CN-121124343-B - Power grid multisource data acquisition resource optimization method based on adaptive scheduling

CN121124343BCN 121124343 BCN121124343 BCN 121124343BCN-121124343-B

Abstract

The invention discloses a power grid multisource data acquisition resource optimization method based on self-adaptive scheduling, which relates to the technical field of data acquisition and comprises the steps of acquiring power grid system information, taking power grid equipment as power grid topological nodes according to power grid equipment information in the power grid system information, acquiring power grid topological node information, and acquiring topological node connection information corresponding to the power grid topological nodes based on power grid line connection information. According to the invention, the power grid equipment is used as power grid topological nodes and power grid line connection information, a data basis is provided for the establishment of a subsequent topological model, a data standard is provided for the distance interval between topological nodes through the topological node reference distance and the topological node reference impedance, the power grid basic area information is obtained through dividing the power grid area, the data acquisition efficiency is improved, and the timeliness and the accuracy of data acquisition are ensured through the core node data acquisition period and the non-core node data acquisition period.

Inventors

WANG JING
WANG YICHEN
YANG YIHUA
MA YIWEN
Xiong xintian
LIU WENXIN
XU SHAOFEI
ZHU CHUNQIANG
DU GUOWEI
Dang ye
ZHAO KAIHANG
QUAN MEI
XUE JING
JING GANG
FENG MIAO

Assignees

西安电力高等专科学校

Dates

Publication Date: 20260512
Application Date: 20250902

Claims (9)

