Direct-current micro-grid control parameter design method controlled by virtual direct-current motor

Abstract

The invention provides a method for designing control parameters of a direct-current micro-grid controlled by a virtual direct-current motor, which belongs to the field of parameter design, and specifically comprises the following steps of: determining a control strategy, establishing a basic model of a direct-current micro-grid system, and simplifying and equivalence the model; establishing a small-signal model of the direct-current micro-grid system, and determining the inertia and damping range; establishing a large signal equivalent model of the simplified and equivalent system based on a modeling mode of an equivalent controlled current source, and obtaining the influence of control parameters on the large disturbance stability of the system; deriving a mixed potential function of the system by using a large-signal equivalent model to obtain a large-signal stability criterion of the direct-current micro-grid, analyzing the influence of control parameters on the system stability, optimizing parameters such as an energy storage unit current loop proportion parameter, an energy storage unit voltage loop proportion parameter, damping and armature resistance, and comprehensively considering the large-signal stability and small-signal stability. Therefore, the system has better dynamic response characteristics and large disturbance stability.

Description

Technical Field

[0001] The present invention relates to the field of parameter design, and in particular to a method for designing control parameters of a direct current microgrid controlled by a virtual direct current motor. Background Art

[0002] With the popularization of DC loads and power sources, DC microgrids have shown significant advantages. In the construction of microgrids, stability boundaries and stability analysis are particularly important. In order to improve the inertia and damping characteristics of traditional DC microgrids, virtual DC motor (VDCM) control is usually used for DC microgrids. Existing studies are mostly based on small signal analysis of microgrids under VDCM control to design control parameters, such as using Nyquist curves and root locus methods to explore the influence of control parameters on stability. However, small signal analysis can only be applied to stability near the equilibrium point, cannot effectively handle large disturbances, and is not applicable to large disturbance processes. Some studies have also analyzed the stability of VDCM-controlled microgrids under large disturbances based on large signals, but they are only based on large disturbance analysis. The range of control parameter values ​​of the system cannot guarantee that the system has good dynamic characteristics under small disturbances, and the mixed potential function method cannot fully reflect the influence of system control parameters.

[0003] In addition, for common large signal analysis methods, such as Lyapunov direct method, TS fuzzy model, and mixed potential function method, only the mixed potential function analysis method can give analytical stability criteria, thereby quantitatively analyzing the impact of parameters on system stability and facilitating parameter design. However, the mixed potential function simplifies the integral link during the analysis process and cannot reflect the impact of integral link parameters, such as inertia, on system stability. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention proposes a control parameter design method for a DC microgrid controlled by a virtual DC motor; firstly, a small signal analysis method is used to analyze the influence of the inertia damping of the system on the dynamic characteristics of the system through small signal analysis, and the influence of the control parameters is given from the perspective of dynamic response, and the parameter range is determined. On this basis, a large signal model of the system is derived through the modeling method of an equivalent controlled current source, so that the obtained stability criterion can reflect the influence of more control parameters on the stability as much as possible. When performing large signal modeling, the influence of parameters on the stability of the system under large disturbances is analyzed by using a mixed potential function, and the parameters are further optimized. The large signal stability and small signal stability are comprehensively considered to ensure the stability and dynamic response characteristics of the system under various disturbances.

[0005] In order to solve the above technical problems, the technical solution provided by the present invention is: A method for designing control parameters of a DC microgrid controlled by a virtual DC motor comprises the following steps: S1. Determine the control strategy, establish the basic model of the DC microgrid system, and simplify and equalize the basic model of the system; the simplified equivalent model includes a virtual DC motor controlled energy storage unit and a constant power load unit; the control strategy includes a DC bus voltage regulation link, a virtual DC generator link, and a current tracking link; S2. Based on the simplified equivalent model obtained in S1, a small signal model of the DC microgrid system is established. The small signal analysis is performed through the zero-pole and dynamic response methods to analyze the control parameter inertia. J and damping D The influence of small disturbance stability and dynamic characteristics of the system, and the determination of control parameter inertia J and damping D scope; S3. Based on the simplified equivalent system of S1, the energy storage power source is equivalent to a controlled current source, and a large signal equivalent model of the system is established; S4. Based on the large signal equivalent model established in S3, the mixed potential function of the system is preliminarily derived; S5. Using the mixed potential function of the system obtained in S4, the stability criterion of the DC microgrid under large disturbance controlled by the virtual DC motor is derived, and the current loop proportional parameters of the energy storage unit are obtained considering the voltage tracking link and the control parameters of the virtual DC motor link. k ip , Energy storage unit voltage loop ratio parameters k vp , Damping D、 Armature resistance R a The large signal stability criterion of the system is used to analyze the control parameter energy storage unit current loop proportional parameter according to the obtained stability criterion. k ip , Energy storage unit voltage loop ratio parameters k vp , Damping D、 Armature resistance R a The impact on system stability, and then optimize the control parameters of the energy storage unit current loop proportional parameters k ip , Energy storage unit voltage loop ratio parameters k vp , Damping D、 Armature resistance R a , combined with the control parameter inertia determined by S2 J and damping D , which makes the system have better dynamic response characteristics and large disturbance stability.

