Photovoltaic grid-connected inverter interaction identification method based on damping ratio characteristics

Abstract

The invention relates to the technical field of power system stability analysis, and particularly provides a photovoltaic grid-connected inverter interaction identification method based on damping ratio characteristics. The method comprises the following steps: establishing a power grid model comprising a photovoltaic inverter, and setting a power grid operation condition; carrying out load flow calculation according to the step 1; based on the step 2, selective characteristic value analysis configuration is carried out; according to the step 3, extracting a dimension reduction mode; the step 4 is utilized to analyze the participation factors, and small signal stability verification is carried out; and according to the step 5, calculating a reference index, and carrying out inverter interaction strength determination, and the method improves the planning and stable operation of the power grid.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system stability analysis, and particularly relates to a photovoltaic grid-connected inverter interaction identification method based on damping ratio characteristics, which is suitable for oscillation risk assessment of inverter clusters in a weak power grid environment. BACKGROUND

[0002] With the continuous increase of the penetration rate of fluctuating renewable energy such as photovoltaic and wind energy in the power system, the large-scale and distributed grid-connected is changing the characteristics of the power grid. As a key link in photovoltaic grid connection, the proportion of power electronic devices such as photovoltaic grid-connected inverters in the power grid is rising, and the resistive output characteristics and the fast and variable dynamic process and control link of the power electronic devices bring new severe challenges to the dynamic stability of the power system. The power grid presents the characteristics of low short-circuit ratio (SCR) and high grid impedance, and the dynamic behavior is more complex. The stability problems related to photovoltaic grid-connected inverters, especially the operation of photovoltaic grid-connected inverters in a weak AC power grid and the interaction between large-scale photovoltaic power station clusters or the power grid, have attracted widespread attention.

[0003] One of the core challenges of the stability problems related to photovoltaic grid-connected inverters is derived from the operation mechanism of the inverter relying on the phase-locked loop (PLL) and the AC power grid synchronization. When connecting to a weak AC power grid, the grid impedance increases, and complex interactions will occur between the control system of the photovoltaic grid-connected inverter, the PLL dynamics and the weak power grid. This instability may lead to low-frequency oscillation, power fluctuation and voltage fluctuation in the system, and in severe cases, trigger protection action to cause the inverter to be disconnected from the grid. At the same time, multiple photovoltaic grid-connected inverters are connected to the same power grid, and their respective fast control systems can produce complex dynamic coupling through the shared AC network impedance, thereby bringing the risk of synchronous oscillation of inverter clusters or resonance between inverters and the power grid at a specific frequency.

[0004] Due to the large-scale introduction of renewable energy, the instability risk related to the control of photovoltaic grid-connected inverters in the power system is increasing. The interaction related to the inverter has a significant impact on the overall stability, safety and reliability of the system, and effective identification of the interaction risk between inverters or between inverters and the power grid is crucial for the planning and stable operation of the power grid. The existing methods for identifying the interaction between converters have their own limitations, for example, the multi-infeed interaction factor (MIIF) is only applicable to LCC-HVDC systems, and the traditional short-circuit ratio (SCR) only reflects the overall strength of the power grid and cannot quantify the multi-inverter interaction risk. SUMMARY

[0005] Therefore, the application provides a photovoltaic grid-connected inverter interaction identification method based on damping ratio characteristics to improve the planning and stable operation of the power grid.

[0006] In a first aspect, the application provides a photovoltaic grid-connected inverter interaction identification method based on damping ratio characteristics, which comprises the following steps:

[0007] Step 1: establishing a power grid model containing photovoltaic inverters and setting power grid operating conditions;

[0008] Step 2: performing power flow calculation according to step 1;

[0009] Step 3: performing selective eigenvalue analysis configuration based on step 2;

[0010] Step 4: extracting dimensionality reduction modalities according to step 3;

[0011] Step 5: analyzing participation factors and performing small signal stability verification by using step 4;

[0012] Step 6: calculating reference indexes and performing inverter interaction intensity determination according to step 5.

[0013] Optionally, the setting of power grid operating conditions in step 1 comprises photovoltaic output level, inverter control mode and parameters, alternating current network strength SCR and load characteristics.

[0014] Optionally, step 3 comprises: using a selective analysis module of power system simulation software, only checking the inverter devices of the target photovoltaic cluster through a device filter, and selecting inverter-related control state variables in the state variables, including the phase / frequency state of the phase-locked loop (PLL), the d / q axis integral state of the current inner loop and the integral state of the power outer loop.

