Rapid evaluation method and system for ultra-short-term transient stability risk of power system

Abstract

The invention discloses a power system ultra-short-term transient stability risk rapid assessment method and system, and the method comprises the steps: determining a clustered anticipated fault subset according to the latest assessment result of the transient stability margin and the source load influence degree under an anticipated fault; determining a key anticipated fault of each subset according to the transient stability margin; according to the random source charge ultra-short-term confidence interval and the transient stability influence degree, random source charge ultra-short-term active power corresponding to each key anticipated fault is determined, and a system ultra-short-term risk operation state corresponding to each key anticipated fault is generated in combination with an ultra-short-term plan operation state and an automatic power generation control / automatic voltage control strategy; and determining the ultra-short-term transient stability risk of the power system through transient stability evaluation of the key anticipated fault in the state. Meanwhile, the invention discloses a corresponding system. According to the method, the key anticipated fault and the corresponding high-risk operation state in the ultra-short-term time period are identified, so that rapid evaluation of the ultra-short-term transient stability risk in consideration of source load randomness is realized.

Description

Technical Field

[0001] This invention belongs to the field of power system stability analysis technology, and relates to a method and system for rapid assessment of ultra-short-term transient stability risks in power systems. Background Technology

[0002] With increasing uncertainty on both the power source and load sides, the possibility of significant deviations between the power system operating state determined by the dispatch plan and the actual operating state is increasing. Current risk control models for stability verification of dispatch plans are insufficient to avoid potential risks in power system operation. Therefore, it is necessary to conduct stability assessments under anticipated faults for power system operating states that may occur within ultra-short-term timeframes. Since the possible power system operating states within ultra-short-term timeframes are inexhaustible, generating power system operating states through sampling and combining uncertain power source and load variables would lead to combinatorial explosion for large power systems with tens of thousands of uncertain power source and load variables. Furthermore, even performing stability assessments for all anticipated faults under a single operating state would be computationally intensive for large-scale anticipated fault sets. Therefore, breakthroughs are urgently needed in both reducing the number of faults and operating states to achieve rapid assessment of ultra-short-term transient stability risks. Summary of the Invention

[0003] Purpose of the invention: The purpose of this invention is to address the above-mentioned problems by providing a method and system for rapid assessment of ultra-short-term transient stability risks in power systems. This method and system can accurately identify key anticipated faults affecting transient stability during ultra-short-term periods and their corresponding high-risk operating states of the power grid, thereby enabling rapid assessment of ultra-short-term transient stability risks in power systems.

[0004] Technical solution: The present invention provides a method for rapid assessment of ultra-short-term transient stability risks in power systems, comprising the following steps:

[0005] Step 1: Based on the latest assessment results of transient stability margin and source load impact under anticipated faults, cluster the anticipated faults in the anticipated fault set to determine the transient stability anticipated fault subset after clustering;

[0006] Step 2: Based on the transient stability margin under the anticipated faults, determine the key anticipated faults corresponding to each subset of anticipated faults, and obtain the set of key anticipated faults for transient stability;

[0007] Step 3: Based on the ultra-short-term confidence interval of the random source load and its impact on transient stability under critical anticipated faults, determine the ultra-short-term active power of the random source load corresponding to each critical anticipated fault in the transient stability critical anticipated fault set.

[0008] Step 4: Based on the ultra-short-term planned operation status and the stochastic source load ultra-short-term active power corresponding to the key anticipated faults, as well as the automatic generation control and automatic voltage control strategies, generate the ultra-short-term risk operation status of the power system corresponding to each key anticipated fault in the transient stability key anticipated fault set.

[0009] Step 5: For each critical anticipated fault in the transient stability critical anticipated fault set, conduct transient stability assessment under the critical anticipated fault according to the ultra-short-term risk operation status of the power system corresponding to the critical anticipated fault.

[0010] Step 6: Based on the transient stability assessment results, determine the ultra-short-term transient stability risk of the power system.

[0011] Furthermore, the transient stability includes transient power angle stability, transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability;

[0012] The transient stability margin includes transient power angle stability margin, transient high voltage stability margin of each preset node for examining transient high voltage stability, transient low voltage stability margin of each preset node for examining transient low voltage stability, transient high frequency stability margin of each preset node for examining transient high frequency stability, and transient low frequency stability margin of each preset node for examining transient low frequency stability.

[0013] For transient power angle stability, the source-load influence degree refers to the influence of the power supply and load at each node connected to the power grid on transient power angle stability. For transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability, the source-load influence degree refers to the influence of the power supply and load at each node connected to the power grid on the transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability of each preset node used to examine transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability of each preset node used to examine transient high frequency stability, respectively.

[0014] Furthermore, step 1 specifically includes:

[0015] The expected fault subset that is transiently stable after clustering is determined by solving the following formula:

[0016]

[0017] In the formula, F is the set of anticipated faults, and N is the set of potential faults. a F represents the number of expected fault subsets for transient power angle stability after clustering. a.n For the nth anticipated fault subset that is transiently stable after clustering, I n For F a.n The absolute value of the transient power angle stability influence under the anticipated fault and F a.nThe ratio of the maximum absolute values ​​of the transient power angle stability influence under the anticipated fault to r is greater than r. a The source load union, r a To set parameters, λ a.f.i To anticipate the impact of a fault f on the transient power angle stability, ε a To set parameters;

[0018] The expected fault subset for transient high-voltage stability after clustering is determined by solving the following formula:

[0019]

[0020] In the formula, F is the set of anticipated faults, and N is the set of potential faults. vu F represents the number of expected fault subsets for transient high-voltage stability after clustering. vu.n B represents the nth anticipated fault subset after clustering for transient high-voltage stability. vu.n For F vu.n The transient high voltage stability margin under the anticipated fault is less than η. vu.cr The union of nodes, η vu.cr α is a set parameter, α is greater than 0, η vu.b,f To anticipate the transient high voltage stability margin of node b under fault f, J n.b For F vu.n The impact of the anticipated fault on the transient high voltage stability of node b and F vu.n The ratio of the maximum values ​​of the transient high-voltage stability impact on node b under the anticipated fault is greater than r. vu The collection consisting of power sources and loads, r vu To set parameters, λ vu.b.f.j To anticipate the impact of a fault f on the transient high-voltage stability of node b, ε vu To set parameters;

[0021] The expected fault subset for transient low-voltage stability after clustering is determined by solving the following formula:

[0022]

[0023] In the formula, F is the set of anticipated faults, and N is the set of potential faults. vd F represents the number of anticipated fault subsets for transient low-voltage stability after clustering. vd.n B represents the nth anticipated fault subset after clustering for transient low-voltage stability. vd.n For F vd.n The transient low voltage stability margin under the anticipated fault is less than η. vd.cr The union of nodes, η vd.cr α is a set parameter, α is greater than 0, η vd.b,f To anticipate the transient low voltage stability margin of node b under fault f, K n.b For Fvd.n The impact of the anticipated fault on the transient low voltage stability of node b and F vd.n The ratio of the maximum values ​​of the transient low voltage stability impact on node b under the anticipated fault is greater than r. vd The collection consisting of power sources and loads, r vd To set parameters, λ vd.b.f.j To anticipate the impact of a fault f on the transient low voltage stability of node b, ε vd To set parameters;

