Early warning method and system for preventing maloperation of spare power automatic switching device based on centralized control system

Abstract

The invention discloses an early warning method and system for preventing maloperation of spare power automatic switching based on a centralized control system, and relates to the technical field of spare power automatic switching, and the method comprises the following steps: obtaining the operation state data and node phase angle data of a power system in real time; according to the operation state data and the node phase angle data, a spare power automatic switching maloperation early warning model is constructed based on machine learning, and a maloperation early warning coefficient is generated; the generated maloperation early warning coefficient is compared with a preset maloperation early warning threshold value, and whether the risk of spare power automatic switching maloperation exists or not is judged; and when the spare power automatic switching maloperation risk exists, re-judgment is carried out based on the factors causing the spare power automatic switching maloperation, and an early warning is given out. When the maloperation early warning coefficient exceeds a preset threshold value, the system can immediately judge the risk of spare power automatic switching maloperation, and re-judgment is carried out based on the factors causing maloperation. According to the invention, the instant response mechanism is helpful for rapidly taking measures and preventing maloperation events.

Description

Technical Field

[0001] The present invention relates to the technical field of power system control, and more specifically, to an early warning method and system for preventing false operation of standby automatic switching based on a centralized control system. Background Art

[0002] Substations are an important part of the power system, and their stable operation is crucial to the safety of the entire power grid. The large-scale access of new energy sources such as wind power and photovoltaics has caused the load of the power grid to be volatile and intermittent. Under low load conditions, if the bus voltage of the substation disappears, the backup automatic transfer device may operate incorrectly, trip the main supply line, and cause the backup automatic transfer to malfunction. During the operation and maintenance process, the secondary circuit breaker of the bus voltage transformer may be disconnected due to operational errors, equipment failures or other reasons. At this time, if a small load is superimposed, it may cause the backup automatic transfer to malfunction and affect the stability of the power grid. Therefore, the design can effectively warn the judgment logic in the above two situations in advance, and remind maintenance and other related personnel to take corresponding effective measures to avoid the impact of new energy grid connection on the backup automatic transfer action and ensure the safe operation of the power grid.

[0003] It is difficult for existing technologies to completely solve the problem of false operation, and it may also increase construction and operation costs. The patent "An export logic method and device for preventing the false operation of the backup power supply automatically" (CN 114598023 A) introduces a current change rate locking condition instead of a no-current fixed value judgment criterion. This method has the risk of the backup power supply refusing to operate. The patent "Method for preventing the backup power supply from falsely operating due to load PT line break under small load conditions" (CN 101699700 A) adds line voltage as an opening condition for the backup power supply action function, and requires the addition of a voltage transformer on the line side, which increases the construction and operation costs of the substation. Therefore, it is particularly important to develop an early warning system that can effectively prevent the false operation of the backup power supply.

[0004] The above disclosed technical solution has at least the following technical problems: the existing technology is difficult to completely solve the problem of false operation, and may also increase construction and operation costs. Under light load conditions, if the substation bus voltage disappears, the backup automatic switching device may erroneously operate, trip the main supply line, and cause false operation of the backup automatic switching. During the operation and maintenance process, the secondary circuit breaker of the bus voltage transformer may be disconnected due to operating errors, equipment failures or other reasons. At this time, if a small load condition is superimposed, it may cause the backup automatic switching to erroneously operate. In view of the above problems, the present invention proposes a solution. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method and system for preventing false operation of standby automatic start-up based on a centralized control system. By constructing a false operation warning model for standby automatic start-up, false operation of standby automatic start-up can be predicted more accurately to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions: A method for preventing false operation of a standby power supply based on a centralized control system comprises the following steps: acquiring the operation status data and node phase angle data of the power system in real time; constructing a false operation warning model for a standby power supply based on machine learning according to the operation status data and the node phase angle data, and generating a false operation warning coefficient; comparing the generated false operation warning coefficient with a preset false operation warning threshold to determine whether there is a risk of false operation of the standby power supply; when there is a risk of false operation of the standby power supply, re-determining based on the factors causing the false operation of the standby power supply and issuing a warning.

