An integrated operation monitoring method for power grid information security

Abstract

This invention relates to the field of power technology, specifically to an integrated operation monitoring method for power grid information security. The method includes: acquiring electrical parameter information of distribution equipment from power grid information; forming a power grid topology using the distribution equipment as power grid nodes; selecting current interaction regions; performing a two-layer mapping of each power grid node; acquiring abnormal events of each power grid node from the upload cycle of power grid information within a preset time period; defining the temporal interaction form of power grid information based on the interaction frequency and type of abnormal events; constructing a node change matrix; obtaining an interaction update sequence using the propagation path of the node change matrix under chain propagation; acquiring the interaction target of each power grid node from the interaction update sequence; determining a current compensation strategy based on the interaction target of each power grid node; performing interaction evaluation on each power grid node included in the current compensation strategy; and adjusting the switches corresponding to each power grid node; thereby improving the stability and efficiency of power grid operation.

Description

Technical Field

[0001] This invention relates to the field of power technology, specifically to an integrated operation monitoring method for power grid information security. Background Technology

[0002] Traditional dynamic adjustment of distribution networks involves modifying the existing network based on an analysis of various aspects to optimize one or more of these aspects. This may include dynamic load, load forecasting, system network losses, voltage levels, and power supply reliability. However, this often leads to a lack of correlation between the electrical parameters of distribution equipment and the physical topology during network operation monitoring. This can result in insufficient accuracy in locating anomalies and the formation of data silos. Furthermore, it necessitates tracking the dynamic changes of various electrical parameters to prevent overcompensation or undercompensation.

[0003] For example, Chinese Patent Publication No. CN115663807A discloses a robust distribution network method based on predicted load and distributed generation output, relating to the field of power technology. The method includes: when the load value of any node in the current power grid structure exceeds a preset load value, performing load prediction on the power grid for future time periods based on historical data to obtain the load data of each node for the future time period; using a clustering algorithm to cluster the load data of each current node and the load data of each node for the future time period to obtain load data with k cluster centers; constructing a dynamic structure model of the power grid based on the load data of the k cluster centers; and solving the dynamic structure model using a search algorithm to obtain the optimal solution corresponding to each cluster center and adjusting the current power grid network structure according to the optimal solution.

[0004] For example, Chinese Patent Publication No. CN117639042A discloses a method, device, electronic equipment, and medium for loss reduction power supply control in medium and low voltage distribution networks. One specific implementation of this method includes: acquiring initial distribution network power values, distribution network output device information, and distribution network energy storage device information; generating a random power supply planning information set; based on the initial distribution network power values ​​and distribution network energy storage device information, initializing each random power supply planning information in the random power supply planning information set to generate initial power supply planning information, thus obtaining an initial power supply planning information set; performing planning processing on the initial power supply planning information set based on the distribution network output device information to obtain target power supply planning information; and controlling the associated distribution network energy storage system to supply power based on the target power supply planning information.

[0005] Existing technologies describe how to identify predicted load output by clustering predicted loads and how to explain the number of iterations in power grid planning and scheduling. However, in the power grid topology, if there are corresponding anomalies in the power grid nodes on the topology, it is difficult to identify the working status of the power distribution equipment represented by each power grid node by simply using load clustering and power planning. This makes it impossible to detect the anomalies of the power grid nodes connected to the relevant power distribution equipment in a timely manner when there are power grid scheduling anomalies, resulting in reduced accuracy in anomaly location and losses in power scheduling. Summary of the Invention

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: an integrated operation monitoring method for power grid information security, comprising: S1, acquiring electrical parameter information of power distribution equipment in power grid information, forming a power grid topology structure by using the power distribution equipment as power grid nodes according to the connection relationship of the power distribution equipment, and selecting the current interaction area based on the distance between each power grid node on the topology structure and the dispatch area during current interaction.

[0007] S2 performs a two-layer mapping of the physical and information layers of each power grid node in the current interaction area. Based on the upload cycle of power grid information within a preset time period, it extracts features of the electrical parameter information of each power grid node in the current interaction area, obtains abnormal events of each power grid node, and defines the time interaction form of power grid information based on the interaction frequency and interaction type of abnormal events.

[0008] S3. Based on the time-based interaction of power grid information, a node change matrix is ​​constructed; using the transmission path of the node change matrix under chain propagation, the interaction update sequence of the current interaction region is obtained.

[0009] S4. Obtain the interaction targets of each power grid node from the interaction update sequence, and determine the current compensation strategy under different current conditions based on the interaction targets of each power grid node.

[0010] S5 performs interactive evaluation of each grid node included in the current compensation strategy and adjusts the corresponding switches of each grid node.

