New energy grid-connected system operation mode optimization method and device based on oscillation stability margin, equipment and medium

Abstract

The invention relates to the technical field of new energy grid connection, in particular to a new energy grid-connected system operation mode optimization method and device based on oscillation stability margin, equipment and a medium, and the method comprises the steps: constructing a small signal state space model of a new energy grid-connected system; determining a dominant oscillation mode of the system and identifying a mode causing instability of the system, constructing a stability boundary based on a new energy output level and a short-circuit ratio, and calculating a system oscillation stability margin under the current operation condition; the system operation mode is adjusted, the short-circuit capacity of a new energy grid-connected point is improved, the system oscillation stability margin is improved, stable operation of the system is ensured, a means for evaluating the system operation state in real time is provided, the system operation mode is optimized based on the oscillation stability margin, the system broadband oscillation risk is reduced, and the system oscillation risk can be evaluated. In actual power grid operation, a new energy broadband oscillation risk early warning system can be combined to optimize a system operation mode online, and safe and stable operation of a new energy grid-connected system is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy grid-connected technology, and in particular to a method, device, equipment and medium for optimizing the operation mode of a new energy grid-connected system based on an oscillation stability margin. Background Art

[0002] With the transformation of the global energy structure, the proportion of clean energy continues to rise, especially new energy, mainly wind power and photovoltaic power generation, is developing rapidly around the world. By 2023, China's cumulative installed capacity of wind power has reached 441GW, and the cumulative installed capacity of photovoltaic power has reached 609GW, accounting for 36% of the country's total installed capacity of power generation. In Northwest, North China and Northeast China, a number of large-scale new energy power generation bases have been formed, and electricity is transmitted to other regions through ultra-high voltage direct current transmission technology. Due to the lack of support from conventional thermal power and hydropower and other synchronous generating units, these new energy bases have relatively weak grid strength and face stability problems such as transient voltage instability and broadband oscillation, which restricts the absorption and transmission capacity of new energy. With the further expansion of new energy installed capacity and the decline in the proportion of traditional synchronous units, the insufficient grid strength in areas where new energy is connected to the grid will become a universal problem.

[0003] At present, the grid-connected system of new energy is mainly realized by two methods: AC and flexible DC. Dynamic reactive compensation devices (such as SVG) are widely used to enhance the stability of the grid. However, due to the large-scale use of power electronic equipment with multi-time scale control characteristics in the grid-connected system, the stability of the system, especially the broadband oscillation problem, has become more prominent. Oscillation accidents related to the grid-connected system of new energy have occurred many times at home and abroad, affecting the safe operation of the power grid on a large scale. For example, in July 2015, an accident occurred in Hami, Xinjiang, China, where the torsional vibration protection of the thermal power unit was tripped due to wind power oscillation. The oscillation affected the 750kV and 500kV power grids, with a wide range of influence, reflecting the complex dynamic characteristics and serious oscillation problems in the system.

[0004] Although the existing optimization methods for the operation mode of renewable energy grid-connected systems can control the oscillation risk to a certain extent, they rely on the adjustment and addition of equipment, which is costly and complex to implement. This optimization method fails to fully utilize the original system structure and it is difficult to achieve efficient oscillation suppression and improve system stability without major changes to the equipment.

[0005] The information disclosed in this background technology section is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0006] The present invention provides a method, device, equipment and medium for optimizing the operation mode of a new energy grid-connected system based on oscillation stability margin, thereby effectively solving the problems in the background technology.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is: a method for optimizing the operation mode of a new energy grid-connected system based on oscillation stability margin, comprising the following steps:

[0008] S10: Construct a small signal state space model of the new energy grid-connected system based on the control structure and control parameters of the actual new energy grid-connected system;

[0009] S20: Based on the small signal state space model, the full-dimensional eigenvalue of the system under the current operating condition is calculated, and the dominant oscillation mode of the system is determined by using the eigenvalue analysis method, wherein the dominant oscillation mode refers to an oscillation mode close to the imaginary axis and having low damping, and the oscillation mode is prone to cause system instability. Based on the dominant oscillation mode, the mode causing system instability is identified;

[0010] S30: for the instability mode, construct a stability boundary based on the new energy output level and the short-circuit ratio, and calculate the system oscillation stability margin under the current operating condition;

[0011] S40: According to the oscillation stability margin, the system operation mode is adjusted to increase the short-circuit capacity at the renewable energy grid connection point, thereby increasing the system oscillation stability margin and ensuring stable operation of the system.

[0012] Further, in step S10, the small signal state space model includes a continuous space state model, including:

[0013]

[0014] In the formula, X s represents the continuous state vector, U xy and i xy Denote the input and output vectors respectively, A cs , B cs , C cs and D cs is a coefficient matrix that can be obtained by linearizing the differential equation or transfer function of the dynamic characteristics of the electrical component, and p represents the differential operator.

[0015] Furthermore, the continuous space state model is discretized by a specific integration rule to obtain a discrete state space model, wherein the discrete state space model is used to describe the behavior of the system by a set of discrete time equations, and the discrete state space model includes:

[0016]

[0017] In the formula, h s (t) represents the state vector in the current discrete state space, A ds , B ds , C ds and D ds is calculated from the coefficient matrix, Δt represents the discrete time step, t represents time, U xy and i xy denote the input and output vectors respectively.

