Transformer area physical topology identification method and system

Abstract

The invention relates to the field of topology identification, and discloses an area physical topology identification method and system, and the method comprises the steps: obtaining an HPLC carrier signal and an HRF wireless signal of a communication node in an area; according to the difference of the channel quality characteristics of the HPLC carrier signal and the HRF wireless signal, grouping communication nodes in the district to obtain a plurality of communication node clusters; calculating the actual line communication distance between the communication node clusters and / or between different communication nodes in the clusters by using the communication time of the HPLC in the line; according to an actual line communication distance, layered division is carried out on communication nodes of different distances, and clustering and layered division of a transformer area physical topology is realized. Based on the HDC dual-mode communication technology, automatic identification of the transformer area physical topology is achieved, a transformer area physical topological graph based on low-voltage electric equipment is formed, and basic data are provided for deepening application of transformer area operation and maintenance, statistics, management and the like.

Description

Technical Field

[0001] The present invention relates to the field of topology recognition, and in particular to a method and system for identifying a physical topology of a substation. Background Art

[0002] The low-voltage distribution network is the end of the power grid. Due to the large area it covers, the complex structure, the large number of equipment, and the low level of automation, there are many blind spots in the management of the low-voltage distribution network. In particular, the power supply equipment between the transformer and the low-voltage user has always been in the blind spot of equipment monitoring.

[0003] To this end, power grid companies are vigorously carrying out the work of information integration of marketing and distribution. The identification of physical topology of the substation is crucial for power grid companies to improve the management level of power supply reliability and improve power supply service capabilities. First, it can help power companies accurately grasp the connection relationship and operating status of equipment in the substation, and provide strong support for subsequent power management and operation and maintenance. Secondly, topology identification technology can realize real-time monitoring and fault warning of the substation power supply network, and improve power supply reliability and stability. Finally, through topology identification technology, power companies can formulate power dispatching and operation and maintenance plans more accurately, reduce operating costs and improve economic benefits.

[0004] Therefore, it is necessary to continuously develop new topology recognition technologies to improve recognition accuracy and reliability. Summary of the invention

[0005] The main purpose of the present invention is to solve the technical problem of low recognition accuracy and reliability in the prior art. A method for identifying the physical topology of a substation area comprises the following steps:

[0006] Obtain HPLC carrier signals and HRF wireless signals of communication nodes within the station area;

[0007] According to the difference in channel quality characteristics between the HPLC carrier signal and the HRF wireless signal, the communication nodes in the station area are grouped to obtain multiple communication node clusters;

[0008] Using the communication time of HPLC in the line, the actual line communication distance between communication node clusters and / or between different communication nodes in a cluster is calculated;

[0009] According to the actual line communication distance, the communication nodes at different distances are divided into layers to realize the clustering and layering of the physical topology of the substation area.

[0010] As a preferred technical solution, the communication nodes in the station area are grouped according to the difference in channel quality characteristics of the HPLC carrier signal and the HRF wireless signal to obtain multiple communication node clusters, including:

[0011] Receive HPLC and HRF signals from all neighboring communication nodes on the network, and obtain the average signal quality level of the entire network after a period of time;

[0012] According to the average signal quality level of the entire network, N communication nodes with better quality are screened out to obtain the average level of the N communication nodes with better quality;

[0013] Obtain the probability distribution function F(x) based on the average level of the entire network and the average level of N sites with good quality;

[0014] According to the probability distribution function F(x), the communication nodes are grouped to obtain multiple communication node clusters.

[0015] As a preferred technical solution, the actual line communication distance Dis between different communication nodes A-B The calculation formula is:

[0016] Dis A-B =(T loop ×V) / 2

[0017] Where V is the power line transmission speed;

[0018] T loop is the net loop transmission time difference. When the processing delays of the two communicating nodes are the same, the formula is:

[0019] T loop =(T4-T1)-2(T RX +T TX )+T comp_A +T comp_B

[0020] Among them, T RX , T TX are the receiving processing delay and sending processing delay of the two communication nodes, T comp_A , T comp_B They are the time compensation values ​​of the receiving processing delay and the sending processing delay of the communication node respectively; T1 is the moment when one communication node starts to send a known signal to another communication node, and T4 is the moment when the communication node confirms receipt of the return signal.

