Wide-area power system state estimation coordination method

Abstract

The invention relates to the technical field of power system state estimation, and particularly discloses a wide-area power system state estimation coordination method, which comprises the following steps: dividing a wide-area power grid into N dynamic monitoring areas based on power grid physical connection characteristics and electrical coupling strength, each area comprising a core node and n edge nodes; implementing dual-channel data fusion in each dynamic monitoring area, and comprehensively calculating the data credibility of each dynamic monitoring area; the whole operation state of the wide-area power grid is judged, and the wide-area power grid is integrally adjusted based on the judgment result, so that the accuracy and the reliability evaluation value of power grid monitoring can be remarkably improved, and accurate state judgment and adjustment are supported. The method has remarkable advantages and necessity in the aspects of improving the operation efficiency of the power grid, reducing the risk and optimizing the resource allocation, and can effectively deal with the complexity and dynamic change of the modern power grid.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system state estimation and relates to a wide-area power system state estimation coordination method. Background Art

[0002] The importance and necessity of wide-area power system state estimation coordination monitoring cannot be ignored. In modern power systems, with the expansion of the power grid scale and the increase in complexity, real-time monitoring and accurate estimation of the system state have become the key to ensuring the safe and stable operation of the power system. First of all, wide-area power system state estimation can provide a comprehensive system operation status, including key parameters such as voltage, frequency, and power flow. This information is crucial for timely identifying potential faults, optimizing power grid operation, improving efficiency, and reducing losses. In addition, coordinated monitoring can achieve cross-regional data sharing and collaborative analysis, helping operators make decisions on a larger scale, especially when dealing with emergencies such as natural disasters or equipment failures. This collaborative mechanism not only improves the power grid's risk resistance ability but also enhances its overall dispatching and control ability, ensuring the continuity and stability of power supply.

[0003] When current technologies perform emergency load shedding and frequency emergency control operations on wide-area power grids, there are still some defects and drawbacks. First of all, real-time performance and accuracy are the main challenges. Due to the large scale and complexity of the power grid, data acquisition and transmission may be affected by delays or errors, resulting in the inability to timely and accurately judge the power grid state. This delay may lead to untimely decisions, thus affecting the power grid stability. Secondly, existing load shedding strategies are usually based on preset rules, lacking flexibility and intelligence, and may not fully consider the priority and dynamic changes of actual loads, resulting in unnecessary economic losses and user dissatisfaction. In addition, frequency emergency control depends on the fast response ability of generating units, and many traditional power generation devices have a slow response speed and cannot quickly adjust the frequency. Summary of the Invention

[0004] In view of the above problems existing in the prior art, the present invention provides a wide-area power system state estimation coordination method to solve the above technical problems.

[0005] In order to achieve the above object and other objects, the technical solution adopted by the present invention is as follows: The present invention provides a wide-area power system state estimation coordination method, and the method includes the following steps: Step S1, divide the wide-area power grid into N dynamic monitoring regions based on the physical connection characteristics and electrical coupling strength of the power grid, and each region includes a core node and n edge nodes; Step S2: Implement dual-channel data fusion in each dynamic monitoring area. Obtain the data of each node in each dynamic monitoring area through the PMU measurement channel, and combine it with the data of each node in each dynamic monitoring area measured by the SCADA channel to comprehensively calculate the data credibility of each dynamic monitoring area; Step S3: Based on the data credibility of each dynamic monitoring area, judge the overall operating state of the wide-area power grid, and perform overall adjustment on the wide-area power grid based on the judgment result.

[0006] The basis for dividing the wide-area power grid into N dynamic monitoring areas is as follows: Obtain the phase angle and active power of the i-th node in the wide-area power grid at the current moment and the previous moment, and obtain the phase angle and active power of the j-th node at the current moment and the previous moment, and calculate the electrical coupling degree between the i-th node and the j-th node , are the active powers of nodes i / j at the current moment, are the active powers of nodes i / j at the previous moment, are the phase angles of nodes i / j at the current moment, are the phase angles of nodes i / j at the previous moment; Collect the communication delay from node i to node j and the impedance similarity , so as to calculate the dynamic weight matrix from node i to node j , where e is the natural constant.