[0018] Further, in step S20, based on the small signal state space model, the full-dimensional eigenvalue of the system under the current operating condition is calculated, the dominant oscillation mode of the system is determined by the eigenvalue analysis method, and the mode that may cause the system to become unstable is identified, and the steps include:

[0019] S21: Calculate the full-dimensional eigenvalue of the system and the corresponding left and right eigenvectors;

[0020] S22: Calculate the participation factor of the system oscillation mode according to the left and right eigenvectors, and determine the main links affecting the oscillation mode based on the participation factor;

[0021] S23: calculating the oscillation frequency and damping ratio of each oscillation mode according to the full-dimensional eigenvalue, and defining the oscillation mode with a small or negative damping ratio as the dominant oscillation mode of the system;

[0022] S24: Based on the dominant oscillation mode, adjusting the short-circuit ratio and the new energy output level of the system, and analyzing the impact of the change in the system operation mode on the dominant oscillation mode by observing the change in the root locus;

[0023] S25: When the root locus changes, if the conjugate characteristic root crosses the imaginary axis and enters the right half of the complex plane, the risk of oscillation instability in the system is identified;

[0024] S26: Based on the oscillation instability risk, determine a critical output level and a critical short-circuit ratio of the system, and identify the oscillation instability risk that occurs when the system is below the critical short-circuit ratio.

[0025] Further, in step S30, for the instability mode, a stability boundary based on the new energy output level and the short circuit ratio is constructed, and the step of constructing the stability boundary includes:

[0026] S31: Calculate the characteristic value corresponding to the system instability mode under the current output;

[0027] S32: Based on the characteristic value, by adjusting the short-circuit ratio of the grid connection point of the new energy station, searching and calculating the critical short-circuit ratio at the current output level;

[0028] S33: Based on the critical short-circuit ratio, gradually increase the output level of the new energy station, and calculate the critical short-circuit ratio of the system at the corresponding output level;

[0029] S34: According to the critical short-circuit ratio of the system at the corresponding output level and the output level of the corresponding new energy station, the critical stable operating point of each system is calibrated, and the stable boundary is drawn in the short-circuit ratio-new energy power space.

[0030] Furthermore, in step S40, the system operation mode is adjusted according to the oscillation stability margin, and the steps include:

[0031] S41: Calculating the oscillation stability margin of the current operating point of the system, wherein the oscillation stability margin includes the oscillation stability margin under normal working conditions and N-1 / N-2 fault working conditions;

[0032] S42: Determine an optimization strategy for the system operation mode based on the oscillation stability margin, the optimization strategy dynamically adjusting system parameters according to the oscillation stability margin of the system;

[0033] S43: Implement the optimization strategy, and recalculate the oscillation stability margin of the optimized system operating point, wherein the oscillation stability margin includes the oscillation stability margin under normal working conditions and N-1 / N-2 fault working conditions;

[0034] S44: Check whether the oscillation stability margin of the optimized system operating point meets the predetermined stable operation requirements under normal operating conditions and N-1 / N-2 fault conditions. If so, end the process; if not, return to step S42, adjust the optimization strategy and recalculate until the oscillation stability margin under normal operating conditions and N-1 / N-2 fault conditions meets the requirements.

[0035] Further, in step S41, the oscillation stability margin model of normal operating conditions includes:

[0036]

[0037] In the formula, OSM SCR It represents the oscillation stability margin under normal operating conditions, SCR represents the short-circuit ratio of the new energy station grid connection point, and CSCR represents the critical value corresponding to the current output level of new energy.

[0038] Further, in step S41, the oscillation stability margin under the N-1 / N-2 fault condition, the model includes:

[0039]

[0040] In the formula, OSM SCR(N-1 / N-2) Indicates the oscillation stability margin under N-1 / N-2 fault conditions, SCR N-1 / N-2It is the short-circuit ratio of the grid-connected points of new energy stations when the system operates in N-1 / N-2 mode. CSCR indicates the critical value corresponding to the current output level of new energy.

[0041] The present invention also includes a device for optimizing the operation mode of a new energy grid-connected system based on an oscillation stability margin, using the above method, including:

[0042] A small signal state space model building unit is used to build a small signal state space model of a new energy grid-connected system according to the control structure and control parameters of an actual new energy grid-connected system;

[0043] An eigenvalue calculation and oscillation mode analysis unit is used to calculate the full-dimensional eigenvalue of the system under the current operating condition based on the small signal state space model, and determine the dominant oscillation mode of the system using the eigenvalue analysis method, wherein the dominant oscillation mode refers to an oscillation mode close to the imaginary axis and with low damping, and the oscillation mode is prone to cause system instability. Based on the dominant oscillation mode, a mode that may cause system instability is identified;

[0044] A stability boundary construction and oscillation stability margin calculation unit, used to construct a stability boundary based on the new energy output level and the short-circuit ratio for the instability mode, and calculate the system oscillation stability margin under the current operating condition;

[0045] The system operation mode adjustment unit is used to adjust the system operation mode according to the oscillation stability margin, increase the short-circuit capacity at the renewable energy grid connection point, thereby increasing the system oscillation stability margin and ensuring stable system operation.

[0046] The present invention also includes a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method described above is implemented.

[0047] The present invention also includes a storage medium on which a computer program is stored. When the computer program is executed by a processor, the method described above is implemented.

[0048] The beneficial effects of the present invention are:

[0049] A stability margin index based on the oscillation stability boundary is proposed. The oscillation stability margin index defined in the present invention can evaluate the current state of the system and the oscillation risk after the expected N-1 / N-2 fault by monitoring the output level of the new energy station and the short-circuit ratio of the grid connection point.

