Intelligent prediction and maintenance method and system of power grid auxiliary control system

Abstract

The invention discloses an intelligent prediction and maintenance method and system for a power grid auxiliary control system, and relates to the technical field of power grid management and control, and the method comprises the steps: obtaining the electromagnetic field intensity and voltage waveform of a power grid in real time, building a standard library, carrying out Fourier transform and modeling, and obtaining an abnormal coefficient through abnormal processing and discontinuous point detection; high-frequency electromagnetic wave influence is predicted according to the coefficient, and a voltage waveform is fitted through a cubic spline interpolation method in case of abnormality, so that the system is ensured to be normal. According to the method, the electromagnetic field intensity is collected in real time, library establishment and comparison are performed, voltage waveform Fourier transform and discontinuity point detection are combined, the abnormal coefficient is comprehensively calculated, high-frequency interference is pre-judged, and waveform distortion is avoided; for abnormal waveforms, cubic spline interpolation is used for fitting discontinuous intervals, continuous functions and derivatives are met, signal self-repairing is achieved, and cost reduction and stability maintaining are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid control, and specifically to an intelligent prediction and maintenance method and system for a power grid auxiliary control system. Background Art

[0002] The intelligent prediction and maintenance system of the power grid auxiliary control system is mainly used for real-time monitoring of the operating states of auxiliary equipment such as transformers, circuit breakers, and motors in the power system, potential fault prediction, and precise maintenance decision-making. By integrating multi-source data and intelligent algorithms, it can identify equipment anomalies in advance, dynamically generate preventive or proactive maintenance strategies, avoid unplanned power outages and over-maintenance, achieve full-life cycle management of equipment, thereby improving the reliability of power grid operation, reducing operation and maintenance costs, optimizing resource allocation, and ensuring the safe and stable operation of the power system.

[0003] When high-power radio transmitting equipment or industrial equipment is operating, it will radiate high-frequency electromagnetic energy in the range of several hundred MHz to GHz into space. These high-frequency electromagnetic waves can directly penetrate the non-shielded enclosure of the power grid auxiliary control system through radiation coupling, or induce electromagnetic energy into the internal circuit of the power grid auxiliary control system through conductors such as cables and antennas between equipment. Due to the overlap of the working frequency band and the interference frequency band of the high-frequency sensitive components in the auxiliary control system, abnormal high-frequency noise is easily injected, resulting in distortion of the voltage waveform signal transmission. Summary of the Invention

[0004] Technical Problem to be Solved

[0005] Aiming at the deficiencies of the prior art, the present invention provides an intelligent prediction and maintenance method and system for a power grid auxiliary control system, which solves the problem that high-frequency electromagnetic energy radiated by high-power radio or industrial equipment enters the power grid auxiliary control system through radiation coupling, causing distortion of the voltage waveform signal transmission due to noise interference of high-frequency sensitive components.

[0006] Technical Solution

[0007] To achieve the above object, the present invention is realized through the following technical solutions: An intelligent prediction and maintenance method and system for a power grid auxiliary control system, including the following specific steps and modules: Step 1: Real-time obtain the actual electromagnetic field intensity inside the power grid, establish a power grid electromagnetic field standard intensity database for matching and anomaly processing to obtain electromagnetic field anomaly values, real-time obtain the voltage waveform and perform Fourier transform, establish a sine or cosine mathematical model based on the time series and the voltage waveform, and obtain the discontinuity value and the number of discontinuity values through the discontinuity point detection algorithm, and comprehensively analyze to obtain the voltage waveform signal anomaly coefficient; Step 2: Predict whether the power grid auxiliary control system is affected by high-frequency electromagnetic waves according to the voltage waveform signal anomaly coefficient. If it is predicted that the power grid auxiliary control system is normal, return to Step 1 and continue to execute Step 1 to Step 2. If it is predicted that the power grid auxiliary control system is abnormal, execute Step 3 to make the power grid auxiliary control system normal; Step 3: Fit the voltage waveform signal by the cubic spline interpolation method to make the power grid auxiliary control system normal.