[0007] The process of dividing the wide-area power grid into N dynamic monitoring areas is as follows: By setting an adaptive threshold Screen strong connection relationships and only retain the significant associations with weight values in the top 30%; For the isolated nodes generated by threshold filtering, use the virtual edge compensation mechanism to assign them weak connection values to ensure network full connectivity; A is the weak connection value; Subsequently, initially estimate the number of partitions N based on the square root of the total number of nodes in the wide-area power grid, and dynamically correct the partition scale through the ratio of the matrix trace to the element sum; Then calculate the normalized Laplacian matrix and perform eigenvalue decomposition, extract the eigenvectors corresponding to the first N largest eigenvalues to construct the feature space, and use the improved K-means++ algorithm to perform clustering in the feature space, forcing the initial centroid distance to be no less than 50% of the maximum distance in the feature space to ensure the rationality of partitioning; After the preliminary division, comprehensively evaluate the node connectivity and the magnitude of the eigenvector within each partition, select the node with the highest comprehensive index as the core monitoring point, calculate the membership degree of the boundary node in the feature space of the adjacent area, and establish an overlapping buffer when the membership degree difference is less than 10% to maintain the continuity of state estimation.

[0008] The operation logic of step S2 is as follows: The data of each node in each dynamic monitoring area includes voltage amplitude, phase angle, active power, reactive power, and frequency; Perform time scale alignment of the PMU measurement channel and the SCADA channel every 200 ms, and record the maximum time difference △t; Thus, calculate the credibility of the voltage amplitude data of each dynamic monitoring area , where λ is the time decay coefficient, λ = 1 / τ, τ is the device clock synchronization period, e is the natural constant, and β1 is the weight coefficient of the set time delay factor corresponding to the data credibility; k is the number of each dynamic monitoring area; is the average relative deviation of voltage measurement in each dynamic monitoring area, and β2 and β3 respectively represent the weighting factors of the reliability evaluation values corresponding to the PMU measurement channel and the SCADA channel, and the sum of the two is 1; represents the reliability evaluation value of the PMU measurement channel, represents the reliability evaluation value of the SCADA channel; According to the calculation method of the credibility of the voltage amplitude data of each dynamic monitoring area, calculate the credibility of the phase angle data, active power data, reactive power data, and frequency data of each dynamic monitoring area in the same way; Sum up the credibility of the voltage amplitude data, phase angle data, active power data, reactive power data, and frequency data of each dynamic monitoring area, and perform a division operation on the summation result and the number 5 to obtain the data credibility of each dynamic monitoring area.

[0009] Average relative deviation of voltage measurement in each dynamic monitoring area The calculation formula is , are the voltage amplitudes corresponding to the PMU measurement channel and the SCADA channel at the i-th node in the k-th dynamic monitoring area respectively, i is the number of each node, i = 1, 2,..., G, and G is the total number of nodes in the dynamic monitoring area, is the set voltage reference value, and Γ is the maximum allowable deviation threshold; represents the reliability evaluation value of the PMU measurement channel, and its specific calculation formula is ; are the number of PMU synchronous phasor matches and the total number of PMU matches respectively; They respectively represent the PMU data packet loss rate and the preset maximum PMU data packet loss rate during the set sliding window period; It is expressed as the reliability evaluation value of the SCADA channel, and its specific calculation formula is: ,in are the actual refresh cycle and standard refresh cycle of the SCADA channel respectively, and ξ is the preset aging attenuation coefficient.

[0010] The operation logic of step S3 is: When the data credibility of each dynamic monitoring area is greater than 0.9, the voltage amplitude of each node in each dynamic monitoring area is subtracted from the rated voltage, and the difference is calculated by absolute value. The value after absolute value calculation is used as the numerator of the fraction, and the rated voltage is used as the denominator of the fraction. Finally, the voltage stability index of each node in each dynamic monitoring area is calculated, and then the sum and average calculation of each dynamic monitoring area and each node are performed respectively. The result of the sum and average calculation of each dynamic monitoring area and each node is subtracted from the number 1, and finally the voltage stability assessment index of the wide area power grid is obtained. ; The phase angle difference of each node in each dynamic monitoring area is obtained by subtracting the phase angle of the jth node from the phase angle of the i-th node in each dynamic monitoring area, and the absolute value operation is performed on it. The phase angle difference with the largest phase angle difference is selected from them and used as the numerator of the fraction. The value π is used as the denominator of the fraction. The result of the fraction operation is subtracted from 1, and the phase angle stability assessment index of the wide area power grid is finally obtained. ; The final comprehensive calculation results in the comprehensive status assessment index of the wide area power grid. , are the total power generation and total load of the wide area power grid respectively.