[0011] The beneficial effects of this invention are as follows: First, this invention constructs a power grid topology based on the connection relationship of power distribution equipment, combines the values ​​of electrical parameters on the power grid topology, integrates data, identifies the current interaction area where the current loss of each power grid node is minimized, and determines the operating status of the power distribution equipment represented by each power grid node during power dispatch, thereby perceiving the overall global state of the power grid and enabling timely identification of abnormal conditions of each power grid node when viewing the operating status of each power grid node.

[0012] Second, this invention extracts various abnormal events under abnormal power grid dispatch by associating the topology of power grid nodes with the physical location of equipment. It maps these abnormal events with the topology and physical location of power grid nodes, enabling timely detection of the relative number of anomalies occurring in different data upload cycles during power dispatch. These numbers are combined with the corresponding locations of power grid nodes to identify abnormal power grid nodes during anomaly detection. At the same time, it generates thresholds for dynamic baseline reference data based on historical data to achieve dynamic updates of anomaly features, thereby improving the timeliness and accuracy of anomaly detection.

[0013] Third, this invention identifies the relative changes of each power grid node by using its interaction frequency, duration, and power gradient, thereby quantifying the abnormal propagation path of the power grid node during power dispatch anomalies and providing a basis for accurate compensation. It then performs current compensation on these power grid nodes with abnormal propagation, locates the compensation target based on the minimum value of current branch interaction types, and locates the target value by combining the average and limit values ​​of current, voltage, and power. Finally, it performs power compensation on the areas that need power compensation, thereby achieving dynamic adaptation and economic optimization of the compensation strategy.

[0014] Fourth, this invention combines interaction frequency and operating cost to screen target areas, and then closes the target area switch according to the principle of maximum similarity and disconnects the compensation device for non-target areas; thereby controlling the scheduling mode of each power grid node in the power system to prevent losses caused by excessive or insufficient power scheduling and improve the overall system's processing speed under power scheduling anomalies. Attached Figure Description

[0015] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0016] Figure 1 This is a flowchart illustrating an integrated operation monitoring method for power grid information security.

[0017] Figure 2 This is a flowchart illustrating step S1 of an integrated power grid information security operation monitoring method.

[0018] Figure 3 This is a flowchart illustrating step S2 of an integrated power grid information security operation monitoring method.

[0019] Figure 4 This is a flowchart illustrating step S3 of an integrated power grid information security operation monitoring method.

[0020] Figure 5 This is a flowchart illustrating step S4 of an integrated power grid information security operation monitoring method.

[0021] Figure 6This is a flowchart illustrating step S5 of an integrated power grid information security operation monitoring method. Detailed Implementation

[0022] The embodiments of the present invention are described in detail below. The embodiments described below are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention. Where specific techniques or conditions are not specified in the embodiments, they shall be performed in accordance with the techniques or conditions described in the literature in the art or in accordance with the product manual.

[0023] See Figure 1 A method for integrated operation monitoring of power grid information security includes: S1, acquiring electrical parameter information of power distribution equipment in power grid information, forming a power grid topology by using the power distribution equipment as power grid nodes according to the connection relationship of the power distribution equipment, and selecting the current interaction area based on the distance between each power grid node on the topology and the dispatch area during current interaction.

[0024] S2 performs a two-layer mapping of the physical and information layers of each power grid node in the current interaction area. Based on the upload cycle of power grid information within a preset time period, it extracts features of the electrical parameter information of each power grid node in the current interaction area, obtains abnormal events of each power grid node, and defines the time interaction form of power grid information based on the interaction frequency and interaction type of abnormal events.

[0025] S3. Based on the time-based interaction of power grid information, a node change matrix is ​​constructed; using the transmission path of the node change matrix under chain propagation, the interaction update sequence of the current interaction region is obtained.

[0026] S4. Obtain the interaction targets of each power grid node from the interaction update sequence, and determine the current compensation strategy under different current conditions based on the interaction targets of each power grid node.

[0027] S5 performs interactive evaluation of each grid node included in the current compensation strategy and adjusts the corresponding switches of each grid node.

[0028] The current interaction region refers to the process of dynamically adjusting the current distribution between regions according to changes in grid load. The current value and adjustment location of the current interaction at this time are set as the current interaction region in the grid topology. Power describes the magnitude of the power interaction during the current interaction, and is used to describe the current change during the current interaction process. The dispatch region is the relative location of the current to be quickly dispatched to restore power supply or support other regions in emergency situations. This region is the region that needs to be dispatched when completing current dispatch and interaction.

[0029] Preferably, the electrical parameter information includes current, voltage, and power.

[0030] In step S1, the main focus is on describing the current interaction form between the various devices and the current values ​​in the power grid information, and determining whether there are various anomalies under the current interaction or how to train the calculation method of the current interaction.

