A hybrid dc instability discrimination method and system based on mode resonance

Abstract

The present disclosure belongs to the technical field of hybrid DC power transmission system stability, and particularly relates to a hybrid DC instability discrimination method and system based on mode resonance, comprising: establishing a full-order state space model of a hybrid DC power transmission system, constructing a system dynamics model under the time scale of a DC control system, linearizing the obtained system dynamics model to obtain a linearized model of the hybrid DC power transmission system; calculating eigenvalues of the linearized model and participation factors of the eigenvalues, screening an alternative resonance mode set according to the obtained eigenvalue distribution, and system parameters strongly related to the alternative resonance mode set; modifying system parameters of the hybrid DC power transmission system, drawing root loci of system eigenvalues, judging whether mode resonance occurs and determining resonance strength of the mode resonance; if mode strong resonance occurs and the resonance strength is greater than a set threshold, it is determined that the system will be unstable, and system parameters at the resonance point are recorded.

Description

Technical Field

[0001] This disclosure belongs to the field of stability analysis technology for hybrid DC transmission systems, specifically relating to a hybrid DC instability discrimination method and system based on mode resonance. Background Technology

[0002] The statements in this section are merely background information relating to this disclosure and do not necessarily constitute prior art.

[0003] Line commutated converter high voltage direct current (LCC-HVDC) transmission systems have been widely used for long-distance, high-capacity power transmission due to their cost and technological advantages in inter-regional power transmission. However, their operation requires commutation support from an AC system. Voltage source converter high voltage direct current (VSC-HVDC) transmission systems, on the other hand, operate independently of an AC system and can achieve independent and rapid control of active and reactive power. Introducing VSC-HVDC into a DC system creates a hybrid DC transmission system that combines the advantages of both LCC-HVDC and VSC-HVDC, improving the overall system operating characteristics. However, hybrid DC transmission systems also have some inherent problems. Hybrid DC transmission systems have both DC electrical coupling on the DC side and AC electrical coupling on the AC side, making them more prone to mode resonance phenomena under strong coupling (i.e., the convergence of different branches of the characteristic root locus). When the two modes of the system state space matrix are close to coincide (strong resonance), the root locus trends of the two modes will change drastically as the parameters change, and one of them will move in the direction of damping reduction, which can lead to system instability in severe cases.

[0004] The inventors have discovered that current research on the stability analysis of DC transmission systems mainly focuses on the motion stability represented by phase trajectory changes, rarely mentioning the use of mode resonance phenomena to judge structural stability. Furthermore, the system topologies that are of interest are mostly single-type DC systems, with little attention paid to hybrid DC transmission systems where there is strong electrical coupling on both the AC and DC sides. Summary of the Invention

[0005] To address the aforementioned issues, this disclosure proposes a hybrid DC instability discrimination method and system based on mode resonance. This method identifies possible resonance modes in the hybrid DC transmission system, provides system parameters related to the resonance modes, and quantifies and evaluates the system stability margin based on the resonance mode information.

[0006] According to some embodiments, the first solution of this disclosure provides a hybrid DC instability discrimination method based on mode resonance, which adopts the following technical solution:

[0007] A hybrid DC instability discrimination method based on mode resonance includes:

[0008] A full-order state-space model of the hybrid DC transmission system is established. Based on the singular perturbation identification of time scale differences, a system dynamics model of the DC control system under the time scale is constructed. The obtained system dynamics model is linearized to obtain a linearized model of the hybrid DC transmission system.

[0009] Calculate the eigenvalues ​​of the linearized model and the participation factors of the eigenvalues, and screen the set of candidate resonance modes and the system parameters strongly correlated with the set of candidate resonance modes based on the obtained eigenvalue distribution.

[0010] Modify the system parameters of the hybrid DC transmission system, plot the root locus of the system's characteristic roots, determine whether mode resonance occurs and determine the resonance intensity of the mode resonance; if the resonance intensity is greater than a set threshold, the system is determined to be unstable, and the system parameters at the resonance point are recorded to complete the instability judgment of the hybrid DC transmission system.

