Wind power integration system transient power angle stability affine quantitative evaluation method considering uncertainty

Abstract

The invention provides a wind power integration system transient power angle stability affine quantitative evaluation method considering uncertainty, comprising the following steps: constructing an affine coupling model between wind power and synchronous machine output, and generating an affine expression containing noise elements; establishing a dynamic equivalent admittance model based on the affine expression and the low-voltage ride-through parameters of the fan, and enabling the power external characteristics of the fan to be equivalent to dynamic parallel grounding admittance; performing network simplification on non-generator nodes in the wind power grid-connected system by using a Ward equivalence technology; based on the simplified admittance matrix and the dynamic equivalent admittance, constructing an affine differential-algebraic equation set with uncertainty, and alternately solving through an implicit trapezoid method and affine arithmetic; performing noise element decomposition on the affine state quantity, analyzing contribution degrees of different uncertain sources to power angle deviation, and establishing a quantitative mapping relation between multi-source disturbance and power angle dynamics; and converting the affine state quantity into an interval envelope, and evaluating the transient power angle stability margin according to the maximum power angle difference deviation quantity.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system stability analysis and new energy grid connection, and specifically relates to an affine quantitative evaluation method for transient power angle stability of a wind power grid connection system taking uncertainty into account. Background Art

[0002] With the rapid increase in the penetration rate of new energy, the inertia characteristics of the power system have been significantly reduced, and the transient power angle stability problem caused by wind power grid connection has become increasingly prominent. In the traditional power system stability analysis, time domain numerical simulation provides technical support for the evaluation of the power angle stability of synchronous generators by constructing a differential-algebraic equation model and numerically solving the dynamic trajectory of the system state quantity. However, the inherent randomness and volatility of wind power output lead to enhanced system uncertainty characteristics, and the existing deterministic simulation methods have the following technical bottlenecks: Insufficient model adaptability: Fixed parameter models cannot accurately characterize the dynamic coupling effects of multi-source uncertainties in the scenario of new energy penetration, and it is difficult to describe the impact of multiple factors such as wind speed fluctuations and synchronous machine response on power angle stability.

[0003] Conflict between computational efficiency and accuracy: The Monte Carlo method requires large-scale repeated simulations, and the computational cost is too high. Although proxy models such as the random response surface method and polynomial chaos expansion improve efficiency, they face the "curse of dimensionality" in high-dimensional scenarios, and the sample generation mechanism is complex, making it difficult to balance real-time and accuracy.

[0004] Lack of physical authenticity: The interval analysis method ignores the dynamic correlation of variables, resulting in conservative results. The stochastic differential equation model weakens the authenticity of dynamic response due to simplified wind turbine control strategy. In addition, existing stochastic analysis methods generally strongly associate the frequency of wind power fluctuations with the numerical integration step size, which is inconsistent with the slow time-varying characteristics of actual output.

[0005] Limitations of uncertainty characterization: Existing technologies mostly rely on a single probability distribution or interval assumption, and lack a unified quantitative framework for the synergistic effects of multiple sources of uncertainty (such as wind speed randomness and grid parameter fluctuations), resulting in insufficient ability to refine the transient stability boundary.

[0006] The above defects seriously restrict the engineering applicability of transient stability assessment of power grids with a high proportion of renewable energy. It is urgent to develop new uncertainty quantification methods to achieve efficient and accurate assessment of transient power angle stability of wind power grid-connected systems. Summary of the invention