[0021] As a preferred technical solution, the actual line communication distance Dis between different communication nodes A-B The calculation formula is:

[0022] Dis A-B =(T loop ×V) / 2

[0023] Where V is the power line transmission speed;

[0024] T loop is the net loop transmission time difference, when the processing delays of the two communicating nodes are different, the formula is:

[0025] T loop =(T4-T1)-(T RX_A +T TX_A )-(T RX_B +T TX_B )+T comp_A +T comp_B

[0026] Among them, T RX_A 、T TX_A 、T RX_B 、T TX_B are the receiving processing delay and sending processing delay of the two communication nodes, T comp_A 、T comp_B They are the time compensation values ​​of the receiving processing delay and sending processing delay of the communication node respectively; T1 is the moment when one communication node starts to send a known signal to another communication node, and T4 is the moment when the communication node confirms that it has received the return signal.

[0027] As a preferred technical solution, the topology identification method further includes a clustering-assisted verification step: based on voltage correlation, the result of clustering and hierarchical division of the physical topology of the substation area is further accurately verified, specifically:

[0028] According to the highly synchronized NTB clock between communication nodes, the voltage and current values ​​of the communication nodes are synchronously collected and stored, and broadcast locally;

[0029] According to the increase and decrease of multiple voltage values ​​at different time points, verify whether the clustering and stratification are correct.

[0030] As a preferred technical solution, the verification of whether the clustering and stratification is correct according to the increase and decrease of multiple voltage values ​​at different time points in the group includes:

[0031] Calculate the voltage similarity between two communication nodes based on the voltage value information of the communication nodes;

[0032] The similarity calculation method of voltage sequence vector uses the cross-correlation algorithm:

[0033]

[0034] Among them, Vi(n) and Vj(n) are the voltage sequence vectors of the two-to-two communication nodes, n is the time index, and when the R of the two-to-two communication nodes in the cluster ij When it is greater than the preset threshold, the clustering and stratification are considered correct.

[0035] As a preferred technical solution, the topology identification method further includes a clustering-assisted verification step: based on the active electric energy, the result of clustering and hierarchical division of the physical topology of the substation area is further accurately verified, specifically:

[0036] The 96 power points of each communication node are collected, namely A0, A1, A2, A3, A4...A95;

[0037] After processing, we get 95 points of electric energy: B0 = A1-A0, B1 = A2-A1, B2 = A3-A2…, B94 = A95-A94

[0038] The following algorithm is used for the 95-point electric energy of the communication node to calculate the covariance Cov(x,y) of the two communication nodes:

[0039] Coυ(X,Y)=E[(X-μ x )(Y-μ y )]

[0040] Among them, X is the power value of the parent communication node, μ x is the average power value of the parent communication node, Y is the power value of the child communication node, μ y is the average power value of the sub-communication nodes;

[0041] If the covariance is positive, it means that X and Y change in the same direction. The larger the covariance, the higher the degree of the same direction. If the covariance is negative, it means that X and Y move in opposite directions. The smaller the covariance, the higher the degree of the opposite direction. The correctness of the clustering and stratification can be verified by the degree of the same direction.

[0042] A second aspect of the present invention provides a system for identifying a physical topology of a substation, comprising:

[0043] An acquisition unit, used for acquiring HPLC carrier signals and HRF wireless signals of communication nodes in the station area;

[0044] A clustering unit is used to group the communication nodes in the station area according to the difference in channel quality characteristics of the HPLC carrier signal and the HRF wireless signal to obtain multiple communication node clusters;

[0045] A communication distance calculation unit, used to calculate the actual line communication distance between communication node clusters and / or between different communication nodes in a cluster by using the communication time of HPLC in the line;

[0046] The clustering and layering division unit is used to perform layering division on communication nodes at different distances according to the actual line communication distance, so as to realize the clustering and layering division of the physical topology of the substation area.

[0047] The third aspect of the present invention provides an electronic device, comprising: a memory and at least one processor, wherein instructions are stored in the memory, and the memory and the at least one processor are interconnected via lines; the at least one processor calls the instructions in the memory so that the electronic device executes the above-mentioned method for identifying the physical topology of the substation.

[0048] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned method for identifying the physical topology of a metropolitan area.

