Smart park electric power operation and maintenance evaluation method and system

Abstract

The invention relates to the technical field of power operation and maintenance, in particular to a smart park power operation and maintenance evaluation method and system, and the method comprises the steps: collecting operation data during the island operation after detecting that a power distribution system is switched from a grid-connected state to an island operation state, and carrying out the disturbance interval screening of the operation data, establishing a local relation model between power change and system response, identifying equivalent control characteristic parameters of the power distribution system under an island operation condition, and generating equivalent characteristic data; constructing an equivalent dynamic model of the power distribution system on the basis, and inverting an equivalent inertia parameter and a damping parameter of the system to obtain synchronization capability data; calculating equivalent power grid parameters and short-circuit support capability of the power distribution system under the island operation condition, and substituting the equivalent power grid parameters and the short-circuit support capability into the relay protection characteristic relation to obtain protection margin data; and performing frequency domain analysis on the power change of the energy storage system, calculating an energy storage life asymmetric erosion amount caused by unplanned island operation, and generating smart park power operation and maintenance evaluation data.

Description

Technical Field

[0001] This invention relates to the field of power operation and maintenance technology, and in particular to a smart park power operation and maintenance assessment method and system. Background Technology

[0002] With the large-scale integration of distributed power sources and energy storage systems in smart parks, the park's power distribution system typically maintains power balance and operational stability through methods such as droop control, virtual inertia control, or voltage-reactive power control when operating in grid-connected mode. Existing operation and maintenance methods mainly analyze and evaluate the power-frequency and power-voltage control characteristics of the system based on equipment design parameters, controller setpoints, or planned test results. When the power distribution system is in islanded operation, it is usually judged whether the system is in an acceptable operating state by whether the operating quantities such as voltage and frequency exceed the limits.

[0003] In the event of unplanned islanding operation, the control loop of distributed power generation and energy storage system may enter an undesigned operating state due to current limiting, saturation, or control reduction, causing the equivalent control characteristics of the system to deviate in actual operation. This deviation will not trigger alarms or protection actions. Without testing or simulation, existing technologies cannot identify and quantify the impact of this equivalent control characteristic drift on the system stability margin. Summary of the Invention

[0004] To overcome the above shortcomings, this invention provides a smart park power operation and maintenance assessment method and system, which aims to improve the problem that existing technologies are unable to identify and quantify the impact of equivalent control characteristic drift on system stability margin without conducting experiments or simulations.

[0005] In a first aspect, the present invention provides the following technical solution: a method for assessing the operation and maintenance of power supply in a smart park, comprising the following steps:

[0006] S1. After detecting that the power distribution system has switched from grid-connected state to unplanned islanded operation state, collect operation data during the islanded operation period;

[0007] S2. Screen the disturbance range of the operating data, establish a local relationship model between power change and system response, identify the equivalent control characteristic parameters of the power distribution system under islanded operation conditions, and generate equivalent characteristic data.

[0008] S3. Construct an equivalent dynamic model of the power distribution system using equivalent characteristic data and system dynamic response characteristics, invert the equivalent inertia parameters and damping parameters of the system, and obtain synchronization capability data accordingly.

[0009] S4. Combining equivalent characteristic data and synchronization capability data, calculate the equivalent grid parameters and short-circuit support capability of the distribution system under islanded operation conditions, and substitute them into the existing relay protection characteristic relationship to obtain protection margin data.

[0010] S5. Using operational data and equivalent characteristic data, frequency domain analysis is performed on the power changes of the energy storage system during islanded operation. Stress indices characterizing high-frequency power support behavior are extracted, and the asymmetric erosion of energy storage lifetime caused by unplanned islanded operation is calculated.

[0011] S6. Generate smart park power operation and maintenance assessment data based on synchronization capability data, protection margin data, and asymmetric erosion of energy storage life.

[0012] By adopting the above technical solution, it is possible to collect operational data during unplanned islanding operation and select naturally formed power disturbance ranges, establish a local relationship model between power change and system response, identify the equivalent control characteristic parameters of the power distribution system under actual operating conditions, and on this basis, model and analyze the dynamic characteristics of the system. Thus, it is possible to identify and quantify the equivalent control characteristic drift caused by unplanned islanding operation without conducting experiments or simulations, and further evaluate the impact of this drift on the system stability margin.

[0013] Preferably, in step S2, the step of filtering the perturbation interval of the running data includes:

[0014] Perform time-series traversal of the operating data to identify time periods in the operating data where the power change exceeds a preset disturbance threshold;

[0015] The duration of the identified time period is determined, and time periods whose duration meets the preset time conditions are retained as candidate disturbance intervals.

[0016] The candidate disturbance intervals are judged for consistency of operating status, and time periods with switching of operating mode or sudden change of control status are eliminated;

[0017] The remaining time period is defined as the disturbance interval.

[0018] Preferably, in step S2, the step of establishing a local relationship model between power change and system response includes:

[0019] Within the disturbance range, the operating data is segmented and processed to extract the power change and system response within the corresponding time period;

[0020] Pair power changes with system response quantities to construct a dataset describing the correspondence between power changes and system response;

[0021] Based on the dataset, a local relationship model between power change and system response is established within the disturbance range.

[0022] Preferably, in step S2, the step of identifying the equivalent control characteristic parameters of the power distribution system under islanded operation conditions and generating equivalent characteristic data includes:

[0023] Based on the local relationship model, the power change and system response within the disturbance interval are subjected to parameter fitting to obtain model parameters characterizing the relationship between power change and system response;

[0024] The model parameters are updated within a time window to obtain the control characteristic parameters corresponding to different disturbance ranges;

[0025] The acquired control characteristic parameters are summarized and processed to form equivalent characteristic data that characterize the control characteristics of the power distribution system under islanded operation conditions.

[0026] Preferably, in step S3, the step of constructing an equivalent dynamic model of the power distribution system using equivalent characteristic data and system dynamic response characteristics includes:

[0027] Obtain the power change characteristic parameters corresponding to the equivalent characteristic data and the corresponding system dynamic response characteristic data;

[0028] Based on power change characteristic parameters and system dynamic response characteristic data, state variables describing the dynamic behavior of the power distribution system are determined.

[0029] Based on the changing relationships between state variables, an equivalent dynamic model is established to characterize the dynamic characteristics of the power distribution system under islanded operation conditions.

[0030] Preferably, in step S3, the steps of retrieving the equivalent inertia parameters and damping parameters of the inversion system include:

[0031] Based on the equivalent dynamic model, time series data corresponding to the dynamic response characteristics of the system during islanded operation are extracted;

[0032] Parameter estimation processing is performed on the time series data to obtain candidate values ​​of inertia and damping parameters that match the equivalent dynamic model;

[0033] Consistency verification is performed on the candidate values ​​of inertia parameter and damping parameter to determine the equivalent inertia parameter and equivalent damping parameter of the system.

