Automatic matching method and device for typical characteristic quantities of intelligent substations and application solutions

Abstract

The present invention discloses a method and device for automatically matching typical characteristic quantities of intelligent substations with application schemes, including: determining basic characteristic quantities and typical characteristic quantities of intelligent substations; adjusting the collection task cycle and collection priority of the initial application scheme of meter reading according to the basic characteristic quantities and typical characteristic quantities, and obtaining a first application scheme; obtaining the collection task success rate of the intelligent substation, adjusting the typical characteristic quantities according to the collection task success rate, dynamically modifying the first application scheme, and obtaining a second application scheme automatically matched with the typical characteristic quantities. The problem that the existing technology cannot meet the diverse requirements of different substations for collection content and priority is solved.

Description

Technical Field

[0001] The present application relates to the field of energy Internet of Things, and specifically to a method and device for automatically matching typical characteristic quantities of smart substations with application solutions. Background Art

[0002] At present, most of the smart meter reading application solutions are configured by power grid staff based on experience and uniformly issued on the master station side. All the stations in the entire power consumption area use a set of application solutions, which does not take into account the complexity and diversity of power consumption in smart stations, which may lead to very unsatisfactory meter reading results in some stations. In fact, the typical characteristics of different smart stations are different, including the length of the communication message and the time consumption of sending and receiving in the station, the scale of users, the collection content, the collection cycle, the collection priority, etc. If you simply use a set of application solutions without considering the actual operating conditions of each station, it may cause the meter reading effect of the station with a small user scale to be better, and the meter reading effect of the station with a large user scale to be very poor. It also cannot meet the diverse needs of different stations for collection content and priority, which seriously restricts the development of grassroots power grid services. Therefore, there is an urgent need for a method that can automatically match application solutions that meet the needs of meter reading services based on the typical characteristics of the station itself. Summary of the invention

[0003] In order to solve the above problems, the present application provides a method for automatically matching typical characteristic quantities of intelligent substations with application solutions, including:

[0004] Determine the basic and typical characteristics of the intelligent substation area;

[0005] According to the basic characteristic quantities and the typical characteristic quantities, adjusting the collection task cycle and the collection priority of the initial application scheme of meter reading to obtain a first application scheme;

[0006] The acquisition task success rate of the intelligent station area is obtained, the typical feature quantity is adjusted according to the acquisition task success rate, the first application scheme is dynamically modified, and a second application scheme that automatically matches the typical feature quantity is obtained.

[0007] Preferably, the basic characteristic quantities include a communication message length L and a communication sending and receiving time T; the typical characteristic quantities include a collection task S, a collection task cycle T, a collection priority and a number of retries.

[0008] Preferably, the evaluation function of the basic characteristic quantity is f(x)=W1R1+W2R2, wherein R1 is the communication success rate, R2 is the communication efficiency, W1 is the communication success rate weight, and W2 is the communication efficiency weight.

[0009] Preferably, adjusting the collection task cycle and priority of the initial application scheme of meter reading according to the basic characteristic quantity and the typical characteristic quantity to obtain the first application scheme includes:

[0010] According to the basic feature quantity and the typical feature quantity, each acquisition task S configured by the intelligent station area master station is obtained. i The optimal communication message length L1 * ,L2 * ,...,L n * The corresponding communication time TP1 * ,TP2 * ,...,TP n * ;

[0011] Estimate each acquisition task S i The actual acquisition time of a single cycle is T i =(L i *N*TP i * ) / L i * ,i=1,2,...,n, where L i * and T i * Each collection task S i The optimal communication message length and the corresponding communication sending and receiving time;

[0012] According to the formula For each collection task S of the initial application solution of meter reading i Perform periodic adjustment, where β is the periodic redundancy coefficient. If T i If it is greater than the corresponding collection task period T, then the collection task period T is increased, and T>T i , obtain the first application solution; if T i If it is smaller than the corresponding collection task period T, there is no need to adjust the collection task period T, and the first application solution is obtained.