1. The power grid multisource data acquisition resource optimization method based on adaptive scheduling is characterized by comprising the following steps of: acquiring power grid system information, wherein the power grid system information comprises power grid area information, power grid equipment information and power grid line connection information; according to the power grid equipment information in the power grid system information, taking power grid equipment as a power grid topological node, and acquiring power grid topological node information; Based on the power grid line connection information, topology node connection information corresponding to the power grid topology nodes is obtained; Acquiring historical power grid data, wherein the historical power grid data comprises historical data corresponding to each power grid topological node; Acquiring power grid topology model information based on power grid topology structure analysis according to historical power grid data, power grid topology node information and topology node connection information, wherein the power grid topology model information comprises power grid topology node information and power grid topology connection information; dividing a power grid region according to the power grid topology model information to obtain power grid basic region information; acquiring power grid data according to the power grid basic area information; the method for obtaining the power grid topology model information based on the power grid topology structure analysis according to the historical power grid data, the power grid topology node information and the topology node connection information specifically comprises the following steps: Acquiring corresponding time stamp information according to historical power grid data; Taking the time stamp as an abscissa and the historical power grid data as an ordinate, and constructing a power grid data time graph corresponding to each power grid topological node; Acquiring a topological node reference distance and a topological node reference impedance based on a power grid data time graph; According to the topology node connection information, taking the ratio of the equipment distance corresponding to any two power grid topology nodes to the reference distance of the topology nodes as the first topology node distance corresponding to the two power grid topology nodes; Taking the ratio of node impedance corresponding to any two power grid topological nodes to the reference impedance of the topological nodes as the distance between the second topological nodes corresponding to the two power grid topological nodes; Taking the product of the distance between the first topological node and the distance between the second topological node, which correspond to any two power grid topological nodes, as the distance between the topological nodes, which correspond to the two power grid topological nodes, to obtain the information of the distance between the topological nodes; And constructing a power grid topology model according to the power grid topology node information, the topology node connection information and the topology node distance information, and obtaining power grid topology model information.
2. The method for optimizing power grid multi-source data acquisition resources based on adaptive scheduling according to claim 1, wherein the obtaining the topological node reference distance and the topological node reference impedance based on the power grid data time graph specifically comprises: According to the power grid data time graph, taking the ratio of the difference value of the historical power grid data corresponding to any two time stamps to the difference value of the two time stamps as a power grid data fluctuation coefficient; taking two power grid curve nodes corresponding to the maximum value of the power grid data fluctuation coefficient in the power grid data time curve graph as a curve mapping node group of the power grid data time curve graph; according to the curve mapping node group, taking a curve mapping node with a front time stamp in the curve mapping node group as a first curve mapping node and a curve mapping node with a rear time stamp as a second curve mapping node on the basis of the time stamp order; Traversing all power grid topological nodes according to the topological node connection information, taking any two power grid topological nodes which are connected with each other as a power grid topological node group, and obtaining power grid topological node group information; taking any one power grid topological node in the power grid topological node group as a first power grid topological node, and taking the other power grid topological node in the power grid topological node group as a second power grid topological node; acquiring curve mapping node groups corresponding to the first power grid topological node and the second power grid topological node; According to the curve mapping node group, taking the time stamp difference value of two curve mapping nodes corresponding to the first power grid topological node as a first time span coefficient, and taking the time stamp difference value of two curve mapping nodes corresponding to the second power grid topological node as a second time span coefficient; Taking the ratio of the first time span coefficient to the second time span coefficient as a curve mapping correction coefficient; and obtaining the reference distance and the reference impedance of the topological node according to the curve mapping correction coefficient.
3. The method for optimizing the power grid multisource data acquisition resources based on adaptive scheduling according to claim 2, wherein the method for acquiring the topological node reference distance and the topological node reference impedance according to the curve mapping correction coefficient specifically comprises the following steps: Taking a curve of the curve mapping node group interval in the power grid data time curve graph corresponding to the first power grid topological node as a power grid data reference curve; taking a curve of the curve mapping node group interval in the power grid data time curve graph corresponding to the second power grid topological node as a power grid data mapping curve; according to the curve mapping correction coefficient, taking a first curve mapping node in a curve mapping node group corresponding to a second power grid topological node as a reference, and carrying out equal proportion adjustment on a power grid data mapping curve to obtain a power grid data mapping correction curve; aligning a first curve mapping node corresponding to a first power grid topological node with a first curve mapping node corresponding to a second power grid topological node, and taking a triangular area formed by a power grid data reference curve and a power grid data mapping correction curve as a power grid data transfer offset coefficient; acquiring a power grid data transfer offset coefficient corresponding to each power grid topological node group according to the power grid topological node group information; taking a power grid topological node group corresponding to the minimum value of the power grid data transmission offset coefficient as a topological model reference node group; Acquiring equipment distance information and node impedance information corresponding to two power grid topological nodes in a topological model reference node group according to the topological model reference node group and the power grid equipment information; and taking the equipment distance information corresponding to the topological model reference node group as the topological node reference distance, and taking the node impedance information corresponding to the topological model reference node group as the topological node reference impedance.
4. The method for optimizing power grid multisource data acquisition resources based on adaptive scheduling according to claim 3, wherein the method is characterized by dividing power grid areas according to power grid topology model information to obtain power grid basic area information, and specifically comprises the following steps: S100, according to the power grid topology model information and the power grid topology node group information, obtaining topology node distance information corresponding to two power grid topology nodes in each power grid topology node group; s200, acquiring a power grid data transfer offset coefficient corresponding to each power grid topological node group; S300, taking the topological node distance corresponding to each power grid topological node group as an independent variable, taking a power grid data transmission offset coefficient as an independent variable, and acquiring a topological distance deviation coefficient of each power grid topological node group based on data fitting; S400, according to the power grid topology model information, based on power grid system design analysis, acquiring a data fluctuation threshold value and a data fluctuation minimum identification value corresponding to each power grid topology node; s500, taking any one power grid topological node as a core node, and acquiring a topological distance deviation coefficient of the power grid topological node and the core node; S600, taking the product of the minimum data fluctuation identification value corresponding to the core node and the topological node distance and the topological distance deviation coefficient as a fluctuation identification index; s700, comparing a data fluctuation threshold corresponding to a power grid topological node with a fluctuation identification index, and if the fluctuation identification index does not exceed the data fluctuation threshold, taking the power grid topological node as a non-core node and dividing the power grid topological node and the core node into the same type of nodes; S800, repeating the steps S500-S700 until all the power grid topological nodes are classified, and acquiring power grid topological node classification information; S900, dividing the same type of power grid topological nodes into the same area according to the power grid area information based on the power grid topological node classification information, and obtaining power grid basic area information.