[0031] Preferably, the power information includes current, power, voltage, equipment location, communication traffic data, etc. of multiple power distribution equipment. The equipment location of the power distribution equipment at this time is regarded as each power grid node in its power grid topology to complete the extraction of current and power. As for the dispatch area, it describes the location corresponding to each power distribution equipment when power allocation is carried out. This area represents the required current and power, as well as the node that needs to be dispatched. These contents are summarized as the current interaction area.

[0032] like Figure 2 As shown, the implementation of step S1 includes: S11, in the power distribution equipment's on state, constructing at least one hierarchical connection relationship for the power distribution equipment based on its location. The hierarchical connection relationship indicates that the power distribution equipment is located in any one of the station control management layer, network communication layer, and field equipment layer, which is used to describe the location of the power distribution equipment in the physical structure and information space.

[0033] S12 utilizes the hierarchical connection relationship of power distribution equipment to generate the power grid topology of the power distribution equipment, and integrates the data of each power grid node according to the electrical parameter information collected on the power grid topology.

[0034] S13 monitors the electrical parameter information of each power grid node, and divides the dispatch area based on the fluctuation ratio of the electrical parameter information of each power grid node and the distance between each power grid node.

[0035] S14: Set the area radius with the scheduling area as the center. When the current loss of each power grid node within the area radius is minimized, output the power grid nodes within the area radius as the current interaction area.

[0036] At this point, the electrical parameter information collected from multiple power distribution devices is integrated, and then the distance and other relationships between these normally operating nodes and the predefined scheduling areas are integrated to determine which power distribution devices and their corresponding grid locations are selected for power scheduling when some areas require current scheduling, in order to maintain or restore the normal operation of other areas.

[0037] Preferably, each power grid node in the power grid topology represents a variety of power distribution equipment, such as power plants, substations, distribution cabinets, and power users. Power users represent units that consume electricity, such as residences and factories, and are the final load points of the power system.

[0038] Preferably, the method for dividing the dispatch area is as follows: the distance between each power grid node in the power grid topology is calculated using the admittance matrix; the ratio of the average power difference between each power grid node at continuous time points to the sum of the average power differences of all power grid nodes is used as the content of the fluctuation ratio of electrical parameter information, and this ratio is used as the weight of each power grid node; based on the weight and distance of each power grid node, each power grid node is clustered, and the largest cluster after the clustering is taken as the output dispatch area.

[0039] Generally, power distribution equipment selected for dispatching areas needs to be relatively close and have minimal changes in electrical parameters over time. In this case, the average power difference over consecutive time points is used to identify multiple nodes with stable power. Clustering these nodes yields multiple power-stable and similarly located power distribution equipment. The largest cluster is then considered the dispatching area for subsequent use, ensuring the safe operation of the power grid while maximizing dispatchable power. A weighted K-means clustering algorithm can be used to obtain the dispatching areas to be output.

[0040] Preferably, the method of selecting the current interaction region further includes: determining the connection path between each power grid node and the adjacent switch based on the number of switches connected to each power grid node, and filtering each power grid node in the current interaction region according to the connection path; so that each power grid node in the current interaction region corresponds to at least one switch, thereby clarifying its topology and thus indicating the direction in which the current should flow during power interaction.

[0041] Preferably, when the radius of the dispatch area is based on the output of the dispatch area, the radius of the cluster corresponding to the dispatch area is used as the initial radius. The current loss of the power grid nodes in the dispatch area is measured by multiplying the square value of the current by the line resistance of the power grid node. Then, the radius of the area is continuously adjusted, with the adjustment value being 10% of the initial radius. This process is iterated until the average value of the current loss in the dispatch area relative to the number of power grid nodes is minimized. This is considered to be the minimum current loss of each power grid node. The power grid nodes included in the area radius at this time and their positions in the power grid topology are output as the current interaction area.

[0042] In one embodiment of the present invention, step S2 mainly identifies whether the current power distribution equipment is operating normally within the power grid topology based on the mapping relationship between each selected power grid node in the current interaction area at both the equipment entity and information space levels, and determines the frequency and coordination state of current interaction based on the form of normal operation, so as to prevent scheduling anomalies under current dispatch.

[0043] Preferably, the physical level identification content is the identification of the timing anomaly patterns of each power grid node, and the information level identification is the identification of parameter transmission anomalies of each power grid node under the guidance of information transmission.

[0044] like Figure 3 As shown, the implementation of step S2 includes: S21, viewing the power grid topology of each power grid node in the current interaction area, associating the power grid topology with the physical location to obtain the physical layer mapping relationship, and introducing the physical layer mapping relationship into the upload cycle of each power grid node to obtain the information layer mapping relationship.