[0050] A system operation mode optimization method based on stability margin is proposed. The system operation mode can be adjusted by optimizing the startup mode and output of synchronous machines, reconstructing the transmission network, optimizing the power flow distribution, etc., to ensure that the new energy grid connection points have sufficient short-circuit capacity and ensure stable system operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0052] Figure 1 A flowchart of a method for optimizing the operation mode of a new energy grid-connected system based on oscillation stability margin;

[0053] Figure 2 This is a schematic diagram of the new energy grid-connected system;

[0054] Figure 3 is the discrete time equivalent circuit diagram of the power element;

[0055] Figure 4 It is a schematic diagram of the system oscillation stability margin;

[0056] Figure 5 It is a specific flow chart of the method for optimizing the operation mode of the new energy grid-connected system based on the oscillation stability margin;

[0057] Figure 6 This is the structure diagram of system A1 in the implementation case;

[0058] Figure 7 This is the oscillation stability boundary diagram of the system in the implementation case;

[0059] Figure 8 This is the time domain simulation result diagram of the system in the implementation case;

[0060] Fig. 9 It is a structural schematic diagram of a device for optimizing the operation mode of a new energy grid-connected system based on oscillation stability margin;

[0061] Fig.10 A schematic diagram of the structure of a computer device. DETAILED DESCRIPTION

[0062] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0063] Embodiment 1:

[0064] like Figures 1 to 5 As shown: A method for optimizing the operation mode of a new energy grid-connected system based on oscillation stability margin, comprising the following steps:

[0065] S10: According to the control structure and control parameters of the actual renewable energy grid-connected system, a small signal state space model of the renewable energy grid-connected system is constructed; according to the system topology, control structure and control parameters in the research system, the continuous space state model of the power element is discretized to obtain a discrete state space model, and then the equivalent circuit model of a single element is obtained from the discrete state space model. Finally, according to the single discrete time equivalent circuit model of all components connected according to the research system topology, the complex target system is represented as a discrete time equivalent circuit network, and the state space model and equivalent circuit network of the renewable energy grid-connected system containing renewable energy stations, SVG, synchronous generators and other components are obtained;

[0066] S20: Based on the small signal state space model, the full-dimensional eigenvalue of the system under the current operating conditions is calculated, and the dominant oscillation mode of the system is determined by the eigenvalue analysis method, wherein the dominant oscillation mode refers to the oscillation mode close to the imaginary axis and with low damping, and the oscillation mode is easy to cause system instability. Based on the dominant oscillation mode, the mode that may cause system instability is identified; secondly, by changing the system operation mode, that is, the power grid strength and the new energy output level, the influence of the system operation mode on the system dominant oscillation mode and the instability scenario are determined;

[0067] S30: For the instability mode, a stability boundary based on the output level of new energy and the short-circuit ratio is constructed, and the system oscillation stability margin under the current operating conditions is calculated; on the basis of clarifying the influence of the system operation mode on the dominant oscillation mode of the system and the instability scenario, by changing the output level of new energy, the critical short-circuit ratio at the onshore centralized control station under each output level is calculated, thereby constructing the system oscillation stability boundary based on the output level of new energy and the short-circuit ratio, and on this basis, the oscillation stability margin of the system at the current operating point is calculated;

[0068] S40: According to the oscillation stability margin, the system operation mode is adjusted by optimizing the synchronous machine startup mode, system power flow distribution, transmission line reconstruction, and configuration of synchronous phase regulators, so as to increase the short-circuit capacity at the renewable energy grid connection point, thereby improving the system oscillation stability margin and ensuring the stable operation of the system. In addition, after the oscillation occurs, the oscillation can also be suppressed by increasing the number of synchronous machines in operation, increasing the number of transmission lines, etc.

[0069] The system operation mode is optimized based on the oscillation stability margin to reduce the system broadband oscillation risk. The system oscillation risk can be evaluated. In the actual power grid operation, the new energy broadband oscillation risk warning system can be combined to optimize the system operation mode online to ensure the safe and stable operation of the new energy grid-connected system.

[0070] Through eigenvalue analysis, the dominant oscillation modes and potential instability modes in the system can be accurately identified. Compared with traditional optimization methods, eigenvalue analysis provides a more scientific and accurate way to timely identify and prevent system instability and avoid large-scale oscillation accidents. This effectively solves the broadband oscillation problem mentioned in the background technology.

[0071] The system oscillation stability boundary is constructed based on the renewable energy output level and the short-circuit ratio, and the oscillation stability margin is defined, providing a means for real-time evaluation of the system operation status. This margin can dynamically reflect the stability of the system. Compared with the existing method that relies on hardware adjustment in the background technology, it is more flexible and low-cost. At the same time, the method can perform adaptive adjustments according to different renewable energy output levels and grid strengths to ensure that the system operates in a stable area.

[0072] By optimizing the system's operating mode (such as generator startup mode, power flow distribution and transmission line reconstruction, etc.), the short-circuit capacity of the renewable energy grid connection point can be improved without making large-scale changes to the system hardware. This method can improve the system's anti-oscillation capability without adding additional hardware equipment, solving the problems of high cost and complex implementation mentioned in the background technology. In addition, this method can also quickly respond to dynamic changes in the system and maintain stable operation of the power grid.

[0073] By calculating the oscillation stability margin of the system, an optimization solution with good adaptability is provided. This solution can adjust the system operation mode in real time according to the current operating conditions of the system to adapt to different renewable energy output levels and changes in the grid topology. This flexibility ensures that the renewable energy grid-connected system can cope with the problem of insufficient grid strength in different scenarios, and solves the stability problem of the new energy base in the background technology that lacks the support of traditional synchronous generator sets.

[0074] In the renewable energy grid-connected system, most common power components are included, among which the power supply components and reactive power compensation components include renewable energy generator sets, supporting SVG, synchronous generators, etc., while the transmission side equipment includes transformers, AC lines, etc., which collect electrical energy and send it to the main grid or load center, such as Figure 2 shown.

[0075] If the grid-connected bus voltage and the current flowing into the grid are regarded as input and output variables, any power element in the above power system can be represented by the following continuous space state model:

[0076] As a preference of the above embodiment, in step S10, the small signal state space model includes a continuous space state model, including:

[0077]

[0078] In the formula, Xs represents the continuous state vector, U xy and i xy Denote the input and output vectors respectively, A cs , B cs , C cs and D cs is a coefficient matrix that can be obtained by linearizing the differential equation or transfer function of the dynamic characteristics of the electrical component, and p represents the differential operator.

