Lightweight multitask real-time scheduling method based on microcomputer

Abstract

The present application relates to the field of data analysis, especially to a kind of lightweight multitasking real-time scheduling method based on microcomputer, including, periodically according to task execution evaluation parameter determine whether scheduling optimization analysis is carried out for task processing process;According to data correlation radiation index and data analysis radiation index determine that radiation synergistic analysis or abnormal effective analysis is carried out for target execution task;Radiation synergistic analysis, determine the synergistic analysis combination of each one kind of execution task, whether initial evaluation priority coefficient is adjusted based on the initial difference parameter of synergistic analysis combination;Abnormal effective analysis, according to correlation reference priority difference index determine whether initial evaluation priority coefficient is adjusted;Execution target matching is carried out for each target execution task, the present application improves the execution arrangement of data processing task in actual operation process can effectively adapt to actual demand, and then the real-time performance and reliability of data processing process are improved.

Description

Technical Field

[0001] This invention relates to the field of data analysis, and in particular to a lightweight multi-task real-time scheduling method based on a microcomputer. Background Technology

[0002] Microcomputers, due to their cost and size advantages, are widely used in the acquisition and analysis of low-level data in power plants. Because the data involved is relatively abundant, it is necessary to set the execution priority for data transmission and processing tasks to ensure the real-time and reliable monitoring of power grid operating parameters. However, in actual operation, different operating conditions have different requirements for data acquisition and analysis. Simply relying on existing fixed priority execution strategies cannot effectively meet the needs of different operating conditions. Therefore, how to optimize the execution priority scheme of the data acquisition and analysis process in a targeted manner based on actual working processes to ensure overall task processing efficiency is a problem that urgently needs to be solved by those skilled in the art.

[0003] Chinese Patent Application Publication No. CN117950833A discloses a task scheduling method, apparatus, computer equipment, storage medium, and computer program product, relating to the field of power automation technology. The method includes: acquiring data analysis tasks published by a virtual power plant unit; matching at least two candidate servers corresponding to the task type of the data analysis task in an edge cluster; calculating the average resource utilization rate of available servers among the candidate servers based on a preset resource utilization rate calculation index; determining a target server among the available servers based on the average resource utilization rate, and assigning the data analysis task to the target server. Chinese Patent Publication No. CN109992388A discloses a multi-task management system for safety-grade equipment software in nuclear power plants, comprising: a time management unit to meet the needs of various application platforms, capable of measuring the running time of functional modules in the nuclear power plant safety-grade equipment software; a task management unit with a task creation interface, through which tasks can be added to the nuclear power plant safety-grade equipment software; a task scheduling unit for scheduling tasks in the nuclear power plant safety-grade equipment software, executing tasks sequentially according to their set priorities; and an exception handling unit for obtaining exception situations of tasks in the nuclear power plant safety-grade equipment software and providing exception handling methods for users to choose from based on the task exception situations. However, the above solution has the following drawbacks: it fails to effectively combine the actual power plant operating conditions to optimize the priority setting scheme for the task processing process in real time, resulting in the task execution arrangement failing to effectively meet the actual data processing needs, thereby affecting the real-time performance and reliability of the monitoring process of power system operating parameters. Summary of the Invention

[0004] To address this, the present invention provides a lightweight multi-task real-time scheduling method based on a microcomputer, which overcomes the problem in the prior art that fails to effectively combine the actual power plant operating conditions with the priority setting scheme for the task processing process for real-time optimization, resulting in the task execution arrangement failing to effectively meet the actual data processing needs, and thus affecting the real-time performance and reliability of the monitoring process of the power system's operating parameters.

[0005] To achieve the above objectives, the present invention provides a lightweight multi-task real-time scheduling method based on a microcomputer, comprising:

[0006] Periodically check the task execution evaluation parameters to determine whether scheduling optimization analysis should be performed on the task processing process;

[0007] During scheduling optimization analysis, the initial evaluation priority coefficient of each target execution task is determined based on the abnormal parameters of the task information, and the category of the target execution task is determined based on the data correlation radiation index and the data analysis radiation index, so as to determine whether to conduct radiation coordination analysis or abnormal effectiveness analysis for each target execution task.

[0008] During radiation synergy analysis, the synergy analysis combination for each type of execution task is determined based on the synergy demand index and the interaction coverage parameter or analysis coverage parameter. Based on the initial difference parameter of the synergy analysis combination, it is determined whether to adjust the initial evaluation priority coefficient for each type of execution task.

[0009] During the analysis of anomalies, the initial evaluation priority coefficient for each type II task is adjusted based on the correlation reference priority difference index.

[0010] Based on the initial assessment priority coefficients for completing the adjustment, each target execution task is executed, and the execution allocation for each target execution task is optimized. Based on the radiation effectiveness assessment parameters, the execution target matching for each target execution task is determined by either execution demand analysis or execution conflict analysis.

