Offshore wind power flexible direct current grid-connected system safety assessment method based on accessibility analysis

Abstract

The invention discloses a safety assessment method for an offshore wind power flexible direct current grid-connected system based on reachability analysis. The method comprises the following steps: constructing a high-dimensional nonlinear differential equation model and a nonlinear hybrid system model of the offshore wind power flexible direct current grid-connected system based on a Kron simplification method; constructing an uncertain variable model with a random change range by utilizing a sino polyhedron, and adding the uncertain variable model into the nonlinear hybrid system model as an uncertain input item; based on a reachability analysis theory, designing an improved reachability set calculation algorithm based on an adaptive time step optimization method, and dynamically balancing the calculation precision and the calculation efficiency of the reachability set by adjusting the time step; and an improved reachable set calculation algorithm is applied to calculate reachable set results of the offshore wind power flexible direct current grid-connected system under the influence of different operation conditions and uncertain factors. According to the method, the operation state of the offshore wind power flexible direct current grid-connected system can be subjected to safety evaluation according to the reachable set result, and important guidance is provided for guaranteeing safe and stable operation of the system.

Description

Technical Field

[0001] This invention relates to the technical field of power system security assessment, and in particular to a method for security assessment of offshore wind power connected to a flexible DC grid system based on accessibility analysis. Background Technology

[0002] Multi-terminal high-voltage direct current (HVDC) systems based on voltage source converters offer advantages such as independent power control, economic efficiency, and reliability, and are frequently used to construct large-capacity, long-distance power transmission systems. They have also become a key technology for the centralized transmission of large-scale offshore wind power over long distances. However, the mutual coupling among numerous power electronic devices and control components in offshore wind power systems connected to the grid via flexible HVDC makes the system's dynamic operation more complex. The inherent weak disturbance immunity and low inertia of offshore wind farms and multi-terminal HVDC systems result in insufficient disturbance support capabilities. Especially under the influence of large disturbances, the transient deviation of the unsupported system state can easily exceed safe limits. With the large-scale development of offshore wind power projects and the continuous increase in the transmission capacity of multi-terminal HVDC systems, the impact of offshore wind power grid connection via multi-terminal HVDC systems on the safe and stable operation of the power system is becoming increasingly significant. Therefore, it is necessary to effectively assess the safe and stable operation capabilities of offshore wind power grid-connected via flexible HVDC systems by analyzing their dynamic behavior.

[0003] In existing research, most studies employ time-domain simulation to test the operational dynamics of offshore wind power systems connected to the grid via flexible DC transmission under large disturbances. Furthermore, to account for the impact of uncertainties such as wind power disturbances, Monte Carlo sampling is used to generate random samples in probabilistic time-domain simulations and incorporate these random samples into the model for analysis. However, time-domain simulations require multiple simulations, resulting in high computational costs and long processing times. Moreover, they can only simulate operational conditions under limited conditions and cannot fully capture the operational dynamics of offshore wind power systems connected to the grid via flexible DC transmission under all possible operating conditions, thus exhibiting limitations.

[0004] Furthermore, current research on offshore wind power systems connected to the DC grid primarily focuses on small-disturbance analysis. The main idea is to obtain a linear model of the offshore wind power system connected to the DC grid near the system's operating point, and then use the eigenvalue method and impedance method to analyze the system's stability under small disturbances. Simultaneously, time-domain simulations are used to indirectly verify the system's stable operation under various disturbance conditions. However, small-signal analysis methods are based on inherent small-signal assumptions and rely on small-signal linearization modeling of the system at its static operating point, limiting their applicability to stable operation under small disturbances. When large-signal transient disturbances occur, the inherent nonlinear characteristics of the system cannot be ignored, rendering the aforementioned small-signal analysis methods inapplicable.

[0005] While existing studies have employed the Lyapunov function method for transient stability analysis of converters, wind turbines, and multi-terminal HVDC systems, this method relies on the existence of suitable Lyapunov functions. However, these functions are extremely difficult to find for complex nonlinear systems, lacking universality and applicability to the study of offshore wind power systems connected to the grid via flexible DC, which exhibit high-order dynamics. Therefore, it remains necessary to explore an analytical method that can fully analyze the operational characteristics of offshore wind power systems connected to the grid via flexible DC under large disturbances while preserving the complex nonlinear dynamics.

[0006] In summary, current research methods are insufficient in terms of theoretical depth, computational efficiency, and analytical comprehensiveness, and a safety assessment method for offshore wind power systems connected to the grid via flexible DC transmission is still lacking. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings and deficiencies of the prior art and provide a safety assessment method for offshore wind power grid-connected systems via flexible DC based on accessibility analysis. Based on the accessibility set results, this method quantitatively analyzes the operational dynamics and safety of offshore wind power grid-connected systems via flexible DC under different operating conditions and uncertainties, providing important guidance for revealing the operating mechanism of offshore wind power grid-connected systems via flexible DC and ensuring the safe and stable operation of the system.

[0008] To achieve the above objectives, the technical solution provided by this invention is: a safety assessment method for offshore wind power connected to a flexible DC grid system based on reachability analysis, comprising the following steps:

[0009] Step 1: Construct a high-dimensional nonlinear differential equation model and a nonlinear hybrid system model for an offshore wind power system connected to the grid via flexible DC transmission, based on the Kron simplification method;

[0010] Step 2: In order to capture the impact of uncertainties in the offshore wind power grid-connected system via flexible DC transmission, an uncertain variable model with a random variation range is constructed using the Chino polyhedron, and the established uncertain variable model is added as an uncertain input term to the nonlinear hybrid system model;

[0011] Step 3: Based on reachability analysis theory, an improved reachability set calculation algorithm based on adaptive time step optimization method is designed. This algorithm adaptively adjusts the time step according to the calculation error, dynamically balances the accuracy and efficiency of reachability set calculation, and improves the ability to characterize the transient steady-state dynamics of nonlinear hybrid system models.

[0012] Step 4: Apply the improved reachability set calculation algorithm to calculate the reachability set results of the offshore wind power grid-connected system under different operating conditions and uncertainties, and quantitatively evaluate the safety of the offshore wind power grid-connected system based on the reachability set results.