[0079] By introducing the continuous space state model, the dynamic behavior of each electrical component in the new energy grid-connected system can be accurately described. The model expresses the relationship between the input, state and output of the electrical component through linear equations, which can capture the complex dynamic characteristics of the system under small disturbances and provide an accurate data basis for the oscillation modal analysis of the system.

[0080] The continuous space state model is discretized by a specific integration rule to obtain a discrete state space model. The discrete state space model is used to describe the behavior of the system through a set of discrete time equations. It is a processing method of the small signal state space model. The discrete state space model includes:

[0081]

[0082] In the formula, h s (t) represents the state vector in the current discrete state space, which is of great significance in the subsequent model modal analysis. ds , B ds , C ds and D ds is calculated from the coefficient matrix, Δt represents the discrete time step, t represents time, U xy and i xy denote the input and output vectors respectively.

[0083] In addition, the second term in the discrete state space model can obtain the discrete time equivalent circuit of the element, such as Figure 3 As shown, it is equivalent to the Norton branch, where g s =-C ds is the equivalent conductance, D ds h s For an equivalent current source, the representation of the discrete-time equivalent circuit is the key to constructing the system state matrix.

[0084] By discretizing the continuous space state model to adapt the model to the digital control environment in modern power systems, the discrete state space model can be applied to digital simulation, online monitoring and control systems, and is more suitable for the actual operation of renewable energy grid-connected systems.

[0085] As a preferred embodiment of the above, in step S20, based on the small signal state space model, the full-dimensional eigenvalue of the system under the current operating condition is calculated, the dominant oscillation mode of the system is determined by the eigenvalue analysis method, and the mode that may cause system instability is identified, the steps include:

[0086] S21: Calculate the full-dimensional eigenvalue of the system and the corresponding left and right eigenvectors;

[0087] S22: Calculate the participation factor of the system oscillation mode according to the left and right eigenvectors, and determine the main links affecting the oscillation mode based on the participation factor;

[0088] S23: Calculate the oscillation frequency and damping ratio of each oscillation mode according to the full-dimensional eigenvalue, and define the oscillation mode with a small or negative damping ratio as the dominant oscillation mode of the system;

[0089] S24: Based on the dominant oscillation mode, adjust the system's short circuit ratio (SCR) and renewable energy output level, and analyze the impact of changes in system operation mode on the dominant oscillation mode by observing changes in the root locus;

[0090] S25: When the root locus changes, if the conjugate characteristic root crosses the imaginary axis and enters the right half of the complex plane, the risk of oscillation instability in the system is identified;

[0091] S26: Based on the risk of oscillation instability, determine the critical output level and critical short-circuit ratio of the system, and identify the risk of oscillation instability that occurs when the system is below the critical short-circuit ratio.

[0092] Based on the construction of the discrete state space model of new energy, the full-dimensional eigenvalue of the system and the corresponding left and right eigenvectors can be calculated under given system operating conditions, wherein the participation factor of the system oscillation mode can be calculated based on the left and right eigenvectors, and the main links affecting the oscillation mode can be determined based on the participation factor; the oscillation frequency and damping ratio of each oscillation mode of the system can be calculated based on the full-dimensional eigenvalue of the system, wherein the oscillation mode with relatively small or negative damping is considered to be the dominant oscillation mode of the system. On the basis of determining the dominant oscillation mode of the system, the system operation mode, i.e., the grid strength and the output level of new energy, can be changed. Here, the short-circuit ratio (SCR) commonly used in the industry is used as an indicator for evaluating the grid strength of the new energy access point, which is equal to the short-circuit capacity of the grid-connected point divided by the installed capacity of the grid-connected power electronic equipment.

[0093] By adjusting the short-circuit ratio (SCR) and the output level of renewable energy respectively, the change of the root locus can be observed. This change provides an important basis for analyzing the change in the system operation mode, especially when studying the influence law of the dominant oscillation mode. When the conjugate characteristic root crosses the imaginary axis and enters the right half of the complex plane, it means that the damping characteristics of the oscillation mode associated with the conjugate characteristic root have changed significantly, which is specifically manifested as the damping changing from a positive value to a negative value, which may lead to the occurrence of oscillation instability. Therefore, in-depth research on the impact of the short-circuit ratio and the output level of renewable energy on the system oscillation characteristics and timely identification of potential instability risks are crucial to ensure the stability and reliability of the power system.

[0094] In addition, according to existing domestic and foreign research results, new energy stations with grid-following control have critical output levels and critical short-circuit ratios when they are connected to the grid. That is, there is a corresponding critical short-circuit ratio at each output level. When the actual operating short-circuit ratio is lower than the critical short-circuit ratio, the system may experience oscillation and instability accidents.

[0095] By calculating the full-dimensional eigenvalue and the left and right eigenvectors and combining them with the participation factor, the dominant oscillation mode and influencing link in the system can be accurately determined. Compared with the traditional empirical method, this eigenvalue analysis method can more accurately find the main oscillation mode that causes system instability, providing a clear direction for subsequent optimization.

[0096] By adjusting the short-circuit ratio (SCR) and the output level of renewable energy, this method can monitor the system operating status in real time and observe the changes in the system root loci. The root locus analysis provides an intuitive representation of the system response as parameters change, and can effectively identify changes in system stability.

[0097] When the root locus shows that the characteristic root crosses the imaginary axis and enters the right half of the complex plane, the system can promptly identify the risk of oscillation instability. This mechanism provides an early warning function for the power grid system, and measures can be taken to avoid fault expansion before the system becomes unstable, thereby ensuring safe operation of the system.

[0098] Based on the risk of oscillation instability, the critical output level and critical short-circuit ratio of the system can be accurately determined, and the risk of instability of the system when it is lower than the critical short-circuit ratio can be identified, which helps provide key reference for system design and scheduling and ensures that the system operates within a stable range.