[0011] Furthermore, when the task execution evaluation parameters for the target evaluation period are greater than the preset task execution evaluation parameters, a scheduling optimization analysis is performed on the task processing process.

[0012] The initial evaluation priority coefficient is positively correlated with the abnormal parameters of the task information;

[0013] The target evaluation period is the execution evaluation period at the current moment.

[0014] Furthermore, the target execution task is categorized into two types: a first-class execution task and a second-class execution task.

[0015] The first type of execution task is a target execution task whose data association radiation index is greater than a preset data association radiation index or whose data analysis radiation index is greater than a preset data analysis index.

[0016] The second type of execution task is a target execution task in which the data association radiation index is less than or equal to the preset data association radiation index and the data analysis radiation index is less than or equal to the preset data analysis radiation index.

[0017] Furthermore, if the target execution task is of a certain type, then a radiation synergy analysis is performed on that target execution task;

[0018] The collaborative demand index is determined based on the data analysis radiation index and the radiation task interaction index, and the collaborative demand index is positively correlated with the data analysis radiation index and the radiation task interaction index, respectively.

[0019] Furthermore, if there exists a type of task whose collaborative demand index is greater than the preset collaborative demand index, then the collaborative analysis combination for that type of task is determined based on the interaction coverage parameters.

[0020] If there exists a type of task whose collaborative demand index is less than or equal to the preset collaborative demand index, then the collaborative analysis combination for that type of task is determined based on the analysis coverage parameters.

[0021] Furthermore, if the initial difference parameter of a collaborative analysis combination of a certain type of execution task is greater than the preset initial difference parameter, the initial evaluation priority coefficient for that type of execution task will be increased based on the dominant difference coefficient.

[0022] The increase in the initial assessment priority coefficient is positively correlated with the dominant difference coefficient.

[0023] Furthermore, if the target execution task is classified as a type II execution task, then an anomaly validity analysis is performed on that target execution task, whereby...

[0024] If the correlation reference priority difference index of two types of execution tasks is greater than the preset correlation reference priority difference index, the initial evaluation priority coefficient of the two types of execution tasks will be reduced according to the correlation reference priority difference index.

[0025] The decrease in the initial assessment priority coefficient is negatively correlated with the associated reference priority difference index.

[0026] Furthermore, if the radiation effectiveness assessment parameter of a target execution task is greater than the preset radiation effectiveness assessment parameter, then execution requirement analysis is used to match the execution target for that target execution task.

[0027] Target matching is performed to determine whether to execute a task targeting a specific target based on the radiation priority difference index.

[0028] The radiation effectiveness assessment parameters are determined based on data analysis of the radiation index and a reference radiation priority index.

[0029] Furthermore, if the radiation priority difference index of the target execution task is greater than the preset radiation priority difference index, the execution allocation device for the target execution task is determined according to the radiation distribution ratio index of each device to be allocated.

[0030] Furthermore, if the radiation effectiveness assessment parameter of a target execution task is less than or equal to the preset radiation effectiveness assessment parameter, then execution conflict analysis is used to match execution targets for each target execution task.

[0031] Determine whether to perform execution target matching for this target based on the predicted execution conflict index of the existing allocation equipment;

[0032] If the predicted execution conflict index is greater than the preset predicted execution conflict index, then the execution allocation device for the target execution task is determined according to the predicted execution conflict index of each device to be matched.

[0033] Compared with the prior art, the beneficial effects of the present invention are that the technical solution of the present invention determines whether to perform scheduling optimization analysis on the task processing process based on task execution evaluation parameters. The task execution evaluation parameters characterize the adaptability of the priority scheme of task execution based on the recent stage to the current stage of the electrical system monitoring process. In the case of poor adaptability, the present invention determines the specific optimization method of the priority execution scheme of task execution according to the actual situation of different target task execution. The present invention optimizes the priority scheme of task execution in a timely manner to meet the actual data processing needs and ensure the real-time performance and reliability of the monitoring process of the power system operating parameters.

[0034] Furthermore, in this invention, the category of the target execution task is determined based on the data association radiation index and the data analysis radiation index. Based on the category of the target execution task, it is determined whether to perform radiation synergy analysis or abnormal effectiveness analysis on the target execution task. The data association radiation index and the data analysis radiation index characterize the degree of influence of the processing status of other target execution tasks on the processing status of the target execution task, as well as the degree of influence on the processing status of other target execution tasks. In this way, the initial evaluation priority coefficient is adjusted in a targeted manner, so that the actual scheduling optimization analysis process can conform to the actual situation. This invention ensures the effectiveness of the optimization results of the priority execution scheme.