[0011] As a further technical limitation, the hybrid DC transmission system includes a grid-commutated HVDC transmission system and a voltage source converter HVDC transmission system; using the variables of the DC inverter-side system control loop and the acquired system parameters of the hybrid DC transmission system, a full-order state-space model of the hybrid DC transmission system is constructed, i.e. Where, x a The state variables of the hybrid DC transmission system include the state variables of the control loops on the inverter side of the grid-commutated HVDC transmission system and the inverter side of the voltage source converter HVDC transmission system, the filter capacitor voltage and inductor current on the inverter side of the grid-commutated HVDC transmission system, the AC grid capacitor voltage and inductor current, and the state variables of the synchronous generator; u is the system input variable.

[0012] Furthermore, based on singular perturbation theory, the time-scale problem of the hybrid DC transmission system model is analyzed; the steps for constructing the system dynamics model of the DC control system under the time scale are as follows:

[0013] Based on the time scale of the DC control system, the full-order state-space model of the hybrid DC transmission system is dynamically divided into fast dynamics and slow dynamics, and a singular perturbation standard model is constructed. Where, x s x is a state variable with slow dynamic characteristics. f Let ε be the state variable with fast dynamic characteristics, t be the singular perturbation parameter, and t be time. Let ε = 0, and the fast dynamics will be described by the quasi-steady-state equation, i.e., 0 = h(t, x). s ,x f ,0), that is, transforming the model into The transformed model is the system dynamics model of the DC control system on the time scale.

[0014] Furthermore, the steady-state point of the system dynamics model under the rated parameters in the time scale of the DC control system is solved; at the steady-state point, the system dynamics model under the time scale of the DC control system is linearized to obtain the linearized model, which is... Where, Δx s Let A be the infinitesimal increment of the state variable, and let A be the system state space matrix.

[0015] As a further technical limitation, in the process of screening the set of candidate resonance modes and their system parameter sets, the eigenvalues ​​of the system state matrix are calculated at the steady state point; based on the distribution of the eigenvalues ​​and the participation factors, eigenvalues ​​of the same order of magnitude and strongly correlated with the common system parameters (large participation factors) are selected as the set of candidate resonance modes, and the strongly correlated common system parameters are used as the set of system parameters.

[0016] As a further technical limitation, the system parameters of the hybrid DC transmission system are modified, and the root locus of the system characteristic roots is plotted, including the following steps: modifying the parameters in the set of system parameters of interest, plotting the curves of the characteristic roots in the set of alternative resonance modes in the complex plane as the parameters change, and completing the plotting of the system characteristic root locus.

[0017] As a further technical limitation, the specific process of determining whether mode resonance occurs and determining the intensity of mode resonance is as follows:

[0018] If two eigenvalues ​​of the system state space matrix first approach each other as the system parameters change unidirectionally, and after they are close to coinciding, the motion directions of the two eigenvalues ​​both turn by about 90°, and then the two eigenvalues ​​continue to move in opposite directions, and the motion direction of one of the eigenvalues ​​is the direction of damping reduction, then it is judged that mode resonance has occurred.

[0019] When mode resonance occurs, the position of the characteristic roots, system parameters, and the shortest distance between characteristic roots in the characteristic root trajectory of the resonance mode are recorded to determine the resonance mode of the hybrid DC transmission system and to determine that the system will become unstable under the recorded system parameter changes. The resonance intensity is evaluated by the shortest distance between characteristic roots.

[0020] If no mode resonance occurs, select other parameters from the system parameter set to draw the system eigenvalue trajectory until the search for all parameters in the system parameter set is completed.

[0021] According to some embodiments, the second aspect of this disclosure provides a hybrid DC instability discrimination system based on mode resonance, employing the following technical solution:

[0022] A hybrid DC instability discrimination system based on mode resonance, comprising:

[0023] The module is configured to establish a full-order state-space model of the hybrid DC transmission system, identify time-scale differences based on singular perturbations, construct a system dynamics model of the DC control system under the time scale, and linearize the obtained system dynamics model to obtain a linearized model of the hybrid DC transmission system.