[0015] Optionally, step 4 comprises: performing reduced-order eigenvalue calculation according to the number N of inverters, so that the complete power system model is reduced to 3N orders only retaining the core state of the inverter.

[0016] Optionally, the analysis of participation factors in step 5 comprises:

[0017] Definition of participation factor to quantify the contribution degree of the kth inverter to the oscillation modalities, and the expression is:

[0018]

[0019] wherein ψ ki and respectively correspond to the components of the state variables of the inverter k in the eigenvector;

[0020] Participation factor constraints are applied, requiring the sum of participation factors of all inverters in the mode to be greater than 60%, thereby excluding irrelevant modes dominated by grid-side equipment. This ensures that the selected modes truly reflect the interactions within the inverter cluster. The expression for this constraint is:

[0021]

[0022] Where N is the number of inverters.

[0023] Optionally, the small-signal stability verification in step 5 includes the following: if all real parts of the eigenvalues ​​are negative, the system is stable; if the real parts of the eigenvalues ​​are non-negative, they are marked as unstable modes.

[0024] Optionally, the calculation of the benchmark index in step 6 includes:

[0025] a. Sort all oscillation modes in ascending order of damping ratio, extract the top M modes with the lowest damping ratio (M≥3), and denot them as ζ1, ζ2, ..., ζ M ;

[0026] b. Calculate the selective modal damping benchmark index SM-DBI, the expression of which is:

[0027] SM-DBI=(ζ1+ζ2+...+ζM) / M.

[0028] Optionally, the inverter interaction strength determination in step 6 includes:

[0029] When SM-DBI ≥ 0.10, the risk level is safe, and the control strategy is to maintain the current parameters; when SM-DBI ∈ [0.05, 0.10), the risk level is warning, and the control strategy is to start adaptive adjustment of the PLL bandwidth; when SM-DBI < 0.05, the risk level is high-risk, and the control strategy is to inject active damping and operate with limited power.

[0030] In a second aspect, embodiments of the present invention provide a computer-readable storage medium comprising a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to execute the photovoltaic grid-connected inverter interaction identification method based on damping ratio characteristics in the first aspect or any possible implementation thereof.

[0031] Thirdly, embodiments of the present invention provide an electronic device, including: one or more processors; a memory; and one or more computer programs, wherein the one or more computer programs are stored in the memory, and the one or more computer programs include instructions that, when executed by the device, cause the device to perform the photovoltaic grid-connected inverter interaction identification method based on damping ratio characteristics in the first aspect or any possible implementation of the first aspect.

[0032] The technical solution provided by this invention includes a method for establishing a power grid model containing photovoltaic inverters and setting power grid operating conditions; performing power flow calculations according to step 1; performing selective eigenvalue analysis and configuration based on step 2; extracting dimensionality reduction modes according to step 3; analyzing participation factors and verifying small-signal stability using step 4; and calculating benchmark indicators and determining inverter interaction strength according to step 5. This method improves the planning and stable operation of the power grid. Attached Figure Description

[0033] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the 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.

[0034] Figure 1 A flowchart of a photovoltaic grid-connected inverter interaction identification method based on damping ratio characteristics provided in an embodiment of the present invention;

[0035] Figure 2 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] It should be understood that the described embodiments are merely some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0038] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” used in the embodiments of this invention are also intended to include the plural forms unless the context clearly indicates otherwise.

[0039] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0040] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0041] Figure 1 The flowchart of the photovoltaic grid-connected inverter interaction identification method based on damping ratio characteristics provided in the embodiments of the present invention is as follows: Figure 1 As shown, the method includes:

[0042] Step 1: Establish a power grid model that includes photovoltaic inverters and set the power grid operating conditions.

[0043] In this embodiment of the invention, step 1 involves establishing a power grid model containing a photovoltaic inverter in power system simulation software (such as DigSilent PowerFactory), and setting the power grid operating conditions, including photovoltaic output level, inverter control mode and parameters, AC network strength SCR, and load characteristics.

[0044] Step 2: Perform power flow calculations based on Step 1;

[0045] Step 3: Based on Step 2, configure selective eigenvalue analysis.

[0046] In this embodiment of the invention, step 3 includes: using the selective analysis module of the power system simulation software, selecting only the inverter equipment of the target photovoltaic cluster through the equipment filter, and selecting inverter-related control state variables in the state variables, including the phase / frequency state of the phase-locked loop (PLL), the d / q axis integral state of the current inner loop, and the integral state of the power outer loop.

[0047] Step 4: Extract the dimensionality-reduced modes based on Step 3.