[0035] Furthermore, in this invention, the collaborative analysis combination of each type of execution task is determined based on the collaborative demand index, interaction coverage parameters, or analysis coverage parameters. The initial difference parameters of the collaborative analysis combination determine whether to adjust the initial evaluation priority coefficient for each type of execution task. Since the processing of one type of execution task is significantly affected by the processing of other target execution tasks, it is necessary to optimize the initial evaluation priority coefficient of the one type of execution task in conjunction with the analysis requirements of the target execution tasks within the collaborative analysis combination. In the actual data processing task execution process, the high coupling between some tasks is considered, further ensuring the smoothness of the task execution arrangement.

[0036] Furthermore, in this invention, the execution target matching for each target execution task is determined based on the radiation effectiveness assessment parameters, and the execution demand analysis or execution conflict analysis is used. The radiation effectiveness assessment parameters characterize the demand of the processing process of the target execution task on the processing results of other target execution tasks. Based on this, a targeted matching method is made for the equipment that executes the target execution task, so as to ensure the smoothness of the overall data processing process for the equipment arrangement scheme for executing each target execution task. Attached Figure Description

[0037] Figure 1 This is a schematic diagram of the lightweight multi-task real-time scheduling method based on a microcomputer according to the present invention.

[0038] Figure 2 This is a flowchart illustrating the present invention for determining whether to perform scheduling optimization analysis on the task processing process based on task execution evaluation parameters.

[0039] Figure 3 This is a flowchart illustrating how the present invention determines the category of a target task based on data-related radiation indices and data-analyzed radiation indices.

[0040] Figure 4 This is a flowchart illustrating the process of matching execution targets for each objective task based on radiation effectiveness assessment parameters, using either execution requirement analysis or execution conflict analysis. Detailed Implementation

[0041] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0042] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0043] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0044] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0045] Please see Figures 1 to 4 As shown, this invention provides a lightweight multi-task real-time scheduling method based on a microcomputer, comprising:

[0046] S1 periodically checks the task execution evaluation parameters to determine whether to perform scheduling optimization analysis on the task processing process;

[0047] S2, During scheduling optimization analysis, the initial evaluation priority coefficient of each target execution task is determined based on the abnormal parameters of the task information, and the category of the target execution task is determined based on the data correlation radiation index and the data analysis radiation index, so as to determine whether to conduct radiation coordination analysis or abnormal effectiveness analysis for each target execution task.

[0048] S3, During radiation synergy analysis, the synergy analysis combination for each type of execution task is determined based on the synergy demand index and the interaction coverage parameter or analysis coverage parameter. Based on the initial difference parameter of the synergy analysis combination, it is determined whether to adjust the initial evaluation priority coefficient for each type of execution task.

[0049] S4, During the analysis of abnormal validity, determine whether to adjust the initial evaluation priority coefficient for each type II task based on the correlation reference priority difference index;

[0050] S5, based on the initial evaluation priority coefficients of the completed adjustment, execute each target execution task, and optimize the execution allocation for each target execution task. Based on the radiation effective evaluation parameters, determine whether to use execution demand analysis or execution conflict analysis to match the execution targets for each target execution task.

[0051] This invention optimizes the priority arrangement of transmission and analysis tasks for power system operation data. The monitored power system is designated as the target analysis system. The target analysis system comprises several task processing devices and several electrical devices. The task processing devices are microcomputers used to perform data transmission and analysis tasks. Transmission or processing tasks of any type of power system operation monitoring data are designated as target execution tasks. The target execution tasks include, but are not limited to: transmission of current and voltage values ​​acquired at different monitoring locations and at different times, frequency measurement tasks, frequency deviation calculation tasks, phase voltage calculation tasks, and power factor angle calculation tasks. The types of operation monitoring data include, but are not limited to, current and voltage values.

[0052] This invention utilizes several priority decision records. Each priority decision record contains at least one optimization process for prioritizing data processing tasks during the power system operation monitoring phase, including task execution evaluation parameters, data correlation radiation index, data analysis radiation index, collaborative demand index, interaction coverage parameters, analysis coverage parameters, initial difference parameters, correlation reference priority difference index, radiation effectiveness evaluation parameters, radiation priority difference index, and predicted execution conflict index. Each priority decision record also has a corresponding qualification mark, which records whether the timeliness and reliability of the data processing task execution arrangement during the power system operation monitoring process meet user requirements.

[0053] Specifically, when the task execution evaluation parameters for the target evaluation period are greater than the preset task execution evaluation parameters, a scheduling optimization analysis is performed on the task processing process.

[0054] The initial evaluation priority coefficient is positively correlated with the abnormal parameters of the task information;

[0055] The target evaluation period is the execution evaluation period at the current moment.

[0056] In this invention, an execution evaluation cycle is applied. The duration of the execution evaluation cycle can be determined by the user. The higher the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process, the shorter the execution evaluation cycle. An execution evaluation cycle of 10 minutes is provided. At the start time of each execution evaluation cycle, the task execution evaluation parameters are detected.