[0013] Preferably, obtaining the collection task success rate of the intelligent station area, adjusting the typical feature quantity according to the collection task success rate, dynamically modifying the first application scheme, and obtaining the second application scheme automatically matching the typical feature quantity, includes:

[0014] Set the collection success rate threshold r of the collection task limit ;

[0015] Obtain the average acquisition success rate of each acquisition task of the first application scheme for multiple consecutive acquisitions. If the acquisition task success rate is less than the threshold r limit , then increase the number of retries of the acquisition task and improve the priority of the acquisition task, and obtain a second application solution that automatically matches the typical feature quantity;

[0016] If the proportion of tasks where the average acquisition success rate is less than the acquisition success rate threshold is greater than or equal to a preset threshold, the cyclic redundancy coefficient β is increased to obtain a second application solution that automatically matches the typical feature value.

[0017] The present application also provides an automatic matching device for typical characteristic quantities of intelligent stations and application solutions, including:

[0018] A characteristic quantity determination unit, used to determine the basic characteristic quantity and typical characteristic quantity of the intelligent substation;

[0019] A first application scheme acquisition unit, configured to adjust the collection task cycle and collection priority of the initial application scheme of meter reading according to the basic characteristic quantity and the typical characteristic quantity, and acquire the first application scheme;

[0020] The second application scheme acquisition unit is used to obtain the collection task success rate of the intelligent station, adjust the typical feature quantity according to the collection task success rate, dynamically modify the first application scheme, and obtain a second application scheme that automatically matches the typical feature quantity.

[0021] Preferably, the basic characteristic quantities include a communication message length L and a communication sending and receiving time T; the typical characteristic quantities include a collection task S, a collection task cycle T, a collection priority and a number of retries.

[0022] Preferably, the evaluation function of the basic characteristic quantity is f(x)=W1R1+W2R2, wherein R1 is the communication success rate, R2 is the communication efficiency, W1 is the communication success rate weight, and W2 is the communication efficiency weight.

[0023] Preferably, the second application solution acquisition unit includes:

[0024] The acquisition success rate threshold setting subunit is used to set the acquisition success rate threshold r of the acquisition task. limit ;

[0025] The automatic matching subunit is used to obtain the average acquisition success rate of each acquisition task of the first application scheme for multiple consecutive acquisitions. If the acquisition task success rate is less than the threshold r limit , then increase the number of retries of the acquisition task and improve the priority of the acquisition task, and obtain a second application solution that automatically matches the typical feature quantity;

[0026] The automatic matching subunit is used to increase the cyclic redundancy coefficient β if the average acquisition success rate is less than the acquisition success rate threshold and the proportion of tasks is greater than or equal to a preset threshold, and obtain a second application scheme that automatically matches the typical feature value. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of a method for automatically matching typical characteristic quantities of a smart substation with an application solution provided in an embodiment of the present application;

[0028] Figure 2 It is a schematic diagram of an automatic matching device for typical characteristic quantities of a smart substation and an application solution provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] Many specific details are described in the following description to facilitate a full understanding of the present application. However, the present application can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of the present application, so the present application is not limited by the specific implementation disclosed below.

[0030] Figure 1 This is a flow chart of a method for automatically matching typical characteristic quantities of intelligent substations with application solutions provided in an embodiment of the present application. Figure 1 The method provided in the embodiments of the present application is described in detail.

[0031] Step S101, determining the basic characteristic quantities and typical characteristic quantities of the intelligent station area.

[0032] The basic feature quantities include a communication message length L and a communication transmission and reception time T. The evaluation function of the basic feature quantity is f(x)=W1R1+W2R2, where R1 is the communication success rate, R2 is the communication efficiency, W1 is the communication success rate weight, and W2 is the communication efficiency weight.

