Method and System for Constructing Power Grid Resource Topology Map Based on Sharded Storage of Distribution Network Data

Abstract

The present application relates to a method and system for constructing a power grid resource topology map based on segmented storage of distribution network data, which belongs to the technical field of distribution network topology analysis. The method includes: receiving the distribution information of the jurisdiction areas of distribution equipment input by a user, and dividing the pre-constructed distribution network topology data into multiple regional data segments according to the distribution information of the jurisdiction areas of distribution equipment, and each regional data segment corresponds to an independent storage unit; dividing multiple topology data segments according to the feeders and transmission lines in each regional data segment; when receiving a data upload request for the distribution network data to be stored, storing the jurisdiction area of the distribution equipment of the distribution network data to be stored, as well as the feeder ID or transmission line ID in the distribution network data to be stored, in the storage unit of the corresponding regional data segment, and updating the corresponding topology data segment. The present application has the effects of reducing the possibility of congestion in the data transmission channel and increasing the storage efficiency of the distribution network data.

Description

Technical Field

[0001] The present application relates to the technical field of distribution network topology analysis, and particularly to a method and system for constructing a power grid resource topology map based on distributed storage of distribution network data. Background Art

[0002] With the rapid development of the power system, the scale of the distribution network is constantly expanding, and the equipment data and topological structure are becoming increasingly complex. The distribution network topology data is an important basis for the operation, monitoring, and fault analysis of the power system. Its efficient storage and management are crucial for improving the intelligent level and operation and maintenance efficiency of the power grid.

[0003] However, when facing large-scale and highly complex topology data, the traditional distribution network data storage and management methods have low storage efficiency due to the huge scale of the topology data. This may lead to the inconsistency of the topology data during the user's data query process, thus reducing the accuracy of the topology data analysis. Summary of the Invention

[0004] In order to improve the efficiency of storing distribution network data and reduce data congestion, the present application provides a method and system for constructing a power grid resource topology map based on distributed storage of distribution network data.

[0005] In a first aspect, the present application provides a method for constructing a power grid resource topology map based on distributed storage of distribution network data, adopting the following technical solution:

[0006] A method for constructing a power grid resource topology map based on distributed storage of distribution network data, the method comprising:

[0007] Receiving the distribution equipment jurisdiction area distribution information input by the user, and dividing the pre-constructed distribution network topology data into multiple regional data slices according to the distribution equipment jurisdiction area distribution information, each of the regional data slices corresponding to an independent storage unit;

[0008] Dividing multiple topology data slices according to the feeders and transmission lines in each of the regional data slices;

[0009] When receiving a data upload request for the distribution network data to be stored, storing the distribution equipment jurisdiction area of the distribution network data to be stored, and the feeder ID or transmission line ID in the distribution network data to be stored, in the storage unit corresponding to the regional data slice, and updating the corresponding topology data slice.

[0010] Optionally, the topology data slice stores a set of a single feeder and all electrical equipment connected to the single feeder, or a set of a single transmission line and all electrical equipment connected to the single transmission line;

[0011] The topological data shard also has connection information between a single feeder and all corresponding electrical devices, or connection information between a single transmission line and all corresponding electrical devices.

[0012] Optionally, the method includes:

[0013] Obtain query request information corresponding to each of the topological data shards, where the query request information includes a query history record and a request query time;

[0014] Generate a priority gradient corresponding to each of the topological data shards under the target area data shard according to pre-stored historical power consumption data of the distribution network and the multiple query request information;

[0015] When multiple pieces of distribution network data to be stored are received simultaneously and stored in the storage unit corresponding to the target area data shard, divide the priorities of storing the multiple pieces of distribution network data to be stored according to the priority gradient corresponding to the topological data shard in the distribution network data to be stored.

[0016] Optionally, the generating a priority gradient corresponding to each of the topological data shards under the target area data shard according to pre-stored historical power consumption data of the distribution network and the multiple query request information includes:

[0017] Generate an abnormal query probability at the current time according to the abnormal working times corresponding to various abnormal working states in the historical power consumption data of the distribution network and the multiple query request information;

[0018] Capture the query quantity of each of the topological data shards under the target area data shard within a preset sampling duration before the current time according to the multiple query request information corresponding to the target area data shard;

[0019] Calculate and generate a current query probability according to the query quantity and a preset query peak value;

[0020] Calculate and generate a priority coefficient according to the current query probability and the abnormal query probability, and divide the corresponding priority gradient according to the priority coefficients corresponding to the multiple topological data shards.

