System inertia calculation method and system based on fault moment sliding window

Abstract

The present invention relates to the technical field of safe and stable control of electric power systems, and provides a method and system for calculating system inertia based on a sliding window at the time of a fault, wherein the method comprises: obtaining the frequency of each monitoring bus of the system, the active data of the tie line and the active output of the unit, and counting the system capacity; filtering the frequency of each monitoring bus, filtering the bus voltage and the active output of the unit; calculating the frequency change rate of each node of the system, and determining the fault time based on the magnitude of the frequency change rate; calculating the voltage fluctuation index of each bus, and determining the system oscillation center; calculating the frequency change rate of each window; calculating the system inertia change curve based on the frequency change rate of each window, the active data of the tie line, the active output of the unit and the system capacity; and obtaining the system inertia according to the system inertia change curve. The present invention identifies the system inertia based on the PMU measured disturbance, and can overcome the problem of inaccurate inertia evaluation caused by traditional SCADA-based grid-connected monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of power system safety and stability control, and in particular to a method and system for calculating system inertia based on a sliding window at the time of a fault. Background Art

[0002] The future development of the power system, such as relatively large generators, virtual power plants, and distributed renewable energy grid connection, will lead to significant changes in system inertia. At present, with the help of data acquisition and monitoring systems, the system inertia is calculated by counting the rotational inertia of all grid-connected synchronous units, and the system inertia is considered to be a constant. Since the monitoring range cannot cover non-coordinated units, loads, and other possible forms of inertia in the future, the inertia value is underestimated and the accuracy is not high. During system operation, if the system inertia is significantly lower than expected in the planning stage, the existing deterministic protection and control may not ensure the stability of the system.

[0003] In recent years, many scholars and research institutions at home and abroad have carried out research on online inertia evaluation and frequency characteristic analysis, and some of the results have been applied to actual power grids, which can be summarized into the following three directions:

[0004] (1) With the help of Supervisory Control And Data Acquisition (SCADA), the system inertia is calculated by counting the rotational inertia of all grid-connected synchronous units, and the system inertia is considered to be a constant. At present, traditional schemes usually use this method to monitor the system inertia level online. Since the monitoring range cannot cover non-coordinated units, loads, and other possible forms of inertia in the future, the inertia value is underestimated and the accuracy is not high;

[0005] (2) With the help of a wide-area measurement system, the system and regional inertia assessment is performed based on the power, frequency and other measurement data measured after a large disturbance and the system swing equation. This method can be applied to offline analysis after an accident or to online analysis. The challenge for online analysis is to obtain the precise time of the disturbance, the amount of disturbance and the rate of change of the system frequency, as well as to filter the data.

[0006] (3) Online evaluation of system inertia based on small disturbance events such as load changes, unit output adjustments, or random power fluctuations. This inertia calculation method relies on power system frequency transients caused by power outages. Such power generation loss events are relatively rare, and although they often cause large frequency disturbances, they require post-incident studies to determine the cause, location, tripping type, etc., so that the inertia and system response can be characterized. The scarcity of these events, especially repeated similar events, makes the verification of these methods difficult. This type of method is still in the exploratory stage and is not yet ready for engineering practice. Summary of the invention

[0007] The purpose of the present invention is to solve at least one technical problem in the background technology and to provide a method and system for calculating system inertia based on a sliding window at the time of a fault.

[0008] To achieve the above object, the present invention provides a method for calculating system inertia based on a sliding window at the time of a fault, comprising:

[0009] When a power disturbance occurs in the power system and causes a fault, the PMU device obtains the system's monitoring bus frequency, tie line active data and unit active output, and calculates the system capacity;

[0010] The empirical mode decomposition method is used to filter the monitored bus frequencies after the system disturbance, and the bus voltage and unit active output are filtered through sliding window mean filtering;

[0011] Based on the filtered frequency data of each monitoring bus of the system, a fixed sliding window is used to calculate the frequency change rate of each node in the system, and the fault time is determined based on the magnitude of the frequency change rate;

[0012] Based on the filtered bus voltage, the voltage fluctuation index of each bus is calculated to determine the system oscillation center;

[0013] Based on the frequency curve of the oscillation center, the determined fault moment is used as the calculation start moment, the sliding window size is continuously increased, and the frequency change rate of each window is calculated;

[0014] The system inertia change curve is calculated based on the frequency change rate of each window, the active data of the tie line, the active output of the unit and the system capacity;

[0015] The system inertia is obtained according to the system inertia change curve.