[0024] The expected fault subset that is transiently stable after clustering is determined by solving the following formula:

[0025]

[0026] In the formula, F is the set of anticipated faults, and N is the set of potential faults. fu F represents the number of transient high-frequency stable anticipated fault subsets after clustering. fu.n B represents the nth anticipated fault subset that is transiently stable at high frequencies after clustering. fu.n For F fu.n The transient high-frequency stability margin under the anticipated fault is less than η. fu.cr The union of nodes, η fu.cr α is a set parameter, α is greater than 0, η fu.b,f To anticipate the transient high-frequency stability margin of node b under fault f, L n.b For F fu.n The impact of the anticipated fault on the transient high-frequency stability of node b and F fu.n The ratio of the maximum values ​​of the transient high-frequency stability impact on node b under the anticipated fault is greater than r. fu The collection consisting of power sources and loads, r fu To set parameters, λ fu.b.f.l To anticipate the transient high-frequency stability impact of the power supply or load l on node b under fault f, ε fu To set parameters;

[0027] The expected fault subset that is transiently stable at low frequencies after clustering is determined by solving the following formula:

[0028]

[0029] In the formula, F is the set of anticipated faults, and N is the set of potential faults. fd F represents the number of expected fault subsets for transient low-frequency stability after clustering. fd.n B represents the nth anticipated fault subset that is transiently stable at low frequencies after clustering. fd.n For F fd.n The transient low-frequency stability margin under the anticipated fault is less than η fd.cr The union of nodes, η fd.cr α is a set parameter, α is greater than 0, ηfd.b,f To anticipate the transient low-frequency stability margin of node b under fault f, M n.b For F fd.n The impact of the anticipated fault on the transient low-frequency stability of node b and F fd.n The ratio of the maximum values ​​of the transient low-frequency stability impact on node b under the anticipated fault is greater than rf. d The collection consisting of power sources and loads, r fd To set parameters, λ fd.b.f.m To anticipate the transient low-frequency stability impact of the power supply or load m on node b under fault f, ε fd To set parameters.

[0030] Furthermore, step 2 specifically includes:

[0031] For each expected fault subset after clustering of transient power angle stability, the expected fault corresponding to the minimum transient power angle stability margin is taken as the key expected fault corresponding to each expected fault subset, and the set of all key expected faults is taken as the key expected fault set corresponding to transient power angle stability.

[0032] For each expected fault subset of transient high voltage stability after clustering, the expected fault corresponding to the minimum transient high voltage stability margin of each node is taken as the key expected fault of each expected fault subset, and the set of all key expected faults is taken as the key expected fault set corresponding to transient high voltage stability.

[0033] For each expected fault subset of transient low voltage stability after clustering, the expected fault corresponding to the minimum transient low voltage stability margin of each node is taken as the key expected fault of each expected fault subset, and the set of all key expected faults is taken as the key expected fault set corresponding to transient low voltage stability.

[0034] For each expected fault subset of transient high-frequency stability after clustering, the expected fault corresponding to the minimum transient high-frequency stability margin of each node is taken as the key expected fault corresponding to each expected fault subset, and the set of all key expected faults is taken as the key expected fault set corresponding to transient high-frequency stability.

[0035] For each expected fault subset of transient low-frequency stability after clustering, the expected fault corresponding to the minimum transient low-frequency stability margin of each node is taken as the key expected fault of each expected fault subset, and the set of all key expected faults is taken as the key expected fault set corresponding to transient low-frequency stability.

[0036] Furthermore, step 3 specifically includes:

[0037] For each critical anticipated fault in the critical anticipated fault set corresponding to transient power angle stability, first determine whether the ratio of the absolute value of the transient power angle stability influence to the maximum value among the absolute values ​​of the transient power angle stability influence under each critical anticipated fault is greater than r. a GL is a set of random power sources and loads. a Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. a Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL a The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value.

[0038]

[0039] In the formula, P i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ. a.i This represents the influence of a random power source or load i on transient power angle stability under critical anticipated faults. An influence value greater than 0 indicates that an increase in active power injected into the grid is beneficial to transient power angle stability; the larger the value, the more beneficial it is to transient power angle stability with the same amount of active power injected into the grid. An influence value less than 0 indicates that an increase in active power injected into the grid is detrimental to transient power angle stability; the smaller the value, the more detrimental it is to transient power angle stability with the same amount of active power injected into the grid.

[0040] For each critical anticipated fault in the critical anticipated fault set corresponding to transient high voltage stability, first determine that the transient high voltage stability margin under each critical anticipated fault is less than η. vu.cr Node set B vu Under the critical anticipated failure, for B vu The ratio of the transient high-voltage stability influence of the intermediate node to the maximum value of the transient high-voltage stability influence is greater than r. vu GL is a set of random power sources and loads. vu Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. vu Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL vu The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value.

[0041]

[0042] In the formula, η vu.bThe transient high-voltage stability margin of node b under critical anticipated fault conditions, where α is a set parameter, α is greater than 0, and P i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ. vu.b.i This represents the impact of a random power source or load i on the transient high voltage stability of node b under a critical anticipated fault. An impact greater than 0 indicates that a reduction in active power injected into the grid is beneficial to transient high voltage stability. The larger the value, the more beneficial a reduction in the same amount of active power injected into the grid is to transient high voltage stability.

[0043] For each critical anticipated fault in the critical anticipated fault set corresponding to transient low voltage stability, first determine that the transient low voltage stability margin under each critical anticipated fault is less than η. vd.cr Node set B vd Under the critical anticipated failure, for B vd The ratio of the transient low-voltage stability influence of the intermediate node to the maximum value of the transient low-voltage stability influence is greater than r. vd GL is a set of random power sources and loads. vd Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. vd Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL vd The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value.

[0044]

[0045] In the formula, η vd.b The transient low voltage stability margin of node b under critical anticipated fault conditions, where α is a set parameter, α is greater than 0, P i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ. vd.b.i This represents the impact of a random power source or load i on the transient low voltage stability of node b under a critical anticipated fault. An impact greater than 0 indicates that an increase in active power injected into the grid is beneficial to transient low voltage stability. The larger the value, the more beneficial it is to transient low voltage stability for the same amount of increase in active power injected into the grid.

[0046] For each critical anticipated fault in the critical anticipated fault set corresponding to transient high-frequency stability, first determine the transient high-frequency stability margin under each critical anticipated fault to be less than η. fu.cr Node set B fu Under the critical anticipated failure, for B fu The ratio of the transient high-frequency stability influence of the intermediate node to the maximum value of the transient high-frequency stability influence is greater than r. fu GL is a set of random power sources and loads. fu Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. fu Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL fu The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value.

[0047]

[0048] In the formula, η fu.b P represents the transient high-frequency stability margin of node b under critical anticipated fault conditions, where α is a set parameter, α is greater than 0, and P i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ. fu.b.i This represents the impact of a random power source or load i on the transient high-frequency stability of node b under a critical anticipated fault. An impact greater than 0 indicates that a reduction in active power injected into the grid is beneficial to transient high-frequency stability. The larger the value, the more beneficial a reduction in the same amount of active power injected into the grid is to transient high-frequency stability.