[0008] Further, the specific way to obtain the electromagnetic field anomaly value is as follows: Clean the actual electromagnetic field intensity, set the electromagnetic field anomaly value, save the standard electromagnetic field intensity in the power grid electromagnetic field standard intensity database, sort the standard electromagnetic field intensity in ascending order by bubble sort, denoted as the standard set, and perform real-time comparison between the actual electromagnetic field intensity and the standard set. If the actual electromagnetic field intensity is less than the minimum standard electromagnetic field intensity in the standard set, calculate the difference between the minimum standard electromagnetic field intensity and the actual electromagnetic field intensity to obtain the electromagnetic field intensity decrease value, and assign the electromagnetic field intensity decrease value to the electromagnetic field anomaly value. If the actual electromagnetic field intensity is greater than the maximum standard electromagnetic field intensity in the standard set, calculate the difference between the actual electromagnetic field intensity and the maximum standard electromagnetic field intensity to obtain the electromagnetic field intensity increase value, and assign the electromagnetic field intensity increase value to the electromagnetic field anomaly value. If the actual electromagnetic field intensity is within the standard set, assign the electromagnetic field anomaly value to zero.

[0009] Further, the specific way to obtain the discontinuity value is as follows: The voltage waveform includes waveform frequency, waveform amplitude, and waveform phase. For the voltage waveform function obtained according to the sine or cosine mathematical model, take the derivative of the voltage waveform function to obtain the voltage waveform derivative function. Calculate the left voltage waveform derivative function value and the right voltage waveform derivative function value for each moment of the voltage waveform derivative function value according to the time series using the limit method. Calculate the difference between the left voltage waveform derivative function value and the right voltage waveform derivative function value to obtain the deviation value. Compare the deviation value with zero. If the deviation value is equal to zero, continue the detection. If the deviation value is not equal to zero, record the absolute value of the deviation value as the discontinuity value.

[0010] Further, the specific way to obtain the left voltage waveform derivative function value is as follows: Select a certain moment and denote it as t, and denote the moment infinitely close to the left of t as t -, so the derivative value of the left voltage waveform is where t represents a certain moment, t - represents infinitely close to the left of t, and ZD′ represents the derivative value of the left voltage waveform.

[0011] Further, the specific method for obtaining the derivative value of the right voltage waveform is as follows: Select a certain moment and denote it as t, and infinitely close to the right of t is denoted as t + , so the derivative value of the right voltage waveform is where t represents a certain moment, t + represents infinitely close to the right of t, and YD′ represents the derivative value of the right voltage waveform.

[0012] Further, the specific method for obtaining the abnormal coefficient of the voltage waveform signal is as follows: Standardize and comprehensively calculate the electromagnetic field abnormal value, the number of discontinuous values, and the discontinuous values to obtain the abnormal coefficient of the voltage waveform signal; where XY represents the abnormal coefficient of the voltage waveform signal, CY represents the electromagnetic field abnormal value, n represents the number of discontinuous values, and JD represents the discontinuous value.

[0013] Further, in step two, the voltage waveform signal threshold is obtained through historical experiments, and the abnormal coefficient of the voltage waveform signal is compared with the voltage waveform signal threshold in real time. If the abnormal coefficient of the voltage waveform signal is less than the voltage waveform signal threshold, it is predicted that the grid auxiliary control system is normal; if the abnormal coefficient of the voltage waveform signal is greater than or equal to the voltage waveform signal threshold, it is predicted that the grid auxiliary control system is abnormal.

[0014] Further, the specific steps to make the grid auxiliary control system normal are as follows: Obtain the discontinuous point through the discontinuous value of the voltage waveform function, denote it as A, set the discontinuous interval containing A, denote the left endpoint of the discontinuous interval as j, and the right endpoint of the discontinuous interval as k. Set the cubic polynomial at 3 +bt 2 +ct + d, make the value of the cubic polynomial equal to the value of the voltage waveform function, and the derivative value of the cubic polynomial equal to the derivative value of the voltage waveform. Substitute j and k into the voltage waveform function respectively to obtain the equation about j and the equation about k. Then substitute j and k into the voltage waveform derivative respectively to obtain the derivative equation about j and the derivative equation about k. Combine the equation about j, the equation about k, the derivative equation about j, and the derivative equation about k to form a system of equations and solve it to obtain a, b, c, and d. Then substitute a, b, c, and d into the cubic polynomial, and substitute the original discontinuous point into the cubic polynomial to obtain the normal voltage waveform value.