[0021] Optionally, the generating an abnormal query probability at the current time according to the abnormal working times corresponding to various abnormal working states in the historical power consumption data of the distribution network and the multiple query request information includes:

[0022] Generate abnormal state probabilities at the current time in various abnormal working states according to the historical power consumption data of the distribution network and a pre-divided cycle period;

[0023] Capture the topological query probabilities of various said abnormal working states according to the historical power consumption data of the distribution network and the multiple said query request information;

[0024] Calculate and generate an abnormal query probability according to the multiple said abnormal state probabilities and the multiple said topological query probabilities.

[0025] Optionally, the generating the abnormal state probabilities at the current moment in various abnormal working states according to the historical power consumption data of the distribution network and the pre-divided cycle periods includes:

[0026] According to the pre-divided cycle periods and the unit time periods pre-divided in the cycle periods, count the abnormal state probabilities in the historical power consumption data of the distribution network in multiple said cycle periods and the same said unit time period as the current moment when in the said abnormal working state.

[0027] Optionally, the capturing the topological query probabilities of various abnormal working states according to the historical power consumption data of the distribution network and the multiple said query request information includes:

[0028] According to the historical power consumption data of the distribution network, mark the time periods within a preset review duration after multiple said abnormal working moments as review time periods;

[0029] According to all the said query request information, capture the topological query probabilities of receiving corresponding query requests within multiple said review time periods corresponding to each said abnormal working state.

[0030] In a second aspect, the present application provides a system for constructing a power grid resource topology map based on sharded storage of distribution network data, adopting the following technical solutions:

[0031] A system for constructing a power grid resource topology map based on sharded storage of distribution network data, the system includes a server terminal, and the server terminal includes,

[0032] An information receiving module, configured to receive the distribution equipment jurisdiction area distribution information input by a user, and divide the pre-constructed distribution network topology data into multiple area data shards according to the distribution equipment jurisdiction area distribution information, and each said area data shard corresponds to an independent storage unit;

[0033] A data division module, configured to divide multiple topological data shards according to the feeders and transmission lines in each said area data shard;

[0034] A data receiving and storage module, configured to, when receiving a data upload request for the distribution network data to be stored, store the distribution equipment jurisdiction area of the distribution network data to be stored and the feeder ID or transmission line ID in the distribution network data to be stored in the storage unit corresponding to the said area data shard, and update the corresponding topological data shard.

[0035] In a third aspect, the present application provides a server terminal, adopting the following technical solution:

[0036] A server terminal, the server terminal includes a processor and a memory, and at least one instruction, at least one program, a code set or an instruction set is stored in the memory, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the method for constructing a power grid resource topology map based on fragmented storage of distribution network data as described in the first aspect.

[0037] In a fourth aspect, the present application provides a computer-readable storage medium, adopting the following technical solution:

[0038] A computer-readable storage medium, at least one instruction, at least one program, a code set or an instruction set is stored in the storage medium, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by a processor to implement the method for constructing a power grid resource topology map based on fragmented storage of distribution network data as described in the first aspect.

[0039] In summary, the present application includes at least one of the following beneficial technical effects:

[0040] In the present application, through the divided multiple storage units, the distribution network data to be stored is stored in the multiple storage units respectively according to the jurisdiction areas of the power distribution equipment, reducing the possibility of data accumulation and congestion of the data transmission channel during data storage, and increasing the storage efficiency of the distribution network data. At the same time, the topology data fragments further divided by the feeder and the transmission line facilitate reducing the efficiency of user access to the distribution network data and loading and constructing the distribution network topology map. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings without creative efforts based on these drawings.

[0042] Figure 1 It is a schematic flowchart of a method for constructing a power grid resource topology map based on fragmented storage of distribution network data provided by an embodiment of the present application.