[0057] If the current time is the start time of an execution evaluation cycle, the task execution evaluation parameters are detected, and this execution evaluation cycle is recorded as the target evaluation cycle. For a single execution evaluation cycle, the task execution evaluation parameters... , Here, n represents the task execution parameters of the previous execution evaluation cycle, and n is the number of execution evaluation cycles within the execution evaluation phase. The execution evaluation phase is the i-th execution evaluation period excluding the previous execution evaluation period within the current execution evaluation phase. The end time of the execution evaluation phase is the end time of the previous execution evaluation period. The duration of the execution evaluation phase can be set by the user according to the actual work scenario. One possible value for the duration of the execution evaluation phase is 10 times the duration of the execution evaluation period. The task execution parameter is the maximum value of the execution waiting time of the target execution tasks generated within the execution evaluation period. For a single target execution task, the execution waiting time is the interval between the generation time of the target execution task and its execution start time.

[0058] For a single target execution task, the task information anomaly parameter is calculated as the absolute value of the difference between the value of the operation monitoring data corresponding to the target execution task and the baseline value corresponding to the operation monitoring data, divided by the baseline value corresponding to the operation monitoring data. The value of the preset task execution evaluation parameter can be determined by the user based on the actual work scenario. For example, the user can set it based on the priority decision record. The higher the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the operation monitoring process of the power system, the smaller the value of the preset task execution evaluation parameter. A method for determining the value of the preset task execution evaluation parameter is provided, which is the minimum value of the task execution evaluation parameter in the execution evaluation cycle of the task processing process scheduling optimization analysis in the priority decision record that meets the timeliness and reliability requirements of the execution arrangement of data processing tasks in the operation monitoring process of the power system.

[0059] Specifically, the target execution task is categorized into two types: Type I execution task and Type II execution task.

[0060] The first type of execution task is a target execution task whose data association radiation index is greater than a preset data association radiation index or whose data analysis radiation index is greater than a preset data analysis index.

[0061] The second type of execution task is a target execution task in which the data association radiation index is less than or equal to the preset data association radiation index and the data analysis radiation index is less than or equal to the preset data analysis radiation index.

[0062] In this invention, a cyclic task evaluation cycle is applied. The duration of the task evaluation cycle can be determined by the user. The higher the user's requirements for the timeliness and reliability of the execution of data processing tasks in the power system operation monitoring process, the shorter the duration of the task evaluation cycle. A task evaluation cycle duration of 5 seconds is provided. At the end of each task evaluation cycle, the category of the target execution task generated within the corresponding task evaluation cycle is analyzed.

[0063] For a single target execution task, the data association radiation index = the number of electrical devices electrically connected to the monitoring location corresponding to the target execution task / the number of electrical devices within the target analysis system. The data analysis radiation index = the number of radiation execution tasks existing within the target execution task / the number of target execution tasks existing in the current task evaluation cycle. Target execution tasks that take the processing output of the target execution task as input are recorded as radiation execution tasks of the target execution task. The values ​​of the preset data association radiation index and the preset data analysis radiation index can be determined by the user according to the actual working scenario. For example, the user can set them according to priority decision records. The user's data processing tasks during the power system operation monitoring process... The higher the requirements for the timeliness and reliability of the execution arrangements of tasks, the smaller the value of the preset data correlation radiation index and the smaller the value of the preset data analysis radiation index. A method for determining the preset data correlation radiation index is provided, in which the maximum value of the data correlation radiation index of the two types of execution tasks in the priority decision record that meets the timeliness and reliability requirements of the execution arrangements of data processing tasks in the power system operation monitoring process is recorded as the preset data correlation radiation index. Similarly, a method for determining the preset data analysis radiation index is provided, in which the maximum value of the data analysis radiation index of the two types of execution tasks in the priority decision record that meets the timeliness and reliability requirements of the user's execution arrangements of data processing tasks in the power system operation monitoring process is recorded as the preset data analysis radiation index.

[0064] Specifically, if a target execution task is classified as a type of execution task, then a radiation-coordination analysis is performed on that target execution task.

[0065] The collaborative demand index is determined based on the data analysis radiation index and the radiation task interaction index, and the collaborative demand index is positively correlated with the data analysis radiation index and the radiation task interaction index, respectively.

[0066] For a single type of execution task, the collaborative demand index is the sum of the data analysis radiation index and the radiation task interaction index of that type of execution task. The radiation task interaction index is the maximum value of the task interaction index between that type of execution task and each of its radiation execution tasks. For any two target execution tasks, the task interaction index is equal to the number of radiation execution tasks that the two target execution tasks share, divided by the number of target execution tasks in the current task evaluation period.