[0007] In a preferred embodiment, the operating status data includes a voltage waveform coefficient and a load abnormality coefficient, and the node phase angle data includes a phase angle deviation coefficient; the specific method for obtaining the voltage waveform coefficient is as follows: real-time acquisition of the voltage waveform data of the power system, and displaying the collected voltage waveform data in the time domain; obtaining the voltage time domain waveform, filtering out the part with the lowest fundamental frequency in the voltage time domain waveform; performing harmonic analysis on the filtered voltage time domain waveform, and obtaining the voltage harmonic amplitude and voltage harmonic period through Fourier transform; combining the voltage harmonic amplitude, voltage harmonic period and harmonic frequency to calculate the harmonic effective value; combining the voltage fundamental frequency, voltage harmonic phase and harmonic effective value to calculate the voltage waveform coefficient.

[0008] In a preferred embodiment, the specific method for obtaining the load anomaly coefficient is as follows: obtain historical load data of the power equipment; calculate the average value, standard deviation, maximum value, and minimum value statistical characteristic values ​​of the load based on the historical load data; set the load threshold range based on the average value, standard deviation, maximum value, and minimum value statistical characteristic values ​​of the load and record the number of load anomalies exceeding the load threshold range; collect and calculate the real-time load standard deviation and load average value at different times within time p; calculate the load anomaly index based on the load standard deviation and load average value; calculate the load anomaly coefficient by combining the load anomaly index with the load anomaly number.

[0009] In a preferred embodiment, the specific method for obtaining the phase angle deviation coefficient is as follows: using a phase meter to collect phase angle data of each node in the power system in real time, using a low-pass filter to remove high-frequency noise and interference in the phase angle data, and retaining effective signals; based on the phasor analysis method, the voltage and current signals are converted into complex forms, and the phase angles of the voltage and current signals are calculated; the phase angle deviations of the voltage and current signals between different nodes are calculated to obtain the deviation values; and the phase angle deviation coefficient is calculated by statistically analyzing the phase angle deviation values ​​in several time periods.

[0010] In a preferred embodiment, the generated malfunction warning coefficient is compared with a preset malfunction warning threshold to determine whether there is a risk of malfunction of the standby automatic start-up, specifically: if the generated malfunction warning coefficient is greater than the preset malfunction warning threshold, there is a risk of malfunction of the standby automatic start-up; if the generated malfunction warning coefficient is less than the preset malfunction warning threshold, the malfunction warning coefficient of the power system in several time periods is continuously obtained to form malfunction warning time series data and the average value and standard deviation of the malfunction warning time series data are calculated; if the average value of the malfunction warning time series data is greater than the average reference threshold of the malfunction warning time series data, a warning is issued and stability maintenance is performed; if the average value of the malfunction warning time series data is less than the average reference threshold of the malfunction warning time series data, and the standard deviation of the malfunction warning time series data is greater than the preset standard deviation reference threshold, continuous monitoring is performed; if the average value of the malfunction warning time series data is less than the average reference threshold of the malfunction warning time series data, and the standard deviation of the malfunction warning time series data is less than the preset standard deviation reference threshold, there is no risk of malfunction of the standby automatic start-up.

[0011] In a preferred embodiment, when there is a risk of misoperation of the backup automatic start-up, a re-judgment is made based on the factors causing the misoperation of the backup automatic start-up and an early warning is issued, specifically: the factors causing the misoperation of the backup automatic start-up include the opening of the current blocking causing the misoperation of the backup automatic start-up and the bus voltage reduction causing the misoperation of the backup automatic start-up; the opening of the current blocking causing the misoperation of the backup automatic start-up is specifically: (a) real-time monitoring of the current of the two incoming lines of the substation; (b) if the incoming line current is less than the no-current set value, the corresponding incoming line meets the early warning action condition 1; (c) real-time monitoring of the two incoming lines If the switch position is in the closed position, the corresponding incoming line meets the warning action condition 2; (d) When any incoming line meets the warning action condition 1 and the warning action condition 2 at the same time, the delay is to avoid the specified time Ts of the standby automatic action time, and the warning signal is output, otherwise it returns to step (a); (e) Through the interface of the centralized control system, the current lock is opened to the maintenance personnel, operation and maintenance personnel, and on-site supervision personnel in the form of pop-up warnings in the substation background, push notifications from the security risk control platform, and SMS push notifications to prevent the wrong classification of the busbar secondary voltage circuit breaker.

