CN-121440924-B - Power system state monitoring method, system, equipment and storage medium

CN121440924BCN 121440924 BCN121440924 BCN 121440924BCN-121440924-B

Abstract

The invention discloses a power system state monitoring method, a system, equipment and a storage medium, which relate to the technical field of power state monitoring, wherein the method comprises the steps of acquiring historical monitoring data of different parameters of each power node when generating early warning signals, analyzing the historical monitoring data to obtain an upper limit value and a lower limit value of a parameter early warning threshold limit value respectively corresponding to the different parameters of each power node, and determining early warning ranges respectively corresponding to the different power nodes; the method and the system have the advantages of defining node early warning relevance, accurately distinguishing multi-node fluctuation and single-node abnormality during real-time monitoring, avoiding false alarm, helping operation and maintenance personnel to quickly locate fault sources, and improving monitoring accuracy and system stability.

Inventors

Gao Yudou
ZHU YANJIE
HUANG ZUYUAN
LI SHENZHANG
ZHANG MEI
YOU SHAOHUA
GENG ZHENWEI

Assignees

云南电力试验研究院(集团)有限公司
云南电网有限责任公司数智运营中心

Dates

Publication Date: 20260512
Application Date: 20251217

Claims (8)

1. A method for monitoring a condition of an electrical power system, comprising: historical monitoring data of different parameters of each power node when an early warning signal is generated is obtained and analyzed, and an upper limit value and a lower limit value of a parameter early warning threshold value corresponding to the different parameters of each power node are obtained; based on the upper limit value and the lower limit value of the parameter early warning threshold value, determining the early warning ranges of different parameters corresponding to each node respectively; analyzing interaction ranges among the early warning ranges of all the power nodes, and generating interaction node lists corresponding to all the power nodes respectively; analyzing the interaction range among the early warning ranges of the power nodes, and generating the interaction node list corresponding to the power nodes respectively comprises the following steps: Selecting an early warning range corresponding to a target node from early warning ranges of all the power nodes, selecting a comparison node from the rest power nodes, acquiring the early warning range, drawing the early warning range and the comparison node in the same area, and determining an interaction range between the target node and the comparison node; Respectively calculating the early warning distance of each parameter in the early warning range of the target node and the interaction distance of each parameter in the interaction range, and calculating the interaction coefficient between the target node and the comparison node by combining the preset weight of each parameter based on the ratio of the interaction distance of each parameter to the early warning distance; Analyzing interaction ranges between the target node early warning range and other residual node early warning ranges one by one in the same way, calculating interaction coefficients between the target node and other nodes, taking corresponding power nodes with the interaction coefficients larger than a specific interaction threshold value as interaction nodes of the target node, sequencing the interaction nodes from large to small according to the interaction coefficients, obtaining an interaction node list corresponding to the target node, and binding the interaction node list with the target node; analyzing interaction ranges among other residual node early warning ranges one by one in the same way, obtaining interaction node lists corresponding to all power nodes respectively, and binding the interaction node lists with the corresponding power nodes; based on the parameter early warning threshold value and the interactive node list, real-time monitoring data of different parameters of each power node are obtained and analyzed in real time, and early warning signals are judged and generated; Based on the parameter early warning threshold value and the interactive node list, the real-time monitoring data of different parameters of each power node are obtained in real time, and the judging and generating of the early warning signal comprise the following steps: Acquiring real-time monitoring data of target parameters of a target node, comparing the real-time monitoring data with the upper limit value and the lower limit value of a parameter early-warning threshold corresponding to the parameters, if the parameter is larger than the upper limit value, generating an early warning signal, if the parameter is smaller than the lower limit value, not processing the early warning signal, and if the parameter is between the upper limit value and the lower limit value, primarily judging that the parameter is in an early warning state; if the preliminary judgment early warning state is established, acquiring an interactive node list of the node, acquiring real-time monitoring data of the same parameters of each interactive node in the list, judging early warning signals of the parameters of each interactive node in the same comparison mode, and counting the number of the early warning signals corresponding to the interactive node list.
2. The method for monitoring the state of a power system according to claim 1, wherein the step of obtaining and analyzing the historical monitoring data of each power node when different parameters generate the early warning signal to obtain the upper limit value and the lower limit value of the parameter early warning threshold value corresponding to the different parameters of each power node respectively comprises the steps of: Randomly selecting one from all power nodes of the power system as a target node, and randomly selecting one from different parameters as a target parameter; acquiring historical monitoring data when target parameters of a target node generate early warning signals for a plurality of times, and analyzing statistical characteristics of the historical monitoring data; Based on the statistical characteristics, the upper limit value and the lower limit value of the parameter early-warning threshold limit value of the target parameter at the target node are determined by combining with a preset adjustment factor.
3. The method for monitoring the state of a power system according to claim 2, wherein the steps of obtaining and analyzing the historical monitoring data of each power node when different parameters generate the early warning signal, and obtaining the upper limit value and the lower limit value of the parameter early warning threshold value corresponding to each power node respectively, further comprise: Repeating the steps of selecting parameters, analyzing historical monitoring data and determining parameter early warning threshold values, and analyzing monitoring data when other residual parameters of the target node generate early warning signals one by one to obtain upper limit values and lower limit values of the parameter early warning threshold values corresponding to different parameters at the target node respectively; And repeating the steps of selecting the target node and analyzing the parameter threshold values, and analyzing the monitoring data one by one when other residual nodes generate the early warning signals to obtain the upper limit value and the lower limit value of the parameter early warning threshold values respectively corresponding to different parameters at each power node.
