure 1 It is a block diagram of the intelligent operation and maintenance system for substations based on big data of the present invention;

[0071] Figure 2 It is a flowchart of the intelligent operation and maintenance method for substations based on big data of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0072] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0073] Example 1, as Figure 1As shown in the figure, the present invention provides a substation intelligent operation and maintenance system based on big data, including an environmental perception module, a central processing module, an environmental monitoring model construction module, an environmental evaluation module, and an intelligent operation and maintenance execution module. Among them, each module is communicatively connected;

[0074] The environmental perception module uses acquisition devices to collect substation environmental data, provides data support for monitoring and analyzing the impact of environmental factors on substation intelligent operation and maintenance, and ensures the safety and stability of power facilities;

[0075] The central processing module is divided into a temperature processing unit, a rainfall processing unit, and a lightning processing unit. Among them, the temperature processing unit is used to obtain the degree of influence of temperature on substation equipment; the rainfall processing unit is used to obtain the degree of influence of rainfall on the substation cable tray; the lightning processing unit is used to obtain the degree of influence of lightning on substation communication equipment;

[0076] The environmental monitoring model construction module uses a neural network algorithm to construct a substation environmental monitoring model, laying a foundation for realizing the intelligent evaluation of the substation environmental state;

[0077] The environmental evaluation module combines the substation environmental monitoring model to evaluate the degree of influence of substation environmental factors on substation intelligent operation and maintenance, providing decision-making support for optimizing operation and maintenance strategies;

[0078] The intelligent operation and maintenance execution module takes corresponding measures according to the evaluation results and issues an alarm to the client to respond to the substation environment, so as to respond to the changes in the substation environment and ensure the safe and stable operation of the power system.

[0079] Preferably, the process of the environmental perception module collecting substation environmental data includes:

[0080] Among them, the acquisition devices include temperature sensors, tipping rain gauges, Rogowski coils, Pearson current transformers, and oscilloscopes; the substation environmental data includes the temperature of substation equipment, the rainfall around the substation cable tray, the lightning current amplitude, and the lightning current steepness;

[0081] The substation equipment has an internal winding. A temperature sensor is embedded in the winding of the substation equipment to collect the temperature of the substation equipment;

[0082] The tipping rain gauge is installed near the cable tray. The tipping rain gauge includes a rain receiving port, a tipping bucket, and a counting device. When rainwater enters the rain receiving port and reaches a certain amount, the tipping bucket rotates. Each rotation represents a rainfall of 0.1 mm. The counting device records the number of rotations of the tipping bucket, and the rainfall around the substation cable tray is obtained through calculation.

[0083] Preferably, the process of the environmental perception module collecting the lightning current amplitude and the lightning current steepness includes:

[0084] According to Faraday's law of electromagnetic induction, the magnetic field generated by the lightning current passes through the Rogowski coil, inducing an electromotive force in the Rogowski coil. Integrating this induced electromotive force with respect to time to obtain a voltage signal, the larger the voltage signal, the larger the lightning current amplitude. By measuring the output signals of the Rogowski coil at different current amplitudes, the proportional relationship between the output voltage signal and the lightning current amplitude is determined. Using the collected voltage signal and the proportional relationship between the output voltage signal and the lightning current amplitude, the lightning current amplitude is calculated;

[0085] The Pearson current transformer has a primary winding and a secondary winding built-in. Based on the principle of electromagnetic induction, the lightning current generates a changing magnetic field around the primary winding of the Pearson current transformer. Through the electromagnetic coupling between the primary winding and the secondary winding, the changing magnetic field around the primary winding generates an induced voltage signal in the secondary winding. Set the parameters of the oscilloscope, and transmit the induced voltage signal to the oscilloscope probe through a wire. The oscilloscope displays the waveform of the induced voltage signal corresponding to the lightning current. Select two points at the rising edge of the waveform displayed on the oscilloscope. By measuring the voltage change and time interval between the selected two points, and using the turns ratio of the Pearson current transformer, the process of calculating the lightning current steepness is as follows:

[0086]

[0087] Among them, is the lightning current steepness, K is the turns ratio of the Pearson current transformer, ΔV is the voltage change between the selected two points, and ΔT is the time interval between the selected two points.

