Method for analyzing oscillation stability boundary of wind-solar-storage system based on loop impedance matrix

Abstract

The application relates to the technical field of new energy grid-connected stability analysis, and discloses a wind-solar-storage system oscillation stability boundary analysis method based on a loop impedance matrix, which comprises the following steps: a broadband frequency sequence impedance model of a wind turbine, a photovoltaic unit, a network-constructed energy storage unit, a power collection line, a transformer and an external power grid is established; a loop impedance matrix is constructed according to the network topology of the wind-solar-storage system; frequency domain characteristic analysis is performed on the loop impedance matrix, a dominant oscillation mode of the system is identified, and a participation factor is calculated; the dominant oscillation mode damping ratio is taken as a stability quantitative index, the network-constructed energy storage output proportion, the power grid strength and the wind-solar output proportion are continuously scanned, the oscillation stability boundary is determined, and a stable operation region and an unstable operation region are divided. The application can represent the multi-branch coupling relationship of the wind-solar-storage system, realize dominant oscillation mode identification and continuous depiction of the stability boundary.

Description

Technical Field

[0001] This invention relates to the field of new energy grid connection stability analysis technology, specifically to a method for oscillation stability boundary analysis of wind-solar-storage systems based on loop impedance matrix. Background Technology

[0002] With the high proportion of new energy sources being integrated into the power system, power electronic power sources such as wind power and photovoltaics are gradually becoming important power sources in the power system. Compared with traditional synchronous generators, wind turbines and photovoltaic units are usually connected to the grid through power electronic converters, resulting in relatively lower system equivalent inertia and damping levels. Under weak grid conditions, the equivalent impedance of the grid increases, and the dynamic coupling between the new energy grid-connected system and the grid is enhanced, which can easily lead to stability problems such as subsynchronous oscillations and medium-to-high frequency oscillations, adversely affecting the safe and stable operation of wind-solar-storage grid-connected systems.

[0003] Most existing renewable energy units adopt grid-following control strategies, using phase-locked loops (PLLs) to synchronize with the grid voltage. This control method is well-suited for conventional grid conditions, but in weak grids or multi-source coupled operation, coupling effects may arise between PLL dynamics, current loop control, control delay, and grid impedance, introducing negative damping characteristics. To improve system stability, grid-connected energy storage is increasingly being introduced into wind-solar-storage systems, providing some voltage and frequency support. However, in systems where wind, solar, and grid-connected energy storage are jointly integrated, differences in control strategies, impedance characteristics, and dynamic responses among different grid-connected units lead to multi-frequency, multi-branch coupling characteristics in system oscillation modes, making it difficult to accurately determine the oscillation stability boundary.

[0004] Currently, common analytical methods for addressing the oscillation stability problem of renewable energy grid-connected systems include impedance analysis, eigenvalue analysis, and time-domain simulation. Impedance analysis typically uses the concept of port equivalent modeling, dividing the system into source-side and grid-side subsystems and combining them with stability criteria for analysis. Eigenvalue analysis usually requires establishing a system state-space model and obtaining oscillation mode information by solving eigenvalues ​​through linearization. Time-domain simulation verifies the system's disturbance response by constructing an electromagnetic transient model. While these methods can be used to some extent for stability analysis of renewable energy grid-connected systems, in multi-source heterogeneous systems composed of wind power, photovoltaics, and grid-connected energy storage, traditional single-port impedance analysis is insufficient to fully reflect the coupling relationships between multiple nodes and branches. The state-space modeling process is complex and requires high model integrity, while time-domain simulation cannot directly and continuously characterize the stability boundary under parameter changes. Therefore, existing methods still cannot meet the needs of oscillation mode identification, coupling path analysis, and continuous stability boundary assessment in wind, solar, and energy storage systems. Summary of the Invention