[0049] For each critical anticipated fault in the critical anticipated fault set corresponding to transient low-frequency stability, first determine that the transient low-frequency stability margin under each critical anticipated fault is less than η. fd.cr Node set B fd Under the critical anticipated failure, for B fd The ratio of the transient low-frequency stability influence of the mid-node to the maximum value of the transient low-frequency stability influence is greater than r. fd GL is a set of random power sources and loads. fd Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. fd Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL fd The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value.

[0050]

[0051] In the formula, η fd.b P represents the transient low-frequency stability margin of node b under critical anticipated fault conditions, where α is a set parameter, and α is greater than 0. i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ. fd.b.i This represents the impact of a random power source or load i on the transient low-frequency stability of node b under a critical anticipated fault. An impact greater than 0 indicates that an increase in active power injected into the grid is beneficial to transient low-frequency stability. The larger the value, the more beneficial it is to transient low-frequency stability for the same amount of active power injected into the grid.

[0052] Furthermore, step 4 specifically involves:

[0053] The following measures are taken for each of the key anticipated faults in the key anticipated fault sets corresponding to transient power angle stability, transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability:

[0054] Step 4-1: Based on the active power plan / DC power plan / energy storage power plan / tie line power plan of ultra-short-term non-random source loads and the active power injected into the grid by random source loads corresponding to critical anticipated faults in the ultra-short-term, the automatic generation control (AGC) strategy in the energy management system is adopted to calculate the active power and DC power / energy storage power / tie line power injected into the grid by each power source and load in the power system.

[0055] Step 4-2: Based on the current reactive power injected into the power grid by the power source and load, the current status of reactive power equipment, and the calculated active power and DC power / energy storage power / tie line power of each power source and load injected into the power grid in the power system, the automatic voltage control (AVC) strategy in the energy management system is used to calculate the reactive power injected into the power grid by each power source and load, the status of reactive power equipment, and the voltage of each node.

[0056] Step 4-3: The calculated active and reactive power and reactive power equipment status of each power source and load injected into the power grid, the voltage of each node and the DC power / energy storage power / tie line power are used as the ultra-short-term risk operating status of the power system corresponding to the critical anticipated fault.

[0057] Furthermore, step 6 specifically involves:

[0058] The key anticipated fault sets obtained in step 5 for each of the transient power angle stability, transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability, along with the minimum values ​​of transient power angle stability margin, transient high voltage stability margin, transient low voltage stability margin, transient high frequency stability margin, and transient low frequency stability margin under each key anticipated fault, and their corresponding key anticipated faults, the ultra-short-term risk operating status of the power system, and the source-load impact degree, are used as the ultra-short-term transient stability risk assessment information of the power system.

[0059] This invention provides a rapid assessment system for ultra-short-term transient stability risks in power systems, comprising:

[0060] Anticipated Fault Clustering Module: Based on the latest evaluation results of transient stability margin and source load impact under anticipated faults, cluster the anticipated faults in the anticipated fault set to determine the transient stability anticipated fault subset after clustering;

[0061] Key anticipated fault set generation module: Based on the transient stability margin under anticipated faults, determine the key anticipated faults corresponding to each subset of anticipated faults, and obtain the key anticipated fault set for transient stability;

[0062] Stochastic source load ultra-short-term active power determination module: Based on the ultra-short-term confidence interval of the stochastic source load and its impact on transient stability under critical anticipated faults, determine the stochastic source load ultra-short-term active power corresponding to each critical anticipated fault in the transient stability critical anticipated fault set.

[0063] Ultra-short-term risk status generation module: Based on the ultra-short-term planned operation status and the stochastic source load ultra-short-term active power corresponding to the key anticipated faults, as well as the automatic generation control and automatic voltage control strategies, the module generates the ultra-short-term risk operation status of the power system corresponding to each key anticipated fault in the transient stability key anticipated fault set.

[0064] Transient stability assessment module: For each critical anticipated fault in the transient stability critical anticipated fault set, transient stability assessment is performed under the critical anticipated fault according to the ultra-short-term risk operation state of the power system corresponding to the critical anticipated fault.

[0065] Ultra-short-term risk determination module: Based on the transient stability assessment results, determine the ultra-short-term transient stability risk of the power system.

[0066] The present invention provides a computer-readable storage medium for storing one or more programs, characterized in that: the one or more programs include instructions, which, when executed by a computing device, cause the computing device to perform any of the methods described above in the method for rapid assessment of ultra-short-term transient stability risks in power systems.

[0067] The present invention provides a computing device comprising: one or more processors, one or more memories, and one or more programs, wherein the one or more programs are stored in the one or more memories and configured to be executed by the one or more processors, and the one or more programs include instructions for performing any of the methods in the above-described rapid assessment methods for ultra-short-term transient stability risks of power systems.

[0068] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages: 1. The present invention determines the key anticipated fault set for different types of transient stability, which is in line with the different characteristics of various stability mechanisms. Furthermore, it determines the high-risk operating state for each key anticipated fault, which is in line with the different influence of source load on the same type of stability under different key anticipated faults.

[0069] 2. Based on the latest assessment results of the margin and source load influence of various transient stability under anticipated faults, the anticipated faults are clustered. The anticipated fault with the smallest margin is selected from the clustered subset of anticipated faults as the key fault to be assessed, which greatly reduces the number of anticipated faults in transient stability assessment.

[0070] 3. For each key anticipated fault corresponding to different transient stability, a corresponding high-risk operating state is generated based on the latest assessment results of the source load influence and the source load confidence interval. This enables the determination of the minimum transient stability margin of the anticipated fault under all possible operating states within the ultra-short time period by only performing a transient stability assessment on the operating state. Attached Figure Description

[0071] Figure 1 This is a flowchart of the method for rapid assessment of ultra-short-term transient stability risk in power systems according to the present invention. Detailed Implementation

[0072] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0073] like Figure 1 As shown, the rapid assessment method for ultra-short-term transient stability risks in power systems includes the following steps:

[0074] Step 1: Based on the latest assessment results of transient stability margin and source load impact under anticipated faults, cluster the anticipated faults in the anticipated fault set to determine the transient stability anticipated fault subset after clustering.

[0075] The transient stability includes five categories: transient power angle stability, transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability. The transient stability margin includes transient power angle stability margin, transient high voltage stability margin for each preset node used to examine transient high voltage stability, transient low voltage stability margin for each preset node used to examine transient low voltage stability, transient high frequency stability margin for each preset node used to examine transient high frequency stability, and transient low frequency stability margin for each preset node used to examine transient low frequency stability. Regarding transient power angle stability, the source-load influence... The degree refers to the influence of the power supply and load at each node connected to the power grid on transient power angle stability. For transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability, the source-load influence degree refers to the influence of the power supply and load at each node connected to the power grid on the transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability of each preset node used to examine transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability of each preset node used to examine transient high frequency stability, respectively.

[0076] The latest assessment results of transient stability margin and source load impact under anticipated faults can be either the transient stability verification results of the most recent planned operating state in the scheduling plan, or the latest online transient stability assessment results.