[0016] According to one aspect of the present invention, the determination of the fault moment based on the frequency change rate is: taking the moment corresponding to the maximum change of the frequency change rate as the fault moment.

[0017] According to one aspect of the present invention, the calculation formula of the voltage fluctuation index of the bus is:

[0018] ;

[0019] Where V i (t) is [t i - , t i + ]The real-time voltage value of the i-th bus in ; is the moment of the i-th bus voltage extreme value; is the busbar voltage before fault; is the set time threshold value, which is usually 0.1s in actual systems;

[0020] The system oscillation center is the bus with the largest voltage fluctuation index.

[0021] According to one aspect of the present invention, the determined fault moment is used as the calculation start moment, the sliding window size is continuously increased, and the frequency change rate of each window is calculated as follows:

[0022] The determined fault time is used as the calculation start time, the sliding window size is continuously increased, the frequency change rate of each window is calculated, and the calculation ends after 3 seconds;

[0023] The variation range of the window width of the sliding window is the sampling interval of the PMU device, and the sampling interval is 0.02 seconds.

[0024] According to one aspect of the present invention, the calculation formula of the system inertia is:

[0025] ;

[0026] In the formula, is the system inertia; is the window frequency change rate; f coi is the center frequency of inertia; f ( t )for t The real-time frequency corresponding to the moment; f 0 is the fault moment frequency; is the disturbance power, which is calculated from the active power data of the tie line and the active power output of the unit; is the system capacity;

[0027] According to one aspect of the present invention, the system inertia obtained according to the system inertia change curve is:

[0028] The minimum value of the system inertia change curve is selected as the system inertia.

[0029] To achieve the above object, the present invention further provides a system inertia calculation system based on a sliding window at the time of a fault, characterized in that it includes:

[0030] The data acquisition module acquires the frequency of each monitoring bus, the active data of the tie line and the active output of the unit from the PMU device when a power disturbance occurs in the power system and causes a fault, and calculates the system capacity;

[0031] The data preprocessing module uses the empirical mode decomposition method to filter the frequencies of each monitored bus after the system disturbance, and uses the sliding window mean filter to filter the bus voltage and the active output of the unit;

[0032] The fault moment identification module uses a fixed sliding window to calculate the frequency change rate of each node in the system based on the filtered frequency data of each monitoring bus in the system, and determines the fault moment based on the frequency change rate;

[0033] The oscillation center determination module calculates the voltage fluctuation index of each bus based on the filtered bus voltage and determines the system oscillation center;

[0034] The window frequency change rate calculation module is based on the frequency curve of the oscillation center, takes the determined fault moment as the calculation start moment, continuously increases the sliding window size, and calculates the frequency change rate of each window;

[0035] The system inertia change curve calculation module calculates the system inertia change curve based on the frequency change rate of each window, the active data of the tie line, the active output of the unit and the system capacity;

[0036] The system inertia confirmation module obtains the system inertia according to the system inertia change curve.

[0037] To achieve the above-mentioned purpose, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the system inertia calculation method based on the sliding window at the moment of fault as described above is implemented.

[0038] To achieve the above object, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the system inertia calculation method based on the sliding window at the moment of failure as described above is implemented.