[0043] Figure 2 It is a schematic flowchart of a process for dividing and storing the priorities of multiple distribution network data to be stored provided by an embodiment of the present application.

[0044] Figure 3 It is a schematic flowchart of a process for dividing multiple priority gradients provided by an embodiment of the present application.

[0045] Figure 4 It is a schematic flowchart for generating the abnormal query probability at the current moment provided by an embodiment of the present application.

[0046] Figure 5 It is a system block diagram of a system for constructing a power grid resource topology map based on sharded storage of distribution network data provided by an embodiment of the present application.

[0047] Figure 6 It is a block diagram of the structure of a server terminal provided by an embodiment of the present application.

[0048] Explanation of reference numerals: 501, information receiving module; 502, data partitioning module; 503, data receiving and storage module; 504, priority partitioning module; 505, data probability calculation module. Detailed implementation manners

[0049] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will further describe the embodiments of the present invention in detail with reference to the accompanying Figure 1-6 drawings.

[0050] An embodiment of the present application provides a method for constructing a power grid resource topology map based on sharded storage of distribution network data. The method can be applied to a system for constructing a power grid resource topology map based on sharded storage of distribution network data. Among them, the execution entity of the system for constructing a power grid resource topology map based on sharded storage of distribution network data can be a server terminal, and the memory of the server terminal is used to store distribution network data.

[0051] An embodiment of the present application illustrates the sharded storage of distribution network data during the process of uploading distribution network data to the server terminal.

[0052] Next, the Figure 1 processing flow shown will be described in detail, and the content can be as follows:

[0053] S101, receive the distribution equipment jurisdiction area distribution information input by the user, and divide the pre-constructed distribution network topology data into multiple regional data shards according to the distribution equipment jurisdiction area distribution information, and each regional data shard corresponds to an independent storage unit.

[0054] In implementation, the server terminal receives the distribution equipment jurisdiction area distribution information input by the user. Here, the distribution equipment jurisdiction area distribution information can be divided according to the prefecture-level administrative jurisdiction or can be manually divided by the user.

[0055] The server terminal has pre-constructed distribution network topology data, and the topology data map of the distribution network is recorded in the distribution network topology data. After the server terminal receives the distribution equipment jurisdiction area distribution information, the server terminal divides the pre-constructed distribution network topology data into multiple regional data shards, and there is a one-to-one mapping relationship between the multiple regional data shards and the multiple distribution equipment jurisdiction areas.

[0056] At the same time, in order to reduce the storage pressure during the upload process of distribution network data and improve the storage efficiency of distribution network data upload, each regional data shard corresponds to an independent storage unit, so that the uploaded data can be respectively divided into the corresponding storage units.

[0057] S102, according to the feeders and transmission lines in each regional data shard, divide into multiple topology data shards.

[0058] In implementation, the server terminal uses the feeders and transmission lines contained in each regional data shard to further divide the regional data shard to generate multiple topology data shards, so as to facilitate users to construct a distribution network topology map and reduce the difficulty of users in data query and construction of the distribution network topology map.

[0059] There are two types of topology data shards. One is the feeder topology data shard, and the other is the transmission line topology data shard.

[0060] Among them, the topology data shard stores a set of a single feeder and all electrical equipment connected to the single feeder, or, a set of a single transmission line and all electrical equipment connected to the single transmission line;

[0061] The topology data shard also has the connection information between a single feeder and all corresponding electrical equipment, or, the connection information between a single transmission line and all corresponding electrical equipment.

[0062] S103, when receiving a data upload request for the distribution network data to be stored, store the distribution equipment jurisdiction area of the distribution network data to be stored, and the feeder ID or transmission line ID in the distribution network data to be stored, in the storage unit of the corresponding regional data shard, and update the corresponding topology data shard.

[0063] In implementation, when the server terminal receives a data upload request for the distribution network data to be stored, the server terminal first matches the distribution equipment jurisdiction area corresponding to the distribution network data to be stored. Here, the distribution equipment jurisdiction area corresponding to the distribution network data to be stored can be carried by the distribution network data to be stored itself, or can be obtained by identifying the location of the data upload terminal for uploading the distribution network data to be stored and then searching for the location of the data upload terminal to match the distribution equipment jurisdiction area.

