Stability evaluation method, system and equipment of power system and medium

Abstract

The invention discloses a stability evaluation method, system and equipment of an electric power system and a medium, and the method is characterized in that the method comprises the steps: obtaining a node voltage parameter and a node injection power parameter of each node in the electric power system; inputting the node voltage parameter and the node injection power parameter into a preset initial power flow equation to perform recursive solution on the initial power flow equation to obtain a node voltage series and a node power series, and processing the node voltage series and the node power series by adopting a Pade approximation method to obtain a node power series; obtaining an initial amplitude and initial power of each node of the power system, performing interval reconstruction on the initial power flow equation based on the initial power to obtain a target power flow equation, and inputting the initial amplitude into the target power flow equation to calculate and obtain an interval voltage solution of each node; and if each interval voltage solution satisfies a first preset condition, evaluating the stability of the power system based on the interval voltage solutions. The accuracy of power flow analysis of the power system can be improved.

Description

Technical Field

[0001] This invention relates to the field of power system analysis, and more particularly to a method, system, equipment, and medium for evaluating the stability of a power system. Background Technology

[0002] Power flow analysis, as a fundamental technology in power grid planning, design, operation, dispatch, and security assessment, is a crucial technical support for evaluating the safety and reliability of system operation, identifying potential risks, and making dispatch decisions. Under operating environments characterized by large-scale integration of new energy sources, increasingly diversified power supply structures, and intensified load fluctuations, the operating state of power systems becomes more complex, and power flow distribution is significantly influenced by the interaction of multiple factors. Therefore, it is necessary to assess the overall stability of the power system through power flow analysis to improve the ability to identify potential instability risks in the power grid, thereby ensuring the safe and stable operation of the power system under complex operating conditions.

[0003] However, existing power flow analysis methods still primarily rely on traditional deterministic modeling, typically assuming that load and generation power are fixed and known quantities, and employing numerical iterative methods such as the Newton-Raphson method to solve nonlinear power flow equations. While these methods have good engineering applicability under given parameter conditions, they fail to reflect a single operating condition when load fluctuations and uncertainties in renewable energy output exist. This makes it difficult to describe the range of changes in the power system's operating state, thus affecting the accuracy of power flow analysis. Summary of the Invention

[0004] This invention provides a method, system, device, and medium for evaluating the stability of power systems, which can improve the accuracy of power flow analysis.

[0005] In a first aspect, embodiments of the present invention provide a method for evaluating the stability of a power system, comprising:

[0006] Obtain the node voltage parameters and node injected power parameters of each node in the power system;

[0007] The node voltage parameters and the node injected power parameters are input into a preset initial power flow equation to recursively solve the initial power flow equation, obtaining the node voltage series and the node power series. The Pad approximation method is used to process the node voltage series and the node power series to obtain the initial amplitude and initial power of each node in the power system. Based on the initial power, the initial power flow equation is reconstructed in intervals to obtain the target power flow equation. The initial amplitude is input into the target power flow equation to calculate the interval voltage solution of each node.

[0008] If each of the interval voltage solutions satisfies the first preset condition, the stability of the power system is evaluated based on the interval voltage solutions.

[0009] This invention, by acquiring node voltage parameters and node injected power parameters reflecting the operating state of the power system, can comprehensively and objectively characterize the real-time operating conditions of the power system, providing a true and complete data foundation for subsequent power flow calculations. This reduces calculation errors caused by incomplete or biased data from the source, thus providing a reliable input guarantee for improving the accuracy of power flow analysis. By introducing node parameters into the holomorphic power flow equations and using the Maclaurin series for recursive solution, the problems of sensitivity to initial conditions and easy getting trapped in local convergence or divergence in traditional numerical iteration methods can be avoided. Simultaneously, by combining Pad approximation to achieve analytical extension, the convergence radius of the series can be expanded, improving the voltage solution accuracy. This ensures that the stability and continuity of the solution can be maintained even under complex operating conditions, thereby improving the reliability of power flow calculation results and power system power flow analysis. The overall accuracy of power flow analysis is improved. Based on this, interval complex power is constructed using nodal power benchmarks, and the pure power flow equations are reconstructed in interval form. This expands the power flow calculation results from single, definite values ​​to interval results, enabling a more realistic reflection of the impact of operating parameter fluctuations on system state. This effectively reduces interval estimation bias and overly conservative issues, thus improving the overall accuracy of power flow analysis. Furthermore, by introducing a convergence criterion based on interval solution consistency, the validity of interval voltage solutions is verified, avoiding the output of non-converged or distorted calculation results. Simultaneously, stability assessment indicators are constructed using interval voltage amplitude and phase angle, achieving a quantitative mapping from power flow calculation results to system operating state determination. This ensures the mathematical reliability and engineering usability of the assessment results, further improving the accuracy of power flow analysis results in stability assessment.

[0010] Furthermore, the step of inputting the node voltage parameters and the node injected power parameters into a preset initial power flow equation to recursively solve the initial power flow equation includes:

[0011] The node voltage parameters and node injected power parameters in the initial power flow equation are subjected to McLaurin series expansion to obtain the first expression;

[0012] Match the coefficients of the same power terms in the first expression and the initial power flow equation to obtain a system of recursive equations;

[0013] The recursive equations are solved recursively step by step to obtain the number of node voltage levels and the number of node power levels for each node.

[0014] This invention achieves the stepwise analytical solution of the power flow equations by expanding the node voltage parameters and injected power parameters into a Maclaurin series and constructing a recursive equation system using coefficient matching of the same power. This transforms the nonlinear problem into a recursive linear calculation process, reduces the dependence on initial values, avoids the risk of iterative divergence, and provides a continuous analytical basis for subsequent Pad approximation, thereby improving the convergence stability and computational reliability of power flow calculation.