[0039] According to the scheme of the present invention, the present invention performs system inertia identification based on PMU measured disturbance, which can overcome the problem of inaccurate inertia evaluation caused by the currently mainly adopted SCADA grid-connected monitoring. After the disturbance occurs, the scheme uses the system capacity before the disturbance, the disturbance power, frequency, bus voltage and other data during the disturbance, through filtering, and performs inertia evaluation on the oscillation center frequency curve based on the rotor motion equation, thereby realizing online monitoring and identification of the system frequency characteristics, and ensuring the safety and stability of the power system frequency. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A flowchart schematically showing a method for calculating system inertia based on a sliding window at the time of a fault according to an embodiment of the present invention;

[0041] Figure 2 Bus frequency curve diagram for power system vibration;

[0042] Figure 3It is the curve diagram of system inertia change;

[0043] Figure 4 This is the frequency response curve of the system. DETAILED DESCRIPTION

[0044] The present invention will now be discussed with reference to exemplary embodiments. It should be understood that the embodiments discussed are only to enable those skilled in the art to better understand and thus implement the present invention, rather than implying any limitation on the scope of the present invention.

[0045] As used herein, the term “including” and variations thereof are to be interpreted as open-ended terms meaning “including, but not limited to.” The term “based on” is to be interpreted as “based, at least in part, on.” The terms “one embodiment” and “an embodiment” are to be interpreted as “at least one embodiment.”

[0046] Figure 1 The flowchart schematically shows a method for calculating system inertia based on a sliding window at the time of a fault according to an embodiment of the present invention. Figure 1 As shown, in this embodiment, the system inertia calculation method based on the sliding window at the time of fault includes:

[0047] When a power disturbance occurs in the power system and causes a fault, the PMU device obtains the system's monitoring bus frequency, tie line active data and unit active output, and calculates the system capacity;

[0048] The empirical mode decomposition method is used to filter the monitored bus frequencies after the system disturbance, and the bus voltage and unit active output are filtered through sliding window mean filtering;

[0049] Based on the filtered frequency data of each monitoring bus of the system, a fixed sliding window is used to calculate the frequency change rate of each node in the system, and the fault time is determined based on the magnitude of the frequency change rate;

[0050] Based on the filtered bus voltage, the voltage fluctuation index of each bus is calculated to determine the system oscillation center;

[0051] Based on the frequency curve of the oscillation center, the determined fault moment is used as the calculation start moment, the sliding window size is continuously increased, and the frequency change rate of each window is calculated;

[0052] The system inertia change curve is calculated based on the frequency change rate of each window, the active data of the tie line, the active output of the unit and the system capacity;

[0053] The system inertia is obtained according to the system inertia change curve.

[0054] Further, according to an embodiment of the present invention, the fault moment is determined based on the magnitude of the frequency change rate: the moment corresponding to the maximum change of the frequency change rate is taken as the fault moment.

[0055] Further, according to an embodiment of the present invention, the calculation formula of the voltage fluctuation index of the bus is:

[0056] ;

[0057] Where V i (t) is [t i - , t i + ]The real-time voltage value of the i-th bus in ; is the moment of the i-th bus voltage extreme value; is the busbar voltage before fault; is the set time threshold value, which is usually 0.1s in actual systems;

[0058] The system oscillation center is the bus with the largest voltage fluctuation index.

[0059] Further, according to an implementation manner of the present invention, the determined fault moment is used as the calculation start moment, the sliding window size is continuously increased, and the frequency change rate of each window is calculated as:

[0060] The determined fault time is used as the calculation start time, the sliding window size is continuously increased, the frequency change rate of each window is calculated, and the calculation ends after 3 seconds;

[0061] The variation range of the window width of the sliding window is the sampling interval of the PMU device, and the sampling interval is 0.02 seconds.

[0062] Further, according to an embodiment of the present invention, the calculation formula of the system inertia is:

[0063] ;

[0064] In the formula, is the system inertia; is the window frequency change rate; f coi is the center frequency of inertia; f ( t )for t The real-time frequency corresponding to the moment; f 0 is the fault moment frequency; is the disturbance power, which is calculated from the active power data of the tie line and the active power output of the unit; is the system capacity;

[0065] Further, according to an embodiment of the present invention, the system inertia is obtained according to the system inertia change curve as follows:

[0066] The minimum value of the system inertia change curve is selected as the system inertia.