[0064] Next, the server terminal matches the corresponding regional data shards through the jurisdiction area of the power distribution equipment corresponding to the power distribution network data to be stored by the customer. Then, the server terminal stores the uploaded power distribution network data to be stored in the storage unit corresponding to the corresponding regional data shard.

[0065] At the same time, the server terminal updates the corresponding topology data shard through the feeder ID or transmission line ID in the power distribution network data to be stored.

[0066] In this application, through the divided multiple storage units, the power distribution network data to be stored is stored in multiple storage units respectively according to the jurisdiction area of the power distribution equipment, reducing the possibility of data accumulation and data transmission channel congestion during data storage, and increasing the storage efficiency of the power distribution network data. At the same time, the topology data shards further divided by the feeder and transmission line facilitate reducing the efficiency of users accessing the power distribution network data and loading and constructing the power distribution network topology map.

[0067] Optionally, in this application, there is also a process as Figure 2 shown, and the specific process is as follows:

[0068] S201, obtain the query request information corresponding to each topology data shard, and the query request information includes the query history record and the request query time.

[0069] In implementation, when the user accesses the server terminal and queries the power distribution network topology data to implement loading the topology map and / or querying the data of electrical equipment in the power distribution network topology map, the server terminal records the user's query record and the topology data shard corresponding to each query.

[0070] The server terminal obtains the query request information corresponding to each topology data shard in the memory, and each query request information includes at least the query history record and the request query time.

[0071] S202, generate the priority gradient corresponding to multiple topology data shards under the target area data shard according to the pre-stored historical power consumption data of the power distribution network and multiple query request information.

[0072] In implementation, the server terminal pre-stores the historical power consumption data of the power distribution network. The historical power consumption data of the power distribution network records the operating conditions of multiple electrical equipment, and the historical power consumption data of the power distribution network also records the abnormal working time when various bad operating states start. The bad operating states here include operating faults, overloads, etc.

[0073] The server terminal determines the priority coefficients of multiple topology data shards based on the abnormal working moments of the bad operation states in the historical power consumption data of the distribution network, the request query probabilities of users for the bad operation states, and the frequencies of request queries before the current moment, and generates a priority gradient corresponding to each of the multiple topology data shards according to the magnitudes of the priority coefficients.

[0074] S203. When multiple pieces of distribution network data to be stored are received simultaneously and stored in the corresponding storage units of the target area data shards, the priorities for storing the multiple pieces of distribution network data to be stored are divided according to the priority gradient of the corresponding topology data shards in the distribution network data to be stored.

[0075] In implementation, when the server terminal receives upload data requests for multiple pieces of distribution network data to be stored simultaneously, and all the multiple pieces of distribution network data to be stored need to be stored in the storage units corresponding to the same area data shard, the server terminal divides the priorities for storing the multiple pieces of distribution network data to be stored according to the priority gradient of the topology data shards corresponding to the feeder ID or transmission line ID in each piece of distribution network data to be stored. Here, the same area data shard is called the target area data shard, and if a piece of distribution network data to be stored corresponds to multiple topology data shards, the piece of distribution network data to be stored is divided into the priority with the higher priority gradient among the two topology data shards.

[0076] In this application, to reduce the impact of the failure to update and synchronize topology data in a timely manner during the user query process, the priorities for storage are divided according to the query history records of the topology data shards for the distribution network data to be stored, so that the topology data shards frequently queried by users can be updated in a timely manner. At the same time, by dividing the priorities, the process of data upload is arranged and stored in an orderly manner, reducing the possibility of data upload congestion. Further, through the divided priorities, the loading speed of the distribution network topology map during user access can be reduced by preloading the topology data shards with higher priorities.

[0077] Optionally, in step S202, there is also a process as Figure 3 shown, and the specific operation process is as follows:

[0078] S301. Generate the abnormal query probability at the current moment according to the abnormal working moments corresponding to multiple bad operation states in the historical power consumption data of the distribution network and multiple query request messages.