[0015] Furthermore, the Pad approximation method is used to process the node voltage levels and node power levels to obtain the initial amplitude and initial power of each node in the power system, including:

[0016] The Pad approximation function is determined based on the holomorphic embedding parameters in the initial power flow equations, the node voltage series, and the node power series.

[0017] When the fully pure embedding parameters satisfy the second preset condition, the Pad approximation function is solved to obtain the voltage analytical solution and power analytical solution for each node;

[0018] The initial amplitude and initial power of each node are determined based on the analytical solutions for voltage and power, respectively.

[0019] This invention introduces Pad approximation to analytically extend the node voltage and power series, transforming the finite series results into more accurate rational function expressions. This effectively expands the convergence domain of the series solution and improves the solution accuracy and stability when the fully embedded parameters are taken as actual operating conditions. As a result, more reliable initial magnitudes of node voltages and initial power are obtained, providing a high-precision benchmark solution for subsequent interval power flow calculations.

[0020] Furthermore, the step of reconstructing the initial power flow equation based on the initial power to obtain the target power flow equation includes:

[0021] Based on the initial power, the interval complex power is determined, and the interval complex power is substituted into the initial power flow equation to replace the node injection power parameters, thereby obtaining the interval equation;

[0022] The node voltage parameters are converted into a power series form of interval variables, and the power series form is coupled with the interval equation to obtain the target power flow equation.

[0023] This invention extends deterministic power parameters to interval complex power and embeds them into the original power flow equations, thereby achieving unified modeling of load and generation uncertainties. By converting node voltage parameters into interval power series and coupling them with interval equations, uncertainties are transmitted and calculated at the equation level, thus directly obtaining an interval power flow model that includes the influence of uncertain factors. This improves the ability of power flow analysis to characterize actual operational fluctuations and the reliability of the results.

[0024] Furthermore, determining the interval complex power based on the initial power includes:

[0025] The active power range and reactive power range of each node are determined based on the initial power and preset variables, respectively.

[0026] The active power range, the reactive power range, and the preset coefficient are weighted and combined to obtain the range complex power.

[0027] This invention extends deterministic power to active and reactive power intervals and combines them with weights to construct a unified interval complex power model. This enables a quantitative characterization of the uncertainty of load and power generation, thereby providing a consistent and controllable input boundary for subsequent interval power flow calculations and improving the stability and reliability of the results.

[0028] Furthermore, the step of inputting the initial amplitude into the target power flow equation to calculate the interval voltage solution for each node includes:

[0029] The initial amplitude is input into the target power flow equation, and the interval voltage and its reciprocal are expanded using McLaurin series to obtain the second expression.

[0030] Based on the second expression and the interval complex power, the target power flow equation is solved recursively step by step to obtain the interval voltage levels of each node;

[0031] The Pad approximation method is used to process the voltage series of each interval to obtain the interval voltage solution for each node.

[0032] This invention introduces an initial amplitude as the initial value for solving the interval power flow problem, and combines McLaurin series recursion and Pad approximation analytical extension to achieve rapid convergence and stable solution of the interval voltage, thereby effectively improving the calculation accuracy and numerical stability of the interval voltage solution and avoiding the distortion problem caused by the accumulation of series truncation error.

[0033] Furthermore, if each of the interval voltage solutions satisfies the first preset condition, then the stability of the power system is evaluated based on the interval voltage solutions, including:

[0034] The voltage levels of each interval are summed to obtain a summation result, and the summation result is compared with the voltage solution of the interval to obtain the voltage boundary difference of each node;

[0035] Determine whether the voltage boundary difference of each node satisfies the third preset condition. If it does, output the voltage amplitude of each node.

[0036] The voltage sensitivity index and tolerance index of each node are determined based on the voltage amplitude of each node in order to evaluate the stability of the power system.

[0037] This invention achieves automated convergence judgment and result screening by determining the consistency between the interval voltage series and the Pad approximation results. Furthermore, it introduces voltage sensitivity and tolerance indices to quantify the system operation risk, thereby improving the reliability of the interval power flow results and the ability to characterize the impact of uncertainties, and providing a scientific basis for power system stability analysis.

[0038] Secondly, embodiments of the present invention provide a power system stability assessment system, the system comprising: an acquisition module, a calculation module, and an assessment module;

[0039] The acquisition module is used to acquire the node voltage parameters and node injected power parameters of each node in the power system.

[0040] The calculation module is used to input the node voltage parameters and the node injected power parameters into a preset initial power flow equation to recursively solve the initial power flow equation, obtain the node voltage series and the node power series, process the node voltage series and the node power series using the Pad approximation method to obtain the initial amplitude and initial power of each node in the power system, reconstruct the initial power flow equation based on the initial power to obtain the target power flow equation, and input the initial amplitude into the target power flow equation to calculate the interval voltage solution of each node;

[0041] The evaluation module is used to evaluate the stability of the power system based on the interval voltage solutions if each interval voltage solution meets a first preset condition.

[0042] This invention combines fully embedded power flow solution, Pad approximation, and interval modeling to achieve integrated processing from deterministic power flow calculation to interval power flow deduction and stability assessment. It can simultaneously obtain interval results and stability evaluation indicators for the voltage of each node under uncertain conditions, thereby improving the accuracy, robustness, and automation level of power system state assessment under complex operating conditions.

[0043] Thirdly, embodiments of the present invention provide a terminal device, including: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus;

[0044] The memory is used to store at least one executable instruction that causes the processor to perform the operation of a power system stability assessment method as described in this application.

[0045] Fourthly, embodiments of the present invention provide a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device or system where the computer-readable storage medium is located to perform a power system stability assessment method as described in this application.