[0067] The value of the preset collaborative demand index can be determined by the user according to the actual working scenario. For example, the user can set it according to the priority decision record. A method for determining the value of the preset collaborative demand index is provided, in which the priority decision record for determining the collaborative analysis combination according to the interaction coverage parameter is recorded as the combination reference record, and the minimum value of the collaborative demand index in the combination reference record that meets the user's timeliness and reliability requirements for the execution arrangement of data processing tasks in the power system operation monitoring process is recorded as the preset collaborative demand index.

[0068] Specifically, if there is a type of task whose collaborative demand index is greater than the preset collaborative demand index, then the collaborative analysis combination of that type of task is determined based on the interaction coverage parameters.

[0069] If there exists a type of task whose collaborative demand index is less than or equal to the preset collaborative demand index, then the collaborative analysis combination for that type of task is determined based on the analysis coverage parameters.

[0070] Specifically, for a single type of execution task, if the collaborative demand index of that type of execution task is greater than the preset collaborative demand index, it indicates that there are many other target execution tasks affected by that type of execution task. Therefore, a collaborative analysis combination is determined based on the interaction coverage parameter to ensure that the subsequent adjustment process of the initial evaluation priority coefficient based on the collaborative analysis combination takes into account the strong coupling between other tasks in the execution order. The interaction coverage parameter of the determined collaborative analysis combination is greater than the preset interaction coverage parameter. The interaction coverage parameter = the number of radiating execution tasks that coexist with each target execution task and that type of execution task within the collaborative analysis combination / the number of radiating execution tasks that exist in that type of execution task.

[0071] The value of the preset interactive coverage parameter can be determined by the user according to the actual working scenario. For example, the user can set it according to the priority decision record. The higher the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process, the larger the value of the preset interactive coverage parameter. A method for determining the value of the preset interactive coverage parameter is provided, which is the minimum value of the interactive coverage parameter of the collaborative analysis combination in the combined reference record that meets the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process.

[0072] For a single type of execution task, if the collaboration demand index of that type of execution task is less than or equal to the preset collaboration demand index, it indicates that there are other target execution tasks that are less affected by that type of execution task. Therefore, a collaboration analysis combination is determined based on the analysis coverage parameter to ensure that the strong coupling between that type of execution task and other target execution tasks is taken into account during the subsequent adjustment of the initial evaluation priority coefficient based on the collaboration analysis combination. The analysis coverage parameter of the determined collaboration analysis combination is greater than the preset analysis coverage parameter. The analysis coverage parameter = the number of target execution tasks in the collaboration analysis combination that use that type of execution task as a radiating execution task / the number of associated execution tasks with that type of execution task.

[0073] The value of the preset analysis coverage parameter can be determined by the user according to the actual working scenario. For example, the user can set it according to the priority decision record. The higher the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process, the larger the value of the preset interactive coverage parameter. A method for determining the value of the preset analysis coverage parameter is provided, in which the priority decision record of the collaborative analysis combination determined according to the analysis coverage parameter is recorded as the collaborative reference record, and the minimum value of the analysis coverage parameter of the collaborative analysis combination in the collaborative reference record that meets the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process is recorded as the preset analysis coverage parameter.

[0074] Specifically, if the initial difference parameter of a collaborative analysis combination of a certain type of execution task is greater than the preset initial difference parameter, the initial evaluation priority coefficient for that type of execution task will be increased based on the dominant difference coefficient.

[0075] The increase in the initial assessment priority coefficient is positively correlated with the absolute value of the dominant difference coefficient.

[0076] Specifically, for a single type of execution task, the initial difference parameter is the average of the differences between the initial evaluation priority coefficients of each target execution task within the collaborative analysis group of that type of execution task and the initial evaluation priority coefficient of that type of execution task. The dominant difference coefficient is the difference between the initial evaluation priority coefficient of the dominant reference execution task and the initial evaluation priority coefficient of that type of execution task. The dominant reference execution task is the target execution task with the largest number of associated execution tasks within the collaborative analysis group. For a single target execution task, the radiating execution tasks of that target execution task and the target execution tasks that use that target execution task as radiating execution tasks are recorded as the associated execution tasks of that target execution task.

[0077] If the initial difference parameter of the collaborative analysis combination determined by a certain type of execution task is greater than the preset initial difference parameter, it indicates that there is a significant difference between the priority processing of this type of execution task and the target execution task with which it has a strong coupling relationship. It is necessary to adjust the initial evaluation priority coefficient according to the difference to avoid the strong coupling between the target execution tasks affecting the task execution efficiency. The value of the preset initial difference parameter can be determined by the user according to the actual working scenario. For example, the user can set it according to the priority decision record. The higher the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process, the smaller the value of the preset initial difference parameter. A method for determining the value of the preset initial difference parameter is provided, which is the average value of the initial difference parameter of the collaborative analysis combination of a certain type of execution task that meets the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process, and is recorded as the preset initial difference parameter.

[0078] Specifically, if the target execution task is classified as a type II execution task, then an anomaly analysis is performed on that target execution task.