[0005] To address the problems of existing technologies, this invention provides a method for boundary analysis of oscillation stability in wind-solar-storage systems based on the loop impedance matrix. The technical solution is as follows: On the one hand, a method for boundary analysis of oscillation stability of wind-solar-storage systems based on loop impedance matrix is ​​provided, including the following steps: Wideband sequence impedance models of wind turbines, photovoltaic units, grid-connected energy storage units, collection lines, transformers and external power grids in the wind-solar-storage system are established to obtain frequency domain impedance models of each grid-connected unit and network branch. Based on the network topology of the wind-solar-storage system, the impedance of each grid-connected unit, the impedance of the collector line, the impedance of the transformer, and the impedance of the external power grid are taken as network branches. The relationship between the branches and the nodes is established, and the loop impedance matrix is ​​constructed based on the relationship. Frequency domain characteristic analysis is performed on the loop impedance matrix to identify the dominant oscillation mode of the wind-solar-storage system, and the participation factor corresponding to the dominant oscillation mode is calculated. Using the damping ratio of the dominant oscillation mode as a stability quantification index, at least one of the following is continuously scanned: the output ratio of grid-type energy storage, grid strength, and wind and solar power output, to obtain the damping ratio of the dominant oscillation mode under different operating conditions. Based on the relationship between the damping ratio of the dominant oscillation mode and the preset damping threshold, the oscillation stability boundary of the wind-solar-storage system within the operating condition space is determined, and the division results of the stable operating region and the unstable operating region are formed based on the oscillation stability boundary.

[0006] Furthermore, establishing broadband sequence impedance models for wind turbines, photovoltaic units, grid-type energy storage units, collector lines, transformers, and the external power grid within a wind-solar-storage system includes: For grid-connected wind turbines and grid-connected photovoltaic units, based on the harmonic linearization method, and taking into account the dynamics of the phase-locked loop, current loop control, feedforward decoupling and control delay, corresponding positive-sequence impedance analytical models and negative-sequence impedance analytical models are established respectively. For grid-type energy storage units, based on the virtual synchronous generator control architecture, a sequence impedance analytical model of the grid-type energy storage unit is established, taking into account the active-frequency control loop, reactive-voltage control loop, voltage and current dual closed-loop control, pulse width modulation control delay and coordinate transformation dynamics, and considering the frequency coupling effect caused by positive sequence voltage disturbance. The external power grid is equivalent to the Thevenin model, and the collector lines and transformers are equivalent to the series impedance model.

[0007] Furthermore, the wind-solar-storage system includes grid-connected wind power stations, grid-connected photovoltaic power stations, and grid-connected energy storage power stations. The grid-connected wind power stations, grid-connected photovoltaic power stations, and grid-connected energy storage power stations are modeled using the single-unit equivalent aggregation method, and are connected to the external power grid after being aggregated to the point of common coupling via step-up transformers and collector lines.

[0008] Furthermore, constructing the loop impedance matrix includes: The Norton equivalent model is used to represent grid-connected wind turbines and grid-connected photovoltaic units. The grid-type energy storage unit and the external power grid are represented using the Thevenin equivalent model; Based on the main circuit topology of the wind-solar-storage system, the system topology is defined, and the aggregate impedance of each unit, the external grid impedance, and the line impedance are regarded as network branches, and the relationship between branches and nodes is clarified. In the system topology, a set of linearly independent basic loops are selected, and a loop-branch correlation matrix is ​​established.

[0009] Furthermore, the loop-branch association matrix is ​​used to represent the association direction and relationship between network branches and basic loops, wherein different matrix elements are used to represent whether the network branches are positively associated, negatively associated, or not associated with the basic loops.

[0010] Furthermore, constructing the loop impedance matrix also includes: Construct a branch impedance diagonal matrix, wherein the diagonal elements of the branch impedance diagonal matrix correspond to the frequency domain impedance of each network branch. Matrix operations are performed based on the loop-branch correlation matrix, the branch impedance diagonal matrix, and the transpose of the loop-branch correlation matrix to obtain the loop impedance matrix, which is used to characterize the dynamic coupling relationship between wind turbines, photovoltaic units, grid-type energy storage units, collector lines, transformers, and the external power grid.

[0011] Furthermore, frequency domain characteristic analysis is performed on the loop impedance matrix to identify the dominant oscillation modes of the wind-solar-storage system, including: Within a preset wideband scanning range, calculate the eigenvalues ​​of the loop impedance matrix point by point. The potential oscillation mode is determined based on the changes in eigenvalues ​​at each frequency point; Record the frequency at which the amplitude of the eigenvalue corresponding to the potential oscillation mode reaches a local extremum as the candidate oscillation frequency; The system's complex frequency modes are obtained by solving for the zeros of the determinant of the loop impedance matrix near each candidate oscillation frequency. Within the frequency band of interest, the dominant oscillation mode is determined based on the real part of each complex frequency mode, and the damping ratio of the dominant oscillation mode is calculated based on the complex frequency mode.