[0034] Preferably, in step S4, the step of calculating the equivalent grid parameters and short-circuit support capability of the power distribution system under islanded operation conditions includes:

[0035] During islanded operation, parameters characterizing voltage and current variation features of the power distribution system are extracted based on operational data;

[0036] Based on the voltage and current variation characteristics, calculate the equivalent grid parameters of the distribution system under islanded operation conditions;

[0037] Based on equivalent grid parameters, the short-circuit support capacity corresponding to the operating state of the power distribution system is calculated.

[0038] Preferably, in step S5, the step of performing frequency domain analysis on the power changes of the energy storage system during islanded operation includes:

[0039] Acquire power time-series data of the energy storage system during islanded operation;

[0040] The power time series data is segmented to form data segments for frequency domain analysis.

[0041] Perform frequency domain transformation on the data segment to obtain the corresponding power spectrum data;

[0042] Based on power spectrum data, frequency domain parameters characterizing the frequency distribution of power changes are extracted.

[0043] Preferably, in step S5, the step of calculating the asymmetric erosion of energy storage lifetime caused by unplanned islanding operation includes:

[0044] Based on the frequency domain parameters obtained from frequency domain analysis, the power change characteristics of the corresponding energy storage system in the charging and discharging directions are extracted respectively.

[0045] The power variation characteristics in the charging and discharging directions are processed independently to obtain the corresponding energy stress parameters;

[0046] Based on the energy stress parameters and according to the preset erosion calculation relationship, the lifetime erosion of the energy storage system under unplanned islanded operation conditions is calculated, and the erosion corresponding to the charging direction and the discharging direction is distinguished to obtain the asymmetric erosion of the energy storage lifetime.

[0047] Secondly, the present invention provides the following technical solution: a smart park power operation and maintenance assessment system, the system comprising:

[0048] The data acquisition module is used to collect operational data during islanding operation after the power distribution system is detected to have switched from grid-connected state to unplanned islanding operation state.

[0049] The disturbance analysis module is used to filter the disturbance range of the operating data, establish a local relationship model between power change and system response, identify the equivalent control characteristic parameters of the power distribution system under islanded operation conditions, and generate equivalent characteristic data.

[0050] The dynamic modeling module is used to construct an equivalent dynamic model of the power distribution system using the equivalent characteristic data and the dynamic response characteristics of the system, invert the equivalent inertia parameters and damping parameters of the system, and obtain synchronization capability data accordingly.

[0051] The power grid support analysis module is used to combine the equivalent characteristic data and synchronization capability data to calculate the equivalent power grid parameters and short-circuit support capability of the distribution system under islanded operation conditions, and substitute them into the existing relay protection characteristic relationship to obtain protection margin data.

[0052] The energy storage frequency domain analysis module is used to perform frequency domain analysis on the power changes of the energy storage system during islanded operation using the operating data and equivalent characteristic data, extract stress indicators characterizing high-frequency power support behavior, and calculate the asymmetric erosion of energy storage lifetime caused by unplanned islanded operation.

[0053] The result generation module is used to generate smart park power operation and maintenance assessment data based on the synchronization capability data, protection margin data, and energy storage lifetime asymmetric erosion.

[0054] The present invention has the following beneficial effects:

[0055] 1. In this invention, by selecting a natural disturbance range during unplanned islanded operation and establishing a local relationship model between power change and system response, the online identification of the equivalent control characteristics of the power distribution system is realized. This solves the problem that the actual control characteristics of distributed power sources and energy storage systems deviate from the design parameters under current limiting, saturation, or control reduction conditions and cannot be identified without testing.

[0056] 2. In this invention, by constructing an equivalent dynamic model based on the dynamic evolution process of frequency and phase angle during islanded operation and inverting the equivalent inertia parameters and damping parameters of the system, the quantitative characterization of the system's synchronization capability is realized, which solves the problem that existing technologies rely solely on instantaneous voltage, frequency, or phase angle thresholds to judge the feasibility of grid connection synchronization and cannot identify the implicit degradation of synchronization capability.

[0057] 3. In this invention, by utilizing the natural disturbances of voltage and current during islanded operation to invert the equivalent grid parameters and short-circuit support capability of the distribution system, and substituting them into the existing relay protection characteristic relationship to calculate the protection margin, the operational status assessment of relay protection coordination under the condition of no short-circuit fault is realized, solving the problem that the existing technology cannot identify the dynamic degradation of protection coordination margin when no protection action occurs.

[0058] 4. In this invention, by performing frequency domain analysis on the power changes of the energy storage system during islanded operation and calculating the lifetime erosion corresponding to the charging and discharging directions respectively, the directionality and asymmetric quantification of the lifetime erosion of the energy storage system are realized, which solves the problem that the existing technology relies only on SOC or SOH indicators and cannot reflect the high-frequency, bidirectional stress lifetime loss caused by unplanned islanded operation. Attached Figure Description

[0059] Figure 1 This is a flowchart of a smart park power operation and maintenance assessment method proposed in this invention;

[0060] Figure 2 This is an architecture diagram of a smart park power operation and maintenance assessment system proposed in this invention. Detailed Implementation

[0061] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] Example 1:

[0063] In the first embodiment of the present invention, the present invention provides a method and system for assessing the operation and maintenance of power supply in smart parks, such as... Figure 1 As shown, it includes the following steps:

[0064] S1. After detecting that the power distribution system has switched from grid-connected state to unplanned islanded operation state, collect operation data during the islanded operation period;

[0065] Specifically, under normal grid-connected operation, the smart park power distribution system maintains electrical connection and exchanges power with the upstream power grid through grid-connected circuit breakers or grid-connected switches. When the grid-connected circuit breaker is disconnected due to external power grid faults, maintenance operations, or other unplanned factors, the power distribution system switches from grid-connected state to unplanned islanded operation state. After the state switch occurs, the system comprehensively judges the opening and closing status of the grid-connected circuit breaker, the continuity of voltage phase angle, and the characteristics of power exchange changes to confirm that the unplanned islanded operation state has been formed.

[0066] After confirming the entry into unplanned islanded operation, the system initiates the operation data acquisition process during islanded operation. The operation data comes from the existing measurement and monitoring units in the park's power distribution system. These measurement and monitoring units can be optionally set at feeders, buses, distributed power grid connection points, and energy storage system interfaces. The collected operation data is used to characterize the power exchange characteristics, electrical operation status, and energy storage system operation behavior of the power distribution system during islanded operation. The operation data is continuously acquired and stored in time series form.

[0067] During the data acquisition process, the sampling period is set according to the operating characteristics of the power distribution system. Optionally, a fixed sampling period can be used for continuous sampling to meet the time resolution requirements of subsequent disturbance range screening and dynamic characteristic analysis. The acquired operating data is cached in chronological order and a time correlation is established with the start time of islanded operation to distinguish between grid-connected operation data and islanded operation data.

