Substation DC power supply state monitoring method

Abstract

The invention discloses a substation direct-current power supply state monitoring method. The method comprises the following steps: calculating a weight coefficient of performance influence in pure discharge and simultaneous charge and discharge states based on test data; defining a state monitoring period, calculating fluctuation coefficients of the output voltage and the output current, calculating fluctuation coefficients in a pure discharge state and a charge-discharge state based on the weight coefficient, and evaluating charge and discharge function faults of the direct-current power supply; obtaining use duration data of the DC power supply and corresponding internal resistance extreme value data; and constructing a linear regression equation for predicting the change of the internal resistance of the direct-current power supply along with the use duration, and predicting the residual use duration before the internal resistance fault of the direct-current power supply occurs. Potential faults are predicted in advance, sufficient time is provided for operation and maintenance personnel to carry out equipment maintenance and replacement, power grid accidents caused by sudden faults are avoided, and the reliability and stability of a direct-current power supply system of the transformer substation are improved.

Description

Technical Field

[0001] This invention relates to the field of power safety, specifically to a method for monitoring the status of DC power supplies in substations. Background Technology

[0002] The DC power supply system of a substation is a critical component for the safe and stable operation of the substation, providing reliable DC power to protection devices, monitoring and control equipment, and communication systems. A failure in the DC power supply system can lead to malfunctions or failures to operate protection devices, potentially triggering power grid accidents and causing significant economic losses. Traditional DC power supply condition monitoring methods have several shortcomings, such as limited monitoring parameters, inability to accurately assess the power supply health status in real time, and difficulty in predicting potential faults. With the continuous expansion of power system scale and the improvement of intelligence levels, there is an urgent need to develop a new method for monitoring the condition of substation DC power supplies. Summary of the Invention

[0003] To address the aforementioned shortcomings of existing technologies, this invention provides a method for monitoring the status of DC power supply in substations. This method can dynamically assess faults in the charging, discharging, and pure discharging states of the DC power supply in real time and predict the duration of future faults.

[0004] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows: A method for monitoring the status of DC power supply in a substation is provided, comprising the following steps: S1: Based on the test data of the DC power supply used in the substation during factory testing, calculate the weighting coefficient of the DC power supply's performance impact under pure discharge and simultaneous charge and discharge conditions. S2: Define the status monitoring cycle of the DC power supply during its use in the substation, collect the maximum values ​​of the DC power supply's output voltage data, output current data, and heating temperature data within the status monitoring cycle, calculate the fluctuation coefficients of the output voltage and output current, and calculate the fluctuation coefficients under pure discharge and simultaneous charging and discharging states based on the weighting coefficients, and evaluate the charging and discharging function faults of the DC power supply. S3: Based on the moment when the heating temperature reaches its maximum value within the condition monitoring cycle, calculate the usage time of the DC power supply and the extreme value of the internal resistance during the condition monitoring cycle to obtain the usage time data of the DC power supply and the corresponding extreme value data of the internal resistance. S4: Construct a linear regression equation to predict the change in internal resistance of the DC power supply with usage time. Based on usage time data and corresponding extreme internal resistance data, fit the linear regression equation using the least squares method, output the fitted linear regression equation, and predict the remaining usage time of the DC power supply before an internal resistance fault occurs. Further, step S1 includes: S11: Obtain the test data of the DC power supply used in the substation during the factory test. The test data includes the test data under pure discharge state and the test data under simultaneous charge and discharge state. Test data under pure discharge conditions includes output voltage data. and output current data , M This refers to the number of times voltage and current data are collected within the test cycle. The first one under pure discharge state M Output current data and output voltage data; Meanwhile, the test data under charge and discharge conditions includes output voltage data. and output current data , They are the first under simultaneous charging and discharging states. M Output current data and output voltage data; S12: Calculate the coefficient of variation of the output voltage under pure discharge conditions. and the coefficient of variation of output voltage under simultaneous charging and discharging conditions ; ; ; in, m The numbers are for the output voltage data and the output current data. The first under pure discharge state m Output voltage data, This represents the average value of the output voltage data under pure discharge conditions. For the first state of simultaneous charging and discharging m Output voltage data, This represents the average value of the output voltage data under simultaneous charging and discharging conditions. S13: Calculate the weighting coefficients for the impact of pure discharge and simultaneous charge and discharge states on the stability of the output voltage during the use of the DC power supply. ; in, This represents the weighting coefficient for the impact of pure discharge state on output voltage stability. This is a weighting coefficient representing the impact of simultaneous charging and discharging states on the stability of the output voltage. S14: Calculate the dispersion coefficient of the output current under pure discharge conditions. and the coefficient of variation of output current under simultaneous charging and discharging conditions ; ; ; in, The first under pure discharge state m Output current data, This represents the average value of the output current data under pure discharge conditions. For the first state of simultaneous charging and discharging m Output current data, This represents the average value of the output current data under simultaneous charging and discharging conditions. S15: Calculate the weighting coefficients for the impact of pure discharge and simultaneous charge and discharge states on the stability of the output current during the use of the DC power supply. ; in, This represents the weighting coefficient for the impact of pure discharge state on the stability of the output current. This is a weighting coefficient representing the impact of simultaneous charging and discharging states on the stability of the output current.