[0049] The present invention has the following beneficial effects:

[0050] By comprehensively considering the differences in channel quality characteristics of HPLC carrier signals and HRF wireless signals, the present invention can more finely distinguish the connection quality and signal propagation characteristics between communication nodes. This helps to more accurately identify the actual connection relationship between communication nodes, thereby constructing a more realistic physical topology map of the station area.

[0051] The present invention calculates the average signal quality level of the entire network, selects communication nodes with better quality, and then constructs a probability distribution function F(x) based on the signal quality levels of these nodes, so as to realize intelligent grouping of communication nodes. This method not only considers the global signal quality, but also takes into account the local high-quality nodes, making the grouping results more reasonable and facilitating the subsequent clustering and layering processing.

[0052] The present invention combines the verification steps based on active electric energy and voltage correlation, and can verify the clustering and layering results of the physical topology of the substation area from different dimensions, thereby improving the comprehensiveness and accuracy of the verification.

[0053] As the regional communication network continues to develop and change, the method of the present invention can dynamically adjust the grouping and layering of communication nodes. When new nodes are added or old nodes are removed, the system can recalculate the signal quality level and update the grouping and layering information to ensure the real-time and accuracy of the network topology. This dynamic optimization capability helps to maintain the efficient operation and continuous stability of the network. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is the physical topology diagram of the existing substation area;

[0055] Figure 2 This is a schematic diagram of loop transmission between CCO and STA1 of the present invention; DETAILED DESCRIPTION

[0056] For ease of understanding, the specific process of the embodiment of the present invention is described below. The first embodiment of the method for identifying the physical topology of the substation area in the embodiment of the present invention includes:

[0057] The HPLC carrier signal and the HRF wireless signal of the communication nodes in the substation area are obtained; the communication nodes in the substation area are grouped according to the difference in the channel quality characteristics of the HPLC carrier signal and the HRF wireless signal to obtain multiple communication node clusters; the actual line communication distance between the communication node clusters and / or between different communication nodes in the cluster is calculated using the communication time of HPLC in the line; the communication nodes at different distances are hierarchically divided according to the actual line communication distance to realize the clustering and hierarchical division of the physical topology of the substation area.

[0058] The present invention utilizes the difference in channel quality-related characteristics between HPLC carrier signals and HRF wireless signals during communication, such as Figure 1 In the same meter box, the same branch box, and the same distribution room, the communication nodes are relatively close to each other, and the signal quality (signal-to-noise ratio, attenuation, etc.) between the communication nodes is also relatively similar. Different meter boxes and branch boxes are affected by space and power supply lines, and the differences between communication nodes are relatively large. The communication nodes in the substation are grouped. In order to reduce the complexity of the algorithm, a representative node can be selected from multiple nodes in the same group to participate in the next step of the recognition algorithm of different levels and different meter boxes to improve the recognition efficiency.

[0059] At present, both dual-mode modules have the function of collecting the SNR and RSSI values ​​of the HPLC and HRF communication channels of neighboring nodes. Communication nodes with different SNR and RSSI values ​​are grouped and classified. Nodes with similar SNRs and the same increase and decrease, high similarity, and smaller RSSI attenuation between each other are grouped into the same group, and can be temporarily grouped into the same meter box. On this basis, chips that support reporting of channel characteristic curve H and channel noise Nosie can also be designed. The correlation between H and Nosie can be more accurately classified and identified than SNR and RSSI.

[0060] By comprehensively considering the differences in channel quality characteristics of HPLC carrier signals and HRF wireless signals, the present invention can more finely distinguish the connection quality and signal propagation characteristics between communication nodes. This helps to more accurately identify the actual connection relationship between communication nodes, thereby constructing a more realistic physical topology map of the station area.

[0061] By using the communication time of HPLC in the line, the actual line communication distance between different communication nodes can be calculated. Nodes with similar distances can be temporarily divided into a group, and then the minimum spanning tree algorithm is used to identify the physical connection relationship between communication nodes. Nodes with different distances are layered and clustered to realize the hierarchical relationship identification of each grouping device.