[0079] If the correlation reference priority difference index of two types of execution tasks is less than or equal to the preset correlation reference priority difference index, the initial evaluation priority coefficient of the two types of execution tasks will be reduced according to the correlation reference priority difference index.

[0080] The decrease in the initial assessment priority coefficient is negatively correlated with the associated reference priority difference index.

[0081] Specifically, for a single Category II execution task, since the processing of Category II execution tasks is less affected by the processing status of other target execution tasks and has a relatively small impact on the processing status of other target execution tasks, an anomaly validity analysis is performed on the target execution task to determine whether the anomaly corresponding to the target execution task is reliable. The correlation reference priority difference index is calculated as: standard deviation of the initial evaluation priority coefficient of each electrical correlation task of the Category II execution task / average value of the initial evaluation priority coefficient of each electrical correlation task of the Category II execution task. The electrical correlation task refers to the target execution task that is electrically connected to the monitoring location corresponding to the Category II execution task.

[0082] The value of the preset associated reference priority difference index can be determined by the user according to the actual working scenario. For example, the user can set it according to the priority decision record. The higher the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process, the smaller the value of the preset associated reference priority difference index. A method for determining the value of the preset associated reference priority difference index is provided, which is the minimum value of the associated reference priority difference index of the two types of execution tasks adjusted for the initial evaluation priority coefficient in the priority decision record that meets the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process.

[0083] Specifically, if the radiation effectiveness assessment parameter of a target execution task is greater than the preset radiation effectiveness assessment parameter, then execution requirement analysis is used to match the execution target for that target execution task.

[0084] Target matching is performed to determine whether to execute a task targeting a specific target based on the radiation priority difference index.

[0085] The radiation effectiveness assessment parameters are determined based on data analysis of the radiation index and a reference radiation priority index.

[0086] Specifically, for a single target execution task, the radiation effective assessment parameter = the number of radiation execution tasks existing for the target execution task / the number of associated execution tasks existing for the target execution task. The radiation priority difference index is the minimum value of the difference between the initial assessment priority coefficient of the target execution task and the initial assessment priority coefficients of each of its radiation execution tasks. For a single target execution task, if the radiation effective assessment parameter of the target execution task is greater than the preset radiation effective assessment parameter, it indicates that the processing of the target execution task has a heavy demand for the processing results of other target execution tasks. In this case, execution demand analysis is used to match execution targets. The radiation priority difference index is used to determine whether there is a certain amount of time to redetermine the execution allocation device for the target execution task and complete the transfer and transmission of the target execution task. This is to determine whether to match execution targets for the target execution task and avoid interfering with the completion of other target execution tasks due to the redetermination of execution target matching for the target execution task.

[0087] The value of the preset radiation effectiveness assessment parameter can be determined by the user according to the actual working scenario. For example, the user can set it according to the priority decision record. The higher the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process, the smaller the value of the preset radiation effectiveness assessment parameter. A method for determining the value of the preset radiation effectiveness assessment parameter is provided, in which the priority decision record for matching the execution target of the target execution task using execution demand analysis is recorded as the matching reference record, and the minimum value of the radiation effectiveness assessment parameter in the matching reference record that meets the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process is recorded as the preset radiation effectiveness assessment parameter.

[0088] Specifically, if the radiation priority difference index of the target execution task is greater than the preset radiation priority difference index, the execution allocation device for the target execution task is determined according to the radiation distribution ratio index of each device to be allocated.

[0089] Specifically, for a single target execution task, if the radiation priority difference index of the target execution task is greater than the preset radiation priority difference index, it indicates that there is a certain difference between the initial evaluation priority coefficient of the target execution task and its radiation execution task. A certain amount of time is reserved for re-determining the execution allocation equipment for the target execution task and completing the transfer and transmission of the target execution task. Therefore, based on the radiation distribution ratio index, the equipment to be allocated for the radiation execution task of the target execution task is re-determined, saving time resources required for the transmission or retrieval of the output content of the analysis completed by the target execution task in subsequent stages. The value of the preset radiation priority difference index can be determined by the user according to the actual working scenario. For example, the user can set it according to the priority decision record. The higher the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process, the smaller the value of the preset radiation priority difference index. A method for determining the value of the preset radiation priority difference index is provided, which is the average value of the radiation priority difference index of the target execution task whose execution allocation equipment is determined based on the radiation distribution ratio index in the priority decision record that meets the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process.

[0090] For a single device to be assigned, the radiation distribution ratio index = the number of associated execution tasks of the target execution task that the device to be assigned needs to complete / the number of target processing tasks that the device to be assigned needs to complete. The device to be assigned with the largest radiation distribution ratio index is recorded as the execution allocation device for the target execution task.

[0091] Specifically, if the radiation effectiveness assessment parameter of a target execution task is less than or equal to the preset radiation effectiveness assessment parameter, then execution conflict analysis is used to match execution targets for each target execution task.