[0077] The expected fault subset that is transiently stable after clustering is determined by solving the following formula:

[0078]

[0079] In the formula, F is the set of anticipated faults, and N is the set of potential faults. a F represents the number of expected fault subsets for transient power angle stability after clustering. a.n For the nth anticipated fault subset that is transiently stable after clustering, I n For F a.n The absolute value of the transient power angle stability influence under the anticipated fault and F a.n The ratio of the maximum absolute values ​​of the transient power angle stability influence under the anticipated fault to r is greater than r. a The source load union, r a To set the parameters, they are usually set to 0.3, λ. a.f.i To anticipate the impact of a fault f on the transient power angle stability, ε a To set the parameter, it is usually set to 0.1.

[0080] The expected fault subset for transient high-voltage stability after clustering is determined by solving the following formula:

[0081]

[0082] In the formula, F is the set of anticipated faults, and N is the set of potential faults. vu F represents the number of expected fault subsets for transient high-voltage stability after clustering. vu.n B represents the nth anticipated fault subset after clustering for transient high-voltage stability. vu.n For F vu.n The transient high voltage stability margin under the anticipated fault is less than η. vu.cr The union of nodes, η vu.cr α is a set parameter, α is greater than 0, and is usually set to 2, η vu.b,f To anticipate the transient high voltage stability margin of node b under fault f, J n.b For F vu.n The impact of the anticipated fault on the transient high voltage stability of node b and F vu.n The ratio of the maximum values ​​of the transient high-voltage stability impact on node b under the anticipated fault is greater than r. vu The collection consisting of power sources and loads, r vu To set the parameters, they are usually set to 0.3, λ. vu.b.f.j To anticipate the impact of a fault f on the transient high-voltage stability of node b, ε vu To set the parameter, it is usually set to 0.05.

[0083] The expected fault subset for transient low-voltage stability after clustering is determined by solving the following formula:

[0084]

[0085] In the formula, F is the set of anticipated faults, and N is the set of potential faults. vd F represents the number of anticipated fault subsets for transient low-voltage stability after clustering. vd.n B represents the nth anticipated fault subset after clustering for transient low-voltage stability. vd.n For F vd.n The transient low voltage stability margin under the anticipated fault is less than η. vd.cr The union of nodes, η vd.cr α is a set parameter, α is greater than 0, and is usually set to 2, η vd.b,f To anticipate the transient low voltage stability margin of node b under fault f, K n.b For F vd.n The impact of the anticipated fault on the transient low voltage stability of node b and F vd.n The ratio of the maximum values ​​of the transient low voltage stability impact on node b under the anticipated fault is greater than r. vd The collection consisting of power sources and loads, r vd To set the parameters, they are usually set to 0.3, λ. vd.b.f.j To anticipate the impact of a fault f on the transient low voltage stability of node b, ε vd To set the parameter, it is usually set to 0.05.

[0086] The expected fault subset that is transiently stable after clustering is determined by solving the following formula:

[0087]

[0088] In the formula, F is the set of anticipated faults, and N is the set of potential faults. fu F represents the number of transient high-frequency stable anticipated fault subsets after clustering. fu.n B represents the nth anticipated fault subset that is transiently stable at high frequencies after clustering. fu.n For F fu.n The transient high-frequency stability margin under the anticipated fault is less than η. fu.cr The union of nodes, η fu.cr α is a set parameter, α is greater than 0, and is usually set to 2, η fu . b,f To anticipate the transient high-frequency stability margin of node b under fault f, L n.b For F fu.n The impact of the anticipated fault on the transient high-frequency stability of node b and F fu.n The ratio of the maximum values ​​of the transient high-frequency stability impact on node b under the anticipated fault is greater than r. fu The collection consisting of power sources and loads, r fu To set the parameters, they are usually set to 0.3, λ. fu.b.f.l To anticipate the transient high-frequency stability impact of the power supply or load l on node b under fault f, ε fu To set the parameter, it is usually set to 0.05.

[0089] The expected fault subset that is transiently stable at low frequencies after clustering is determined by solving the following formula:

[0090]

[0091] In the formula, F is the set of anticipated faults, and N is the set of potential faults. fd F represents the number of expected fault subsets for transient low-frequency stability after clustering. fd.n B represents the nth anticipated fault subset that is transiently stable at low frequencies after clustering. fd.n For F fd.n The transient low-frequency stability margin under the anticipated fault is less than η fd.cr The union of nodes, η fd.cr α is a set parameter, α is greater than 0, and is usually set to 2, η fd .b ,f To anticipate the transient low-frequency stability margin of node b under fault f, M n.b For F fd.n The impact of the anticipated fault on the transient low-frequency stability of node b and F fd.n The ratio of the maximum values ​​of the transient low-frequency stability impact on node b under the anticipated fault is greater than r.fd The collection consisting of power sources and loads, r fd To set the parameters, they are usually set to 0.3, λ. fd.b.f.m To anticipate the transient low-frequency stability impact of the power supply or load m on node b under fault f, ε fd To set the parameter, it is usually set to 0.05.

[0092] Using the above method, clustered subsets of anticipated transient power angle stability faults, transient high voltage stability faults, transient low voltage stability faults, transient high frequency stability faults, and transient low frequency stability faults are obtained. The anticipated faults in each subset exhibit similar transient stability characteristics. For each subset, it is not necessary to perform transient stability assessments on all faults within the subset; only one representative key anticipated fault needs to be identified and included in the key anticipated fault set for transient stability assessment.

[0093] Step 2: Based on the transient stability margin under the anticipated faults, determine the key anticipated faults corresponding to each subset of anticipated faults, and obtain the set of key anticipated faults for transient stability.

[0094] Specifically, including,

[0095] For each expected fault subset after clustering of transient power angle stability, the expected fault corresponding to the minimum transient power angle stability margin is taken as the key expected fault corresponding to each expected fault subset, and the set of all key expected faults is taken as the key expected fault set corresponding to transient power angle stability.

[0096] For each anticipated fault subset of transient high voltage stability after clustering, the anticipated fault corresponding to the minimum transient high voltage stability margin of each node is taken as the key anticipated fault of each anticipated fault subset, and the set of all key anticipated faults is taken as the key anticipated fault set corresponding to transient high voltage stability.

[0097] For each anticipated fault subset of transient low voltage stability after clustering, the anticipated fault corresponding to the minimum transient low voltage stability margin of each node is taken as the key anticipated fault of each anticipated fault subset, and the set of all key anticipated faults is taken as the key anticipated fault set corresponding to transient low voltage stability.

[0098] For each expected fault subset of transient high-frequency stability after clustering, the expected fault corresponding to the minimum transient high-frequency stability margin of each node is taken as the key expected fault of each expected fault subset, and the set of all key expected faults is taken as the key expected fault set corresponding to transient high-frequency stability.

[0099] For each expected fault subset of transient low-frequency stability after clustering, the expected fault corresponding to the minimum transient low-frequency stability margin of each node is taken as the key expected fault of each expected fault subset, and the set of all key expected faults is taken as the key expected fault set corresponding to transient low-frequency stability.