5. The method for optimizing power grid multi-source data acquisition resources based on adaptive scheduling according to claim 4, wherein the method for acquiring power grid data according to power grid basic area information specifically comprises the following steps: acquiring core nodes corresponding to each power grid basic area according to the power grid basic area information; Acquiring historical power grid data corresponding to each core node according to the historical power grid data; According to the historical power grid data corresponding to each core node, taking the average value of the historical power grid data as a power grid data reference value of the core node; based on the time stamp information of the historical power grid data corresponding to each core node, taking the ratio of the difference value between the historical power grid data corresponding to each time stamp and the power grid data reference value as the data deviation reference coefficient of the core node; Taking the average value of the data deviation reference coefficients corresponding to all the time stamps in the historical power grid data corresponding to each core node as the data deviation coefficient corresponding to the core node; acquiring a first data acquisition period and a second data acquisition period based on the power grid data acquisition requirement, wherein the first data acquisition period is the data acquisition period of a core node, and the second data acquisition period is the data acquisition period of a non-core node; Taking the absolute value of the difference value between the data deviation coefficient corresponding to each core node and 1 as a data acquisition correction coefficient; taking the product of the data acquisition correction coefficient corresponding to each core node and the first data acquisition period as the core node data acquisition period corresponding to the core node; taking the product of the topological node distance between each non-core node and the core node in the power grid basic area and the topological distance deviation coefficient as a data difference identification coefficient corresponding to the non-core node; taking the ratio of the data acquisition correction coefficient to the data difference identification coefficient as a data acquisition secondary correction coefficient; Taking the product of the data acquisition secondary correction coefficient corresponding to each non-core node and the second data acquisition period as the non-core node data acquisition period corresponding to the non-core node; and acquiring power grid data of the power grid topological nodes in all power grid basic areas according to the core node data acquisition period and the non-core node data acquisition period corresponding to each power grid basic area.
6. An adaptive scheduling-based power grid multi-source data acquisition resource optimization system for implementing the optimization method according to any one of claims 1-5, comprising: The main control module is used for taking power grid equipment as power grid topological nodes according to power grid equipment information in power grid system information, acquiring power grid topological node information, taking power grid line connection information as a basis, acquiring topology node connection information corresponding to the power grid topological nodes, acquiring topology node reference distances and topology node reference impedances according to curve mapping correction coefficients, acquiring topology node distance information according to the topology node reference distances and the topology node reference impedances, constructing a power grid topological model according to the power grid topological node information, the topology node connection information and the topology node distance information, acquiring power grid topological model information, dividing a power grid region according to the power grid topological model information, acquiring power grid basic region information, acquiring core nodes corresponding to each power grid basic region according to the power grid basic region information, acquiring historical power grid data corresponding to each core node according to historical power grid data, taking a historical power grid data average value as a power grid data reference value of the core node, acquiring a core node data acquisition period and a non-core node data acquisition period according to the power grid data reference value, and acquiring power grid data basic data of all the power grid nodes in the power grid basic region according to the core node data acquisition period and the non-core node data acquisition period; The information acquisition module is used for acquiring grid system information, wherein the grid system information comprises grid area information, grid equipment information and grid line connection information, historical grid data are acquired, the historical grid data comprise historical data corresponding to each grid topological node, corresponding time stamp information is acquired according to the historical grid data, a time stamp is taken as an abscissa, the historical grid data are taken as an ordinate, and a grid data time graph corresponding to each grid topological node is constructed; The evaluation module is used for taking the ratio of the difference value of the historical power grid data corresponding to any two time stamps to the difference value of the two time stamps as a power grid data fluctuation coefficient, obtaining a curve mapping correction coefficient according to the power grid data fluctuation coefficient, carrying out equal proportion adjustment on the power grid data mapping curve according to the curve mapping correction coefficient by taking a first curve mapping node in a curve mapping node group corresponding to a second power grid topological node as a reference, obtaining a power grid data mapping correction curve, aligning the first curve mapping node corresponding to the first power grid topological node with a first curve mapping node corresponding to the second power grid topological node, and taking the triangular area formed by the power grid data reference curve and the power grid data mapping correction curve as a power grid data transmission offset coefficient; The display module is interacted with the main control module and is used for outputting and displaying power grid topology model information, power grid basic area information, core node data acquisition periods and non-core node data acquisition periods corresponding to each power grid basic area.
7. The adaptive scheduling-based power grid multi-source data acquisition resource optimization system according to claim 6, wherein the main control module specifically comprises: The control unit is used for dividing a power grid region according to power grid topology model information, acquiring power grid basic region information, acquiring core nodes corresponding to each power grid basic region according to the power grid basic region information, acquiring historical power grid data corresponding to each core node according to historical power grid data, taking a historical power grid data mean value as a power grid data reference value of the core node according to the historical power grid data corresponding to each core node, acquiring a core node data acquisition period and a non-core node data acquisition period according to the power grid data reference value, and acquiring power grid data of all power grid topological nodes in the power grid basic region according to the core node data acquisition period and the non-core node data acquisition period corresponding to each power grid basic region; The information receiving unit is interacted with the information acquisition module and the evaluation module and is used for receiving data and transmitting the data to the data model unit; the data model unit is used for taking power grid equipment as power grid topological nodes according to power grid equipment information in power grid system information, acquiring power grid topological node information, acquiring topological node connection information corresponding to the power grid topological nodes based on power grid line connection information, acquiring topological node reference distances and topological node reference impedance according to curve mapping correction coefficients, acquiring topological node distance information according to the topological node reference distances and the topological node reference impedance, constructing a power grid topological model according to the power grid topological node information, the topological node connection information and the topological node distance information, and acquiring power grid topological model information.
8. The power grid multi-source data acquisition resource optimization system based on adaptive scheduling according to claim 6, wherein the information acquisition module specifically comprises: The system comprises a first acquisition unit, a second acquisition unit and a control unit, wherein the first acquisition unit is used for acquiring power grid system information, the power grid system information comprises power grid area information, power grid equipment information and power grid line connection information, and acquiring historical power grid data, and the historical power grid data comprises historical data corresponding to each power grid topological node; the second acquisition unit is used for acquiring corresponding time stamp information according to the historical power grid data, taking the time stamp as an abscissa and the historical power grid data as an ordinate, and constructing a power grid data time graph corresponding to each power grid topological node.
9. The adaptive scheduling-based power grid multi-source data acquisition resource optimization system according to claim 6, wherein the evaluation module specifically comprises: the first evaluation unit is used for taking the ratio of the difference value of the historical power grid data corresponding to any two time stamps to the difference value of the two time stamps as a power grid data fluctuation coefficient according to a power grid data time curve graph, and acquiring a curve mapping correction coefficient according to the power grid data fluctuation coefficient; The second evaluation unit is used for carrying out equal proportion adjustment on the power grid data mapping curve by taking a first curve mapping node in a curve mapping node group corresponding to a second power grid topological node as a reference according to the curve mapping correction coefficient, obtaining a power grid data mapping correction curve, aligning the first curve mapping node corresponding to the first power grid topological node with the first curve mapping node corresponding to the second power grid topological node, and taking a triangular area formed by the power grid data reference curve and the power grid data mapping correction curve as a power grid data transmission offset coefficient.