[0068] During islanded operation, the data acquisition process is based on the power fluctuations and dynamic responses formed under the natural operating conditions of the system, without introducing additional experimental disturbances or human control operations. This allows the acquired data to reflect the actual operating behavior characteristics of the distribution system under unplanned islanded operation conditions. This data serves as the basic input for subsequent disturbance interval screening, local relationship model establishment, and equivalent control characteristic parameter identification, thus providing a data foundation for subsequent analysis of the dynamic characteristics of the distribution system, grid support capacity, and energy storage operation behavior.

[0069] By using the above-mentioned operational data collection methods, subsequent steps can continuously analyze the power distribution system under a unified time benchmark and consistent operating status, thereby forming a complete smart park power operation and maintenance assessment process.

[0070] S2. Screen the disturbance range of the operating data, establish a local relationship model between power change and system response, identify the equivalent control characteristic parameters of the power distribution system under islanded operation conditions, and generate equivalent characteristic data.

[0071] Furthermore, in step S2, the step of filtering the disturbance range of the running data includes:

[0072] Perform time-series traversal of the operating data to identify time periods in the operating data where the power change exceeds a preset disturbance threshold;

[0073] The duration of the identified time period is determined, and time periods whose duration meets the preset time conditions are retained as candidate disturbance intervals.

[0074] The candidate disturbance intervals are judged for consistency of operating status, and time periods with switching of operating mode or sudden change of control status are eliminated;

[0075] The remaining time period is defined as the disturbance interval.

[0076] Furthermore, in step S2, the step of establishing a local relationship model between power change and system response includes:

[0077] Within the disturbance range, the operating data is segmented and processed to extract the power change and system response within the corresponding time period;

[0078] Pair power changes with system response quantities to construct a dataset describing the correspondence between power changes and system response;

[0079] Based on the dataset, a local relationship model between power change and system response is established within the disturbance range.

[0080] Furthermore, in step S2, the steps of identifying the equivalent control characteristic parameters of the power distribution system under islanded operation conditions and generating equivalent characteristic data include:

[0081] Based on the local relationship model, the power change and system response within the disturbance interval are subjected to parameter fitting to obtain model parameters characterizing the relationship between power change and system response;

[0082] The model parameters are updated within a time window to obtain the control characteristic parameters corresponding to different disturbance ranges;

[0083] The acquired control characteristic parameters are summarized and processed to form equivalent characteristic data that characterize the control characteristics of the power distribution system under islanded operation conditions.

[0084] Specifically, step S2 is initiated after the data collection during islanded operation is completed. The operation data is input to the operation and maintenance assessment processing unit in the form of a time series. The operation data may include data for characterizing the power exchange characteristics of the power distribution system and data for characterizing the dynamic response of the system. The power exchange characteristic data may include active power series and reactive power series, and the dynamic response data may include frequency series and voltage amplitude series. Before entering step S2, the operation data may be processed by outlier removal and missing segment marking to ensure the stability of the subsequent disturbance identification and parameter fitting process.

[0085] During the perturbation interval screening process, the running data is traversed over time to construct a power change sequence. The power change can be obtained by differentiating adjacent sampling points, for example, by dividing the time interval by... With time The active power difference is defined as:

[0086] ;

[0087] in Indicates time The active power sample value, when When the time period is specified, the continuous time period containing that time is identified as a candidate time period for disturbance, and the disturbance threshold is set. It can be set according to the capacity level or historical statistical characteristics of the park's power distribution system;

[0088] When determining the duration of candidate disturbance time periods, the sampling period is used as the basis. Calculate the length of the time period:

[0089] ;

[0090] in The number of sampling points within a time period, when When the preset time conditions are met, the interval is retained as a candidate perturbation interval to avoid introducing instantaneous spikes or slow drifts into the subsequent modeling process;

[0091] When judging the consistency of the operating state of candidate disturbance intervals, operating mode or control state discrimination information is introduced to eliminate time periods with operating mode switching or control state abrupt changes, and retain time periods with continuous operating state and consistent control mode as disturbance intervals. The time boundaries of the disturbance intervals are kept consistent in subsequent processing.

[0092] When establishing a local relationship model between power change and system response, the operating data is segmented using the disturbance interval as the data boundary, and the power change and system response within the corresponding time period are extracted. The power change may optionally include... and The system response may optionally include frequency variation. With voltage change Each change is obtained through the difference between adjacent sampling points or the deviation relative to the reference value;

[0093] A dataset is constructed by pairing power change with system response.

[0094] ;

[0095] A local relational model is established within the disturbance interval, which can optionally be represented in linear form as follows:

[0096] ;

[0097] ;

[0098] in and These represent the equivalent control characteristic parameters that represent the power-frequency and reactive-voltage relationships, respectively.

[0099] In the process of identifying equivalent control characteristic parameters, parameter fitting is performed on the dataset within the disturbance interval based on the local relation model. The parameter fitting can optionally adopt the least squares estimation method. The estimated value of the equivalent control characteristic parameter is obtained by minimizing the sum of squared residuals. When continuous updates are required, the parameter fitting process can be combined with a time window update mechanism.

[0100] When summarizing control characteristic parameters obtained from multiple disturbance intervals or multiple time windows, equivalent characteristic data is formed through statistical aggregation and consistency screening. The equivalent characteristic data includes at least the equivalent control characteristic parameter values ​​and their corresponding disturbance interval information, which are used for subsequent equivalent dynamic modeling and system capability assessment.

[0101] S3. Construct an equivalent dynamic model of the power distribution system using equivalent characteristic data and system dynamic response characteristics, invert the equivalent inertia parameters and damping parameters of the system, and obtain synchronization capability data accordingly.

[0102] Furthermore, in step S3, the step of constructing an equivalent dynamic model of the power distribution system using equivalent characteristic data and system dynamic response characteristics includes:

[0103] Obtain the power change characteristic parameters corresponding to the equivalent characteristic data and the corresponding system dynamic response characteristic data;

[0104] Based on power change characteristic parameters and system dynamic response characteristic data, state variables describing the dynamic behavior of the power distribution system are determined.

[0105] Based on the changing relationships between state variables, an equivalent dynamic model is established to characterize the dynamic characteristics of the power distribution system under islanded operation conditions.

[0106] Furthermore, in step S3, the steps for retrieving the equivalent inertia parameters and damping parameters of the inverted system include:

[0107] Based on the equivalent dynamic model, time series data corresponding to the dynamic response characteristics of the system during islanded operation are extracted;

[0108] Parameter estimation processing is performed on the time series data to obtain candidate values ​​of inertia and damping parameters that match the equivalent dynamic model;

[0109] Consistency verification is performed on the candidate values ​​of inertia parameter and damping parameter to determine the equivalent inertia parameter and equivalent damping parameter of the system.

[0110] Specifically, step S3 is initiated after the equivalent characteristic data is generated. The equivalent characteristic data and the system dynamic response characteristics are used as unified inputs into the dynamic modeling and parameter inversion processing flow. The equivalent characteristic data comes from the aforementioned local relationship modeling and parameter fitting process between power change and system response, and is used to characterize the control behavior characteristics of the power distribution system under islanded operation conditions. The system dynamic response characteristics come from the frequency, voltage or phase angle change sequence corresponding to power disturbance in the operating data during islanded operation, and are used to characterize the dynamic evolution process of the power distribution system under disturbance.