[0088] Preferably, the process of the temperature processing unit obtaining the influence degree of temperature on substation equipment includes:

[0089] Preprocess the temperature data of substation equipment, select the MySQL database, design the MySQL database table, and insert the preprocessed temperature data of substation equipment into the MySQL database table to store the temperature data of substation equipment;

[0090] Set the lower threshold and upper threshold of the ambient temperature for the operation of substation equipment. The influence degree of temperature on substation equipment includes the influence degree of low temperature on substation equipment and the influence degree of high temperature on substation equipment;

[0091] When the temperature of the substation equipment collected is lower than the lower threshold of the ambient temperature for the operation of substation equipment, the process of obtaining the influence degree of low temperature on substation equipment is as follows:

[0092]

[0093] Among them, PDDI is the influence degree of low temperature on substation equipment, Tmin is the lower limit threshold of the ambient temperature for the operation of substation equipment, T e is the temperature data of substation equipment, k 1 is the low-temperature influence coefficient;

[0094] When the temperature of the substation equipment collected is higher than the upper limit threshold of the ambient temperature for the operation of substation equipment, the process of obtaining the influence degree of high temperature on substation equipment is as follows:

[0095]

[0096] where OHRI is the influence degree of high temperature on substation equipment, T max is the upper limit threshold of the ambient temperature for the operation of substation equipment, T e is the temperature data of substation equipment, k 2 is the high-temperature influence coefficient.

[0097] Preferably, the process of the rainfall processing unit obtaining the influence degree of rainfall on the substation cable tray includes:

[0098] Preprocess the rainfall data around the substation cable tray, select the MySQL database, design the MySQL database table, insert the preprocessed rainfall data around the substation cable tray into the MySQL database table, and store the rainfall data around the substation cable tray;

[0099] Set the rainfall threshold around the substation cable tray. When the rainfall around the substation cable tray collected is higher than the rainfall threshold around the substation cable tray, the process of obtaining the influence degree of rainfall on the substation cable tray is as follows:

[0100]

[0101] where FRI is the influence degree of rainfall on the substation cable tray, R 0 is the rainfall threshold around the substation cable tray, R e is the rainfall around the substation cable tray.

[0102] Preferably, the process of the lightning processing unit obtaining the influence degree of lightning on the substation communication equipment includes:

[0103] Preprocess the lightning current amplitude data and lightning current steepness data, select the MySQL database, design the MySQL database table, insert the preprocessed lightning current amplitude data and lightning current steepness data into the MySQL database table, and store the lightning current amplitude data and lightning current steepness data;

[0104] Among them, the influence degree of lightning on substation communication equipment includes the influence degree of lightning current amplitude on substation communication equipment and the influence degree of lightning current steepness on substation communication equipment;

[0105] Set the lightning current amplitude threshold and its weight. When the collected lightning current amplitude is higher than the lightning current amplitude threshold, the acquisition process of the influence degree of lightning current amplitude on substation communication equipment is as follows:

[0106]

[0107] CI = w 1 ×C m

[0108] Among them, CI is the influence degree of lightning current amplitude on substation communication equipment, C m is the lightning current amplitude influence coefficient, I 0 is the lightning current amplitude threshold, I e is the lightning current amplitude, w 1 is the lightning current amplitude weight;

[0109] Set the lightning current steepness threshold and its weight. When the collected lightning current steepness is higher than the lightning current steepness threshold, the acquisition process of the influence degree of lightning current steepness on substation communication equipment is as follows:

[0110]

[0111] CS = w 2 ×C n

[0112] Among them, CS is the influence degree of lightning current steepness on substation communication equipment, C n is the lightning current steepness influence coefficient, S 0 is the lightning current steepness threshold, S e is the lightning current steepness, w 2 is the lightning current steepness weight;

[0113] Combining the influence degree of lightning current amplitude on substation communication equipment and the influence degree of lightning current steepness on substation communication equipment, the process of obtaining the influence degree of lightning on substation communication equipment includes:

[0114] CQ = CI + CS

[0115] Among them, CQ is the influence degree of lightning on substation communication equipment, CI is the influence degree of lightning current amplitude on substation communication equipment, and CS is the influence degree of lightning current steepness on substation communication equipment.