[0013] Furthermore, in step 1, the offshore wind power grid-connected system via flexible DC transmission comprises an offshore wind farm based on direct-drive wind turbines, a multi-terminal high-voltage DC transmission system based on voltage source converters, and a receiving-end power grid. The offshore wind power grid-connected system via flexible DC transmission includes N nodes and N… w One offshore wind farm, a multi-terminal high-voltage direct current transmission system including N v A converter station at the sending end, DC transmission lines and N s There are N receiving-end converter stations, and the receiving-end power grid includes N g A synchronous generator.

[0014] Furthermore, in step 1, in order to capture the complex nonlinear operating characteristics of the offshore wind power grid-connected system via flexible DC transmission, detailed nonlinear mathematical models of the offshore wind farm, the multi-terminal high-voltage DC transmission system, and the receiving-end power grid are established, and a detailed nonlinear differential-algebraic equation model of the offshore wind power grid-connected system via flexible DC transmission is formed. To eliminate the influence of algebraic equations, the Kron simplification method is used to construct a high-dimensional nonlinear differential equation model of the offshore wind power grid-connected system via flexible DC transmission. Finally, considering the interaction between the continuous dynamics of the system and discrete events, a nonlinear hybrid system model of the offshore wind power grid-connected system via flexible DC transmission is constructed.

[0015] Furthermore, the detailed nonlinear mathematical model of the offshore wind farm is constructed using the single-machine equivalent aggregation method, including a permanent magnet synchronous generator model, a converter control model, and an AC transmission line model.

[0016] The detailed nonlinear mathematical model of the multi-terminal high-voltage direct current transmission system consists of a sending-end converter station model, a receiving-end converter station model, a DC line model, and an AC line model.

[0017] The detailed nonlinear mathematical model of the receiving-end power grid consists of a synchronous generator model and a line power flow model;

[0018] By integrating the state variables and algebraic variables from the detailed nonlinear mathematical models of each component of the offshore wind power grid-connected system via flexible DC transmission, the vector matrix of the state variables of the offshore wind power grid-connected system via flexible DC transmission is defined as follows:

[0019] The vector matrix of algebraic variables is Where i = 1, 2, ..., N w j = 1, 2, ..., N v k = 1, 2, ..., N g n = 1, 2, ..., N; For the set of real numbers; ω wri and U wdci These represent the mechanical angular velocity and DC voltage of the i-th offshore wind farm, respectively; i wdi and i wqiLet w represent the d-axis and q-axis components of the current of the permanent magnet synchronous generator in the i-th offshore wind farm, respectively; 11i w 12i w 13i w 21i w 22i and w 23i These are the intermediate control variables for the inner and outer control loops of the converter in the i-th offshore wind farm, respectively; i gdi and i gqi These are the d-axis and q-axis components of the output current of the i-th offshore wind farm, respectively; u cdi and u cqi These are the d-axis and q-axis components of the capacitor voltage on the AC transmission line of the i-th offshore wind farm, respectively; i pdi and i pqi Let i represent the d-axis and q-axis components of the current on the AC transmission line of the i-th offshore wind farm, respectively; vdj and i vqj These represent the d-axis and q-axis components of the current on the AC line connected to the j-th sending-end converter station in a multi-terminal HVDC transmission system, respectively; u tdj and u tqj These represent the d-axis and q-axis components of the voltage on the AC line connected to the j-th sending-end converter station in a multi-terminal HVDC transmission system, respectively; 31j and w 32j w is the intermediate control variable in the control loop of the j-th sending-end converter station in a multi-terminal high-voltage direct current transmission system. 41 w 42 w 43 and w 44 For intermediate control variables in the control loop of the receiving-end converter station in a multi-terminal high-voltage direct current transmission system; u sd and u sq These represent the d-axis and q-axis components of the AC side voltage of the receiving-end converter station in a multi-terminal high-voltage direct current transmission system, respectively; i sd and i sq These are the d-axis and q-axis components of the AC current at the receiving-end converter station in a multi-terminal high-voltage direct current transmission system; I dcj and U dcj These represent the DC current and DC voltage at the j-th sending-end converter station in a multi-terminal high-voltage direct current transmission system, respectively; U vdc δ represents the DC voltage at the receiving-end converter station side in a multi-terminal high-voltage direct current transmission system. k and ω k E′ represents the power angle and angular velocity of the k-th synchronous generator, respectively. qk Let u be the internal electromotive force of the k-th synchronous generator; md and u mq These are the d-axis and q-axis components of the voltage at the node connecting the multi-terminal high-voltage direct current transmission system to the receiving-end power grid, respectively; V n and θn Let be the voltage and phase angle of the nth node in the receiving-end power grid, respectively; the detailed nonlinear differential-algebraic equation model of the offshore wind power system connected to the flexible DC grid is expressed as:

[0020]

[0021] In the formula, y(t) is the derivative of the vector matrix of state variables of the offshore wind power grid-connected system via flexible DC; y(t) is the vector matrix of algebraic variables; f(·) and g(·) are the sets of detailed nonlinear differential equations and algebraic equations of the offshore wind power grid-connected system via flexible DC, respectively; u(t) represents the set of input variables of the offshore wind power grid-connected system via flexible DC; t is the time variable.

[0022] Furthermore, considering the impact of the cumulative error caused by the interaction between algebraic equations and differential equations on the reachability set calculation, the Kron simplification method is adopted to construct a high-dimensional nonlinear differential equation model of the offshore wind power grid-connected system via flexible DC, which does not rely on algebraic equations. The process is as follows: First, the internal reactance of the synchronous generator is incorporated into the transformer impedance, and the equivalent admittance of the load is calculated, deriving N. Y The node admittance matrix Y is obtained; then, the Kron simplification method is used to process the node admittance matrix Y to obtain a simplified admittance matrix containing only synchronous generator nodes. Finally, based on the simplified admittance matrix, the electromagnetic power of the synchronous generator can be calculated without solving algebraic equations to obtain the node voltage and phase angle, and the voltage of the node connecting the multi-terminal HVDC transmission system to the receiving-end grid can be obtained according to Kirchhoff's current law. Through the above processing, algebraic variables can be completely eliminated, and the detailed nonlinear differential-algebraic equation model of offshore wind power connected to the flexible DC grid can be transformed into a high-dimensional nonlinear differential equation model.