[0006] Preferably, In S1: The DC-DC converter used in the energy storage unit works in the BUCK circuit mode. R b is the equivalent resistance of the energy storage converter 、 L is the filter inductor of the energy storage converter, and the duty cycle of the circuit is d , the input voltage is U bat , the DC bus voltage is u dc , the simplified equivalent model is: ; in, C is the DC bus capacitor, i bat is the inductor current, i CPL is the current of the constant power load unit, t A variable describing time.

[0007] Preferably, The S2 is specifically: S2.1 establishes a small signal model of a bidirectional DC-DC converter based on the simplified equivalent model obtained in S1; S2.2 establishes a small signal model of a bidirectional DC-DC converter controlled by VDCM based on the small signal model of the bidirectional DC-DC converter obtained in S2.1; S2.3 Based on the small signal model of the bidirectional DC-DC converter controlled by VDCM obtained in S2.2, plot the different inertia J and different damping D Zero-pole diagram of the control system and analysis of relevant parameters J and D Impact on system stability; S2.4 Based on the small signal model of the bidirectional DC-DC converter controlled by VDCM obtained in S2.2, analyze the relevant parameters J and D Impact on the dynamic response characteristics of the system; S2.5 Determine the control parameter inertia based on the analysis results of S2.3 and S2.4 J and damping D range.

[0008] Preferably, The S4 is specifically: The mixed potential function of the large signal equivalent model system is as follows: The current potential function of the battery is: ; The current potential function of the load is: ; The voltage potential function of a DC capacitor is: ; Combining the above formula, the mixed potential function of the system is: ; According to the mixed potential function theory, the correct mixed potential function should satisfy the following relationship: ; in, i represents the inductor current in the circuit, v represents the capacitor voltage in the circuit, is a diagonal matrix composed of all inductors in the circuit, is a diagonal matrix composed of all the capacitors in the circuit, is the mixed potential function For current i The partial guide, is the mixed potential function Voltage v The partial derivative of Verify the obtained system mixed potential function model: ; It is concluded that the established mixed potential function is correct; According to the general expression of the mixed potential function: ; in, represents the current potential function, B ( v ) represents the voltage potential function, Determined by the circuit topology, it represents the energy of the capacitor and some non-energy storage components in the circuit; by analyzing the established system, we can get: ; therefore: ; in is the current potential function The second-order partial derivative of the current is is the voltage potential function B ( v ) with respect to the second-order partial derivative of voltage; make The minimum eigenvalue of μ 1 , The minimum eigenvalue of μ 2 ,but: ; According to the above analysis, if all voltages and currents in the system meet the following conditions: ,Right now: ; The system can run stably.

[0009] Preferably, The S4 derivation of the large signal stability criterion of the system based on virtual DC motor control is specifically: First, simplify the control strategy of the virtual DC motor part: Take mechanical torque T m As input, the reference value of the inductor current can be obtained I ref for: ; in, R a is the armature resistance, C T is the gain coefficient, is the magnetic flux, is the rated angular frequency, D For damping, J is the inertia, s Represents the integral link, T m According to the DC bus voltage regulation link, we can get: ; in, M 1 It is the integral link of the voltage regulation part of the energy storage unit. k vp The proportionality coefficient of the voltage regulation part of the energy storage unit, k vi is the integral coefficient of the voltage regulation part of the energy storage unit, U dcref is the bus voltage reference value; make I ref The integral part is M 2 According to the current tracking link, the duty cycle of the bidirectional converter can be obtained d for: ; in, k ii is the integral coefficient of the current tracking link, k ip is the proportional coefficient of the current tracking link,T e is the electromagnetic torque; In order to facilitate the use of mixed potential function analysis, the inductor current reference value is ignored. I ref The integral part, M 1 The integral model where the torque is located and the integral link where the torque is located, and substitute equation (17) into equation (1) to obtain the inductor current i bat for: ; Ignoring the time-varying term, the derivative of the inductor current with respect to the capacitor voltage can be obtained: for: ; Therefore, the stability criterion of the system is: ; in, P CPL is the power of the constant power load; When the control parameter energy storage unit current loop proportional parameter k ip , Energy storage unit voltage loop ratio parameters k vp , Damping D、 Armature resistance R a When the stability criterion shown in equation (20) is satisfied, the system can satisfy the large disturbance stability; According to formula (20), the influence of control parameters on the large disturbance stability of the system is analyzed to determine the value range of the control parameters.