[0012] In a preferred embodiment, the bus voltage reduction causes the standby automatic re-start malfunction, specifically: (1) real-time monitoring of the current of the two incoming lines of the substation; (2) if the incoming line current is less than the no-current set value, the corresponding incoming line meets the warning action condition one; (3) real-time monitoring of the switch positions of the two incoming lines, if they are in the closed position, the corresponding incoming line meets the warning action condition two; (4) when any incoming line meets both the warning action conditions one and two, after a delay of the specified time Ts to avoid the standby automatic re-start action time, the warning signal is output, otherwise it returns to step (1); (5) through the interface of the centralized control system, the current lock is opened to the maintenance personnel, operation and maintenance personnel, and on-site supervision personnel in the form of a pop-up warning window in the background of the substation, a push notification from the security risk control platform, and a text message push notification, to prevent the bus secondary voltage from being misclassified.

[0013] In a preferred embodiment, the method for preventing the false operation of the standby power supply based on the centralized control system is characterized by comprising the following modules: a data acquisition module, a module for constructing a false operation warning model for the standby power supply, a module for judging the false operation of the standby power supply, and a re-judgment module. Data acquisition module: used to obtain the operating status data and node phase angle data of the power system in real time; module for constructing a false operation warning model for the standby power supply: used to construct a false operation warning model for the standby power supply based on machine learning according to the operating status data and node phase angle data, and generate a false operation warning coefficient; module for judging the false operation of the standby power supply: used to compare the generated false operation warning coefficient with the preset false operation warning threshold value, and judge whether there is a risk of false operation of the standby power supply; re-judgment module: used to make a re-judgment and issue a warning based on the factors causing the false operation of the standby power supply when there is a risk of false operation of the standby power supply.

[0014] The technical effects and advantages of the early warning method and system for preventing false operation of standby automatic switching based on the centralized control system of the present invention are as follows: 1. The present invention obtains the operating status data and node phase angle data of the power system in real time through the centralized control system. This means that the system can instantly reflect the current status of the power system without waiting for manual input or delayed data transmission. The standby automatic re-start misoperation warning model constructed using machine learning technology can generate a misoperation warning coefficient based on real-time data. By training and learning patterns in historical data, the machine learning algorithm can more accurately predict and identify risk factors that may cause standby automatic re-start misoperation. When the misoperation warning coefficient exceeds the preset threshold, the system can immediately determine that there is a risk of standby automatic re-start misoperation, and re-judge based on the factors that cause the misoperation. This immediate response mechanism helps to take quick measures to prevent the occurrence of misoperation events. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 The present invention is a schematic structural diagram of an early warning method for preventing false operation of standby automatic switching based on a centralized control system.

[0016] Figure 2The present invention is a schematic structural diagram of an early warning system for preventing false operation of standby automatic switching based on a centralized control system. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Embodiment 1, Figure 1 The present invention provides a method for preventing false operation of standby automatic switching based on a centralized control system, comprising the following steps: S1, real-time acquisition of power system operation status data and node phase angle data; The operating status data includes a voltage waveform coefficient and a load abnormality coefficient, and the node phase angle data includes a phase angle deviation coefficient; The voltage waveform factor reflects the shape and quality of the voltage waveform and is an important indicator for evaluating the stability of the voltage waveform of the power system. When the voltage waveform factor deviates from the normal value, it may mean that the voltage waveform of the power system is distorted or unstable. By real-time monitoring and analyzing the changes in the voltage waveform factor, the stability and reliability of the power system can be improved, the occurrence of false operation of the backup automatic switching can be reduced, and a strong guarantee can be provided for the safe operation of the power system.

[0019] The specific method for obtaining the voltage waveform coefficient is as follows: Collect voltage waveform data of the power system in real time and display the collected voltage waveform data in the time domain; Obtain the voltage time domain waveform, and filter out the part with the lowest fundamental frequency in the voltage time domain waveform; Perform harmonic analysis on the filtered voltage time domain waveform, and obtain the voltage harmonic amplitude and voltage harmonic period through Fourier transform; Combining the voltage harmonic amplitude, voltage harmonic period and harmonic frequency, the effective value of harmonics is calculated; The voltage waveform coefficient is calculated by combining the voltage fundamental frequency, voltage harmonic phase and harmonic effective value.