[0007] In view of the defects of the existing technology such as insufficient model adaptability, contradiction between calculation efficiency and accuracy, lack of physical authenticity and limitation of multi-source uncertainty representation, the present invention provides an affine quantitative evaluation method for transient power angle stability of wind power grid-connected system taking into account uncertainty, and achieves technical breakthroughs through the following innovative designs: Affine coupling mechanism of multi-source uncertainty: A dynamic correlation model between wind turbine output and synchronous machine mechanical power is established, and multi-source uncertainties such as wind speed fluctuation and synchronous machine response are quantified into affine expressions. The coupling strength of the noise element coefficient to the system dynamics is characterized; Full-time dynamic equivalent modeling: A wind turbine dynamic admittance model is constructed based on low voltage ride-through parameters to accurately describe the physical characteristics of active / reactive power control during faults, and the Ward equivalent technology is combined to achieve refined simplification of network topology; Affine-numerical hybrid solution strategy: Combining the numerical stability of the implicit trapezoidal method with the uncertainty propagation capability of affine arithmetic, alternately solving affine differential-algebraic equations to achieve efficient tracking of the dynamic trajectory of uncertainty in the time domain; Disturbance tracing and stability margin analysis: The contribution of multi-source uncertainty to the power angle offset is quantified through noise element decomposition, and the affine state quantity is converted into an interval envelope. An engineerable stability margin evaluation index is constructed based on the maximum power angle difference boundary.

[0008] The present invention breaks through the conservative limitations of traditional methods, significantly improves the accuracy and efficiency of transient stability assessment of new energy high-penetration power grids, and provides high-reliability decision support for the safe operation of power systems.

[0009] The technical solution specifically adopted by the present invention to solve the technical problem is: An affine quantitative evaluation method for transient power angle stability of a wind power grid-connected system taking into account uncertainty comprises the following steps: An affine coupling model between wind power and synchronous generator output is constructed. Based on the affine power flow, the uncertainty effect of wind speed fluctuation on the mechanical power of the synchronous generator is quantified, and an affine expression including noise elements is generated. Based on the affine expression and the low voltage ride-through parameters of the wind turbine, a dynamic equivalent admittance model is established to convert the power external characteristics of the wind turbine into a dynamic parallel-connected ground admittance; The Ward equivalent technique is used to simplify the non-generator nodes in the wind power grid-connected system and obtain the simplified node admittance matrix. Based on the simplified node admittance matrix and dynamic equivalent admittance, an affine differential-algebraic equation system with uncertainty is constructed, and the affine state quantity of the synchronous generator power angle is obtained by alternating the implicit trapezoidal method and affine arithmetic. Performing noise element decomposition on the affine state quantity, analyzing the contribution of different uncertainty sources to the power angle offset, and establishing a quantitative mapping relationship between multi-source disturbance and power angle dynamics; The affine state quantity is converted into an interval envelope, and the transient power angle stability margin is evaluated according to the maximum power angle difference deviation.

[0010] Furthermore, the affine coupling model is constructed by defining the wind turbine output as the affine center value during the steady state, superimposing a linear combination of multiple noise elements characterizing the random fluctuations of wind speed and their corresponding coefficients, wherein the coefficients can reflect the dynamic coupling strength of each noise element to the mechanical power of the synchronous machine after affine power flow quantization.

[0011] Furthermore, the dynamic equivalent admittance model is derived as follows: based on the complex power control characteristics of the wind turbine during low voltage ride-through, a dynamic equivalent admittance model is established, and the wind turbine is equivalent to a dynamic parallel-to-ground admittance, and the value of the dynamic parallel-to-ground admittance is the ratio of the conjugate value of the wind turbine complex power at time t to the square of the wind turbine access node voltage.

[0012] Furthermore, the Ward equivalent technology specifically includes: modeling the load node as a constant admittance model, and generating an equivalent network equation that only retains the synchronous generator node by merging the admittance parameters of all non-generator nodes except the synchronous generator node.

[0013] Furthermore, the numerical integration process of the implicit trapezoidal method is: the affine state quantity at time step n+1 is equal to the state quantity at time step n, plus the product of half of the integration step and the sum of the right-hand side terms of the differential equations at time step n and time step n+1, wherein the right-hand side term represents the derivative term of the system dynamic equation, and the value of the derivative term is calculated by the affine state quantity of the corresponding time step.

