A coordinated approach to wide-area power system state estimation

Abstract

The present invention relates to the technical field of power system state estimation, and specifically discloses a wide-area power system state estimation coordination method. 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, each area containing a core node and n edge nodes; dual-channel data fusion is implemented in each dynamic monitoring area, and the data credibility of each dynamic monitoring area is comprehensively calculated; and the overall operating status of the wide-area power grid is judged, and the wide-area power grid is adjusted as a whole based on the judgment results. This method can significantly improve the accuracy and reliability evaluation value of power grid monitoring and support accurate state judgment and adjustment. This method has significant benefits and necessity in improving power grid operation efficiency, reducing risks, and optimizing resource allocation, and can effectively cope with the complexity and dynamic changes of modern power grids.

Description

Technical Field

[0001] The 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 coordinated monitoring of wide-area power system state estimation cannot be ignored. In modern power systems, as the scale and complexity of power grids increase, real-time monitoring and accurate estimation of system state become key to ensuring safe and stable operation of the power system. First, wide-area power system state estimation can provide comprehensive system operating conditions, including key parameters such as voltage, frequency, and power flow. This information is crucial for timely identifying potential faults, optimizing grid operation, improving efficiency, and reducing losses. In addition, coordinated monitoring enables cross-regional data sharing and collaborative analysis, helping operators make decisions on a larger scale, especially when responding to emergencies such as natural disasters or equipment failures. This collaborative mechanism not only improves the grid's risk resistance but also enhances its overall dispatching and control capabilities, ensuring the continuity and stability of power supply.

[0003] Current technologies still have some defects and drawbacks when performing emergency load shedding and frequency emergency control operations on wide-area power grids. First, real-time and accuracy are the main challenges. Due to the large scale and complexity of the power grid, data collection and transmission may be affected by delays or errors, resulting in an inability to accurately judge the status of the power grid in a timely manner. This delay may lead to untimely decision-making, thereby affecting the stability of the power grid. Secondly, existing load shedding strategies are usually based on preset rules, lack 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 relies on the rapid response capability of the generator set, while many traditional power generation equipment have a slow response speed and cannot quickly adjust the frequency. Summary of the Invention

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

[0005] In order to achieve the above-mentioned and other purposes, the technical solutions adopted by the present invention are as follows:

[0006] The present invention provides a wide-area power system state estimation and coordination method, which includes the following steps:

[0007] 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, each area including a core node and n edge nodes;

[0008] Step S2: Implement dual-channel data fusion in each dynamic monitoring area, obtain 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;

[0009] Step S3: Based on the data credibility of each dynamic monitoring area, the overall operation status of the wide area power grid is judged, and the wide area power grid is adjusted as a whole based on the judgment result.

[0010] The basis for dividing the wide area power grid into N dynamic monitoring areas is:

[0011] Obtain the phase angle and active power of the i-th node at the current moment and the previous moment in the wide area power grid, 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 power of node i / j at the current moment, are the active power of node i / j at the previous moment, are the phase angles of nodes i / j at the current moment, are the phase angles of node i / j at the previous moment;

[0012] Collect the communication delay from node i to node j and impedance similarity , thereby calculating the dynamic weight matrix from node i to node j , e is a natural constant.

[0013] The partitioning process of dividing the wide area power grid into N dynamic monitoring areas is as follows:

[0014] By setting the adaptive threshold Filter strong connections and only retain significant connections with weight values ​​in the top 30%;

[0015] For the isolated nodes caused by threshold filtering, a virtual edge compensation mechanism is used to give them The weak connection value of , ensures the full connectivity of the network; A is the weak connection value;

[0016] 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;

[0017] Then, the normalized 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. The initial centroid distance is forced to be no less than 50% of the maximum distance in the feature space to ensure the rationality of the partitioning.

[0018] After completing the preliminary division, the node connectivity and eigenvector modulus are comprehensively evaluated in each partition. 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 the state estimation.