[0005] Further, step S2 includes: S21: Define the status monitoring cycle for DC power supply operation in substations. T Data collection status monitoring cycle T Output voltage data of internal DC power supply Output current data and the maximum value of the heating temperature data ; A Condition monitoring cycle T The number of times the output voltage and output current data are collected internally. These are the status monitoring cycles. T The first internal collection A Output voltage data and output current data; S22: Rated output voltage based on DC power supply Rated output current Calculate the output voltage fluctuation coefficient Output current fluctuation coefficient ; ; in, a Condition monitoring cycle T Numbering of internal output voltage data and output current data. These are the status monitoring cycles. T The first internal collection a Output voltage data and output current data; S23: Set the threshold for the output voltage fluctuation coefficient during DC power supply operation. Output current fluctuation coefficient threshold ; like or If the DC power supply fails, proceed to step S24; otherwise, return to step S21 and continue collecting output voltage data, output current data, and heating temperature data for the next state monitoring cycle. S24: According to the status monitoring cycle T The number of times the internal DC power supply is in pure discharge state and simultaneously in charge and discharge state. f , g And based on weighting coefficients , , , Calculate the fluctuation coefficient under pure discharge and simultaneous charge-discharge conditions. ; ; S25: Set the fluctuation coefficient threshold for the DC power supply under pure discharge and simultaneous charge / discharge conditions. ; like and If the DC power supply fails to discharge, it is determined that the discharge function is faulty and the charging function is normal. like and If the DC power supply's charging and discharging functions are normal, then it can be determined that the DC power supply's charging and discharging functions are normal. like and If the charging function of the DC power supply is faulty, the discharging function is normal. like and If so, it is determined that both the charging and discharging functions of the DC power supply are faulty.

[0006] Further, step S3 includes: S31: Extract during the status monitoring cycle T The internal heating temperature reaches its maximum value. The moment , u This refers to the number of status monitoring cycles experienced after the DC power supply has been put into use, based on the start time of the DC power supply's commissioning. Calculate the status monitoring cycle T The internal heating temperature reaches its maximum value. DC power supply usage time ; S32: Based on the condition monitoring cycle T Output voltage data of the internally acquired DC power supply Output current data Calculate the internal resistance of the DC battery corresponding to each set of voltage and current data. ; S33: Obtain the DC power supply status monitoring cycle T Internal resistance data at various times , For the first A Identify and filter internal resistance data. The maximum value in As a condition monitoring cycle T internal resistance extreme value ; S34: Obtain the DC power supply usage duration calculated for each historical state monitoring cycle during DC power supply usage. and the corresponding internal resistance extreme values Obtain DC power supply usage time data and internal resistance extreme value data .