[0116] Preferably, the environmental monitoring model construction module uses the neural network algorithm. The process of constructing the substation environmental monitoring model includes:

[0117] Taking the temperature and its influence degree on substation equipment, the rainfall and its influence degree on the substation cable tray, the lightning current amplitude, the lightning current steepness, and the influence degree of lightning on substation communication equipment as a data set, it is divided into a training set and a test set according to a ratio of 7:3.

[0118] Selecting MLP as the neural network structure, the input layer includes four neurons, which receive temperature data, rainfall data, lightning current amplitude data, and lightning current steepness data. The hidden layer is equipped with Sigmoid function and MSE function. The output layer includes three neurons, which output the influence degree of temperature on substation equipment, the influence degree of rainfall on the substation cable tray, and the influence degree of lightning on substation communication equipment.

[0119] Using the training set data to train the neural network model, setting the learning rate to 0.01 and the number of iterations to 3000. Through iterative training, learn the non-linear relationship between temperature data and the influence degree of temperature on substation equipment, the non-linear relationship between rainfall data and the influence degree of rainfall on the substation cable tray, and the non-linear relationship between lightning current amplitude data, lightning current steepness data and the influence degree of lightning on substation communication equipment. Using the Sigmoid function to map the output value of the output layer to the interval [0,1] to obtain the neural network model.

[0120] Inputting the test set data into the trained neural network model, using the MSE function to evaluate the error between the output value and the actual value of the neural network model, adjusting the parameters of the neural network model according to the evaluation result, optimizing the performance of the neural network model, and obtaining the substation environment monitoring model.

[0121] Preferably, the process of the environmental evaluation module evaluating the influence degree of substation environmental factors on substation intelligent operation and maintenance includes:

[0122] According to the fact that substation equipment, substation cable trays, and substation communication equipment are components in the process of substation intelligent operation and maintenance, in accordance with the standard that the influence degree of temperature on substation equipment is equivalent to the influence degree of temperature on substation intelligent operation and maintenance, the influence degree of rainfall on substation cable trays is equivalent to the influence degree of rainfall around the substation cable trays on substation intelligent operation and maintenance, and the influence degree of lightning on substation communication equipment is equivalent to the influence degree of lightning on substation intelligent operation and maintenance, combined with the substation environment monitoring model, evaluate the influence degree of substation environmental factors on substation intelligent operation and maintenance.

[0123] When the influence degree of temperature on the intelligent operation and maintenance of the substation is less than 30%, the temperature has a low influence on the intelligent operation and maintenance of the substation; when the influence degree of temperature on the intelligent operation and maintenance of the substation is between 30% and 60%, the temperature has a medium influence on the intelligent operation and maintenance of the substation; when the influence degree of temperature on the intelligent operation and maintenance of the substation is higher than 60%, the temperature has a high influence on the intelligent operation and maintenance of the substation;

[0124] When the influence degree of rainfall on the intelligent operation and maintenance of the substation is less than 40%, the rainfall has a low influence on the intelligent operation and maintenance of the substation; when the influence degree of rainfall on the intelligent operation and maintenance of the substation is between 40% and 60%, the rainfall has a medium influence on the intelligent operation and maintenance of the substation; when the influence degree of rainfall on the intelligent operation and maintenance of the substation is higher than 60%, the rainfall has a high influence on the intelligent operation and maintenance of the substation;

[0125] When the influence degree of lightning on the intelligent operation and maintenance of the substation is less than 20%, the lightning has a low influence on the intelligent operation and maintenance of the substation; when the influence degree of lightning on the intelligent operation and maintenance of the substation is between 20% and 50%, the lightning has a medium influence on the intelligent operation and maintenance of the substation; when the influence degree of lightning on the intelligent operation and maintenance of the substation is higher than 50%, the lightning has a high influence on the intelligent operation and maintenance of the substation.

