A method for stability analysis and parameter optimization of a new energy interconnection system

Abstract

The present invention discloses a method for stability analysis and parameter optimization of a new energy interconnected system. First, an integrated line network model is established; an inverter including VSG control, droop control, and PQ control is modeled; based on the integrated line network model and the inverter model, a small-signal model of the new energy interconnected system is established; by screening and calculating, the participation factors of the new energy interconnected system are obtained, and then the oscillation modes of the new energy interconnected system and the reasons affecting the system stability are obtained; by adjusting the system parameters corresponding to the main state variables in each oscillation mode of the new energy interconnected system and combining with the change of the position of the characteristic roots, the control parameters are optimized, thereby improving the stability of the new energy interconnected system. This method uses sensitivity analysis to optimize the sensitive parameters of the system, improves the system stability, and provides a reference for the stability and parameter optimization strategy of the new energy interconnected system.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy interconnected systems, and particularly to a method for analyzing the stability and optimizing parameters of a new energy interconnected system. Background Art

[0002] Problems such as energy shortage and difficult power supply exist in islands (reefs), polar regions and remote areas in our country. According to different geographical locations and climatic conditions, selecting appropriate distributed power sources to build a stable and independently operating new energy interconnected system is an economical and convenient method. Distributed power sources need to be connected to the interconnected system through power electronic devices, but power electronic devices have the characteristics of small inertia and poor overload capacity, which undoubtedly brings challenges to the interconnection stability of the system.

[0003] At present, the following problems exist in the small-signal stability of new energy interconnected systems:

[0004] 1. In terms of modeling: Most models are for droop inverter networking systems, and a small part involves PQ control inverters, without centralized analysis in combination with VSG inverters;

[0005] 2. In terms of load: Most of the studied interconnected systems adopt a centralized load form, but in actual microgrids, there are inevitably various load forms, not just centralized loads;

[0006] 3. In terms of network architecture: Existing studies mostly analyze simple parallel inverters, while in actual situations, multiple inverters operate with different network architectures.

[0007] Therefore, research needs to be carried out on interconnected systems containing VSG, and at the same time, the small-signal modeling methods of the system when the load is in a distributed topology need to be discussed; finally, different analyses need to be considered for different actual network architectures during modeling to achieve an accurate description of the new energy interconnected system and provide a reference for the parameter design of the new energy interconnected system. Summary of the Invention

[0008] The purpose of the present invention is to provide a method for analyzing the stability and optimizing parameters of a new energy interconnected system. This method uses sensitivity analysis to optimize the sensitive parameters of the system, improving the system stability and providing a reference for the stability and parameter optimization strategy of the new energy interconnected system.

[0009] The purpose of the present invention is achieved through the following technical solutions:

[0010] A method for analyzing the stability and optimizing parameters of a new energy interconnected system, the method comprising:

[0011] Step 1: Establish a stability model applicable to the new energy interconnected system and perform integrated line network modeling;

[0012] Step 2: Model the inverters including VSG control, droop control, and PQ control;

[0013] Step 3: Based on the integrated line network model established in Step 1 and the inverter models under different types of control established in Step 2, establish a small-signal model of the new energy interconnected system;

[0014] Step 4: Based on the established small-signal model of the new energy interconnected system, obtain the participation factors of the new energy interconnected system through screening and calculation, and then obtain the oscillation modes of the new energy interconnected system and the reasons affecting the system stability;

[0015] Step 5: By adjusting the system parameters corresponding to the main state variables in each oscillation mode of the new energy interconnected system and combining with the change of the position of the characteristic roots, optimize the control parameters, thereby improving the stability of the new energy interconnected system.

[0016] It can be seen from the technical solutions provided by the present invention described above that the above method uses sensitivity analysis to optimize the sensitive parameters of the system, improves the system stability, and provides a reference for the stability and parameter optimization strategy of the new energy interconnected system. Brief Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 It is a schematic flow chart of the method for analyzing the stability and optimizing the parameters of the new energy interconnected system provided by the embodiment of the present invention;

[0019] Figure 2 It is a schematic diagram of the network topology structure of the AC microgrid provided by the embodiment of the present invention;

[0020] Figure 3 It is a phase-locked loop (PLL) control block diagram of the inverter with PQ control described in the embodiment of the present invention;

[0021] Figure 4 It is a schematic diagram of the distribution of the system characteristic roots after optimizing the filter parameters described in the embodiment of the present invention. Detailed Embodiment

[0022] The following clearly and completely describes the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments, which does not constitute a limitation to the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the protection scope of the present invention.