[0011] Compare the comprehensive status assessment index of the wide area power grid with the set threshold; If the former is greater than or equal to the latter, it means that the operation status of the wide area power grid is normal operation and no operation is performed on it; If the former is less than the latter, it means that the operation state of the wide area power grid is abnormal, and emergency load shedding and frequency emergency control operations are performed on the wide area power grid: , It is the emergency load shedding data value of the wide area power grid; , It is the frequency emergency control data value of the wide area power grid; is the average frequency of the entire network.

[0012] As described above, a wide-area power system state estimation coordination method provided by the present invention has at least the following beneficial effects: A wide-area power system state estimation coordination method provided by the present invention divides the wide-area power grid into multiple dynamic monitoring regions based on the physical connection characteristics and electrical coupling strength of the power grid. Dividing the dynamic monitoring regions helps improve the fineness of power grid monitoring. Each region contains a core node and multiple edge nodes. This structure can effectively capture the electrical characteristics and dynamic changes within the region, ensuring the accuracy and timeliness of monitoring data. Through dual-channel data fusion, multi-source data can be comprehensively utilized to improve the credibility and robustness of the data. This fusion technology can effectively filter out noise and abnormal data, ensuring the reliability evaluation value of the monitoring results; it can significantly improve the accuracy and efficiency of power grid state estimation. The traditional single data channel may be affected by sensor failures or data transmission interruptions, while dual-channel fusion can provide redundancy and supplementation to ensure data integrity. Through regional division and data fusion, power grid operators can obtain more accurate state estimations, promptly identify potential problems, and optimize resource allocation. This is crucial for improving the operating efficiency and safety of the power grid. In addition, regional division can also achieve distributed computing and monitoring, reducing the burden of centralized processing, and lowering system complexity and computing costs.

[0013] Through regional division, the local characteristics and overall dynamics of the power grid can be better understood. The state information of each region can be summarized to form an overall judgment of the wide-area power grid, thereby supporting more accurate decision-making and adjustment. For example, by identifying abnormalities in a certain region, local adjustment measures can be quickly implemented to prevent problems from spreading to the entire power grid. This monitoring and adjustment mechanism that combines local and overall aspects can improve the response speed and adaptability of the power grid. At the same time, it can achieve more efficient resource allocation and risk management. Through the collaborative monitoring of the core node and edge nodes within the region, operators can better understand the load distribution and electrical coupling characteristics of the power grid, thereby optimizing power generation and transmission strategies. This not only improves the economy of the power grid but also enhances its resistance to emergencies. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0015] Figure 1 It is a connection schematic diagram of the steps of the method of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0016] The following will combine the embodiments of the present invention. The above content is only an example and explanation of the concept of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by this claim book, they should all fall within the protection scope of the present invention.

[0017] Embodiment 1: Please refer to Figure 1 As shown, a wide-area power system state estimation coordination method, which includes the following steps: Step S1: Based on the physical connection characteristics and electrical coupling strength of the power grid, divide the wide-area power grid into N dynamic monitoring areas, and each area contains a core node and n edge nodes; The basis for dividing the wide-area power grid into N dynamic monitoring areas is: Obtain the phase angle and active power of the i-th node in the wide-area power grid at the current moment and the previous moment, and obtain the phase angle and active power of the j-th node at the current moment and the previous moment, and thus calculate the electrical coupling degree between the i-th node and the j-th node , are the active powers of nodes i / j at the current moment respectively, are the active powers of nodes i / j at the previous moment respectively, are the phase angles of nodes i / j at the current moment respectively, are the phase angles of nodes i / j at the previous moment respectively; Collect the communication delay and impedance similarity of the link from node i to node j. The collection process is summarized as follows: For communication delay collection, first, clock synchronization calibration is performed through the IEEE 1588 PTP v2.1 hardware timestamp scheme, a fiber optic B-code time synchronization network is constructed, and the fiber optic transmission delay and switch forwarding delay are calculated using the delay compensation formula. For nodes where PTP cannot be deployed, NTPv4 hierarchical time calibration is enabled to ensure that the maximum time deviation is controlled within ±2ms. Then, by designing a probe frame with a 64-byte ICMP frame and a 16-byte power-specific extension header, 1 group of 3 frames of burst is sent every 200ms, and after continuously sending for 10 cycles, pause for 2 seconds. The sending end and the receiving end respectively record the DPDK hardware timestamp accurate to the μs level and the arrival timestamp captured by the FPGA packet capture engine, calculate the end-to-end delay, perform validity filtering and clock deviation compensation. At the same time, through sFlow sampling analysis of link utilization and QoS priority mapping, the dynamic compensation algorithm adjusts the final delay value according to the link utilization, stores the delay matrix in the TSDB time series database, and abnormal events trigger SNMP trap alarms; Impedance similarity acquisition first imports the CIM / E format power grid model from EMS, analyzes the electrical connection relationship between nodes i and j, constructs the node admittance matrix and extracts the self-admittance and mutual admittance, and obtains real-time measurement data through PMU and SCADA. Calculate the theoretical impedance and measured impedance, perform data cleaning, and remove invalid light-load data. Then, extract the frequency domain features of the impedance, calculate the spectrum correlation coefficient and time domain similarity index, and the comprehensive similarity is obtained by weighting the frequency domain correlation coefficient and time domain similarity index.

