CN-121036056-B - Cross-region power quality data aggregation and optimization control method and device

CN121036056BCN 121036056 BCN121036056 BCN 121036056BCN-121036056-B

Abstract

The application relates to a trans-regional power quality data aggregation and optimization control method and device. The method comprises the steps of acquiring all power parameters in power systems of different power grid areas in real time through a multi-protocol adaptive interface of an edge intelligent control terminal, preprocessing data to obtain power system acquisition data of the power grid areas, fusing the power system acquisition data of the power grid areas, adding area labels of the power grid areas into the fused data to obtain a power data aggregation result, carrying out power risk assessment on power quality indexes of the power grid areas and power flow coherence indexes of the power grid areas according to the power data aggregation result to obtain a power abnormality assessment result, generating a control strategy based on the power abnormality assessment result, and sending the control strategy to the power systems of the power grid areas, wherein the control strategy is a strategy for carrying out differential power optimization control on the different power grid areas. By adopting the method, the cooperative control efficiency of the electric energy quality can be improved.

Inventors

KUANG YE
ZHOU JIN
CAI WENTING
XU CHUN
DONG XIAOYIN
SUN GUANGHUI
WU DAN
YANG YUCHAO
WU JIAWEN
LIN JUNHONG

Assignees

南方电网数字电网研究院股份有限公司

Dates

Publication Date: 20260512
Application Date: 20251022

Claims (9)

1. The cross-regional power quality data aggregation and optimization control method is characterized by being applied to an edge intelligent control terminal, and comprises the following steps: acquiring various electric power parameters in electric power systems of different power grid areas in real time through a multi-protocol adaptation interface of the edge intelligent control terminal to perform data preprocessing, so as to obtain electric power system acquisition data of each power grid area; The method comprises the steps of obtaining an electric power data aggregation result by fusing acquired data of electric power systems of all power grid areas and adding area labels of all power grid areas into the fused data, wherein the area labels are used for marking data sources; The power flow coherence index is dynamically updated by the edge intelligent control terminal based on real-time communication among the power grid areas and is used for representing the power transmission coherence coefficient between the corresponding power grid area and other power grid areas; generating a control strategy based on the electric energy abnormality evaluation result, and sending the control strategy to the electric power system of each power grid area, wherein the control strategy is a strategy for performing differentiated electric energy optimization control on different power grid areas; the method further comprises the steps of adopting power flow coherence indexes of each power grid region under different detection periods to construct time sequence vectors of the power flow coherence indexes of each power grid region, determining a target electric energy abnormality type according to the similarity degree between the time sequence vectors and abnormal sample sequence vectors, and taking a preset control strategy corresponding to the target electric energy abnormality type as an electric energy optimization control strategy; comparing the time sequence vector with a template library, matching the similarity of the time sequence vector and the abnormal sample sequence vector corresponding to various abnormal types stored in the template library according to a similarity algorithm, and taking the abnormal type corresponding to the matching result with the highest similarity as the target electric energy abnormal type; the method further comprises the following steps of obtaining the similarity: Assuming that the time series vector X is The abnormal sample sequence vector Y is The local distance D (i, j) of the i-th element of X and the j-th element of Y is: Where e is a natural constant, point x is the number of power transmission nodes included in the region corresponding to X, line x is the number of power transmission paths included in the region corresponding to X, point y is the number of power transmission nodes included in the region corresponding to Y, line y is the number of power transmission paths included in the region corresponding to Y, vpoint is the average of the numbers of power transmission nodes included in the respective regions, vline is the average of the numbers of power transmission paths included in the respective regions, An element value of the i-th element of X, An element value of the j-th element of Y; substituting the obtained local distances into a dynamic time warping algorithm to obtain the similarity.
2. The method according to claim 1, wherein the performing the power risk assessment with the power flow coherence index of each power grid region according to the power quality index of each power grid region determined according to the power data aggregation result to obtain a power abnormality assessment result includes: Acquiring reference information corresponding to different power quality indexes respectively to perform power quality index comparison, and acquiring normal state information of the power flow coherence indexes to perform power flow coherence index comparison; if the electric energy quality index comparison result is detected to be abnormal, and/or the power flow coherence index comparison result is/are detected to be abnormal, determining that the electric energy abnormality assessment result is that the electric energy abnormality exists.
3. The method according to claim 2, wherein the method further comprises: Generating a power quality index change function according to the power quality index and the historical index data of each power grid area; Based on the power quality index change function, obtaining a predicted power quality index of each power grid area; and comparing the predicted power quality index of each power grid area with the reference information to obtain a power risk prediction result.
4. The method according to claim 1, wherein the method further comprises: determining the number of power transmission paths connected with other power grid areas in any power grid area based on the number of power transmission nodes in any power grid area; and calculating the power flow coherence index of any power grid region according to the detection designated time period and the number of the electric energy transmission paths.
5. The method according to claim 2, wherein the method further comprises: when abnormal decline of the power flow coherence indexes of the power grid areas is detected, determining a target power grid area from the power grid areas, wherein the decline amplitude between the power flow coherence indexes of the target power grid area and the normal state information is maximum; and executing abnormal source regulation and control processing by analyzing the abnormal state of each electric energy transmission path in the target power grid area.
6. The device is characterized by being applied to an edge intelligent control terminal, and comprises: the power data acquisition module is used for acquiring various power parameters in the power systems of different power grid areas in real time through the multi-protocol adaptation interface of the edge intelligent control terminal to perform data preprocessing so as to obtain power system acquisition data of each power grid area; The power data aggregation module is used for obtaining a power data aggregation result by fusing the acquired data of the power systems of the power grid areas and adding area labels of the power grid areas into the fused data, wherein the area labels are used for marking data sources; the power flow coherence index is dynamically updated by the edge intelligent control terminal based on real-time communication among the power grid areas and is used for representing the power transmission coherence coefficient between the corresponding power grid area and other power grid areas; the control strategy generation module is used for generating a control strategy based on the electric energy abnormality evaluation result and sending the control strategy to the electric power system of each power grid area, wherein the control strategy is a strategy for performing differentiated electric energy optimization control on different power grid areas; The system comprises a coherence index regulation module, a target electric energy abnormality type, a preset control strategy corresponding to the target electric energy abnormality type, a power optimization control strategy and a power optimization control module, wherein the coherence index regulation module is used for constructing a time sequence vector of the power flow coherence index of each power grid region by adopting the power flow coherence index of each power grid region under different detection periods; The coherence index regulation module is further used for comparing the time sequence vector with a template library, matching the similarity of the time sequence vector and the abnormal sample sequence vector corresponding to various abnormal types stored in the template library according to a similarity algorithm, and taking the abnormal type corresponding to the matching result with the highest similarity as the target electric energy abnormal type; the coherence index regulation module is further configured to obtain the similarity by assuming that the time sequence vector X is The abnormal sample sequence vector Y is The local distance D (i, j) of the i-th element of X and the j-th element of Y is: Where e is a natural constant, point x is the number of power transmission nodes included in the region corresponding to X, line x is the number of power transmission paths included in the region corresponding to X, point y is the number of power transmission nodes included in the region corresponding to Y, line y is the number of power transmission paths included in the region corresponding to Y, vpoint is the average of the numbers of power transmission nodes included in the respective regions, vline is the average of the numbers of power transmission paths included in the respective regions, An element value of the i-th element of X, An element value of the j-th element of Y; substituting the obtained local distances into a dynamic time warping algorithm to obtain the similarity.
7. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 5 when the computer program is executed.
8. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 5.
9. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 5.