[0067] According to the above scheme of the present invention, the present invention performs system inertia identification based on PMU measured disturbance, which can overcome the problem of inaccurate inertia evaluation caused by the currently mainly adopted SCADA grid-connected monitoring. After the disturbance occurs, the scheme uses the system capacity before the disturbance, the disturbance power, frequency, bus voltage and other data during the disturbance, through filtering, and performs inertia evaluation on the oscillation center frequency curve based on the rotor motion equation, thereby realizing online monitoring and identification of the system frequency characteristics, and ensuring the safety and stability of the power system frequency.

[0068] Furthermore, the present invention also provides a system inertia calculation system based on a sliding window at the time of a fault, comprising:

[0069] The data acquisition module acquires the frequency of each monitoring bus, the active data of the tie line and the active output of the unit from the PMU device when a power disturbance occurs in the power system and causes a fault, and calculates the system capacity;

[0070] The data preprocessing module uses the empirical mode decomposition method to filter the frequencies of each monitored bus after the system disturbance, and uses the sliding window mean filter to filter the bus voltage and the active output of the unit;

[0071] The fault moment identification module uses a fixed sliding window to calculate the frequency change rate of each node in the system based on the filtered frequency data of each monitoring bus in the system, and determines the fault moment based on the frequency change rate;

[0072] The oscillation center determination module calculates the voltage fluctuation index of each bus based on the filtered bus voltage and determines the system oscillation center;

[0073] The window frequency change rate calculation module is based on the frequency curve of the oscillation center, takes the determined fault moment as the calculation start moment, continuously increases the sliding window size, and calculates the frequency change rate of each window;

[0074] The system inertia change curve calculation module calculates the system inertia change curve based on the frequency change rate of each window, the active data of the tie line, the active output of the unit and the system capacity;

[0075] The system inertia confirmation module obtains the system inertia according to the system inertia change curve.

[0076] Further, according to an embodiment of the present invention, the fault moment is determined based on the magnitude of the frequency change rate: the moment corresponding to the maximum change of the frequency change rate is taken as the fault moment.

[0077] Further, according to an embodiment of the present invention, the calculation formula of the voltage fluctuation index of the bus is:

[0078] ;

[0079] Where V i (t) is [t i - , t i + ]The real-time voltage value of the i-th bus in ; is the moment of the i-th bus voltage extreme value; is the busbar voltage before fault; is the set time threshold value, which is usually 0.1s in actual systems;

[0080] The system oscillation center is the bus with the largest voltage fluctuation index.

[0081] Further, according to an implementation manner of the present invention, the determined fault moment is used as the calculation start moment, the sliding window size is continuously increased, and the frequency change rate of each window is calculated as:

[0082] The determined fault time is used as the calculation start time, the sliding window size is continuously increased, the frequency change rate of each window is calculated, and the calculation ends after 3 seconds;

[0083] The variation range of the window width of the sliding window is the sampling interval of the PMU device, and the sampling interval is 0.02 seconds.

[0084] Further, according to an embodiment of the present invention, the calculation formula of the system inertia is:

[0085] ;

[0086] In the formula, is the system inertia; is the window frequency change rate; f coi is the center frequency of inertia; f ( t )for t The real-time frequency corresponding to the moment; f 0 is the fault moment frequency; is the disturbance power, which is calculated from the active power data of the tie line and the active power output of the unit; is the system capacity;

[0087] Further, according to an embodiment of the present invention, the system inertia is obtained according to the system inertia change curve as follows:

[0088] The minimum value of the system inertia change curve is selected as the system inertia.

[0089] According to the above scheme of the present invention, the present invention performs system inertia identification based on PMU measured disturbance, which can overcome the problem of inaccurate inertia evaluation caused by the currently mainly adopted SCADA grid-connected monitoring. After the disturbance occurs, the scheme uses the system capacity before the disturbance, the disturbance power, frequency, bus voltage and other data during the disturbance, through filtering, and performs inertia evaluation on the oscillation center frequency curve based on the rotor motion equation, thereby realizing online monitoring and identification of the system frequency characteristics, and ensuring the safety and stability of the power system frequency.

[0090] Furthermore, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the system inertia calculation method based on the sliding window at the time of fault as described above is implemented.

[0091] Furthermore, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the system inertia calculation method based on the sliding window at the moment of failure as described above is implemented.