[0046] The above description is merely an overview of the technical solutions of the embodiments of the present invention. In order to better understand the technical means of the embodiments of the present invention and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0047] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0048] Figure 1 This is a flowchart illustrating one embodiment of a power system stability assessment method provided in this application;

[0049] Figure 2 This is a flowchart illustrating steps S201 to S203 provided in this application;

[0050] Figure 3 This is a flowchart illustrating steps S301 to S303 provided in this application;

[0051] Figure 4 This is a schematic diagram of the execution flow of the power system stability assessment method provided in this application;

[0052] Figure 5 This is a schematic diagram of the IEEE 30-node system topology provided in this application;

[0053] Figure 6 This is a schematic diagram of an embodiment of a power system stability assessment method provided in this application. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0055] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0056] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0057] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0058] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0059] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple groups" refers to two or more (including two groups), and "multiple pieces" refers to two or more (including two pieces).

[0060] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0061] Power flow analysis, a fundamental technology in power grid planning, design, operation, scheduling, and security assessment, plays a crucial role in calculating and analyzing the voltage distribution at each node and the power distribution along lines within a power system. This allows for the assessment of the system's operational safety and reliability, identification of potential risks, and the provision of a basis for dispatch decisions. Under the operating environment of large-scale renewable energy integration, increasingly diversified power supply structures, and intensifying load fluctuations, the power system's operating state exhibits significant uncertainty. Power flow distribution is significantly influenced by the coupling effects of multiple random factors. Therefore, power flow analysis is necessary to assess the overall stability of the power system, thereby improving the ability to identify potential instability risks and ensuring the safe and stable operation of the power system under complex conditions. However, existing power flow analysis methods still primarily rely on traditional deterministic modeling. These methods typically assume that load and generation power are fixed known quantities and employ numerical iterative methods such as the Newton-Raphson method to solve nonlinear power flow equations. While these methods have some engineering applicability under certain parameter conditions, in the presence of load fluctuations and uncertainties in renewable energy output, the calculation results only reflect a single operating condition and are insufficient to characterize the range of changes in the system's operating state. This, in turn, affects the ability of power flow analysis results to describe the actual operating state and the accuracy of the analysis.

[0062] See Figure 1 To improve the accuracy of power flow analysis, an embodiment of the present invention provides a method for evaluating the stability of a power system, including steps S101 to S103.

[0063] Step S101: Obtain the node voltage parameters and node injected power parameters of each node in the power system;

[0064] In some embodiments, firstly, basic operating data of the power system is imported through a power dispatch automation system, energy management system, or offline simulation platform to perform node modeling of the power system, obtaining the node number, node type, and network topology relationship between all nodes in the power system; wherein, the node type includes at least slack nodes, PQ nodes, and PV nodes. Secondly, according to the node type, the corresponding node voltage parameters and node injected power parameters are extracted respectively: for slack nodes, their given voltage amplitude and phase angle are obtained as reference voltage parameters; for PQ nodes, their corresponding active power load value and reactive power load value are obtained as node injected power parameters; for PV nodes, their generating active power and node voltage amplitude are obtained as node constraint parameters, and their reactive power allowable upper and lower limits are collected as operating constraints. Then, the node voltage parameters include the initial voltage amplitude, initial phase angle, and node specified voltage value of each node, and the node injected power parameters include the active power injected and reactive power injected by each node; wherein, the injected power is the algebraic sum of generating power and load power, used to characterize the power state injected into or absorbed from the grid by each node. Finally, the obtained node voltage parameters and node injected power parameters are normalized, including unifying the dimensions, standardizing conversion, and removing outlier data, to form a unified parameter input format, which serves as the basic input data for subsequent construction of fully embedded power flow equations and interval arithmetic modeling.

[0065] Through the above steps, unified modeling and standardized collection of power system node types, operating parameters and topology are achieved, ensuring that node voltage parameters and injected power parameters are complete, accurate and in a unified format, providing a reliable data foundation for subsequent power flow equation construction and interval extrapolation, and improving the accuracy of calculation results and the consistency of system modeling from the source.

[0066] Step S102: Input the node voltage parameters and the node injected power parameters into a preset initial power flow equation to recursively solve the initial power flow equation, obtain the node voltage series and the node power series, process the node voltage series and the node power series using the Pad approximation method to obtain the initial amplitude and initial power of each node in the power system, reconstruct the initial power flow equation based on the initial power to obtain the target power flow equation, and input the initial amplitude into the target power flow equation to calculate the interval voltage solution of each node;

[0067] In some embodiments, the step of inputting the node voltage parameters and the node injected power parameters into a preset initial power flow equation to recursively solve the initial power flow equation includes: performing Maclaurin series expansion on the node voltage parameters and node injected power parameters in the initial power flow equation to obtain a first expression; matching the coefficients of the same power terms in the first expression and the initial power flow equation to obtain a recursive equation system; and recursively solving the recursive equation system step by step to obtain the node voltage level and node power level of each node.

[0068] In some embodiments, the node voltage parameters and node injected power parameters in the initial power flow equations are subjected to McLaurin series expansion to obtain a first expression, specifically: First, the initial power flow equations are constructed:

[0069]

[0070] Where N is the total number of system nodes; k and m are node numbers, k is the current node, and m is any node connected to it; Y km Let be the k-th and m-th elements in the node admittance matrix, representing the equivalent admittance between nodes; V represents the parallel (to-ground) susceptance / admittance of node k; k (s), V m (s) represents the voltages at nodes k and m (in holomorphic function form expressed in holomorphic embedded parameter s); The voltage setpoint for node k (the given amplitude for a balanced or PV node); For a given complex power injection at node k, Q k (s) represents the active power and reactive power of node k, where Q k (s) represents reactive power that varies with s; j is the imaginary unit, j 2 =-1; (·) * For complex conjugate operation; s is the holomorphic embedding parameter (s=0 is the unloaded ground state, s=1 is the target operating point); This represents the summation over all nodes, and represents the relationship between the injected current and the admittance network.