[0100] By using the above method, the anticipated faults with the smallest transient stability margin in each subset are included in the set of critical anticipated faults. In the ultra-short term, it is possible to more accurately identify the critical anticipated faults that affect the transient power angle stability, transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability of the power system, thereby reducing the size of the set of anticipated faults for transient stability assessment.

[0101] Step 3: Based on the ultra-short-term confidence interval of the random source load and its impact on transient stability under critical anticipated faults, determine the ultra-short-term active power of the random source load corresponding to each critical anticipated fault in the transient stability critical anticipated fault set.

[0102] Specifically, including,

[0103] For each critical anticipated fault in the critical anticipated fault set corresponding to transient power angle stability, first determine whether the ratio of the absolute value of the transient power angle stability influence to the maximum value among the absolute values ​​of the transient power angle stability influence under each critical anticipated fault is greater than r. a GL is a set of random power sources and loads. a Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. a Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL a The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value.

[0104]

[0105] In the formula, P i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ. a.i This represents the influence of a random power source or load i on transient power angle stability under critical anticipated faults. An influence value greater than 0 indicates that an increase in active power injected into the grid is beneficial to transient power angle stability; the larger the value, the more beneficial it is to transient power angle stability with the same amount of active power injected into the grid. An influence value less than 0 indicates that an increase in active power injected into the grid is detrimental to transient power angle stability; the smaller the value, the more detrimental it is to transient power angle stability with the same amount of active power injected into the grid.

[0106] Using the above method, the most unfavorable stochastic source load active power value for the transient power angle stability of the power grid under critical anticipated faults is obtained, laying the foundation for generating risky operating states for ultra-short-term transient power angle stability.

[0107] For each critical anticipated fault in the critical anticipated fault set corresponding to transient high voltage stability, first determine that the transient high voltage stability margin under each critical anticipated fault is less than η. vu.cr Node set B vu Under the critical anticipated failure, for B vu The ratio of the transient high-voltage stability influence of the intermediate node to the maximum value of the transient high-voltage stability influence is greater than r. vu GL is a set of random power sources and loads. vu Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. vu Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL vu The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value.

[0108]

[0109] In the formula, η vu.b The transient high-voltage stability margin of node b under critical anticipated fault conditions, where α is a set parameter, α is greater than 0, and P i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ. vu.b.i This represents the impact of a random power source or load i on the transient high voltage stability of node b under a critical anticipated fault. An impact greater than 0 indicates that a reduction in active power injected into the grid is beneficial to transient high voltage stability. The larger the value, the more beneficial a reduction in the same amount of active power injected into the grid is to transient high voltage stability.

[0110] Using the above method, the most unfavorable stochastic source-load active power value for transient high voltage stability of the power grid under critical anticipated faults is obtained, laying the foundation for generating risky operating states for ultra-short-term transient high voltage stability.

[0111] For each critical anticipated fault in the critical anticipated fault set corresponding to transient low voltage stability, first determine that the transient low voltage stability margin under each critical anticipated fault is less than η. vd.cr Node set B vd Under the critical anticipated failure, for B vdThe ratio of the transient low-voltage stability influence of the intermediate node to the maximum value of the transient low-voltage stability influence is greater than r. vd GL is a set of random power sources and loads. vd Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. vd Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL vd The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value.

[0112]

[0113] In the formula, η vd.b The transient low voltage stability margin of node b under critical anticipated fault conditions, where α is a set parameter, α is greater than 0, P i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ. vd.b.i This represents the impact of a random power source or load i on the transient low voltage stability of node b under a critical anticipated fault. An impact greater than 0 indicates that an increase in active power injected into the grid is beneficial to transient low voltage stability. The larger the value, the more beneficial it is to transient low voltage stability for the same amount of increase in active power injected into the grid.

[0114] Using the above method, the most unfavorable stochastic source-load active power value for the transient low voltage stability of the power grid under critical anticipated faults is obtained, laying the foundation for generating risky operating states for ultra-short-term transient low voltage stability.

[0115] For each critical anticipated fault in the critical anticipated fault set corresponding to transient high-frequency stability, first determine the transient high-frequency stability margin under each critical anticipated fault to be less than η. fu.cr Node set B fu Under the critical anticipated failure, for B fu The ratio of the transient high-frequency stability influence of the intermediate node to the maximum value of the transient high-frequency stability influence is greater than r. fu GL is a set of random power sources and loads. fu Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. fu Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL fu The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value.

[0116]

[0117] In the formula, η fu.b P represents the transient high-frequency stability margin of node b under critical anticipated fault conditions, where α is a set parameter, α is greater than 0, and P i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ. fu.b.i This represents the impact of a random power source or load i on the transient high-frequency stability of node b under a critical anticipated fault. An impact greater than 0 indicates that a reduction in active power injected into the grid is beneficial to transient high-frequency stability. The larger the value, the more beneficial a reduction in the same amount of active power injected into the grid is to transient high-frequency stability.

[0118] Using the above method, the most unfavorable stochastic source load active power value for the transient high-frequency stability of the power grid under critical anticipated faults is obtained, laying the foundation for generating risky operating states for ultra-short-term transient high-frequency stability.

[0119] For each critical anticipated fault in the critical anticipated fault set corresponding to transient low-frequency stability, first determine that the transient low-frequency stability margin under each critical anticipated fault is less than η. fd.cr Node set B fd Under the critical anticipated failure, for B fd The ratio of the transient low-frequency stability influence of the mid-node to the maximum value of the transient low-frequency stability influence is greater than r. fd GL is a set of random power sources and loads. fd Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. fd Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL fd The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value.

[0120]

[0121] In the formula, η fd.b P represents the transient low-frequency stability margin of node b under critical anticipated fault conditions, where α is a set parameter, and α is greater than 0. i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ.fd.b.i This represents the impact of a random power source or load i on the transient low-frequency stability of node b under a critical anticipated fault. An impact greater than 0 indicates that an increase in active power injected into the grid is beneficial to transient low-frequency stability. The larger the value, the more beneficial it is to transient low-frequency stability for the same amount of active power injected into the grid.

[0122] Using the above method, the most unfavorable stochastic source-load active power value for the transient low-frequency stability of the power grid under critical anticipated faults is obtained, laying the foundation for generating ultra-short-term transient low-frequency stability risk operating states.

[0123] Step 4: Based on the ultra-short-term planned operation status and the stochastic source load ultra-short-term active power corresponding to the key anticipated faults, as well as the automatic generation control and automatic voltage control strategies, generate the ultra-short-term risk operation status of the power system corresponding to each key anticipated fault in the transient stability key anticipated fault set.

[0124] Specifically,

[0125] The following measures are taken for each of the key anticipated faults in the key anticipated fault sets corresponding to transient power angle stability, transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability:

[0126] 4-1) First, based on the active power plan / DC power plan / energy storage power plan / tie line power plan of ultra-short-term non-random source loads and the active power of random source loads injected into the grid in the ultra-short-term according to the critical anticipated faults, the automatic generation control (AGC) strategy in the energy management system is adopted to calculate the active power and DC power / energy storage power / tie line power injected into the grid by each power source and load in the power system.