[0020] The calculation formula of the effective value of harmonics is:

[0021] The specific calculation formula of the voltage waveform coefficient is as follows:

[0022] in, is the voltage harmonic period, is the harmonic frequency, is the voltage harmonic amplitude, is the voltage harmonic frequency, is the voltage harmonic phase, F is the harmonic effective value, is the voltage waveform factor.

[0023] The voltage waveform coefficient has the following effects on preventing the false alarm of the backup automatic switching: Real-time monitoring of voltage waveform stability: The voltage waveform coefficient can reflect the voltage waveform stability of the power system in real time. When the voltage waveform is distorted or unstable, it may cause equipment damage, power quality degradation, or even system crash. By monitoring the voltage waveform coefficient, abnormal voltage waveforms can be discovered in a timely manner, so that appropriate measures can be taken to intervene and adjust.

[0024] Warning of the risk of false operation of the backup automatic switch: When the voltage waveform is unstable or severely distorted, the backup automatic switch may malfunction, resulting in unnecessary power switching or fault expansion. When the voltage waveform coefficient deviates from the normal value, the risk of false operation of the backup automatic switch increases. By monitoring the voltage waveform coefficient, this risk can be discovered and warned in time, thereby avoiding false operation of the backup automatic switch.

[0025] Improve the reliability of power system operation: Through real-time monitoring and analysis of voltage waveform coefficients, operation and maintenance personnel can promptly discover potential problems in the power system, such as voltage fluctuations and harmonic interference. If these problems are not handled in a timely manner, they may cause equipment damage, power quality degradation, or even system collapse. By promptly discovering and handling these problems, the stable operation of the power system can be ensured and the reliability of the power system can be improved.

[0026] Assisted fault diagnosis and location: When a power system fails, the voltage waveform factor may change. By analyzing the change in the voltage waveform factor, the type and location of the fault can be determined. For example, when the voltage waveform factor suddenly drops, it may mean that a device in the power system has a short circuit or ground fault. By combining other electrical parameters and fault information, the specific location and cause of the fault can be further determined, so that appropriate measures can be taken to repair it.

[0027] The load anomaly coefficient is an indicator used to measure the load changes in the power system. It can be obtained by real-time monitoring of the load data of the power system and calculating parameters such as the load fluctuation range and change rate. When the load anomaly coefficient exceeds a certain threshold, it means that the power system may have load anomalies or faults, and timely measures need to be taken to deal with them.

[0028] The specific method for obtaining the load abnormality coefficient is as follows: Obtain historical load data of power equipment; According to the historical load data, calculate the average value, standard deviation, maximum value and minimum value of the load statistical characteristic values; Set the load threshold range according to the load average, standard deviation, maximum and minimum statistical characteristic values ​​and record the number of load anomalies exceeding the load threshold range; Collect and calculate the real-time load standard deviation and load average at different times within p time; Calculate the load abnormality index based on the load standard deviation and load average value; The load abnormality index is combined with the load abnormality times to calculate the load abnormality coefficient.

[0029] The specific calculation formula of the load abnormality index is:

[0030] The specific calculation formula of the load abnormality coefficient is:

[0031] in, is the load abnormality indicator, is the real-time load at the i-th moment, n is the total number of moments collected within p time, is the load anomaly coefficient, t is the number of historical load anomalies, and W is the threshold used for normalization.

[0032] From the calculation expression of the load abnormality coefficient, it can be seen that when the performance value of the load abnormality coefficient is larger, the load fluctuation of the power system is larger, and the possibility of the occurrence of the backup automatic transfer malfunction is higher; conversely, when the performance value of the system load response coefficient is smaller, the load fluctuation of the power system is smaller, and the possibility of the occurrence of the backup automatic transfer malfunction is lower.

[0033] The load abnormality coefficient has the following effects on preventing the false alarm of the backup automatic start-up: Real-time monitoring of load fluctuations: The load anomaly coefficient can help the system monitor the load changes in the power system in real time and identify abnormal load fluctuations in a timely manner. This is crucial for determining whether the equipment is within the normal operating range.

[0034] Improve the accuracy of false operation identification: By analyzing the load abnormality coefficient, the system can more accurately identify potential false operation situations and reduce the false alarm rate. This makes the early warning system more accurate in determining whether the backup automatic start-up needs to be triggered.