[0024] The analysis module is configured to calculate the eigenvalues ​​of the linearized model and the participation factors of the eigenvalues, filter the set of candidate resonance modes based on the obtained eigenvalue distribution, and the system parameters that are strongly correlated with the set of candidate resonance modes.

[0025] The discrimination module is configured to modify the system parameters of the hybrid DC transmission system, draw the root locus of the system characteristic roots, determine whether mode resonance occurs and determine the resonance intensity of the mode resonance; if the resonance intensity is greater than a set threshold, the system is determined to be unstable, the system parameters at the resonance point are recorded, and the instability discrimination of the hybrid DC transmission system is completed.

[0026] According to some embodiments, a third aspect of this disclosure provides a computer-readable storage medium, employing the following technical solution:

[0027] A computer-readable storage medium having a program stored thereon that, when executed by a processor, implements the steps of the hybrid DC instability discrimination method based on mode resonance as described in the first aspect of this disclosure.

[0028] According to some embodiments, the fourth solution of this disclosure provides an electronic device that adopts the following technical solution:

[0029] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the hybrid DC instability discrimination method based on mode resonance as described in the first aspect of this disclosure.

[0030] Compared with the prior art, the beneficial effects of this disclosure are as follows:

[0031] (1) This disclosure can be used as a reference in the process of setting system parameters, so as to avoid system resonance by reasonably configuring system parameters; when the system exhibits mode resonance, the stability margin of the system can be quantitatively evaluated by algorithm, so as to provide a reference for improving the safe and stable operation of hybrid DC transmission system;

[0032] (2) This disclosure takes into account the needs of stability analysis of hybrid DC transmission systems and proposes a technical route for evaluating system stability based on resonance modes. It divides the resonance modes and system parameters with strong coupling relationship based on the correlation between resonance modes and system parameters, identifies possible characteristic root resonance modes, and effectively avoids system instability caused by system mode resonance.

[0033] (3) This disclosure obtains the possible resonance modes and related system parameters by drawing characteristic root trajectories, and quantitatively evaluates the impact of the resonance mode on system stability, providing technical support for the safe and stable operation of hybrid DC transmission systems. Attached Figure Description

[0034] The accompanying drawings, which form part of this disclosure, are used to provide a further understanding of this disclosure. The illustrative embodiments of this disclosure and their descriptions are used to explain this disclosure and do not constitute an undue limitation of this disclosure.

[0035] Figure 1 This is a flowchart of the hybrid DC instability discrimination method based on mode resonance in Embodiment 1 of this disclosure;

[0036] Figure 2 This is a schematic diagram of the steps of the hybrid DC instability discrimination method based on mode resonance in Embodiment 1 of this disclosure;

[0037] Figure 3(a) is a schematic diagram of the root locus in the non-resonance form in Embodiment 1 of this disclosure;

[0038] Figure 3(b) is a schematic diagram of the root locus in the resonance mode in Embodiment 1 of this disclosure;

[0039] Figure 4 This is a system diagram of the hybrid DC transmission system in Embodiment 1 of this disclosure;

[0040] Figure 5 This is a diagram of the system mode resonance phenomenon in Embodiment 1 of this disclosure;

[0041] Figure 6 This is a block diagram of the hybrid DC instability discrimination system based on mode resonance in Embodiment 2 of this disclosure. Detailed Implementation

[0042] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0043] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0044] Where there is no conflict, the embodiments and features described herein can be combined with each other.

[0045] Example 1

[0046] Embodiment 1 of this disclosure introduces a hybrid DC instability discrimination method based on mode resonance.

[0047] like Figure 1 As shown, a hybrid DC instability discrimination method based on mode resonance includes:

[0048] A full-order state-space model of the hybrid DC transmission system is established. Based on the singular perturbation identification of time scale differences, a system dynamics model of the DC control system under the time scale is constructed. The obtained system dynamics model is linearized to obtain a linearized model of the hybrid DC transmission system.

[0049] Calculate the eigenvalues ​​of the linearized model and the participation factors of the eigenvalues, and screen the set of candidate resonance modes and the system parameters strongly correlated with the set of candidate resonance modes based on the obtained eigenvalue distribution.