[0014] Furthermore, the noise element decomposition is achieved in the following manner: a set of noise elements characterizing multi-source uncertainty is extracted from an affine expression of the synchronous generator power angle, and the power angle offset is equal to the sum of the linear combinations of each noise element and its corresponding influence coefficient, wherein the coefficient quantitatively reflects the contribution of different uncertainty sources to the power angle dynamics.

[0015] Furthermore, the conversion method of the interval envelope is: converting the power angle in affine form into an interval form, the lower limit of the interval is the affine center value minus the sum of the absolute values ​​of all noise element coefficients, and the upper limit is the center value plus the sum of the absolute values ​​of all noise element coefficients; extracting the maximum power angle difference interval at the end of the simulation, and calculating the transient power angle stability margin index according to the upper limit value of the interval, and the calculation formula is 180° minus the upper limit value and the percentage of 180°.

[0016] Furthermore, when alternately solving the affine differential-algebraic equation, the affine trigonometric function in the equation is linearized using the Chebyshev approximation method, which specifically includes the following steps: Expand the trigonometric functions into linear combinations of affine variables and determine the coefficients by minimizing the approximation error; Substitute the linearized expression into the differential-algebraic equation to reduce the conservatism of the nonlinear operation.

[0017] Furthermore, the alternating solution process includes: (a) Set the initial simulation time T = 0 and the integration step Δt; (b) Calculate the current step affine state quantity by implicit trapezoidal method; (c) Update simulation time T = T + Δt; (d) Repeat steps (b)-(c) until T reaches the preset simulation time.

[0018] And, an electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the program.

[0019] A non-transitory computer-readable storage medium stores a computer program, which implements the steps of the method described above when executed by a processor.

[0020] Compared with the prior art, the present invention and its preferred embodiments include at least the following beneficial effects: Improve the accuracy of dynamic characterization of multi-source uncertainty: By constructing an affine coupling mechanism for wind turbine-synchronous machine output, the simplified assumption of the dynamic coupling relationship of multi-source uncertainty in traditional models is overcome, and a refined characterization of the influence of multiple factors such as wind speed fluctuations and grid parameter changes is achieved; Enhance the physical authenticity of dynamic response: Establish a full-time dynamic equivalent admittance model based on low voltage ride-through parameters to avoid oversimplification of wind turbine control strategies in conventional methods and accurately characterize the dynamic regulation characteristics of active / reactive power during faults; Optimize the balance between computational efficiency and accuracy: adopt a hybrid solution strategy of implicit trapezoidal method and affine arithmetic to significantly reduce the computational complexity of high-dimensional uncertainty propagation while ensuring numerical stability, breaking through the "dimensionality curse" limitation of traditional proxy models; Achieve quantifiable analysis of stability margin: quantify the contribution of different uncertainty sources to power angle stability through noise element decomposition and interval envelope conversion technology, and construct an engineering evaluation index based on the maximum power angle difference boundary to solve the problem of conservative results or blurred boundaries of existing methods; Reduce conservative errors in nonlinear operations: Introduce the Chebyshev approximation method to linearize affine trigonometric functions, effectively reduce the over-conservatism of interval analysis, and improve the credibility of transient stability assessment results; Enhance the robustness of the simulation process: Through iterative solution and step-size adaptive loop logic design, the numerical convergence and result reliability of time-domain simulation in complex scenarios are ensured.

[0021] The present invention comprehensively solves the core problems such as model distortion, low efficiency, and fuzzy boundaries in the transient stability assessment of new - energy - highly - penetrated power grids, providing technical support with both theoretical rigor and engineering applicability for the safe operation of power systems. Brief Description of the Drawings

[0022] The following further details the present invention in conjunction with the drawings and specific embodiments: Figure 1 It is the flowchart of the transient power - angle stability affine quantization assessment for a wind - power integrated system considering uncertainties in the embodiment of the present invention. Specific Embodiments

[0023] To make the features and advantages of the present invention more obvious and understandable, specific embodiments are hereinafter given for detailed description as follows: It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs.