[0071] In some embodiments, after constructing the initial power flow equations containing holomorphic embedded parameters s, in order to transform the originally nonlinear power flow equations into a recursively solvable linear form, the key unknown variables in the initial power flow equations are analytically functionalized, that is, the node voltage parameters V... k (s) and reactive power parameter Q in the node injected power parameters k(s) is considered as a holomorphic function of the holomorphic embedded parameter s, and its Maclaurin series expansion is performed around s=0. Therefore, the power series expression of the node voltage parameters with respect to the holomorphic embedded parameter s is first constructed:

[0072]

[0073] Among them, V k [n] represents the series term corresponding to the voltage of node k at order n. Furthermore, for the reactive power parameter Q, which is an unknown quantity in the node-injected power parameters of the PV node... k (s), which is also expanded into a power series form with respect to the holomorphic embedding parameter s:

[0074]

[0075] Among them, Q k [n] represents the series term corresponding to the reactive power of node k at order n. This is because the holomorphic power flow equations contain the reciprocal terms of the node voltages. To facilitate subsequent calculations, the reciprocal of the voltage is further expressed as an independent series:

[0076]

[0077] Among them, W k [n] represents the coefficient of the reciprocal series of the voltage at node k at the nth order. To establish W... k [n] and V k The recurrence relation between [n] corresponds to the identity relation: V k [s]·W k By performing a power series expansion of [s] = 1 and comparing coefficients using convolution operations, the recurrence formula for the reciprocal term is derived:

[0078]

[0079] Among them, V k [0] is the initial value of the node voltage at zero order, set according to the bud solution condition as: V k [0] = 1p.u., Q k [0] = 0. The above expanded expression, together with the reciprocal recurrence relation, constitutes the "first expression," providing an analytical basis for the subsequent construction of recurrence relations and the solution of order.

[0080] In some embodiments, the coefficients of the first expression and the initial power flow equation are matched for terms of the same power to obtain a recursive equation system. Specifically, the series forms of the node voltage, reactive power, and their reciprocals are substituted into the initial power flow equation. By comparing the terms of the same power of the holomorphic embedded parameter s, a system of linear algebraic equations between each order of unknown coefficients is established, thereby realizing the transformation from nonlinear equations to linear recursive equations. For PQ nodes, the series is substituted into the node power balance equation:

[0081]

[0082] Further, let's consider the above equations according to s n Expanding and rearranging by powers, we obtain the recurrence relation for node PQ at order n:

[0083]

[0084] For PV nodes, since reactive power is the variable to be determined, we substitute it into the following embedded expression:

[0085]

[0086] Expanding this equation by the same power and simplifying it, we obtain the nth order recurrence relation as follows:

[0087]

[0088] Meanwhile, to ensure that the calculation results satisfy the physical meaning, a voltage magnitude constraint condition is also introduced in the recursive process to apply voltage amplitude constraints to the PV nodes: when n = 0, V k [0] = 1; when n = 1, When n≥2 Furthermore, for the slack node, its voltage level is directly determined based on the given reference voltage as: V k [0] = 1, V k [n] = 0, n ≥ 2. Therefore, by using the method of "series substitution + matching of terms of the same power", the original nonlinear power flow model is transformed into a set of linear recursive equations that are solved step by step according to order.

[0089] In some embodiments, the recursive equations are solved recursively step by step to obtain the nodal voltage levels and nodal power levels at each node. Specifically, after constructing the recursive equations, the voltage levels and reactive power levels at each node are solved recursively step by step. Specifically, starting from the known zeroth-order initial value: V k [0] = 1, Q k Starting from [0] = 0, first calculate W using the reciprocal relation. k[1], and then substitute it into the first-order recurrence equations for PQ nodes and PV nodes, and solve to obtain: {V k [1],Q k [1]}. Subsequently, the calculated low-order coefficients V k [0],V k [1],...,V k [n-1] and W k [0],...,W k Substituting [n-1] into the higher-order recurrence relation, and solving sequentially under the premise of satisfying the voltage constraints of each node, we obtain: {V k [n],Q k [n]}. By recursively deriving upwards step by step, a complete nodal voltage series representation is finally formed: V k (s)=V k [0]+V k [1]s+V k [2]s 2 +… and reactive power series representation: Q k (s)=Q k [0]+Q k [1]s+Q k [2]s 2 +…. When the holomorphic embedding parameter s = 1, summing the levels yields the analytical solution to the initial power flow problem:

[0090]

[0091] Among them, V k [n] represents the voltage series coefficient of node k at the nth order, indicating the contribution of that order to the node voltage; Q k [n] represents the reactive power series coefficient of node k at the nth order, indicating the incremental contribution of that order to the node's reactive power. Thus, deterministic solutions for node voltage and reactive power in the power system can be obtained directly without numerical iteration.

[0092] In some embodiments, the step of using the Pad approximation method to process the node voltage series and the node power series to obtain the initial amplitude and initial power of each node in the power system includes: determining the Pad approximation function based on the holomorphic embedding parameters in the initial power flow equations, the node voltage series, and the node power series; solving the Pad approximation function when the holomorphic embedding parameters satisfy a second preset condition to obtain the voltage analytical solution and power analytical solution for each node; and determining the initial amplitude and initial power of each node based on the voltage analytical solution and the power analytical solution, respectively.

[0093] In some embodiments, the Pad approximation function is determined based on the holomorphic embedding parameter in the initial power flow equation, the node voltage series, and the node power series. Specifically, after completing the order-wise solution of the node voltage series and the node reactive power series, although the McLaurin series has good convergence in the neighborhood of the holomorphic embedding parameter s, the series may suffer from insufficient convergence radius when the holomorphic embedding parameter gradually approaches the physically corresponding value s = 1, thus affecting the accuracy and stability of the analytical solution. Therefore, in this embodiment, the Pad approximation method is further introduced to analytically extend the node voltage series to expand the convergence region through rational function approximation, thereby improving the calculation accuracy at s = 1. Specifically, the voltage power series of node k is used as an example: Based on this, construct a Pad approximation function of the following form:

[0094]

[0095] Where L is the order of the numerator polynomial; M is the order of the denominator polynomial; a i b are the coefficients of the numerator polynomial; j The coefficients of the denominator polynomial; Let be the Pad approximation expression for the node voltages. Based on the principle of consistency in expansion accuracy between the Pad approximation function and the original Maclaurin series, the following requirements must be met:

[0096]

[0097] That is, the Pad approximation function at s=0 is completely consistent with the original series at the first L+M+1 orders, thus serving as the constraint basis for subsequent calculation of polynomial coefficients.