[0050] Modify the corresponding system parameters of the hybrid DC transmission system, plot the system characteristic root locus, determine whether mode resonance occurs and determine the resonance intensity of the mode resonance; if the resonance intensity is greater than the set threshold, it is determined that the system will be unstable, record the system parameters at the resonance point, and complete the instability judgment of the hybrid DC transmission system.

[0051] This embodiment aims to identify possible resonance modes in a hybrid DC transmission system, provide system parameters related to the resonance modes, and quantify and evaluate the system stability margin based on the resonance mode information.

[0052] like Figure 2 As shown, the hybrid DC instability discrimination method based on mode resonance includes the following steps:

[0053] (1) Construct a full-order model of the hybrid DC transmission system using the variables of the control loop of the DC inverter side system and the obtained system parameters of the hybrid DC transmission system;

[0054] (2) Based on singular perturbation theory, the time scale problem of the hybrid DC transmission system model is analyzed. Taking the time scale of the DC control system as the benchmark, the model dynamics are divided into fast dynamics and slow dynamics, and the system dynamics model under the time scale of the DC control system is constructed and linearized;

[0055] (3) Calculate the eigenvalues ​​of the system state matrix at the steady state point. Based on the distribution of the eigenvalues ​​and the participation factors, select the eigenvalues ​​of the same order of magnitude and those that are strongly correlated with the common system parameters (with large participation factors) as the set of candidate resonance modes. Use the strongly correlated common system parameters as the set of system parameters.

[0056] (4) Calculate the system characteristic roots based on the linearized model of the hybrid DC transmission system, modify the parameters in the set of system parameters of interest, draw the curves of the characteristic roots in the set of candidate resonance modes in the complex plane as the parameters change, and complete the drawing of the system characteristic root trajectory.

[0057] (5) When mode resonance occurs, record the position of the characteristic roots, system parameters, and the shortest distance between characteristic roots in the characteristic root trajectory of the resonance mode to determine the resonance mode of the hybrid DC transmission system and determine that the system will become unstable under the recorded system parameter changes. The resonance intensity is evaluated by the shortest distance between characteristic roots. When no mode resonance occurs, select other parameters in the system parameter set to draw the system characteristic root trajectory until all parameters in the system parameter set have been searched.

[0058] Constructing a full-order model of a hybrid DC transmission system

[0059] A full-order dynamic model of the hybrid DC transmission system is constructed using the variables of the control loop on the DC inverter side and the capacitor voltage and inductor current on the grid side as state variables. Its form is as follows:

[0060]

[0061] Where x represents all state variables of the hybrid DC transmission system, including the state variables of the control loops on the inverter side of the grid-commutated HVDC transmission system and the inverter side of the voltage source converter HVDC transmission system, the filter capacitor voltage and inductor current on the inverter side of the grid-commutated HVDC transmission system, the AC grid capacitor voltage and inductor current, the synchronous generator state variables, etc.; u represents the system input variable, and y represents the system output variable.

[0062] The DC control system is described in detail using differential algebraic equations. The control links involved include LCC constant DC voltage control, VSC constant DC voltage control, VSC constant active power control, VSC constant reactive power control, VSC current inner loop control, and phase-locked loop control.

[0063] LCC constant DC voltage control, described as follows:

[0064]

[0065] β=x i1 +k ip (U dc -U dcref (3)

[0066] In the formula, β is the inverter firing angle, U dcref U is the reference value for the DC voltage of the LCC.dc The measured value of the DC side voltage of the LCC, k ip k ii To determine the parameters of the DC voltage controller.

[0067] VSC constant DC voltage control, described as follows:

[0068]

[0069] i vd_ref =k p5 (U dcrefVSC -U dcVSC )+x dcVSC (5)

[0070] In the formula, i vd_ref U is the d-axis current reference value for the inner current loop. dcrefVSC U is the reference value for the VSC DC voltage. dcVSC The measured value of the DC side voltage of VSC, k p5 k i5 To determine the parameters of the DC voltage controller.