[0045] S22, verify the electrical parameter information within the upload period, and identify the characteristic type of the abnormal event corresponding to the electrical parameter information. The characteristic types include: continuous abnormality, transient abnormality, periodic abnormality, and correlation abnormality of electrical parameter information. Continuous abnormality is represented by the effective value of current and the harmonic distortion rate of voltage. It is used to indicate whether the values ​​of parameters such as voltage and current continuously exceed the limit within a continuous period of time. For example, the part of voltage and current exceeding the average value plus three standard deviations within a set unit time is identified. The length of the unit time can be selected as 10s, 30s, 60s, etc., as required. Alternatively, the unit time can be linked to the data upload period and set using the timestamp corresponding to one-tenth of the data sampled in the data upload period.

[0046] Transient anomalies are represented by voltage sag depth and current surge peak, indicating a sudden drop in data. This means that the electrical parameter information suddenly decreases at a certain point in time, and such an occurrence is identified as a transient anomaly.

[0047] Periodic anomalies are represented by power fluctuation spectra, which indicate whether current and voltage increase or decrease within a specific period. Anomalies with periodic patterns are considered periodic anomalies, and the frequency of occurrence of such anomalies within the preset time period and the upload cycle is identified to indicate the duration of the periodic change.

[0048] Correlation-type anomalies indicate power imbalance among multiple nodes, suggesting excessive power differences between them. In this case, correlation-type anomalies primarily indicate whether there are abnormalities in parameter transmission between uploaded data nodes, and the differences between various grid nodes. As shown in Table 1, these four feature types can be identified using corresponding algorithms to determine whether there are interactive anomalies.

[0049] Table 1. Characteristic Types of Abnormal Events

[0050]

[0051] Table 1 illustrates the main parameters identified under multiple feature types, along with the main parameter types and their corresponding data. Subsequently, for these abnormal events, the power grid information is monitored during the power dispatching process to prevent dispatching anomalies or multiple operations of a single power distribution device, which could result in the final dispatched current failing to meet the power dispatching requirements.

[0052] S23, use the number of times the characteristic type of the abnormal event occurs within a preset time period as the interaction frequency, and use the node associated with the characteristic type of the abnormal event as the interaction type; output the data corresponding to the interaction frequency and interaction type as a time interaction format.

[0053] The output time-based interaction format will aggregate data from the power distribution equipment represented by the corresponding power grid nodes in a time-series format, summarizing data under the same feature type. It will identify the location of anomalies and the power grid topology within the current power interaction area. Starting from the power grid topology, it will aggregate the characteristics of the anomalies to identify the main changing parameters and specific anomaly patterns. Then, it will aggregate the occurrence of interaction types and frequencies, identify the conditional probability of each node under the corresponding anomaly event, and identify the conditional probability according to the normal transmission order of current data to find the single device or multiple devices affecting power dispatch anomalies.

[0054] Preferably, defining the time interaction form of power grid information further includes: outputting the nodes associated with the interaction type according to the transmission order of abnormal events among power grid nodes to form dynamic baseline reference data; the dynamic baseline reference data is used to identify abnormal behaviors that deviate from the normal mode and to explain the transmission path of abnormalities in power dispatch, and to explain how to make subsequent adjustments based on the path to reduce the losses in power dispatch.

[0055] The parameter thresholds of the dynamic baseline reference data are calculated and updated according to the power grid information upload cycle. The feature types of each abnormal event are extracted using the dynamic baseline reference data. The updated dynamic baseline reference data is used as the output time interaction form.

[0056] The dynamic baseline reference data described above is updated each time based on the abnormal events identified within the input data period. If the upper and lower limits of the values ​​represented by the abnormal events increase, an update is performed, and these increases are output to identify obviously abnormal data in the power grid information. Simultaneously, dynamic baseline reference data is acquired according to the transmission sequence to identify which devices are abnormal and how their communication and current interactions with other devices are connected under normal operating conditions. This facilitates the extraction of abnormal devices and those affected by them. Based on these devices, the main anomalies under current power dispatch can be identified. Correlation of these anomalies with power parameters makes it easier to control power distribution equipment in multiple regions and groups, and to adjust the power grid topology in a timely manner.

[0057] Preferably, the parameter threshold of the dynamic baseline reference data can be set by the average of the upper and lower limits of the corresponding electrical parameter information of the dynamic baseline reference data. When updating the parameter threshold, the data of the nodes associated with the interaction type obtained within the upload period is updated, and the data with corresponding numerical changes each time is output. The output time interaction form includes the interaction type, feature type, interaction frequency, and the value of the corresponding electrical parameter to determine the data that has changed significantly, so as to determine whether the current power grid dispatch is operating normally.

[0058] In one embodiment of the present invention, the node change matrix records nodes whose states change at adjacent time points, and this part of the data is regarded as the node change matrix. For example, when a node changes from a normal working state to a power dispatching state under the power grid dispatching command, or from a normal working state to an abnormal working state, the node whose state changes at this time is extracted, and the transmission path under chain propagation is identified to identify how the state of the current node is propagated, and how parameters such as current, voltage and power are updated and changed at the corresponding time after propagation, so as to explain how the current circuit controls the adjustment of its various power distribution equipment under the power grid dispatching command.