[0111] In constructing the equivalent dynamic model of the power distribution system, power change characteristic parameters are first obtained from the equivalent characteristic data. The power change characteristic parameters may include equivalent power frequency control characteristic parameters and equivalent reactive voltage control characteristic parameters. At the same time, system dynamic response characteristic data corresponding to power disturbances are extracted from the operating data. The system dynamic response characteristic data may include frequency time series, phase angle time series or a combination thereof. The power change characteristic parameters and the system dynamic response characteristic data maintain a consistent index relationship on the time axis to ensure the causal correspondence between variables in the subsequent modeling process.

[0112] When determining the state variables describing the dynamic behavior of the power distribution system, based on the overall dynamic characteristics of the power distribution system under islanded operation conditions, the system state variables are selected as dynamic quantities that can reflect the system's inertia and damping characteristics. The state variables may optionally include the system frequency deviation. and its rate of change, or equivalent phase angle deviation and its rate of change, of which This represents the offset of the system frequency relative to the steady-state reference frequency. This represents the offset of the system's equivalent phase angle relative to the reference phase angle, a time variable. Indicates the continuous time during the operation of the isolated island;

[0113] When establishing the equivalent dynamic model, the equivalent dynamic equations describing the dynamic behavior of the power distribution system are constructed based on the changing relationships between state variables. The equivalent dynamic model can optionally be expressed in the form of a second-order dynamic model. For example, when frequency is used as the state variable, the equivalent dynamic model can be expressed as:

[0114] ;

[0115] in, This represents the equivalent inertia parameter of the power distribution system, used to characterize the system's inertial response capability to power disturbances. This represents the equivalent damping parameter of the power distribution system, used to characterize the damping attenuation characteristics of the system's frequency deviation. This represents the equivalent active power disturbance applied to the system under islanded operation conditions. It can be determined by both equivalent characteristic data and operational data. The equivalent dynamic model is limited to the islanded operation condition and the disturbance range and is used to reflect the local dynamic characteristics of the system under this condition.

[0116] In the process of inverting the equivalent inertia parameters and damping parameters of the system, based on the established equivalent dynamic model, time series data corresponding to the dynamic response characteristics of the system during islanded operation are extracted. The time series data may optionally include frequency deviation sequences. and the corresponding power perturbation sequence ,in Representing discrete sampling times, the equivalent dynamic model can be expressed in discrete-time form, and the above dynamic equations can be discretized as follows:

[0117] ;

[0118] in Indicates the sampling period;

[0119] When performing parameter estimation on time series data, a set of parameter estimation equations is constructed based on a discretized model. By combining the equations corresponding to multiple sampling times, a set of equations for inertia parameters is formed. With damping parameters For the overdetermined system of equations, parameter estimation can optionally be achieved using the least squares estimation method. The least squares estimation method is a numerical estimation method that solves for the parameters by minimizing the sum of squared residuals between the model's predicted values ​​and the actual measured values. Its objective function can be expressed as:

[0120] ;

[0121] By analyzing the objective function Find the minimum value to obtain candidate values ​​for the inertia parameter that match the equivalent dynamic model. Candidate values ​​of damping parameters subscript Indicates the candidate estimation results;

[0122] When verifying the consistency of candidate values ​​for inertia and damping parameters, numerical consistency analysis is performed on the candidate values ​​obtained within different disturbance intervals or time windows. The consistency verification may optionally include calculating the statistical dispersion of the parameter sequence, such as calculating the mean and standard deviation of the candidate values. When the candidate values ​​are within a preset allowable fluctuation range, the corresponding inertia and damping parameters are determined as the equivalent inertia parameters of the power distribution system under islanded operation conditions. and equivalent damping parameters This completes the inversion process of the system's equivalent inertia parameters and damping parameters;

[0123] After obtaining the equivalent inertia parameters and damping parameters, the system synchronization capability is further characterized based on the equivalent dynamic model. The synchronization capability data can be quantitatively described by the combination relationship between the inertia parameters and the damping parameters. For example, the synchronization capability index can be constructed to characterize the dynamic recovery capability of the system frequency, or the synchronization capability data can be formed by analyzing the dynamic response range of the frequency deviation under a given power disturbance condition. The synchronization capability data, together with the aforementioned equivalent characteristic data, protection margin data, and energy storage lifetime erosion, constitute the components of the smart park power operation and maintenance assessment data, and serve as the input basis for subsequent operation and maintenance analysis and decision-making processes.

[0124] S4. Combining equivalent characteristic data and synchronization capability data, calculate the equivalent grid parameters and short-circuit support capability of the distribution system under islanded operation conditions, and substitute them into the existing relay protection characteristic relationship to obtain protection margin data.

[0125] Furthermore, in step S4, the steps for calculating the equivalent grid parameters and short-circuit support capability of the distribution system under islanded operation conditions include:

[0126] During islanded operation, parameters characterizing voltage and current variation features of the power distribution system are extracted based on operational data;

[0127] Based on the voltage and current variation characteristics, calculate the equivalent grid parameters of the distribution system under islanded operation conditions;

[0128] Based on equivalent grid parameters, the short-circuit support capacity corresponding to the operating state of the power distribution system is calculated.

[0129] Specifically, step S4 is initiated after obtaining the equivalent characteristic data and synchronization capability data. The operating data continues to be used as input in the extraction process of voltage change characteristics and current change characteristics. The operating data can be optionally derived from the metering sampling device, feeder monitoring device, or protection measurement circuit of the park's power distribution system. The equivalent characteristic data is used to characterize the control behavior characteristics under islanded operation conditions, and the synchronization capability data is used to characterize the dynamic capability characteristics under islanded operation conditions. By associating the operating data with the equivalent characteristic data and synchronization capability data under the same time base, the subsequent calculation of equivalent grid parameters and the formation of protection margin data have consistent data input and logical continuity.

[0130] When extracting voltage and current change characteristic parameters, operational data segments during islanded operation are selected and processed into time windows. The length of the time window can be optionally set based on the sampling period and the protection action time scale. Characterization calculations are performed on the voltage and current sampling sequences within each time window. The voltage sampling sequence can be represented as follows: The current sampling sequence can be represented as ,in The voltage change characteristic parameters, representing discrete sampling times, may optionally include a voltage increment sequence. In addition to the effective value change amplitude of voltage, the characteristic parameters of current change may optionally include the current increment sequence. The effective value change of current, voltage increment, and current increment can be obtained by the difference between adjacent sampling points, and are expressed as follows:

[0131] ;

[0132] ;

[0133] in Indicates the sampling time voltage sampling value, Indicates the sampling time The current sampling value, This represents the voltage change at the corresponding moment. This represents the change in current at the corresponding moment.