[0015] Further, the method for obtaining the discontinuous interval is as follows: Traverse other moments on both sides of the discontinuous point, and randomly select continuous points on both sides of A to form the discontinuous interval.

[0016] Further, a voltage waveform signal analysis module, a voltage waveform signal prediction module, and a power grid auxiliary control system maintenance module; the voltage waveform signal analysis module is used to obtain the actual electromagnetic field strength inside the power grid in real time, establish a power grid electromagnetic field standard strength database for matching and anomaly processing, obtain the electromagnetic field anomaly value, obtain the voltage waveform in real time and perform Fourier transform, establish a sine or cosine mathematical model according to the time series and the voltage waveform, and obtain the discontinuity value and the number of discontinuity values through the discontinuity point detection algorithm, and comprehensively analyze to obtain the voltage waveform signal anomaly coefficient; the voltage waveform signal prediction module is used to predict whether the power grid auxiliary control system is affected by high-frequency electromagnetic waves according to the voltage waveform signal anomaly coefficient. If it is predicted that the power grid auxiliary control system is normal, return to step 1 and continue to execute steps 1 to 2. If it is predicted that the power grid auxiliary control system is abnormal, execute step 3 to make the power grid auxiliary control system normal; the power grid auxiliary control system maintenance module: is used to fit the voltage waveform signal by the cubic spline interpolation method to make the power grid auxiliary control system normal.

[0017] Advantageous Effects

[0018] Compared with the prior art, the embodiments of the present invention at least have the following advantages or beneficial effects:

[0019] 1. Collect the electromagnetic field strength in real time and establish a standard library, compare the actual value with the standard value to identify anomalies, combine the Fourier transform of the voltage waveform and the discontinuity point detection, comprehensively calculate the anomaly coefficient, predict the influence of high-frequency electromagnetic waves in advance, avoid voltage waveform distortion, reduce the risk of unplanned power outages, and improve the operation reliability of the power grid auxiliary control system.

[0020] 2. For abnormal waveforms, fit the discontinuous interval by the cubic spline interpolation method, construct a cubic polynomial and satisfy the conditions of function and derivative continuity, generate normal waveform values after solving the coefficients, eliminate the derivative discontinuity and waveform distortion caused by high-frequency interference, realize signal self-repair, reduce the maintenance cost, and ensure the stable operation of the equipment.

[0021] Of course, it is not necessary for any product implementing the present invention to achieve all the above-mentioned advantages simultaneously. Description of the Drawings

[0022] Figure 1 It is a flowchart of an intelligent prediction and maintenance method for a power grid auxiliary control system of the present invention.

[0023] Figure 2 It is a structural diagram of an intelligent prediction and maintenance system for a power grid auxiliary control system of the present invention. Detailed Embodiments

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0025] It should be noted that, in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or sequence between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device.

[0026] As Figure 1 shown, the embodiments of the present invention provide an intelligent prediction and maintenance method for a power grid auxiliary control system, including the following specific methods:

[0027] Step 1: Obtain the actual electromagnetic field intensity inside the power grid in real time through a field strength meter. Since high-frequency electromagnetic waves will cause changes in the actual electromagnetic field intensity in the power grid, the influence of external high-frequency electromagnetic waves on the power grid auxiliary control system is predicted according to the changes in the actual electromagnetic field intensity. The actual electromagnetic field intensity is cleaned to remove redundant values, improve the quality of the actual electromagnetic field intensity, establish a power grid electromagnetic field standard intensity database for storing the standard electromagnetic field intensity in the power grid, and match and perform anomaly processing on the actual electromagnetic field intensity and the standard electromagnetic field intensity to obtain an electromagnetic field anomaly value.