[0035] Predicting system stability: The load abnormality coefficient can reflect the overall stability of the power system. A larger abnormality coefficient may indicate system instability. Early warning can help operators take measures to prevent false operations.

[0036] Optimize protection settings: According to the changes in the load anomaly coefficient, the system can dynamically adjust the protection settings to improve the adaptability of the protection and ensure safety and reliability under different load conditions.

[0037] Auxiliary decision support: The analysis results of the load abnormality coefficient can provide operators with important decision-making basis, helping them to quickly determine whether manual intervention or system adjustment is required when faced with abnormal situations.

[0038] Data-driven improvements: With the continuous monitoring and analysis of load anomaly coefficients, the system can accumulate data and gradually optimize algorithms and models, thereby improving long-term early warning effects and the intelligence level of the system.

[0039] The phase angle deviation coefficient is an indicator that describes the phase angle difference between different nodes in the power system. It can be obtained by measuring the voltage or current phase angle between different nodes and calculating the difference between them. The phase angle deviation coefficient reflects the electrical connection and power transmission between different nodes in the power system. When the phase angle deviation coefficient exceeds a certain range, it means that the power system may have power transmission imbalance or fault conditions, and timely measures need to be taken to adjust and handle them.

[0040] The specific method for obtaining the phase angle deviation coefficient is as follows: The phase meter is used to collect the phase angle data of each node in the power system in real time, and a low-pass filter is used to remove high-frequency noise and interference in the phase angle data to retain the effective signal; Based on the phasor analysis method, the voltage and current signals are converted into complex form and the phase angles of the voltage and current signals are calculated; Calculate the phase angle deviation of the voltage and current signals between different nodes to obtain the deviation value; The phase angle deviation coefficient is calculated by statistically analyzing the phase angle deviation values ​​in several time periods.

[0041] The specific calculation formula of the phase angle is:

[0042] The specific calculation formula of the deviation value is:

[0043] The specific calculation formula of the phase angle deviation coefficient is:

[0044] in, is the phase angle, and are the orthogonal components of the signal, is the deviation value, is the j+1th phase angle is the jth phase angle, is the phase angle deviation coefficient, is the number of phase angle time series.

[0045] The phase angle deviation coefficient has the following effects on preventing false alarm of standby automatic switching: Real-time monitoring of system status: By continuously monitoring the phase angle deviation coefficient, the operating status of the power system can be reflected in a timely manner. When the deviation exceeds the normal range, the system can quickly identify potential risks and avoid false operation of the backup automatic switch.

[0046] Providing early warning information: Abnormal changes in the phase angle deviation coefficient can serve as early warning signals to alert operators to possible faults or unstable factors, so that they can take measures to adjust and repair them in advance.

[0047] Improve system stability: Regular analysis of historical data and trends of phase angle deviation coefficients helps identify weak links in the system, optimize configuration and control strategies, and improve the overall stability of the system.

[0048] Support decision making: Provide data-based decision support to help operators evaluate equipment operating conditions and load changes, so as to arrange maintenance and operation strategies more reasonably.

[0049] Reduce the risk of false operation: Accurate phase angle deviation monitoring can significantly reduce the risk of false operation caused by phase angle abnormalities, especially during load fluctuations or system failures, ensuring the reliable operation of power equipment.

[0050] Promote the optimization of equipment protection settings: Analyzing the phase angle deviation coefficient can provide a basis for optimizing equipment protection settings, making the sensitivity and time characteristics of the protection device more in line with actual operating requirements and reducing the possibility of false operation.

[0051] Improve fault location capability: When a fault occurs, rapid evaluation of the phase angle deviation coefficient can help locate the source of the fault, shorten fault handling time, and reduce accident losses.

[0052] S2, builds a false operation warning model for standby automatic switching based on machine learning according to the operation status data and node phase angle data, and generates a false operation warning coefficient; The specific calculation formula of the standby automatic transfer malfunction warning model is as follows:

[0053] in, is the false alarm coefficient, is the voltage waveform factor, is the load abnormality coefficient, is the phase angle deviation coefficient, is the preset voltage waveform coefficient weight factor, is the preset load abnormality coefficient weight factor, is the preset phase angle deviation coefficient weight factor.