[0023]

[0024] Furthermore, considering the interaction between discrete events such as continuous dynamics, parameter changes, and fault disturbances in the offshore wind power grid-connected system via flexible DC, a nonlinear hybrid system model of the offshore wind power grid-connected system via flexible DC is constructed using the hybrid automata method: Given a set of disturbances R = {R1, R2, ..., R...} consisting of m disturbance events. a ,R a+1 ,...,R m}, where R a For the a-th disturbance event, where a = 1, 2, ..., m, the operating state of offshore wind power connected to the grid via a flexible DC transmission system can be decomposed into m+1 modes, and the set of modes is represented as M = {M0, M1, ..., M}. a-1 M a ,...,M m}, where M0 is the initial mode, M a For the a-th mode, when the disturbance event R a When this occurs, offshore wind power connected to the grid via a flexible DC grid connection system will switch from Mode M. a-1 Switch to Mode M a The nonlinear hybrid system model H is constructed as follows:

[0025] H=(x 0 ,u 0 ,R,M,E,f,T H )

[0026] In the formula, x 0 and u 0 These represent the initial state set and input set corresponding to mode M0, respectively; E is the disturbance event R. a The triggered time-series events caused offshore wind power to switch to Mode M via a flexible DC grid connection system. a ;T H This is a transition function that describes the state transition of offshore wind power from one mode to another via a flexible DC grid-connected system.

[0027] Furthermore, in step 2, in order to capture the impact of uncertainties such as wind power fluctuations and measurement noise in the offshore wind power grid-connected system via flexible DC transmission, an uncertain variable model with a random variation range is constructed using a Chino polyhedron. This established uncertain variable model is then added as an uncertain input term to the nonlinear hybrid system model. The uncertain variable model is expressed as follows:

[0028]

[0029] In the formula, the counting variable o = 1, 2, ..., n z U w is an uncertain variable; 'a' is the center of the Chino polyhedron, used to represent the magnitude of the uncertain variable; h o It is composed of the coefficient α o The scaled generator describes the range of variation of the uncertain variable, n. z The number of generators; by configuring the above-mentioned uncertain variable model, which can flexibly represent any range of uncertainty, in the nonlinear hybrid system model, it is beneficial to quantitatively assess its impact on the offshore wind power grid-connected system via flexible DC transmission.

[0030] Furthermore, in step 3, the reachability analysis theory can obtain all possible dynamic behaviors of the offshore wind power grid-connected system via flexible DC in a single calculation. By verifying whether the reachability set containing the trajectory of the offshore wind power grid-connected system via flexible DC exceeds the specified safety boundary, the safety verification of the operating status of the offshore wind power grid-connected system via flexible DC is realized. This is used to study the operating characteristics of the offshore wind power grid-connected system via flexible DC under different operating conditions and with the influence of uncertain factors.

[0031] When solving and analyzing the nonlinear hybrid system model of offshore wind power connected to the grid via flexible DC, the reachability analysis principle is used to calculate the reachable set under the current mode from the initial state during the period when there is no interference from discrete events. When a discrete event occurs, the obtained set is discretized and transformed to a new state space according to the nonlinear hybrid system model, and the reachable set under the new mode is recalculated.

[0032] When calculating the reachable set of a nonlinear hybrid system model, the computational error generated by Taylor expansion decreases as the time step decreases, while the computational error generated by set order reduction increases as the time step decreases. To balance the two types of computational errors generated by Taylor expansion and set order reduction to minimize the total computational error and address the problem that a fixed time step cannot accurately capture complex nonlinear dynamics, an adaptive time step optimization method is designed. This method keeps the reachable set computational error within an acceptable range while improving computational efficiency. The entire solution time range is divided into finite time intervals T, and the optimal time step Δt is determined. op Then, the interval T is divided into k op There are k subintervals. op =T / Δt op The size of the reachable set during the q-th iteration after a finite time interval T. Estimated as In the formula, S r S is the expansion factor introduced by set reduction. e This is an estimate of the scaling effect of the exponential term. The size of the initial reachable set. The magnitude of the abstract error during the q-th iteration; the magnitude of the abstract error at different time steps according to the reachability set computation rules. A superlinear relationship exists. The abstract error can be calculated by using a finite time interval T as the step size. The approximation is obtained by multiplying by a scaling factor; assuming the optimal time step Δt. op =μ γ T, where μ is the scaling factor and γ is the scaling order, then k op =μ -γ The magnitude of the abstract error can be expressed as Where ρ l This represents the scaling factor after scaling by l. Finally, the optimization objective for finding the optimal time step is transformed into finding the optimal scaling number γ. op The objective function is expressed as Optimal time step By solving optimization problems get;

[0033] After obtaining the optimal time step, based on the principle of reachability analysis, the reachable sets within the optimal time step, under different modes, and within the specified running time range are calculated respectively. Considering the difficulty of obtaining the exact reachable set of the nonlinear hybrid system model, an over-approximation method is used to obtain the predicted value of the reachable set within an acceptable error range: First, the abstract linear system after Taylor expansion is solved at time step Δt = Δt op Accessible set within Next, the union of the reachable sets within each time step is calculated, and the reachable set in the s-th mode is computed. Where t s and t s+1 These are the start and end times of the s-th mode, respectively. Finally, considering the dynamic transformation of the nonlinear hybrid system model under the influence of discrete events within a specified running time range, the final reachability set result is obtained by combining the reachability sets of each mode. Where t0 and t end These are the start and end times of the specified operating time range.

[0034] Furthermore, in step 4, based on the nonlinear hybrid system model of the offshore wind power grid-connected system via flexible DC, the improved reachability set calculation algorithm designed in step 3 is applied to calculate the reachability set of the offshore wind power grid-connected system under different operating conditions and uncertainties. Based on the reachability set results, the impact of different fault types and different degrees of wind power disturbances on the offshore wind power grid-connected system via flexible DC is quantitatively analyzed, and a safety assessment of the offshore wind power grid-connected system via flexible DC is conducted.

[0035] Furthermore, the operating conditions of the offshore wind power grid-connected system via flexible DC transmission are divided into normal operation, fault occurrence, and post-fault state. Time is used as the switching condition, and wind power disturbance and controller measurement noise are used as uncertainty factors. The reachable set under each operating condition is calculated to fully capture the range of changes in the operating trajectory of the offshore wind power grid-connected system via flexible DC transmission. Based on whether the obtained reachable set containing all possible operating trajectories oscillates and whether it exceeds the allowable safe operating range, a safety assessment of the offshore wind power grid-connected system via flexible DC transmission is conducted. This provides important guidance for revealing the operating mechanism of the offshore wind power grid-connected system via flexible DC transmission under different operating conditions and ensuring the safe and stable operation of the system.