[0028] The specific way to obtain the electromagnetic field anomaly value is as follows:

[0029] Set the abnormal value of the electromagnetic field. Sort the standard electromagnetic field intensity in ascending order by bubble sort, denoted as the standard set. Compare the actual electromagnetic field intensity with the standard set in real time. If the actual electromagnetic field intensity is less than the minimum standard electromagnetic field intensity in the standard set, calculate the difference between the minimum standard electromagnetic field intensity and the actual electromagnetic field intensity to obtain the decreased value of the electromagnetic field intensity, which is greater than zero, and assign the decreased value of the electromagnetic field intensity to the abnormal value of the electromagnetic field. If the actual electromagnetic field intensity is greater than the maximum standard electromagnetic field intensity in the standard set, calculate the difference between the actual electromagnetic field intensity and the maximum standard electromagnetic field intensity to obtain the increased value of the electromagnetic field intensity, which is greater than zero, and assign the increased value of the electromagnetic field intensity to the abnormal value of the electromagnetic field. If the actual electromagnetic field intensity is within the standard set, it indicates that the actual electromagnetic field intensity meets the standard of the power grid electromagnetic field standard intensity database, that is, the actual electromagnetic field intensity is normal, and the power grid auxiliary control system is not affected by high-frequency electromagnetic waves. Then assign the abnormal value of the electromagnetic field to zero.

[0030] Obtain the voltage waveform in real time through a high-voltage probe and a high-speed oscilloscope. Since the high-frequency interference of high-frequency electromagnetic waves is superimposed on the power-frequency voltage, and the power-frequency voltage is the standard voltage frequency in the power grid, high-order harmonics are generated, resulting in voltage waveform distortion and affecting the accuracy of the voltage waveform signal of the power grid auxiliary control system. Therefore, obtain the voltage through the high-voltage probe and transmit it to the high-speed oscilloscope to obtain the voltage waveform. Predict whether the power grid auxiliary control system is affected by external high-frequency electromagnetic waves based on whether the voltage waveform is distorted. Clean the voltage waveform to remove redundant values and improve the accuracy of the voltage waveform. Perform Fourier transform on the voltage waveform to convert the chaotic voltage waveform into a sine wave or a cosine wave to obtain the voltage sine or cosine waveform. The voltage sine or cosine waveform includes waveform frequency, waveform amplitude, and waveform phase. Establish a sine or cosine mathematical model based on the waveform frequency, waveform amplitude, and waveform phase according to the time series to obtain the voltage waveform function. Detect the derivative discontinuity of the voltage waveform function through the discontinuity detection algorithm to obtain the discontinuity value.

[0031] The specific method for obtaining the discontinuity value is as follows:

[0032] Since the voltage waveform function is a sine or cosine function, both the function and its derivative are continuous. Take the derivative of the voltage waveform function to obtain the voltage waveform derivative function. Calculate the left voltage waveform derivative function value and the right voltage waveform derivative function value for the voltage waveform derivative function value at each moment according to the time series using the limit method. Calculate the difference between the left voltage waveform derivative function value and the right voltage waveform derivative function value to obtain the deviation value. Compare the deviation value with zero. If the deviation value is equal to zero, it means that the left voltage waveform derivative function value is equal to the right voltage waveform derivative function value, that is, the voltage waveform derivative function is continuous. Therefore, the voltage waveform function is continuous, that is, the voltage waveform is normal, and continue the detection. If the deviation value is not equal to zero, record the absolute value of the deviation value as the discontinuity value.

[0033] The specific methods for obtaining the derivative values of the left voltage waveform and the right voltage waveform are as follows:

[0034] Select a certain moment and denote it as t. Denote the moment infinitely close to the left of t as t - , and denote the moment infinitely close to the right of t as t + . Therefore, the derivative value of the left voltage waveform is where t represents a certain moment, t - represents the moment infinitely close to the left of t, and ZD′ represents the derivative value of the left voltage waveform; the derivative value of the right voltage waveform is where t represents a certain moment, t + represents the moment infinitely close to the right of t, and YD′ represents the derivative value of the right voltage waveform.