[0098] In some embodiments, when the fully virtually embedded parameters satisfy a second preset condition, the Pad approximation function is solved to obtain the voltage analytical solution and power analytical solution for each node. Specifically, in this embodiment, the second preset condition is: the fully virtually embedded parameters take the physical value s = 1, that is, the analytical extension from the embedded domain to the actual power grid operating state is completed. When solving the coefficients of the Pad approximation function, a linear equation system is constructed using the "direct matrix method". First, the denominator coefficient constraint relationship is constructed using the Maclaurin series terms: for n = L+1, L+2, ..., L+M, according to the series matching principle, the following linear equation system is constructed: This constitutes the relationship between the unknown coefficient b. j The linear equation system is solved using matrix methods to obtain the solution set of denominator coefficients: {b1, b2, ..., b M After obtaining the denominator coefficients, the numerator polynomial coefficients are constructed based on the explicit calculation relationship:

[0099]

[0100] This allows us to fully determine the Pad approximation function. Furthermore, when the fully embedded parameters satisfy the second preset condition s = 1, substituting them into the Pad approximation function yields the analytical solutions for the voltages at each node:

[0101]

[0102] Meanwhile, for nodal reactive power, the Pad approximation function can be constructed in the same way:

[0103]

[0104] And by taking the value at s=1, the analytical solution of reactive power for each node is obtained:

[0105] In some embodiments, the initial magnitude and initial power of each node are determined based on the analytical voltage solution and the analytical power solution, respectively. Specifically, the analytical voltage solution and the analytical reactive power solution obtained through analytical extension are used as the output results of the deterministic power flow solution. Specifically, the initial magnitude of the voltage at each node is determined as follows: The nodal voltage magnitude is obtained by taking the modulus of the analytical solution, and this serves as the initial voltage reference value for subsequent interval power flow calculations and sensitivity analysis. The active power reference value P for each node... k With reactive power reference value Q k Determined in the following ways: The node current is calculated using the network admittance matrix: Therefore, based on the initial amplitude and initial power of each node obtained by analytical continuation, the power flow distribution state of the power system under deterministic operating conditions is constructed, which serves as the basic input for subsequent interval embedding analysis and power system stability assessment.

[0106] In some embodiments, the step of reconstructing the initial power flow equation based on the initial power to obtain the target power flow equation includes: determining the interval complex power based on the initial power; substituting the interval complex power into the initial power flow equation to replace the node injected power parameters to obtain the interval equation; converting the node voltage parameters into a power series form of interval variables; and coupling the power series form with the interval equation to obtain the target power flow equation.

[0107] In some embodiments, the interval complex power is determined based on the initial power, and the interval complex power is substituted into the initial power flow equation to replace the node injection power parameters, resulting in the interval equation. Specifically, to introduce load fluctuations and renewable energy output uncertainties into the power flow analysis process, the initial amplitude and initial power of each node obtained in the above steps are first used as reference quantities. Specifically, for each node k, the active power reference value P is extracted from the deterministic power flow calculation results. k With reactive power reference value Q k By combining this with a pre-defined uncertainty percentage parameter α, the uncertainty range of the power input is constructed, thereby expanding the deterministic parameter into an interval form. After setting the uncertainty percentage, interval modeling is performed on active power and reactive power respectively, resulting in:

[0108]

[0109] in, This represents the active power of node k in the interval; Let α represent the reactive power of node k within the interval; α is the uncertainty proportionality parameter. For power generation nodes containing renewable energy, since their output is constrained by physical structure, the interval boundaries are further modified to ensure that the interval meets the actual operable range: in, and This represents the upper and lower bounds of the power at node k in a physically feasible sense. After completing the interval power modeling, the interval active power and interval reactive power are combined into interval complex power so that they can be directly embedded into the power flow equations: Right now:

[0110]

[0111] In this embodiment, the constructed interval complex power is used to replace the deterministic nodal injection power parameters in the initial power flow equations. This allows the initial power flow equations to be reconstructed into interval form.

[0112] It should be noted that the interval holomorphic power flow equations for different types of nodes are expressed as follows: PQ node interval equations: PV node interval equation: Balance node: in: Let be the complex voltage over the interval at node k; Inter-node series admittance; is the node-to-ground susceptance; the asterisk * indicates the conjugate operation; s is the holomorphic embedding parameter. Thus, the reconstruction from the initial power flow equations to the interval equations is completed.

[0113] In some embodiments, the node voltage parameters are converted into a power series form of interval variables, and the power series form is coupled with the interval equation to obtain the target power flow equation. Specifically, after obtaining the interval equation, to achieve the step-by-step solution of the interval voltage, the node voltage parameters are converted into an interval power series form with respect to the embedded parameter s. The interval voltage is expressed in Maclaurin series form:

[0114]

[0115] in, This is the nth order interval voltage term; These represent the lower and upper bounds of the interval, respectively. Since the interval equations involve voltage reciprocal operations, to ensure consistency in the series substitution, their reciprocal forms are also constructed:

[0116]

[0117] in, After constructing the interval power series, the interval voltage series and the interval reciprocal series are simultaneously substituted into the aforementioned interval equations, and the power flow equations for each node are expanded using terms of the same power. By categorizing the terms according to the power of the embedded parameter s and comparing the coefficients of each order, the interval algebraic equations are transformed into a set of interval recursive equations. That is, through the method of "matching terms of the same power," the interval power flow problem is transformed into a problem concerning interval variables. and The recursive formula is used to obtain the interval holomorphic embedded power flow equation (i.e., the target power flow equation), which lays the foundation for subsequent stepwise recursive solution.