[0054] S3, comparing the generated malfunction warning coefficient with the preset malfunction warning threshold to determine whether there is a risk of malfunction of the backup automatic start-up; The generated malfunction warning coefficient is compared with the preset malfunction warning threshold to determine whether there is a risk of malfunction of the backup automatic start-up, specifically: If the generated false operation warning coefficient is greater than the preset false operation warning threshold, there is a risk of false operation of the backup automatic switch; If the generated malfunction warning coefficient is less than the preset malfunction warning threshold, then continue to obtain the malfunction warning coefficients of the power system in several time periods to form malfunction warning time series data and calculate the average value and standard deviation of the malfunction warning time series data; If the average value of the false alarm time series data is greater than the average reference threshold of the false alarm time series data, an alarm is issued and stability maintenance is performed; If the average value of the false alarm time series data is less than the average reference threshold value of the false alarm time series data, and the standard deviation of the false alarm time series data is greater than the preset standard deviation reference threshold value, continuous monitoring is performed; If the average value of the false operation warning time series data is less than the average reference threshold value of the false operation warning time series data, and the standard deviation of the false operation warning time series data is less than the preset standard deviation reference threshold value, there is no risk of false operation of the standby automatic start-up.

[0055] S4: When there is a risk of false operation of the standby automatic start-up, a re-judgment is made based on the factors that lead to the false operation of the standby automatic start-up and an early warning is issued.

[0056] When there is a risk of malfunction of the standby automatic start-up, a re-judgment is made based on the factors that cause the malfunction of the standby automatic start-up and an early warning is issued, specifically: The factors causing the malfunction of the standby automatic transfer include the opening of the current blocking and the reduction of the bus voltage; For the false operation of the backup automatic switch caused by the opening of the current blocking, the specific reasons are: A, real-time monitoring of the current of the two incoming lines of the substation; B. If the incoming line current is less than the no-current set value, the corresponding incoming line meets the warning action condition 1; C. Real-time monitoring of the switch positions of the two incoming lines. If they are in the closed position, the corresponding incoming line meets the second warning action condition; D. When any incoming line meets both the warning action condition 1 and the warning action condition 2, the delay is longer than the specified time Ts of the standby automatic action time, and the warning signal is output, otherwise it returns to step A; E. Through the interface of the centralized control system, the maintenance personnel, operation and maintenance personnel, and on-site supervisors are prompted with current blocking and opening by means of pop-up warnings in the substation background, push notifications from the security risk control platform, and SMS push notifications to prevent the misclassification of the busbar secondary voltage circuit breaker.

[0057] For the malfunction of the backup automatic switching caused by the reduction of bus voltage, the specific reasons are: A. Real-time monitoring of the current of the two incoming lines of the substation; B. If the incoming line current is less than the no-current setting value, the corresponding incoming line meets the warning action condition 1; C. Real-time monitoring of the switch positions of the two incoming lines. If they are in the closed position, the corresponding incoming line meets the second early warning action condition; D. When any incoming line meets both the warning action condition 1 and the warning action condition 2, the warning signal is output after the specified time Ts of the standby automatic action time is delayed, otherwise it returns to step A; E. Through the interface of the centralized control system, the maintenance personnel, operation and maintenance personnel, and on-site supervisors are prompted with current blocking and opening by means of pop-up warnings in the substation background, push notifications from the security risk control platform, and SMS push notifications to prevent the misclassification of the busbar secondary voltage circuit breaker.

[0058] Embodiment 2, a method for preventing false operation of standby automatic start-up based on a centralized control system, is characterized in that it comprises the following modules: a data acquisition module, a standby automatic start-up false operation warning model construction module, a standby automatic start-up false operation judgment module and a re-judgment module.

[0059] Data acquisition module: used to obtain the operating status data and node phase angle data of the power system in real time; The module for constructing the standby automatic start-up malfunction warning model is used to construct the standby automatic start-up malfunction warning model based on machine learning according to the operation status data and node phase angle data, and generate the malfunction warning coefficient; The standby automatic start-up misoperation judgment module is used to compare the generated misoperation warning coefficient with the preset misoperation warning threshold to determine whether there is a risk of standby automatic start-up misoperation; Re-judgment module: It is used to re-judgment and issue an early warning based on the factors that cause the false operation of the standby automatic start-up when there is a risk of false operation of the standby automatic start-up.