[0059] like Figure 4 As shown, the implementation of step S3 also includes: S31, retrieving the power grid dispatching instructions from the power grid information, defining the state propagation set according to the power grid dispatching instructions, and generating the state change probability of each power grid node based on the power grid topology.

[0060] S32, the state change probabilities are weighted according to the propagation paths of each power grid node to form a node change matrix.

[0061] S33: Identify the interaction frequency, interaction duration, and power change gradient of the node change matrix, and construct an interaction update sequence.

[0062] Preferably, the aforementioned power grid dispatch instructions include, but are not limited to, control instructions issued by the energy management system connected to the current power distribution equipment, such as AGC regulation and circuit breaker operation; the dispatch log file contains the instruction type, target equipment, execution time, and real-time control signals, such as GOOSE messages and MMS service calls, to describe the specific content of the dispatch performed by the current power distribution equipment.

[0063] Preferably, the state propagation set is defined according to the propagation type of each power grid node. For example, it is classified according to the propagation type, triggering conditions and propagation characteristics of each power distribution device in the power grid dispatching instructions to describe the working status of the power distribution device represented by each power grid node in the power grid. The content of its propagation type will be marked in advance according to the type of power distribution device. At this time, it is to verify whether there is a delay or other abnormal problem when the corresponding power distribution devices are mutually dispatched under the dispatching situation, and to quantify these problems in detail, as shown in Table 2.

[0064] Table 2. Classification of Transmission Types

[0065]

[0066] Table 2 illustrates the data content that each power grid node can represent in its state propagation set, and obtains the probability of each power grid node under the corresponding state propagation according to this state propagation set and the power grid topology; sets the existence of propagation type based on whether the corresponding power distribution equipment of each power grid node is triggered, and extracts data under the corresponding characteristics according to the propagation characteristics.

[0067] For example, state propagation set To perform mathematical display, ;in, Represents the set of power grid nodes. This represents the i-th node; This represents the time delay for the state to propagate to node i. This represents the delay calculation function. Starting from any node j, it calculates the delay from that node to the current node i. It mainly describes whether the state propagation is in a normal state, in order to find out if there are nodes with transmission delay. If there are, it means that the current, voltage and other electrical parameter information uploaded by that node may have real-time problems. This represents the line impedance between nodes i and j. The range of values ​​for i and j is based on the number of data in the set of power grid nodes. For example, the range of values ​​for i and j is 1 to N, where N represents the number of data in the set of power grid nodes. It indicates the power flow direction between nodes, and its unit is MW. It mainly indicates how power is conducted between nodes, whether a certain node is the input and a certain node is the output, so as to identify whether the power flow of power dispatch meets the preset requirements. This represents the weight of each power grid node, reflecting its importance in state propagation.

[0068] for ;in, This represents the shortest number of hops from node i to j in the topological path, i.e., the number of line segments the path passes through, indicating how many connecting edges are needed between node i and node j; , This represents the weighting coefficient, typically set to 0.7 or 0.3. In this case, through state propagation, the grid nodes whose current, voltage, and power exceed certain thresholds are identified, and the connection status of these nodes within the grid topology is described.

[0069] Then, the state change probabilities of each power grid node in the state propagation set are set. ,like ;in, The degree of node i represents the number of edges connecting the current power grid node i to other nodes. This number is determined based on the connection relationship between each node and other nodes in the power grid topology, and represents the propagation situation of each power grid node relative to others. This represents the attenuation coefficient; a value of 0.1 is chosen here. It represents an exponential constant.

[0070] At this point, we can obtain information on how each power grid node propagates. Then, we identify the propagation between power grid nodes along the defined propagation path, weight the data, and use the weighted data as the node change matrix.

[0071] Preferably, the current interaction intensity of each power grid node on the conduction path is used as the path weighting method. The current interaction intensity is set according to the average current between each power grid node, and the normalized current interaction intensity is used as the weighting method for each power grid node on the conduction path.

[0072] Preferably, assuming that when constructing the node change matrix, the collected data is extracted from the sliding time window, and the interaction frequency, interaction duration, and power change gradient are recorded in each sliding time window, the identification will be based on the current state change to determine how the current distribution equipment should be turned on and off to complete the corresponding power dispatch. The power change gradient represents the power difference at fixed time intervals within the interaction duration divided by the value of that time interval, used to represent the power change within the time interval.

[0073] For example, when constructing an interactive update sequence, the implementation method also includes: identifying the input terminal corresponding to each grid node; if the current grid node is the input terminal, then limiting the power supply of the current grid node according to the average value of the power change gradient under the corresponding interaction frequency; and taking the interaction frequency, interaction duration and power change gradient corresponding to the current grid node as the output interactive update sequence.