[0012] Further, calculating the participation factor corresponding to the dominant oscillation mode includes: At the frequency of the dominant oscillation mode, calculate the left and right eigenvector matrices of the loop impedance matrix; For each loop in the wind-solar-storage system, the participation factor of each loop under the current dominant oscillation mode is calculated based on the left eigenvector matrix and the right eigenvector matrix; The participation factors of all loops are normalized. The loop with the largest normalized participation factor value is identified as the main excitation source and main response point of the dominant oscillation mode.

[0013] Furthermore, continuous scanning of at least one of the following: the proportion of grid-connected energy storage output, grid strength, and the proportion of wind and solar power output includes: At least one of the following factors was selected as the scanning target: the proportion of grid-connected energy storage output, grid strength, and the proportion of wind and solar power output. At each scan step, the wideband sequence impedance model corresponding to the current operating conditions is re-established, and the corresponding loop impedance matrix is ​​reconstructed. Frequency domain characteristic analysis is performed on the loop impedance matrix corresponding to the current operating conditions to obtain the damping ratio of the dominant oscillation mode and the corresponding participation factor under the current operating conditions.

[0014] Furthermore, determining the oscillation stability boundary of the wind-solar-storage system within the operating condition space includes: Solve for the set of operating points where the damping ratio of the dominant oscillation mode is equal to a preset damping threshold; The set of operating points is defined as the oscillation stability boundary of the wind-solar-storage system within the corresponding operating condition space. Based on the trend of the oscillation stability boundary changing with the scanned object, the influence relationship between the output ratio of grid-type energy storage, grid strength and wind and solar power output ratio on the oscillation stability of the wind-solar-storage system is obtained.

[0015] The beneficial effects of the technical solution provided by the embodiments of the present invention are as follows: This invention establishes a unified frequency domain impedance model for wind turbines, photovoltaic (PV) units, grid-connected energy storage units, collector lines, transformers, and the external power grid. It also constructs a loop impedance matrix based on the network topology of the wind-solar-storage system, enabling a unified representation of the dynamic coupling relationships between wind power, PV, grid-connected energy storage, and the external power grid in matrix form. Compared to analyses focusing only on a single port or operating condition, this invention better reflects the coupling relationships between multiple nodes and branches in a multi-source heterogeneous wind-solar-storage system, providing a more complete frequency domain analysis foundation for system oscillation mode analysis.

[0016] This invention identifies the dominant oscillation modes of wind-solar-storage systems by performing frequency domain characteristic analysis on the loop impedance matrix. Combined with participation factor analysis, it determines the main excitation sources and main response points of the corresponding dominant oscillation modes, thus helping to clarify the key links in oscillation generation and propagation. This method does not require establishing a complete state-space model; it only relies on the frequency domain impedance models of each grid-connected unit and network branch, and system topology information, to complete the identification of dominant oscillation modes and coupling path analysis, reducing the modeling difficulty of oscillation stability analysis in complex wind-solar-storage systems.

[0017] This invention uses the damping ratio of the dominant oscillation mode as a stability quantification index. It continuously scans operating conditions such as the proportion of grid-connected energy storage output, grid strength, and the proportion of wind and solar power output to obtain the oscillation stability boundary under different operating conditions and to define the stable and unstable operating regions. This provides a basis for assessing the oscillation stability of wind-solar-storage systems, configuring grid-connected energy storage, analyzing grid strength adaptability, and optimizing operating parameters, thereby improving the stable operation capability of wind-solar-storage grid-connected systems under weak grid and multi-source coupling conditions. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a structural diagram of a wind-solar-storage system according to an embodiment of the present invention; Figure 2 This is an equivalent model diagram of the wind-solar-storage grid-connected system according to an embodiment of the present invention; Figure 3 This is a graph showing the frequency-damping ratio variation of the dominant oscillation mode in a specific application example of the present invention; Figure 4 These are stability boundary diagrams under different SCR-α conditions in specific application examples of this invention; Figure 5 This is a diagram showing the change in active power at the PCC point of a wind-solar grid-connected system in a specific application example of the present invention. Figure 6 This is an FFT result diagram of the active power at the PCC point of a wind-solar grid-connected system in a specific application example of the present invention; Figure 7 This is a graph showing the change in active power at PCC points under different grid-type energy storage penetration rates in a specific application example of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0021] This embodiment provides a method for analyzing the oscillation stability boundary of a wind-solar-storage system based on a loop impedance matrix. It is applicable to grid-connected wind-solar-storage systems consisting of grid-connected wind turbines, grid-connected photovoltaic units, grid-connected energy storage units, and an external power grid. This embodiment first establishes a wide-sequence impedance model for each grid-connected unit and network branch. Then, it constructs a loop impedance matrix based on the network topology of the wind-solar-storage system. Through frequency domain characteristic analysis, participation factor analysis, and continuous parameter scanning, it obtains the dominant oscillation mode, main participating ports, and oscillation stability boundary, thereby achieving a quantitative analysis of the oscillation stability characteristics of the wind-solar-storage system. The method specifically includes the following steps.