[0023] As Figure 1 shown is a schematic flowchart of a method for stability analysis and parameter optimization of a new energy interconnection system provided by an embodiment of the present invention, and the method includes:

[0024] Step 1: Establish a stability model applicable to the new energy interconnection system and perform integrated line network modeling;

[0025] In this step, as Figure 2 shown is a schematic diagram of the network topology structure of the AC microgrid provided by an embodiment of the present invention, Figure 2 where: One support type micro-source is selected for each node for voltage and frequency support. Gi is an AC power generation micro-source, and Li is an electrical load. Among them, G1 consists of 2 droop inverters; G2 consists of 2 VSG inverters and 1 PQ inverter; G3 consists of 1 droop inverter, 1 VSG inverter and 1 PQ inverter.

[0026] The active power and reactive power output by the i-th micro-source converter are:

[0027]

[0028] where, V i and δ i are respectively the amplitude and phase angle of the output voltage of the i-th micro-source; V P and δ P are respectively the voltage amplitude and phase angle of the point of common coupling (PCC point); is the admittance value between the i-th micro-source and the PCC point;

[0029] According to Kirchhoff's current and voltage laws, the node voltage of the PCC point is:

[0030]

[0031] Define where ω s is the angular frequency of the new energy interconnection system under steady-state operation;

[0032] Under a high-inductive transmission line, there is φ i ≈ -π / 2, so the node power equation of micro-source i is:

[0033]

[0034] The voltage loop of the micro-source uses droop control, and its expression is:

[0035] V = V 0 -nQ (4)

[0036] where, V 0 is the rated AC voltage amplitude; Q is the reactive power output of the micro-source; n is the voltage droop coefficient;

[0037] Substituting the voltage droop equation (4) into equation (3) and linearizing it at its steady-state operating point, we can obtain:

[0038]

[0039] where,

[0040]

[0041] Writing equations (5)-(6) in matrix form, we can obtain:

[0042]

[0043] where,

[0044] where Δp, Δq, ΔQ, K pQ , K qQ , are all matrices and have no physical meaning. The element definitions are as shown in equations (5)-(7).

[0045] Step 2: Model the inverter including VSG control, droop control, and PQ control;

[0046] In this step, 1) Model the inverter with VSG control, which is specifically expressed as:

[0047]

[0048] where, J is the virtual inertia coefficient; k is the governor gain; D is the virtual damping coefficient; P ini is the initial output power;

[0049] Meanwhile, the power filtering expression of the reactive droop loop of VSG is:

[0050]

[0051] By linearizing equations (9) and (10), the small-signal model of the inverter with VSG control is obtained as:

[0052]

[0053] Finally, substituting Δp and Δq in Equation (5) into Equation (11), we can obtain:

[0054]

[0055] 2) Model the inverter with droop control, which is specifically expressed as:

[0056]

[0057] where p h , q h and P h , Q h are the active power and reactive power before and after filtering of the h-th droop unit respectively; the filter cut-off frequency is ω c ;

[0058] Linearize Equation (9) at the steady-state point and combine it with Equation (5) to obtain the small-signal model of the inverter with droop control, which is expressed as:

[0059]

[0060] 3) Model the inverter with PQ control

[0061] As Figure 3 shown is the phase-locked loop (PLL) control block diagram of the inverter with PQ control according to the embodiment of the present invention. The dynamic characteristics of the PLL will affect the performance of the inverter grid connection. The modeling of the PLL is as follows:

[0062]

[0063] where θ i is the phase-locked phase angle of the i-th inverter with PQ control; u q_j is the q-axis output voltage of the inverter; Kp and Ki are the proportional-integral parameters of the PLL controller.