[0007] Further, step S4 includes: S41: Constructing the predicted internal resistance of the DC power supply A linear regression equation that varies with usage duration; ; in, This refers to the duration of DC power supply use. These are the rate of change of internal resistance and the constant term, respectively. j This is the number for the condition monitoring cycle; S42: Fit the linear regression equation using the least squares method. The objective function of the least squares method is: ; in, For the first j The extreme values ​​of internal resistance corresponding to each state monitoring cycle For the first j The usage time corresponding to each status monitoring cycle; S43: Data on DC power supply usage duration and internal resistance extreme value data Substitute these values ​​into the objective function of the least squares method, and consider the rate of change of internal resistance and the constant term. Taking partial derivatives, we obtain a system of equations; ; S44: Solving the system of equations will yield the fitted rate of change of internal resistance. and constant term This leads to the obtained linear regression equation that has been successfully fitted. ; S45: Set the threshold value for the extreme value of internal resistance in DC battery internal resistance faults. And input the fitted linear regression equation. In the calculation, the usage time of the DC power supply with internal resistance fault is determined. Based on the current usage time of the DC resistor Calculate the remaining service life of the DC power supply before an internal resistance fault occurs. ; like If so, the DC resistor has already developed an internal resistance fault; like If this happens, the DC resistor will soon experience an internal resistance failure. like Then the DC resistance over time An internal resistance fault will subsequently occur.

[0008] The beneficial effects of this invention are as follows: Based on the factory-measured speed data of the DC power supply, this invention accurately obtains the influence weights of the DC power supply's charging and discharging states and pure discharge states on its discharge performance. This data is used to calculate and evaluate the discharge performance under charging and discharging states and pure discharge states during subsequent use, and to assess the stability of the discharge performance under each state. Simultaneously, by analyzing the heat generation of the DC battery under charging and discharging states and pure discharge states, a linear regression equation is constructed to predict the internal resistance of the DC battery, which is used to assess the lifespan and internal resistance failures of the DC battery. This allows for early prediction of potential faults, providing maintenance personnel with sufficient time for equipment inspection and replacement, avoiding power grid accidents caused by sudden faults, and improving the reliability and stability of the substation DC power supply system. Attached Figure Description

[0009] Figure 1 This is a flowchart of a method for monitoring the status of DC power supply in a substation. Detailed Implementation

[0010] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0011] like Figure 1 As shown, a method for monitoring the status of a DC power supply in a substation includes the following steps: S1: Based on the test data of the DC power supply used in the substation during factory testing, calculate the weighting coefficients of the performance impact of the DC power supply under pure discharge and simultaneous charge-discharge states. Step S1 specifically includes: S11: Obtain the test data of the DC power supply used in the substation during the factory test. The test data includes the test data under pure discharge state and the test data under simultaneous charge and discharge state. Test data under pure discharge conditions includes output voltage data. and output current data , M This refers to the number of times voltage and current data are collected within the test cycle. The first one under pure discharge state M Output current data and output voltage data; Meanwhile, the test data under charge and discharge conditions includes output voltage data. and output current data , They are the first under simultaneous charging and discharging states. M Output current data and output voltage data; S12: Calculate the coefficient of variation of the output voltage under pure discharge conditions. and the coefficient of variation of output voltage under simultaneous charging and discharging conditions ; ; ; in, m The numbers are for the output voltage data and the output current data. The first under pure discharge state m Output voltage data, This represents the average value of the output voltage data under pure discharge conditions. For the first state of simultaneous charging and discharging m Output voltage data, This represents the average value of the output voltage data under simultaneous charging and discharging conditions. S13: Calculate the weighting coefficients for the impact of pure discharge and simultaneous charge and discharge states on the stability of the output voltage during the use of the DC power supply. ; in, This represents the weighting coefficient for the impact of pure discharge state on output voltage stability. This is a weighting coefficient representing the impact of simultaneous charging and discharging states on the stability of the output voltage. S14: Calculate the dispersion coefficient of the output current under pure discharge conditions. and the coefficient of variation of output current under simultaneous charging and discharging conditions ; ; ; in, The first under pure discharge state m Output current data, This represents the average value of the output current data under pure discharge conditions. For the first state of simultaneous charging and discharging m Output current data, This represents the average value of the output current data under simultaneous charging and discharging conditions. S15: Calculate the weighting coefficients for the impact of pure discharge and simultaneous charge and discharge states on the stability of the output current during the use of the DC power supply. ; in, This represents the weighting coefficient for the impact of pure discharge state on the stability of the output current. This is a weighting coefficient representing the impact of simultaneous charging and discharging states on the stability of the output current.