[0036] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0037] 1. This invention employs a detailed nonlinear mathematical model of an offshore wind power grid-connected system via flexible DC transmission, which fully captures the complex internal operating dynamics of the offshore wind farm, the multi-terminal high-voltage DC transmission system, and the receiving-end power grid, providing a more reliable basis for quantitative analysis of the safety of the offshore wind power grid-connected system under different operating conditions.

[0038] 2. This invention considers the impact of the cumulative error caused by the interaction between algebraic equations and differential equations on the reachability set calculation. It adopts the Kron simplification method to construct a high-dimensional nonlinear differential equation model of offshore wind power connected to the grid via flexible DC without relying on algebraic equations, which is more conducive to improving the accuracy and efficiency of reachability set calculation.

[0039] 3. This invention considers the impact of uncertainties in offshore wind power grid-connected systems via flexible DC transmission. It utilizes the Chino polyhedron to construct an uncertain variable model with a random variation range, and incorporates the established uncertain variable model as a disturbance input into the offshore wind power grid-connected system via flexible DC transmission. This captures the impact of uncertainties such as wind power disturbances and measurement noise on the operational performance of the offshore wind power grid-connected system via flexible DC transmission, providing a convenient and effective modeling and analysis method for quantitatively assessing the impact of uncertainties.

[0040] 4. Considering the limitations of fixed time step selection and inability to adapt to complex nonlinear dynamics, this invention designs an improved reachable set calculation algorithm based on an adaptive time step optimization method. The algorithm adaptively adjusts the time step according to the calculation error, dynamically balances the accuracy and efficiency of reachable set calculation, and improves the ability to characterize the transient steady-state dynamics of nonlinear hybrid systems.

[0041] 5. This invention utilizes an improved reachability set calculation algorithm to effectively predict the range of changes in the internal state of offshore wind power connected to the grid via flexible DC under different operating conditions and uncertainties. Based on whether the reachability set containing all possible operating trajectories exhibits oscillations and exceeds the allowable safe operating range, a safety assessment is conducted on the offshore wind power connected to the grid via flexible DC. This provides important guidance for revealing the operating mechanism of the offshore wind power connected to the grid via flexible DC under different operating conditions and ensuring the safe and stable operation of the system.

[0042] 6. The improved reachability set calculation algorithm designed in this invention can directly handle the complex characteristics of offshore wind power connected to the grid via flexible DC transmission, and can efficiently cope with the inherent high-dimensional nonlinearity, randomness and uncertainty characteristics of offshore wind power connected to the grid via flexible DC transmission. Attached Figure Description

[0043] Figure 1 This is a flowchart of the method of the present invention.

[0044] Figure 2 This is a structural diagram of an offshore wind power grid-connected system via flexible DC transmission, according to an embodiment of the present invention.

[0045] Figure 3 This is a flowchart illustrating the safety assessment process for an offshore wind power grid-connected system via flexible DC transmission, as described in an embodiment of the present invention. Detailed Implementation

[0046] The present invention will be further described in detail below with reference to the embodiments and accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0047] like Figure 1 As shown in the figure, this embodiment discloses a safety assessment method for offshore wind power connected to a flexible DC grid system based on reachability analysis, the specific details of which are as follows:

[0048] Step 1: Construct a high-dimensional nonlinear differential equation model and a nonlinear hybrid system model for an offshore wind power system connected to a flexible DC grid based on the Kron simplification method, as detailed below:

[0049] like Figure 2 As shown, the offshore wind power grid-connected system via flexible DC transmission consists of an offshore wind farm based on direct-drive wind turbines, a multi-terminal high-voltage direct current transmission system based on voltage source converters, and a receiving-end power grid. The offshore wind power grid-connected system via flexible DC transmission includes N nodes and N... w One offshore wind farm, a multi-terminal high-voltage direct current transmission system including N v A converter station at the sending end, DC transmission lines and N s There are N receiving-end converter stations, and the receiving-end power grid includes N g A synchronous generator was used. First, to capture the complex nonlinear operating characteristics of the offshore wind power grid-connected system via flexible DC transmission, detailed nonlinear mathematical models of the offshore wind farm, multi-terminal HVDC transmission system, and receiving-end power grid were established, forming a detailed nonlinear differential-algebraic equation model of the offshore wind power grid-connected system via flexible DC transmission. Second, to eliminate the influence of algebraic equations, the Kron simplification method was used to construct a high-dimensional nonlinear differential equation model of the offshore wind power grid-connected system via flexible DC transmission. Finally, considering the interaction between continuous dynamics and discrete events, a nonlinear hybrid system model of the offshore wind power grid-connected system via flexible DC transmission was constructed. The modeling process specifically includes the following steps:

[0050] 1) A detailed nonlinear mathematical model of an offshore wind farm is constructed using the single-machine equivalent aggregation method. Specifically, it includes a permanent magnet synchronous generator model, a controller model for the generator-side converter and the grid-side converter, and an AC transmission line model composed of an inductor current dynamic model and a capacitor voltage dynamic model.

[0051] 2) Construct a detailed nonlinear mathematical model of the multi-terminal high-voltage direct current transmission system, including the sending-end converter station model, the receiving-end converter station model, the DC line model, and the AC line model. The sending-end converter station and receiving-end converter station models are mainly represented by inner and outer loop controller models. The sending-end converter station adopts a constant AC voltage-frequency control mode, and the receiving-end converter station adopts a constant DC voltage-reactive power control mode.

[0052] 3) Construct a detailed nonlinear mathematical model of the receiving-end power grid, including a synchronous generator model and a line power flow model, wherein the synchronous generator adopts a third-order model;

[0053] 4) Integrate the detailed nonlinear mathematical models of each component of the offshore wind power grid-connected system via flexible DC transmission, and construct a detailed nonlinear differential-algebraic equation model of the offshore wind power grid-connected system via flexible DC transmission in the form of a system of differential-algebraic equations.