[0134] When calculating the equivalent grid parameters under islanded operation conditions, the calculation relationship of equivalent parameters is established based on the characteristic parameters of voltage and current changes. The equivalent grid parameters can optionally be expressed in the form of equivalent impedance, which can be expressed as either complex impedance or amplitude impedance. As one possible approach, the estimated equivalent impedance is constructed using the ratio of voltage change to current change. It can be represented as:

[0135] ;

[0136] in Indicates at the sampling time The corresponding equivalent grid parameters, if they exist In cases where the value is too small, leading to instability, a threshold for the current change can be optionally introduced. And in satisfying Equivalent impedance calculation is performed at the sampling points, and the current change threshold is set. The settings can be determined based on the measurement resolution or noise level to ensure the numerical stability of the equivalent power grid parameters calculated.

[0137] When extending the equivalent grid parameters from instantaneous estimates to representative values ​​within a time window, it is optional to assign values ​​to multiple sampling points within the time window. Perform statistical aggregation processing. The statistical aggregation method can optionally include mean, weighted mean, or median, and the weights can optionally be determined by... Alternatively, the residual consistency index can be determined to obtain the equivalent grid parameters at the time window level. And associate it with the synchronization capability data to mark the dynamic capability status corresponding to the equivalent grid parameter;

[0138] When calculating short-circuit support capacity based on equivalent grid parameters, the short-circuit support capacity can be characterized, optionally in the form of equivalent short-circuit current capacity or equivalent short-circuit capacity. As one possible approach, given a nominal voltage amplitude... Under the condition of equivalent short-circuit current capability It can be represented as:

[0139] ;

[0140] in This indicates the nominal voltage amplitude at the corresponding voltage level. This represents the magnitude of the equivalent impedance and the equivalent short-circuit capacity. This can be further expressed as:

[0141] ;

[0142] in The capacity representation quantity corresponding to the short-circuit support capability is obtained through the above calculations, which yields the short-circuit support capability value corresponding to the islanded operation state of the power distribution system.

[0143] When incorporating short-circuit support capability into the relay protection characteristic relationship to form protection margin data, the relay protection characteristic relationship may optionally include the correspondence between current setting and operating time, or the correspondence between current multiple and operating time. The relay protection characteristic relationship can be determined by the protection setting sheet or the characteristic parameters of the protection device. As one possible approach, an inverse time protection characteristic function can be used to represent the relationship between operating time and fault current. The operating time function can be expressed as:

[0144] ;

[0145] in This indicates that when the current amplitude is The action time of the moment, This indicates the protection starting current setting. This represents the inverse-time characteristic parameter, given by the protection setting scheme, and the current amplitude. The equivalent short-circuit current capability can be calculated from the short-circuit support capability. Replacement, to obtain the main protection action time With backup protection action time subscript This represents the set of characteristic parameters for the main protection channel, indicated by the subscript. This represents the set of characteristic parameters for the backup protection channel;

[0146] When generating protection margin data, coordination margin parameters are constructed based on the time difference between the main protection's operating time and the backup protection's operating time. It can be represented as:

[0147] ;

[0148] in A measure of the time difference in the protection margin data. This indicates the operating time of the backup protection under the equivalent short-circuit current capability condition. This indicates the operating time of the main protection under the equivalent short-circuit current capability condition. The protection margin data may optionally further include the corresponding equivalent grid parameters. Short-circuit support capability or In addition, time window identification information is used to form structured data records corresponding to the operating status during island operation, which, together with equivalent characteristic data, synchronization capability data, and energy storage life erosion, constitute the components of smart park power operation and maintenance assessment data.

[0149] S5. Using operational data and equivalent characteristic data, frequency domain analysis is performed on the power changes of the energy storage system during islanded operation. Stress indices characterizing high-frequency power support behavior are extracted, and the asymmetric erosion of energy storage lifetime caused by unplanned islanded operation is calculated.

[0150] Furthermore, in step S5, the step of performing frequency domain analysis on the power changes of the energy storage system during islanded operation includes:

[0151] Acquire power time-series data of the energy storage system during islanded operation;

[0152] The power time series data is segmented to form data segments for frequency domain analysis.

[0153] Perform frequency domain transformation on the data segment to obtain the corresponding power spectrum data;

[0154] Based on power spectrum data, frequency domain parameters characterizing the frequency distribution of power changes are extracted.

[0155] Furthermore, in step S5, the step of calculating the asymmetric erosion of energy storage lifetime caused by unplanned islanding operation includes:

[0156] Based on the frequency domain parameters obtained from frequency domain analysis, the power change characteristics of the corresponding energy storage system in the charging and discharging directions are extracted respectively.

[0157] The power variation characteristics in the charging and discharging directions are processed independently to obtain the corresponding energy stress parameters;

[0158] Based on the energy stress parameters and according to the preset erosion calculation relationship, the lifetime erosion of the energy storage system under unplanned islanded operation conditions is calculated, and the erosion corresponding to the charging direction and the discharging direction is distinguished to obtain the asymmetric erosion of the energy storage lifetime.

[0159] Specifically, step S5 is initiated after the completion of data collection and generation of equivalent characteristic data during islanded operation. The operational data includes power-related sampling information of the energy storage system during islanded operation. The equivalent characteristic data is used to characterize the control behavior characteristics of the power distribution system under islanded operation conditions and serves as the associated input for energy storage power change analysis. Step S5 forms frequency domain parameters by performing frequency domain analysis on the power change of the energy storage system, and extracts stress indicators characterizing high-frequency power support behavior based on these parameters. At the same time, it calculates energy stress parameters by combining the power change characteristics of the charging and discharging directions, and then forms lifetime erosion amount according to the preset erosion calculation relationship and obtains lifetime asymmetric erosion amount. The stress indicators and lifetime asymmetric erosion amount obtained in step S5 are output in the form of structured data and participate in the generation process of smart park power operation and maintenance assessment data.

[0160] When acquiring power time-series data of an energy storage system, the power sampling sequence at the energy storage system interface is extracted from the operational data. This power sampling sequence can be represented as... ,in Indicates the sampling time The power sampling value of the energy storage system, sampling time With sampling period satisfy , Indicates the start time of the isolated island's operation. Representing a non-negative integer index, the power sampling sequence can optionally be distinguished by positive or negative signs to indicate the charging and discharging direction, for example, by... Defined as the discharge direction, Defined as the charging direction, if the symbols are reversed on site, the corresponding symbols can also be used and the whole text can be kept consistent. The power sampling sequence can optionally record the corresponding energy storage system operation mode flag bit at the same time so as to identify the power limiting or control mode switching segment in subsequent processing.