Description

Power grid multisource data acquisition resource optimization method based on adaptive scheduling Technical Field The invention relates to the technical field of data acquisition, in particular to a power grid multisource data acquisition resource optimization method based on self-adaptive scheduling. Background Along with the continuous and rapid development of national economy and the continuous improvement of the living standard of people, the information quantity required by a power grid operation management system is larger and larger, and various applications and services put higher and higher requirements on the information quality, such as the reliability, the real-time performance, the communication capacity, the data integrity and the like of data, so that the requirements on the remote data acquisition and monitoring of a power system are also increased. The excessive high, low and fluctuation of the power grid data level can have serious influence on user load equipment, the running of the power grid self equipment, the grid loss of the power grid and the like. The reliability of the power grid data acquisition is improved, the integrity and timeliness of the data are guaranteed, and the method has important significance for enhancing the monitoring of the power grid data and improving the quality of the power grid data. At present, the condition of a power grid system cannot be accurately estimated, different power grid node characteristics are accurately analyzed according to the distribution condition of the power grid system, a proper data acquisition strategy cannot be determined according to historical data, the power grid data are always directly acquired in a fixed acquisition period in the prior art, all the nodes are further classified, then the fixed acquisition period is set for each type of node, abnormal power grid data cannot be timely found, the stability and the reliability of the power grid system are affected, but if the acquisition period is independently set for each node, the data processing amount is larger, the acquisition efficiency is lower, and the timeliness of the power grid data acquisition is affected. Disclosure of Invention In order to solve the technical problems, the technical scheme provides the power grid multisource data acquisition resource optimization method based on the self-adaptive scheduling, which solves the problems that the condition of a power grid system cannot be accurately estimated, different power grid node characteristics cannot be accurately analyzed according to the distribution condition of the power grid system, a proper data acquisition strategy cannot be determined according to historical data, the power grid data is always directly acquired in a fixed acquisition period in the prior art, all nodes are further classified, then the fixed acquisition period is set for each type of nodes, abnormal power grid data cannot be found in time, the stability and the reliability of the power grid system are influenced, and if the acquisition period is independently set for each node, the data processing amount is large, the acquisition efficiency is low, and the timeliness of the power grid data acquisition is influenced. In order to achieve the above purpose, the invention adopts the following technical scheme: a power grid multisource data acquisition resource optimization method based on self-adaptive scheduling comprises the following steps: acquiring power grid system information, wherein the power grid system information comprises power grid area information, power grid equipment information and power grid line connection information; according to the power grid equipment information in the power grid system information, taking power grid equipment as a power grid topological node, and acquiring power grid topological node information; Based on the power grid line connection information, topology node connection information corresponding to the power grid topology nodes is obtained; Acquiring historical power grid data, wherein the historical power grid data comprises historical data corresponding to each power grid topological node; Acquiring power grid topology model information based on power grid topology structure analysis according to historical power grid data, power grid topology node information and topology node connection information, wherein the power grid topology model information comprises power grid topology node information and power grid topology connection information; dividing a power grid region according to the power grid topology model information to obtain power grid basic region information; and acquiring power grid data according to the power grid basic area information. Preferably, the obtaining the power grid topology model information based on the power grid topology structure analysis according to the historical power grid data, the power grid topology node information and the topology node connection informati