[0079] In implementation, multiple cycle periods are pre-divided in the server terminal, and multiple unit time periods are divided within each cycle period. In the embodiments of this application, the cycle period is in years as the unit, and the unit time period is in months as the unit.

[0080] The server terminal obtains the abnormal query probability at the current moment based on the abnormal working moments corresponding to the bad working states and the query request information in the historical power consumption data of the distribution network.

[0081] For example, the server terminal obtains the abnormal query probability for the current month based on the historical power consumption data of the distribution network.

[0082] S302. According to the multiple query request information corresponding to the target area data shard, capture the query quantity of each topological data shard under the target area data shard within a preset sampling duration before the current moment.

[0083] In implementation, the server terminal summarizes the multiple query request information corresponding to the target area data shard.

[0084] Then, the server terminal captures the query history records within the sampling duration before the current moment from the summarized multiple query request information, and counts the query quantity of the query history records corresponding to each topological data shard captured. For example, within one week before the current moment, one of the topological data shards in the target area data shard was accessed and queried 8 times.

[0085] S303. Calculate and generate the current query probability according to the query quantity and the preset query peak value.

[0086] In implementation, the server terminal divides the query data by the preset query peak value to calculate and generate the current query probability. Here, the query peak value is generally the same as the number of days of the sampling duration.

[0087] S304. Calculate and generate the priority coefficient according to the current query probability and the abnormal query probability, and divide the corresponding priority gradient according to the priority coefficients corresponding to the multiple topological data shards.

[0088] In implementation, if the server terminal identifies that the current query probability is greater than or equal to 1, the priority coefficient is 1.

[0089] If the server terminal identifies that the current query probability is less than 1, it calculates and generates the union of the current query probability and the abnormal query probability, and uses the solved value as the priority coefficient.

[0090] Then, the server terminal divides the corresponding priority gradient for the topological data shards according to the magnitudes of the priority coefficients of each topological data shard.

[0091] Optionally, in step S301, there is also a process as Figure 4 shown, and the specific operation process is as follows:

[0092] S401. Generate the abnormal state probabilities at the previous moment under various bad working states according to the historical power consumption data of the distribution network and the pre-divided cycle period.

[0093] In implementation, the server terminal matches the unit time period corresponding to the current moment within the cycle period.

[0094] Next, the specific processing flow of the server terminal is as follows:

[0095] According to the pre-divided cycle period and the pre-divided unit time periods in the cycle period, the abnormal state probability in the bad working state is statistically calculated in the historical power consumption data of the distribution network for multiple cycle periods and the same unit time period to which the current moment belongs.

[0096] The server terminal refers to the same unit time period to which the current moment belongs in multiple cycle periods as the target unit time period. Then the server terminal statistically calculates the abnormal state probability of generating a bad working state within the target unit time period in multiple cycle periods.

[0097] For example, in the past 5 years, there were 2 years in which a bad working state occurred in August of the target unit time period, so the abnormal state probability is 40%.

[0098] S402. According to the historical power consumption data of the distribution network and multiple query request messages, capture the topology query probability under various bad working states.

[0099] In implementation, after the server terminal identifies a bad working state, it monitors whether the user queries the corresponding topology data shard due to the bad working state, and calculates and statistically generates the probability that the user queries the corresponding topology data shard due to the bad working state.

[0100] Specifically, the operation flow of step S402 is as follows:

[0101] According to the historical power consumption data of the distribution network, mark the time period within the preset review duration after multiple abnormal working moments as the review time period;

[0102] According to all the query request messages, capture the topology query probability of receiving the corresponding query request within multiple review time periods corresponding to each bad working state.

[0103] In implementation, the server terminal processes all the bad working states and the corresponding abnormal working moments recorded in the historical power consumption data of the distribution network. Specifically, the server terminal marks the time period within the preset review duration after all the abnormal working moments as the review time period.

[0104] Then the server terminal captures the topology query probability of receiving the corresponding query request within multiple review time periods corresponding to each bad working state in all the query request messages.