[0012] In a substation, the DC power supply provides reliable DC power to the protection devices, measurement and control equipment, communication systems, etc. The substation is in a state of continuous operation for a long time. Depending on the switching and working status of the DC power supply equipment in the substation, the amount of electricity that the DC power supply needs to release varies. Therefore, the DC power supply in the substation will be constantly switching between pure discharge state and charging and discharging state. It is generally not in a pure charging state. When the DC power supply has little electricity stored in it, it enters the charging and discharging state. When the DC power supply has a lot of electricity stored in it, it enters the pure discharge state.

[0013] This invention calculates the weighting coefficients for heat dissipation performance, output voltage, and current performance under two states based on the factory test data of the DC power supply. The DC power supply is in its optimal performance state at the time of leaving the factory, and the test results are less affected by the usage state and environment. High-precision weighting coefficients can be calculated. The weighting coefficients represent the degree of influence on the performance of the DC power supply when it is in pure discharge state and randomly switching between charge and discharge states during use. The larger the weighting coefficient, the greater the degree of performance influence under that state. Therefore, it can be used for state performance detection and evaluation of DC power supply during use.

[0014] S2: Define the status monitoring cycle for the DC power supply during its use in the substation. Collect the maximum values ​​of the DC power supply's output voltage, output current, and temperature data within the monitoring cycle. Calculate the fluctuation coefficients of the output voltage and output current, and based on weighted coefficients, calculate the fluctuation coefficients under pure discharge and simultaneous charge / discharge states to assess the charging and discharging function faults of the DC power supply. Step S2 specifically includes the following steps: S21: Define the status monitoring cycle for DC power supply operation in substations. T Data collection status monitoring cycle T Output voltage data of internal DC power supply Output current data and the maximum value of the heating temperature data ; A Condition monitoring cycle TThe number of times the output voltage and output current data are collected internally. These are the status monitoring cycles. T The first internal collection A Output voltage data and output current data; S22: Rated output voltage based on DC power supply Rated output current Calculate the output voltage fluctuation coefficient Output current fluctuation coefficient ; ; in, a Condition monitoring cycle T Numbering of internal output voltage data and output current data. These are the status monitoring cycles. T The first internal collection a Output voltage data and output current data; S23: Set the threshold for the output voltage fluctuation coefficient during DC power supply operation. Output current fluctuation coefficient threshold ; like or If the DC power supply fails, proceed to step S24; otherwise, return to step S21 and continue collecting output voltage data, output current data, and heating temperature data for the next state monitoring cycle. S24: According to the status monitoring cycle T The number of times the internal DC power supply is in pure discharge state and simultaneously in charge and discharge state. f , g And based on weighting coefficients , , , Calculate the fluctuation coefficient under pure discharge and simultaneous charge-discharge conditions. ; ; S25: Set the fluctuation coefficient threshold for the DC power supply under pure discharge and simultaneous charge / discharge conditions. ; like and If the DC power supply fails to discharge, it is determined that the discharge function is faulty and the charging function is normal. like and If the DC power supply's charging and discharging functions are normal, then it can be determined that the DC power supply's charging and discharging functions are normal. like and If the charging function of the DC power supply is faulty, the discharging function is normal. like and If so, it is determined that both the charging and discharging functions of the DC power supply are faulty.