[0022] Step 1: Establish a wideband sequence impedance model for wind and solar turbine units and grid-connected energy storage.

[0023] like Figure 1 The diagram shows the structure of the wind-solar-storage system. The grid-connected wind-solar power station and the grid-connected energy storage power station are modeled using the single-unit equivalent aggregation method, with each unit having a rated capacity of 1.5MW. Each equivalent power station is connected to the 35kV collection system via a step-up transformer and then aggregated to the Point of Common Coupling (PCC) via collection lines, subsequently connected to the 220kV grid via a 35kV / 220kV step-up substation. The external power grid is represented using the Thevenin equivalent model, and its strength is characterized by the SCR (Signal Capacity Ratio), expressed as Equation (1). The grid-connected energy storage penetration rate α is defined as the proportion of the actual active power output of the energy storage to the total power of the system, expressed as Equation (2).

[0024] (1) In the formula: U N The rated voltage of the power grid; S N To provide capacity for the system.

[0025] (2) In the formula: P PV P WT P ESS These are the active power outputs of photovoltaic units, wind turbine units, and grid-connected energy storage, respectively.

[0026] Figure 1 In the middle, L f1 L f2 L f3 These are the filter inductors for photovoltaic units, direct-drive wind turbines, and energy storage units, respectively; C f1 C f2 C f3These are the filter capacitors for the photovoltaic unit, the direct-drive wind turbine, and the energy storage unit, respectively; k T1 k T2 These are the transformer turns ratios of the equivalent power station and the transformer turns ratios of the step-up substation from the PCC point to the grid connection point, respectively; R L1 R L2 R L3 For the collector circuit resistance; L L1 L L2 L L3 For collector line inductance; Z g This is the equivalent impedance of the power grid.

[0027] For grid-connected converters such as wind and solar power, analytical models of positive and negative sequence impedances are established based on harmonic linearization methods, comprehensively considering PLL dynamics, current loop control, feedforward decoupling, and control delay. For grid-connected energy storage units, analytical models of sequence impedances are established based on the Virtual Synchronous Generator (VSG) control architecture, comprehensively considering its active-frequency control loop, reactive-voltage control loop, voltage-current dual closed-loop control, PWM control delay, and Park transformation dynamics, and taking into account the frequency coupling effect caused by positive sequence voltage disturbances. At the same time, the external power grid is equivalent to the Thevenin model, and the collector lines and transformers are equivalent to series impedance models, thus forming a unified impedance modeling framework for multi-source systems.

[0028] Step one yields the sequence impedance models of photovoltaic units, wind turbine units, grid-type energy storage units, external power grid equivalent impedance models, and collector lines and transformer impedance models. These impedance models together form the unified frequency domain impedance modeling basis for the wind-solar-storage system and serve as the data source for subsequent branch impedance matrix construction.

[0029] Step 2: Construct the loop impedance matrix of the wind-solar-storage system.

[0030] The impedance models of each power source unit established in Step 1 are unified into frequency domain impedance form. GFL wind power and photovoltaic units are represented using the Norton equivalent model, while GFM energy storage and the external power grid are represented using the Thevenin equivalent model. The equivalent model of the wind-solar-storage grid-connected system is as follows: Figure 2 As shown. Based on the actual main circuit topology of the wind-solar-storage system, perform the following sub-steps: (1) Define the system topology, regard the aggregate impedance of each unit, the grid impedance and the line impedance as network branches, and clarify the relationship between branches and nodes; (2) Select a set of linearly independent basic loops l1, l2, l3 in the topology diagram and establish a loop-branch correlation matrix B, where the element Bij∈{0,1,-1}, Bij=1 indicates that branch j is positively correlated with independent loop i, Bij=-1 indicates that it is negatively correlated, and Bij=0 indicates that there is no correlation. (3) Construct the branch impedance diagonal matrix Z0(s), where the diagonal elements are the frequency domain impedances of each branch; (4) Based on network topology theory, the loop impedance matrix Z is obtained through matrix operations. loop (s)=BZ0(s)B T .

