A method for analyzing maintenance correlation considering equipment sensitivity

Abstract

The application discloses a kind of overhaul correlation analysis methods considering equipment sensitivity, the method obtains power grid operation mode, and with power grid network frame in power grid operation mode as model, operating state as measurement;Obtain power grid equipment overhaul plan, match the overhaul equipment with power grid network frame model, and update the overhaul equipment state to power grid operation mode, generate new overhaul operation mode;The operation mode of initial unstacked overhaul equipment state is defined as ground state, and the ground state is calculated The sensitivity relationship of all network equipment;Fault analysis is carried out on the newly generated overhaul operation mode, and the risk events under all overhaul modes are obtained;The overhaul equipment is associated with the risk events of all overhaul modes using the sensitivity relationship of all network equipment, and the overhaul correlation result is obtained.The application associates the risk events existing between the overhaul equipment and the equipment failure, to solve the possible defect problems in the original manual preparation of overhaul plan process.

Description

Technical Field

[0001] This invention relates to the field of smart grid operation technology, and more specifically to a maintenance correlation analysis method that takes into account equipment sensitivity. Background Technology

[0002] Currently, most maintenance plans in the power system's dispatching agencies are prepared manually. This involves using computers to implement the manual processes based on the actual dispatching work of the power grid company, essentially computerizing the existing manual planning steps. While this software provides computer support for maintenance planners and reduces their workload, it often fails to consider optimization. The resulting maintenance plans are merely feasible, not optimal or even superior. Therefore, to avoid these shortcomings in the maintenance plan preparation process, a correlation analysis of the maintenance plan and its consequences is necessary. Summary of the Invention

[0003] The purpose of this invention is to provide a maintenance correlation analysis method that takes into account equipment sensitivity, which can solve the problem that the manually prepared maintenance plan in the prior art is not optimized enough.

[0004] The objective of this invention is achieved through the following technical solution:

[0005] This invention provides a maintenance correlation analysis method considering equipment sensitivity, comprising the following steps:

[0006] The power grid operation mode is obtained, and the power grid structure in the power grid operation mode is used as a model, and the operation status is used as a measurement.

[0007] Obtain the power grid equipment maintenance plan, match the maintenance equipment with the power grid network model, update the status of the maintenance equipment to the power grid operation mode, and generate a new maintenance operation mode;

[0008] The initial operating mode without superimposed maintenance equipment state is defined as the ground state mode, and the sensitivity relationship of all network equipment is calculated based on the ground state mode;

[0009] Fault analysis is performed on the newly generated maintenance operation modes to obtain risk events under all maintenance modes;

[0010] By utilizing the sensitivity relationship of all network devices, the risk events of the equipment under maintenance are correlated with all maintenance methods to obtain maintenance correlation results.

[0011] Furthermore, updating the status of the equipment under maintenance to the power grid operation mode and generating a new maintenance operation mode includes updating the status of the equipment under maintenance to the power grid operation mode according to the set maintenance time, and generating a maintenance operation mode for each new maintenance time cycle of the power grid.

[0012] Furthermore, the fault analysis of the newly generated maintenance operation mode includes performing N-1 and N-2 fault scans on the new maintenance operation mode, and monitoring the load and load loss of all equipment after a fault.

[0013] Furthermore, the acquisition of the power grid equipment maintenance plan includes acquiring the type of equipment to be maintained, the start time of maintenance, and the end time of maintenance.

[0014] The beneficial effects of this invention are:

[0015] This invention addresses the shortcomings of manually prepared maintenance plans by correlating the sensitivity relationships between calculated devices with the risk events associated with device malfunctions. This improves the quality of maintenance plans. Furthermore, it solves the problem of numerous power grid risks and unclear relationships between risks and the devices being maintained due to a large number of devices requiring maintenance and unreasonable scheduling, thus enhancing the safety of equipment maintenance. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart illustrating the steps of a maintenance correlation analysis method that takes equipment sensitivity into account. Detailed Implementation

[0018] The embodiments of this disclosure will now be described in detail with reference to the accompanying drawings.

[0019] The following specific examples illustrate the implementation of this disclosure. Those skilled in the art can easily understand other advantages and effects of this disclosure from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. This disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this disclosure. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0020] Please see Figure 1This invention provides a maintenance correlation analysis method considering equipment sensitivity, comprising the following steps:

[0021] Step S1: Obtain the power grid operation mode, and use the power grid structure in the power grid operation mode as a model and the operation status as a measurement.

[0022] The BPA system provides information about the power grid's operation. The BPA system program is a crucial tool for power system analysis and calculation. Offline BPA systems expose data files in a special format (*.dat). Parsing these files according to a specified format allows for the acquisition of models from the BPA data. The acquired data includes load, generator output, and other data. Power flow calculations are then performed, and the power flow on each branch and the voltage on the bus can be extracted from the power flow calculation results file and converted into measurements for input.

[0023] Step S2: Obtain the power grid equipment maintenance plan, match the maintenance equipment with the power grid model, update the status of the maintenance equipment to the power grid operation mode, and generate a new maintenance operation mode.

[0024] The maintenance plan for power grid equipment is obtained from the OMS system, which is the power grid's outage management system. The maintenance plan includes information such as the equipment to be maintained, the start time, and the end time. The start and end times of maintenance for a single piece of equipment are defined as a maintenance time cycle, which can be set to one day or other time periods, depending on the maintenance needs of the equipment.