[0071] VSC constant active power control, described as follows:

[0072]

[0073] i vd_ref =k p4 (P refVSC -P VSC )+x PVSC (7)

[0074] In the formula, i vd_ref P is the d-axis current reference value for the inner current loop. refVSC P is the reference value for active power in VSC. VSC k is the measured active power output of VSC. p4 k i4 To determine the active power controller parameters.

[0075] VSC constant reactive power control, described as follows:

[0076]

[0077] i vq_ref =k p3 (Q refVSC -Q VSC )+x QVSC (9)

[0078] In the formula, i vq_ref Q is the q-axis current reference value for the inner current loop. refVSCQ is the VSC reactive power reference value. VSC k is the measured reactive power output of VSC. p3 k i3 To determine the parameters of the reactive power controller.

[0079] VSC current inner loop control, described as:

[0080]

[0081]

[0082] u diffd =u sd +k p1 (i vd_ref -i vd )+x1-ωLi vq (12)

[0083] u diffq =u sq +k p2 (i vq_ref -i vq )+x2+ωLi vd (13)

[0084] In the formula, i vd i vq These represent the d-axis and q-axis components of the AC side current, respectively, where ω is the electrical angular velocity output by the phase-locked loop, and u... diffd u diffq These are the d-axis and q-axis components of the differential-mode voltage reference value output by the inner current loop controller, respectively, k p1 k i1 k p2 k i2 These are the parameters for the inner current loop controller.

[0085] Phase-locked loop controller, described as follows:

[0086]

[0087]

[0088] ω=x ipll -K ppll u q +ω0 ​​(16)

[0089] In the formula, θ is the phase of the common coupling point voltage output by the phase-locked loop, and u q For the voltage q-axis component at the point of common coupling, k pp ll, k ipll These are the parameters for the phase-locked loop controller.

[0090] Constructing a system dynamics model and linearization of a DC control system on a time scale

[0091] Based on singular perturbation theory, and taking the time scale of the control system as the benchmark, the detailed model of the hybrid DC transmission system is transformed into a singular perturbation standard model (17), where x s x is a state variable with slow dynamic characteristics. f These are state variables with fast dynamic characteristics.

[0092]

[0093] The fast dynamics are described by quasi-steady-state equations, resulting in a system dynamic model of the DC control system on the time scale (18).

[0094]

[0095] Linearizing the hybrid DC transmission system model (18) at the steady-state point on the time scale of the DC control system yields the system linearization model:

[0096]

[0097] Where, Δx s Let A be the infinitesimal increment of the state variable, and let A be the system state space matrix.

[0098] Filtering the set of alternative modes

[0099] Under rated parameters, the steady-state point of the system dynamics model on the time scale of the DC control system is solved, and the eigenvalues ​​of the system state matrix are calculated at this steady-state point. Based on the distribution of the eigenvalues ​​and the participation factors, eigenvalues ​​of the same order of magnitude and strongly correlated with common system parameters (large participation factors) are selected as the candidate resonance mode set, and the strongly correlated common system parameters are used as the system parameter set.

[0100] Plotting the system's eigenvalue locus image

[0101] Based on the linearized model of the system, the system eigenvalues ​​are calculated, the parameters in the set of system parameters of key interest are modified, and the curves of the eigenvalues ​​in the set of candidate resonance modes in the complex plane as the parameters change are plotted to complete the plotting of the system eigenvalue trajectories.

[0102] Based on the direction of change of the real part of the eigenvalues ​​as the classification criterion, the possible changes in eigenvalues ​​due to directional changes in system parameters are as follows:

[0103] (1) The real part of the eigenvalue decreases as the parameter orientation changes. At this time, the eigenvalue moves away from the imaginary axis. This situation will not affect the stability of the system.

[0104] (2) The real part of the eigenvalue increases as the parameter orientation changes. At this time, the eigenvalue moves towards the imaginary axis, which may affect the stability of the system.

[0105] (3) As the system parameters change unidirectionally, the two characteristic roots first approach each other. After they are close to coinciding, the motion directions of the two characteristic roots both turn by about 90°. Then the two characteristic roots continue to move in opposite directions, and the motion direction of one of the characteristic roots is the direction of damping reduction, which will affect the stability of the system.