[0024] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0025] To achieve the transient power - angle stability affine quantization assessment for a wind - power integrated system considering uncertainties, the embodiment of the present invention first constructs an affine coupling mechanism for the uncertainties of the wind - turbine - synchronous - generator output, mathematically models the uncertainties of the output of traditional units caused by wind - power output fluctuations, and constructs a full - time - period dynamic model of the voltage - drop process in combination with the low - voltage ride - through parameters; secondly, an affine differential - algebraic equation set is established to completely describe the dynamic behavior of the system with uncertainty factors; then, the numerical analysis of the affine differential - algebraic equation is realized through the trapezoidal integration method and the alternating solution strategy to accurately track the propagation law of uncertainty in the time domain; further, the perturbation source of the affine quantity of the synchronous - generator power angle is analyzed through the noise coefficient to quantitatively analyze the dynamic influence degree of wind - power fluctuations on the power - angle deviation; finally, the affine - form power angle is converted into an interval envelope, and an index for engineering - assessable transient stability margin is constructed through the upper and lower bounds of the trajectory. The method proposed by the present invention shows better calculation accuracy and efficiency compared with traditional methods while ensuring numerical stability, and significantly reduces the conservativeness of interval analysis.

[0026] The solution of the embodiment of the present invention is roughly divided into the following steps: (1) Construct an affine coupling mechanism for wind turbine-synchronous generator output uncertainty to achieve a refined characterization of the synchronous generator mechanical power by multi-source uncertainty factors; (2) A wind power affine model considering dynamic characteristics is constructed based on the low voltage ride-through parameters, and its power external characteristics are equivalent to the dynamic parallel-to-ground admittance; (3) Using the Ward equivalent technique, the remaining nodes except the synchronous generator nodes are shrunk to construct a mathematical model that characterizes the dynamic behavior of the wind power grid-connected system; (4) Combining the implicit trapezoidal method and affine arithmetic, the affine state quantity of the wind power grid-connected system is obtained by alternately solving the affine differential and algebraic equations; (5) Tracing the disturbance source of the synchronous generator power angle affine quantity, quantitatively analyzing the influence of different uncertainty factors on the power angle dynamics based on various noise coefficients, and establishing a quantitative mapping relationship between multi-source disturbance and power angle offset; (6) Convert the power angle affine quantity into interval form, obtain the power angle trajectory envelope, and evaluate the transient power angle stability margin.

[0027] The process of the affine quantitative evaluation method for transient power angle stability of wind power grid-connected system taking into account uncertainty proposed in the embodiment of the present invention is as follows: Figure 1 As shown: Input Parameters Step 1: Input grid structure parameters, synchronous unit parameters, and wind turbine dynamic characteristic parameters First, you need to input the parameters related to the grid structure, the parameters of the synchronous unit and the dynamic characteristic parameters of the wind turbine.

[0028] Model building Step 2: Construct the fan-synchronous machine output affine association model and the fan dynamic admittance model According to the input parameters, the output affine association model between the wind turbine and the synchronous machine and the dynamic admittance model of the wind turbine are constructed.

[0029] Step 3: Construct the affine differential-algebraic equations for low voltage ride-through of integrated generators and wind turbines Based on the above model, a set of affine differential-algebraic equations including the low voltage ride-through characteristics of generators and wind turbines is further constructed.

[0030] Initialization and simulation calculation Step 4: Set the fault type, location and removal time, and set the simulation time T=0 Set the fault type, location and clearing time, and initialize the simulation time to 0.

[0031] Step 5: Apply implicit trapezoidal integration method to solve affine differential equations The constructed affine differential equation is solved using the implicit trapezoidal integration method.