[0126] Preferably, the process of the intelligent operation and maintenance execution module taking corresponding measures and sending signals to the client to respond to the substation environment includes:

[0127] When the temperature has a low influence on the intelligent operation and maintenance of the substation, strengthen the monitoring frequency of the temperature, record the real-time temperature data, and predict the temperature change trend; when the temperature has a medium influence on the intelligent operation and maintenance of the substation, start the heat dissipation equipment, send a temperature warning signal to the client, and let the client formulate a solution; when the temperature has a high influence on the intelligent operation and maintenance of the substation, start the refrigeration equipment, stop the operation of the temperature-abnormal equipment, send a temperature emergency signal to the client, and let the client repair the temperature-abnormal equipment;

[0128] When the rainfall has a low influence on the intelligent operation and maintenance of the substation, continuously monitor the rainfall and the operation status of the drainage system, and record the rainfall data; when the rainfall has a medium influence on the intelligent operation and maintenance of the substation, increase the monitoring frequency of the rainfall, check the drainage pipes, and send a rainfall warning signal to the client; when the rainfall has a high influence on the intelligent operation and maintenance of the substation, start the drainage equipment, increase the waterproof sandbags, stop the operation of the equipment greatly affected by the rainfall, and send a rainfall emergency signal to the client;

[0129] When the impact of lightning on the intelligent operation and maintenance of the substation is low, increase the monitoring frequency of lightning current amplitude and lightning current steepness, record lightning activity data, send lightning prompt information to the client, and let the client check the operation status of lightning protection equipment; when the impact of lightning on the intelligent operation and maintenance of the substation is medium, check the grounding resistance access of lightning protection equipment, adjust the operation mode of substation equipment according to the lightning impact situation, and send a lightning warning signal to the client; when the impact of lightning on the intelligent operation and maintenance of the substation is high, send a lightning emergency signal to the client, and let the client start the emergency repair work.

[0130] Embodiment 2, as Figure 2 shown, based on Embodiment 1, the present invention provides a technical solution: a method for intelligent operation and maintenance of a substation based on big data, which is used to implement the above-mentioned intelligent operation and maintenance system of a substation based on big data, and consists of the following steps:

[0131] Step 1: Use temperature sensors, tipping bucket rain gauges, Rogowski coils, Pearson current transformers, and oscilloscopes to collect the temperature of substation equipment, the rainfall around the substation cable tray, lightning current amplitude, and lightning current steepness respectively.

[0132] Step 2: Preprocess the substation environmental data, select the MySQL database to store the substation environmental data, and use the substation environmental data to obtain the influence degree of temperature on substation equipment, the influence degree of rainfall on the substation cable tray, and the influence degree of lightning on substation communication equipment respectively.

[0133] Step 3: Use the neural network algorithm to construct a substation environmental monitoring model.

[0134] Step 4: Combine the substation environmental monitoring model to evaluate the influence degree of substation environmental factors on the intelligent operation and maintenance of the substation.

[0135] Step 5: According to the evaluation results, take corresponding measures and send an alarm to the client to deal with the substation environment.

[0136] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. The intelligent operation and maintenance system of substation based on big data includes environment perception module, central processing module, environment monitoring model building module, environment assessment module and intelligent operation and maintenance execution module, among which: The electrical signal connection between modules is characterized by: The environmental perception module collects substation environmental data using a collection device; The central processing module is divided into a temperature processing unit, a rainfall processing unit and a lightning processing unit, wherein the temperature processing unit is used to obtain the degree of influence of temperature on substation equipment; the rainfall processing unit is used to obtain the degree of influence of rainfall on substation cable trays; the lightning processing unit is used to obtain the degree of influence of lightning on substation communication equipment; The environmental monitoring model building module uses a neural network algorithm to build a substation environmental monitoring model; The environmental assessment module, combined with the substation environmental monitoring model, assesses the impact of substation environmental factors on substation intelligent operation and maintenance; The intelligent operation and maintenance execution module takes corresponding measures and sends an alarm to the client to deal with the substation environment according to the evaluation results.

2. The intelligent operation and maintenance system for substations based on big data according to claim 1 is characterized in that: The process of collecting substation environmental data by the environment perception module includes: The acquisition equipment includes a temperature sensor, a tipping bucket rain gauge, a Rogowski coil, a Pearson current transformer and an oscilloscope; the substation environmental data includes the temperature of the substation equipment, the rainfall around the substation cable tray, the lightning current amplitude and the lightning current steepness; The substation equipment has built-in windings, and a temperature sensor is embedded in the windings of the substation equipment to collect the temperature of the substation equipment; The tipping bucket rain gauge is installed near the cable bridge. The tipping bucket rain gauge includes a rain receiving port, a tipping bucket and a counting device. When rainwater enters the rain receiving port and reaches a certain amount, the tipping bucket reverses. Each reversal represents 0.1 mm of rainfall. The counting device records the number of times the tipping bucket flips, and the rainfall around the substation cable bridge is obtained by calculation.