[0118] In some embodiments, determining the interval complex power based on the initial power includes: determining the active power interval and reactive power interval of each node based on the initial power and preset variables; and weighting the active power interval, the reactive power interval, and preset coefficients to obtain the interval complex power.

[0119] In some embodiments, the active power range and reactive power range of each node are determined based on the initial power and preset variables, specifically: based on the node active power reference value P. k The extended proportional coefficient α is used to construct a corresponding active power interval expression for each node using interval arithmetic modeling:

[0120]

[0121] Specifically, based on the operation control strategies and load regulation ranges of each node in the power grid, a preset power expansion ratio coefficient α is obtained. This expansion ratio coefficient is used to reflect the allowable variation range of power relative to its reference value; (1-α)Pk (1+α)P is the lower limit of the interval; k This is the upper limit of the interval; Let represent the active power of node k within a given interval. Using the same interval expansion method as the active power, we model the reactive power of the node within an interval, obtaining the corresponding reactive power interval model:

[0122]

[0123] in: Represents the reactive power of node k in the interval; lower limit (1-α)Q k With upper limit (1+α)Q k These correspond to the permissible variation boundaries of reactive power. For nodes containing renewable energy generation units, since their output power is affected by equipment capacity or control limits, the interval boundaries need to be corrected to meet physical constraints, specifically: That is, by adjusting the lower and upper limits of the range, the active power range is always kept within the allowable power range of the equipment; reactive power is also constrained and adjusted in the same way. At this point, the active power range of each node has been completed. and reactive power range The construction of this provides the input basis for subsequent interval power flow equations.

[0124] In some embodiments, the active power range, the reactive power range, and a preset coefficient are weighted and combined to obtain the range complex power. Specifically, the obtained active power range and reactive power range are used as the real and imaginary parts of the complex power, respectively. Based on the complex power definition formula: S = P + jQ, it is extended to the range expression form to construct the range complex power input for node k. Active power in the interval Interval reactive power Substituting the upper and lower bounds into the above equation, we obtain the complete expression for the complex power over the interval:

[0125]

[0126] Wherein, the real part interval represents the range of active power variation at the node; the imaginary part interval represents the range of reactive power variation at the node; the complex intervals together constitute the complex interval modeling form of the node injected power. The complex power intervals are then... As a power input term in interval variable form, it is used to replace the scalar power term in the original deterministic power flow equation and as the injected power parameter in the subsequent interval holomorphic embedding power flow equation reconstruction process, so that the system model is transformed from deterministic form to interval form.

[0127] Please refer to Figure 2In some embodiments, the step of inputting the initial amplitude into the target power flow equation to calculate the interval voltage solution for each node includes: steps S201 to S203;

[0128] Step S201: Input the initial amplitude into the target power flow equation, and perform McLaurin series expansion on the interval voltage and the reciprocal of the interval voltage in the target power flow equation to obtain the second expression;

[0129] In some embodiments, the node interval complex power obtained in the preceding steps and initial amplitude |V k Input to the target power flow equation. (For node voltage) and the reciprocal of the node voltage Expanding it using the Maclaurin series yields a series expression in interval form, which is the second expression:

[0130]

[0131] in, This represents the nth-order voltage level of node k in interval s; This represents the reciprocal series of the voltage at node k over the nth order interval s; the upper and lower bounds are respectively... and Used for interval arithmetic operations.

[0132] Step S202: Based on the second expression and the interval complex power, the target power flow equation is solved recursively step by step to obtain the interval voltage level of each node;

[0133] In some embodiments, the interval McLaurin series expression (i.e., the second expression) obtained in the preceding steps is substituted into the interval holomorphic embedded power flow equation (i.e., the target power flow equation), and recursive relationships are established for PQ nodes and PV nodes respectively:

[0134] PQ node recursive formula:

[0135]

[0136] PV node recursive formula:

[0137]

[0138] in, This represents the interval series of reactive power at the PV node. Using the above recursive formula, the interval voltage series of each order can be calculated sequentially.

[0139] Step S203: The Pad approximation method is used to process the voltage series of each interval to obtain the interval voltage solution of each node.

[0140] In some embodiments, the number of node interval voltage levels Construct an interval Pad approximation function:

[0141]

[0142] Where L and M are the orders of the numerator and denominator polynomials, respectively; Let be the interval coefficients of the numerator and denominator. Taking the interval Padre approximation function at s=1, we obtain the analytical solution for the interval voltage at each node:

[0143] Through the above steps, the node power and voltage are modeled in a unified interval form based on the deterministic power flow solution, and deeply coupled with the fully embedded power flow equation. This allows the interval analytical solution of each node voltage to be obtained directly without random sampling, effectively improving the ability to characterize load fluctuations and changes in renewable energy output, and enhancing the completeness, stability and engineering usability of the power flow calculation results.

[0144] Step S103: If each of the interval voltage solutions satisfies the first preset condition, the stability of the power system is evaluated based on the interval voltage solutions.

[0145] Please refer to Figure 3 In some embodiments, if each of the interval voltage solutions satisfies a first preset condition, then the stability of the power system is evaluated based on the interval voltage solutions, including steps S301 to S303.

[0146] Step S301: Summate the voltage levels of each interval to obtain a summation result, and compare the summation result with the voltage solution of the interval to obtain the voltage boundary difference of each node;

[0147] In some embodiments, the number of node interval voltage levels obtained in the aforementioned steps Summing the first n orders yields the partial sum of the McLaurin series of voltages over the node intervals: Simultaneously, calculate the result of the Pad approximation function for the nodal interval at s=1: By comparing the summation results with the Pad approximation results, the voltage boundary differences at each node are obtained:

[0148]

[0149] In this embodiment, if For any node k, the convergence threshold tolerance = 10 is exceeded. -6 If pu, then increase the series order n and continue to solve recursively to ensure that the contribution of higher-order terms to the interval voltage is fully considered.