[0019] The operation logic of step S2 is:

[0020] The data of each node in each dynamic monitoring area includes voltage amplitude, phase angle, active power, reactive power and frequency;

[0021] The PMU measurement channel and SCADA channel time scale alignment is performed every 200ms, and the maximum time difference △t is recorded;

[0022] The reliability of the voltage amplitude data of each dynamic monitoring area is calculated based on this , where λ is the time attenuation coefficient, λ=1 / τ, τ is the device clock synchronization period, e is a natural constant, β1 is the weight coefficient of the data credibility corresponding to the set delay factor; k is the number of each dynamic monitoring area; is the average relative deviation of voltage measurement in each dynamic monitoring area, β2 and β3 are weighting factors of the reliability evaluation values ​​corresponding to the PMU measurement channel and SCADA channel, respectively, and the sum of the two is 1; Represents the reliability evaluation value of the PMU measurement channel, Expressed as the reliability evaluation value of the SCADA channel;

[0023] The phase angle data reliability, active power data reliability, reactive power data reliability and frequency data reliability of each dynamic monitoring area are calculated in the same way as the voltage amplitude data reliability of each dynamic monitoring area.

[0024] 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 are summed, and the summed result is divided by the number 5 to obtain the data credibility of each dynamic monitoring area.

[0025] 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, G is the total number of nodes in the dynamic monitoring area, is the set voltage reference value, Γ is the maximum allowable deviation threshold;

[0026] It represents the reliability evaluation value of the PMU measurement channel. Its specific calculation formula is: ; They are the PMU synchrophasor matching number and the PMU total matching number respectively; They represent the PMU data packet loss rate and the preset maximum PMU data packet loss rate during the set sliding window period respectively;

[0027] 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.

[0028] The operation logic of step S3 is:

[0029] 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 the 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 of each dynamic monitoring area and each node are calculated. The result of the sum and average calculation of each dynamic monitoring area and each node is subtracted from 1 to finally obtain the voltage stability assessment index of the wide area power grid. ;

[0030] 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. The absolute value operation is performed on the phase angle difference, and the phase angle difference with the largest phase angle difference is selected 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 to finally obtain the phase angle stability assessment index of the wide area power grid. ;

[0031] The final comprehensive calculation results in the comprehensive state assessment index of the wide area power grid. , are the total power generation and total load of the wide area power grid, respectively.

[0032] Comparing the comprehensive status assessment index of the wide-area power grid with the set threshold;

[0033] If the former is greater than or equal to the latter, it means that the wide area power grid is in normal operation and no operation is performed on it;

[0034] If the former is less than the latter, it means that the wide area power grid is in an abnormal operating state, and emergency load shedding and frequency emergency control operations are performed on the wide area power grid:

[0035] , It is the emergency load shedding data value of the wide area power grid;

[0036] , It is the frequency emergency control data value of the wide area power grid; is the average frequency of the entire network.

[0037] As described above, the wide-area power system state estimation and coordination method provided by the present invention has at least the following beneficial effects:

[0038] This invention provides a coordinated method for wide-area power system state estimation. This method divides a wide-area power grid into multiple dynamic monitoring regions based on the grid's physical connectivity characteristics and electrical coupling strength. This dynamic monitoring region division helps improve the precision of grid monitoring. Each region consists of a core node and multiple edge nodes. This structure effectively captures the electrical characteristics and dynamic changes within the region, ensuring the accuracy and timeliness of monitoring data. Dual-channel data fusion enables the comprehensive utilization of multi-source data, improving data reliability and robustness. This fusion technique effectively filters out noise and abnormal data, ensuring the reliability assessment of monitoring results and significantly improving the accuracy and efficiency of grid state estimation. While traditional single data channels may be affected by sensor failures or data transmission interruptions, dual-channel fusion provides redundancy and supplementation, ensuring data integrity. Through regional division and data fusion, grid operators can obtain more accurate state estimates, promptly identify potential issues, and optimize resource allocation. This is crucial for improving grid operational efficiency and security. Furthermore, regional division enables distributed computing and monitoring, reducing the burden of centralized processing, system complexity, and computational costs.

[0039] Regionalization allows for a better understanding of both the local characteristics and overall dynamics of the power grid. Status information from each region can be aggregated to form a comprehensive assessment of the wide-area power grid, supporting more accurate decision-making and adjustments. For example, by identifying anomalies in a specific region, local adjustments can be quickly implemented to prevent the problem from spreading to the entire grid. This integrated monitoring and adjustment mechanism improves the grid's responsiveness and adaptability, while also enabling more efficient resource allocation and risk management. Through collaborative monitoring of core and edge nodes within a region, operators can better understand the grid's load distribution and electrical coupling characteristics, enabling them to optimize generation and transmission strategies. This not only improves the grid's economic efficiency but also strengthens its resilience to emergencies. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0041] Figure 1 It is a schematic diagram of the connection of each step of the method of the present invention. DETAILED DESCRIPTION

[0042] The above contents described below in conjunction with the implementation of the present invention are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they shall fall within the scope of protection of the present invention.