[0106] Based on the plotted eigenvalue locus, possible resonance modes are determined.

[0107] Stability determination

[0108] When mode resonance occurs, the position of the eigenvalues, system parameters, and the shortest distance between eigenvalues ​​in the eigenvalue trajectory of the resonance mode are recorded to determine the resonance mode of the hybrid DC transmission system. It is also determined that the system will become unstable under the recorded system parameter changes, and the resonance intensity is evaluated by the shortest distance between eigenvalues. When mode resonance does not occur, other parameters in the system parameter set are selected again to draw the system eigenvalue trajectory until all parameters in the system parameter set have been searched.

[0109] Simulation Analysis

[0110] Building such Figure 4 The simulation model of the receiving-end system with hybrid LCC and VSC feed is shown. In this model, the rectifier side is equivalent to a DC current source. The operating strategy of the LCC station is constant DC voltage control. Among the three VSC stations, stations 1 and 3 operate under constant active power and constant reactive power control, while station 2 operates under constant DC voltage and constant reactive power control. The AC power grid is approximated using the Thevenin equivalent model. The control parameters involved in this system are shown in Table 1.

[0111] Table 1 Control parameters of the hybrid DC transmission system

[0112]

[0113]

[0114] By modifying the system parameters, the system eigenvalue locus diagrams are shown in Figures 3(a) and 3(b). From the root locus diagrams, it can be seen that the eigenvalues ​​of the system state matrix exhibit two changing trends as the system parameters change:

[0115] (1) Non-resonance form: In this case, the real part of the eigenvalues ​​of the system state matrix changes monotonically with the unidirectional change of the system parameters;

[0116] (2) Resonance form: In this case, the real part of the eigenvalues ​​of the system state matrix shows a trend of first increasing and then decreasing (or first decreasing and then increasing) as the system parameters change unidirectionally.

[0117] Define the rate of change of the eigenvalues ​​as:

[0118] v λ =Δλ / Δk (20)

[0119] Where Δk is the change in system parameters and Δλ is the change in the real part of the eigenvalues. As the two eigenvalues ​​approach each other, that is, as they approach the resonance point, their rate of change gradually increases, and the change in the real part of the eigenvalues ​​is most dramatic near the resonance point.

[0120] The following table, Table 2, illustrates the variation law of resonance caused by the change in the proportional-integral coefficient of the VSC-HVDC constant DC voltage control.

[0121] In this example, Mode 1 and Mode 2 are two modes from the candidate resonant mode set that are strongly correlated with the proportional-integral term in the VSC-HVDC constant DC voltage control. For example... Figure 5 As shown, resonance occurred between the two as the proportional-integral coefficient of the VSC-HVDC constant DC voltage control decreased from 950 to 150.

[0122] Table 2. Rate of change of characteristic roots

[0123]

[0124]

[0125] In resonance mode, as the two eigenvalues ​​gradually approach each other, the rate of change of the eigenvalues ​​gradually increases. When the two eigenvalues ​​are close to coinciding, even a very small change in the system parameters can lead to a drastic change in the real part of the eigenvalue. Furthermore, since the direction of change of one of the eigenvalues ​​is the direction of damping reduction, mode resonance exhibits properties that are detrimental to system stability.

[0126] This embodiment avoids system resonance by rationally configuring system parameters during system parameter setting. When mode resonance occurs, the system stability margin can be quantitatively assessed through algorithms, providing a reference for improving the safe and stable operation of hybrid DC transmission systems. Considering the characteristics of stability analysis requirements for hybrid DC transmission systems, a technical route for assessing system stability based on resonance modes is proposed. Resonance modes and system parameters with strong coupling relationships are classified based on the correlation between resonance modes and system parameters, identifying possible characteristic root resonance modes and effectively avoiding system instability caused by system mode resonance. Possible resonance modes and their associated system parameters are obtained by plotting characteristic root trajectories, and the impact of these resonance modes on system stability is quantitatively assessed, providing technical support for the safe and stable operation of hybrid DC transmission systems.