[0150] Step S302: Determine whether each voltage boundary difference satisfies the third preset condition. If it does, output the voltage amplitude of each node.

[0151] In some embodiments, the third preset condition: ΔV k <tolerance, tolerance=10 -6 If the condition holds true for all nodes, then the recursive voltage series of the interval is considered to have converged. After convergence, the complete interval voltage of each node is output. In this embodiment, the following settings can be directly applied to the balancing node: This ensures that the node voltage remains constant, in accordance with physical constraints.

[0152] Step S303: Determine the voltage sensitivity index and tolerance index of each node based on the voltage amplitude to evaluate the stability of the power system.

[0153] In some embodiments, based on the upper and lower bounds of the voltage amplitude of each node obtained in step S302, the node voltage sensitivity index VSI is calculated to reflect the sensitivity of the interval voltage to uncertain power input.

[0154]

[0155] in, The deterministic voltage magnitude at node k (obtained by conventional HELM calculation when there is no uncertainty); These are the lower and upper limits of the node voltage range output in step S302, respectively. Simultaneously, a tolerance index AI is introduced to evaluate the ability of the range results to cover real voltage fluctuations (which can be verified through Monte Carlo simulation):

[0156]

[0157] Where, N MC This represents the total number of voltage samples in the Monte Carlo simulation. Voltage falling within the node interval The number of samples within the range. In this embodiment, to ensure the reliability of the interval results, the AI ​​judgment criterion can be set as: AI k ≥95%. When all nodes meet this condition, it indicates that the power flow results of the interval can cover the vast majority of real voltage fluctuations, avoiding the omission of risks caused by excessive interval contraction.

[0158] For ease of understanding, Figure 4This is a schematic diagram of the execution flow of the power system stability assessment method provided in this application. First, in the "Initialization" step, the network structure parameters, node power parameters, baseline values, and uncertainty analysis parameters of the power system are input to construct the basic data model for power flow calculation. Then, a deterministic holomorphic power flow equation is constructed based on the Holomorphic Embedded Power Flow Method (HELM), and the deterministic voltage and power results of each node are solved using the McLaurin series and Pad approximation, serving as the baseline for subsequent interval modeling. Next, in the "Introducing Interval Arithmetic Theory" step, uncertain loads and outputs are modeled in interval form. Second, the interval variables are embedded into the HELM holomorphic power flow equation, and the interval-form power flow equation is recursively solved to obtain the series solution of the interval voltage for each node. Finally, a convergence criterion is constructed to verify the consistency of the McLaurin series and Pad approximation results. Iteration stops when a preset threshold condition is met, ultimately outputting stable interval power flow results that effectively reflect the impact of uncertainty on the power system's operating state.

[0159] For example, an application example is provided to verify the proposed power system stability assessment method based on the IEEE 30-bus system. First, the system baseline parameter is set as S. base =100MVA, V base =132kV, f base =50Hz, and based on the type and uncertainty characteristics of the load and generation sides, power ranges for each node are constructed: for PQ nodes, the uncertainty percentage α = 5%; for conventional PV nodes, α = 10%; for renewable energy access nodes (such as PV nodes 11 and 13 with wind power access), α = 20%. Subsequently, the deterministic power flow is solved using the HELM method to obtain the voltage and power reference values ​​for each node. Based on this, and combined with interval arithmetic theory, the active power range for each node is constructed. and reactive power range The physical constraint boundaries of the renewable energy nodes are then corrected. Next, the interval power is embedded into the holomorphic power flow equations, and the voltage series of each node interval is obtained through Maclaurin series expansion and hierarchical solution. The Pad approximation method is then used for analytical extension. A convergence threshold of tolerance = 10 is set. -6 `pu` determines the consistency between the interval voltage series and the Pad approximation result, and outputs the final interval voltage solution after recursion convergence. Applying this method, the interval voltage magnitude and phase angle at each node can be obtained. Simultaneously, the voltage sensitivity index (VSI) and range tolerance index (AI) were calculated to verify the coverage of actual voltage fluctuations by the range results. The results showed that the AI ​​values ​​all exceeded 95%, indicating that the method can effectively reflect the voltage fluctuation range of the system under power uncertainty, and provide a quantitative basis for the steady-state security and uncertainty analysis of the power system.

[0160] For ease of understanding, Figure 5 This is a schematic diagram of the IEEE 30-node system topology provided in this application, used to verify the power system stability assessment method described in this application. The system consists of 30 nodes, 41 transmission lines, and 6 generators. Nodes 1, 2, 5, 8, 11, and 13 are connected to generators, and some nodes (such as 11 and 13) are assumed to be connected to renewable energy generation. Each line in the diagram represents a transmission line, the arrow direction indicates the reference direction for power flow calculation, and each node number corresponds to its sequence number. Through this system, power flow analysis can be performed on node voltage amplitude, phase angle, and power flow, and combined with the method of this invention, the voltage range and power system stability under different power uncertainties can be assessed.

[0161] Through the above steps, by introducing interval arithmetic into the fully embedded power flow method (HELM), the voltage of each node under uncertain power conditions is solved in intervals. Combined with the convergence criterion, high accuracy and stability verification are achieved, which can accurately characterize the voltage fluctuation range. Furthermore, the voltage sensitivity index (VSI) and capacity index (AI) are used to quantitatively evaluate the stability of the power system. In the presence of uncertainties in load and renewable energy output, the reliability of voltage assessment is improved, the risk of misjudgment is reduced, and an effective decision-making basis is provided for the steady-state safe operation of the power grid.