[0031] Z loop (s) comprehensively describes the dynamic coupling relationship between different new energy subsystems and the external power grid, and its eigenvalue distribution directly reflects the potential oscillation mode of the system.

[0032] Figure 2 middle, I GFL_PV With Z PV These are the equivalent current source current and impedance of the GFL photovoltaic unit, respectively; I GFL_WT With Z WT These represent the equivalent current source current and impedance of the GFL wind turbine, respectively; V GFM_ESS With Z ESS These are the equivalent voltage source voltage and impedance of the GFM energy storage system, respectively; V g With Z g These are the equivalent voltage source voltage and impedance of the AC power grid, respectively; Z L1 Z L2 and Z L3 These are the impedances of the collector lines for each power station.

[0033] Step two yields a loop impedance matrix that characterizes the dynamic coupling relationship between wind turbines, photovoltaic units, grid-connected energy storage units, power collection lines, transformers, and the external power grid. This loop impedance matrix serves as input for subsequent frequency domain feature analysis, dominant oscillation mode identification, and participation factor calculation.

[0034] Step 3: Identify the dominant oscillation mode of the system and calculate the participation factor.

[0035] The frequency domain characteristic analysis of the loop impedance matrix constructed in step two includes the following two sub-steps: (1) Modal frequency and damping identification: Within the preset wideband scanning range, the eigenvalues ​​of the loop impedance matrix are calculated point by point. The mode with the minimum eigenvalue at each frequency point is defined as the potential oscillation mode at that frequency point, and the frequency at which the modal impedance amplitude reaches its peak is recorded as the candidate oscillation frequency. Near each candidate oscillation frequency, the zero-point equation of the determinant of the loop impedance matrix, det(Z), is solved. loop(s))=0, thus obtaining the complex frequency mode s of the system. k =σ k +jω k , where σ k For modal damping, ω k Let σ be the oscillation angular frequency; within the frequency band of interest, find the real part σ of all complex frequency modes. k The largest mode is defined as the dominant oscillation mode, and the damping ratio ζ of the dominant oscillation mode is calculated according to formula (3). k .

[0036] (3) (2) Participation factor analysis: At the frequency of the dominant oscillation mode, calculate the left eigenvector matrix L and the right eigenvector matrix T of the loop impedance matrix; for the i-th loop in the system, calculate its participation factor PF under the current dominant mode, and normalize the participation factors of all loops; the loop with the largest normalized participation factor value is determined as the main excitation source and response point of the dominant oscillation mode.

[0037] (4) In the formula, L k,i Let T be the element in the k-th row and i-th column of the left eigenvector matrix L. It reflects the resonant observability of the i-th loop in the k-th oscillation mode; i,k The right eigenvector matrix The element in the i-th row and k-th column. It reflects the resonant excitability of the i-th loop in the k-th oscillation mode. PF i,k Let be the participation factor of the i-th loop in the k-th mode.

[0038] Step 3 obtains the oscillation frequency, modal damping, damping ratio, and participation factor distribution of each loop for the dominant oscillation mode of the system, and determines the main excitation source and main response point of the corresponding dominant oscillation mode based on the participation factor distribution.

[0039] Step 4: Continuous scanning of the system oscillation stability boundary.

[0040] The dominant mode damping ratio ζ calculated in step three k As a quantitative indicator of stability, perform parameter scanning to construct the system stability boundary: (1) Select one or more key parameters as scanning variables, including at least one of α, SCR and wind and solar power output ratio.

[0041] (2) Repeat steps one to three at each scan step to calculate the dominant mode damping ratio ζ at the current running point. k And the corresponding participation factors.

[0042] (3) Solve the equation ζ k =ζ th , where ζ th The set of all operating points that satisfy this equation constitutes the oscillation stability boundary of the system within this parameter space, where the preset damping threshold is used.

[0043] (4) Based on the trend of the stability boundary with the scanning parameters, the influence of grid-type energy storage penetration rate and grid strength on system stability is quantitatively revealed.

[0044] Step four obtains the oscillation stability boundary under different grid-type energy storage penetration rates, different grid strengths, or different wind and solar power output ratios, and forms the division results of stable operation area and unstable operation area based on the oscillation stability boundary.