[0105] For example, the review duration is 2 days. That is, after the server terminal recognizes an abnormal working state, it records whether the user queries the corresponding topology data shard within 2 days and calculates the topology query probability for each type of abnormal working state. For example, for the abnormal working state of overload, there are 10 corresponding review periods. Within these 10 review periods, only in 5 review periods, a query for the topology data shard corresponding to the abnormal working state is received. Then the topology query probability is 50%.

[0106] S403. Calculate and generate an abnormal query probability based on multiple abnormal state probabilities and multiple topology query probabilities.

[0107] In implementation, the server terminal multiplies multiple abnormal state probabilities and the corresponding topology query probabilities to calculate the probability of generating an abnormal operation state and querying the corresponding topology data shard simultaneously within the target unit time period, which is called the abnormal query probability here.

[0108] Then the server terminal solves the set of multiple abnormal query probabilities, that is, the obtained set is the probability that, within the target unit time period, any one or more abnormal operation states occur and, at the same time, within the review period after the occurrence of the abnormal operation state, the corresponding topology data shard is queried by the user, which is called the abnormal query probability.

[0109] As Figure 5 shown, the embodiment of the present application also discloses a power grid resource topology map system based on the distributed storage of power distribution network data shards. The system includes a server terminal, and the server terminal includes

[0110] An information receiving module 501, configured to receive the distribution information of the jurisdiction areas of power distribution equipment input by the user, and divide the pre-constructed power distribution network topology data into multiple regional data shards according to the distribution information of the jurisdiction areas of power distribution equipment. Each regional data shard corresponds to an independent storage unit;

[0111] A data division module 502, configured to divide multiple topology data shards according to the feeders and transmission lines in each regional data shard;

[0112] A data receiving and storing module 503, configured to, when receiving a data upload request for the power distribution network data to be stored, store the jurisdiction area of the power distribution equipment of the power distribution network data to be stored and the feeder ID or transmission line ID in the power distribution network data to be stored in the storage unit of the corresponding regional data shard, and update the corresponding topology data shard.

[0113] Inside the server terminal, the topology data shard stores a set of a single feeder and all electrical equipment connected to the single feeder, or a set of a single transmission line and all electrical equipment connected to the single transmission line;

[0114] The topological data sharding also has connection information between a single feeder and all corresponding electrical devices, or connection information between a single transmission line and all corresponding electrical devices.

[0115] Optionally, the server terminal can also be used for:

[0116] The information receiving module 501 is used to obtain the query request information corresponding to each topological data sharding. The query request information includes query history records and the request query time.

[0117] The priority division module 504 is used to generate the priority gradients corresponding to multiple topological data shards under the target area data shard according to the pre-stored historical power consumption data of the distribution network and multiple query request information.

[0118] The priority division module 504 is used to divide the priorities of storing multiple pieces of distribution network data to be stored according to the priority gradients of the corresponding topological data shards in the distribution network data to be stored when multiple pieces of distribution network data to be stored are received simultaneously and stored in the storage unit corresponding to the target area data shard.

[0119] Optionally, the server terminal is specifically used for:

[0120] The data probability calculation module 505 is used to generate the abnormal query probability at the current moment according to the abnormal working moments corresponding to various bad working states in the historical power consumption data of the distribution network and multiple query request information.

[0121] The data probability calculation module 505 is used to capture the query quantity of each topological data shard under the target area data shard within a preset sampling duration before the current moment according to the multiple query request information corresponding to the target area data shard.

[0122] The data probability calculation module 505 is used to calculate and generate the current query probability according to the query quantity and the preset query peak value.

[0123] The priority division module 504 is used to calculate and generate a priority coefficient according to the current query probability and the abnormal query probability, and divide the corresponding priority gradients according to the priority coefficients corresponding to multiple topological data shards.

[0124] Optionally, the server terminal is specifically used for:

[0125] The data probability calculation module 505 is used to generate the abnormal state probability at the current moment in various bad working states according to the historical power consumption data of the distribution network and the pre-divided cycle period.

[0126] The data probability calculation module 505 is used to capture the topological query probability of various bad working states according to the historical power consumption data of the distribution network and multiple query request information.

[0127] A data probability calculation module 505 is configured to calculate and generate an abnormal query probability according to multiple abnormal state probabilities and multiple topology query probabilities.