[0010] A DC microgrid system controlled by a virtual DC motor is designed using the above method.

[0011] The beneficial effects of the present invention are: On the basis of traditional DC microgrid control, the present invention takes into account the influence of low inertia and weak damping of DC microgrid on system stability under traditional PI control mode, and proposes a control parameter design method for virtual DC motor control. It not only analyzes the influence of main control parameters on system stability from the perspective of small signal stability, but also uses mixed potential function to analyze the influence of system control parameters on stability during large disturbance. It comprehensively considers large signal stability and small signal stability to perform parameter optimization design, has better dynamic response characteristics and large disturbance stability, and can provide a reference for control parameter design of independent DC microgrid. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 The overall technical flow chart of the DC microgrid parameter design method controlled by VDCM of the present invention Figure 2 System topology diagram Figure 3 The block diagram of the virtual DC generator control Figure 4 This is the small signal model diagram of the bidirectional DCDC Figure 5 Small signal model diagram of the converter under VDCM control Figure 6 For different J The zero-pole diagram of the system Figure 7 For different D The zero-pole diagram of the system Figure 8 For different J Time UI Unit step response diagram of (s) Fig. 9 For different D Time UI Unit step response (s) Fig.10 for Figure 2 Equivalent model diagram of the system shown Fig.11 Simplified control block diagram of the VDCM module Fig.12 For different k vp The stability boundary diagram of the system Fig.13 For different k vp Comparison chart of system stability Fig.14 for k ip Impact diagram on system stability Fig.15 For different k ip Comparison chart of system stability Fig.16 For different k vp Down D Impact on system stability Fig.17 For different D Comparison chart of system stability Fig.18 for R a Impact on system stability Fig.19 For different R a Comparison chart of system stability DETAILED DESCRIPTION

[0013] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the following embodiments are provided only for the purpose of illustration and are not intended to limit the scope of the present invention. Those skilled in the art may make various modifications and substitutions to the present invention without departing from the purpose and spirit of the present invention.

[0014] The present invention provides a method for designing control parameters of a DC microgrid controlled by a virtual DC motor, which is specifically as follows: S1. Determine the control strategy, establish the basic model of the DC microgrid system, and simplify the basic model of the system. The simplified equivalent model includes the energy storage unit and the constant power load unit controlled by VDCM; S2. Based on the simplified equivalent model obtained in S1, a small signal model of the DC microgrid system is established, and small signal analysis is performed through zero-pole and dynamic response methods to analyze inertia. J and damping D The influence of small disturbance stability and dynamic characteristics of the system, and the determination of control parameter inertia J and damping D scope; S2 is specifically: S2.1 establishes a small signal model of a bidirectional DC-DC converter based on the simplified equivalent model obtained in S1; S2.2 establishes a small signal model of a bidirectional DC-DC converter controlled by VDCM based on the small signal model of the bidirectional DC-DC converter obtained in S2.1; S2.3 Based on the small signal model of the bidirectional DC-DC converter controlled by VDCM obtained in S2.2, plot the different inertia J and different damping D Zero-pole diagram of the control system and analysis of relevant parameters J and D Impact on system stability; S2.4 Based on the small signal model of the bidirectional DC-DC converter controlled by VDCM obtained in S2.2, analyze the relevant parameters J and D Impact on the dynamic response characteristics of the system; S2.5 Determine the control parameter inertia based on the analysis results of S2.3 and S2.4J and damping D scope; S3. Based on the simplified equivalent system of S1, the energy storage power source is equivalent to a controlled current source, and a large signal equivalent model of the system is established; S4. Based on the large signal model established in S3, the mixed potential function of the system is preliminarily derived; S5. Using the mixed potential function of the system obtained in S3, the stability criterion of the DC microgrid under large disturbance controlled by the virtual DC motor is derived, and the current loop proportional parameters of the energy storage unit are obtained considering the voltage tracking link and the control parameters of the virtual DC motor link. k ip , Energy storage unit voltage loop ratio parameters k vp , Damping D、 Armature resistance R a The large signal stability criterion of the system is used to analyze the control parameter energy storage unit current loop proportional parameter according to the obtained stability criterion. k ip , Energy storage unit voltage loop ratio parameters k vp , Damping D、 Armature resistance R a The impact on system stability, and then optimize the control parameters of the energy storage unit current loop proportional parameters k ip , Energy storage unit voltage loop ratio parameters k vp , Damping D、 Armature resistance R a , combined with the control parameter inertia determined by S2 J and damping D , which makes the system have better dynamic response characteristics and large disturbance stability, and at the same time obtains the system's limit power, providing a reference for the control parameter design of the DC microgrid.