4. A method for monitoring a state of a power system according to claim 3, wherein determining the pre-warning ranges of the different parameters at each node based on the upper limit value and the lower limit value of the pre-warning threshold value of the parameters comprises: Taking the power node with the parameter early warning threshold value analysis as an object, and sequentially taking the power node as a target power node; Drawing an area circle with a preset radius, drawing parameter lines representing each parameter at equal intervals according to the number of the parameters by taking the origin of the area circle as an endpoint, and marking nodes corresponding to the parameter unit values on the parameter lines; Marking corresponding data points on corresponding parameter lines according to the upper limit value of the parameter early warning threshold value of different parameters at the target power node, and sequentially connecting the corresponding data points to generate an external boundary line of the target power node; marking corresponding data points on corresponding parameter lines according to the lower limit value of the parameter early warning threshold value of different parameters at the target power node, and sequentially connecting the corresponding data points to generate an inner boundary line of the target power node; determining the range between the external boundary line and the internal boundary line of the target power node as the early warning range of the target power node; And drawing an area circle and a parameter line according to the power node serving as a target object, marking the node, respectively marking data points according to the upper limit value and the lower limit value of the parameter early warning threshold value, and connecting the data points to generate an external boundary line and an internal boundary line, further determining the operation flow of the early warning range, analyzing other residual nodes, and determining the early warning range of different parameters respectively corresponding to each node.
5. The method for monitoring the state of a power system according to claim 4, wherein the real-time acquisition of real-time monitoring data for analyzing different parameters of each power node based on the parameter early-warning threshold value and the interactive node list, and the determining and generating the early-warning signal comprise: Calculating the ratio of the number of the early warning signals to the total number of the interaction nodes, comparing the ratio with a preset threshold value, if the ratio is larger than the preset threshold value, judging that the target parameter abnormality of the target node is fluctuation caused by normal interaction between the nodes, generating no early warning signal, otherwise, judging that the target parameter abnormality is independent abnormality, generating an abnormality signal and sending the corresponding power node and the abnormality parameter to a manager; And analyzing the real-time monitoring data of different parameters of each power node according to the operation process of acquiring the node target parameter real-time monitoring data, comparing the node target parameter real-time monitoring data with a parameter early-warning threshold value, judging the early-warning state, counting the number of the interactive node early-warning signals, calculating the ratio and comparing the ratio with a preset threshold value to judge whether to generate the early-warning signals, and generating the early-warning signals corresponding to the different parameters of each power node.
6. A power system condition monitoring system applying the method of any one of claims 1-5, comprising: the historical data threshold analysis module is used for acquiring and analyzing historical monitoring data of each power node when different parameters generate early warning signals to obtain an upper limit value and a lower limit value of a parameter early warning threshold value corresponding to the different parameters of each power node respectively; The early warning range definition module is used for determining early warning ranges of different parameters corresponding to each node respectively based on the upper limit value and the lower limit value of the parameter early warning threshold value; The interactive node list generation module is used for analyzing the interactive range among the early warning ranges of all the power nodes and generating interactive node lists corresponding to all the power nodes respectively; analyzing the interaction range among the early warning ranges of the power nodes, and generating the interaction node list corresponding to the power nodes respectively comprises the following steps: Selecting an early warning range corresponding to a target node from early warning ranges of all the power nodes, selecting a comparison node from the rest power nodes, acquiring the early warning range, drawing the early warning range and the comparison node in the same area, and determining an interaction range between the target node and the comparison node; Respectively calculating the early warning distance of each parameter in the early warning range of the target node and the interaction distance of each parameter in the interaction range, and calculating the interaction coefficient between the target node and the comparison node by combining the preset weight of each parameter based on the ratio of the interaction distance of each parameter to the early warning distance; Analyzing interaction ranges between the target node early warning range and other residual node early warning ranges one by one in the same way, calculating interaction coefficients between the target node and other nodes, taking corresponding power nodes with the interaction coefficients larger than a specific interaction threshold value as interaction nodes of the target node, sequencing the interaction nodes from large to small according to the interaction coefficients, obtaining an interaction node list corresponding to the target node, and binding the interaction node list with the target node; analyzing interaction ranges among other residual node early warning ranges one by one in the same way, obtaining interaction node lists corresponding to all power nodes respectively, and binding the interaction node lists with the corresponding power nodes; The real-time data early warning judging module is used for acquiring and analyzing real-time monitoring data of different parameters of each power node in real time based on the parameter early warning threshold value and the interactive node list, and judging and generating early warning signals; Based on the parameter early warning threshold value and the interactive node list, the real-time monitoring data of different parameters of each power node are obtained in real time, and the judging and generating of the early warning signal comprise the following steps: Acquiring real-time monitoring data of target parameters of a target node, comparing the real-time monitoring data with the upper limit value and the lower limit value of a parameter early-warning threshold corresponding to the parameters, if the parameter is larger than the upper limit value, generating an early warning signal, if the parameter is smaller than the lower limit value, not processing the early warning signal, and if the parameter is between the upper limit value and the lower limit value, primarily judging that the parameter is in an early warning state; if the preliminary judgment early warning state is established, acquiring an interactive node list of the node, acquiring real-time monitoring data of the same parameters of each interactive node in the list, judging early warning signals of the parameters of each interactive node in the same comparison mode, and counting the number of the early warning signals corresponding to the interactive node list.
7. An electronic device, comprising: A memory and a processor; The memory is for storing computer executable instructions, the processor being for executing the computer executable instructions which when executed by the processor implement the steps of the method of any one of claims 1 to 5.
8. A computer-readable storage medium, characterized in that it stores computer-executable instructions which, when executed by a processor, implement the steps of the method of any one of claims 1 to 5.