[0099] Through the above series of calculations and adjustments, this method can not only identify potential risks of oscillation instability, but also dynamically adjust operating parameters to improve the stability margin of the system, ensuring that the system maintains safe and stable operation under complex and changeable operating conditions.

[0100] By optimizing the system operation mode (such as adjusting the short-circuit ratio and the output level) instead of relying on hardware adjustments, the transformation cost can be effectively reduced. There is no need to make large-scale changes to equipment or install additional devices. Stability can be improved simply by optimizing system parameters.

[0101] On the basis of determining the typical instability scenarios of the renewable energy grid-connected system, the meaning of the system operating point is first defined: the short-circuit ratio of the grid-connected point under the current operation mode of the system and the corresponding point in the short-circuit ratio-new energy power space under the renewable energy output level / output combination.

[0102] In this embodiment, in step S30, for the instability mode, a stability boundary based on the new energy output level and the short circuit ratio is constructed, and the step of constructing the stability boundary includes:

[0103] S31: Calculate the characteristic value corresponding to the system instability mode under the current output;

[0104] S32: Based on the eigenvalue, by adjusting the short-circuit ratio of the grid connection point of the new energy station, search and calculate the critical short-circuit ratio at the current output level; that is, the short-circuit ratio of the grid connection point when the system instability oscillation mode enters the right half plane from the left half plane of the complex plane and the real part of the eigenvalue is exactly 0;

[0105] S33: Based on the critical short-circuit ratio, gradually increase the output level of the new energy station, and calculate the critical short-circuit ratio of the system under the corresponding output level; ensure that the interval between two adjacent output levels is not too large to ensure the smoothness of the stable boundary. At the same time, in order to reduce the calculation pressure, the output level interval should not be too small. It is recommended to take 0.1pu as the output interval;

[0106] S34: According to the critical short-circuit ratio of the system at the corresponding output level and the output level of the corresponding new energy station, the critical stable operation point of each system is calibrated, and the stability boundary is drawn in the short-circuit ratio-new energy power space. The new energy output level can be used as the y-axis and the short-circuit ratio of the grid connection point can be used as the x-axis. The critical stable operation points of each system can be marked in the two-dimensional short-circuit ratio-new energy power space, and then the points can be connected to obtain the stability boundary of the new energy grid-connected system.

[0107] According to the above steps, the core idea of ​​the method for constructing the oscillation stability boundary of the new energy grid-connected system can be obtained, that is, by obtaining the critical short-circuit ratio of the system at each output level, the oscillation stability boundary of the system can be obtained.

[0108] By calculating the eigenvalues ​​of the system at different output levels, the unstable oscillation mode of the system can be accurately identified. Eigenvalue analysis can help discover the potential instability mode of the system and help identify system stability risks in advance. Compared with the traditional rough estimation method, this technical solution ensures the accurate positioning of the oscillation instability point by accurately calculating the eigenvalues ​​of the system.

[0109] By adjusting the short-circuit ratio of the new energy station to calculate the critical short-circuit ratio, a means of flexibly adjusting the system operation mode is provided. As an important indicator for evaluating the strength of the power grid at the new energy grid-connected point, the short-circuit ratio can respond to power grid changes in a timely manner through dynamic adjustment, flexibly control the stability of the system, avoid the limitations of traditional systems that rely on fixed parameters, and make the system more adaptable and anti-interference.

[0110] By gradually increasing the output level of new energy stations, calculating and calibrating the critical short-circuit ratio at each output level, a system stability boundary based on new energy output and short-circuit ratio was constructed. The construction of this boundary can not only comprehensively and intuitively demonstrate the stability of the system under different working conditions, but also provide a scientific basis for system operation optimization. Compared with traditional methods, system operators can more accurately evaluate the stability of the system under different load conditions based on the stability boundary.

[0111] By adjusting system parameters (such as short-circuit ratio, output level, etc.) within the stability boundary to ensure stable system operation, the high cost of hardware changes or additional equipment installation is avoided. This software and algorithm-based optimization method can make full use of existing system resources, avoid large hardware investments, and reduce the cost of system upgrades and maintenance.

[0112] As a preferred embodiment of the above, in step S40, the system operation mode is adjusted according to the oscillation stability margin, such as Figure 5 As shown, the steps include:

[0113] S41: Calculate the oscillation stability margin of the current operating point of the system, where the oscillation stability margin includes the oscillation stability margin under normal working conditions and N-1 / N-2 fault working conditions;

[0114] S42: Based on the oscillation stability margin, determine the optimization strategy of the system operation mode. The optimization strategy dynamically adjusts the system parameters according to the oscillation stability margin of the system, such as the synchronous machine startup mode, reactive power compensation, etc.;

[0115] S43: Implement the optimization strategy and recalculate the oscillation stability margin of the optimized system operating point, where the oscillation stability margin includes the oscillation stability margin under normal working conditions and N-1 / N-2 fault working conditions;

[0116] Among them, N-1 / N-2 is a commonly used symbol in the power system, representing the number of all devices in the normal working state of the power system; N-1 / N-2 fault condition means that in the power system, assuming that one or two devices (such as generators, transformers or transmission lines) fail and are disconnected, by checking the oscillation stability margin under the N-1 / N-2 fault condition, the power system can better respond to emergencies and improve the reliability and stability of operation;

[0117] S44: Whether the oscillation stability margin of the system operating point after the core optimization meets the predetermined stable operation requirements under normal operating conditions and N-1 / N-2 fault conditions. If so, end the process; if not, return to step S42, adjust the optimization strategy and recalculate until the oscillation stability margin under normal operating conditions and N-1 / N-2 fault conditions meets the requirements.