[0018] Thus, the dynamic weight matrix from node i to node j is calculated , e is a natural constant.

[0019] The partitioning process of dividing the wide area power grid into N dynamic monitoring areas is as follows: By setting the adaptive threshold Filter strong connections and only retain significant associations with weight values ​​in the top 30%; For the isolated nodes generated by threshold filtering, a virtual edge compensation mechanism is used to give them The weak connection value ensures the full connectivity of the network; A is the weak connection value; Then, the number of partitions N is preliminarily estimated based on the square root of the total number of nodes in the wide area power grid, and the partition size is dynamically corrected by the ratio of the matrix trace to the sum of the elements; Then, the standardized Laplacian matrix is ​​calculated and eigendecomposition is performed. The eigenvectors corresponding to the first N largest eigenvalues ​​are extracted to construct the feature space. The improved K-means++ algorithm is used to perform clustering in the feature space, forcing the initial centroid distance to be no less than 50% of the maximum distance in the feature space to ensure the rationality of the partition. After completing the preliminary division, the node connectivity and feature vector modulus are comprehensively evaluated in each partition, and the nodes with the highest comprehensive index are selected as core monitoring points. The membership of the boundary nodes in the feature space of the adjacent area is calculated. When the membership difference is less than 10%, an overlapping buffer zone is established to maintain the continuity of state estimation.

[0020] Step S2: implement dual-channel data fusion in each dynamic monitoring area, obtain the data of each node in each dynamic monitoring area through the PMU measurement channel, combine the data of each node in each dynamic monitoring area measured by the SCADA channel, and comprehensively calculate the data credibility of each dynamic monitoring area; The operation logic of step S2 is: The data of each node in each dynamic monitoring area includes voltage amplitude, phase angle, active power, reactive power and frequency; The PMU measurement channel and SCADA channel time alignment is performed every 200ms, and the maximum time difference △t is recorded; The reliability of the voltage amplitude data in each dynamic monitoring area is calculated based on this , where λ is the time decay coefficient, λ = 1 / τ, τ is the device clock synchronization period, e is the natural constant, and β1 is the weight coefficient corresponding to the data credibility of the set time delay factor; k is the number of each dynamic monitoring area; Average relative deviation of voltage measurement in each dynamic monitoring area The calculation formula is , are the voltage amplitudes of the PMU measurement channel and the SCADA channel corresponding to the i-th node in the k-th dynamic monitoring area respectively, i is the number of each node, i = 1, 2,..., G, and G is the total number of nodes in the dynamic monitoring area, is the set voltage reference value, and Γ is the maximum allowable deviation threshold; β2 and β3 respectively represent the weighting factors of the reliability evaluation values corresponding to the PMU measurement channel and the SCADA channel, and the sum of the two is 1, , ; represents the reliability evaluation value of the PMU measurement channel, and its specific calculation formula is ; are the number of PMU synchronous phasor matches and the total number of PMU matches respectively; respectively represent the PMU data packet loss rate and the preset maximum PMU data packet loss rate during the set sliding window period; represents the reliability evaluation value of the SCADA channel, and its specific calculation formula is , where are the actual refresh period and the standard refresh period of the SCADA channel respectively, and ξ is the preset aging decay coefficient; Calculate the data credibility of the phase angle data, active power data, reactive power data, and frequency data of each dynamic monitoring area in the same way as the calculation method of the voltage amplitude data credibility of each dynamic monitoring area; Sum up the voltage amplitude data credibility, phase angle data credibility, active power data credibility, reactive power data credibility, and frequency data credibility of each dynamic monitoring area, and perform a division operation on the sum result and the number 5 to obtain the data credibility of each dynamic monitoring area.