[0033] For a certain periodic collection task, different lengths of primary communication messages can be split by combining different data item combinations with reading multiple historical records at one time, and then n groups of different values ​​of the length of a primary communication message and two indicator weights W1 and W2 are determined based on expert experience; under normal operating conditions of the substation, the length of a primary communication message is used as the control variable to test the communication success rate and communication efficiency of the entire collection process when a certain collection task is split into different primary communication message lengths for collection. The communication success rate calculation formula is R1=N success / N total , where N success is the number of successful communications, N total is the total number of communications, and the communication efficiency calculation formula is R2=L effect / T total , where L effect The total length of effective messages to complete the collection task, T totalIn order to complete the total communication time of the acquisition task, the communication success rate R1 and the communication efficiency R2 are taken as the average values ​​of multiple tests under similar working conditions to reduce the interference of the operating conditions on the test results; the final comprehensive evaluation value is calculated according to the multi-objective evaluation function formula, and the maximum evaluation value obtained is the optimal evaluation f * , the corresponding optimal communication message length is L * ; Then, test the acquisition task once the communication message length is L * The time taken for a communication to be sent and received is the average value of multiple tests under similar working conditions as TP. * Similarly, all typical acquisition tasks are tested and calculated in the above manner to obtain the optimal communication message length and the corresponding communication transmission and reception time for each task.

[0034] The typical feature quantities include collection task S, collection task cycle T, collection priority, retry times M, and user scale N.

[0035] Step S102: adjusting the collection task cycle and collection priority of the initial application scheme for meter reading according to the basic characteristic quantities and the typical characteristic quantities, and obtaining a first application scheme.

[0036] The periodic acquisition tasks configured by the master station are S1, S2, ..., S n , n is the number of periodic collection tasks, and the master station configuration collection task period of the corresponding task is T1, T2, ..., T n , according to the collected content, estimate the message length L1, L2, ..., L required to complete each periodic collection task for a single user in a single cycle n According to the basic feature quantity and typical feature quantity, each collection task S configured by the intelligent station area master station is obtained. i The optimal communication message length L1 * ,L2 * ,...,L n * And the corresponding communication transmission and reception time TP1 * ,TP2 * ,...,TP n * ; Estimate each acquisition task S i The actual acquisition time of a single cycle is T i =(L i *N*TP i * ) / L i * ,i=1,2,...,n, where L i * and T i * Each collection task Si The optimal communication message length and the corresponding communication sending and receiving time are given; considering the priority of short-cycle task execution, the actual collection time of a single cycle is T i Sort by time from shortest to longest: According to the formula For each collection task S of the initial application solution of meter reading i Perform periodic adjustment, where β is the periodic redundancy coefficient. If T i If it is greater than the corresponding collection task cycle T, it is considered that the collection cycle T configured by the master station for the task is too small and the collection cannot be completed within this cycle. In this case, the collection task cycle T should be increased and T>T i , obtain the first application solution; if T i If it is less than the corresponding collection task period T, there is no need to adjust the collection task period T, and the first application scheme is obtained. Repeat this process until the period adjustment of all periodic tasks is completed. The initial application scheme can be adjusted as follows: the collection period of each task is T1, T2, ..., T n , the length of a communication message is L1 * ,L2 * ,...,L n * ,The shorter the task collection cycle is, the higher the priority is, and the initial retry times for all tasks are M.

[0037] Step S103, obtaining the collection task success rate of the intelligent station, adjusting the typical feature quantity according to the collection task success rate, dynamically modifying the first application scheme, and obtaining a second application scheme that automatically matches the typical feature quantity.

[0038] According to expert experience, set the collection success rate threshold r of the collection task limit ; Obtain the average acquisition success rate of each acquisition task of the first application scheme for multiple consecutive acquisitions. If the acquisition task success rate is less than the threshold r limit , then increase the number of retries of the acquisition task and improve the priority of the acquisition task, and obtain a second application solution that automatically matches the typical feature; if the average acquisition success rate is less than the acquisition success rate threshold and the proportion of tasks is greater than or equal to the preset threshold, it means that the acquisition cycle setting is inappropriate, readjust the task cycle, increase the cycle redundancy coefficient β, and obtain a second application solution that automatically matches the typical feature.