[0015] S3: Based on the moment when the heating temperature reaches its maximum value within the condition monitoring cycle, calculate the DC power supply's usage duration and the internal resistance extreme value during the condition monitoring cycle, obtaining the DC power supply's usage duration data and the corresponding internal resistance extreme value data. Step S3 specifically includes the following steps: S31: Extract during the status monitoring cycle T The internal heating temperature reaches its maximum value. The moment , u This refers to the number of status monitoring cycles experienced after the DC power supply has been put into use, based on the start time of the DC power supply's commissioning. Calculate the status monitoring cycle T The internal heating temperature reaches its maximum value. DC power supply usage time ; S32: Based on the condition monitoring cycle T Output voltage data of the internally acquired DC power supply Output current data Calculate the internal resistance of the DC battery corresponding to each set of voltage and current data. ; S33: Obtain the DC power supply status monitoring cycle T Internal resistance data at various times , For the first A Identify and filter internal resistance data. The maximum value in As a condition monitoring cycle T internal resistance extreme value ; S34: Obtain the DC power supply usage duration calculated for each historical state monitoring cycle during DC power supply usage. and the corresponding internal resistance extreme values Obtain DC power supply usage time data and internal resistance extreme value data This invention will determine the extreme values ​​of internal resistance during the state monitoring cycle. With temperature data reaching its maximum value The equivalent time correspondence indicates that the DC power supply reaches its maximum heating temperature. The reason is due to the extreme value of internal resistance. This is caused by the delay in heating, thus avoiding errors caused by the delay in heating.

[0016] S4: Construct a linear regression equation to predict the change in internal resistance of the DC power supply with usage time. Based on usage time data and corresponding extreme internal resistance data, fit the linear regression equation using the least squares method, output the fitted linear regression equation, and predict the remaining usage time of the DC power supply before an internal resistance fault occurs. Step S41 specifically includes the following steps: S41: Constructing the predicted internal resistance of the DC power supply A linear regression equation that varies with usage duration; ; in, This refers to the duration of DC power supply use. These are the rate of change of internal resistance and the constant term, respectively. j This is the number for the condition monitoring cycle; S42: Fit the linear regression equation using the least squares method. The objective function of the least squares method is: ; in, For the first j The extreme values ​​of internal resistance corresponding to each state monitoring cycle For the first j The usage time corresponding to each status monitoring cycle; S43: Data on DC power supply usage duration and internal resistance extreme value data Substitute these values ​​into the objective function of the least squares method, and consider the rate of change of internal resistance and the constant term. Taking partial derivatives, we obtain a system of equations; ; S44: Solving the system of equations will yield the fitted rate of change of internal resistance. and constant term This leads to the obtained linear regression equation that has been successfully fitted. ; S45: Set the threshold value for the extreme value of internal resistance in DC battery internal resistance faults. And input the fitted linear regression equation. In the calculation, the usage time of the DC power supply with internal resistance fault is determined. Based on the current usage time of the DC resistor Calculate the remaining service life of the DC power supply before an internal resistance fault occurs. ; like If so, the DC resistor has already developed an internal resistance fault; like If this happens, the DC resistor will soon experience an internal resistance failure. like Then the DC resistance over time An internal resistance fault will subsequently occur.

[0017] Internal resistance issues cause the battery to generate more heat, leading to an increase in battery temperature. The amount of heat generated by an internal resistance failure is related to the magnitude of the internal resistance. The higher the internal resistance, the more heat is generated, and the more pronounced the temperature increase.

[0018] This invention, based on factory-measured speed data of DC power supplies, accurately obtains the impact weights of charging / discharging and pure discharge states on discharge performance. This data is used to calculate and evaluate discharge performance under charging / discharging and pure discharge states during subsequent use, and to assess the stability of discharge performance under each state. Simultaneously, by analyzing the heat generation of the DC battery under charging / discharging and pure discharge states, a linear regression equation is constructed to predict the internal resistance of the DC battery, used for assessing the battery's lifespan and internal resistance failures. This allows for early prediction of potential faults, providing maintenance personnel with sufficient time for equipment inspection and replacement, avoiding power grid accidents caused by sudden failures, and improving the reliability and stability of the substation's DC power supply system.