[0045] In summary, this embodiment establishes a unified frequency domain impedance model for wind turbines, photovoltaic units, grid-connected energy storage units, collector lines, transformers, and the external power grid. By constructing a loop impedance matrix based on the system topology, it achieves the identification of dominant oscillation modes, analysis of participating factors, and scanning of oscillation stability boundaries for the wind-solar-storage system. Through continuous analysis of operating parameters such as grid-connected energy storage penetration rate, grid strength, and the proportion of wind and solar power output, it obtains stability boundaries and stability region divisions under different operating conditions, providing a reference for oscillation stability assessment, grid-connected energy storage configuration, and optimization of operating parameters for the wind-solar-storage system.

[0046] Application Examples Build such a system in MATLAB / SIMULINK Figure 1 The electromagnetic transient simulation model of the wind-solar-storage system shown is analyzed using the proposed method, and the results are verified by simulation.

[0047] (1) The effect of the permeability of grid-type energy storage on the oscillation mode.

[0048] With a fixed wind power output of 75MW and a photovoltaic output of 75MW, an SCR of 1.3, and an energy storage penetration rate α gradually increasing from 0 to 0.6, the curves showing the dominant oscillation mode frequency and damping ratio as a function of α, calculated according to steps one through three, are as follows: Figure 3 As shown. Figure 3 This indicates that as α increases, the oscillation frequency decreases slightly from 78.92Hz to 77.36Hz, the damping ratio increases monotonically from -0.0016 to 0.080, and the stability boundary is crossed at α≈0.1228.

[0049] To further analyze the overall impact of α on the system's oscillation characteristics, the distribution of oscillation modes and corresponding participation factors under different α conditions were statistically analyzed, as shown in Table 1.

[0050] Table 1 Oscillation modes at different α

[0051] Table 1 shows that the system oscillation characteristics exhibit a non-monotonic change with increasing α, and new modes emerge under high penetration. When α=0, the system possesses a low-frequency, strongly damped mode at 23.88Hz dominated by the wind power loop and a supersynchronous unstable mode at 78.92Hz. When α=0.1, the real part of the supersynchronous mode decreases, but it remains unstable, and the energy storage loop participation factor is still relatively small. When α=0.4, the system has only one stable mode at 78.04Hz, at which point the energy storage loop participation factor rises to 0.031, but the wind power loop still dominates, indicating that the grid-type energy storage provides sufficient damping to suppress the original oscillations. When α increases to 0.6, the system exhibits two stable modes: a new strongly damped mode at 58.76Hz dominated by the energy storage loop and a stable mode at 77.36Hz still dominated by the wind power loop. This demonstrates that under high penetration conditions, grid-type energy storage not only suppresses the original oscillations but also participates in the formation of new dynamic characteristics.

[0052] (2) Stability boundary analysis under different α and SCR With 75MW each of fixed wind and solar power, parameter scanning was performed according to step four under different SCR conditions to extract the stability boundary corresponding to zero damping ratio. The results are as follows: Figure 4 As shown. Figure 4 This indicates that, under the condition 1 ≤ SCR < 1.33, the system possesses a minimum energy storage permeability α required to maintain stability. min , and α min The α value decreases nonlinearly with increasing SCR: when SCR=1.0 min When α ≈0.59, SCR=1.2 min When α is approximately 0.375 and SCR = 1.25, min When α is approximately 0.275 and SCR = 1.3, min ≈0.123; When SCR≥1.33, the system can remain stable under the condition of gridless energy storage access (α=0), and the damping of the grid-connected wind and solar turbine itself is sufficient to suppress oscillation.

[0053] (3) Time-domain simulation verification A nonlinear time-domain simulation model with the same parameters as described above was established in MATLAB / SIMULINK for verification.

[0054] Without the introduction of grid-type energy storage (α=0), when the SCR changes from 2 to 1.3, the time-domain response of the active power at the PCC point is as follows: Figure 5 As shown, the system exhibits continuous oscillation characteristics. Fast Fourier Transform analysis was performed on the active power signal during the steady-state oscillation phase (SCR=1.3), and the results are as follows. Figure 6As shown, there is a significant amplitude peak in the system spectrum around 79Hz, which is consistent with the oscillation mode frequency identified by frequency domain modal analysis.

[0055] Under the same grid strength (SCR=1.25) and wind and solar power output conditions (75MW each), comparative simulations were conducted with different α values. The simulation included a step change in energy storage output: initial output was 0, 45MW was added at 0.4s, increased to 57MW at 0.6s, and increased to 75MW at 0.8s. The time-domain response of active power at the PCC point is as follows: Figure 7 As shown.