3. The intelligent operation and maintenance system for substations based on big data according to claim 2 is characterized in that: The process of collecting lightning current amplitude and lightning current steepness by the environment perception module includes: According to Faraday's law of electromagnetic induction, the magnetic field generated by the lightning current passes through the Rogowski coil, generating an induced electromotive force in the Rogowski coil. The induced electromotive force is integrated with time to obtain a voltage signal. The larger the voltage signal, the larger the lightning current amplitude. By measuring the output signal of the Rogowski coil at different current amplitudes, the proportional relationship between the output voltage signal and the lightning current amplitude is determined. The lightning current amplitude is calculated using the collected voltage signal and the proportional relationship between the output voltage signal and the lightning current amplitude. The Pearson current transformer has a built-in primary winding and a secondary winding. Based on the principle of electromagnetic induction, the lightning current generates a changing magnetic field around the primary winding of the Pearson current transformer. Through the electromagnetic coupling between the primary winding and the secondary winding, the changing magnetic field around the primary winding generates an induced voltage signal in the secondary winding. The oscilloscope parameters are set, and the induced voltage signal is transmitted to the oscilloscope probe through a wire. The oscilloscope displays the induced voltage signal waveform corresponding to the lightning current. Two points are selected on the rising edge of the waveform displayed on the oscilloscope. The voltage change and time interval between the two selected points are obtained by measurement. The process of calculating the lightning current steepness using the Pearson current transformer ratio is as follows: in, is the lightning current steepness, K is the Pearson current transformer ratio, ΔV is the voltage change between the two selected points, and ΔT is the time interval between the two selected points.

4. The intelligent operation and maintenance system for substations based on big data according to claim 3 is characterized by: The process of the temperature processing unit obtaining the influence of temperature on the substation equipment includes: Preprocess the temperature data of the substation equipment, select the MySQL database, design the MySQL database table, insert the preprocessed temperature data of the substation equipment into the MySQL database table, and store the temperature data of the substation equipment; Setting a lower threshold value and an upper threshold value of the ambient temperature for the operation of the substation equipment, wherein the influence of the temperature on the substation equipment includes the influence of low temperature on the substation equipment and the influence of high temperature on the substation equipment; When the collected substation equipment temperature is lower than the lower limit threshold of the ambient temperature of the substation equipment, the process of obtaining the degree of influence of low temperature on the substation equipment is as follows: Among them, PDDI is the impact of low temperature on substation equipment, T min is the lower limit threshold of the ambient temperature for substation equipment operation, T e is the temperature data of the substation equipment, k1 is the low temperature influence coefficient; When the collected substation equipment temperature is higher than the upper threshold of the ambient temperature of the substation equipment, the process of obtaining the degree of influence of high temperature on the substation equipment is as follows: Among them, OHRI is the impact of high temperature on substation equipment, T max is the upper threshold of the ambient temperature for substation equipment operation, T e is the temperature data of substation equipment, and k2 is the high temperature influence coefficient.

5. The intelligent operation and maintenance system for substations based on big data according to claim 4 is characterized in that: The process of obtaining the influence of rainfall on the cable tray of the substation by the rainfall processing unit includes: Preprocess the rainfall data around the substation cable tray, select the MySQL database, design the MySQL database table, insert the preprocessed rainfall data around the substation cable tray into the MySQL database table, and store the rainfall data around the substation cable tray; The rainfall threshold around the substation cable tray is set. When the collected rainfall around the substation cable tray is higher than the rainfall threshold around the substation cable tray, the process of obtaining the influence of rainfall on the substation cable tray is as follows: Among them, FRI is the impact of rainfall on the substation cable tray, R0 is the rainfall threshold around the substation cable tray, and R e It is the rainfall around the substation cable tray.