[0161] When segmenting power time series data, it is done according to time windows. Slicing is performed to form data segments for frequency domain analysis, and the time window length can be optionally set to... There are sampling points and the corresponding time length is . Adjacent time windows may optionally overlap to improve the temporal resolution of frequency domain parameters; the overlap ratio may optionally be determined by the step size. Characterize and satisfy Thus forming the first Data fragments:

[0162] ;

[0163] in Indicates the segment number, Indicates the index of the sampling point within the fragment. Indicates the first The discrete power sequence of several data segments can be processed during segmentation, with optional mean-reduction or windowing applied to each segment to reduce frequency domain leakage. Mean-reduction can be achieved, for example, by... Implementation, in which This represents the average power of a segment, and windowing processing is used, for example, through... Implementation, in which Represents a sequence of window functions, optionally a Hanning window or a Hamming window;

[0164] When performing frequency domain transformation on data segments, a discrete Fourier transform is performed on each data segment to obtain power spectrum data. The discrete Fourier transform can be expressed as:

[0165] ;

[0166] in Indicates the first Data segments in the frequency index Complex spectrum value at that location, , The imaginary unit is used. Power spectrum data can be expressed either as an amplitude spectrum or a power spectral density. The amplitude spectrum can be represented as... The power spectrum can be expressed as Frequency index With actual frequency The correspondence can be expressed as:

[0167] ;

[0168] in Indicates the first The frequency value corresponding to each frequency point;

[0169] When extracting frequency domain parameters based on power spectrum data, a set of frequency domain parameters characterizing the frequency distribution of power changes is constructed. These parameters may optionally include high-frequency energy proportions, bandwidth energy integral values, or spectral peak positions. As one possible approach, high-frequency bandwidth boundaries are preset. With the highest analysis frequency ,in Indicates the starting frequency of the high-frequency band. Nyquist frequency can be used Or, based on the analysis requirements, to satisfy... The frequency point set is ,satisfy The frequency point set is Then the first High-frequency energy of each segment It can be represented as:

[0170] ;

[0171] No. The total energy of each segment It can be represented as:

[0172] ;

[0173] This yields the high-frequency energy percentage parameter:

[0174] ;

[0175] in Indicates the first One of the frequency domain parameters of each segment, which can optionally be associated with power control characteristic parameters in the equivalent characteristic data, to mark the correspondence between power changes and control behavior at the data level;

[0176] When extracting stress indices characterizing high-frequency power support behavior, frequency domain parameters are mapped to stress indices. These stress indices can optionally be defined using a high-frequency energy weighted form, for example, defining the first... Stress index of each segment for:

[0177] ;

[0178] in This indicates the numerical value of the stress index. This represents the frequency weighting coefficient, which optionally increases with increasing frequency to reflect the weighting differences of different frequency components. Optionally adopt Or other monotonic function forms, and remaining consistent with the definitions in the embodiments, the stress index can optionally be aggregated over time to obtain the overall stress level during islanded operation, for example, through:

[0179] ;

[0180] The summary stress index is obtained, among which Indicates the total number of segments;

[0181] When calculating the asymmetric erosion of energy storage lifetime caused by unplanned islanded operation, the power change characteristics in the charging and discharging directions are extracted based on frequency domain parameters and processed independently. The power sequence in the charging direction can be defined as:

[0182] ;

[0183] The discharge direction power sequence can be defined as:

[0184] ;

[0185] in This indicates the power component in the charging direction and is a non-positive value. This represents the power component in the discharge direction and is non-negative. During independent processing, the same segmented and frequency domain analysis process as described above can be optionally performed on the charging and discharging directions respectively, forming a frequency domain parameter set for the charging direction and a frequency domain parameter set for the discharging direction, and then calculating the energy stress parameters in the charging direction respectively. Energy stress parameters relative to the discharge direction The energy stress parameter can be optionally obtained by integrating or accumulating the stress index over time, for example:

[0186] ;

[0187] ;

[0188] in This represents the set of indices corresponding to the charging direction segment. This represents the set of indices corresponding to the discharge direction segment. Indicates the charging direction. The stress index of each segment Indicates the direction of discharge. The stress index of each segment, Represents the time weight of a single segment and optionally takes a step time. ;

[0189] When calculating lifetime erosion according to a preset erosion calculation relationship, the preset erosion calculation relationship is used to map energy stress parameters to lifetime erosion. The preset erosion calculation relationship can optionally be expressed in the form of a power function mapping, with lifetime erosion in the charging direction. It can be represented as

[0190] ;

[0191] Discharge direction lifetime erosion It can be represented as:

[0192] ;

[0193] in , Calculate the relationship parameters for erosion in the charging direction. The parameters for calculating erosion in the discharge direction can be obtained through experimental calibration or fitting of historical operating data and written into the configuration file during system deployment. The lifetime asymmetric erosion can be expressed as a combination of the lifetime erosion in the charging direction and the lifetime erosion in the discharging direction. For example, the lifetime asymmetric erosion can be defined. for:

[0194] ;

[0195] in The absolute difference characterization measure representing the amount of asymmetric erosion can also optionally be used. To preserve directional information and maintain consistent definitions in the embodiments, step S5 saves and outputs stress indicators, charging direction lifetime erosion, discharging direction lifetime erosion, and lifetime asymmetric erosion in a structured form, so as to form smart park power operation and maintenance assessment data together with synchronization capability data and protection margin data.

[0196] S6. Generate smart park power operation and maintenance assessment data based on synchronization capability data, protection margin data, and asymmetric erosion of energy storage life.

[0197] Specifically, step S6 is initiated after the generation of synchronization capability data, protection margin data, and asymmetric erosion of energy storage lifetime. As the generation link of operation and maintenance assessment data, step S6 performs unified access and consistency processing on the output data from different analysis links. The synchronization capability data comes from the dynamic modeling and inertia damping parameter inversion process and reflects the dynamic capability status of the distribution system under islanded operation conditions. The protection margin data comes from the calculation of equivalent grid parameters and short-circuit support capability and the coordination margin characterization quantity formed by combining the relationship of relay protection characteristics. The asymmetric erosion of energy storage lifetime comes from the mapping process of energy storage power frequency domain analysis and erosion calculation relationship and reflects the directional stress accumulation of the energy storage system during islanded operation. Step S6 associates the three types of data under the same islanded operation event identifier and forms a unified data object for smart park power operation and maintenance assessment data.

[0198] During the data access process, an event identifier is constructed for each unplanned isolated operation. The event identifier can optionally be encoded from information such as the islanding start time, the status change record of the grid-connected circuit breaker, and the park number. Subsequently, the synchronization capability data, protection margin data, and asymmetric erosion of the energy storage lifetime are written into the data buffer associated with the event identifier. The synchronization capability data can optionally include the equivalent inertia parameter. Equivalent damping parameters and the set of synchronization capability indicators derived therefrom, the protection margin data optionally including equivalent grid parameters. Short-circuit support capability or and compatibility margin The asymmetric erosion of energy storage lifetime may optionally include the erosion of lifetime in the charging direction. Discharge direction lifetime erosion amount and asymmetric erosion The meaning of the symbols for each data item should remain consistent with the aforementioned steps to ensure consistency in symbol definitions throughout the entire process;

[0199] During the consistency processing, time alignment and unit specifications for the three types of data are uniformly configured, with time alignment based on the start time of the isolated data. As a reference time zero point, the data records output from different steps are mapped to a unified time axis. The unit specification can optionally adopt a unified unit of measurement for basic quantities such as power, voltage, current, and frequency, and adopt a preset dimensional expression method for indicators derived from basic quantities. When there are missing or abnormal fields, a missing marker is used to mark them and the original record is retained. The missing marker can optionally be a null value marker or a preset invalid code to ensure that the generated evaluation data object can reflect the integrity of the data source link and meet the subsequent data consumer's needs for identifying abnormal situations.