[0062] The design principle of using HPLC signal loopback to measure power line distance is as follows:

[0063] Taking the loopback transmission between CCO and STA1 as an example, the loopback transmission process is explained in detail. Figure 2 It shows that at time T1, CCO starts to send a known signal to STA1; at time T2, STA1 confirms receipt of the known signal and switches to the sending state; at time T3, STA1 starts to return a known signal to CCO; at time T4, CCO confirms receipt of the return signal.

[0064] Then the CCO-STA1 loop transmission time difference from CCO to STA1 is T loop_raw The expression is:

[0065] T loop_raw =(T4-T1)

[0066] Assume that the receiving processing delay of the two communicating nodes is T RX , the sending processing delay is T TX The processing delay of the two communication nodes is the same, and the time compensation value is T comp_A , T comp_B (can be positive or negative),

[0067] Then the expression of the net loop transmission time difference is T loop for:

[0068] T loop =(T4-T1)-2(T RX +T TX )+T comp_A +T comp_B

[0069] If the receiving or processing delays of the two communicating nodes are different, the above equation becomes:

[0070] T loop =(T4-T1)-(T RX_A +T TX_A )-(T RX_B +T TX_B )+T comp_A +T comp_B

[0071] Assuming the power line transmission speed is V meters / second,

[0072] Then the power line distance Dis from node A to node B is A-B The expression is:

[0073] Dis A-B =(Tloop ×V) / 2

[0074] The present invention calculates the average signal quality level of the entire network, selects communication nodes with better quality, and then constructs a probability distribution function F(x) based on the signal quality levels of these nodes, so as to realize intelligent grouping of communication nodes. This method not only considers the global signal quality, but also takes into account the local high-quality nodes, making the grouping results more reasonable and facilitating the subsequent clustering and layering processing.

[0075] As a preferred embodiment, the communication nodes in the station area are grouped according to the difference in channel quality characteristics of the HPLC carrier signal and the HRF wireless signal to obtain multiple communication node clusters, including:

[0076] Receive the HPLC and HRF signals of all neighbor communication nodes on the network, and obtain the average signal quality level of the entire network after a period of time; according to the average signal quality level of the entire network, screen out N communication nodes with better quality and obtain the average level of N communication nodes with better quality; obtain the probability distribution function F(x) according to the average level of the entire network and the average level of N sites with better quality; according to the probability distribution function F(x), group the communication nodes to obtain multiple communication node clusters.

[0077] The details are as follows:

[0078] Each node receives HPLC (probably some kind of high frequency pulse communication signal) and HRF (probably some kind of high frequency radio frequency signal) signals from all its neighbors.

[0079] Record the signal quality of each signal (such as signal-to-noise ratio SNR, received power, etc.).

[0080] Assume that there are M nodes in the network, and each node i collects the signal quality data set from its neighbors as Qi = {qi1,qi2,...,qin i}, where n i is the number of neighbors of node i.

[0081] The average signal quality Q of the entire network can be calculated as:

[0082]

[0083] Sorting and filtering:

[0084] Merge the signal quality data from all nodes into one large set:

[0085]

[0086] Sort the elements in set Q.

[0087] Select the N nodes with the best signal quality, denoted as the set S = {s1, s2, ..., sN}, where sk is the signal quality of the k-th node with the best quality.

[0088] Calculate the average signal quality of the N nodes:

[0089]

[0090] Construct the probability distribution function F(x):

[0091] Assume that the signal quality data follows a normal distribution, but usually it needs to be fitted according to the actual data.

[0092] Use statistical methods (such as maximum likelihood estimation, moment estimation) to estimate the parameters of the distribution.

[0093] Assume the distribution function is f(x), then the probability distribution function F(x) (i.e., the cumulative distribution function) is:

[0094]

[0095] Determine the grouping thresholds:

[0096] According to F(x) and the required number of groups or grouping strategy (such as equal-probability grouping), determine the grouping thresholds.

[0097] For example, if the nodes are to be divided into K groups, K - 1 thresholds T1, T2, ..., TK - 1 can be selected such that each group contains the same number of nodes or has similar probability mass.

[0098] Grouping:

[0099] According to the signal quality qi of each node and the threshold Tj, assign the nodes to the corresponding groups.

[0100] For example, if T1 ≤ qi < T2, then node i belongs to the second group.