[0074] If the current grid node is the output end, then the node change matrix is ​​filtered according to the interaction frequency and duration of the current grid node, and the data with power change gradient greater than the average power change gradient is used as the output interaction update sequence.

[0075] If the current grid node is an intermediate node, then the portion where both the interaction frequency and the power change gradient exceed the average value is taken as the output interaction update sequence. Here, the average value refers to the average value extracted over multiple sliding time windows, and the power change gradient is the value greater than the average power change gradient. This portion of values ​​that change significantly and frequently is taken as the output interaction update sequence.

[0076] In the above description, the power grid nodes at the input end dynamically adjust the power supply at the input end based on the average value of the power change gradient under the interaction frequency; the main purpose is to prevent grid instability: by limiting the power supply, grid frequency or voltage fluctuations caused by excessive power change gradients, such as the volatility of renewable energy, are avoided.

[0077] The power grid nodes at the output end filter the node change matrix based on the interaction frequency and duration, selecting data whose power change gradient is greater than the average value. By filtering high-frequency and long-duration interaction events, the power distribution at the output end is optimized, ineffective transmission is reduced, and loads with large power change gradients are prioritized to improve the economic efficiency of the power grid. At the same time, in the event of corresponding anomalies, the abnormal data is quickly identified to ensure the operation of the power grid.

[0078] The intermediate power grid nodes respond quickly to load changes or faults in the power grid by selecting high-frequency, high-gradient data; they also select the corresponding data from each power grid node during transmission to verify whether the transmission loss is normal, which facilitates subsequent cost verification of power grid dispatching and improves the overall efficiency of power grid dispatching.

[0079] In one embodiment of the present invention, the interaction target of each power grid node represents the power grid node selected in pairs when identifying the relative propagation between power grid nodes in the interaction update sequence, and the corresponding power grid node is regarded as its mapping structure interval in the power grid topology, to identify the area where multiple power distribution equipment interacts during current interaction. Then, the resulting operating cost is queried to quantify the loss situation under each current interaction mobilization.

[0080] like Figure 5 As shown, step S4 further includes: S41, querying the interaction type of each interaction target based on the current branch of each interaction target during current interaction, finding the minimum value of each interaction type, and tracking the interaction target based on the minimum value of each interaction type; wherein the current branch refers to the path in the circuit through which the same current flows, which includes components such as resistors and capacitors, and is divided into active branches with power supply and passive branches without power supply.

[0081] S42, for any interaction type of the interaction target, identify the current, voltage and power of the interaction target under each interaction type, and fuse the average value and limit value of the interaction current, voltage and power to obtain the target value of each interaction target.

[0082] S43, set the current compensation strategy according to the target value of each interactive target and the position of the interactive target on the current branch.

[0083] Preferably, the interaction type describes the labels set when outputting the data corresponding to current, voltage, and power in the interaction update sequence during the processing in steps S3 and S2; then, the power grid nodes represented by each interaction target are tracked according to each interaction type, and the minimum value of each interaction type is identified. The minimum value is used to identify the cost generated under the interaction condition of the current at the minimum value. This cost is convenient for predicting the total lower limit of the current interaction cost, with the aim of optimizing circuit performance and reducing costs; that is, the current compensation and adjustment are set according to the overall cost of the current power grid node operating at its minimum value, so as to reduce the loss caused by abnormal propagation of current, voltage, etc., and reduce the cost of abnormal scheduling.

[0084] Preferably, the method for fusing the average and limit values ​​of the interactive current, voltage, and power can be to obtain the target value by weighted averaging. For example, the standard value and the limit value can be set with weights of 0.6 and 0.4, respectively, or the target value can be obtained by calculating the ratio of the average and limit values ​​from historical data based on the current average and limit values. Then, based on the target value of each interactive target and the position of the interactive target on the current branch, a pre-set current compensation strategy is retrieved from the database. When the similarity between the target value and the position of the interactive target on the current branch and the historical data reaches the maximum, the corresponding current compensation strategy is output. The similarity calculation method uses cosine similarity for the target value of the interactive target and the distance value of the position of the interactive target on the current branch. Finally, the current compensation strategy corresponding to the maximum value of both similarities is selected to adjust the output of each power grid node to ensure that the power distribution equipment can operate in a relatively stable manner under abnormal conditions.

[0085] Preferably, the limit values ​​of current, voltage, and power represent the maximum and minimum values ​​that exist within the current upload cycle; the average values ​​of current, voltage, and power also refer to the average values ​​calculated within the current upload cycle.

[0086] Preferably, the current compensation strategy represents the current, voltage, and power values ​​of each grid node operating under the current grid node's grid topology, as well as the logical position corresponding to each grid node. This facilitates subsequent identification of the position of the interaction target on the current branch within the grid topology and whether it is close to the grid node corresponding to the current, voltage, and power adjustment required by the current compensation strategy. This is to describe the control method of the grid nodes included in the interaction target.