[0035] Count the number of discontinuous values to obtain the number of discontinuous values. Standardize and comprehensively calculate the electromagnetic field abnormal values, the number of discontinuous values, and the discontinuous values to obtain the abnormal coefficient of the voltage waveform signal. where XY represents the abnormal coefficient of the voltage waveform signal, which reflects whether the high-frequency electromagnetic wave causes an abnormality to the grid voltage waveform signal for prediction. CY represents the electromagnetic field abnormal value, which reflects whether the actual electromagnetic field intensity of the grid is abnormal. The larger the electromagnetic field abnormal value, the more abnormal the actual electromagnetic field intensity. n represents the number of discontinuous values, JD represents the discontinuous value and is not equal to zero. The larger the sum of the discontinuous values, the more discontinuous values there are, that is, the more discontinuous points of the voltage waveform function, reflecting the more serious distortion of the voltage waveform.

[0036] Step 2: Predict whether the grid auxiliary control system is affected by high-frequency electromagnetic waves according to the abnormal coefficient of the voltage waveform signal. Obtain the voltage waveform signal threshold through historical experiments, and compare the abnormal coefficient of the voltage waveform signal with the voltage waveform signal threshold in real time. If the abnormal coefficient of the voltage waveform signal is less than the voltage waveform signal threshold, it is predicted that the grid auxiliary control system is normal, return to Step 1 and continue to execute Step 1 to Step 2. If the abnormal coefficient of the voltage waveform signal is greater than or equal to the voltage waveform signal threshold, it is predicted that the grid auxiliary control system is abnormal, and execute Step 3 to make the grid auxiliary control system normal.

[0037] Step 3: Fit the voltage waveform signal by the cubic spline interpolation method to generate a normal voltage waveform, and prevent the high-frequency electromagnetic energy radiated by high-power radio or industrial equipment from entering the grid auxiliary control system through radiation coupling, so that the high-frequency sensitive components are affected by noise interference and cause distortion of the voltage waveform signal transmission.

[0038] The specific method for obtaining the normal voltage waveform is as follows:

[0039] By using the discontinuous value of the voltage waveform function, the discontinuous point is obtained and denoted as A. Other moments on both sides of the discontinuous point are traversed, and continuous points on both sides of A are randomly selected to form a discontinuous interval, where A is within the discontinuous interval and is the only discontinuous point. The left endpoint of the discontinuous interval is denoted as j, and the right endpoint of the discontinuous interval is denoted as k. A cubic polynomial at 3 +bt 2 +ct + d is set. By taking the derivative twice, the continuity is further verified, and the value of the cubic polynomial is made equal to the value of the voltage waveform function, and the derivative value of the cubic polynomial is made equal to the derivative value of the voltage waveform derivative function, ensuring overall continuity and smoothness while maintaining the original voltage waveform function value and voltage waveform derivative function value. Substitute j and k into the voltage waveform function respectively to obtain an equation about j and an equation about k. Then substitute j and k into the voltage waveform derivative function respectively to obtain a derivative equation about j and a derivative equation about k. Combine the equation about j, the equation about k, the derivative equation about j, and the derivative equation about k to form a system of equations and solve them to obtain a, b, c, and d. Then substitute a, b, c, and d into the cubic polynomial. At this time, the cubic polynomial is continuous, and the discontinuous interval becomes a continuous interval. Substitute the original discontinuous point into the cubic polynomial to obtain the normal voltage waveform value, ensuring the normal voltage waveform signal.

[0040] As Figure 2 shown, an intelligent prediction and maintenance system for a power grid auxiliary control system is provided in an embodiment of the present invention, which includes the following specific modules:

[0041] A voltage waveform signal analysis module, which is used to obtain the actual electromagnetic field strength inside the power grid in real time, establish a power grid electromagnetic field standard strength database for matching and anomaly processing to obtain electromagnetic field anomaly values, obtain the voltage waveform in real time and perform Fourier transform, establish a sine or cosine mathematical model based on the time series and the voltage waveform, and obtain the discontinuous value and the number of discontinuous values through a discontinuous point detection algorithm, and comprehensively analyze to obtain the voltage waveform signal anomaly coefficient;

[0042] A voltage waveform signal prediction module, which is used to predict whether the power grid auxiliary control system is affected by high-frequency electromagnetic waves according to the voltage waveform signal anomaly coefficient. If it is predicted that the power grid auxiliary control system is normal, return to step one and continue to execute steps one to two. If it is predicted that the power grid auxiliary control system is abnormal, execute step three to make the power grid auxiliary control system normal;

[0043] A power grid auxiliary control system maintenance module: which is used to fit the voltage waveform signal by cubic spline interpolation method to make the power grid auxiliary control system normal.