[0048] In this embodiment of the invention, step 4 includes: performing a reduced-order characteristic value calculation based on the number of inverters N, so that the complete power system model is reduced to order 3N, which retains only the core state of the inverters.

[0049] Step 5: Using the methods from Step 4, analyze the participating factors and verify the stability of the small signal.

[0050] In this embodiment of the invention, step 5, analyzing the participating factors, includes:

[0051] Define participation factors The expression for quantifying the contribution of the k-th inverter to the oscillation mode is as follows:

[0052]

[0053] Where ψ ki and These correspond to the components of the state variables of inverter k in the eigenvector;

[0054] Participation factor constraints are applied, requiring the sum of participation factors of all inverters in the mode to be greater than 60%, thereby excluding irrelevant modes dominated by grid-side equipment. This ensures that the selected modes truly reflect the interactions within the inverter cluster. The expression for this constraint is:

[0055]

[0056] Where N is the number of inverters.

[0057] In this embodiment of the invention, the small-signal stability verification in step 5 includes the following: when all real parts of the eigenvalues ​​are negative, the system is stable; if the real parts of the eigenvalues ​​are non-negative, they are marked as unstable modes.

[0058] Step 6: Based on Step 5, calculate the benchmark index and determine the inverter interaction strength.

[0059] In this embodiment of the invention, step 6, calculating the benchmark index, includes:

[0060] a. Sort all oscillation modes in ascending order of damping ratio, extract the top M modes with the lowest damping ratio (M≥3), and denot them as ζ1, ζ2, ..., ζ M ;

[0061] b. Calculate the selective modal damping benchmark index SM-DBI, the expression of which is:

[0062] SM-DBI=(ζ1+ζ2+...+ζM) / M.

[0063] In this embodiment of the invention, step 6, determining the inverter interaction strength, includes:

[0064] When SM-DBI ≥ 0.10, the risk level is safe, and the control strategy is to maintain the current parameters; when SM-DBI ∈ [0.05, 0.10), the risk level is warning, and the control strategy is to start adaptive adjustment of the PLL bandwidth; when SM-DBI < 0.05, the risk level is high-risk, and the control strategy is to inject active damping and operate with limited power.

[0065] Eigenvalue analysis is an effective method for studying the stability of power systems. The eigenvalues, damping ratios, and participation factors obtained through eigenvalue analysis are important bases for system stability analysis. The interactions within a power system are reflected in the damping ratios of the system's oscillation modes. Low damping ratios typically lead to prolonged oscillation times, indicating the presence of undesirable interactions within the system.

[0066] This invention proposes a Selective Mode Damping Benchmark Index (SM-DBI), which extracts key low-damping modes reflecting inverter interaction through eigenvalue analysis and establishes a quantitative evaluation system.

[0067] Compared with the prior art, the present invention has the following advantages:

[0068] 1. Identifying the interaction risks among multiple inverters: Based on the relevant functions of power system simulation software, this invention proposes the Selective Modal Damping Benchmark Index (SM-DBI), which directly correlates the damping ratio with the inverter interaction strength, thereby realizing the quantitative identification of the interaction risks among multiple inverters.

[0069] 2. Prevent large-scale oscillation accidents: Based on the Selective Mode Damping Benchmark Index (SM-DBI), establish a quantitative evaluation system, identify high-risk inverters by participating factors, and carry out targeted maintenance to reduce inspection costs and oscillation accident rate.

[0070] 3. Optimize power plant design and operation: During the power plant planning stage, use SM-DBI to assess the interaction risks of different inverter layout schemes (string spacing, etc.) to avoid cluster resonance; and perform inverter parameter tuning based on SM-DBI results.

[0071] The technical solution provided by this invention includes a method for establishing a power grid model containing photovoltaic inverters and setting power grid operating conditions; performing power flow calculations according to step 1; performing selective eigenvalue analysis and configuration based on step 2; extracting dimensionality reduction modes according to step 3; analyzing participation factors and verifying small-signal stability using step 4; and calculating benchmark indicators and determining inverter interaction strength according to step 5. This method improves the planning and stable operation of the power grid.

[0072] The various steps in the embodiments of the present invention can be performed by an electronic device. This electronic device includes, but is not limited to, tablet computers, portable PCs, and desktop computers.

[0073] This invention provides a computer-readable storage medium including a stored program, wherein, when the program is running, it controls the electronic device containing the computer-readable storage medium to execute the above-described embodiment of the photovoltaic grid-connected inverter interaction identification method based on damping ratio characteristics.