[0127] Example 2

[0128] Embodiment 2 of this disclosure introduces a hybrid DC instability discrimination system based on mode resonance.

[0129] like Figure 6 As shown, a hybrid DC instability discrimination system based on mode resonance includes:

[0130] The module is configured to establish a full-order state-space model of the hybrid DC transmission system, identify time-scale differences based on singular perturbations, construct a system dynamics model of the DC control system under the time scale, and linearize the obtained system dynamics model to obtain a linearized model of the hybrid DC transmission system.

[0131] The analysis module is configured to calculate the eigenvalues ​​of the linearized model and the participation factors of the eigenvalues, filter the set of candidate resonance modes based on the obtained eigenvalue distribution, and the system parameters that are strongly correlated with the set of candidate resonance modes.

[0132] The discrimination module is configured to modify the corresponding system parameters of the hybrid DC transmission system, draw the system characteristic root locus, determine whether mode resonance occurs and determine the resonance intensity of the mode resonance; if the resonance intensity is greater than the set threshold, the system is determined to be unstable, the system parameters at the resonance point are recorded, and the instability discrimination of the hybrid DC transmission system is completed.

[0133] The detailed steps are the same as those of the hybrid DC instability discrimination method based on mode resonance provided in Example 1, and will not be repeated here.

[0134] Example 3

[0135] Embodiment 3 of this disclosure provides a computer-readable storage medium.

[0136] A computer-readable storage medium having a program stored thereon that, when executed by a processor, implements the steps of the hybrid DC instability discrimination method based on mode resonance as described in Embodiment 1 of this disclosure.

[0137] The detailed steps are the same as those of the hybrid DC instability discrimination method based on mode resonance provided in Example 1, and will not be repeated here.

[0138] Example 4

[0139] Embodiment 4 of this disclosure provides an electronic device.

[0140] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the hybrid DC instability discrimination method based on mode resonance as described in Embodiment 1 of this disclosure.

[0141] The detailed steps are the same as those of the hybrid DC instability discrimination method based on mode resonance provided in Example 1, and will not be repeated here.

[0142] While the specific embodiments of this disclosure have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of this disclosure. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of this disclosure are still within the scope of protection of this disclosure.

Claims

1. A hybrid DC instability discrimination method based on mode resonance, characterized in that, include: A full-order state-space model of the hybrid DC transmission system is established. Based on the singular perturbation identification of time scale differences, a system dynamics model of the DC control system under the time scale is constructed. The obtained system dynamics model is linearized to obtain a linearized model of the hybrid DC transmission system. Calculate the eigenvalues ​​of the linearized model and the participation factors of the eigenvalues, and screen the set of candidate resonance modes and the system parameters strongly correlated with the set of candidate resonance modes based on the distribution of the obtained eigenvalues. Modify the system parameters of the hybrid DC transmission system, plot the root locus of the system's characteristic roots, determine whether mode resonance occurs, and determine the resonance intensity of the mode resonance. If the resonance intensity is greater than the set threshold, the system is determined to be unstable. The system parameters at the resonance point are recorded to complete the instability judgment of the hybrid DC transmission system. The hybrid DC transmission system includes a grid-commutated high-voltage DC transmission system and a voltage source converter high-voltage DC transmission system; Using the variables of the DC inverter-side system control loop and the acquired parameters of the hybrid DC transmission system, a full-order state-space model of the hybrid DC transmission system is constructed, namely... ;in, x The state variables of the hybrid DC transmission system include the state variables of the control loops on the inverter side of the grid-commutated HVDC transmission system and the inverter side of the voltage source converter HVDC transmission system, the filter capacitor voltage and inductor current on the inverter side of the grid-commutated HVDC transmission system, the AC grid capacitor voltage and inductor current, and the state variables of the synchronous generator. u Input variables to the system, y Output variables for the system; The steps for constructing the system dynamics model of the DC control system on the time scale are as follows: Based on the time scale of the DC control system, the full-order state-space model of the hybrid DC transmission system is dynamically divided into fast dynamics and slow dynamics, and a singular perturbation standard model is constructed. ,in, x s For state variables with slow dynamic characteristics, x f For state variables with fast dynamic characteristics, For singular perturbation parameters, t For time; make The fast dynamics are described by quasi-steady-state equations, i.e. That is, transforming the model into The transformed model is the system dynamics model of the DC control system on the time scale; The specific process for determining whether mode resonance occurs and determining the intensity of mode resonance is as follows: If two eigenvalues ​​of the system state space matrix first approach each other as the system parameters change unidirectionally, and after they are close to coinciding, the motion directions of the two eigenvalues ​​both turn by about 90°, and then the two eigenvalues ​​continue to move in opposite directions, and the motion direction of one of the eigenvalues ​​is the direction of damping reduction, then it is judged that mode resonance has occurred. When mode resonance occurs, the position of the characteristic roots, system parameters, and the shortest distance between characteristic roots in the characteristic root trajectory of the resonance mode are recorded to determine the resonance mode of the hybrid DC transmission system and to determine that the system will become unstable under the recorded system parameter changes. The resonance intensity is evaluated by the shortest distance between characteristic roots. If no mode resonance occurs, select other parameters from the system parameter set to draw the system eigenvalue trajectory until the search for all parameters in the system parameter set is completed.