[0101] The solution of the present invention can ensure the reliability and efficiency of in-cluster communication by screening out communication nodes with better signal quality as the core or representatives of the cluster. These high-quality nodes can transmit data more effectively, reduce the retransmission and packet loss phenomena caused by poor signal quality, and thus improve the communication efficiency of the entire network. When a node fails or the signal quality drops sharply, this solution can quickly identify and isolate the affected cluster, reducing the impact of the failure.

[0102] As a preferred embodiment, the topology recognition method further includes a clustering-assisted verification step: based on voltage correlation, further accurately verify the result of the clustered and hierarchical partitioning of the physical topology of the substation area, specifically:

[0103] According to the highly synchronized NTB clock between communication nodes, the voltage and current values ​​of the communication nodes are synchronously collected and stored, and broadcast locally; according to the increase and decrease of multiple voltage values ​​at different time points, it is verified whether the clustering and hierarchical division is correct.

[0104] Specifically, as a preferred embodiment, verifying whether the clustering and layering division is correct according to the increase and decrease of multiple voltage values ​​at different time points in the group includes:

[0105] According to the voltage value information of the communication node, the voltage similarity of the two communication nodes is calculated; the similarity calculation method of the voltage sequence vector uses the cross-correlation algorithm:

[0106]

[0107] Among them, Vi(n) and Vj(n) are the voltage sequence vectors of the two-to-two communication nodes, n is the time index, and when the R of the two-to-two communication nodes in the cluster ij When it is greater than the preset threshold, the clustering and stratification are considered correct.

[0108] Alternatively, the following algorithms can be used:

[0109] The normalized cross-correlation (also called cross-correlation coefficient or correlation coefficient) is used as a measure of similarity. The normalized cross-correlation Rij can be defined as:

[0110]

[0111] Where N is the length of the voltage sequence, μi and μj are the means of Vi(n) and Vj(n), respectively.

[0112] Calculate voltage similarity: For each pair of communicating nodes in the cluster, use the above normalized cross-correlation algorithm to calculate their voltage similarity Rij.

[0113] Set a threshold value: According to the actual application scenario and the characteristics of the data, set a reasonable threshold value. This threshold value should be able to distinguish nodes belonging to the same cluster (high similarity) from nodes that do not belong to the same cluster (low similarity).

[0114] Verify the partition: If the Rij values ​​of the two communicating nodes in the cluster are greater than the preset threshold value, it is considered that the nodes in the cluster are similar in voltage characteristics, thereby verifying the correctness of the clustering and hierarchical partitioning.

[0115] By calculating the normalized mutual correlation coefficient (Rij) of the voltage sequence between two communication nodes, the similarity of the voltage changes between them can be accurately quantified. This method is more detailed and accurate than simply comparing voltage values ​​or voltage change trends, and can more effectively identify nodes belonging to the same cluster. This verification method does not depend on a specific grid structure or communication protocol, and only needs to obtain the voltage sequence data of the communication node for verification. Therefore, it is suitable for different types of substation physical topologies and different data acquisition systems, and has strong adaptability and flexibility.

[0116] As another preferred embodiment, the topology identification method further includes a clustering-assisted verification step: based on the active electric energy, the result of clustering and hierarchical division of the physical topology of the substation area is further accurately verified, specifically:

[0117] The 96 power points of each communication node are collected, namely A0, A1, A2, A3, A4...A95;

[0118] After processing, we get 95 points of electric energy: B0 = A1-A0, B1 = A2-A1, B2 = A3-A2…, B94 = A95-A94

[0119] The following algorithm is used for the 95-point electric energy of the communication node to calculate the covariance Cov(x,y) of the two communication nodes:

[0120] Coυ(X,Y)=E[(X-μ x )(Y-μ y )]

[0121] Among them, X is the power value of the parent communication node, μ x is the average power value of the parent communication node, Y is the power value of the child communication node, μ y is the average power value of the sub-communication nodes;

[0122] If the covariance is positive, it means that X and Y change in the same direction. The larger the covariance, the higher the degree of same direction. If the covariance is negative, it means that X and Y move in opposite directions. The smaller the covariance, the higher the degree of opposite direction. The correctness of clustering and stratification can be verified by the degree of same direction.