[0054] By integrating the state variables and algebraic variables from the detailed nonlinear mathematical models of each component of the offshore wind power grid-connected system via flexible DC transmission, the vector matrix of the state variables of the offshore wind power grid-connected system via flexible DC transmission is defined as follows:

[0055] The vector matrix of algebraic variables is Where i = 1, 2, ..., N w j = 1, 2, ..., N v k = 1, 2, ..., N g n = 1, 2, ..., N; For the set of real numbers; ω wri and U wdci These represent the mechanical angular velocity and DC voltage of the i-th offshore wind farm, respectively; i wdi and i wqi Let w represent the d-axis and q-axis components of the current of the permanent magnet synchronous generator in the i-th offshore wind farm, respectively; 11i w 12i w 13i w 21i w 22i and w 23i These are the intermediate control variables for the inner and outer control loops of the converter in the i-th offshore wind farm, respectively; i gdi and i gqi These are the d-axis and q-axis components of the output current of the i-th offshore wind farm, respectively; u cdi and u cqi These are the d-axis and q-axis components of the capacitor voltage on the AC transmission line of the i-th offshore wind farm, respectively; i pdi and i pqi Let i represent the d-axis and q-axis components of the current on the AC transmission line of the i-th offshore wind farm, respectively; vdj and i vqj These represent the d-axis and q-axis components of the current on the AC line connected to the j-th sending-end converter station in a multi-terminal HVDC transmission system, respectively; u tdj and u tqj These represent the d-axis and q-axis components of the voltage on the AC line connected to the j-th sending-end converter station in a multi-terminal HVDC transmission system, respectively; 31j and w 32j w is the intermediate control variable in the control loop of the j-th sending-end converter station in a multi-terminal high-voltage direct current transmission system. 41 w 42 w 43 and w44 For intermediate control variables in the control loop of the receiving-end converter station in a multi-terminal high-voltage direct current transmission system; u sd and u sq These represent the d-axis and q-axis components of the AC side voltage of the receiving-end converter station in a multi-terminal high-voltage direct current transmission system, respectively; i sd and i sq These are the d-axis and q-axis components of the AC current at the receiving-end converter station in a multi-terminal high-voltage direct current transmission system; I dcj and U dcj These represent the DC current and DC voltage at the j-th sending-end converter station in a multi-terminal high-voltage direct current transmission system, respectively; U vdc δ represents the DC voltage at the receiving-end converter station side in a multi-terminal high-voltage direct current transmission system. k and ω k E′ represents the power angle and angular velocity of the k-th synchronous generator, respectively. qk Let u be the internal electromotive force of the k-th synchronous generator; md and u mq These are the d-axis and q-axis components of the voltage at the node connecting the multi-terminal high-voltage direct current transmission system to the receiving-end power grid, respectively; V n and θ n Let be the voltage and phase angle of the nth node in the receiving-end power grid, respectively. The detailed nonlinear differential-algebraic equation model of an offshore wind power system connected to a flexible DC grid is expressed as:

[0056]

[0057] In the formula, y(t) is the derivative of the vector matrix of state variables of the offshore wind power system connected to the grid via flexible DC; y(t) is the vector matrix of algebraic variables; f(·) and g(·) are the sets of detailed nonlinear differential equations and algebraic equations of the offshore wind power system connected to the grid via flexible DC, respectively; u(t) represents the set of input variables of the offshore wind power system connected to the grid via flexible DC; t is the time variable.

[0058] Considering the impact of accumulated errors arising from the interaction between algebraic and differential equations on reachability set calculations, a Kron simplification method is employed to construct a high-dimensional nonlinear differential equation model of an offshore wind power system connected to a flexible DC grid, independent of algebraic equations. First, the internal reactance of the synchronous generator is incorporated into the transformer impedance, and the equivalent admittance of the load is calculated, deriving N... Y The node admittance matrix Y is obtained; then, the Kron simplification method is used to process the node admittance matrix Y to obtain a simplified admittance matrix containing only synchronous generator nodes. Finally, based on the simplified admittance matrix, the electromagnetic power of the synchronous generator can be calculated without solving algebraic equations to obtain the node voltages and phase angles, and the voltages of the nodes connecting the multi-terminal HVDC transmission system to the receiving-end grid can be obtained according to Kirchhoff's current law. Through the above processing, algebraic variables can be completely eliminated, and the detailed nonlinear differential-algebraic equation model of the offshore wind power grid-connected system via flexible DC transmission can be transformed into a high-dimensional nonlinear differential equation model.

[0059]

[0060] Considering the interactions between continuous dynamics and discrete events such as parameter variations and fault disturbances in an offshore wind power system connected to a flexible DC grid, a nonlinear hybrid system model of the offshore wind power system connected to a flexible DC grid is constructed using the hybrid automata method. Given a set of m disturbance events, R = {R1, R2, ..., R...} a ,R a+1 ,...,R m}, where R a (a = 1, 2, ..., m) represents the a-th disturbance event. The operating state of offshore wind power connected to the flexible DC grid can be decomposed into m+1 modes, and the set of modes is represented as M = {M0, M1, ..., M}. a-1 M a ,...,M m}, where M0 is the initial mode, M a For the a-th mode, when the disturbance event R a When this occurs, offshore wind power connected to the grid via a flexible DC grid connection system will switch from Mode M. a-1 Switch to Mode M a The nonlinear hybrid system model H can be constructed as:

[0061] H=(x 0 ,u 0 ,R,M,E,f,T H )

[0062] In the formula, x 0 and u 0 These represent the initial state set and input set corresponding to mode M0, respectively; E is the disturbance event R. a The triggered time-series events caused offshore wind power to switch to Mode M via a flexible DC grid connection system. a ;T H This is a transition function that describes the state transition of offshore wind power from one mode to another via a flexible DC grid-connected system.

[0063] Step 2: To capture the impact of uncertainties such as wind power fluctuations and measurement noise in offshore wind power grid-connected systems via flexible DC transmission, an uncertain variable model with a random variation range is constructed using a Chino polyhedron. This uncertain variable model is then added as an uncertain input term to the nonlinear hybrid system model. The specific implementation method is as follows:

[0064] The model of uncertain variables with a random range of variation constructed using the Chino polyhedron is expressed as follows:

[0065]

[0066] In the formula, the counting variable o = 1, 2, ..., n z U w is an uncertain variable; 'a' is the center of the Chino polyhedron, used to represent the magnitude of the uncertain variable; h o It is composed of the coefficient α o The scaled generator describes the range of variation of the uncertain variable, n. z The number of generators. By configuring the above-mentioned uncertain variable model, which can flexibly represent any range of uncertainty, in the nonlinear hybrid system model, it is beneficial to quantitatively assess its impact on offshore wind power connected to the grid via flexible DC transmission.