[0162] like Figure 6 As shown, based on the above method embodiments, corresponding apparatus embodiments are provided;

[0163] An embodiment of the present invention provides a schematic diagram of the structure of a power system stability assessment system, including: an acquisition module 100, a calculation module 200, and an assessment module 300;

[0164] The acquisition module 100 is used to acquire the node voltage parameters and node injected power parameters of each node in the power system.

[0165] The calculation module 200 is used to input the node voltage parameters and the node injected power parameters into a preset initial power flow equation to recursively solve the initial power flow equation, obtain the node voltage series and the node power series, process the node voltage series and the node power series using the Pad approximation method to obtain the initial amplitude and initial power of each node in the power system, reconstruct the initial power flow equation based on the initial power to obtain the target power flow equation, and input the initial amplitude into the target power flow equation to calculate the interval voltage solution of each node;

[0166] The evaluation module 300 is used to evaluate the stability of the power system based on the interval voltage solutions if each interval voltage solution meets the first preset condition.

[0167] It is understood that the above-described apparatus embodiments correspond to the method embodiments of the present invention, and can implement the power system stability assessment method provided by any of the above-described method embodiments of the present invention. More detailed workflows and principles of this system can be found, but are not limited to, the relevant descriptions of the above methods.

[0168] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0169] Based on the above-described embodiment of a power system stability assessment method, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a power system stability assessment method according to any embodiment of the present invention.

[0170] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0171] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0172] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0173] Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute a power system stability assessment method according to any of the above-described method embodiments of the present invention.

[0174] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0175] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for evaluating the stability of a power system, characterized in that, include: Obtain the node voltage parameters and node injected power parameters of each node in the power system; The node voltage parameters and the node injected power parameters are input into a preset initial power flow equation to recursively solve the initial power flow equation, obtaining the node voltage series and the node power series. The Pad approximation method is used to process the node voltage series and the node power series to obtain the initial amplitude and initial power of each node in the power system. Based on the initial power, the initial power flow equation is reconstructed in intervals to obtain the target power flow equation. The initial amplitude is input into the target power flow equation to calculate the interval voltage solution of each node. If each of the interval voltage solutions satisfies the first preset condition, the stability of the power system is evaluated based on the interval voltage solutions.

2. The method for evaluating the stability of a power system as described in claim 1, characterized in that, The step of inputting the node voltage parameters and the node injected power parameters into a preset initial power flow equation to recursively solve the initial power flow equation includes: The node voltage parameters and node injected power parameters in the initial power flow equation are subjected to McLaurin series expansion to obtain the first expression; Match the coefficients of the same power terms in the first expression and the initial power flow equation to obtain a system of recursive equations; The recursive equations are solved recursively step by step to obtain the number of node voltage levels and the number of node power levels for each node.

3. The method for evaluating the stability of a power system as described in claim 1, characterized in that, The Pad approximation method is used to process the node voltage levels and node power levels to obtain the initial amplitude and initial power of each node in the power system, including: The Pad approximation function is determined based on the holomorphic embedding parameters in the initial power flow equations, the node voltage series, and the node power series. When the fully pure embedding parameters satisfy the second preset condition, the Pad approximation function is solved to obtain the voltage analytical solution and power analytical solution for each node; The initial amplitude and initial power of each node are determined based on the analytical solutions for voltage and power, respectively.

4. The method for evaluating the stability of a power system as described in claim 1, characterized in that, The step of reconstructing the initial power flow equation based on the initial power to obtain the target power flow equation includes: Based on the initial power, the interval complex power is determined, and the interval complex power is substituted into the initial power flow equation to replace the node injection power parameters, thereby obtaining the interval equation; The node voltage parameters are converted into a power series form of interval variables, and the power series form is coupled with the interval equation to obtain the target power flow equation.

5. The method for evaluating the stability of a power system as described in claim 4, characterized in that, The determination of the interval complex power based on the initial power includes: The active power range and reactive power range of each node are determined based on the initial power and preset variables, respectively. The active power range, the reactive power range, and the preset coefficient are weighted and combined to obtain the range complex power.

6. The method for evaluating the stability of a power system as described in claim 1, characterized in that, The step of inputting the initial amplitude into the target power flow equation to calculate the interval voltage solution for each node includes: The initial amplitude is input into the target power flow equation, and the interval voltage and its reciprocal are expanded using McLaurin series to obtain the second expression. Based on the second expression and the interval complex power, the target power flow equation is solved recursively step by step to obtain the interval voltage levels of each node; The Pad approximation method is used to process the voltage series of each interval to obtain the interval voltage solution for each node.

7. The method for evaluating the stability of a power system as described in claim 6, characterized in that, If each of the interval voltage solutions satisfies a first preset condition, then the stability of the power system is evaluated based on the interval voltage solutions, including: The voltage levels of each interval are summed to obtain a summation result, and the summation result is compared with the voltage solution of the interval to obtain the voltage boundary difference of each node; Determine whether the voltage boundary difference of each node satisfies the third preset condition. If it does, output the voltage amplitude of each node. The voltage sensitivity index and tolerance index of each node are determined based on the voltage amplitude of each node in order to evaluate the stability of the power system.

8. A stability assessment system for a power system, characterized in that, The system includes: an acquisition module, a calculation module, and an evaluation module; The acquisition module is used to acquire the node voltage parameters and node injected power parameters of each node in the power system. The calculation module is used to input the node voltage parameters and the node injected power parameters into a preset initial power flow equation to recursively solve the initial power flow equation, obtain the node voltage series and the node power series, process the node voltage series and the node power series using the Pad approximation method to obtain the initial amplitude and initial power of each node in the power system, reconstruct the initial power flow equation based on the initial power to obtain the target power flow equation, and input the initial amplitude into the target power flow equation to calculate the interval voltage solution of each node; The evaluation module is used to evaluate the stability of the power system based on the interval voltage solutions if each interval voltage solution meets a first preset condition.

9. A terminal device, characterized in that, The system includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements a power system stability assessment method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, include: A stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform a power system stability assessment method as described in any one of claims 1-7.

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