[0044] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An intelligent prediction and maintenance method for a power grid auxiliary control system, characterized in that: It includes the following specific steps: Step 1: Obtain the actual electromagnetic field intensity inside the power grid in real time, establish a standard electromagnetic field intensity database for the power grid for matching and anomaly processing to obtain the electromagnetic field anomaly value, obtain the voltage waveform in real time and perform Fourier transform, establish a sine or cosine mathematical model based on the time series and the voltage waveform, and obtain the discontinuity value and the number of discontinuity values through the discontinuity point detection algorithm, and comprehensively analyze to obtain the voltage waveform signal anomaly coefficient; Step 2: Predict whether the auxiliary control system of the power grid is affected by high-frequency electromagnetic waves according to the voltage waveform signal anomaly coefficient. If it is predicted that the auxiliary control system of the power grid is normal, return to Step 1 and continue to execute Steps 1 to 2. If it is predicted that the auxiliary control system of the power grid is abnormal, execute Step 3 to make the auxiliary control system of the power grid normal; Step 3: Fit the voltage waveform signal by the cubic spline interpolation method to make the auxiliary control system of the power grid normal.

2. The intelligent prediction and maintenance method of a power grid auxiliary control system according to claim 1, characterized in that: The specific way to obtain the electromagnetic field anomaly value is as follows: Clean the actual electromagnetic field intensity, set the electromagnetic field anomaly value, save the standard electromagnetic field intensity in the power grid electromagnetic field standard intensity database, sort the standard electromagnetic field intensity in ascending order by bubble sort, denoted as the standard set, and perform real-time comparison between the actual electromagnetic field intensity and the standard set. If the actual electromagnetic field intensity is less than the minimum standard electromagnetic field intensity in the standard set, calculate the difference between the minimum standard electromagnetic field intensity and the actual electromagnetic field intensity to obtain the electromagnetic field intensity decrease value, and assign the electromagnetic field intensity decrease value to the electromagnetic field anomaly value. If the actual electromagnetic field intensity is greater than the maximum standard electromagnetic field intensity in the standard set, calculate the difference between the actual electromagnetic field intensity and the maximum standard electromagnetic field intensity to obtain the electromagnetic field intensity increase value, and assign the electromagnetic field intensity increase value to the electromagnetic field anomaly value. If the actual electromagnetic field intensity is within the standard set, assign zero to the electromagnetic field anomaly value.

3. The intelligent prediction and maintenance method of a power grid auxiliary control system according to claim 1, characterized in that: The specific way to obtain the discontinuity value is as follows: The voltage waveform includes waveform frequency, waveform amplitude, and waveform phase. For the voltage waveform function obtained according to the sine or cosine mathematical model, take the derivative of the voltage waveform function to obtain the voltage waveform derivative function. Calculate the left voltage waveform derivative function value and the right voltage waveform derivative function value for the value of the voltage waveform derivative function at each moment according to the time series by the limit method, calculate the difference between the left voltage waveform derivative function value and the right voltage waveform derivative function value to obtain the deviation value, and compare the deviation value with zero. If the deviation value is equal to zero, continue the detection. If the deviation value is not equal to zero, record the absolute value of the deviation value as the discontinuity value.

4. The intelligent prediction and maintenance method of a power grid auxiliary control system according to claim 3, characterized in that: The specific way to obtain the left voltage waveform derivative function value is as follows: Select a certain moment and denote it as \(t\), and denote the moment infinitely close to the left of \(t\) as \(t^-\). - , so the derivative value of the left voltage waveform is where \(t\) represents a certain moment, \(t^-\) - represents the moment infinitely close to the left of \(t\), and \(ZD'\) represents the derivative value of the left voltage waveform.