[0064] Step 3: Based on the integrated line network model established in Step 1 and the inverter models under different types of control established in Step 2, establish a small-signal model of the new energy interconnected system;

[0065] In this step, based on the integrated line network model established in Step 1 and the inverter models under different types of control established in Step 2, combine Equations (7), (12), (14), and (15), and eliminate the intermediate variables to establish the small-signal model of the new energy interconnected system as follows:

[0066]

[0067] Among them, the state variables are:

[0068]

[0069]

[0070] Among them, and are the internal and external state variables of the VSG respectively; and are the internal and external state variables of the droop control respectively.

[0071] Step 4: Based on the established small-signal model of the new energy interconnected system, through screening and calculation, obtain the participation factors of the new energy interconnected system, and then obtain the oscillation modes of the new energy interconnected system and the reasons affecting the system stability;

[0072] For example, based on the established small-signal model of the new energy interconnected system, the conjugate eigenvalues of the system are expressed as λ = σ ± jω, and the corresponding oscillation mode of the new energy interconnected system is e σt sin(ωt + θ), where the real part reflects the oscillation amplitude and the imaginary part reflects the oscillation frequency;

[0073] For any eigenvalue λ i , v i is called the right eigenvector of matrix A with respect to λ i , and it satisfies the equation Av i = λ i v i ; similarly, u i is called the left eigenvector of matrix A with respect to λ i , and it satisfies the equation u i A = λ i u i ; and the sensitivity of each element in matrix A is defined as

[0074] Furthermore, by combining the left and right eigenvectors, the participation matrix P is obtained, which is used to represent the participation degree of state variables in the oscillation mode, and is expressed as:

[0075]

[0076] The element P ki = u ki v ki is the participation factor, which represents the participation degree of the kth state variable in the ith oscillation mode;

[0077] The dominant characteristic roots in the underdamped state of the system are screened out for analysis. They are renumbered and analyzed, and the information statistics are shown in Table 1. The main state variables affecting the oscillation mode are obtained:

[0078] Table 1

[0079]

[0080] Then, using the method of obtaining participation factors introduced above and combining with Table 1, the participation degree of state variables in the oscillation mode can be obtained. From the analysis, it can be seen that the reasons affecting the system stability are as follows: the power distribution control link mainly affects the characteristic roots in the low-frequency band of the system, the voltage control link mainly affects the middle-frequency band, and the current control link and the output filter mainly affect the high-frequency characteristic roots.

[0081] Step 5: Optimize the control parameters by adjusting the system parameters corresponding to the main state variables in each oscillation mode of the new energy interconnected system and combining with the change of the position of the characteristic roots, so as to improve the stability of the new energy interconnected system.

[0082] In this step, in the principle of automatic control, the characteristic roots closer to the imaginary axis are called dominant characteristic roots, and the dominant characteristic roots have a greater impact on the stability of the new energy interconnected system; and the low-damping oscillation mode is not conducive to the system stability. Therefore, the greater the system damping degree, the stronger its stability. The system damping ratio ξ is expressed as:

[0083]

[0084] Optimizing the low-damping oscillation mode can improve the system stability. For example, modifying the oscillation mode 3 shown in Table 1 and combining with the participation factor, it can be obtained that the key state variables causing the low damping of the system are the d-axis and q-axis components of the current output by the droop control in G3, which are mainly affected by its LC filter parameters. Therefore, adjust its LC value to improve the system stability.

[0085] As Figure 4 shown is the schematic diagram of the system characteristic root distribution after optimizing the filter parameters in the embodiment of the present invention. Compared with the original characteristic roots, the optimized system has higher damping and is more stable.

[0086] It should be noted that when changing a certain main participation factor, other oscillation modes will also change slightly. Therefore, the method of improving the system stability through sensitivity analysis is not unique. In actual optimization, the comprehensive stability performance of the whole system should be taken as the main consideration, and global optimization should be achieved as much as possible.

[0087] It should be noted that the content not described in detail in the embodiment of the present invention belongs to the prior art well known to those skilled in the art.

[0088] As described above, it is only the preferred specific implementation manner of the present invention. However, the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims. The information disclosed in the background art part of this article is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as an admission or imply in any form that this information constitutes the prior art known to those skilled in the art.