[0092] Based on the above solution of the present invention, the solution of the present invention is described in detail in the following in conjunction with the accompanying drawings in the form of a specific embodiment.

[0093] Example 1

[0094] Taking the tripping event of a unit in a power grid as an example, the disturbance instance in the power grid is analyzed, and the system inertia calculation method based on the sliding window at the time of the fault includes:

[0095] Step 1: Acquisition of measured data: The active output of the unit before the fault was 400MW, the benchmark capacity was 72775MVA, and the system inertia obtained based on the SCADA grid-connected synchronous machine evaluation was 4.34s;

[0096] Step 2: Data preprocessing: Use the empirical mode decomposition method to filter the frequency of each monitored bus after the system disturbance in step 1, and use the sliding window mean filter to filter the bus voltage and unit active output;

[0097] Step 3: Fault time identification: Based on the frequency data of each bus in the system, a fixed sliding window is used to calculate the frequency change rate of each node in the system, and the fault time is determined based on the magnitude of the frequency change rate. The fault time is t0=2.0s.

[0098] Step 4: Identify the oscillation center: Calculate the voltage fluctuation index of each busbar and determine the system oscillation center. The frequency curve of the system oscillation is as follows: Figure 2 shown.

[0099] Step 5: Sliding window inertia evaluation based on fault time: Based on the oscillation center frequency curve obtained in step 4, take the fault time t0=2.0s determined in step 3 as the calculation start time, continuously increase the sliding window size, calculate the frequency change rate of each window, and obtain the system inertia change curve, such as Figure 3 shown.

[0100] The specific calculation formula is: .

[0101] In the formula, f coi is the center frequency of inertia; f ( t )for t The real-time frequency corresponding to the moment; f 0 is the fault moment frequency; is the disturbance power, Obtained through calculation of the tie line active data and the unit active output in step 1; is the system inertia; is the system capacity; is the window frequency change rate;

[0102] Step 6: System inertia characterization: Select the minimum value of the system inertia change curve in step 5 as the system inertia, such as Figure 3 As shown, H (system inertia) = 5.11s.

[0103] Based on the system equivalent swing equation, the frequency characteristics of the system after power disturbance are analyzed using different inertia time constants and compared with the measured data. =400MW is used as a constant, and the frequency response curve of the system is calculated when H=4.34s (i.e., the system inertia measured based on the SCADA grid-connected synchronous machine) and H=5.11s (the system inertia obtained based on the calculation method of the present invention), and compared with the measured PMU frequency curve of the station. The results are as follows: Figure 4 As shown, the frequency response curve of the system calculated by the system inertia obtained by the calculation method based on the present invention is basically consistent with the measured inertia center frequency curve (measured PMU frequency curve). However, the frequency response curve of the system calculated by the system inertia obtained by the SCADA grid-connected synchronous machine evaluation is quite different from the measured inertia center frequency curve (measured PMU frequency curve). It can be seen that the system inertia obtained by the calculation method of the present invention is more accurate and precise.

[0104] Those skilled in the art will appreciate that the modules and algorithm steps 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 the present invention.

[0105] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the aforementioned method implementation methods, and will not be repeated here.

[0106] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0107] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0108] In addition, each functional module in the embodiment of the present invention 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.

[0109] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the energy-saving signal sending / receiving method of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical disks.

[0110] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other.

[0111] It should be understood that the size of the serial numbers of each step in the content of the invention and the implementation methods of the present invention does not absolutely mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the implementation methods of the present invention.