[0032] Step 6: Substitute the solution of the differential equation into the affine algebraic equation to solve the system state quantity Substitute the solution of the differential equation into the affine algebraic equation to solve the state quantity of the system.

[0033] Cycle judgment Step 7: Determine whether the simulation time has been reached Determine whether the current simulation has reached the preset simulation time.

[0034] If No (N): Update the simulation time T = T + Δt, and return to step 5 to continue the simulation calculation.

[0035] If yes (Y): proceed to the next step.

[0036] Results Analysis Step 8: Quantitatively analyze the influence of various uncertain factors on the synchronous machine power angle Various uncertain factors are quantitatively analyzed to determine their influence on the synchronous machine power angle.

[0037] Step 9: Obtain the synchronous generator power angle trajectory envelope and evaluate the transient power angle stability margin According to the analysis results, the power angle trajectory envelope of the synchronous generator set is obtained, and the stability margin of its transient power angle is evaluated.

[0038] The following is a detailed introduction to the embodiments of the present invention: 1 Affine correlation model of fan-synchronous machine output

[0039] (1) Affine modeling of wind turbine output during steady state Quantify the uncertainty of wind turbine output into affine form: (1) Where: is the affine center value of the fan output during steady state; ε i Noise element characterizing wind speed fluctuations; is the corresponding noise element coefficient.

[0040] (2) Affine coupling mechanism of wind turbine-synchronous machine output uncertainty The node injection power equation is established under the affine power flow framework: (2) Where: , is the affine output of the synchronous machine during steady state; P Li , Q Liis the load power; Y ij is the element in the i th row and j th column of the nodal admittance matrix; is the nodal affine voltage during the steady state.

[0041] By iteratively solving the above equations through the affine Newton - Raphson method, the affine expressions of the output of each synchronous machine are obtained: (3) In the formula: is the influence degree of the output uncertainty of the j wind turbine on the output of the i synchronous machine; is the new noise element and its coefficient generated by the affine operation.

[0042] The time - domain simulation uses the steady - state power flow state variables as the initial values for the transient stability calculation. Among them, the mechanical power of the synchronous machine , and remains unchanged during the transient power - angle stability calculation (the generator adopts the second - order model).

[0043] 2 Wind Turbine Control Strategy and Simulation Model

[0044] (1) Low - voltage ride - through characteristics of wind turbines When a short - circuit fault occurs in the wind power grid - connected system, if the terminal voltage of the wind turbine is lower than the threshold U in , the wind turbine will enter the low - voltage ride - through control mode; when the fault is cleared and the terminal voltage recovers to the threshold U out , the wind turbine will switch to the output recovery state. During the low - voltage ride - through period, in order to prevent the inverter from over - current, the wind turbine will control the active current to decrease rapidly. In order to prevent the voltage from being too low, the wind turbine will also control the reactive current to increase in a certain proportion according to the degree of voltage reduction. After the wind turbine completes a low - voltage ride - through, its output will recover to the operating state before the fault. The low - voltage ride - through mathematical model of the wind turbine is as follows: (4) In the formula: S w (t) represents the complex power of the wind turbine at t time; t 0 , t 1 , t 2 respectively represent the end time of the steady - state operation stage, the end time of the low - voltage ride - through stage, and the end time of the low - voltage ride - through recovery stage; , respectively represent t0 and t 1 The fan active power setting value during the period; , Respectively t 1 and t 2 The reactive power setting value of the fan during the period; for t 2 Reactive power decay time constant during the period; k p for t 2 Active power recovery speed during the period.

[0045] (2) Wind turbine dynamic grounding admittance model Assume that the injection power of the wind turbine is S w , the unity power factor control mode is adopted during the steady state. The power external characteristics of wind power are equivalent to the parallel grounding admittance model. According to the low voltage ride-through characteristics of the wind turbine in formula (4), its dynamic equivalent admittance can be derived as follows: (5) Where: “*” is the conjugation operator; , Respectively t The wind turbine equivalent admittance matrix and the voltage of the wind turbine access node at the moment.