[0200] When generating power operation and maintenance assessment data for smart parks, synchronization capacity data, protection margin data, and asymmetric erosion of energy storage lifetime are encapsulated according to a unified data structure. The data structure can optionally be expressed in the form of an object-oriented set of fields or a set of key-value pairs. The set of fields must include at least an event identifier. The starting point of the isolated island The field group includes a synchronization capability field group, a protection margin field group, and an energy storage erosion field group, wherein the synchronization capability field group optionally includes... Represents a set of synchronization capability indicators and can be derived from... and The combination relationship is calculated, and as one possible approach, the set of synchronization capability indicators can be defined as:

[0201] ;

[0202] in This indicates a positive infinitesimal that avoids a denominator of zero and can optionally be much smaller than 0. The numerical value, the protection margin field group optionally includes or The energy storage erosion field group may optionally include The above encapsulation process forms an evaluation data record corresponding to a single isolated event;

[0203] During the output and application of the assessment data, the assessment data is recorded and written to local storage or uploaded to the data service interface of the park operation and maintenance platform. The output format can be a structured file or a message queue data packet. The structured file includes, for example, JSON or tabular files, and the message queue data packet includes, for example, topic messages based on a publish-subscribe mechanism. After receiving the assessment data, the operation and maintenance platform can optionally associate and archive the assessment data with the park equipment ledger, relay protection setting sheet, and energy storage operation log, and realize historical event backtracking and data retrieval according to event identifiers. The assessment data can also optionally be used to trigger subsequent data analysis processes, such as data aggregation for generating operation and maintenance reports, threshold comparison for forming alarm rule inputs, or event archiving for forming operation and maintenance work orders. Step S6 realizes the unified organization and structured output of multi-source assessment results through the above operation process, thereby completing the generation process of smart park power operation and maintenance assessment data.

[0204] Example 2:

[0205] In scenarios where unplanned isolated operation occurs in smart parks, the operating status and control characteristics of distributed power sources and energy storage systems may undergo implicit changes. Existing operation and maintenance methods struggle to comprehensively assess system stability, synchronization capabilities, relay protection coordination, and energy storage operational stress based on actual operating data without conducting experiments or simulations. To address these issues, this invention provides a smart park power operation and maintenance assessment system, the structure of which is as follows: Figure 2 As shown. The specific implementation process of this system is as follows:

[0206] The data acquisition module is used to collect operational data during islanding operation after the power distribution system is detected to have switched from grid-connected state to unplanned islanding operation state.

[0207] The disturbance analysis module is used to filter the disturbance range of the operating data, establish a local relationship model between power change and system response, identify the equivalent control characteristic parameters of the power distribution system under islanded operation conditions, and generate equivalent characteristic data.

[0208] The dynamic modeling module is used to construct an equivalent dynamic model of the power distribution system using equivalent characteristic data and system dynamic response characteristics, invert the equivalent inertia parameters and damping parameters of the system, and obtain synchronization capability data accordingly.

[0209] The power grid support analysis module is used to combine equivalent characteristic data and synchronization capability data to calculate the equivalent power grid parameters and short-circuit support capability of the distribution system under islanded operation conditions, and substitute them into the existing relay protection characteristic relationship to obtain protection margin data.

[0210] The energy storage frequency domain analysis module is used to perform frequency domain analysis on the power changes of the energy storage system during islanded operation using operational data and equivalent characteristic data, extract stress indicators characterizing high-frequency power support behavior, and calculate the asymmetric erosion of energy storage lifetime caused by unplanned islanded operation.

[0211] The results generation module is used to generate smart park power operation and maintenance assessment data based on synchronization capability data, protection margin data, and asymmetric erosion of energy storage lifetime.

[0212] Specifically, during system operation, the data acquisition module is responsible for collecting and organizing the operation data of the park's power distribution system during islanded operation. The operation data is used to reflect the actual operation behavior of the power distribution system, distributed power sources and energy storage system in islanded operation state, and serves as a unified data source for subsequent analysis modules. The acquisition process is consistent with the method of acquiring operation data in the aforementioned method embodiment, and will not be elaborated here.

[0213] After the operational data acquisition is completed, the disturbance analysis module filters the natural disturbances during islanded operation based on the acquired operational data, and establishes a local relationship model between power change and system response within the effective disturbance range, thereby identifying the equivalent control characteristic parameters of the distribution system under islanded operation conditions. The equivalent control characteristic parameters are output in the form of equivalent characteristic data to provide input for subsequent dynamic analysis. This process corresponds to the aforementioned disturbance range screening and control characteristic identification steps, and will not be elaborated here.

[0214] After obtaining the equivalent characteristic data, the dynamic modeling module combines the system dynamic response characteristics extracted from the operating data to model and analyze the dynamic behavior of the power distribution system under islanded operation conditions. Based on the equivalent dynamic model, the equivalent inertia parameters and equivalent damping parameters of the system are inverted, thereby forming synchronization capability data to characterize the synchronization capability status of the system. This synchronization capability data is used to reflect the dynamic capability level of the system under the current islanded operation conditions.

[0215] After the synchronization capability data is generated, the power grid support analysis module receives the equivalent characteristic data and synchronization capability data, and calculates the equivalent power grid parameters and short-circuit support capability of the distribution system based on the voltage and current operating characteristics during islanded operation. The short-circuit support capability is then substituted into the existing relay protection characteristic relationship to obtain the corresponding protection margin data, which is used to characterize the changes in the relay protection coordination status under islanded operation conditions.

[0216] Meanwhile, the energy storage frequency domain analysis module processes the power changes of the energy storage system during islanded operation. By performing frequency domain analysis on the power time series, it extracts stress indicators related to high-frequency power support behavior and calculates the asymmetric erosion of energy storage lifetime caused by unplanned islanded operation. This analysis process corresponds to the aforementioned energy storage power frequency domain analysis and lifetime erosion calculation method.

[0217] After each module completes its corresponding data processing, the result generation module uniformly organizes and encapsulates the synchronization capability data, protection margin data, and asymmetric erosion of energy storage lifetime to form smart park power operation and maintenance assessment data corresponding to a single unplanned island operation event. The assessment data is then output to the park operation and maintenance system or energy management platform for subsequent operation recording, operation and maintenance analysis, or event backtracking, thereby completing the overall implementation process of the smart park power operation and maintenance assessment system.