Claims

1. A method for calculating system inertia based on a sliding window at the time of a fault, characterized in that: include: When a power disturbance occurs in the power system and causes a fault, the PMU device obtains the system's monitoring bus frequency, tie line active data and unit active output, and calculates the system capacity; The empirical mode decomposition method is used to filter the monitored bus frequencies after the system disturbance, and the bus voltage and unit active output are filtered through sliding window mean filtering; Based on the filtered frequency data of each monitoring bus of the system, a fixed sliding window is used to calculate the frequency change rate of each node in the system, and the fault time is determined based on the magnitude of the frequency change rate; Based on the filtered bus voltage, the voltage fluctuation index of each bus is calculated to determine the system oscillation center; Based on the frequency curve of the oscillation center, the determined fault moment is used as the calculation start moment, the sliding window size is continuously increased, and the frequency change rate of each window is calculated; The system inertia change curve is calculated based on the frequency change rate of each window, the active data of the tie line, the active output of the unit and the system capacity; The system inertia is obtained according to the system inertia change curve; The calculation formula of the voltage fluctuation index of the bus is: ； Where V i (t) is [t i - , t i + ]The real-time voltage value of the i-th bus in ; is the moment of the i-th bus voltage extreme value; is the busbar voltage before fault; is the set time threshold value, which is usually 0.1s in actual systems; The system oscillation center is the bus with the largest voltage fluctuation index; The calculation formula for the system inertia is: ； In the formula, is the system inertia; is the window frequency change rate; is the center frequency of inertia; for t The real-time frequency corresponding to the moment; is the fault moment frequency; is the disturbance power, which is calculated from the active data of the tie line and the active output of the unit; is the system capacity.

2. The method for calculating system inertia based on a sliding window at the time of a fault according to claim 1, characterized in that: The method of determining the fault time based on the frequency change rate is as follows: taking the time corresponding to the maximum change of the frequency change rate as the fault time.

3. The method for calculating system inertia based on a sliding window at the time of a fault according to claim 1, characterized in that: The determined fault moment is used as the calculation start moment, the sliding window size is continuously increased, and the frequency change rate of each window is calculated as follows: The determined fault time is used as the calculation start time, the sliding window size is continuously increased, the frequency change rate of each window is calculated, and the calculation ends after 3 seconds; The variation range of the window width of the sliding window is the sampling interval of the PMU device, and the sampling interval is 0.02 seconds.

4. The method for calculating system inertia based on a sliding window at the time of a fault according to any one of claims 1 to 3, characterized in that: The system inertia obtained according to the system inertia change curve is: The minimum value of the system inertia change curve is selected as the system inertia.

5. System inertia calculation system based on sliding window at fault time, characterized in that: include: The data acquisition module acquires the frequency of each monitoring bus, the active data of the tie line and the active output of the unit from the PMU device when a power disturbance occurs in the power system and causes a fault, and calculates the system capacity; The data preprocessing module uses the empirical mode decomposition method to filter the frequencies of each monitored bus after the system disturbance, and uses the sliding window mean filter to filter the bus voltage and the active output of the unit; The fault moment identification module uses a fixed sliding window to calculate the frequency change rate of each node in the system based on the filtered frequency data of each monitoring bus in the system, and determines the fault moment based on the frequency change rate; The oscillation center determination module calculates the voltage fluctuation index of each bus based on the filtered bus voltage and determines the system oscillation center; The window frequency change rate calculation module is based on the frequency curve of the oscillation center, takes the determined fault moment as the calculation start moment, continuously increases the sliding window size, and calculates the frequency change rate of each window; The system inertia change curve calculation module calculates the system inertia change curve based on the frequency change rate of each window, the active data of the tie line, the active output of the unit and the system capacity; System inertia confirmation module, which obtains the system inertia according to the system inertia change curve; The calculation formula of the voltage fluctuation index of the bus is: ； Where V i (t) is [t i - , t i + ]The real-time voltage value of the i-th bus in ; is the moment of the i-th bus voltage extreme value; is the busbar voltage before fault; is the set time threshold value, which is usually 0.1s in actual systems; The system oscillation center is the bus with the largest voltage fluctuation index; The calculation formula for the system inertia is: ； In the formula, is the system inertia; is the window frequency change rate; is the center frequency of inertia; for t The real-time frequency corresponding to the moment; is the fault moment frequency; is the disturbance power, which is calculated from the active data of the tie line and the active output of the unit; is the system capacity.

6. An electronic device, characterized in that The invention comprises a processor, a memory and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the method for calculating the system inertia based on a sliding window at the time of a fault as described in any one of claims 1 to 4 is implemented.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for calculating system inertia based on a sliding window at the time of a fault according to any one of claims 1 to 4 is implemented.

Images