[0060] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0061] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0062] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0063] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0064] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0065] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for preventing false operation of standby automatic switching based on a centralized control system, characterized in that: The following steps are involved: Obtain the operating status data and node phase angle data of the power system in real time; According to the operation status data and node phase angle data, a standby automatic start-up malfunction warning model is built based on machine learning to generate a malfunction warning coefficient; Compare the generated malfunction warning coefficient with the preset malfunction warning threshold to determine whether there is a risk of malfunction of the backup automatic start-up; When there is a risk of false operation of the backup automatic start-up, a re-judgment is made based on the factors that cause the false operation of the backup automatic start-up and an early warning is issued.

2. The early warning method for preventing false operation of standby automatic switching based on the centralized control system according to claim 1 is characterized in that: The operating status data includes a voltage waveform coefficient and a load abnormality coefficient, and the node phase angle data includes a phase angle deviation coefficient; The specific method for obtaining the voltage waveform coefficient is as follows: Collect voltage waveform data of the power system in real time and display the collected voltage waveform data in the time domain; Obtain the voltage time domain waveform, and filter out the part with the lowest fundamental frequency in the voltage time domain waveform; Perform harmonic analysis on the filtered voltage time domain waveform, and obtain the voltage harmonic amplitude and voltage harmonic period through Fourier transform; Combining the voltage harmonic amplitude, voltage harmonic period and harmonic frequency, the effective value of harmonics is calculated; The voltage waveform coefficient is calculated by combining the voltage fundamental frequency, voltage harmonic phase and harmonic effective value.

3. The early warning method for preventing false operation of standby automatic switching based on the centralized control system according to claim 2 is characterized in that: The specific method for obtaining the load abnormality coefficient is as follows: Obtain historical load data of power equipment; According to the historical load data, calculate the average value, standard deviation, maximum value and minimum value of the load statistical characteristic values; Set the load threshold range according to the load average, standard deviation, maximum and minimum statistical characteristic values ​​and record the number of load anomalies exceeding the load threshold range; Collect and calculate the real-time load standard deviation and load average at different times within p time; Calculate the load abnormality index based on the load standard deviation and load average value; The load abnormality index is combined with the load abnormality times to calculate the load abnormality coefficient.

4. The early warning method for preventing false operation of standby automatic switching based on the centralized control system according to claim 3 is characterized in that: The specific method for obtaining the phase angle deviation coefficient is as follows: The phase meter is used to collect the phase angle data of each node in the power system in real time, and a low-pass filter is used to remove high-frequency noise and interference in the phase angle data to retain the effective signal; Based on the phasor analysis method, the voltage and current signals are converted into complex form and the phase angles of the voltage and current signals are calculated; Calculate the phase angle deviation of the voltage and current signals between different nodes to obtain the deviation value; The phase angle deviation coefficient is calculated by statistically analyzing the phase angle deviation values ​​in several time periods.

5. The early warning method for preventing false operation of standby automatic switching based on the centralized control system according to claim 4 is characterized in that: The generated malfunction warning coefficient is compared with the preset malfunction warning threshold to determine whether there is a risk of malfunction of the backup automatic start-up, specifically: If the generated false operation warning coefficient is greater than the preset false operation warning threshold, there is a risk of false operation of the backup automatic switch; If the generated malfunction warning coefficient is less than the preset malfunction warning threshold, then continue to obtain the malfunction warning coefficients of the power system in several time periods to form malfunction warning time series data and calculate the average value and standard deviation of the malfunction warning time series data; If the average value of the false alarm time series data is greater than the average reference threshold of the false alarm time series data, an alarm is issued and stability maintenance is performed; If the average value of the false alarm time series data is less than the average reference threshold value of the false alarm time series data, and the standard deviation of the false alarm time series data is greater than the preset standard deviation reference threshold value, continuous monitoring is performed; If the average value of the false operation warning time series data is less than the average reference threshold value of the false operation warning time series data, and the standard deviation of the false operation warning time series data is less than the preset standard deviation reference threshold value, there is no risk of false operation of the standby automatic start-up.