[0218] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for assessing the operation and maintenance of power systems in a smart industrial park, characterized in that, Includes the following steps: S1. After detecting that the power distribution system has switched from grid-connected state to unplanned islanded operation state, collect operation data during the islanded operation period; S2. Screen the disturbance range of the operating data, establish a local relationship model between power change and system response, identify the equivalent control characteristic parameters of the power distribution system under islanded operation conditions, and generate equivalent characteristic data. S3. Construct an equivalent dynamic model of the power distribution system using equivalent characteristic data and system dynamic response characteristics, invert the equivalent inertia parameters and damping parameters of the system, and obtain synchronization capability data accordingly. S4. Combining equivalent characteristic data and synchronization capability data, calculate the equivalent grid parameters and short-circuit support capability of the distribution system under islanded operation conditions, and substitute them into the existing relay protection characteristic relationship to obtain protection margin data. S5. Using operational data and equivalent characteristic data, frequency domain analysis is performed on the power changes of the energy storage system during islanded operation. Stress indices characterizing high-frequency power support behavior are extracted, and the asymmetric erosion of energy storage lifetime caused by unplanned islanded operation is calculated. S6. Generate smart park power operation and maintenance assessment data based on synchronization capability data, protection margin data, and asymmetric erosion of energy storage life.

2. The smart park power operation and maintenance assessment method according to claim 1, characterized in that, In step S2, the step of filtering the perturbation range of the running data includes: Perform time-series traversal of the operating data to identify time periods in the operating data where the power change exceeds a preset disturbance threshold; The duration of the identified time period is determined, and time periods whose duration meets the preset time conditions are retained as candidate disturbance intervals. The candidate disturbance intervals are judged for consistency of operating status, and time periods with switching of operating mode or sudden change of control status are eliminated; The remaining time period is defined as the disturbance interval.

3. The method for assessing the operation and maintenance of power systems in a smart park according to claim 1, characterized in that, In step S2, the step of establishing a local relationship model between power change and system response includes: Within the disturbance range, the operating data is segmented and processed to extract the power change and system response within the corresponding time period; Pair power changes with system response quantities to construct a dataset describing the correspondence between power changes and system response; Based on the dataset, a local relationship model between power change and system response is established within the disturbance range.

4. The method for assessing the operation and maintenance of power systems in a smart park according to claim 1, characterized in that, In step S2, the step of identifying the equivalent control characteristic parameters of the power distribution system under islanded operation conditions and generating equivalent characteristic data includes: Based on the local relationship model, the power change and system response within the disturbance interval are subjected to parameter fitting to obtain model parameters characterizing the relationship between power change and system response; The model parameters are updated within a time window to obtain the control characteristic parameters corresponding to different disturbance ranges; The acquired control characteristic parameters are summarized and processed to form equivalent characteristic data that characterize the control characteristics of the power distribution system under islanded operation conditions.

5. The method for assessing the operation and maintenance of power systems in a smart park according to claim 1, characterized in that, In step S3, the step of constructing an equivalent dynamic model of the power distribution system using equivalent characteristic data and system dynamic response characteristics includes: Obtain the power change characteristic parameters corresponding to the equivalent characteristic data and the corresponding system dynamic response characteristic data; Based on power change characteristic parameters and system dynamic response characteristic data, state variables describing the dynamic behavior of the power distribution system are determined. Based on the changing relationships between state variables, an equivalent dynamic model is established to characterize the dynamic characteristics of the power distribution system under islanded operation conditions.

6. The method for assessing the operation and maintenance of power systems in a smart park according to claim 1, characterized in that, In step S3, the steps for retrieving the equivalent inertia parameters and damping parameters of the inverted system include: Based on the equivalent dynamic model, time series data corresponding to the dynamic response characteristics of the system during islanded operation are extracted; Parameter estimation processing is performed on the time series data to obtain candidate values ​​of inertia and damping parameters that match the equivalent dynamic model; Consistency verification is performed on the candidate values ​​of inertia parameter and damping parameter to determine the equivalent inertia parameter and equivalent damping parameter of the system.

7. The method for assessing the operation and maintenance of power systems in a smart park according to claim 1, characterized in that, In step S4, the step of calculating the equivalent grid parameters and short-circuit support capability of the power distribution system under islanded operation conditions includes: During islanded operation, parameters characterizing voltage and current variation features of the power distribution system are extracted based on operational data; Based on the voltage and current variation characteristics, calculate the equivalent grid parameters of the distribution system under islanded operation conditions; Based on equivalent grid parameters, the short-circuit support capacity corresponding to the operating state of the power distribution system is calculated.

8. The method for assessing the operation and maintenance of power systems in a smart park according to claim 1, characterized in that, In step S5, the step of performing frequency domain analysis on the power changes of the energy storage system during islanded operation includes: Acquire power time-series data of the energy storage system during islanded operation; The power time series data is segmented to form data segments for frequency domain analysis. Perform frequency domain transformation on the data segment to obtain the corresponding power spectrum data; Based on power spectrum data, frequency domain parameters characterizing the frequency distribution of power changes are extracted.

9. A smart park power operation and maintenance assessment method according to claim 1, characterized in that, In step S5, the step of calculating the asymmetric erosion of energy storage lifetime caused by unplanned islanding operation includes: Based on the frequency domain parameters obtained from frequency domain analysis, the power change characteristics of the corresponding energy storage system in the charging and discharging directions are extracted respectively. The power variation characteristics in the charging and discharging directions are processed independently to obtain the corresponding energy stress parameters; Based on the energy stress parameters and according to the preset erosion calculation relationship, the lifetime erosion of the energy storage system under unplanned islanded operation conditions is calculated, and the erosion corresponding to the charging direction and the discharging direction is distinguished to obtain the asymmetric erosion of the energy storage lifetime.

10. A smart park power operation and maintenance assessment system, characterized in that, The system for a smart park power operation and maintenance assessment method according to any one of claims 1-9 comprises: The data acquisition module is used to collect operational data during islanding operation after the power distribution system is detected to have switched from grid-connected state to unplanned islanding operation state. The disturbance analysis module is used to filter the disturbance range of the operating data, establish a local relationship model between power change and system response, identify the equivalent control characteristic parameters of the power distribution system under islanded operation conditions, and generate equivalent characteristic data. The dynamic modeling module is used to construct an equivalent dynamic model of the power distribution system using the equivalent characteristic data and the dynamic response characteristics of the system, invert the equivalent inertia parameters and damping parameters of the system, and obtain synchronization capability data accordingly. The power grid support analysis module is used to combine the equivalent characteristic data and synchronization capability data to calculate the equivalent power grid parameters and short-circuit support capability of the distribution system under islanded operation conditions, and substitute them into the existing relay protection characteristic relationship to obtain protection margin data. The energy storage frequency domain analysis module is used to perform frequency domain analysis on the power changes of the energy storage system during islanded operation using the operating data and equivalent characteristic data, extract stress indicators characterizing high-frequency power support behavior, and calculate the asymmetric erosion of energy storage lifetime caused by unplanned islanded operation. The result generation module is used to generate smart park power operation and maintenance assessment data based on the synchronization capability data, protection margin data, and energy storage lifetime asymmetric erosion.

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