5. The intelligent prediction and maintenance method of a power grid auxiliary control system according to claim 3, characterized in that: The specific way to obtain the right voltage waveform derivative function value is as follows: Select a certain moment and denote it as t. Denote the moment infinitely close to the right of t as t + , so the derivative value of the right voltage waveform is where t represents a certain moment, and t + represents the moment infinitely close to the right of t, and YD′ represents the derivative value of the right voltage waveform.

6. The intelligent prediction and maintenance method of a power grid auxiliary control system according to claim 1, wherein: The specific way to obtain the voltage waveform signal anomaly coefficient is as follows: Standardize and comprehensively calculate the electromagnetic field anomaly value, the number of discontinuity values, and the discontinuity value to obtain the voltage waveform signal anomaly coefficient; Where XY represents the voltage waveform signal anomaly coefficient, CY represents the electromagnetic field anomaly value, n represents the number of discontinuity values, and JD represents the discontinuity value.

7. According to the intelligent prediction and maintenance method of an auxiliary control system of a power grid described in claim 1, characterized in that: In step two, the voltage waveform signal threshold is obtained through historical experiments, and the voltage waveform signal anomaly coefficient is compared with the voltage waveform signal threshold in real time. If the voltage waveform signal anomaly coefficient is less than the voltage waveform signal threshold, it is predicted that the grid auxiliary control system is normal. If the voltage waveform signal anomaly coefficient is greater than or equal to the voltage waveform signal threshold, it is predicted that the grid auxiliary control system is abnormal.

8. An intelligent prediction and maintenance method for a power grid auxiliary control system according to claim 1, characterized in that: The specific steps to make the grid auxiliary control system normal are as follows: Obtain the discontinuous point from the discontinuous value of the voltage waveform function, denoted as A. Set the discontinuous interval containing A, where the left endpoint of the discontinuous interval is denoted as j and the right endpoint of the discontinuous interval is denoted as k. Set the cubic polynomial at 3 +bt 2 +ct + d such that the value of the cubic polynomial is equal to the value of the voltage waveform function and the derivative value of the cubic polynomial is equal to the derivative value of the voltage waveform function. Substitute j and k into the voltage waveform function respectively to obtain the equation about j and the equation about k. Then substitute j and k into the derivative of the voltage waveform function respectively to obtain the derivative equation about j and the derivative equation about k. Combine the equation about j, the equation about k, the derivative equation about j, and the derivative equation about k into a system of equations and solve them to obtain a, b, c, and d. Then substitute a, b, c, and d into the cubic polynomial, and substitute the original discontinuous point into the cubic polynomial to obtain the normal voltage waveform value.

9. The intelligent prediction and maintenance method of a power grid auxiliary control system according to claim 8, characterized in that: The acquisition method of the discontinuous interval is as follows: Traverse other moments on both sides of the discontinuous point, and randomly select continuous points on both sides of A to form a discontinuous interval.

10. An intelligent prediction and maintenance system for a power grid auxiliary control system, which is used to implement the intelligent prediction and maintenance method of a power grid auxiliary control system according to any one of claims 1-9, characterized in that The system includes: a voltage waveform signal analysis module, a voltage waveform signal prediction module, and a grid auxiliary control system maintenance module; The voltage waveform signal analysis module is used to obtain the actual electromagnetic field strength inside the grid in real time, establish a grid electromagnetic field standard strength database for matching and anomaly processing to obtain the electromagnetic field anomaly value, obtain the voltage waveform in real time and perform Fourier transform, establish a sine or cosine mathematical model based on the time series and the voltage waveform, and obtain the discontinuous value and the number of discontinuous values through the discontinuous point detection algorithm, and comprehensively analyze to obtain the voltage waveform signal anomaly coefficient; The voltage waveform signal prediction module is used to predict whether the grid auxiliary control system is affected by high-frequency electromagnetic waves according to the voltage waveform signal anomaly coefficient. If it is predicted that the grid auxiliary control system is normal, return to step one and continue to execute step one to step two. If it is predicted that the grid auxiliary control system is abnormal, execute step three to make the grid auxiliary control system normal; The grid auxiliary control system maintenance module: is used to fit the voltage waveform signal by the cubic spline interpolation method to make the grid auxiliary control system normal.

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