[0046] In order to avoid excessive complexity of the model, the present invention proposes an affine dimensionality reduction strategy for the wind power model. During the transient stability study period, the output of the wind turbine is degraded to the affine center value, and the parallel-connected grounded admittance matrix is ​​simultaneously converted into deterministic parameters to achieve effective simplification of computational complexity.

[0047] 3 Affine model for time domain simulation of wind power grid-connected system

[0048] (1) Ward equivalence In transient stability analysis, a load model with static impedance characteristics is used to simplify the voltage-power coupling relationship of each node load into a linear admittance parameter model, that is, the electrical equivalence of the load is achieved through a constant grounding admittance matrix. The mathematical model of the load is as follows: (6) Where: P L , Q L are the active / reactive power of the load respectively; is the voltage of the load node during steady state; is the load equivalent grounding admittance.

[0049] The network equation of the wind power grid-connected system can be described as: (7) Where: is the synchronous generator self-admittance; is the mutual admittance between the synchronous generator node and the network node, is the mutual admittance between the network node and the synchronous generator node, and ; It is the node admittance matrix after incorporating the load equivalent admittance and the wind turbine dynamic admittance (only the self-admittance of the corresponding node needs to be corrected); is the terminal voltage of the synchronous generator, its amplitude remains constant during the transient period, and its phase angle is the generator affine power angle; is the affine voltage of the network node; Affine injection current for synchronous generator.

[0050] Simplify the network of equation (7) and perform Ward equivalent processing on the remaining nodes (network nodes) except the synchronous generator, and we can get: (8) (9) (2) Constructing a system of affine differential-algebraic equations For a containing n If we define a system with synchronous generators ; , then formula (8) can be rewritten as: (10) Where: is the affine injection current of the i-th synchronous generator; is the element in the i-th row and j-th column of the node admittance matrix, representing the mutual admittance between node i and node j; is the terminal potential of the jth synchronous generator, its amplitude remains constant during the transient period, and its phase angle is the affine power angle.

[0051] No. i Electromagnetic power of synchronous generators It can be expressed by the following formula: (11) Where: ; ; is the affine power angle of the synchronous generator.

[0052] The differential equation for transient stability of wind power grid-connected system can be expressed as: (12) Where: and Respectively i The inertia time constant, rotor angular velocity, damping coefficient and mechanical power of a synchronous generator. Affine power flow calculation can be performed during the steady state to obtain the affine quantity of the mechanical power of the synchronous generator.

[0053] Equations (11) and (12) constitute a set of affine differential-algebraic equations that describe the dynamic characteristics of the wind power grid-connected system.

[0054] 4 Solving affine differential-algebraic equations

[0055] Combining implicit trapezoidal and affine arithmetic, equations (11) and (12) can be rewritten as: (13) (14) (15) Among them, for real affine ,according to Convert affine numbers to intervals [ a , b ], whose affine trigonometric functions can be linearized by Chebyshev approximation get: (16) (17) Where: n ] is the first n Second value integral; Δ t is the numerical integration time step; the affine state quantity of the uncertainty time domain simulation of the wind power grid-connected system can be obtained by alternately solving the affine differential equation-algebraic equation composed of equations (13)-(15).

[0056] like Figure 1 As shown, in the simulation calculation of this embodiment, the fault type is set to a three-phase short circuit fault, the fault location is the fan connected to the bus, and the cut-off time is 0.1 seconds; the total simulation time is preset to 1 second, and the integral step length Δt=0.01 seconds. The affine differential-algebraic equation is iteratively solved by the implicit trapezoidal method, and the simulation time T=T+0.01 seconds is updated after each step length calculation is completed, until T≥1 second when the simulation is terminated and the result analysis stage is entered.