[0087] In one embodiment of the present invention, such as Figure 6 As shown, the implementation of step S5 also includes: S51, obtaining the coordinates of each grid node included in the current compensation strategy, generating the current compensation region, and detecting the overlap between the current compensation region and the current interaction region.

[0088] S52, determine whether the overlap is less than the overlap threshold. If it is less than the overlap threshold, reacquire the current compensation region. Otherwise, determine whether the current compensation region is the target region based on the interaction frequency and operating cost of the current compensation region.

[0089] S53, if it is the target area, record the interaction frequency of the target area, update the target area according to the upload cycle corresponding to the interaction frequency, and close the switches of each power grid node in the target area when the similarity value of the target area is the largest in multiple upload cycles; if it is not the target area, open the switches of each power grid node in the current compensation area.

[0090] Preferably, the overlap described above is obtained by comparing whether the grid nodes in the current compensation area and the current interaction area overlap, which is the ratio of the intersection of the current compensation area and the union of the current interaction area. By generating a current compensation area and performing overlap analysis with the interaction area, it is ensured that the compensation measures accurately cover the actual grid area that needs intervention, avoiding resource waste. The overlap threshold required here can be 90%, or the average overlap calculated from historical data of executing this current compensation strategy can be used as the overlap threshold at this time. That is, when an anomaly occurs in the current interaction area, the compensation area is quickly located through overlap analysis. If the overlap is insufficient, it means that the adjustment method may not cover the current branch with an anomaly, so the compensation area is replanned to ensure that the intervention measures directly act on the anomaly source, avoiding resource waste caused by blind compensation and shortening the response time for anomaly handling.

[0091] Preferably, the operating costs described later can be described based on the power loss generated by each power grid node in the target area during current interaction, i.e., by multiplying the square of the current by the line resistance of the corresponding power distribution equipment between the power grid nodes. These can be obtained directly by measuring the power distribution equipment. As for determining whether the current compensation area is the target area, it is based on the interval of the interaction frequency at the current power grid node location. If the interaction frequency of the area is within this interval, and its operating cost is less than 5% of the annual electricity revenue at that location, or less than the average operating cost in its historical data during current interaction, then the area is considered as the target area.

[0092] Preferably, the frequency intervals for interactions are adjusted according to the location of the power distribution equipment. For example, intervals are set for industrial power grids, commercial power grids, and residential power grids, respectively: a high-frequency interval (greater than 12 times / hour), a medium-frequency interval (6 to 12 times / hour), and a low-frequency interval (less than 6 times / hour). These three intervals can also be adjusted based on the average of the upper and lower limits of anomalies observed in that region in historical data, to describe the current interaction of power distribution equipment at different locations in the power grid topology. At this point, the target region is selected by combining the interaction frequency and operating cost, reducing economic costs while ensuring compensation effectiveness. Then, the target region is updated according to the data collected within the upload cycle. By periodically updating the target region and controlling the switch status, dynamic balance of the power grid is achieved, reducing fluctuations caused by frequent adjustments. Finally, the similarity within the upload cycle is calculated by performing cosine similarity calculations on the current, voltage, and power of the corresponding power grid nodes in the target region for each upload cycle, and then averaging the results to illustrate the similarity of the target region across multiple upload cycles. If the similarity is the highest at this point, the switch is closed to solidify the compensation strategy, avoiding power grid fluctuations caused by frequent switching. If the current does not meet the target area for current dispatch interaction, the switch in the non-target area is disconnected to prevent overcompensation or undercompensation, thereby improving the stability of the power grid control.

[0093] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention, which are still covered within the protection scope of the present invention.

Claims

1. A method for integrated operation monitoring of power grid information security, characterized in that, include: S1, obtain the electrical parameter information of the power distribution equipment in the power grid information, and form a power grid topology by taking the power distribution equipment as power grid nodes according to the connection relationship of the power distribution equipment. Select the current interaction area based on the distance between each power grid node on the topology and the dispatch area during current interaction. S2, performs a two-layer mapping of the physical and information layers of each power grid node in the current interaction area, extracts features of the electrical parameter information of each power grid node in the current interaction area based on the upload cycle of power grid information within a preset time period, obtains abnormal events of each power grid node, and defines the time interaction form of power grid information based on the interaction frequency and interaction type of abnormal events. S3, based on the time-based interaction of power grid information, constructs a node change matrix; By utilizing the propagation path of the node change matrix under chain propagation, the interactive update sequence of the current interaction region is obtained; S4. Obtain the interaction target of each power grid node from the interaction update sequence, and determine the current compensation strategy under different current conditions based on the interaction target of each power grid node. S5 performs interactive evaluation of each grid node included in the current compensation strategy and adjusts the corresponding switches of each grid node. The implementation of step S1 includes: in the on state of the power distribution equipment, constructing a hierarchical connection relationship of at least one power distribution equipment according to its location; using the hierarchical connection relationship of the power distribution equipment to generate the power grid topology of the power distribution equipment, and integrating the data of each power grid node according to the electrical parameter information collected on the power grid topology; monitoring the electrical parameter information of each power grid node, and dividing the dispatch area according to the fluctuation ratio of the electrical parameter information of each power grid node and the distance between each power grid node; setting the area radius with the dispatch area as the center, and when the current loss of each power grid node within the area radius is minimized, outputting each power grid node within the area radius as the current interaction area.