Claims

1. A method for monitoring the status of DC power supply in a substation, characterized in that, Includes the following steps: S1: Based on the test data of the DC power supply used in the substation during factory testing, calculate the weighting coefficient of the DC power supply's performance impact under pure discharge and simultaneous charge and discharge conditions. S2: Define the status monitoring cycle of the DC power supply during its use in the substation, collect the maximum values ​​of the DC power supply's output voltage data, output current data, and heating temperature data within the status monitoring cycle, calculate the fluctuation coefficients of the output voltage and output current, and calculate the fluctuation coefficients under pure discharge and simultaneous charging and discharging states based on the weighting coefficients, and evaluate the charging and discharging function faults of the DC power supply. S3: Based on the moment when the heating temperature reaches its maximum value within the condition monitoring cycle, calculate the usage time of the DC power supply and the extreme value of the internal resistance during the condition monitoring cycle to obtain the usage time data of the DC power supply and the corresponding extreme value data of the internal resistance. S4: Construct a linear regression equation to predict the change of internal resistance of DC power supply with usage time. Based on usage time data and corresponding internal resistance extreme value data, fit the linear regression equation using the least squares method, output the fitted linear regression equation, and predict the remaining usage time of DC power supply before internal resistance failure occurs.

2. The substation DC power supply status monitoring method according to claim 1, characterized in that, Step S1 includes: S11: Obtain the test data of the DC power supply used in the substation during the factory test. The test data includes the test data under pure discharge state and the test data under simultaneous charge and discharge state. Test data under pure discharge conditions includes output voltage data. and output current data , M This refers to the number of times voltage and current data are collected within the test cycle. The first one under pure discharge state M Output current data and output voltage data; Meanwhile, the test data under charge and discharge conditions includes output voltage data. and output current data , They are the first under simultaneous charging and discharging states. M Output current data and output voltage data; S12: Calculate the coefficient of variation of the output voltage under pure discharge conditions. and the coefficient of variation of output voltage under simultaneous charging and discharging conditions ; ； ； in, m The numbers are for the output voltage data and the output current data. The first under pure discharge state m Output voltage data, This represents the average value of the output voltage data under pure discharge conditions. For the first state of simultaneous charging and discharging m Output voltage data, This represents the average value of the output voltage data under simultaneous charging and discharging conditions. S13: Calculate the weighting coefficients for the impact of pure discharge and simultaneous charge and discharge states on the stability of the output voltage during the use of the DC power supply. ； in, This represents the weighting coefficient for the impact of pure discharge state on output voltage stability. This is a weighting coefficient representing the impact of simultaneous charging and discharging states on the stability of the output voltage. S14: Calculate the dispersion coefficient of the output current under pure discharge conditions. and the coefficient of variation of output current under simultaneous charging and discharging conditions ; ； ； in, The first under pure discharge state m Output current data, This represents the average value of the output current data under pure discharge conditions. For the first charge and discharge state m Output current data, This represents the average value of the output current data under simultaneous charging and discharging conditions. S15: Calculate the weighting coefficients for the impact of pure discharge and simultaneous charge and discharge states on the stability of the output current during the use of the DC power supply. ； in, This represents the weighting coefficient for the impact of pure discharge state on the stability of the output current. This is a weighting coefficient representing the impact of simultaneous charging and discharging states on the stability of the output current.