[0092] Determine whether to perform execution target matching for the target execution task based on the predicted execution conflict index of the existing allocation equipment for the target execution task;

[0093] If the predicted execution conflict index is greater than the preset predicted execution conflict index, then the execution allocation device for the target execution task is determined according to the predicted execution conflict index of each device to be matched.

[0094] Specifically, for a single target execution task, if the radiation effective assessment parameter of the target execution task is less than or equal to the preset radiation effective assessment parameter, it indicates that the demand for the processing results of other target execution tasks during the processing of the target execution task is relatively light. Execution conflict analysis is used to match execution targets for each target execution task to determine whether the existing allocation device for the target execution task has a high risk of being allocated to other target execution tasks. The existing allocation device is the task processing device currently executing the target execution task. For a single task processing device, the predicted execution conflict index of the task processing device for the target execution task is = the number of one type of execution task among the target processing tasks that the task processing device needs to complete / the number of target processing tasks that the task processing device needs to complete.

[0095] For a target execution task whose single radiation effective assessment parameter is less than or equal to the preset radiation effective assessment parameter, if the predicted execution conflict index of the existing allocation device is greater than the preset predicted execution conflict index, it indicates that the existing allocation device has a high risk of acquiring new target execution tasks in the future. Therefore, the target execution task that is less affected by interference from other target execution tasks is reallocated. The matching device is the task processing device other than the existing allocation device. The matching device with the smallest predicted execution conflict index is recorded as the execution allocation device for the target execution task.

[0096] The value of the preset predicted execution conflict index can be determined by the user based on the actual working scenario. For example, the user can set it based on the priority decision record. The higher the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process, the smaller the value of the preset predicted execution conflict index. A method for determining the value of the preset predicted execution conflict index is provided, which records the priority decision record of the execution allocation device for the target execution task based on the predicted execution conflict index of each device to be matched as the prediction reference record, and records the minimum value of the predicted execution conflict index in the prediction reference record that meets the user's requirements for the timeliness and reliability of the execution arrangement of data processing tasks in the power system operation monitoring process as the preset predicted execution conflict index.

[0097] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0098] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A lightweight multi-task real-time scheduling method based on a microcomputer, characterized in that, include: Periodically check the task execution evaluation parameters to determine whether scheduling optimization analysis should be performed on the task processing process; During scheduling optimization analysis, the initial evaluation priority coefficient of each target execution task is determined based on the abnormal parameters of the task information. The transmission or processing task of any type of power system operation monitoring data is recorded as a target execution task. Target execution tasks include first-class execution tasks and second-class execution tasks. For a single target execution task, the data association radiation index = the number of electrical devices with electrical connections to the monitoring location corresponding to the target execution task / the number of electrical devices in the target analysis system; the data analysis radiation index = the number of radiation execution tasks present in the target execution task / the number of target execution tasks present in the current task evaluation cycle. One type of execution task is a target execution task where the data association radiation index is greater than the preset data association radiation index or the data analysis radiation index is greater than the preset data analysis index. The second type of execution task is a target execution task where the data association radiation index is less than or equal to the preset data association radiation index and the data analysis radiation index is less than or equal to the preset data analysis index. If there is a target execution task that is a type of execution task, then a radiation collaboration analysis is performed on the target execution task. If the collaboration demand index of a type of execution task is greater than the preset collaboration demand index, the collaboration analysis combination of that type of execution task is determined according to the interaction coverage parameter. Conversely, the collaboration analysis combination of that type of execution task is determined according to the analysis coverage parameter, and the initial evaluation priority coefficient of each type of execution task is adjusted based on the initial difference parameter of the collaboration analysis combination. For a single type of execution task, the collaborative demand index is the sum of the data analysis radiation index and the radiation task interaction index of that type of execution task. The radiation task interaction index is the maximum value of the task interaction index between that type of execution task and each of its radiation execution tasks. The interaction coverage parameter is the number of radiation execution tasks that coexist with each target execution task and that type of execution task within the collaborative analysis combination / the number of radiation execution tasks that exist for that type of execution task. The analysis coverage parameter is the number of target execution tasks within the collaborative analysis combination that use that type of execution task as a radiation execution task / the number of associated execution tasks that exist with that type of execution task. The radiation execution tasks of that target execution task and the target execution tasks that use that target execution task as a radiation execution task are recorded as the associated execution tasks of that target execution task. If there is a target execution task that is a type II execution task, then perform an abnormal effectiveness analysis on the target execution task and determine whether to adjust the initial evaluation priority coefficient for each type II execution task based on the correlation reference priority difference index. Based on the initial assessment priority coefficients for completing the adjustment, each target execution task is executed, and the execution allocation for each target execution task is optimized. Based on the radiation effectiveness assessment parameters, the execution target matching for each target execution task is determined by either execution demand analysis or execution conflict analysis.