2. The integrated operation monitoring method for power grid information security according to claim 1, characterized in that, Electrical parameter information includes current, voltage, and power.

3. The integrated operation monitoring method for power grid information security according to claim 1, characterized in that, The implementation of selecting the current interaction region also includes: determining the connection path between each power grid node and the adjacent switch based on the number of switches connected to each power grid node, and filtering each power grid node in the current interaction region according to the connection path; so that each power grid node in the current interaction region corresponds to at least one switch.

4. The integrated operation monitoring method for power grid information security according to claim 1, characterized in that, Step S2 can be implemented in the following ways: Examine the power grid topology of each power grid node in the current interaction area, associate the power grid topology with the physical location to obtain the physical level mapping relationship, and introduce the physical level mapping relationship into the upload cycle of each power grid node to obtain the information level mapping relationship. The electrical parameter information within the upload period is checked, and the characteristic types of the abnormal events corresponding to the electrical parameter information are identified. The characteristic types include: continuous abnormality, transient abnormality, periodic abnormality, and correlation abnormality of electrical parameter information. The frequency of interaction is determined by the number of times the characteristic type of an abnormal event occurs within a preset time period, and the node associated with the characteristic type of the abnormal event is determined by the interaction type. The data corresponding to the interaction frequency and interaction type are output in the form of time interaction.

5. The integrated operation monitoring method for power grid information security according to claim 4, characterized in that, Defining the time-based interaction format of power grid information also includes: According to the propagation order of abnormal events among various power grid nodes, the nodes associated with the interaction type are output to form dynamic baseline reference data; The parameter thresholds of the dynamic baseline reference data are calculated and updated according to the power grid information upload cycle. The feature types of each abnormal event are extracted using the dynamic baseline reference data. The updated dynamic baseline reference data is used as the output time interaction form.

6. The integrated operation monitoring method for power grid information security according to claim 1, characterized in that, The implementation of step S3 also includes: Retrieve grid dispatch instructions from grid information, define a state propagation set based on the grid dispatch instructions, and generate the state change probability of each grid node based on the grid topology. The probability of state change is weighted according to the propagation path of each power grid node to form a node change matrix; Identify the interaction frequency, interaction duration, and power change gradient of the node change matrix, and construct an interaction update sequence.

7. The integrated operation monitoring method for power grid information security according to claim 6, characterized in that, Other ways to implement interactive update sequences include: Identify the input terminals corresponding to each grid node. If the current grid node is an input terminal, limit the power supply of the current grid node according to the average value of the power change gradient under the corresponding interaction frequency. The interaction frequency, interaction duration and power change gradient corresponding to the current grid node are used as the output interaction update sequence. If the current grid node is the output end, then based on the interaction frequency and duration of the current grid node, the node change matrix is ​​filtered, and the data with power change gradient greater than the average power change gradient is used as the output interaction update sequence. If the current grid node is an intermediate node, then the part where both the interaction frequency and the power change gradient exceed the average value is obtained as the output interaction update sequence.

8. The integrated operation monitoring method for power grid information security according to claim 1, characterized in that, Step S4 also includes: By querying the current branches of each interactive target during current interaction, the interaction types of each interactive target are found, and the minimum value of each interaction type is used to track the interactive target. For any interaction type of the interaction target, identify the current, voltage and power of the interaction target under each interaction type, and fuse the average value and limit value of the interaction current, voltage and power to obtain the target value of each interaction target. A current compensation strategy is set based on the target value of each interactive target and the position of the interactive target on the current branch.

9. The integrated operation monitoring method for power grid information security according to claim 1, characterized in that, The implementation of step S5 also includes: The coordinates of each grid node included in the current compensation strategy are obtained, the current compensation region is generated, and the overlap between the current compensation region and the current interaction region is detected. Determine whether the overlap exceeds the overlap threshold. If it does, reacquire the current compensation region. Otherwise, determine whether the current compensation region is the target region based on the interaction frequency and operating cost of the current compensation region. If it is the target area, record the interaction frequency of the target area, update the target area according to the upload cycle corresponding to the interaction frequency, and close the switches of each power grid node in the target area when the similarity value of the target area is the largest in multiple upload cycles; if it is not the target area, open the switches of each power grid node in the current compensation area.

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