6. The intelligent operation and maintenance system for substations based on big data according to claim 5 is characterized in that: The process of obtaining the influence degree of lightning on the communication equipment of the substation by the lightning processing unit includes: Preprocess the lightning current amplitude data and the lightning current steepness data, select the MySQL database, design the MySQL database table, insert the preprocessed lightning current amplitude data and the lightning current steepness data into the MySQL database table, and store the lightning current amplitude data and the lightning current steepness data; The influence degree of lightning on the substation communication equipment includes the influence degree of lightning current amplitude on the substation communication equipment and the influence degree of lightning current steepness on the substation communication equipment; The lightning current amplitude threshold and its weight are set. When the collected lightning current amplitude is higher than the lightning current amplitude threshold, the process of obtaining the influence of the lightning current amplitude on the substation communication equipment is as follows: CI=w1×C m Where CI is the impact of lightning current amplitude on substation communication equipment, C m is the lightning current amplitude influence coefficient, I0 is the lightning current amplitude threshold, I e is the lightning current amplitude, w1 is the lightning current amplitude weight; Set the lightning current steepness threshold and its weight. When the collected lightning current steepness is higher than the lightning current steepness threshold, the process of obtaining the influence of the lightning current steepness on the substation communication equipment is as follows: CS=w2×C n Among them, CS is the impact of lightning current steepness on substation communication equipment, C n is the lightning current steepness influence coefficient, S0 is the lightning current steepness threshold, S e is the lightning current steepness, w2 is the lightning current steepness weight; Combining the influence of lightning current amplitude on substation communication equipment and the influence of lightning current steepness on substation communication equipment, the process of obtaining the influence of lightning on substation communication equipment includes: CQ=CI+CS Among them, CQ is the impact degree of lightning on substation communication equipment, CI is the impact degree of lightning current amplitude on substation communication equipment, and CS is the impact degree of lightning current steepness on substation communication equipment.

7. The intelligent operation and maintenance system for substations based on big data according to claim 6 is characterized by: The environmental monitoring model building module adopts a neural network algorithm to build a substation environmental monitoring model, and the process includes: The temperature and its influence on substation equipment, rainfall and its influence on substation cable tray, lightning current amplitude and lightning current steepness, and the influence of lightning on substation communication equipment are used as data sets and divided into training set and test set in a ratio of 7:3; MLP is selected as the neural network structure. The input layer includes four neurons, which receive temperature data, rainfall data, lightning current amplitude data and lightning current steepness data. The hidden layer is equipped with Sigmoid function and MSE function. The output layer includes three neurons, which output the influence of temperature on substation equipment, the influence of rainfall on substation cable tray and the influence of lightning on substation communication equipment. The neural network model is trained using the training set data, with the learning rate set to 0.01 and the number of iterations set to 3000. Through iterative training, the nonlinear relationship between temperature data and the degree of influence of temperature on substation equipment, the nonlinear relationship between rainfall data and the degree of influence of rainfall on substation cable trays, and the degree of influence of lightning current amplitude data and lightning current steepness data on substation communication equipment are learned. The output value of the output layer is mapped to the [0,1] interval using the Sigmoid function to obtain the neural network model. The test set data is input into the trained neural network model, and the MSE function is used to evaluate the error between the output value of the neural network model and the actual value. The parameters of the neural network model are adjusted according to the evaluation results, the performance of the neural network model is optimized, and the substation environment monitoring model is obtained.