[0067] Step 3: Based on reachability analysis theory, an improved reachability set calculation algorithm based on an adaptive time step optimization method is designed. The time step is adaptively adjusted according to the calculation error to dynamically balance the accuracy and efficiency of reachability set calculation, thereby improving the ability to characterize the metastable dynamics of nonlinear hybrid system models. The improved reachability set calculation algorithm flow can be obtained through... Figure 3 The process is represented as follows, and the specific implementation method is as follows:

[0068] 1) When calculating the reachable set of a nonlinear hybrid system model, the computational error caused by Taylor expansion decreases as the time step decreases, while the computational error caused by set reduction increases as the time step decreases. To balance the two types of computational errors caused by Taylor expansion and set reduction to minimize the total computational error and address the problem that a fixed time step cannot accurately capture complex nonlinear dynamics, an adaptive time step optimization method is designed to keep the reachable set computational error within an acceptable range while improving computational efficiency. The entire solution time range is divided into finite time intervals T, and the optimal time step Δt is determined. op Afterwards, the interval T can be divided into k op There are k subintervals. op =T / Δt op The size of the reachable set during the q-th iteration after a finite time interval T. It can be estimated as In the formula Sr S is the expansion factor introduced by set reduction. e This is an estimate of the scaling effect of the exponential term. The size of the initial reachable set. Let be the magnitude of the abstract error during the q-th iteration. Based on the reachability set computation rules, the magnitude of the abstract error at different time steps... A superlinear relationship exists. The abstract error obtained by calculating with a finite time interval T as the step size can be used as a means to solve the problem. This is approximated by multiplying by a scaling factor. Assume the optimal time step Δt. op =μ γ T, where μ is the scaling factor and γ is the scaling order, then k op =μ -γ The magnitude of the abstract error can be expressed as... Where ρ l Let γ be the scaling factor after scaling by l. Finally, the optimization objective for finding the optimal time step can be transformed into finding the optimal scaling number γ. op The objective function is expressed as Optimal time step It can be achieved by solving optimization problems get.

[0069] 2) After obtaining the optimal time step, based on the principle of reachability analysis, the reachability sets of the nonlinear hybrid system model are calculated within the optimal time step, under different modes, and within the specified running time range. Considering the difficulty of obtaining the exact reachability set of the nonlinear hybrid system model, an over-approximation method is used to obtain the predicted value of the reachability set within an acceptable error range. First, with t... i Starting time, in t i+1 The time step for the termination time is Δt = Δt op =t i+1 -t i Internally, through Taylor expansion at the linearization point Obtaining an abstract linear system In the formula x L and u L These are matrices composed of the linearized points of the state variables and input variables, respectively. For an abstract linear system, the state variable vector, for The derivative value of , where A is the coefficient matrix of the abstract linear system. It is a perturbation term that includes linearization error and uncertain input. According to the superposition principle of abstract linear systems, the abstract linear system at t... i+1 Time-accessible set Composed of homogeneous and non-homogeneous solutions, denoted as In the formula For in t i The reachable set of time, u ψ t is the center value of the disturbance term. i+1 The reachable set of a time-invariant hybrid system model The reachable set of an abstract linear system The reachable set of the perturbation term Composition, represented as: The reachable set within time step Δt CH(·) is obtained by calculating the convex hull.

[0070] 3) Perform a union of the reachable sets within the time range of the current mode, and calculate the reachable set for the s-th mode. Where t s and t s+1 These are the start and end times of the s-th mode, respectively.

[0071] 4) Consider the dynamic transformation of the nonlinear hybrid system model under the influence of discrete events within a specified running time range, and obtain the final reachability set result by combining the reachability sets of each mode. Where t0 and t end These are the start and end times of the specified operating time range.

[0072] Step 4: Apply the improved reachability set calculation algorithm to calculate the reachability set results of the offshore wind power grid-connected system under different operating conditions and uncertainties. Based on the reachability set results, quantitatively assess the safety of the offshore wind power grid-connected system. The specific implementation method is as follows:

[0073] The operating conditions of offshore wind power connected to the grid via flexible DC are divided into normal operation, fault occurrence, and post-fault state. Time is used as the switching condition, and wind power disturbance and controller measurement noise are used as uncertainty factors. The reachable set under each operating condition is calculated to fully capture the range of changes in the operating trajectory of the internal state of the offshore wind power connected to the grid via flexible DC. Based on whether the obtained reachable set containing all possible operating trajectories shows oscillation and whether it exceeds the allowable safe operating range, a safety assessment of the offshore wind power connected to the grid via flexible DC is carried out. This provides important guidance for revealing the operating mechanism of the offshore wind power connected to the grid via flexible DC under different operating conditions and ensuring the safe and stable operation of the system.

[0074] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for safety assessment of offshore wind power through flexible direct current grid-connected system based on reachability analysis, characterized in that, The method comprises the following steps: Step 1: constructing a high-dimensional nonlinear differential equation model and a nonlinear hybrid system model of the offshore wind power through flexible direct grid system based on a Kron simplification method; Step 2: in order to capture the influence of uncertain factors in the offshore wind power through flexible direct grid system, a Zonotope is used to construct an uncertain variable model with a random variation range, and the established uncertain variable model is added to the nonlinear hybrid system model as an uncertain input item; Step 3: based on the reachability analysis theory, an improved reach set calculation algorithm based on an adaptive time step optimization method is designed, the time step is adaptively adjusted according to the calculation error, the calculation accuracy and efficiency of the reach set are dynamically balanced, and the characterization ability of the transient state dynamics of the nonlinear hybrid system model is improved; Step 4: the improved reach set calculation algorithm is applied to calculate the reach set results of the offshore wind power through flexible direct grid system under the influence of different operating conditions and uncertain factors, and the safety of the offshore wind power through flexible direct grid system is quantitatively evaluated according to the reach set results.