[0056] Figure 7 This indicates that the system exhibits oscillations and divergence without a grid; the divergence rate slows down after 45MW is put into operation but remains unstable; the oscillations begin to decay after 57MW is put into operation, and the system enters a critical stable state (corresponding to the theoretical α). min (≈0.275); After 75MW was put into operation, the oscillations decayed rapidly, and the system returned to stable operation. This result is highly consistent with the theoretical stability boundary.

[0057] In summary, this embodiment verifies the oscillation stability boundary analysis method based on the loop impedance matrix proposed in this invention by constructing an electromagnetic transient simulation model of a wind-solar-storage system and combining it with comparative analysis under different grid-type energy storage penetration rates, grid short-circuit ratios, and wind and solar power output conditions. The verification results show that this method can identify the dominant oscillation modes in the wind-solar-storage system, determine the mode frequencies, damping characteristics, and main participating ports under different operating conditions, and continuously characterize the system's oscillation stability boundary based on the change in the damping ratio of the dominant mode. The simulation results are consistent with the stability boundary analysis results, indicating that the method described in this embodiment can provide a valid basis for assessing the oscillation stability of wind-solar-storage systems, configuring grid-type energy storage penetration rates, and optimizing operating parameters under weak grid conditions.

Claims

1. A method for boundary analysis of oscillation stability in wind-solar-storage systems based on loop impedance matrix, characterized in that, Includes the following steps: Wideband sequence impedance models of wind turbines, photovoltaic units, grid-connected energy storage units, collection lines, transformers and external power grids in the wind-solar-storage system are established to obtain frequency domain impedance models of each grid-connected unit and network branch. Based on the network topology of the wind-solar-storage system, the impedance of each grid-connected unit, the impedance of the collector line, the impedance of the transformer, and the impedance of the external power grid are taken as network branches. The relationship between the branches and the nodes is established, and the loop impedance matrix is ​​constructed based on the relationship. Frequency domain characteristic analysis is performed on the loop impedance matrix to identify the dominant oscillation mode of the wind-solar-storage system, and the participation factor corresponding to the dominant oscillation mode is calculated. Using the damping ratio of the dominant oscillation mode as a stability quantification index, at least one of the following is continuously scanned: the output ratio of grid-type energy storage, grid strength, and wind and solar power output, to obtain the damping ratio of the dominant oscillation mode under different operating conditions. Based on the relationship between the damping ratio of the dominant oscillation mode and the preset damping threshold, the oscillation stability boundary of the wind-solar-storage system within the operating condition space is determined, and the division results of the stable operating region and the unstable operating region are formed based on the oscillation stability boundary.

2. The method for boundary analysis of oscillation stability of wind-solar-storage systems based on loop impedance matrix according to claim 1, characterized in that, Establishing broadband sequence impedance models for wind turbines, photovoltaic units, grid-connected energy storage units, collector lines, transformers, and the external power grid within a wind-solar-storage system includes: For grid-connected wind turbines and grid-connected photovoltaic units, based on the harmonic linearization method, and taking into account the dynamics of the phase-locked loop, current loop control, feedforward decoupling and control delay, corresponding positive-sequence impedance analytical models and negative-sequence impedance analytical models are established respectively. For grid-type energy storage units, based on the virtual synchronous generator control architecture, a sequence impedance analytical model of the grid-type energy storage unit is established, taking into account the active-frequency control loop, reactive-voltage control loop, voltage and current dual closed-loop control, pulse width modulation control delay and coordinate transformation dynamics, and considering the frequency coupling effect caused by positive sequence voltage disturbance. The external power grid is equivalent to the Thevenin model, and the collector lines and transformers are equivalent to the series impedance model.

3. The method for boundary analysis of oscillation stability of wind-solar-storage systems based on loop impedance matrix according to claim 1, characterized in that, The wind-solar-storage system includes grid-connected wind power stations, grid-connected photovoltaic power stations, and grid-connected energy storage power stations. The grid-connected wind power stations, grid-connected photovoltaic power stations, and grid-connected energy storage power stations are modeled using the single-unit equivalent aggregation method, and are connected to the external power grid after being aggregated to the point of common coupling via step-up transformers and collector lines.