6. The early warning method for preventing false operation of standby automatic switching based on the centralized control system according to claim 5 is characterized in that: When there is a risk of malfunction of the standby automatic start-up, a re-judgment is made based on the factors that cause the malfunction of the standby automatic start-up and an early warning is issued, specifically: The factors causing the faulty operation of the backup automatic transfer include the opening of the current blocking causing the faulty operation of the backup automatic transfer and the reduction of the bus voltage causing the faulty operation of the backup automatic transfer; The current blocking is opened, which causes the standby automatic switching to malfunction, specifically: (a) Real-time monitoring of the current of the two incoming lines of the substation; (b) If the incoming line current is less than the no-current setting value, the corresponding incoming line meets the warning action condition 1; (c) Real-time monitoring of the switch positions of the two incoming lines. If they are in the closed position, the corresponding incoming line meets the second early warning action condition; (d) When any incoming line meets both the warning action condition 1 and the warning action condition 2, the delay is longer than the specified time Ts of the standby automatic action time, and the warning signal is output, otherwise, it returns to step (a); (e) Through the interface of the centralized control system, the maintenance personnel, operation and maintenance personnel, and on-site supervisors are informed of the current blocking and opening by means of pop-up warnings in the substation background, push notifications from the security risk control platform, and SMS push notifications to prevent the busbar secondary voltage from being mistakenly disconnected.

7. The early warning method for preventing false operation of standby automatic switching based on the centralized control system according to claim 6 is characterized in that: The bus voltage reduction causes the backup automatic switching to malfunction, specifically: (1) Real-time monitoring of the current of the two incoming lines of the substation; (2) If the incoming line current is less than the no-current set value, the corresponding incoming line meets the warning action condition 1; (3) Monitor the switch positions of the two incoming lines in real time. If they are in the closed position, the corresponding incoming line meets the second warning action condition; (4) When any incoming line meets both the warning action condition 1 and the warning action condition 2, the warning signal is output after the specified time Ts of the standby automatic switching action time is delayed, otherwise it returns to step (1); (5) Through the interface of the centralized control system, the maintenance personnel, operation and maintenance personnel, and on-site supervisors are informed of the opening of current blocking to prevent the misclassification of the busbar secondary voltage circuit breaker by means of pop-up warnings in the substation background, push notifications from the security risk control platform, and SMS push notifications.

8. The early warning method for preventing false operation of standby automatic switching based on the centralized control system according to claim 7 is characterized in that: The calculation formula of the effective value of harmonics is: The specific calculation formula of the voltage waveform coefficient is as follows: in, is the voltage harmonic period, is the harmonic frequency, is the voltage harmonic amplitude, is the voltage harmonic frequency, is the voltage harmonic phase, F is the effective value of the harmonic, is the voltage waveform factor.

9. The early warning method for preventing false operation of standby automatic switching based on the centralized control system according to claim 8 is characterized in that: The specific calculation formula of the standby automatic transfer malfunction warning model is as follows: in, is the false alarm coefficient, is the voltage waveform factor, is the load abnormality coefficient, is the phase angle deviation coefficient, is the preset voltage waveform coefficient weight factor, is the preset load abnormality coefficient weight factor, is the preset phase angle deviation coefficient weight factor.

10. A warning system for preventing erroneous operation of automatic switching of a standby device based on a centralized control system, used to implement a warning method for preventing erroneous operation of automatic switching of a standby device based on a centralized control system as claimed in any one of claims 1 to 9, characterized in that: The invention comprises the following modules: a data acquisition module, a standby automatic start-up false operation warning model construction module, a standby automatic start-up false operation judgment module and a re-judgment module. Data acquisition module: used to obtain the operating status data and node phase angle data of the power system in real time; The module for constructing the standby automatic start-up malfunction warning model is used to construct the standby automatic start-up malfunction warning model based on machine learning according to the operation status data and node phase angle data, and generate the malfunction warning coefficient; The standby automatic start-up misoperation judgment module is used to compare the generated misoperation warning coefficient with the preset misoperation warning threshold to determine whether there is a risk of standby automatic start-up misoperation; Re-judgment module: when there is a risk of false operation of the standby automatic start-up, it is used to re-judgment and issue an early warning based on the factors that cause the false operation of the standby automatic start-up.

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