Description

Cross-region power quality data aggregation and optimization control method and device Technical Field The present application relates to the field of power systems, and in particular, to a method, an apparatus, a computer device, a computer readable storage medium, and a computer program product for cross-regional power quality data aggregation and optimization control. Background With the development of a novel power system towards the high-proportion renewable energy source access and the multi-energy complementation direction, the inter-regional power grid interconnection scale is continuously expanded, and the electric energy quality monitoring and cooperative control face challenges of high isomerism of power grid data in different regions, insufficient response instantaneity under the fluctuation of new energy sources and the randomness of loads, and the like. In the traditional technology, a centralized cloud processing mode is generally adopted, massive original data needs to be transmitted, requirements on data throughput and time delay are difficult to meet, sudden electric energy conditions cannot be handled, traditional electric energy quality detection is generally limited to single-area independent monitoring, only analysis is conducted on electric power parameters of the area, a cooperative control strategy cannot be formed, cross-area abnormal sources are more difficult to accurately identify, and improvement of overall electric energy quality of a power grid is restricted. Disclosure of Invention In view of the foregoing, it is desirable to provide a method, apparatus, computer device, computer readable storage medium, and computer program product for cross-regional power quality data aggregation and optimization control. In a first aspect, the present application provides a cross-regional power quality data aggregation and optimization control method, which is applied to an edge intelligent control terminal, and the method includes: acquiring various electric power parameters in electric power systems of different power grid areas in real time through a multi-protocol adaptation interface of the edge intelligent control terminal to perform data preprocessing, so as to obtain electric power system acquisition data of each power grid area; The method comprises the steps of obtaining an electric power data aggregation result by fusing acquired data of electric power systems of all power grid areas and adding area labels of all power grid areas into the fused data, wherein the area labels are used for marking data sources; The power flow coherence index is dynamically updated by the edge intelligent control terminal based on real-time communication among the power grid areas and is used for representing the power transmission coherence coefficient between the corresponding power grid area and other power grid areas; And generating a control strategy based on the electric energy abnormality evaluation result, and sending the control strategy to the electric power system of each power grid area, wherein the control strategy is a strategy for performing differentiated electric energy optimization control on different power grid areas. In one embodiment, the electrical energy quality index of each power grid area determined according to the electrical power data aggregation result and the power flow coherence index of each power grid area perform electrical energy risk assessment to obtain an electrical energy anomaly assessment result, including: Acquiring reference information corresponding to different power quality indexes respectively to perform power quality index comparison, and acquiring normal state information of the power flow coherence indexes to perform power flow coherence index comparison; if the electric energy quality index comparison result is detected to be abnormal, and/or the power flow coherence index comparison result is/are detected to be abnormal, determining that the electric energy abnormality assessment result is that the electric energy abnormality exists. In one embodiment, the method further comprises: Generating a power quality index change function according to the power quality index and the historical index data of each power grid area; Based on the power quality index change function, obtaining a predicted power quality index of each power grid area; and comparing the predicted power quality index of each power grid area with the reference information to obtain a power risk prediction result. In one embodiment, the method further comprises: determining the number of power transmission paths connected with other power grid areas in any power grid area based on the number of power transmission nodes in any power grid area; and calculating the power flow coherence index of any power grid region according to the detection designated time period and the number of the electric energy transmission paths. In one embodiment, the method further comprises: when abnormal d