[0021] When the data credibility of a certain dynamic monitoring area is < 0.9, the system will start a hierarchical closed-loop processing process: First, trigger the anomaly location mechanism, use the hybrid neural network model to extract spatio-temporal features from the high-dimensional state matrix of 10 consecutive cycles, and output the anomaly probability; if the anomaly probability > 0.75, broadcast a collaborative verification request to adjacent areas through the federated learning framework, and synchronously activate the three-level coordinated optimization - the first level adjusts the local measurement weight matrix and recalculates the state estimation, the second level introduces the dynamic data of PMUs in adjacent areas to construct a joint observation model, and the third level calls the ADMM-based network-wide state reconstruction algorithm for global consistency correction; at the same time, start the blockchain smart contract to perform multi-node cross-verification on the correction results, and the verification items include the power flow equation residual (threshold ±2%), the continuity of time-series data (DTW distance < 0.1), and the LSTM prediction deviation (MAE < 3%); if the verification pass rate is lower than 85%, switch to the historical similar scenario mode, use dynamic time warping (DTW) to match the optimal coordination strategy of similar anomaly cases in the recent 30 days, and update the coordination strategy knowledge base in real time; finally, generate a self-healing instruction set containing the weight adjustment coefficient (Δω ∈ [-0.2, 0.5]), the sampling frequency (dynamically adjusted from 1 to 5 Hz), and the communication channel priority (QoS level 1-3). After the processing is completed, re-evaluate the credibility to form a closed-loop management of "anomaly detection - collaborative correction - credible verification - strategy evolution" to ensure that the regional state estimation error is restored to the benchmark level within 300 ms.

[0022] Step S3: Based on the data credibility of each dynamic monitoring area, judge the overall operation state of the wide-area power grid, and make an overall adjustment to the wide-area power grid based on the judgment result.

[0023] The operation logic of Step S3 is as follows: When the data credibility of each dynamic monitoring area is greater than 0.9, subtract the rated voltage from the voltage amplitude of each node in each dynamic monitoring area, perform an absolute value operation on the difference, use the result after the absolute value operation as the numerator of the fraction, and use the rated voltage as the denominator of the fraction. Finally, calculate the voltage stability index of each node in each dynamic monitoring area, and then perform summation and mean calculation on each dynamic monitoring area and each node respectively. Subtract the result of the summation and mean calculation of each dynamic monitoring area and each node from the number 1 to finally obtain the voltage stability evaluation index of the wide-area power grid ; Subtract the phase angle of the j-th node from the phase angle of the i-th node in each dynamic monitoring area to obtain the phase angle difference of each node in each dynamic monitoring area, perform an absolute value operation on it, select the largest phase angle difference from them, use it as the numerator of the fraction, use the value π as the denominator of the fraction, and subtract the operation result of the fraction from the number 1 to finally obtain the phase angle stability evaluation index of the wide-area power grid ; Finally, through comprehensive operations, the comprehensive state evaluation index of the wide-area power grid is obtained. , which are the total power generation and total load of the wide-area power grid respectively.

[0024] Compare the comprehensive state evaluation index of the wide-area power grid with the set threshold; If the former is greater than or equal to the latter, it indicates that the operating state of the wide-area power grid is normal, and no operation is performed on it; If the former is less than the latter, it indicates that the operating state of the wide-area power grid is abnormal, and emergency load shedding and frequency emergency control operations are performed on the wide-area power grid: , is the emergency load shedding data value of the wide-area power grid; The core idea of the above calculation formula is to relieve the grid pressure by reducing the load, especially when the power generation is insufficient to meet the load demand. In the formula, represents the total load of the current power grid, while represents the current total power generation. The purpose of the formula is to take measures to reduce part of the load when the load exceeds 90% of the power generation capacity to avoid grid overload: The implementation logic is as follows: 1. Monitor the grid status: Monitor the load and power generation of the grid in real time, and obtain the and data through the SCADA system or other monitoring tools; 2. Calculate the difference between load and power generation: Calculate -0.9× , which reflects the gap between the current load and the power generation capacity. If the result is positive, it means that the load exceeds 90% of the safe power generation capacity; 3. Evaluate the load to be reduced: Use to determine whether load shedding is required. If the difference is positive, it means that load shedding is required; if it is zero or negative, no action is needed; 4. Implement load shedding: According to the calculation result, reduce 20% of the excess load. This can be executed through an automated control system, selectively shutting down some non-critical loads or negotiating with users through a demand response mechanism for load adjustment.