[0043] Example 1: Please refer to Figure 1 As shown, a wide area power system state estimation coordination method includes the following steps:

[0044] 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, each area including a core node and n edge nodes;

[0045] The basis for dividing the wide area power grid into N dynamic monitoring areas is:

[0046] Obtain the phase angle and active power of the i-th node at the current moment and the previous moment in the wide area power grid, 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 power of node i / j at the current moment, are the active power of node i / j at the previous moment, are the phase angles of nodes i / j at the current moment, are the phase angles of node i / j at the previous moment;

[0047] Collect the communication delay from node i to node j and impedance similarity , the collection process can be summarized as follows:

[0048] Communication delay collection first uses the IEEE 1588 PTP v2.1 hardware timestamp solution to perform clock synchronization calibration, build a fiber B-code timing network, and use the delay compensation formula to calculate the fiber transmission delay and switch forwarding delay. For nodes where PTP cannot be deployed, NTPv4 hierarchical time synchronization is enabled to ensure that the maximum time deviation is controlled within ±2ms. Next, by designing a probe frame with a 64-byte ICMP frame and a 16-byte power-specific extension header, a burst of 3 frames is sent every 200ms. After 10 consecutive cycles, a pause of 2 seconds is paused. The sending and receiving ends respectively record the DPDK hardware timestamp and FPGA packet capture engine arrival timestamp accurate to the μs level, calculate the end-to-end delay, and perform validity filtering and clock deviation compensation. At the same time, through sFlow sampling and analysis of link utilization and QoS priority mapping, the dynamic compensation algorithm adjusts the final delay value according to the link utilization, and stores the delay matrix in the TSDB time series database. Abnormal events trigger SNMP trap alarms;

[0049] Impedance similarity acquisition begins by importing a CIM / E-formatted power grid model from the EMS. The electrical connections between nodes i and j are analyzed, a node admittance matrix is ​​constructed, and the self-admittance and mutual admittance are extracted. Real-time measurement data is simultaneously acquired through the PMU and SCADA. Theoretical and measured impedances are calculated, and data cleaning is performed to remove invalid light-load data. Next, frequency domain feature extraction is performed on the impedances, and the spectral correlation coefficient and time domain similarity index are calculated. The overall similarity is derived by weighting the frequency domain correlation coefficient and the time domain similarity index.

[0050] Thus calculating the dynamic weight matrix from node i to node j , e is a natural constant.

[0051] The partitioning process of dividing the wide area power grid into N dynamic monitoring areas is as follows:

[0052] By setting the adaptive threshold Filter strong connections and only retain significant connections with weight values ​​in the top 30%;

[0053] For the isolated nodes caused by threshold filtering, a virtual edge compensation mechanism is used to give them The weak connection value of , ensures the full connectivity of the network; A is the weak connection value;

[0054] 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;

[0055] Then, the normalized 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. The initial centroid distance is forced to be no less than 50% of the maximum distance in the feature space to ensure the rationality of the partitioning.

[0056] After completing the preliminary division, the node connectivity and eigenvector modulus are comprehensively evaluated in each partition. 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 the state estimation.

[0057] Step S2: Implement dual-channel data fusion in each dynamic monitoring area, obtain 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;

[0058] The operation logic of step S2 is:

[0059] The data of each node in each dynamic monitoring area includes voltage amplitude, phase angle, active power, reactive power and frequency;

[0060] The PMU measurement channel and SCADA channel time scale alignment is performed every 200ms, and the maximum time difference △t is recorded;

[0061] The reliability of the voltage amplitude data of each dynamic monitoring area is calculated based on this , where λ is the time attenuation coefficient, λ=1 / τ, τ is the device clock synchronization period, e is a natural constant, β1 is the weight coefficient of the data credibility corresponding to the set delay factor; k is the number of each dynamic monitoring area;

[0062] 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, G is the total number of nodes in the dynamic monitoring area, is the set voltage reference value, Γ is the maximum allowable deviation threshold;

[0063] β2 and β3 are weighted factors of the reliability evaluation values ​​of the PMU measurement channel and SCADA channel, respectively, and their sum is 1. , ; It represents the reliability evaluation value of the PMU measurement channel. Its specific calculation formula is: ; They are the PMU synchrophasor matching number and the PMU total matching number respectively; They represent the PMU data packet loss rate and the preset maximum PMU data packet loss rate during the set sliding window period respectively;

[0064] 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;

[0065] The phase angle data reliability, active power data reliability, reactive power data reliability and frequency data reliability of each dynamic monitoring area are calculated in the same way as the voltage amplitude data reliability of each dynamic monitoring area.