2. The offshore wind power system based on the security evaluation method of the reachability analysis and the parallel grid system through the flexible direct, according to claim 1, its characterized in that: In step 1, the offshore wind power through flexible grid-connected system is composed of offshore wind farms based on direct-drive wind turbine generators, multi-terminal high-voltage direct current transmission system based on voltage source converters and receiving end power grid, and the offshore wind power through flexible grid-connected system contains N nodes and N offshore wind farms, the multi-terminal high-voltage direct current transmission system contains N sending end converter stations, direct current transmission lines and N receiving end converter stations, and the receiving end power grid contains N synchronous generators. w v s g ​​​​ 3. The offshore wind power system based on the security evaluation method of the reachability analysis and the parallel grid system through the flexible direct, according to claim 2, its characterized in that: In step 1, in order to capture the complex nonlinear operating characteristics of the offshore wind power through flexible direct grid system, detailed nonlinear mathematical models of the offshore wind farm, the multi-terminal high-voltage direct current transmission system and the receiving end power grid are established, and the detailed nonlinear differential-algebraic equation model of the offshore wind power through flexible direct grid system is formed, in order to eliminate the influence of algebraic equations, the Kron simplification method is used to construct the high-dimensional nonlinear differential equation model of the offshore wind power through flexible direct grid system, finally, the interaction between the continuous dynamics and the discrete events of the system is considered, and the nonlinear hybrid system model of the offshore wind power through flexible direct grid system is constructed.

4. The offshore wind power system based on the security evaluation method of the reachability analysis and the parallel grid system through the flexible direct, according to claim 3, its characterized in that: The detailed nonlinear mathematical model of the offshore wind farm is constructed by using a single machine equivalent aggregation method, and comprises a permanent magnet synchronous generator model, a converter control model and an alternating current transmission line model; The detailed nonlinear mathematical model of the multi-terminal high-voltage direct current transmission system comprises a sending end converter station model, a receiving end converter station model, a direct current line model and an alternating current line model; The detailed nonlinear mathematical model of the receiving end power grid comprises a synchronous generator model and a line flow model; By integrating the state variables and algebraic variables in the detailed nonlinear mathematical models of each component of the offshore wind farm through VSC-HVDC grid integration system, the vector matrix of the state variables of the offshore wind farm through VSC-HVDC grid integration system is defined as , the vector matrix of the algebraic variables is where i = 1, 2, …, N w , j = 1, 2, …, N v , k = 1, 2, …, N g , n = 1, 2, …, N is a real set; ω wri and U wdci are the mechanical angular velocity and the DC voltage of the i th offshore wind farm, respectively; i wdi and i wqi are the d-axis and q-axis components of the current of the permanent magnet synchronous generator in the i th offshore wind farm, respectively; w 11i , w 12i , w 13i , w 21i , w 22i and w 23i are intermediate control variables of the inner and outer control loops of the converter in the i th offshore wind farm, respectively; i gdi and i gqi are the d-axis and q-axis components of the output current of the i th offshore wind farm; u cdi and u cqi are the d-axis and q-axis components of the capacitor voltage on the AC transmission line of the i th offshore wind farm; i pdi and i pqi are the d-axis and q-axis components of the current on the AC transmission line of the i th offshore wind farm; i vdj and i vqj represent the d-axis and q-axis components of the current on the AC line connected to the j th sending end converter station in the multi-terminal HVDC transmission system; u tdj and u tqj represent the d-axis and q-axis components of the voltage on the AC line connected to the j th sending end converter station in the multi-terminal HVDC transmission system; w 31j and w 32j are intermediate control variables of the control loop of the j th sending end converter station in the multi-terminal HVDC transmission system; w 41 , w 42 , w 43 and w 44 are intermediate control variables of the control loop of the receiving end converter station in the multi-terminal HVDC transmission system; u sd and u sq represent the d-axis and q-axis components of the AC side voltage of the receiving end converter station in the multi-terminal HVDC transmission system; i sd and i sq I d and I q are the d-axis and q-axis components of the AC side current of the receiving converter station in the multi-terminal HVDC power transmission system, respectively; dcj and U dcj I d and I q are the d-axis and q-axis components of the AC side current of the receiving converter station in the multi-terminal HVDC power transmission system, respectively; vdc U dc represents the DC voltage at the receiving converter station side in the multi-terminal HVDC power transmission system; δ k and ω k E k and E' k are the power angle and angular velocity of the kth synchronous generator, respectively; E' k qk u k and u' k are the internal electromotive force of the kth synchronous generator; u md and u mq V d and V q are the d-axis and q-axis components of the voltage at the node connected to the receiving grid in the multi-terminal HVDC power transmission system, respectively; V n and θ n V n and θ n are the voltage and phase angle of the nth node in the receiving grid, respectively; the detailed nonlinear differential-algebraic equation model of the offshore wind power through the flexible AC transmission system is represented as: In the formula, is the derivative of the state variable vector matrix x(t) of the offshore wind power through flexible grid-connected system; y(t) is the vector matrix of algebraic variables; f(·) and g(·) are respectively the detailed nonlinear differential equation set and the algebraic equation set of the offshore wind power through flexible grid-connected system; u(t) represents the input variable set of the offshore wind power through flexible grid-connected system; t is the time variable.

5. The offshore wind power system based on the security evaluation method of the reachability analysis and the parallel grid system through the flexible direct, according to claim 4, its characterized in that: Considering the influence of the cumulative error caused by the interaction between algebraic equations and differential equations on the reachable set calculation, the Kron reduction method is used to construct the high-dimensional nonlinear differential equation model of the offshore wind power through flexible grid system which is independent of algebraic equations. The process is as follows: First, the internal reactance of the synchronous generator is included in the transformer impedance, and the equivalent admittance of the load is calculated, and the N Y order node admittance matrix Y is derived; then, the Kron reduction method is used to process the node admittance matrix Y, and the simplified admittance matrix containing only the synchronous generator nodes is obtained Finally, according to the simplified admittance matrix, the electromagnetic power of the synchronous generator can be calculated without obtaining the node voltage and phase angle by solving the algebraic equation, and the voltage of the node connected with the multi-terminal high-voltage direct current transmission system and the receiving end power grid is obtained according to Kirchhoff's current law. Through the above processing, the algebraic variable can be completely eliminated, and the detailed nonlinear differential-algebraic equation model of the offshore wind power through flexible grid system can be converted into a high-dimensional nonlinear differential equation model:

6. The offshore wind power system based on the security evaluation method of the reachability analysis and the parallel grid system through the flexible direct, according to claim 5, its characterized in that: Considering the interactions between discrete events such as continuous dynamics, parameter changes, and fault disturbances in an offshore wind power grid-connected system via flexible DC transmission, a nonlinear hybrid system model of the offshore wind power grid-connected system via flexible DC transmission is constructed using the hybrid automata method: Given a set of disturbances R = {R1, R2, ..., R...} consisting of m disturbance events. a ,R a+1 ,...,R m }, where R a For the a-th disturbance event, where a = 1, 2, ..., m, the operating state of offshore wind power connected to the grid via a flexible DC transmission system can be decomposed into m+1 modes, and the set of modes is represented as M = {M0, M1, ..., M}. a-1 M a ,...,M m }, where M0 is the initial mode, M a For the a-th mode, when the disturbance event R a When this occurs, offshore wind power connected to the grid via a flexible DC grid connection system will switch from Mode M. a-1 Switch to Mode M a The nonlinear hybrid system model H is constructed as follows: H = (x 0 , u 0 , R, M, E, f, T H ) where x 0 and u 0 represent the initial state set and input set corresponding to mode M0, respectively; E is a time-ordered event triggered by a disturbance R a that causes the offshore wind farm through flexible AC transmission system to switch to mode M a ; T H is a transition function that describes the state of the offshore wind farm through flexible AC transmission system switching from one mode to another.