[0127] 4-2) Then, based on the current reactive power and reactive power equipment status injected into the power grid by the power source and load, and the calculated active power and DC power / energy storage power / tie line power injected into the power grid by each power source and load in the power system, the automatic voltage control (AVC) strategy in the energy management system is used to calculate the reactive power and reactive power equipment status and the voltage of each node injected into the power grid by each power source and load in the power system.

[0128] 4-3) Finally, the calculated active and reactive power and reactive power equipment status of each power source and load injected into the grid, the voltage of each node and the DC power / energy storage power / tie line power are used as the ultra-short-term risk operating status of the power system corresponding to the critical anticipated fault.

[0129] Using the above method, the most unfavorable short-term risk operating states of the power system corresponding to each of the key anticipated fault sets for transient power angle stability, transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability are obtained.

[0130] Step 5: For each critical anticipated fault in the transient stability critical anticipated fault set, conduct transient stability assessment under the critical anticipated fault according to the ultra-short-term risk operation status of the power system corresponding to the critical anticipated fault.

[0131] Among them, conducting transient stability assessment under critical anticipated faults refers to assessing the transient power angle stability margin, transient high voltage stability margin, transient low voltage stability margin, transient high frequency stability margin, transient low frequency stability margin, and the influence of source load on different transient stability conditions for each critical anticipated fault.

[0132] Step 6: Based on the transient stability assessment results, determine the ultra-short-term transient stability risk of the power system.

[0133] Specifically,

[0134] The key anticipated faults corresponding to transient power angle stability, transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability are collected. The minimum values ​​of transient power angle stability margin, transient high voltage stability margin, transient low voltage stability margin, transient high frequency stability margin, and transient low frequency stability margin, as well as the corresponding key anticipated faults, the ultra-short-term risk operation status of the power system, and the source-load impact are used as the ultra-short-term transient stability risk assessment information of the power system.

[0135] Using the above method, based on the latest assessment results of transient stability margin and source-load impact under anticipated faults, anticipated faults are clustered to obtain a set of key anticipated faults. This further generates the corresponding ultra-short-term risk operating states of the power system. On the one hand, this significantly reduces the number of anticipated faults and ultra-short-term operating states requiring transient stability assessment, improving the calculation speed of the assessment. On the other hand, it can accurately identify severe anticipated faults and high-risk operating states within ultra-short-term periods, quickly assess the transient stability risk of the power system, and provide the minimum transient stability margin that dispatchers are most concerned about, along with the corresponding key anticipated faults, ultra-short-term risk operating states of the power system, and source-load impact, thus providing a basis for ultra-short-term transient stability risk prevention and control decisions.

[0136] A rapid assessment system for ultra-short-term transient stability risks in power systems, including:

[0137] Anticipated Fault Clustering Module: Based on the latest evaluation results of transient stability margin and source load impact under anticipated faults, cluster the anticipated faults in the anticipated fault set to determine the transient stability anticipated fault subset after clustering;

[0138] Key anticipated fault set generation module: Based on the transient stability margin under anticipated faults, determine the key anticipated faults corresponding to each subset of anticipated faults, and obtain the key anticipated fault set for transient stability;

[0139] Stochastic source load ultra-short-term active power determination module: Based on the ultra-short-term confidence interval of the stochastic source load and its impact on transient stability under critical anticipated faults, determine the stochastic source load ultra-short-term active power corresponding to each critical anticipated fault in the transient stability critical anticipated fault set.

[0140] Ultra-short-term risk status generation module: Based on the ultra-short-term planned operation status and the stochastic source load ultra-short-term active power corresponding to the key anticipated faults, as well as the automatic generation control and automatic voltage control strategies, the module generates the ultra-short-term risk operation status of the power system corresponding to each key anticipated fault in the transient stability key anticipated fault set.

[0141] Transient stability assessment module: For each critical anticipated fault in the transient stability critical anticipated fault set, transient stability assessment is performed under the critical anticipated fault according to the ultra-short-term risk operation state of the power system corresponding to the critical anticipated fault.

[0142] Ultra-short-term risk determination module: Based on the transient stability assessment results, determine the ultra-short-term transient stability risk of the power system.

[0143] A computer-readable storage medium storing one or more programs, the one or more programs including instructions that, when executed by a computing device, cause the computing device to perform a method for rapid assessment of ultra-short-term transient stability risks in power systems.

[0144] A computing device includes one or more processors, one or more memories, and one or more programs, wherein the one or more programs are stored in the one or more memories and configured to be executed by the one or more processors, and the one or more programs include instructions for performing a method for rapid assessment of ultra-short-term transient stability risks in power systems.

[0145] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0146] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0147] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0148] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0149] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A rapid assessment method for ultra-short-term transient stability risks in power systems, characterized in that, Includes the following steps: Step 1: Based on the latest assessment results of transient stability margin and source load impact under anticipated faults, cluster the anticipated faults in the anticipated fault set to determine the transient stability anticipated fault subset after clustering; Step 2: Based on the transient stability margin under the anticipated faults, determine the key anticipated faults corresponding to each subset of anticipated faults, and obtain the set of key anticipated faults for transient stability; Step 3: Based on the ultra-short-term confidence interval of the random source load and its impact on transient stability under critical anticipated faults, determine the ultra-short-term active power of the random source load corresponding to each critical anticipated fault in the transient stability critical anticipated fault set. Step 4: Based on the ultra-short-term planned operation status and the stochastic source load ultra-short-term active power corresponding to the key anticipated faults, as well as the automatic generation control and automatic voltage control strategies, generate the ultra-short-term risk operation status of the power system corresponding to each key anticipated fault in the transient stability key anticipated fault set. Step 5: For each critical anticipated fault in the transient stability critical anticipated fault set, conduct transient stability assessment under the critical anticipated fault according to the ultra-short-term risk operation status of the power system corresponding to the critical anticipated fault. Step 6: Based on the transient stability assessment results, determine the ultra-short-term transient stability risk of the power system.

2. The method for rapid assessment of ultra-short-term transient stability risk in power systems according to claim 1, characterized in that: The transient stability includes transient power angle stability, transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability; The transient stability margin includes transient power angle stability margin, transient high voltage stability margin of each preset node for examining transient high voltage stability, transient low voltage stability margin of each preset node for examining transient low voltage stability, transient high frequency stability margin of each preset node for examining transient high frequency stability, and transient low frequency stability margin of each preset node for examining transient low frequency stability. For transient power angle stability, the source-load influence degree refers to the influence of the power supply and load at each node connected to the power grid on transient power angle stability. For transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability, the source-load influence degree refers to the influence of the power supply and load at each node connected to the power grid on the transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability of each preset node used to examine transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability of each preset node used to examine transient high frequency stability, respectively.