[0128] Optionally, the server terminal is specifically configured to:

[0129] The data probability calculation module 505 is configured to, according to a pre-divided cycle period and a pre-divided unit time period in the cycle period, count the abnormal state probabilities in a bad working state in the historical power consumption data of the distribution network within multiple cycle periods and the same unit time period to which the current moment belongs.

[0130] Optionally, the server terminal is specifically configured to:

[0131] The data probability calculation module 505 is configured to mark, according to the historical power consumption data of the distribution network, the time periods within a preset review duration after multiple abnormal working moments as review time periods;

[0132] The data probability calculation module 505 is configured to capture, according to all query request information, the topology query probabilities of receiving corresponding query requests within multiple review time periods corresponding to each bad working state.

[0133] Figure 5 It is a schematic structural diagram of the server terminal provided in an embodiment of the present application. The server terminal may vary greatly due to configuration or performance differences, and may include one or more central processing units (for example, one or more processors) and a memory, and one or more storage media for storing applications or data (for example, one or more mass storage devices). Among them, the memory and the storage media may be transient storage or persistent storage. The programs stored in the storage media may include one or more modules (not marked in the figure), and each module may include a series of instruction operations on the server terminal.

[0134] The server terminal may further include one or more power supplies, one or more wired or wireless network interfaces, one or more input / output interfaces, one or more keyboards, and / or one or more operating systems.

[0135] The server terminal may include a memory and one or more programs, where one or more programs are stored in the memory and are configured to be executed by one or more processors. One or more programs include processing for the server terminal in the method for constructing a power grid resource topology map based on data sharding storage of a distribution network as described above.

[0136] Those of ordinary skill in the art can understand that all or part of the steps for implementing the above embodiments can be completed by hardware, or can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable storage medium, and the storage medium mentioned above can be a read-only memory, etc.

[0137] The above are all preferred embodiments of this application, and the protection scope of this application is not limited thereby. Therefore, all equivalent changes made according to the structure, shape, and principle of this application shall be covered within the protection scope of this application.

[0138] Although the present invention is disclosed as above, the protection scope of the present invention is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and these changes and modifications will all fall within the protection scope of the present invention.

Claims

1. A method for constructing a power grid resource topology map based on distribution network data sharding storage, characterized in that: The method comprises: Receive distribution information of the power distribution equipment jurisdiction area input by the user, and divide the pre-built power distribution network topology data into multiple regional data slices according to the distribution information of the power distribution equipment jurisdiction area, each of the regional data slices corresponds to an independent storage unit; Dividing a plurality of topological data slices according to the feeders and transmission lines in each of the regional data slices; When a data upload request for the distribution network data to be stored is received, the distribution equipment jurisdiction area of ​​the distribution network data to be stored and the feeder ID or transmission line ID in the distribution network data to be stored are stored in a storage unit corresponding to the regional data slice, and the corresponding topology data slice is updated; The method comprises: Obtain query request information corresponding to each of the topological data slices, wherein the query request information includes a query history record and a query request time; Generate priority gradients corresponding to a plurality of topological data slices under a target area data slice according to pre-stored historical power consumption data of the distribution network and a plurality of query request information; When a plurality of distribution network data to be stored are received at the same time and stored in the storage unit corresponding to the target area data slice, the priority of storing the plurality of distribution network data to be stored is divided according to the priority gradient of the distribution network data to be stored corresponding to the topology data slice; The step of generating priority gradients corresponding to the plurality of topological data slices under the target area data slice according to the pre-stored historical power consumption data of the distribution network and the plurality of query request information includes: Generate an abnormal query probability at the current moment according to the abnormal working moments corresponding to the multiple bad working states in the historical power consumption data of the distribution network and the multiple query request information; According to the plurality of query request information corresponding to the target area data slice, the number of queries for each topological data slice under the target area data slice within a preset sampling time before the current moment is captured; Calculate and generate a current query probability according to the query quantity and a preset query peak value; A priority coefficient is calculated based on the current query probability and the abnormal query probability, and corresponding priority gradients are divided based on the priority coefficients corresponding to the plurality of topological data shards.