Description

Power system state monitoring method, system, equipment and storage medium Technical Field The present invention relates to the field of power state monitoring technologies, and in particular, to a method, a system, an apparatus, and a storage medium for monitoring a power system state. Background With the high-proportion access of new energy in the power system, the fluctuation of the operation parameters of each power node is greatly enhanced, which forms a great challenge for the safe and stable operation of the power system. Accurate monitoring and early warning of power node parameters become key points for guaranteeing reliable operation of a power system, so that how to improve accuracy and reliability of the monitoring system, avoid misjudgment and delay fault processing become technical problems to be solved urgently. At present, a power system generally adopts a mode of being provided with various monitoring terminals, acquires a plurality of key parameter data such as voltage, current, temperature, vibration and the like in real time, and sends out an early warning signal when the parameters exceed a preset static threshold value. However, this conventional monitoring approach has significant drawbacks. Because the parameter early warning threshold regions of all nodes of the power system are possibly overlapped in a crossing way, the system is easy to generate misjudgment in the monitoring process, and sends out wrong early warning signals, so that the reliability and the accuracy of the monitoring system are reduced. In addition, the existing system only analyzes parameter states independently for single nodes, and the interactivity of the early warning areas among the nodes is ignored. When the power grid trend is suddenly changed, a plurality of associated nodes often enter an early warning interval at the same time and are misjudged as multipoint faults, so that operation and maintenance personnel are difficult to quickly locate a real fault source and possibly ignore a real independent fault. Disclosure of Invention The present invention has been made in view of the above-described problems. Therefore, the invention solves the technical problems that a plurality of nodes trigger early warning at the same time in the interaction range, prompt systematic risk, and the early warning system sends out a plurality of early warning signals, so that operation and maintenance personnel can not quickly locate a real fault source in a large amount of information, and delay processing due to misjudgment. In order to solve the technical problems, the invention provides the following technical scheme: In a first aspect, the present invention provides a method for monitoring a state of an electric power system, including: historical monitoring data of different parameters of each power node when an early warning signal is generated is obtained and analyzed, and an upper limit value and a lower limit value of a parameter early warning threshold value corresponding to the different parameters of each power node are obtained; determining an early warning range corresponding to each power node respectively based on the upper limit value and the lower limit value of the parameter early warning threshold value; analyzing interaction ranges among the early warning ranges of all the power nodes, and generating interaction node lists corresponding to all the power nodes respectively; Based on the parameter early warning threshold value and the interactive node list, real-time monitoring data of different parameters of each power node are obtained in real time, and early warning signals are judged and generated. As a preferable aspect of the power system condition monitoring method, wherein: The step of obtaining and analyzing the historical monitoring data of each power node when different parameters generate the early warning signals, and the step of obtaining the upper limit value and the lower limit value of the parameter early warning threshold value corresponding to the different parameters of each power node respectively comprises the following steps: Randomly selecting one from all power nodes of the power system as a target node, and randomly selecting one from different parameters as a target parameter; acquiring historical monitoring data when target parameters of a target node generate early warning signals for a plurality of times, and analyzing statistical characteristics of the historical monitoring data; Based on the statistical characteristics, the upper limit value and the lower limit value of the parameter early-warning threshold limit value of the target parameter at the target node are determined by combining with a preset adjustment factor. As a preferable aspect of the power system condition monitoring method, wherein: The step of obtaining and analyzing the historical monitoring data of each power node when different parameters of each power node generate the early warning signals, and the s