[0039] If the average collection success rate of each collection task of the current application solution for multiple days is greater than the threshold, the operation status of the solution is monitored for a long time, feature values ​​are extracted from the monitoring messages, and a typical feature library of the substation operating conditions is established to provide a reference for the setting of relevant expert experience parameters in the process of automatic matching of feature values ​​and application solutions.

[0040] Specific application examples are as follows:

[0041] 15-minute load profile and hourly freeze for two periodic tasks.

[0042] Step 1: For the hourly frozen collection task, five different values ​​of the length of a communication message are determined based on expert experience by combining different data item combinations with reading multiple historical records at one time, as well as the indicator weights W1=0.8 and W2=0.2. Under normal operating conditions of the substation, the length of a communication message is used as the control variable to test the communication success rate and communication efficiency of the entire collection process when the hourly frozen collection task is split into different lengths of a communication message for collection. The communication success rate calculation formula is R1=N success / N total , where N success is the number of successful communications, N total is the total number of communications, and the communication efficiency calculation formula is R2=L effect / T total , where L effect The total length of effective messages to complete the collection task, T total In order to complete the total communication time of the acquisition task, the communication success rate R1 and the communication efficiency R2 are taken as the average values ​​of multiple tests under similar working conditions to reduce the interference of the operating conditions on the test results; the final comprehensive evaluation value is calculated according to the multi-objective evaluation function formula, and the maximum evaluation value obtained is the optimal evaluation f * , the corresponding optimal communication message length is L * ; Then, the test freezes the acquisition task once every hour. The length of the communication message is L * When a communication is sent and received, the average value of multiple tests under similar working conditions is taken as T * Similarly, the 15-minute load curve collection task is tested and calculated in the above manner, and the optimal communication message length for this task is L * And the corresponding communication time T * .

[0043] Step 2: The master station configuration collection period corresponding to the two periodic tasks S1 and S2 of 15-minute load curve and hourly freezing is T1 and T2. According to the collection content, the message length L1 and L2 required to complete the single-cycle single-user collection of each periodic task are estimated. The optimal communication message length L1 for each task is obtained from step 1. * ,L2 * The corresponding communication time is T1 * ,T2 * ; First, estimate the actual single-cycle acquisition time T1 and T2 of periodic tasks S1 and S2, and then sort the actual single-cycle acquisition time from short to long. Then press the formula Adjust the cycle; if T1 is greater than the corresponding task cycle T, it is considered that the acquisition cycle T configured by the master station for the task is too small, and the acquisition cannot be completed within the cycle. The acquisition cycle T should be increased to satisfy T>T1. If T1 is less than the task cycle T, there is no need to adjust the cycle T; similarly, complete the adjustment of another task cycle. The initial application solution can be adjusted as follows: the acquisition cycle of the 15-minute load curve and the hourly freezing task is T1, T2, and the optimal communication message length is L1 * ,L2 * ,The 15-minute load curve task has a higher priority than the hourly freeze task, and the initial retry times of both tasks are M=3.

[0044] Step 3: Set the collection success rate threshold r for each collection task based on expert experience limit =0.95, calculate the average collection success rate of each collection task for P = 5 consecutive days. If the collection success rate of a task is less than the threshold, try to increase the number of retries of the task and appropriately increase the task priority. If the proportion of tasks with an average collection success rate less than the collection success rate threshold reaches w limit =0.4, indicating that the acquisition cycle setting is inappropriate. Return to step 2 to readjust the task cycle and try to increase the cycle redundancy coefficient β appropriately.

[0045] Step 4: After the average collection success rate of each collection task of the current application scheme for P = 5 consecutive days is greater than the threshold, the operation status of the scheme is monitored for a long time, feature values ​​are extracted from the monitoring messages, and a typical feature library of the substation operation conditions is established to provide a reference for the setting of relevant expert experience parameters in the process of automatic matching of feature values ​​and application schemes.