[0025] , is the frequency emergency control data value of the wide-area power grid; is the average frequency of the entire network.

[0026] The above calculation formula is used to adjust the power grid frequency to ensure that it is maintained at the rated value (usually 50Hz). The stability of the frequency is crucial for the normal operation of the power grid, because frequency deviation may cause equipment damage or system instability.

[0027] The implementation logic is as follows: 1. Frequency monitoring: Continuously monitor the average frequency of the power grid , usually monitored by a frequency meter or intelligent sensor; 2. Calculate the frequency deviation: Calculate 50 - , this value represents the deviation between the current frequency and the rated frequency; 3. Evaluate the adjustment requirement: Determine the adjustment intensity according to the magnitude of the deviation. The coefficient of 0.5 multiplied in the formula is used to control the adjustment amplitude to ensure a smooth adjustment process without overshoot; 4. Implement frequency adjustment: Adjust the frequency by adjusting the speed of the generator or using energy storage devices. The generator can quickly respond to frequency changes by changing the fuel input or speed, while the energy storage device can provide or absorb power to stabilize the frequency.

[0028] It should be understood that in various embodiments of the present application, the magnitudes of the serial numbers of the above processes do not mean the order of execution, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0029] It should be understood that determining B according to A does not mean determining B only according to A, but also B can be determined according to A and / or other information.

[0030] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present application, and all should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0031] Finally: The above is only the preferred embodiment of the present invention and is not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A wide-area power system state estimation coordination method, characterized in that, It includes the following steps: Step S1: Based on the physical connection characteristics and electrical coupling strength of the power grid, the wide-area power grid is divided into N dynamic monitoring areas, and each area contains a core node and n edge nodes; Step S2: Implement dual-channel data fusion within each dynamic monitoring area. Obtain the data of each node within each dynamic monitoring area through the PMU measurement channel, combine it with the data of each node within each dynamic monitoring area measured by the SCADA channel, and comprehensively calculate the data credibility of each dynamic monitoring area; Step S3: Based on the data credibility of each dynamic monitoring area, judge the overall operation state of the wide-area power grid, and perform overall adjustment on the wide-area power grid based on the judgment result.

2. A wide-area power system state estimation coordination method according to claim 1, characterized in that The partitioning basis for dividing the wide-area power grid into N dynamic monitoring areas is: Obtain the phase angles and active powers of the \(i\)-th node in the wide-area power grid at the current moment and the previous moment, and obtain the phase angles and active powers of the \(j\)-th node at the current moment and the previous moment, and thereby calculate the electrical coupling degree between the \(i\)-th node and the \(j\)-th node , are the active powers of nodes \(i / j\) at the current moment, are the active powers of nodes \(i / j\) at the previous moment, are the phase angles of nodes \(i / j\) at the current moment, are the phase angles of nodes \(i / j\) at the previous moment; Communication delay from collection node i to node j and impedance similarity , thereby calculating the dynamic weight matrix from node i to node j , where e is the natural constant.

3. A wide-area power system state estimation coordination method according to claim 2, characterized in that, The partitioning process of dividing the wide-area power grid into N dynamic monitoring areas is as follows: By setting an adaptive threshold Filter strong connection relationships and only retain the significant associations with weight values in the top 30%; For the isolated nodes generated by threshold filtering, a virtual edge compensation mechanism is adopted to assign them with weak connection values to ensure the full connectivity of the network; A is the weak connection value; Subsequently, initially estimate the number of partitions N according to the square root of the total number of nodes in the wide-area power grid, and dynamically correct the partition scale through the ratio of the matrix trace to the element sum; Then calculate the normalized Laplacian matrix and perform eigen-decomposition, extract the eigenvectors corresponding to the first N largest eigenvalues to construct the feature space, and execute clustering within the feature space using the improved K-means++ algorithm, forcing the initial centroid distance to be no less than 50% of the maximum distance in the feature space to ensure the rationality of partitioning; After the preliminary partitioning is completed, comprehensively evaluate the node connectivity and the norm of the eigenvector within each partition, select the node with the highest comprehensive index as the core monitoring point, calculate the membership degree of the boundary node in the feature space of the adjacent area, and establish an overlapping buffer when the membership degree difference is less than 10% to maintain the continuity of state estimation.