[0025] The equipment under maintenance is matched with the power grid equipment in the power grid model data obtained in step S1, and the equipment is set to maintenance status. The maintenance operation mode for each new maintenance time cycle is generated in chronological order according to the maintenance start time and maintenance end time of the equipment under maintenance.

[0026] Step S3: Define the initial operating mode without superimposed maintenance equipment state as the ground state mode, and calculate the sensitivity relationship of all network equipment for the ground state mode;

[0027] The initial operating mode is defined as the base state operating mode. Based on the base state operating mode, the entire network N-1 fault scan and power flow changes of all branches are calculated to obtain the device sensitivity relationships for all equipment:

[0028]

[0029] With P i Indicates the ground state power flow of branch i;

[0030] With P' i This represents the power flow of branch i after a fault in branch j;

[0031] P i This indicates that the power flow is interrupted due to a fault in branch j;

[0032] by This represents the sensitivity of branch j to branch i;

[0033] The sensitivity relationship between devices across the entire network is obtained by performing an N-1 fault scan across the entire network.

[0034] Step S4: Perform fault analysis on the newly generated maintenance operation mode to obtain the risk events under all maintenance modes;

[0035] Perform N-1 and N-2 fault scans on the newly generated maintenance operation mode and monitor the load status of all equipment after a fault. Define the overload of the equipment after a fault as a risk event and calculate the risk events under all maintenance modes. Based on the newly generated maintenance operation mode after superimposing the maintenance plan on the initial mode in step S3, calculate N-1 and N-2 fault scans, classify the load status of the equipment after a fault, and define the risk of overload as exceeding the limit according to whether the power flow of the equipment after a fault exceeds its own short-term current carrying capacity. If the limit is exceeded, it is ignored.

[0036] Step S5: Use the sensitivity relationship of all network devices to correlate the maintenance equipment with the risk events of all maintenance methods to obtain maintenance correlation results.

[0037] The calculated sensitivity relationships between devices link risk events under various maintenance methods to the devices under maintenance. Devices at risk of overload under each maintenance method are classified as either faulty or overloaded. Based on the devices under maintenance for each method, faulty or overloaded devices are located in the device sensitivity relationship data. Their sensitivity values ​​are then checked against a set threshold to determine if a risk event is related to the device under maintenance. Finally, a risk event-equipment relationship table is output, representing the correlation between risk events and maintenance equipment under each maintenance method.

[0038] It should be noted that N-1 and N-2 mentioned above refer to:

[0039] The N-1 operating mode means that if any independent component (generator, transmission line, transformer, etc.) among the N components of the power system fails and is disconnected, it should not cause power outages for users due to overload tripping of other lines, should not damage the stability of the system, and should not cause accidents such as voltage collapse.

[0040] The N-2 operating mode refers to the principle that if any two independent components (generators, transmission lines, transformers, etc.) among the N components of a power system fail and are disconnected, it should not cause power outages for users due to overload tripping of other lines, should not damage the stability of the system, and should not result in accidents such as voltage collapse.

[0041] Furthermore, in a preferred embodiment of this application, updating the status of the equipment under maintenance to the power grid operation mode and generating a new maintenance operation mode includes updating the status of the equipment under maintenance to the power grid operation mode according to the set maintenance time (as specified in the maintenance plan in the power outage management system), thereby generating a maintenance operation mode for each new maintenance time cycle of the power grid. The new maintenance time cycle is generally set to daily, but can be set weekly as needed; no specific limitation is made here.

[0042] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0043] The above description is merely illustrative of the embodiments of the present invention and is not intended to limit the present invention. For those skilled in the art, any modifications, equivalent substitutions, improvements, etc., made without creative effort within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A maintenance correlation analysis method considering equipment sensitivity, characterized in that, Includes the following steps: The power grid operation mode is obtained, and the power grid structure in the power grid operation mode is used as a model, and the operation status is used as a measurement. Obtain the power grid equipment maintenance plan, match the maintenance equipment with the power grid network model, update the status of the maintenance equipment to the power grid operation mode, and generate a new maintenance operation mode; The initial operating mode without superimposed maintenance equipment state is defined as the ground state mode, and the sensitivity relationship of all network equipment is calculated based on the ground state mode; Fault analysis is performed on the newly generated maintenance operation modes to obtain risk events under all maintenance modes; By leveraging the sensitivity relationships of all network devices, the risk events of the equipment under maintenance are correlated with those of all maintenance methods to obtain maintenance correlation results. This correlation includes: defining equipment at risk of overload under a given maintenance method as a risk event; the equipment at risk of overload includes faulty equipment and overloaded equipment; based on the equipment under maintenance in the maintenance method, searching for the sensitivity value corresponding to the faulty or overloaded equipment in the network device sensitivity relationship data; and determining whether the risk event is related to the equipment under maintenance based on whether the sensitivity value exceeds a set threshold. The fault analysis of the newly generated maintenance operation mode includes performing N-1 and N-2 fault scans on the new maintenance operation mode, and monitoring the load and load loss of all equipment after a fault.

2. The maintenance correlation analysis method considering equipment sensitivity according to claim 1, characterized in that, The step of updating the status of the equipment under maintenance to the power grid operation mode and generating a new maintenance operation mode includes updating the status of the equipment under maintenance to the power grid operation mode according to the set maintenance time, and generating a maintenance operation mode for each new maintenance time cycle of the power grid.

3. The maintenance correlation analysis method considering equipment sensitivity according to claim 1, characterized in that, The acquisition of the power grid equipment maintenance plan includes acquiring the types of equipment to be maintained, the start time of maintenance, and the end time of maintenance.

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