3. The method for rapid assessment of ultra-short-term transient stability risk in power systems according to claim 2, characterized in that: Step 1 specifically includes: The expected fault subset that is transiently stable after clustering is determined by solving the following formula: In the formula, F is the set of anticipated faults, and N is the set of potential faults. a F represents the number of expected fault subsets for transient power angle stability after clustering. a.n For the nth anticipated fault subset that is transiently stable after clustering, I n For F a.n The absolute value of the transient power angle stability influence under the anticipated fault and F a.n The ratio of the maximum absolute values ​​of the transient power angle stability influence under the anticipated fault to r is greater than r. a The source load union, r a To set parameters, λ a.f.i To anticipate the impact of a fault f on the transient power angle stability, ε a To set parameters; The expected fault subset for transient high-voltage stability after clustering is determined by solving the following formula: In the formula, F is the set of anticipated faults, and N is the set of potential faults. vu F represents the number of expected fault subsets for transient high-voltage stability after clustering. vu.n B represents the nth anticipated fault subset after clustering for transient high-voltage stability. vu.n For F vu.n The transient high voltage stability margin under the anticipated fault is less than η. vu.cr The union of nodes, η vu.cr α is a set parameter; α is greater than 0, η vu.b,f To anticipate the transient high voltage stability margin of node b under fault f, J n.b For F vu.n The impact of the anticipated fault on the transient high voltage stability of node b and F vu.n The ratio of the maximum values ​​of the transient high-voltage stability impact on node b under the anticipated fault is greater than r. vu The collection consisting of power sources and loads, r vu To set parameters, λ vu.b.f.j To anticipate the impact of a fault f on the transient high-voltage stability of node b, ε vu To set parameters; The expected fault subset for transient low-voltage stability after clustering is determined by solving the following formula: In the formula, F is the set of anticipated faults, and N is the set of potential faults. vd F represents the number of anticipated fault subsets for transient low-voltage stability after clustering. vd.n B represents the nth anticipated fault subset after clustering for transient low-voltage stability. vd.n For F vd.n The transient low voltage stability margin under the anticipated fault is less than η. vd.cr The union of nodes, η vd.cr α is a set parameter; α is greater than 0, η vd.b,f To anticipate the transient low voltage stability margin of node b under fault f, K n.b For F vd.n The impact of the anticipated fault on the transient low voltage stability of node b and F vd.n The ratio of the maximum values ​​of the transient low voltage stability impact on node b under the anticipated fault is greater than r. vd The collection consisting of power sources and loads, r vd To set parameters, λ vd.b.f.j To anticipate the impact of a fault f on the transient low voltage stability of node b, ε vd To set parameters; The expected fault subset that is transiently stable after clustering is determined by solving the following formula: In the formula, F is the set of anticipated faults, and N is the set of potential faults. fu F represents the number of transient high-frequency stable anticipated fault subsets after clustering. fu.n B represents the nth anticipated fault subset that is transiently stable at high frequencies after clustering. fu.n For F fu.n The transient high-frequency stability margin under the anticipated fault is less than η. fu.cr The union of nodes, η fu.cr α is a set parameter; α is greater than 0, η fu.b,f To anticipate the transient high-frequency stability margin of node b under fault f, L n.b For F fu.n The impact of the anticipated fault on the transient high-frequency stability of node b and F fu.n The ratio of the maximum values ​​of the transient high-frequency stability impact on node b under the anticipated fault is greater than r. fu The collection consisting of power sources and loads, r fu To set parameters, λ fu.b.f.l To anticipate the transient high-frequency stability impact of the power supply or load l on node b under fault f, ε fu To set parameters; The expected fault subset that is transiently stable at low frequencies after clustering is determined by solving the following formula: In the formula, F is the set of anticipated faults, and N is the set of potential faults. fd F represents the number of expected fault subsets for transient low-frequency stability after clustering. fd.n B represents the nth anticipated fault subset that is transiently stable at low frequencies after clustering. fd.n For F fd.n The transient low-frequency stability margin under the anticipated fault is less than η fd.cr The union of nodes, η fd.cr α is a set parameter; α is greater than 0, η fd.b,f To anticipate the transient low-frequency stability margin of node b under fault f, M n.b For F fd.n The impact of the anticipated fault on the transient low-frequency stability of node b and F fd.n The ratio of the maximum values ​​of the transient low-frequency stability impact on node b under the anticipated fault is greater than r. fd The collection consisting of power sources and loads, r fd To set parameters, λ fd.b.f.m To anticipate the transient low-frequency stability impact of the power supply or load m on node b under fault f, ε fd To set parameters.

4. The method for rapid assessment of ultra-short-term transient stability risk in power systems according to claim 2, characterized in that: Step 2 specifically includes: For each expected fault subset after clustering of transient power angle stability, the expected fault corresponding to the minimum transient power angle stability margin is taken as the key expected fault corresponding to each expected fault subset, and the set of all key expected faults is taken as the key expected fault set corresponding to transient power angle stability. For each expected fault subset of transient high voltage stability after clustering, the expected fault corresponding to the minimum transient high voltage stability margin of each node is taken as the key expected fault of each expected fault subset, and the set of all key expected faults is taken as the key expected fault set corresponding to transient high voltage stability. For each expected fault subset of transient low voltage stability after clustering, the expected fault corresponding to the minimum transient low voltage stability margin of each node is taken as the key expected fault of each expected fault subset, and the set of all key expected faults is taken as the key expected fault set corresponding to transient low voltage stability. For each expected fault subset of transient high-frequency stability after clustering, the expected fault corresponding to the minimum transient high-frequency stability margin of each node is taken as the key expected fault corresponding to each expected fault subset, and the set of all key expected faults is taken as the key expected fault set corresponding to transient high-frequency stability. For each expected fault subset of transient low-frequency stability after clustering, the expected fault corresponding to the minimum transient low-frequency stability margin of each node is taken as the key expected fault of each expected fault subset, and the set of all key expected faults is taken as the key expected fault set corresponding to transient low-frequency stability.