4. A wide-area power system state estimation coordination method according to claim 1, characterized in that The operation logic of Step S2 is: The data of each node within each dynamic monitoring area includes voltage amplitude, phase angle, active power, reactive power, and frequency; Perform time-scale alignment of the PMU measurement channel and the SCADA channel every 200 ms, and record the maximum time difference △t; Calculate the credibility of the voltage amplitude data for each dynamic monitoring area accordingly , where λ is the time decay coefficient, λ = 1 / τ, τ is the device clock synchronization period, e is the natural constant, and β1 is the weight coefficient corresponding to the data credibility of the set time delay factor; k is the number of each dynamic monitoring area; is the average relative deviation of the voltage measurement in each dynamic monitoring area, and β2 and β3 respectively represent the weighting factors of the reliability evaluation values corresponding to the PMU measurement channel and the SCADA channel, and the sum of the two is 1; represents the reliability evaluation value of the PMU measurement channel, represents the reliability evaluation value of the SCADA channel; Calculate the data credibility of the phase angle, active power, reactive power, and frequency of each dynamic monitoring area in the same way as the calculation method of the data credibility of the voltage amplitude data of each dynamic monitoring area; Sum up the data credibility of the voltage amplitude, phase angle, active power, reactive power, and frequency of each dynamic monitoring area, and perform a division operation on the sum result and the number 5 to obtain the data credibility of each dynamic monitoring area.

5. A wide-area power system state estimation coordination method according to claim 4, characterized in that: Average relative deviation of voltage measurement in each dynamic monitoring area The calculation formula is , are the voltage amplitudes of the i-th node in the k-th dynamic monitoring area corresponding to the PMU measurement channel and the SCADA channel respectively. i is the number of each node, i = 1, 2,..., G, and G is the total number of nodes in the dynamic monitoring area. is the set voltage reference value, and Γ is the maximum allowable deviation threshold; Indicates the reliability evaluation value of the PMU measurement channel, and its specific calculation formula is ; are the number of PMU synchronized phasor matches and the total number of PMU matches respectively; respectively represent the PMU data packet loss rate and the preset maximum PMU data packet loss rate during the set sliding window period; Denoted as the reliability evaluation value of the SCADA channel, and its specific calculation formula is , where are respectively the actual refresh period and the standard refresh period of the SCADA channel, and ξ is a preset aging attenuation coefficient.

6. The wide-area power system state estimation coordination method according to claim 1, characterized in that, The operation logic of Step S3 is: When the data credibility of each dynamic monitoring area is greater than 0.9, subtract the rated voltage from the voltage amplitude of each node in each dynamic monitoring area respectively, perform an absolute value operation on the difference, then use the value after the absolute value operation as the numerator of the fraction, and use the rated voltage as the denominator of the fraction. Finally, calculate the voltage stability index of each node in each dynamic monitoring area, then sum and calculate the average value for each dynamic monitoring area and each node respectively, and subtract the result of the sum and average value calculation of each dynamic monitoring area and each node from the number 1 to finally obtain the voltage stability evaluation index of the wide-area power grid ; Subtract the phase angle of the i-th node from the phase angle of the j-th node in each dynamic monitoring area to obtain the phase angle difference of each node in each dynamic monitoring area, perform an absolute value operation on it, select the largest phase angle difference from them, use it as the numerator of the fraction, use the value π as the denominator of the fraction, and subtract the operation result of the fraction from the number 1 to finally obtain the phase angle stability evaluation index of the wide-area power grid ; Finally, through comprehensive operations, the comprehensive state evaluation index of the wide-area power grid is obtained. , which are the total power generation and total load of the wide-area power grid, respectively.

7. A wide-area power system state estimation coordination method according to claim 6, characterized in that: Compare the comprehensive state evaluation index of the wide-area power grid with a set threshold; If the former is greater than or equal to the latter, it means that the operation state of the wide-area power grid is in a normal operation state, and no operation is performed on it; If the former is less than the latter, it means that the operation state of the wide-area power grid is in an abnormal operation state, and emergency load shedding and frequency emergency control operations are performed on the wide-area power grid: , is the emergency load shedding data value of the wide-area power grid; , is the frequency emergency control data value of the wide-area power grid; is the average frequency of the whole network.

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