3. The substation DC power supply status monitoring method according to claim 2, characterized in that, Step S2 includes: S21: Define the status monitoring cycle for DC power supply operation in substations. T Data collection status monitoring cycle T Output voltage data of internal DC power supply Output current data and the maximum value of the heating temperature data ; A Condition monitoring cycle T The number of times the output voltage and output current data are collected internally. These are the status monitoring cycles. T The first internal collection A Output voltage data and output current data; S22: Rated output voltage based on DC power supply Rated output current Calculate the output voltage fluctuation coefficient Output current fluctuation coefficient ; ； in, a Condition monitoring cycle T Numbering of internal output voltage data and output current data. These are the status monitoring cycles. T The first internal collection a Output voltage data and output current data; S23: Set the threshold for the output voltage fluctuation coefficient during DC power supply operation. Output current fluctuation coefficient threshold ; like or If the DC power supply fails, proceed to step S24; otherwise, return to step S21 and continue collecting output voltage data, output current data and heating temperature data for the next state monitoring cycle. S24: According to the condition monitoring cycle T The number of times the internal DC power supply is in pure discharge state and simultaneously in charge and discharge state. f , g And based on weighting coefficients , , , Calculate the fluctuation coefficient under pure discharge and simultaneous charge-discharge conditions. ; ； S25: Set the fluctuation coefficient threshold for the DC power supply under pure discharge and simultaneous charge / discharge conditions. ; like and If the DC power supply fails to discharge, it is determined that the discharge function is faulty and the charging function is normal. like and If the DC power supply's charging and discharging functions are normal, then it can be determined that the DC power supply's charging and discharging functions are normal. like and If the charging function of the DC power supply is faulty, the discharging function is normal. like and If so, it is determined that both the charging and discharging functions of the DC power supply are faulty.

4. The substation DC power supply status monitoring method according to claim 3, characterized in that, Step S3 includes: S31: Extract during the status monitoring cycle T The internal heating temperature reaches its maximum value. The moment , u This refers to the number of status monitoring cycles experienced after the DC power supply has been put into use, based on the start time of the DC power supply's commissioning. Calculate the status monitoring cycle T The internal heating temperature reaches its maximum value. DC power supply usage time ; S32: Based on the condition monitoring cycle T Output voltage data of the internally acquired DC power supply Output current data Calculate the internal resistance of the DC battery corresponding to each set of voltage and current data. ; S33: Obtain the DC power supply status monitoring cycle T Internal resistance data at various times , For the first A Identify and filter internal resistance data. The maximum value in As a condition monitoring cycle T internal resistance extreme value ; S34: Obtain the DC power supply usage duration calculated for each historical state monitoring cycle during DC power supply usage. and the corresponding internal resistance extreme values Obtain DC power supply usage time data and internal resistance extreme value data .

5. The substation DC power supply status monitoring method according to claim 4, characterized in that, Step S4 includes: S41: Constructing the predicted internal resistance of the DC power supply A linear regression equation that varies with usage duration; ； in, This refers to the duration of DC power supply use. These are the rate of change of internal resistance and the constant term, respectively. j This is the number for the condition monitoring cycle; S42: Fit the linear regression equation using the least squares method. The objective function of the least squares method is: ； in, For the first j The extreme values ​​of internal resistance corresponding to each state monitoring cycle For the first j The usage time corresponding to each status monitoring cycle; S43: Data on DC power supply usage duration and internal resistance extreme value data Substitute these values ​​into the objective function of the least squares method, and consider the rate of change of internal resistance and the constant term. Taking partial derivatives, we obtain a system of equations; ； S44: Solving the system of equations will yield the fitted rate of change of internal resistance. and constant term This leads to the obtained linear regression equation that has been successfully fitted. ; S45: Set the threshold value for the extreme value of internal resistance in DC battery internal resistance faults. And input the fitted linear regression equation. In the calculation, the usage time of the DC power supply with internal resistance fault is determined. Based on the current usage time of the DC resistor Calculate the remaining service life of the DC power supply before an internal resistance fault occurs. ; like If so, the DC resistor has already developed an internal resistance fault; like If this happens, the DC resistor will soon experience an internal resistance failure. like Then the DC resistance over time An internal resistance fault will subsequently occur.

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