8. The intelligent operation and maintenance system for substations based on big data according to claim 7 is characterized in that: The environmental assessment module evaluates the impact of substation environmental factors on substation intelligent operation and maintenance, including: According to the fact that substation equipment, substation cable tray and substation communication equipment are components of the intelligent operation and maintenance process of substations, the impact of temperature on substation equipment is equivalent to the impact of temperature on the intelligent operation and maintenance of substations, the impact of rainfall on substation cable trays is equivalent to the impact of rainfall around substation cable trays on the intelligent operation and maintenance of substations, and the impact of lightning on substation communication equipment is equivalent to the impact of lightning on the intelligent operation and maintenance of substations. Combined with the substation environmental monitoring model, the impact of substation environmental factors on the intelligent operation and maintenance of substations is evaluated; When the impact of temperature on the intelligent operation and maintenance of substation is less than 30%, the impact of temperature on the intelligent operation and maintenance of substation is low; when the impact of temperature on the intelligent operation and maintenance of substation is between 30% and 60%, the impact of temperature on the intelligent operation and maintenance of substation is medium; when the impact of temperature on the intelligent operation and maintenance of substation is higher than 60%, the impact of temperature on the intelligent operation and maintenance of substation is high; When the impact of rainfall on the intelligent operation and maintenance of substations is less than 40%, the impact of rainfall on the intelligent operation and maintenance of substations is low; when the impact of rainfall on the intelligent operation and maintenance of substations is between 40% and 60%, the impact of rainfall on the intelligent operation and maintenance of substations is medium; when the impact of rainfall on the intelligent operation and maintenance of substations is higher than 60%, the impact of rainfall on the intelligent operation and maintenance of substations is high; When the impact of lightning on the intelligent operation and maintenance of substations is less than 20%, the impact of lightning on the intelligent operation and maintenance of substations is low; when the impact of lightning on the intelligent operation and maintenance of substations is between 20% and 50%, the impact of lightning on the intelligent operation and maintenance of substations is medium; when the impact of lightning on the intelligent operation and maintenance of substations is higher than 50%, the impact of lightning on the intelligent operation and maintenance of substations is high.

9. The intelligent operation and maintenance system for substations based on big data according to claim 8 is characterized in that: The process of the intelligent operation and maintenance execution module taking corresponding measures and sending signals to the client to deal with the substation environment includes: When the temperature has a low impact on the intelligent operation and maintenance of the substation, the frequency of temperature monitoring is increased, real-time temperature data is recorded, and the temperature change trend is predicted; when the temperature has a medium impact on the intelligent operation and maintenance of the substation, the heat dissipation equipment is started, and a temperature warning signal is sent to the client, and the client formulates a solution; when the temperature has a high impact on the intelligent operation and maintenance of the substation, the refrigeration equipment is started, the operation of the equipment with abnormal temperature is stopped, and a temperature emergency signal is sent to the client, and the client repairs the equipment with abnormal temperature; When rainfall has a low impact on the intelligent operation and maintenance of the substation, the operation status of rainfall and drainage system is continuously monitored and rainfall data is recorded; when rainfall has a medium impact on the intelligent operation and maintenance of the substation, the monitoring frequency of rainfall is increased, the drainage pipes are checked, and a rainfall warning signal is issued to the client; when rainfall has a high impact on the intelligent operation and maintenance of the substation, the drainage equipment is started, waterproof sandbags are added, the operation of equipment greatly affected by rainfall is stopped, and a rainfall emergency signal is issued to the client; When lightning has a low impact on the intelligent operation and maintenance of the substation, the monitoring frequency of the lightning current amplitude and lightning current steepness is increased, the lightning activity data is recorded, and a lightning prompt message is sent to the client, who checks the operation of the lightning protection equipment; when lightning has a medium impact on the intelligent operation and maintenance of the substation, the grounding resistance access of the lightning protection equipment is checked, and the operation mode of the substation equipment is adjusted according to the impact of lightning, and a lightning warning signal is sent to the client; when lightning has a high impact on the intelligent operation and maintenance of the substation, a lightning emergency signal is sent to the client, and the client initiates emergency repair work.

10. A substation intelligent operation and maintenance method based on big data, implemented based on the substation intelligent operation and maintenance system based on big data according to any one of claims 1 to 9, characterized in that: It consists of the following steps: Step 1: Use temperature sensors, tipping bucket rain gauges, Rogowski coils, Pearson current transformers and oscilloscopes to collect the temperature of substation equipment, rainfall around the substation cable tray, lightning current amplitude and lightning current steepness; Step 2: Preprocess the substation environmental data, select a MySQL database, store the substation environmental data, and use the substation environmental data to obtain the degree of influence of temperature on substation equipment, the degree of influence of rainfall on substation cable trays, and the degree of influence of lightning on substation communication equipment; Step 3: Use neural network algorithm to build a substation environment monitoring model; Step 4: Combine the substation environmental monitoring model to evaluate the impact of substation environmental factors on substation intelligent operation and maintenance; Step 5: Based on the evaluation results, take appropriate measures and send an alarm to the client to deal with the substation environment.

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