[0118] A system operation mode optimization method based on stability margin is proposed. The system operation mode can be adjusted by optimizing the startup mode and output of synchronous machines, reconstructing the transmission network, optimizing the power flow distribution, etc., to ensure that the new energy grid connection points have sufficient short-circuit capacity and ensure stable system operation.

[0119] By calculating the oscillation stability margin under normal operating conditions and N-1 / N-2 fault conditions, the stability of the system under different operating conditions can be comprehensively evaluated. Whether in normal operating conditions or when single-point or multi-point faults occur, the stability of the system can be analyzed and evaluated.

[0120] According to the oscillation stability margin, the system can dynamically adjust the operating mode and parameters, such as the synchronous machine startup mode and reactive power compensation. According to the real-time monitoring of the system status, the system can flexibly respond to the current operating conditions and avoid stability problems caused by fixed settings.

[0121] The system is not only optimized under normal operating conditions, but also evaluates N-1 / N-2 fault conditions to ensure stability in the event of single-point or multi-point failures. This multi-condition evaluation mechanism reduces the possibility of system instability in the event of a failure. By simultaneously calculating the stability margin under normal conditions and N-1 / N-2 conditions, the system avoids focusing on instability judgments based on a single condition, which ensures that the system meets stability requirements under a variety of potential operating modes and avoids unnecessary risks caused by ignoring specific fault situations.

[0122] On the basis of constructing the system oscillation stability boundary, we can define the stability margin requirement for normal system operation, such as 20%, and the N-1 stability margin, such as 10%, by analogy with the static stability reserve coefficient of the power system. In practical applications, we can discuss its reasonable value range in detail.

[0123] 1) Definition of oscillation stability margin

[0124] Under the current operating conditions of the system, the short-circuit ratio SCR of the new energy station grid connection point minus the critical CSCR corresponding to the current output level of the new energy divided by the current SCR is defined as the oscillation stability margin based on the short-circuit ratio:

[0125] Wherein, in step S41, the oscillation stability margin model of normal working conditions includes:

[0126]

[0127] In the formula, OSM SCR It represents the oscillation stability margin under normal operating conditions, SCR represents the short-circuit ratio of the new energy station grid connection point, and CSCR represents the critical value corresponding to the current output level of new energy.

[0128] The oscillation stability margin model clarifies the quantification method of the system's stability margin under normal operating conditions, that is, it is calculated through the relationship between the system short circuit ratio (SCR) and the corresponding critical short circuit ratio (CSCR). This model can accurately describe the stability of the system under the current operating conditions and provide a quantitative basis for the safety assessment of the system operation.

[0129] 2) N-1 / N-2 oscillation stability margin

[0130] As a preference of the above embodiment, in step S41, the oscillation stability margin under the N-1 / N-2 fault condition, the model includes:

[0131] In order to reasonably evaluate the oscillation risk of the system under the N-1 / N-2 operation mode, on this basis, the system N-1 / N-2 stability margin index can also be defined, which is defined as the distance between the system operating point after N-1 / N-2 occurs under the current operating conditions of the system and the system stability boundary. The calculation formula is as follows:

[0132]

[0133] In the formula, OSM SCR(N-1 / N-2) Indicates the oscillation stability margin under N-1 / N-2 fault conditions, SCR N-1 / N-2 It is the short-circuit ratio of the new energy station grid connection point when the system is operated in N-1 / N-2 mode. CSCR represents the critical value corresponding to the current output level of new energy. Figure 4 shown.

[0134] By calculating the oscillation stability margin under the N-1 / N-2 working conditions, it is possible to timely warn of possible oscillation instability risks when a fault occurs or in a fault simulation. The model clearly describes whether the system's operating margin is sufficient in the event of a fault. If the oscillation stability margin is too low, it indicates that the system is at risk of instability.

[0135] When it is calculated that the oscillation stability margin of the system under the N-1 / N-2 working condition is insufficient, the system can dynamically adjust the operating mode according to the model results and take necessary emergency response measures to ensure that the system does not become unstable when a fault occurs. Through this model, it can be accurately determined when the emergency response needs to be initiated.

[0136] Based on the system oscillation stability margin, the short-circuit capacity at the renewable energy grid connection point can be increased by optimizing the synchronous machine startup mode, system power flow distribution, transmission line reconstruction, and configuration of synchronous phase regulators, thereby improving the system oscillation stability margin and ensuring that the system always maintains safe and stable operation. In addition, after the oscillation occurs, the oscillation can be suppressed by increasing the number of synchronous machines in operation, increasing the number of transmission lines, and other methods.

[0137] Embodiment 2:

[0138] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and examples.

[0139] The implementation case of the present invention provides an example of a single offshore wind farm connected to a 10-machine 39-node system via AC transmission:

[0140] 1. Example introduction: Figure 6 The example shown is modified from the IEEE 10-machine 39-bus system, in which a wind farm with an installed capacity of 300MW is transmitted to an onshore centralized control station via a step-up transformer and a submarine cable, and then connected to the bus 23 of the 10-machine 39-bus system via an overhead transmission line at a certain distance. At the onshore centralized control station, SVG is configured according to 20% of the installed capacity of renewable energy for dynamic reactive power compensation.

[0141] Introduction to initial working conditions: The WF output level of the wind farm is 0.1pu, and the short-circuit ratio of the onshore centralized control station is 2.89.

[0142] 2. Eigenvalue calculation: Under the given initial value of the power flow, the full-dimensional eigenvalue of the system is calculated. According to the calculation results, the damping ratio of each oscillation mode is determined. The one with the smaller damping ratio is the dominant oscillation mode of the system. Some of the calculation results are given here, as shown in Table 1.