7. The offshore wind power system based on the security evaluation method of the reachability analysis and the parallel grid system through the flexible direct, according to claim 6, its characterized in that: In step 2, in order to capture the influence of uncertain factors such as wind power fluctuation and measurement noise in the offshore wind power through flexible direct grid system, a Zonotope is used to construct an uncertain variable model with a random variation range, and the established uncertain variable model is added to the nonlinear hybrid system model as an uncertain input item, and the uncertain variable model is represented as: where the counting variable o = 1, 2,..., n z , U w is an uncertain variable; a is the center of the Ginopoly, which is used to represent the amplitude of the uncertain variable; h o is the generating element scaled by the coefficient a o , which describes the variation range of the uncertain variable, n z is the number of generating elements; by configuring the above uncertain variable model capable of flexibly representing any uncertainty range in the nonlinear hybrid system model, it is beneficial to quantitatively evaluate its impact on the offshore wind power through the flexible and parallel grid system.

8. The offshore wind power system based on the security evaluation method of the reachability analysis and the parallel grid system through the flexible direct, according to claim 7, its characterized in that: In step 3, the reachability analysis theory can obtain all possible dynamic behaviors of the offshore wind power through flexible direct grid system in a single calculation, and the safety of the offshore wind power through flexible direct grid system is verified by verifying whether the reach set containing the trajectory of the offshore wind power through flexible direct grid system exceeds the specified safety boundary, and the operating characteristics of the offshore wind power through flexible direct grid system under different operating conditions and the influence of uncertain factors are studied; When solving and analyzing the nonlinear hybrid system model of offshore wind power through flexible grid-connected system, the reachability analysis principle is used to calculate the reachable set under the current mode from the initial state in the period without disturbance of discrete events. When the discrete event occurs, the obtained set is discretely converted to the new state space according to the nonlinear hybrid system model, and the reachable set under the new mode is recalculated. When calculating the reachable set of the nonlinear hybrid system model, the calculation error caused by Taylor expansion will decrease with the decrease of the time step, while the calculation error caused by set reduction will increase with the decrease of the time step. In order to balance the two kinds of calculation errors caused by Taylor expansion and set reduction respectively to minimize the total calculation error, solve the problem that fixed step length cannot accurately capture complex nonlinear dynamics, and design an adaptive time step optimization method to keep the reachable set calculation error within an acceptable range while improving the calculation efficiency. The entire solution time range is divided into finite time intervals T, and the optimal time step Δt is determined. op Then, the interval T is divided into k op There are k subintervals. op =T / Δt op The size of the reachable set during the q-th iteration after a finite time interval T. Estimated as In the formula, S r S is the expansion factor introduced by set reduction. e This is an estimate of the scaling effect of the exponential term. The size of the initial reachable set. The magnitude of the abstract error during the q-th iteration; the magnitude of the abstract error at different time steps according to the reachability set computation rules. A superlinear relationship exists. The abstract error can be calculated by using a finite time interval T as the step size. The approximation is obtained by multiplying by a scaling factor; assuming the optimal time step Δt. op =μ γ T, where μ is the scaling factor and γ is the scaling order, then k op =μ -γ The magnitude of the abstract error can be expressed as Where ρ l The scaling factor is calculated by scaling up to l. Finally, the optimization objective for finding the optimal time step is transformed into finding the optimal scaling number γ. op The objective function is expressed as Optimal time step By solving optimization problems get; After the optimal time step is obtained, the reachable set in the optimal time step, different modes and the specified running time range is calculated according to the principle of reachability analysis. Considering the difficulty of obtaining the accurate reachable set of the nonlinear hybrid system model, the approximate method is used to obtain the predicted value of the reachable set within the acceptable error range. Firstly, the reachable set of the abstract linear system after Taylor expansion is solved in the time step Δt = Δt op Then, the union set of the reachable set in each time step is obtained, and the reachable set in the s th mode is calculated Where t s and t s+1 are the start time and end time of the s th mode respectively; Finally, considering the dynamic transition of the nonlinear hybrid system model under the influence of discrete events within the specified running time range, the final reachable set result is obtained by combining the reachable set in each mode Where t0 and t end are the start time and end time of the specified running time range respectively.​ 9. The offshore wind power system based on the security evaluation method of the reachability analysis and the parallel grid system through the flexible direct, according to claim 8, its characterized in that: In step 4, based on the nonlinear hybrid system model of offshore wind power through flexible grid-connected system, the improved reachable set calculation algorithm designed in step 3 is applied to calculate the reachable set of offshore wind power through flexible grid-connected system under the influence of different operating conditions and uncertainty factors, and the influence of different fault types and different degrees of wind power disturbance on offshore wind power through flexible grid-connected system is quantitatively analyzed according to the reachable set results, and the safety of offshore wind power through flexible grid-connected system is evaluated.

10. The offshore wind power system based on the security evaluation method of the reachability analysis and the parallel grid system through the flexible direct, according to claim 9, its characterized in that: The operating conditions of the offshore wind power through flexible grid-connected system are divided into normal operation, fault occurrence and post-fault state, time is taken as the switching condition, wind power disturbance and controller measurement noise are taken as uncertainty factors, the reachable set under each operating condition is calculated, the change range of the operating trajectory of the internal state of the offshore wind power through flexible grid-connected system is fully captured, and according to whether the obtained reachable set containing all possible operating trajectories appears oscillation and whether it exceeds the allowed safe operating range, the safety of the offshore wind power through flexible grid-connected system is evaluated, which provides important guidance for revealing the operating mechanism of the offshore wind power through flexible grid-connected system under different operating conditions and ensuring the safe and stable operation of the system.

Images