[0074] Figure 2 A schematic diagram of an electronic device provided in an embodiment of the present invention, such as... Figure 2 As shown, the electronic device 21 includes a processor 211, a memory 212, and a computer program 213 stored in the memory 212 and executable on the processor 211. When the computer program 213 is executed by the processor 211, it implements the photovoltaic grid-connected inverter interaction identification method based on damping ratio characteristics in the embodiment. To avoid repetition, it will not be described in detail here.

[0075] Electronic device 21 includes, but is not limited to, processor 211 and memory 212. Those skilled in the art will understand that... Figure 2 This is merely an example of electronic device 21 and does not constitute a limitation on electronic device 21. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device may also include input / output devices, network access devices, buses, etc.

[0076] The processor 211 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0077] The memory 212 can be an internal storage unit of the electronic device 21, such as a hard disk or RAM of the electronic device 21. The memory 212 can also be an external storage device of the electronic device 21, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the electronic device 21. Furthermore, the memory 212 can include both internal and external storage units of the electronic device 21. The memory 212 is used to store computer programs and other programs and data required by network devices. The memory 212 can also be used to temporarily store data that has been output or will be output.

[0078] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0079] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for identifying the interaction of photovoltaic grid-connected inverters based on damping ratio characteristics, characterized in that, The method includes: Step 1: Establish a power grid model that includes photovoltaic inverters and set the power grid operating conditions; Step 2: Perform power flow calculations based on Step 1; Step 3: Based on Step 2, configure selective eigenvalue analysis; Step 4: Based on Step 3, extract the dimensionality-reduced modes; Step 5: Using the methods from Step 4, analyze the participating factors and verify the stability of the small signal. Step 6: Based on Step 5, calculate the benchmark index and determine the inverter interaction strength.

2. The method according to claim 1, characterized in that, The grid operating conditions set in step 1 include photovoltaic output level, inverter control mode and parameters, AC network strength SCR and load characteristics.

3. The method according to claim 1, characterized in that, Step 3 includes: using the selective analysis module of the power system simulation software, selecting only the inverter equipment of the target photovoltaic cluster through the equipment filter, and selecting the inverter-related control state variables in the state variables, including the phase / frequency state of the phase-locked loop (PLL), the d / q axis integral state of the inner current loop, and the integral state of the outer power loop.

4. The method according to claim 1, characterized in that, Step 4 includes: performing a reduced-order eigenvalue calculation based on the number of inverters N, so that the complete power system model is reduced to order 3N, retaining only the core state of the inverters.

5. The method according to claim 1, characterized in that, The analysis of participating factors in step 5 includes: Define participation factors The expression for quantifying the contribution of the k-th inverter to the oscillation mode is as follows: Where ψ ki and These correspond to the components of the state variables of inverter k in the eigenvector; Participation factor constraints are applied, requiring the sum of participation factors of all inverters in the mode to be greater than 60%, thereby excluding irrelevant modes dominated by grid-side equipment. This ensures that the selected modes truly reflect the interactions within the inverter cluster. The expression for this constraint is: Where N is the number of inverters.

6. The method according to claim 5, characterized in that, The small-signal stability verification in step 5 includes the following: if all eigenvalues ​​have negative real parts, the system is stable; if the real parts of the eigenvalues ​​are non-negative, they are marked as unstable modes.

7. The method according to claim 1, characterized in that, The calculation of the benchmark index in step 6 includes: a. Sort all oscillation modes in ascending order of damping ratio, extract the top M modes with the lowest damping ratio (M≥3), and denot them as ζ1, ζ2, ..., ζ M ; b. Calculate the selective modal damping benchmark index SM-DBI, the expression of which is: SM-DBI=(ζ1+ζ2+...+ζM) / M.

8. The method according to claim 7, characterized in that, The inverter interaction strength determination in step 6 includes: When SM-DBI ≥ 0.10, the risk level is safe, and the control strategy is to maintain the current parameters; when SM-DBI ∈ [0.05, 0.10), the risk level is warning, and the control strategy is to start adaptive adjustment of the PLL bandwidth; when SM-DBI < 0.05, the risk level is high-risk, and the control strategy is to inject active damping and operate with limited power.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the computer-readable storage medium to perform the photovoltaic grid-connected inverter interaction identification method based on damping ratio characteristics as described in any one of claims 1 to 8.

10. An electronic device, characterized in that, include: One or more processors; Memory; And one or more computer programs, wherein the one or more computer programs are stored in the memory, the one or more computer programs including instructions that, when executed by the device, cause the device to perform the photovoltaic grid-connected inverter interaction identification method based on damping ratio characteristics as described in any one of claims 1 to 8.

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