4. The method for oscillation stability boundary analysis of wind-solar-storage systems based on loop impedance matrix according to claim 1, characterized in that, Constructing the loop impedance matrix includes: The Norton equivalent model is used to represent grid-connected wind turbines and grid-connected photovoltaic units. The grid-type energy storage unit and the external power grid are represented using the Thevenin equivalent model; Based on the main circuit topology of the wind-solar-storage system, the system topology is defined, and the aggregate impedance of each unit, the external grid impedance, and the line impedance are regarded as network branches, and the relationship between branches and nodes is clarified. In the system topology, a set of linearly independent basic loops are selected, and a loop-branch correlation matrix is ​​established.

5. The method for oscillation stability boundary analysis of wind-solar-storage systems based on loop impedance matrix according to claim 4, characterized in that, The loop-branch association matrix is ​​used to represent the association direction and relationship between network branches and basic loops. Different matrix elements are used to represent whether the network branch is positively associated, negatively associated, or not associated with the basic loop.

6. The method for boundary analysis of oscillation stability of wind-solar-storage systems based on loop impedance matrix according to claim 5, characterized in that, Constructing the loop impedance matrix further includes: Construct a branch impedance diagonal matrix, wherein the diagonal elements of the branch impedance diagonal matrix correspond to the frequency domain impedance of each network branch. Matrix operations are performed based on the loop-branch correlation matrix, the branch impedance diagonal matrix, and the transpose of the loop-branch correlation matrix to obtain the loop impedance matrix, which is used to characterize the dynamic coupling relationship between wind turbines, photovoltaic units, grid-type energy storage units, collector lines, transformers, and the external power grid.

7. The method for boundary analysis of oscillation stability of wind-solar-storage systems based on loop impedance matrix according to claim 1, characterized in that, Frequency domain characteristic analysis of the loop impedance matrix identifies the dominant oscillation modes of the wind-solar-storage system, including: Within a preset wideband scanning range, calculate the eigenvalues ​​of the loop impedance matrix point by point. The potential oscillation mode is determined based on the changes in eigenvalues ​​at each frequency point; Record the frequency at which the amplitude of the eigenvalue corresponding to the potential oscillation mode reaches a local extremum as the candidate oscillation frequency; The system's complex frequency modes are obtained by solving for the zeros of the determinant of the loop impedance matrix near each candidate oscillation frequency. Within the frequency band of interest, the dominant oscillation mode is determined based on the real part of each complex frequency mode, and the damping ratio of the dominant oscillation mode is calculated based on the complex frequency mode.

8. The method for boundary analysis of oscillation stability of wind-solar-storage systems based on loop impedance matrix according to claim 1, characterized in that, The calculation of the participation factor corresponding to the dominant oscillation mode includes: At the frequency of the dominant oscillation mode, calculate the left and right eigenvector matrices of the loop impedance matrix; For each loop in the wind-solar-storage system, the participation factor of each loop under the current dominant oscillation mode is calculated based on the left eigenvector matrix and the right eigenvector matrix; The participation factors of all loops are normalized. The loop with the largest normalized participation factor value is identified as the main excitation source and main response point of the dominant oscillation mode.

9. The method for boundary analysis of oscillation stability of wind-solar-storage systems based on loop impedance matrix according to claim 1, characterized in that, Continuous scanning of at least one of the following: the proportion of grid-connected energy storage output, grid strength, and the proportion of wind and solar power output, including: At least one of the following factors was selected as the scanning target: the proportion of grid-connected energy storage output, grid strength, and the proportion of wind and solar power output. At each scan step, the wideband sequence impedance model corresponding to the current operating conditions is re-established, and the corresponding loop impedance matrix is ​​reconstructed. Frequency domain characteristic analysis is performed on the loop impedance matrix corresponding to the current operating conditions to obtain the damping ratio of the dominant oscillation mode and the corresponding participation factor under the current operating conditions.

10. The method for boundary analysis of oscillation stability of wind-solar-storage systems based on loop impedance matrix according to claim 1, characterized in that, Determining the oscillation stability boundary of a wind-solar-storage system within the operating condition space includes: Solve for the set of operating points where the damping ratio of the dominant oscillation mode is equal to a preset damping threshold; The set of operating points is defined as the oscillation stability boundary of the wind-solar-storage system within the corresponding operating condition space. Based on the trend of the oscillation stability boundary changing with the scanned object, the influence relationship between the output ratio of grid-type energy storage, grid strength and wind and solar power output ratio on the oscillation stability of the wind-solar-storage system is obtained.

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