5. The method for rapid assessment of ultra-short-term transient stability risk in power systems according to claim 2, characterized in that: Step 3 specifically includes: For each critical anticipated fault in the critical anticipated fault set corresponding to transient power angle stability, first determine whether the ratio of the absolute value of the transient power angle stability influence to the maximum value among the absolute values ​​of the transient power angle stability influence under each critical anticipated fault is greater than r. a GL is a set of random power sources and loads. a Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. a Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL a The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value. In the formula, P i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ. a.i This represents the influence of a random power source or load i on transient power angle stability under critical anticipated faults. An influence value greater than 0 indicates that an increase in active power injected into the grid is beneficial to transient power angle stability; the larger the value, the more beneficial it is to transient power angle stability with the same amount of active power injected into the grid. An influence value less than 0 indicates that an increase in active power injected into the grid is detrimental to transient power angle stability; the smaller the value, the more detrimental it is to transient power angle stability with the same amount of active power injected into the grid. For each critical anticipated fault in the critical anticipated fault set corresponding to transient high voltage stability, first determine that the transient high voltage stability margin under each critical anticipated fault is less than η. vu.cr Node set B vu Under the critical anticipated failure, for B vu The ratio of the transient high-voltage stability influence of the intermediate node to the maximum value of the transient high-voltage stability influence is greater than r. vu GL is a set of random power sources and loads. vu Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. vu Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL vu The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value. In the formula, η vu.b The transient high-voltage stability margin of node b under critical anticipated fault conditions, where α is a set parameter, α is greater than 0, and P i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ. vu.b.i This represents the impact of a random power source or load i on the transient high voltage stability of node b under a critical anticipated fault. An impact greater than 0 indicates that a reduction in active power injected into the grid is beneficial to transient high voltage stability. The larger the value, the more beneficial a reduction in the same amount of active power injected into the grid is to transient high voltage stability. For each critical anticipated fault in the critical anticipated fault set corresponding to transient low voltage stability, first determine that the transient low voltage stability margin under each critical anticipated fault is less than η. vd.cr Node set B vd Under the critical anticipated failure, for B vd The ratio of the transient low-voltage stability influence of the intermediate node to the maximum value of the transient low-voltage stability influence is greater than r. v The set GL consisting of random power sources and loads of d vd Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. vd Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL vd The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value. In the formula, η vd.b The transient low voltage stability margin of node b under critical anticipated fault conditions, where α is a set parameter, α is greater than 0, P i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ. vd.b.i This represents the impact of a random power source or load i on the transient low voltage stability of node b under a critical anticipated fault. An impact greater than 0 indicates that an increase in active power injected into the grid is beneficial to transient low voltage stability. The larger the value, the more beneficial it is to transient low voltage stability for the same amount of increase in active power injected into the grid. For each critical anticipated fault in the critical anticipated fault set corresponding to transient high-frequency stability, first determine the transient high-frequency stability margin under each critical anticipated fault to be less than η. fu.cr Node set B fu Under the critical anticipated failure, for B fu The ratio of the transient high-frequency stability influence of the intermediate node to the maximum value of the transient high-frequency stability influence is greater than r. fu GL is a set of random power sources and loads. fu Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. fu Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL fu The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value. In the formula, η fu.b P represents the transient high-frequency stability margin of node b under critical anticipated fault conditions, where α is a set parameter, α is greater than 0, and P i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ. fu.b.i This represents the impact of a random power source or load i on the transient high-frequency stability of node b under a critical anticipated fault. An impact greater than 0 indicates that a reduction in active power injected into the grid is beneficial to transient high-frequency stability. The larger the value, the more beneficial a reduction in the same amount of active power injected into the grid is to transient high-frequency stability. For each critical anticipated fault in the critical anticipated fault set corresponding to transient low-frequency stability, first determine that the transient low-frequency stability margin under each critical anticipated fault is less than η. fd.cr Node set B fd Under the critical anticipated failure, for B fd The ratio of the transient low-frequency stability influence of the mid-node to the maximum value of the transient low-frequency stability influence is greater than r. fd GL is a set of random power sources and loads. fd Then, the GL corresponding to each key anticipated fault is determined by solving the following formulas. fd Active power injected into the grid by stochastic source loads in the ultra-short term, for those not belonging to GL fd The random source loads are used to set the active power injected into the grid in the ultra-short term to the corresponding active power prediction value. In the formula, η fd.b P represents the transient low-frequency stability margin of node b under critical anticipated fault conditions, where α is a set parameter, and α is greater than 0. i0 For the active power injected into the grid by a random source or load i under the power system operating state corresponding to the latest assessment results of transient stability margin and source-load impact, P i P is the active power injected into the grid by a random source or load i during the ultra-short term. i.d P i.u These represent the lower and upper limits of the ultra-short-term active power confidence interval for stochastic power sources or loads i, respectively, and λ. fd.b.i This represents the impact of a random power source or load i on the transient low-frequency stability of node b under a critical anticipated fault. An impact greater than 0 indicates that an increase in active power injected into the grid is beneficial to transient low-frequency stability. The larger the value, the more beneficial it is to transient low-frequency stability for the same amount of active power injected into the grid.

6. The method for rapid assessment of ultra-short-term transient stability risk in power systems according to claim 2, characterized in that: Step 4 specifically involves: The following measures are taken for each of the key anticipated faults in the key anticipated fault sets corresponding to transient power angle stability, transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability: Step 4-1: Based on the active power plan / DC power plan / energy storage power plan / tie line power plan of ultra-short-term non-random source loads and the active power injected into the grid by random source loads corresponding to critical anticipated faults in the ultra-short-term, the automatic generation control (AGC) strategy in the energy management system is adopted to calculate the active power and DC power / energy storage power / tie line power injected into the grid by each power source and load in the power system. Step 4-2: Based on the current reactive power injected into the power grid by the power source and load, the current status of reactive power equipment, and the calculated active power and DC power / energy storage power / tie line power of each power source and load injected into the power grid in the power system, the automatic voltage control (AVC) strategy in the energy management system is used to calculate the reactive power injected into the power grid by each power source and load, the status of reactive power equipment, and the voltage of each node. Step 4-3: The calculated active and reactive power and reactive power equipment status of each power source and load injected into the power grid, the voltage of each node and the DC power / energy storage power / tie line power are used as the ultra-short-term risk operating status of the power system corresponding to the critical anticipated fault.

7. The method for rapid assessment of ultra-short-term transient stability risk in power systems according to claim 2, characterized in that: Step 6 specifically involves: The key anticipated fault sets obtained in step 5 for each of the transient power angle stability, transient high voltage stability, transient low voltage stability, transient high frequency stability, and transient low frequency stability, along with the minimum values ​​of transient power angle stability margin, transient high voltage stability margin, transient low voltage stability margin, transient high frequency stability margin, and transient low frequency stability margin under each key anticipated fault, and their corresponding key anticipated faults, the ultra-short-term risk operating status of the power system, and the source-load impact degree, are used as the ultra-short-term transient stability risk assessment information of the power system.

8. A rapid assessment system for ultra-short-term transient stability risks in power systems, characterized in that: include, Anticipated Fault Clustering Module: Based on the latest evaluation results of transient stability margin and source load impact under anticipated faults, cluster the anticipated faults in the anticipated fault set to determine the transient stability anticipated fault subset after clustering; Key anticipated fault set generation module: Based on the transient stability margin under anticipated faults, determine the key anticipated faults corresponding to each subset of anticipated faults, and obtain the key anticipated fault set for transient stability; Stochastic source load ultra-short-term active power determination module: Based on the ultra-short-term confidence interval of the stochastic source load and its impact on transient stability under critical anticipated faults, determine the stochastic source load ultra-short-term active power corresponding to each critical anticipated fault in the transient stability critical anticipated fault set. Ultra-short-term risk status generation module: Based on the ultra-short-term planned operation status and the stochastic source load ultra-short-term active power corresponding to the key anticipated faults, as well as the automatic generation control and automatic voltage control strategies, the module generates the ultra-short-term risk operation status of the power system corresponding to each key anticipated fault in the transient stability key anticipated fault set. Transient stability assessment module: For each critical anticipated fault in the transient stability critical anticipated fault set, transient stability assessment is performed under the critical anticipated fault according to the ultra-short-term risk operation state of the power system corresponding to the critical anticipated fault. Ultra-short-term risk determination module: Based on the transient stability assessment results, determine the ultra-short-term transient stability risk of the power system.

9. A computer-readable storage medium for storing one or more programs, characterized in that: The one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any of the methods in the rapid assessment methods for ultra-short-term transient stability risks of power systems according to claims 1 to 7.

10. A computing device, characterized in that: include: One or more processors, one or more memories, and one or more programs, wherein the one or more programs are stored in the one or more memories and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods in the rapid assessment methods for ultra-short-term transient stability risks of power systems according to claims 1 to 7.

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