2. The hybrid DC instability discrimination method based on mode resonance as described in claim 1, characterized in that, The obtained system dynamics model is linearized to obtain a linearized model of the hybrid DC transmission system, including the following steps: Solve for the steady-state point of the system dynamics model of the DC control system under the rated parameters on the time scale; Linearizing the system dynamics model of the DC control system at the steady-state point on the time scale yields the linearized model, which is... ;in, Let A be the infinitesimal increment of the state variable, and let A be the system state space matrix.

3. The hybrid DC instability discrimination method based on mode resonance as described in claim 2, characterized in that, The calculation of the eigenvalues ​​and participation factors of the linearized model, the selection of a set of candidate resonance modes based on the distribution of the obtained eigenvalues, and the determination of system parameters strongly correlated with the set of candidate resonance modes, includes the following steps: Calculate the eigenvalues ​​of the system state space matrix at the steady state point; based on the distribution of the eigenvalues ​​and the participation factors, select eigenvalues ​​of the same order of magnitude that are strongly correlated with common system parameters as the set of candidate resonance modes, and use the strongly correlated common system parameters as the set of system parameters.

4. The hybrid DC instability discrimination method based on mode resonance as described in claim 3, characterized in that, Modifying the system parameters of a hybrid DC transmission system and plotting the root locus of the system's characteristic roots includes the following steps: Modify the parameters in the system parameter set, plot the curves of the eigenvalues ​​in the candidate resonance mode set as the parameters change in the complex plane, and complete the plotting of the system eigenvalue trajectories.

5. A hybrid DC instability discrimination system based on mode resonance, employing the hybrid DC instability discrimination method based on mode resonance as described in any one of claims 1-4, characterized in that, include: The module is configured to establish a full-order state-space model of the hybrid DC transmission system, identify time-scale differences based on singular perturbations, construct a system dynamics model of the DC control system under the time scale, and linearize the obtained system dynamics model to obtain a linearized model of the hybrid DC transmission system. The analysis module is configured to calculate the eigenvalues ​​of the linearized model and the participation factors of the eigenvalues, filter the set of candidate resonance modes based on the obtained eigenvalue distribution, and the system parameters that are strongly correlated with the set of candidate resonance modes. The discrimination module is configured to modify the system parameters of the hybrid DC transmission system, draw the root locus of the system characteristic roots, determine whether mode resonance occurs and determine the resonance intensity of the mode resonance; if mode resonance occurs and the resonance intensity is greater than a set threshold, the system is determined to be unstable, the system parameters at the resonance point are recorded, and the instability discrimination of the hybrid DC transmission system is completed.

6. A computer-readable storage medium having a program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps mentioned in the hybrid DC instability discrimination method based on mode resonance as described in any one of claims 1-4.

7. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps mentioned in the hybrid DC instability discrimination method based on mode resonance as described in any one of claims 1-4.

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