[0057] 5 Tracing and quantification of synchronous machine power angle disturbance

[0058] (1) Power angle affine noise element decomposition Extract the set of noise elements in the affine expression of the synchronous machine power angle: (18) Where: The uncertainty sources are wind power output fluctuations, output fluctuations of different synchronous machines, etc. The noise element The corresponding coefficient; is the affine center value of the power angle of the i-th synchronous generator at time t, representing the deterministic power angle trajectory when there is no wind power fluctuation.

[0059] (2) Quantifying the impact of uncertainty factors on power angle The influence of each noise element on the synchronous generator power angle is given by the following formula: (19).

[0060] 6 Transient power angle stability margin assessment

[0061] (1) Affine-interval transformation The power angle affine quantity is converted into t Convert to interval form: (20) Similarly, the affine angle difference Converted into interval numbers, we can get the power angle envelope trajectory: (twenty one) Where: i and j The synchronous machines are numbered. The present invention uses the power angle of the balancing machine as a reference to calculate the power angle difference of the remaining synchronous machines relative to the balancing machine.

[0062] (2) Transient power angle stability margin assessment The affine value of each synchronous machine power angle By time t Convert to interval form and calculate the relative power angle difference interval between two synchronous generators: (twenty two) Where: , For each unit i The lower and upper bounds of the power angle interval; Indicates the unit i and j The power angle difference range.

[0063] At the end of the simulation t end , extract the deviation of the maximum power angle difference interval: (twenty three) Where: , fort end The upper and lower bounds of the power angle difference interval at each moment.

[0064] Define the transient power angle stability margin index: (twenty four) like : Determine that the system has a high stability margin; :Determine that the system is in a critical stable state; if It is determined that the risk of system instability is significant.

[0065] Based on the same inventive concept, the present invention also provides a computer device, which includes: one or more processors, and a memory for storing one or more computer programs; the program includes program instructions, and the processor is used to execute the program instructions stored in the memory. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is used to implement one or more instructions, specifically for loading and executing one or more instructions in a computer storage medium to implement the above method.

[0066] It should be further explained that, based on the same inventive concept, the present invention also provides a computer storage medium, on which a computer program is stored, and the computer program is executed by the processor to execute the above method. The storage medium can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electrical, magnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0067] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0068] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change or modify it into an equivalent embodiment with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention still belongs to the protection scope of the technical solution of the present invention.

[0069] The present invention is not limited to the above-mentioned optimal implementation mode. Anyone can derive other forms of affine quantitative evaluation methods for transient power angle stability of wind power grid-connected systems taking into account uncertainty under the inspiration of the present invention. All equivalent changes and modifications made within the scope of the patent application of the present invention should fall within the scope of the present invention.

Claims

1. An affine quantitative evaluation method for transient power angle stability of wind power grid-connected system taking into account uncertainty, characterized in that: The following steps are involved: An affine coupling model between wind power and synchronous generator output is constructed. Based on the affine power flow, the uncertainty effect of wind power output fluctuation on the synchronous generator mechanical power is quantified, and an affine expression including noise elements is generated. Based on the affine expression and the low voltage ride-through parameters of the wind turbine, a dynamic equivalent admittance model is established to convert the power external characteristics of the wind turbine into a dynamic parallel-connected ground admittance; The Ward equivalent technique is used to simplify the non-generator nodes in the wind power grid-connected system and obtain the simplified node admittance matrix. Based on the simplified node admittance matrix and dynamic equivalent admittance, an affine differential-algebraic equation system with uncertainty is constructed, and the affine state quantity of the synchronous generator power angle is obtained by alternating the implicit trapezoidal method and affine arithmetic. Performing noise element decomposition on the affine state quantity, analyzing the contribution of different uncertainty sources to the power angle offset, and establishing a quantitative mapping relationship between multi-source disturbance and power angle dynamics; The affine state quantity is converted into an interval envelope, and the transient power angle stability margin is evaluated according to the maximum power angle difference deviation.