2. The lightweight multi-task real-time scheduling method based on a microcomputer according to claim 1, characterized in that, When the task execution evaluation parameters for the target evaluation period are greater than the preset task execution evaluation parameters, a scheduling optimization analysis is performed on the task processing process. The initial evaluation priority coefficient is positively correlated with the abnormal parameters of the task information; The target evaluation period is the execution evaluation period at the current moment; For a single execution evaluation cycle, the task execution evaluation parameters , These are the task execution parameters from the previous execution evaluation cycle. The number of assessment cycles performed within the assessment phase. For the i-th execution evaluation period excluding the previous execution evaluation period within the execution evaluation phase, the task execution parameter is the maximum value of the execution waiting time of the target execution task generated within the execution evaluation period. For a single target execution task, the execution waiting time is the interval between the generation time of the target execution task and its execution start time. The task information anomaly parameter = the absolute value of the difference between the value of the operation monitoring data corresponding to the target execution task and the baseline value corresponding to the operation monitoring data / the baseline value corresponding to the operation monitoring data. The content corresponding to the target execution task includes the transmission of current and voltage values ​​acquired at different monitoring locations and at different times, frequency measurement tasks, frequency deviation calculation tasks, phase voltage calculation tasks, and power factor angle calculation tasks. The categories of operation monitoring data include current values ​​and voltage values.

3. The lightweight multi-task real-time scheduling method based on a microcomputer according to claim 1, characterized in that, If the initial difference parameter of a collaborative analysis combination of a certain type of task is greater than the preset initial difference parameter, the initial evaluation priority coefficient for that type of task will be increased based on the dominant difference coefficient. The increase in the initial assessment priority coefficient is positively correlated with the dominant difference coefficient; For a single type of execution task, the initial difference parameter is the average of the differences between the initial evaluation priority coefficients of each target execution task in the collaborative analysis group of that type of execution task and the initial evaluation priority coefficients of that type of execution task. The dominant difference coefficient is the difference between the initial evaluation priority coefficient of the dominant reference execution task and the initial evaluation priority coefficients of that type of execution task. The dominant reference execution task is the target execution task with the largest number of associated execution tasks in the collaborative analysis group.

4. The lightweight multi-task real-time scheduling method based on a microcomputer according to claim 1, characterized in that, If the correlation reference priority difference index of two types of execution tasks is greater than the preset correlation reference priority difference index, the initial evaluation priority coefficient of the two types of execution tasks will be reduced according to the correlation reference priority difference index. The decrease in the initial assessment priority coefficient is negatively correlated with the associated reference priority difference index; The correlation reference priority difference index = the standard deviation of the initial evaluation priority coefficient of each electrical correlation task in the two types of execution tasks / the average of the initial evaluation priority coefficients of each electrical correlation task in the two types of execution tasks. The electrical correlation task is the target execution task of electrical equipment that is electrically connected to the monitoring location corresponding to the two types of execution tasks.

5. The lightweight multi-task real-time scheduling method based on a microcomputer according to claim 1, characterized in that, If the radiation effectiveness assessment parameter of a target execution task is greater than the preset radiation effectiveness assessment parameter, then execution requirement analysis is used to match the execution target for that target execution task. The radiation priority difference index is used to determine whether to perform a task for the target and to perform target matching. The radiation priority difference index is the minimum value of the difference between the initial evaluation priority coefficient of the target execution task and the initial evaluation priority coefficient of each radiation execution task. The radiation effectiveness assessment parameters are determined based on data analysis of the radiation index and a reference radiation priority index.

6. The lightweight multi-task real-time scheduling method based on a microcomputer according to claim 5, characterized in that, If the radiation priority difference index of the target execution task is greater than the preset radiation priority difference index, the execution allocation device for the target execution task shall be determined according to the radiation distribution ratio index of each device to be allocated. For a single device to be assigned, the radiation distribution ratio index = the number of associated execution tasks of the target execution task that the device to be assigned needs to complete / the number of target processing tasks that the device to be assigned needs to complete.

7. The lightweight multi-task real-time scheduling method based on a microcomputer according to claim 1, characterized in that, If the radiation effectiveness assessment parameter of a target execution task is less than or equal to the preset radiation effectiveness assessment parameter, then execution conflict analysis is used to match execution targets for each target execution task. Based on the predicted execution conflict index of the existing allocation equipment, it is determined whether to perform execution target matching for the target task. For a single task processing device, the predicted execution conflict index of the task processing device for the target task is = the number of one type of execution task in the target processing tasks that the task processing device needs to complete / the number of target processing tasks that the task processing device needs to complete. If the predicted execution conflict index is greater than the preset predicted execution conflict index, then the execution allocation device for the target execution task is determined according to the predicted execution conflict index of each device to be matched.

Images