[0046] Based on the same inventive concept, the present application also provides an automatic matching device for typical characteristic quantities of intelligent substations and application solutions, such as Figure 2 As shown, including:

[0047] The characteristic quantity determination unit 210 is used to determine the basic characteristic quantity and typical characteristic quantity of the intelligent station area;

[0048] A first application scheme acquisition unit 220, configured to adjust the collection task cycle and collection priority of the initial application scheme of meter reading according to the basic characteristic quantity and the typical characteristic quantity, and acquire the first application scheme;

[0049] The second application scheme acquisition unit 230 is used to acquire the acquisition task success rate of the intelligent station, adjust the typical feature quantity according to the acquisition task success rate, dynamically modify the first application scheme, and acquire the second application scheme automatically matched with the typical feature quantity.

[0050] Preferably, the characteristic quantity determination unit is used to determine the basic characteristic quantities and typical characteristic quantities of the intelligent substation, wherein the basic characteristic quantities include the length L of a communication message and the time T for sending and receiving a communication; the typical characteristic quantities include the collection task S, the collection task cycle T, and the collection priority.

[0051] Preferably, the evaluation function of the basic characteristic quantity is f(x)=W1R1+W2R2, wherein R1 is the communication success rate, R2 is the communication efficiency, W1 is the communication success rate weight, and W2 is the communication efficiency weight.

[0052] Preferably, the second application solution acquisition unit includes:

[0053] The acquisition success rate threshold setting subunit is used to set the acquisition success rate threshold r of the acquisition task. limit ;

[0054] The automatic matching subunit is used to obtain the average acquisition success rate of each acquisition task of the first application scheme for multiple consecutive acquisitions. If the acquisition task success rate is less than the threshold r limit , then increase the number of retries of the acquisition task and improve the priority of the acquisition task to obtain a second application solution for automatic matching of the typical feature quantity;

[0055] The automatic matching subunit is used to increase the cyclic redundancy coefficient β to obtain the second application scheme of automatic matching of the typical feature quantity if the proportion of tasks with an average collection success rate less than the collection success rate threshold is greater than or equal to a preset threshold.

[0056] The present application provides a method and device for automatically matching typical characteristic quantities of a smart substation with application solutions. Typical characteristic quantities are extracted according to the operating conditions of the smart substation itself, and application solutions are automatically matched to achieve self-diagnosis and self-optimization of application solutions to meet the meter reading needs of different substations.

[0057] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0058] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0059] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0060] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application rather than to limit its protection scope. Although the present application has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that after reading the present application, those skilled in the art can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the application, and these changes, modifications or equivalent substitutions are all within the scope of the claims to be approved by the application.

Claims

1. A method for automatically matching typical characteristic quantities of intelligent substations with application solutions, characterized in that: include: Determine the basic and typical characteristics of the intelligent substation area; According to the basic characteristic quantity and the typical characteristic quantity, the collection task cycle and the collection priority of the initial application scheme of meter reading are adjusted to obtain the first application scheme, including: According to the basic feature quantity and the typical feature quantity, each acquisition task S configured by the intelligent station area master station is obtained. i The optimal communication message length L1 * ,L2 * ,...,L n * The corresponding communication time TP1 * ,TP2 * ,...,TP n * ; Estimate each acquisition task S i The actual acquisition time of a single cycle is T i =(L i *N*TP i * ) / L i * ,i=1,2,...,n, where L i * and T i * Each collection task S i The optimal communication message length and the corresponding communication sending and receiving time; According to the formula For each collection task S of the initial application solution of meter reading i Perform periodic adjustment, where β is the periodic redundancy coefficient. If T i If it is greater than the corresponding collection task period T, then the collection task period T is increased, and T>T i , obtain the first application solution; if T i If it is less than the corresponding collection task period T, there is no need to adjust the collection task period T, and the first application solution is obtained; Acquiring a collection task success rate of the intelligent station area, adjusting the typical feature quantity according to the collection task success rate, dynamically modifying the first application scheme, and acquiring a second application scheme that automatically matches the typical feature quantity, including: Set the collection success rate threshold r of the collection task limit ; Obtain the average acquisition success rate of each acquisition task of the first application scheme for multiple consecutive acquisitions. If the acquisition task success rate is less than the threshold r limit , then increase the number of retries of the acquisition task and improve the priority of the acquisition task, and obtain a second application solution that automatically matches the typical feature quantity; If the proportion of tasks where the average acquisition success rate is less than the acquisition success rate threshold is greater than or equal to a preset threshold, the cyclic redundancy coefficient β is increased to obtain a second application solution that automatically matches the typical feature value.