Claims

1. A method for stability analysis and parameter optimization of new energy interconnected systems. It is characterized in that The method comprises: Step 1: Establish a stability model suitable for the new energy interconnection system and conduct integrated line network modeling; In step 1, each node selects a supporting micro-source for voltage and frequency support, Gi is the AC power generation micro-source, and Li is the power load; among them, G1 is composed of 2 droop inverters; G2 is composed of 2 VSG inverters and 1 PQ inverter; G3 is composed of 1 droop inverter, 1 VSG inverter and 1 PQ inverter; The active power and reactive power output by the i-th micro-source converter are: Among them, V i and δ i are respectively the amplitude and phase angle of the output voltage of the i-th micro-source; V P and δ P are respectively the voltage amplitude and phase angle of the point of common coupling; is the admittance value between the i-th micro-source and the PCC point; According to Kirchhoff's current-voltage law, the node voltage at the PCC point is: Definition where ω s is the angular frequency of the new energy interconnected system under steady-state operation; Under a high-sensitivity transmission line, there is φ i ≈ -π / 2. Therefore, the nodal power equation of the micro-source i is: The voltage loop of the micro source uses droop control, and its expression is: V = V 0 -nQ (4) Among them, V 0 is the rated AC voltage amplitude; Q is the reactive power output by the micro-source; n is the voltage droop coefficient; Substituting the voltage droop equation (4) into equation (3) and linearizing it at its steady-state operating point, we can obtain: in, By writing equations (5)-(6) in matrix form, we can obtain: Among them, where Δp, Δq, ΔQ, K pQ , K qQ , are all matrices and have no physical meaning. The elements are defined as shown in Eqs. (5)-(7); Step 2: Model the inverter including VSG control, droop control, and PQ control; The process of step 2 is specifically as follows: 1) Model the inverter controlled by VSG, which is specifically expressed as follows: Among them, J is the virtual inertia coefficient; k is the governor gain; D is the virtual damping coefficient; P ini is the initial output power; At the same time, the power filter expression of the reactive power droop loop of VSG is: By linearizing equations (9) and (10), the small signal model of the VSG controlled inverter is expressed as: Finally, substituting Δp and Δq in equation (5) into equation (11), we can obtain: 2) Model the inverter with droop control, which is specifically expressed as: Among them, p h , q h and P h , Q h are the active power and reactive power before and after filtering of the h-th droop unit respectively; the filter cut-off frequency is ω c ; At the steady-state point, equation (13) is linearized and connected in parallel with equation (5), and the small signal model of the droop-controlled inverter is expressed as: 3) Modeling the PQ-controlled inverter The dynamic characteristics of the phase-locked loop will affect the performance of the inverter grid connection. The modeling of the PLL is as follows: where θ i is the phase-locked phase angle of the i-th inverter controlled by PQ; u q_j is the q-axis output voltage of the inverter; Kp and Ki are the proportional-integral parameters of the PLL controller; Step 3: Based on the integrated line network model established in step 1 and the inverter models under different types of control established in step 2, a small signal model of the new energy interconnection system is established; In step 3, specifically, equations (7), (12), (14), and (15) are combined, and intermediate variables are eliminated to establish a small signal model of the new energy interconnection system as follows: Among them, the state variables are: Among them, and are the internal and external state variables of the VSG respectively; and are the internal and external state variables of the droop control respectively; Step 4: Based on the established small signal model of the new energy interconnection system, the participation factor of the new energy interconnection system is obtained by screening and calculating, and then the oscillation mode of the new energy interconnection system and the reasons affecting the system stability are obtained; Step 5: By adjusting the system parameters corresponding to the main state variables in each oscillation mode of the new energy interconnected system, and combining with the position change of the characteristic root to optimize the control parameters, the stability of the new energy interconnected system is improved.

2. According to the method for stability analysis and parameter optimization of new energy interconnection system according to claim 1, It is characterized in that In step 5, The characteristic root closer to the imaginary axis is called the dominant characteristic root, and the dominant characteristic root has a greater impact on the stability of the new energy interconnection system; the low damping oscillation mode is not conducive to the stability of the system, so the greater the system damping degree, the stronger its stability will be. The system damping ratio ξ is expressed as: Optimizing the low-damping oscillation mode can improve system stability. By combining participation factors, the key state variables causing low damping in the system are the d- and q-axis components of the current output by the droop control in G3, which are affected by its LC filter parameters. Therefore, adjust the LC values to improve system stability.

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