2. The method according to claim 1, characterized in that The topology data slice stores a single feeder and a collection of all electrical devices connected to the single feeder, or a single transmission line and a collection of all electrical devices connected to the single transmission line; The topology data slice also contains connection information between a single feeder and all corresponding electrical devices, or connection information between a single transmission line and all corresponding electrical devices.

3. The method according to claim 1, characterized in that The generating of the abnormal query probability at the current moment according to the abnormal working moments corresponding to the multiple bad working states in the historical power consumption data of the distribution network and the multiple query request information comprises: Generate the abnormal state probabilities of the multiple bad working states at the current moment according to the historical power consumption data of the distribution network and the pre-divided cycle period; Capturing topological query probabilities of a plurality of the bad working states according to the historical power consumption data of the distribution network and the plurality of the query request information; An abnormal query probability is generated by calculation according to the plurality of abnormal state probabilities and the plurality of topology query probabilities.

4. The method according to claim 3, characterized in that The generating of abnormal state probabilities at the current moment under various bad working states according to the historical power consumption data of the distribution network and the pre-divided cycle period includes: According to the pre-divided cycle periods and the pre-divided unit time periods in the cycle periods, statistics are collected on the abnormal state probabilities of being in the poor working state in the same unit time period belonging to multiple cycle periods and the current moment in the historical power consumption data of the distribution network.

5. The method according to claim 4, characterized in that The method of capturing topological query probabilities of multiple bad working states according to the historical power consumption data of the distribution network and the plurality of query request information includes: According to the historical power consumption data of the distribution network, marking the time periods within the preset review time after the multiple abnormal working moments as review time periods; According to all the query request information, the topology query probability of receiving the corresponding query request in the corresponding multiple review time periods under each of the bad working states is captured.

6. A system for constructing a power grid resource topology map based on distribution network data shard storage, characterized in that: The system includes a server terminal, and the server terminal includes, An information receiving module, used to receive the distribution information of the distribution equipment jurisdiction area input by the user, and divide the pre-built distribution network topology data into a plurality of regional data slices according to the distribution information of the distribution equipment jurisdiction area, each of which corresponds to an independent storage unit; A data partitioning module, used for partitioning a plurality of topological data slices according to the feeders and transmission lines in each of the regional data slices; A data receiving and storing module is used for, when receiving a data upload request for the distribution network data to be stored, storing the distribution equipment jurisdiction area of ​​the distribution network data to be stored and the feeder ID or transmission line ID in the distribution network data to be stored in a storage unit corresponding to the regional data slice, and updating the corresponding topology data slice; An information receiving module is used to obtain query request information corresponding to each topological data shard, where the query request information includes query history records and query request time; A priority division module is used to generate a priority gradient corresponding to multiple topological data slices under the target area data slice according to the pre-stored distribution network historical power consumption data and multiple query request information; A priority division module is used to divide the priority of storing the multiple distribution network data to be stored according to the priority gradient of the corresponding topological data slice in the distribution network data to be stored when multiple distribution network data to be stored are received at the same time and stored in the storage unit corresponding to the target area data slice; A data probability calculation module is used to generate an abnormal query probability at the current moment according to abnormal working moments corresponding to a plurality of bad working states in the historical power consumption data of the distribution network and a plurality of query request information; The data probability calculation module is used to capture the number of queries for each topological data shard under the target area data shard within a preset sampling time before the current moment according to multiple query request information corresponding to the target area data shard; The data probability calculation module is used to calculate and generate the current query probability according to the query quantity and the preset query peak value; The priority division module is used to calculate and generate a priority coefficient based on the current query probability and the abnormal query probability, and divide the corresponding priority gradient according to the priority coefficients corresponding to multiple topological data shards.

7. A server terminal, characterized in that: The server terminal includes a processor and a memory, wherein the memory stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the method for constructing a power grid resource topology map based on distribution network data sharding storage as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The storage medium stores at least one instruction, at least one program, a code set or an instruction set, and the at least one instruction, the at least one program, the code set or the instruction set are loaded and executed by the processor to implement the method for constructing a power grid resource topology map based on distribution network data sharding storage as described in any one of claims 1 to 5.

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