[0143] Table 1 Dominant oscillation modes of the system

[0144]

[0145] Among them, the participation factor analysis can be performed on each oscillation mode, and it can be mainly divided into four categories according to the different participation factors: electrical resonance mode, wind power control mode, SVG control mode and synchronous low-frequency oscillation mode. On this basis, by changing the system operation mode, it can be found that under low short-circuit ratio and low output level, the sub-synchronous oscillation mode λ dominated by wind power current control 158，159 Oscillation instability may occur, so a stable boundary is subsequently constructed around this instability mode.

[0146] 3. Stability boundary construction and system stability margin calculation:

[0147] A comprehensive assessment of the oscillation risk of the AC grid-connected renewable energy system is conducted: First, the subsynchronous oscillation mode λ dominated by wind power current control that may cause instability is targeted. 158，159 Construct the system oscillation stability boundary based on short-circuit ratio and output level, such as Figure 7 shown.

[0148] Secondly, the stability margin of the basic operating condition of the calculation system can be defined according to the oscillation stability margin as shown in the first row of Table 2. At this time, the oscillation stability margin OSM SCR If it is less than 0, it means that the system may be oscillating and unstable.

[0149] Furthermore, considering that the short-circuit ratio of the centralized control station is 3.0 at the initial time, the wind power output is 0.4pu, and the wind farm's transmission overhead line is operated in a single loop, the calculated system oscillation stability margin is 12.3% at this time, which can maintain stable operation. At 5s, the wind power output is reduced to 0.1pu, and the oscillation stability margin is reduced to -7.67%. If it is less than 0, instability may occur. Combined with PSCAD / EMTDC, time domain simulation is performed as follows Figure 8 It can be seen that the system has subsynchronous oscillation instability at this time, which is consistent with the analysis results. In order to suppress the oscillation, the wind farm's transmission overhead line is adjusted from single-circuit operation to double-circuit operation, and the system oscillation stability margin is increased to 7.7%>0. The system oscillation converges and resumes stable operation. Combined with PSCAD / EMTDC, the time domain simulation is consistent with the analysis results.

[0150] Table 2 System operating point changes and their stability margins

[0151] Wind power output Centralized control station short circuit ratio Short circuit ratio of critical centralized control station <![CDATA[Oscillation Stability Margin OSM SCR > 0.1pu 2.89 3.40 -17.6％ 0.4pu 3.0 2.63 12.3％ 0.14pu 3.0 3.23 -7.67％ 0.14pu 3.5 3.23 7.7％

[0152] This verifies the effectiveness of the method for optimizing the operation mode of the new energy grid-connected system based on oscillation stability margin provided by the present invention.

[0153] The present invention also includes a device for optimizing the operation mode of a new energy grid-connected system based on an oscillation stability margin, using the method as described above, such as Fig. 9 As shown, including:

[0154] A small signal state space model building unit is used to build a small signal state space model of a new energy grid-connected system according to the control structure and control parameters of an actual new energy grid-connected system;

[0155] The eigenvalue calculation and oscillation mode analysis unit is used to calculate the full-dimensional eigenvalue of the system under the current operating condition based on the small signal state space model, and determine the dominant oscillation mode of the system using the eigenvalue analysis method, wherein the dominant oscillation mode refers to an oscillation mode close to the imaginary axis and with low damping, and the oscillation mode is easy to cause system instability. Based on the dominant oscillation mode, the mode that may cause system instability is identified;

[0156] The stability boundary construction and oscillation stability margin calculation unit is used to construct the stability boundary based on the output level of new energy and the short-circuit ratio for the instability mode, and calculate the system oscillation stability margin under the current operating conditions;

[0157] The system operation mode adjustment unit is used to adjust the system operation mode according to the oscillation stability margin, increase the short-circuit capacity at the renewable energy grid connection point, thereby increasing the system oscillation stability margin and ensuring stable system operation.

[0158] See also Fig.10 A computer device 400 provided in an embodiment of the present application includes: a processor 410 and a memory 420, wherein the memory 420 stores a computer program executable by the processor 410, and when the computer program is executed by the processor 410, the above method is executed.

[0159] The embodiment of the present application further provides a storage medium 430 on which a computer program is stored. When the computer program is run by the processor 410, the above method is executed.

[0160] Among them, the storage medium 430 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable red-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, disk or optical disk.

[0161] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. "Multiple" means two or more, unless otherwise clearly and specifically defined.

[0162] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0163] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0164] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0165] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0166] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0167] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0168] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A method for optimizing the operation mode of a new energy grid-connected system based on oscillation stability margin, characterized in that: The steps include: S10: Construct a small signal state space model of the new energy grid-connected system based on the control structure and control parameters of the actual new energy grid-connected system; S20: Based on the small signal state space model, the full-dimensional eigenvalue of the system under the current operating condition is calculated, and the dominant oscillation mode of the system is determined by using the eigenvalue analysis method, wherein the dominant oscillation mode refers to an oscillation mode close to the imaginary axis and having low damping, and the oscillation mode is prone to cause system instability. Based on the dominant oscillation mode, the mode causing system instability is identified; S30: for the instability mode, construct a stability boundary based on the new energy output level and the short-circuit ratio, and calculate the system oscillation stability margin under the current operating condition; S40: According to the oscillation stability margin, the system operation mode is adjusted to increase the short-circuit capacity at the renewable energy grid connection point, thereby increasing the system oscillation stability margin and ensuring stable operation of the system.

2. The method for optimizing the operation mode of a new energy grid-connected system based on oscillation stability margin according to claim 1 is characterized in that: In step S10, the small signal state space model includes a continuous space state model, including: In the formula, X s represents the continuous state vector, U xy and i xy Denote the input and output vectors respectively, A cs , B cs , C cs and D cs is a coefficient matrix that can be obtained by linearizing the differential equation or transfer function of the dynamic characteristics of the electrical component, and p represents the differential operator.