[0123] By calculating the power covariance between the parent communication node and the child communication node, the synchronization or reversal of the power changes between them can be quantified. The positive and negative sign and size of the covariance directly reflect whether the trend of power changes between nodes is consistent, thereby effectively verifying the correctness of clustering and hierarchical division. This method is more comprehensive and accurate than relying solely on voltage or current data.

[0124] The covariance of the present invention is an objective statistic, which is calculated based on a large amount of electric energy data and is not affected by human factors or subjective judgment. Therefore, the verification method can provide a more objective and reliable verification result and reduce the possibility of misjudgment and missed judgment.

[0125] The method of the present invention is applicable to different types of communication nodes and different power grid environments. As long as enough power data can be collected, the correctness of clustering and hierarchical division can be verified by calculating the covariance. This makes the method highly adaptable and flexible.

[0126] With the development of smart grid technology, the collection and processing of power data has become very convenient and efficient. Therefore, this verification method can realize automatic processing by writing corresponding algorithm programs, reducing manual intervention and labor intensity.

[0127] If the calculated covariance is not consistent with the expected (e.g., the covariance between nodes that should change in the same direction is negative), this may mean that there is a fault or abnormality in the power grid. Therefore, this verification method can not only be used to verify the correctness of the topology partitioning, but also as an auxiliary means of power grid fault detection.

[0128] Since this method is based on real-time or periodic power data collection, it can support dynamic verification of the physical topology of the substation area. That is, as the operating status of the power grid changes, the covariance can be recalculated and the correctness of the clustering and hierarchical division can be verified to ensure the real-time and accuracy of the topology information.

[0129] The above describes the method for identifying the physical topology of a substation in an embodiment of the present invention. The following describes the device for identifying the physical topology of a substation in an embodiment of the present invention. The first embodiment of the device for identifying the physical topology of a substation in an embodiment of the present invention includes:

[0130] An acquisition unit, used for acquiring HPLC carrier signals and HRF wireless signals of communication nodes in the station area;

[0131] A clustering unit is used to group the communication nodes in the station area according to the difference in channel quality characteristics of the HPLC carrier signal and the HRF wireless signal to obtain multiple communication node clusters;

[0132] A communication distance calculation unit, used to calculate the actual line communication distance between communication node clusters and / or between different communication nodes in a cluster by using the communication time of HPLC in the line;

[0133] The clustering and layering division unit is used to perform layering division on communication nodes at different distances according to the actual line communication distance, so as to realize the clustering and layering division of the physical topology of the substation area.

[0134] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device, or unit can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0135] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identifying physical topology of a substation, characterized in that: The topology identification method comprises the following steps: Obtain HPLC carrier signals and HRF wireless signals of communication nodes within the station area; According to the difference in channel quality characteristics between the HPLC carrier signal and the HRF wireless signal, the communication nodes in the station area are grouped to obtain multiple communication node clusters; Using the communication time of HPLC in the line, the actual line communication distance between communication node clusters and / or between different communication nodes in a cluster is calculated; According to the actual line communication distance, the communication nodes at different distances are divided into layers to realize the clustering and layering of the physical topology of the substation area.

2. A method for identifying a physical topology of a substation according to claim 1, characterized in that: The communication nodes in the station area are grouped according to the difference in channel quality characteristics of the HPLC carrier signal and the HRF wireless signal to obtain multiple communication node clusters, including: Receive HPLC and HRF signals from all neighboring communication nodes on the network, and obtain the average signal quality level of the entire network after a period of time; According to the average signal quality level of the entire network, N communication nodes with better quality are screened out to obtain the average level of the N communication nodes with better quality; Obtain the probability distribution function F(x) based on the average level of the entire network and the average level of N sites with good quality; According to the probability distribution function F(x), the communication nodes are grouped to obtain multiple communication node clusters.

3. A method for identifying a physical topology of a substation according to claim 1, characterized in that: The actual line communication distance Dis between different communication nodes A-B The calculation formula is: Dis A-B =(T loop ×V) / 2 Where V is the power line transmission speed; T loop is the net loop transmission time difference. When the processing delays of the two communicating nodes are the same, the formula is: T loop =(T4-T1)-2(T RX +T TX )+T comp_A +T comp_B Among them, T RX 、T TX are the receiving processing delay and sending processing delay of the two communication nodes, T comp_A 、T comp_B They are the time compensation values ​​of the receiving processing delay and the sending processing delay of the communication node respectively; T1 is the moment when one communication node starts to send a known signal to another communication node, and T4 is the moment when the communication node confirms receipt of the return signal.