[0066] 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 are summed, and the summed result is divided by the number 5 to obtain the data credibility of each dynamic monitoring area.

[0067] When the data credibility of a certain dynamic monitoring area is less than 0.9, the system will start a hierarchical closed-loop processing process: first, the abnormal location mechanism is triggered, and the hybrid neural network model is used to extract the spatiotemporal features of the high-dimensional state matrix for 10 consecutive cycles, and the abnormal probability is output; if the abnormal probability is greater than 0.75, the collaborative verification request is broadcast to the adjacent areas through the federated learning framework, and the three-level coordinated optimization is activated simultaneously - the first level adjusts the local measurement weight matrix and recalculates the state estimation, the second level introduces the dynamic data of the PMU in the adjacent area to build a joint observation model, and the third level calls the full-network state reconstruction algorithm based on ADMM for global consistency correction; at the same time, the blockchain smart contract is started to implement multi-node cross-validation of the correction results, and the verification items include the residual of the power flow equation (threshold ±2% of the original value), time series data continuity (DTW distance <0.1), and LSTM prediction bias (MAE <3%). If the verification pass rate is less than 85%, it switches to the historical similarity scenario mode, uses dynamic time warping (DTW) to match the optimal coordination strategy for similar anomaly cases in the past 30 days, and updates the coordination strategy knowledge base in real time. Finally, it generates a self-healing instruction set including the weight adjustment coefficient (Δω∈[-0.2,0.5]), sampling frequency (dynamic adjustment from 1 to 5Hz), and communication channel priority (QoS levels 1-3). After processing is completed, the credibility is reassessed, forming a closed-loop management of "anomaly detection-coordinated correction-trusted verification-strategy evolution" to ensure that the regional state estimation error returns to the baseline level within 300ms.

[0068] Step S3: Based on the data credibility of each dynamic monitoring area, the overall operation status of the wide area power grid is judged, and the wide area power grid is adjusted as a whole based on the judgment result.

[0069] The operation logic of step S3 is:

[0070] 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 the 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 of each dynamic monitoring area and each node are calculated. The result of the sum and average calculation of each dynamic monitoring area and each node is subtracted from 1 to finally obtain the voltage stability assessment index of the wide area power grid. ;

[0071] 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. The absolute value operation is performed on the phase angle difference, and the phase angle difference with the largest phase angle difference is selected 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 to finally obtain the phase angle stability assessment index of the wide area power grid. ;

[0072] The final comprehensive calculation results in the comprehensive state assessment index of the wide area power grid. , are the total power generation and total load of the wide area power grid, respectively.

[0073] Comparing the comprehensive status assessment index of the wide-area power grid with the set threshold;

[0074] If the former is greater than or equal to the latter, it means that the wide area power grid is in normal operation and no operation is performed on it;

[0075] If the former is less than the latter, it means that the wide area power grid is in an abnormal operating state, and emergency load shedding and frequency emergency control operations are performed on the wide area power grid:

[0076] , It is the emergency load shedding data value of the wide area power grid;

[0077] The core idea of ​​the above calculation formula is to relieve the pressure on the power grid by reducing the load, especially when the power generation is insufficient to meet the load demand. represents the total load of the current power grid, and 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 overloading the grid:

[0078] The implementation logic is as follows:

[0079] 1. Monitoring the grid status: Real-time monitoring of the load and power generation of the grid, obtained through the SCADA system or other monitoring tools and data;

[0080] 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;

[0081] 3. Evaluate the load that needs to be reduced: Use Determine if load shedding is necessary. If the difference is positive, load shedding is necessary; if it is zero or negative, no action is required.

[0082] 4. Implement load reduction: Based on the calculated results, reduce the excess load by 20%. This can be done through automated control systems, selectively shutting down non-critical loads, or through demand response mechanisms to negotiate load adjustments with customers.

[0083] , It is the frequency emergency control data value of the wide area power grid; is the average frequency of the entire network.

[0084] The above formula is used to adjust the grid frequency to ensure it remains at the rated value (usually 50 Hz). Frequency stability is critical to the normal operation of the grid, as frequency deviations can cause equipment damage or system instability.