3. The method for optimizing the operation mode of a new energy grid-connected system based on oscillation stability margin according to claim 2 is characterized in that: The continuous space state model is discretized by a specific integration rule to obtain a discrete state space model, wherein the discrete state space model is used to describe the behavior of the system by a set of discrete time equations, and the discrete state space model includes: In the formula, h s (t) represents the state vector in the current discrete state space, A ds , B ds , C ds and D ds is calculated from the coefficient matrix, Δt represents the discrete time step, t represents time, U xy and i xy denote the input and output vectors respectively.

4. The method for optimizing the operation mode of a new energy grid-connected system based on oscillation stability margin according to claim 1 is characterized in that: In step S20, based on the small signal state space model, the full-dimensional eigenvalue of the system under the current operating condition is calculated, the dominant oscillation mode of the system is determined by the eigenvalue analysis method, and the mode that may cause system instability is identified. The steps include: S21: Calculate the full-dimensional eigenvalue of the system and the corresponding left and right eigenvectors; S22: Calculate the participation factor of the system oscillation mode according to the left and right eigenvectors, and determine the main links affecting the oscillation mode based on the participation factor; S23: calculating the oscillation frequency and damping ratio of each oscillation mode according to the full-dimensional eigenvalue, and defining the oscillation mode with a small or negative damping ratio as the dominant oscillation mode of the system; S24: Based on the dominant oscillation mode, adjusting the short-circuit ratio and the new energy output level of the system, and analyzing the impact of the change in the system operation mode on the dominant oscillation mode by observing the change in the root locus; S25: When the root locus changes, if the conjugate characteristic root crosses the imaginary axis and enters the right half of the complex plane, the risk of oscillation instability in the system is identified; S26: Based on the oscillation instability risk, determine a critical output level and a critical short-circuit ratio of the system, and identify the oscillation instability risk that occurs when the system is below the critical short-circuit ratio.

5. The method for optimizing the operation mode of a new energy grid-connected system based on oscillation stability margin according to claim 1, characterized in that: In step S30, for the instability mode, a stability boundary based on the new energy output level and the short circuit ratio is constructed, and the step of constructing the stability boundary includes: S31: Calculate the characteristic value corresponding to the system instability mode under the current output; S32: Based on the characteristic value, by adjusting the short-circuit ratio of the grid connection point of the new energy station, searching and calculating the critical short-circuit ratio at the current output level; S33: Based on the critical short-circuit ratio, gradually increase the output level of the new energy station, and calculate the critical short-circuit ratio of the system at the corresponding output level; S34: According to the critical short-circuit ratio of the system at the corresponding output level and the output level of the corresponding new energy station, the critical stable operating point of each system is calibrated, and the stable boundary is drawn in the short-circuit ratio-new energy power space.

6. The method for optimizing the operation mode of a new energy grid-connected system based on oscillation stability margin according to claim 1 is characterized in that: In step S40, the system operation mode is adjusted according to the oscillation stability margin, and the steps include: S41: Calculating the oscillation stability margin of the current operating point of the system, wherein the oscillation stability margin includes the oscillation stability margin under normal working conditions and N-1 / N-2 fault working conditions; S42: Determine an optimization strategy for the system operation mode based on the oscillation stability margin, the optimization strategy dynamically adjusting system parameters according to the oscillation stability margin of the system; S43: Implement the optimization strategy, and recalculate the oscillation stability margin of the optimized system operating point, wherein the oscillation stability margin includes the oscillation stability margin under normal working conditions and N-1 / N-2 fault working conditions; S44: Check whether the oscillation stability margin of the optimized system operating point meets the predetermined stable operation requirements under normal operating conditions and N-1 / N-2 fault conditions. If so, end the process; if not, return to step S42, adjust the optimization strategy and recalculate until the oscillation stability margin under normal operating conditions and N-1 / N-2 fault conditions meets the requirements.

7. The method for optimizing the operation mode of a new energy grid-connected system based on oscillation stability margin according to claim 6 is characterized in that: In step S41, the oscillation stability margin model of normal operating conditions includes: In the formula, OSM SCR It represents the oscillation stability margin under normal operating conditions, SCR represents the short-circuit ratio of the new energy station grid connection point, and CSCR represents the critical value corresponding to the current output level of new energy.

8. The method for optimizing the operation mode of a new energy grid-connected system based on oscillation stability margin according to claim 6 is characterized in that: In step S41, the oscillation stability margin under the N-1 / N-2 fault condition, the model includes: In the formula, OSM SCR(N-1 / N-2) Indicates the oscillation stability margin under N-1 / N-2 fault conditions, SCR N-1 / N-2 It is the short-circuit ratio of the grid-connected points of new energy stations when the system operates in N-1 / N-2 mode. CSCR indicates the critical value corresponding to the current output level of new energy.

9. A device for optimizing the operation mode of a new energy grid-connected system based on oscillation stability margin, characterized in that: Use of the method according to any one of claims 1 to 8, comprising: A small signal state space model building unit is used to build a small signal state space model of a new energy grid-connected system according to the control structure and control parameters of an actual new energy grid-connected system; An eigenvalue calculation and oscillation mode analysis unit, used to calculate the full-dimensional eigenvalue of the system under the current operating condition based on the small signal state space model, and determine the dominant oscillation mode of the system using the eigenvalue analysis method, wherein the dominant oscillation mode refers to an oscillation mode close to the imaginary axis and with low damping, and the oscillation mode is prone to cause system instability, and based on the dominant oscillation mode, identify the mode that may cause system instability; A stability boundary construction and oscillation stability margin calculation unit, used to construct a stability boundary based on the new energy output level and the short-circuit ratio for the instability mode, and calculate the system oscillation stability margin under the current operating condition; The system operation mode adjustment unit is used to adjust the system operation mode according to the oscillation stability margin, increase the short-circuit capacity at the renewable energy grid connection point, thereby increasing the system oscillation stability margin and ensuring stable system operation.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

11. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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