2. The method according to claim 1, characterized in that: The basic characteristic quantities include a communication message length L and a communication sending and receiving time T; the typical characteristic quantities include a collection task S, a collection task cycle T, a collection priority and a number of retries.

3. The method according to claim 2, characterized in that The evaluation function of the basic characteristic quantity is f(x)=W1R1+W2R2, wherein R1 is the communication success rate, R2 is the communication efficiency, W1 is the communication success rate weight, and W2 is the communication efficiency weight.

4. An automatic matching device for typical characteristic quantities of intelligent substations and application solutions, characterized in that: include: A characteristic quantity determination unit, used to determine the basic characteristic quantity and typical characteristic quantity of the intelligent substation; The first application scheme acquisition unit is used to adjust the collection task cycle and collection priority of the initial application scheme of meter reading according to the basic characteristic quantity and the typical characteristic quantity to acquire the first application scheme, including: According to the basic feature quantity and the typical feature quantity, each acquisition task S configured by the intelligent station area master station is obtained. i The optimal communication message length L1 * ,L2 * ,...,L n * The corresponding communication time TP1 * ,TP2 * ,...,TP n * ; Estimate each acquisition task S i The actual acquisition time of a single cycle is T i =(L i *N*TP i * ) / L i * ,i=1,2,...,n, where L i * and T i * Each collection task S i The optimal communication message length and the corresponding communication sending and receiving time; According to the formula For each collection task S of the initial application solution of meter reading i Perform periodic adjustment, where β is the periodic redundancy coefficient. If T i If it is greater than the corresponding collection task period T, then the collection task period T is increased, and T>T i , obtain the first application solution; if T i If it is less than the corresponding collection task period T, there is no need to adjust the collection task period T, and the first application solution is obtained; The second application scheme acquisition unit is used to acquire the collection task success rate of the intelligent station area, adjust the typical feature quantity according to the collection task success rate, dynamically modify the first application scheme, and acquire the second application scheme that automatically matches the typical feature quantity, including: Set the collection success rate threshold r of the collection task limit ; Obtain the average acquisition success rate of each acquisition task of the first application scheme for multiple consecutive acquisitions. If the acquisition task success rate is less than the threshold r limit , then increase the number of retries of the acquisition task and improve the priority of the acquisition task, and obtain a second application solution that automatically matches the typical feature quantity; If the proportion of tasks where the average acquisition success rate is less than the acquisition success rate threshold is greater than or equal to a preset threshold, the cyclic redundancy coefficient β is increased to obtain a second application solution that automatically matches the typical feature value.

5. The device according to claim 4, characterized in that: The basic characteristic quantities include a communication message length L and a communication sending and receiving time T; the typical characteristic quantities include a collection task S, a collection task cycle T, a collection priority and a number of retries.

6. The device according to claim 4, characterized in that The evaluation function of the basic characteristic quantity is f(x)=W1R1+W2R2, wherein R1 is the communication success rate, R2 is the communication efficiency, W1 is the communication success rate weight, and W2 is the communication efficiency weight.

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