4. A method for identifying a physical topology of a substation according to claim 1, characterized in that: The actual line communication distance Dis between different communication nodes A-B The calculation formula is: Dis A-B =(T loop ×V) / 2 Where V is the power line transmission speed; T loop is the net loop transmission time difference. When the processing delays of two communicating nodes are different, the formula is: T loop =(T4-T1)-(T RX_A +T TX_A )-(T RX_B +T TX_B )+T comp_A +T comp_B Among them, T RX_A 、T TX_A 、T RX_B 、T TX_B are the receiving processing delay and sending processing delay of the two communication nodes, T comp_A 、T comp_B They are the time compensation values ​​of the receiving processing delay and sending processing delay of the communication node respectively; T1 is the moment when one communication node starts to send a known signal to another communication node, and T4 is the moment when the communication node confirms that it has received the return signal.

5. The method for identifying a physical topology of a substation according to claim 1, characterized in that: The topology identification method further includes a clustering-assisted verification step: based on voltage correlation, the result of clustering and layering of the physical topology of the substation area is further accurately verified, specifically: According to the highly synchronized NTB clock between communication nodes, the voltage and current values ​​of the communication nodes are synchronously collected and stored, and broadcast locally; According to the increase and decrease of multiple voltage values ​​at different time points, verify whether the clustering and stratification are correct.

6. A method for identifying a physical topology of a substation according to claim 5, characterized in that: The verification of whether the clustering and stratification is correct according to the increase and decrease of multiple voltage values ​​at different time points in the group includes: Calculate the voltage similarity between two communication nodes based on the voltage value information of the communication nodes; The similarity calculation method of voltage sequence vector uses the cross-correlation algorithm: Among them, Vi(n) and Vj(n) are the voltage sequence vectors of the two-to-two communication nodes, n is the time index, and when the R of the two-to-two communication nodes in the cluster ij When it is greater than the preset threshold, the clustering and stratification are considered correct.

7. A method for identifying a physical topology of a substation according to claim 1, characterized in that: The topology identification method further includes a clustering auxiliary verification step: based on the active electric energy, the result of clustering and layering of the physical topology of the substation area is further accurately verified, specifically: The 96 power points of each communication node are collected, namely A0, A1, A2, A3, A4...A95; After processing, we get 95 points of electric energy: B0 = A1-A0, B1 = A2-A1, B2 = A3-A2…, B94 = A95-A94 The following algorithm is used for the 95-point electric energy of the communication node to calculate the covariance Cov(x,y) of the two communication nodes: Cov(X,Y)=E[(X-μ x )(Y-μ y )] Among them, X is the power value of the parent communication node, μ x is the average power value of the parent communication node, Y is the power value of the child communication node, μ y is the average power value of the sub-communication nodes; If the covariance is positive, it means that X and Y change in the same direction. The larger the covariance, the higher the degree of same direction. If the covariance is negative, it means that X and Y move in opposite directions. The smaller the covariance, the higher the degree of opposite direction. The correctness of clustering and stratification can be verified by the degree of same direction.

8. A physical topology identification system for a substation, characterized in that: The system comprises: An acquisition unit, used for acquiring HPLC carrier signals and HRF wireless signals of communication nodes in the station area; A clustering unit is used to group the communication nodes in the station area according to the difference in channel quality characteristics of the HPLC carrier signal and the HRF wireless signal to obtain multiple communication node clusters; A communication distance calculation unit, used to calculate the actual line communication distance between communication node clusters and / or between different communication nodes in a cluster by using the communication time of HPLC in the line; The clustering and layering division unit is used to perform layering division on communication nodes at different distances according to the actual line communication distance, so as to realize the clustering and layering division of the physical topology of the substation area.

9. An electronic device, comprising a memory and at least one processor, wherein instructions are stored in the memory; The at least one processor calls the instructions in the memory to enable the electronic device to execute each step of the method for identifying the physical topology of a metropolitan area as described in any one of claims 1 to 7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the various steps of the method for identifying the physical topology of a substation as described in any one of claims 1 to 7 are implemented.

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