[0085] The implementation logic is as follows:

[0086] 1. Frequency monitoring: real-time monitoring of the average frequency of the power grid , usually monitored by frequency meters or smart sensors;

[0087] 2. Calculate the frequency deviation: Calculate 50- , this value indicates the deviation between the current frequency and the rated frequency;

[0088] 3. Evaluate the need for adjustment: The magnitude of the adjustment will be determined based on the size of the deviation. The 0.5 factor in the formula is used to control the magnitude of the adjustment, ensuring a smooth and non-overly aggressive process.

[0089] 4. Implement frequency adjustment: Frequency adjustment can be performed by adjusting the speed of the generator or using energy storage devices. Generators can quickly respond to frequency changes by changing fuel input or speed, while energy storage devices can provide or absorb power to stabilize the frequency.

[0090] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0091] It should be understood that determining B based on A does not mean determining B based solely on A. B can also be determined based on A and / or other information.

[0092] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0093] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A wide-area power system state estimation and coordination method, characterized in that: The following steps are involved: 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, each area including a core node and n edge nodes; Step S2: Implement dual-channel data fusion in each dynamic monitoring area, obtain 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 scale alignment is performed every 200ms, and the maximum time difference △t is recorded; The reliability of the voltage amplitude data of each dynamic monitoring area is calculated based on this , where λ is the time attenuation coefficient, λ=1 / τ, τ is the device clock synchronization period, e is a natural constant, β1 is the weight coefficient of the data credibility corresponding to the set delay factor; k is the number of each dynamic monitoring area; is the average relative deviation of voltage measurement in each dynamic monitoring area, β2 and β3 represent the weighting factors of the reliability of the PMU measurement channel and SCADA channel respectively, and the sum of the two is 1; Indicates the reliability of the PMU measurement channel, It is expressed as the reliability of the SCADA channel, Γ is the maximum allowable deviation threshold; The phase angle data reliability, active power data reliability, reactive power data reliability and frequency data reliability of each dynamic monitoring area are calculated in the same way as the voltage amplitude data reliability of each dynamic monitoring area. 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 are summed, and the summed result is divided by the number 5 to obtain the data credibility of each dynamic monitoring area; Step S3: Based on the data credibility of each dynamic monitoring area, the overall operation status of the wide area power grid is judged, and the wide area power grid is adjusted as a whole based on the judgment result.

2. A wide area power system state estimation and coordination method according to claim 1, characterized in that: 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 at the current moment and the previous moment in the wide area power grid, 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 power of node i / j at the current moment, are the active power of node i / j at the previous moment, are the phase angles of nodes i / j at the current moment, are the phase angles of node i / j at the previous moment; Collect the communication delay from node i to node j and impedance similarity , thereby calculating the dynamic weight matrix from node i to node j , e is a natural constant.

3. A wide area power system state estimation and 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 the adaptive threshold Filter strong connections and only retain significant connections with weight values ​​in the top 30%; For the isolated nodes caused by threshold filtering, a virtual edge compensation mechanism is used to give them Weak connection value to ensure full network connectivity; 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 normalized 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. The initial centroid distance is forced to be no less than 50% of the maximum distance in the feature space to ensure the rationality of the partitioning. After completing the preliminary division, the node connectivity and eigenvector modulus are comprehensively evaluated in each partition. 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 the state estimation.

4. The wide-area power system state estimation and coordination method according to claim 1, 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, G is the total number of nodes in the dynamic monitoring area, is the set voltage reference value; It represents the reliability of the PMU measurement channel. Its specific calculation formula is: ; They are the PMU synchrophasor matching number and the PMU total matching number respectively; They represent the PMU data packet loss rate and the preset maximum PMU data packet loss rate during the set sliding window period respectively; It is expressed as the reliability 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.

5. A wide area power system state estimation and 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, 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 the 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 of each dynamic monitoring area and each node are calculated. The result of the sum and average calculation of each dynamic monitoring area and each node is subtracted from 1 to finally obtain the voltage stability assessment index of the wide area power grid. ; 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. The absolute value operation is performed on the phase angle difference, and the phase angle difference with the largest phase angle difference is selected 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 to finally obtain the phase angle stability assessment index of the wide area power grid. ; The final comprehensive calculation results in the comprehensive state assessment index of the wide area power grid. , are the total power generation and total load of the wide area power grid, respectively.

6. A wide area power system state estimation and coordination method according to claim 5, characterized in that: Comparing 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 wide area power grid is in normal operation and no operation is performed on it; If the former is less than the latter, it means that the wide area power grid is in an abnormal operating state, 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.

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