2. The affine quantitative evaluation method for transient power angle stability of wind power grid-connected system taking into account uncertainty according to claim 1 is characterized by: The affine coupling model is constructed by defining the wind turbine output as the affine center value during the steady state, superimposing a linear combination of multiple noise elements representing random fluctuations in wind speed and their corresponding coefficients, wherein the coefficients are quantized by affine power flow to reflect the dynamic coupling strength of each noise element to the mechanical power of the synchronous machine.

3. The affine quantitative evaluation method for transient power angle stability of wind power grid-connected system taking uncertainty into account according to claim 1 is characterized by: The dynamic equivalent admittance model is derived as follows: based on the complex power control characteristics of the wind turbine during low voltage ride-through, a dynamic equivalent admittance model is established, and the wind turbine is equivalent to a dynamic parallel-to-ground admittance, and the value of the dynamic parallel-to-ground admittance is the ratio of the conjugate value of the wind turbine complex power at time t to the square of the wind turbine access node voltage.

4. The affine quantitative evaluation method for transient power angle stability of wind power grid-connected system taking uncertainty into account according to claim 1 is characterized by: The Ward equivalent technology specifically includes: modeling the load node as a constant admittance model, and generating an equivalent network equation that only retains the synchronous generator node by merging the admittance parameters of all non-generator nodes except the synchronous generator node.

5. The affine quantitative evaluation method for transient power angle stability of wind power grid-connected system taking uncertainty into account according to claim 1 is characterized by: The numerical integration process of the implicit trapezoidal method is: the affine state quantity at time step n+1 is equal to the state quantity at time step n, plus the product of half of the integration step and the sum of the right-hand side terms of the differential equations at time step n and time step n+1, wherein the right-hand side term represents the derivative term of the system dynamic equation, and the value of the derivative term is calculated by the affine state quantity at the corresponding time step.

6. The affine quantitative evaluation method for transient power angle stability of wind power grid-connected system taking into account uncertainty according to claim 1 is characterized by: The noise element decomposition is achieved in the following way: a set of noise elements characterizing multi-source uncertainty is extracted from an affine expression of the synchronous generator power angle, and the power angle offset is equal to the sum of the linear combinations of each noise element and its corresponding influence coefficient, wherein the coefficient quantitatively reflects the contribution of different uncertainty sources to the power angle dynamics.

7. The affine quantitative evaluation method for transient power angle stability of wind power grid-connected system taking uncertainty into account according to claim 1 is characterized by: The conversion method of the interval envelope is: converting the power angle in affine form into an interval form, the lower limit of the interval is the affine center value minus the sum of the absolute values ​​of all noise element coefficients, and the upper limit is the center value plus the sum of the absolute values ​​of all noise element coefficients; extracting the maximum power angle difference interval at the end of the simulation, and calculating the transient power angle stability margin index according to the upper limit value of the interval, and the calculation formula is 180° minus the upper limit value and the percentage of 180°.

8. The affine quantitative evaluation method for transient power angle stability of wind power grid-connected system taking uncertainty into account according to claim 1 is characterized by: When alternately solving the affine differential-algebraic equation, the affine trigonometric function in the equation is linearized using the Chebyshev approximation method, which specifically includes the following steps: Expand the trigonometric functions into linear combinations of affine variables and determine the coefficients by minimizing the approximation error; Substitute the linearized expression into the differential-algebraic equation to reduce the conservatism of the nonlinear operation.

9. The affine quantitative evaluation method for transient power angle stability of wind power grid-connected system taking uncertainty into account according to claim 1 is characterized by: The alternating solution process includes: (a) Set the initial simulation time T = 0 and the integration step Δt; (b) Calculate the current step affine state quantity by implicit trapezoidal method; (c) Update simulation time T = T + Δt; (d) Repeat steps (b)-(c) until T reaches the preset simulation time.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the methods of claims 1-9 when executing the program.

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