[0015] The overall technical solution is as follows Figure 1 As shown, the specific steps are as follows: 1. Modeling the DC Microgrid The system topology studied in this invention is as follows Figure 2 As shown, it consists of a VDCM-controlled energy storage unit and a constant power load (both photovoltaic and closed-loop controlled load units can be equivalent to a constant power load).

[0016] The DC-DC converter used in the energy storage unit works in the BUCK circuit mode. R b 、L bis the energy storage converter equivalent resistance and filter resistance, and the duty cycle of the circuit is d , the input voltage is U bat , the DC bus voltage is u dc , therefore, the mathematical model of the DC-DC converter is: ; in, t The energy storage unit converter adopts virtual DC generator control. The VDCM control strategy mainly includes DC bus voltage regulation, virtual DC generation and current tracking. The control strategy model is as follows: Figure 3 shown.

[0017] 2. Small signal stability analysis of DC microgrid system In order to analyze the small signal stability of the DC microgrid controlled by VDCM, a small signal model of bidirectional DC-DC converter is established for analysis, such as Figure 4 As shown, is the DC component of the energy storage unit inductor current, is the small signal AC component of the inductor current of the energy storage unit, U bat is the DC voltage component of the battery, is the small signal AC component of the battery voltage, It is the small signal component of the energy storage unit switch duty cycle. On this basis, the small signal model of the bidirectional DC-DC converter of the VDCM control system is established as follows: Figure 5 As shown, "△" represents the change of the corresponding quantity. Based on this small signal model, the different inertias are plotted. J Time and different damping D Zero-pole diagram of the control system and analysis of relevant parameters J and D Impact on the dynamic performance of the control system.

[0018] VDCM J and D The small signal stability of the system needs to be met, so the stability of the system is analyzed based on the established bidirectional DC-DC converter small signal model of the VDCM control system.

[0019] (1) Inertia J Impact on system stability When damping D When unchanged, J When the closed-loop dominant pole of the system changes from 0.001 to 2, Figure 6 As shown. Figure 6 It can be seen that with JAs the system poles approach the imaginary axis, the system stability gradually deteriorates. J When it is close to 2, the dominant pole is close to zero, so J When taking values, try not to exceed 2, and J =0.001 or so, the system has better stability.

[0020] (2) Damping D Impact on system stability Fixed inertia J The damping coefficient is increased from 0.1 to 10, and the corresponding closed-loop dominant pole is as follows: Figure 7 As shown by Figure 7 It can be seen that with D As the dominant pole of the system gradually moves away from the imaginary axis, the stability of the system increases. D When it is larger, the system stability is better.

[0021] (3) Inertia J and damping D Impact on system dynamic response according to Figure 5 The bidirectional DC-DC converter small signal model of the VDCM control system shown in the figure can be used to derive the step response waveform of the system. Figure 8 For damping D =1, when the load current changes suddenly, different inertia J The step response waveform of the DC bus voltage is shown below. Fig. 9 Inertia J =0.01, different damping D The step response waveform of the DC bus voltage is shown in Figure 1. Figure 8 It can be seen that with the inertia J As the voltage increases, the response becomes slower and the system inertia increases, but the voltage recovery time becomes longer and the voltage drop amplitude also increases. Fig. 9 It can be seen that with D As the damping increases, the DC bus voltage develops towards over-damping, but as the damping increases, the initial drop amplitude of the DC bus voltage also increases.

[0022] Therefore, when the system is disturbed, in order to reduce the bus voltage fluctuation, the small signal stability and dynamic response characteristics of the system should be considered comprehensively. J =0.01, D =10.

[0023] 3. Large signal stability analysis of DC microgrid system The present invention uses the third theorem of the mixed potential function theory to analyze the stability of the system, and the theorem is as follows: definition represents the inductor current in the circuit, represents the capacitor voltage in the circuit, is the current potential function The second-order partial derivative of the current is is the voltage potential function B ( v ) with respect to the second-order partial derivative of voltage, that is, The minimum eigenvalue of μ 1 , The minimum eigenvalue of μ 2 , is a diagonal matrix composed of all inductors in the circuit, is a diagonal matrix composed of all the capacitors in the circuit. If Both exist: ; in represents any number greater than 0, and when When: ; , the system can run stably.

[0024] in, P i is the mixed potential function The derivative of the current, P v is the mixed potential function In order to more comprehensively reflect the influence of control parameters on system stability, the present invention equates the energy storage power supply controlled by VDCM to a controlled current source to obtain a large signal model of the system, and obtains an equivalent model of the system as follows: Fig.10 shown.

[0025] according to Fig.10 The equivalent model shown can write the mixed potential function of the system as follows: (1) The current potential function of the battery is: ; (2) Load current potential function: ; (3) Voltage potential function of DC capacitor: ; Combining the above formula, we can get the mixed potential function of the system: for: ; According to the mixed potential function theory, the correct mixed potential function should satisfy the following relationship: ; The obtained DC microgrid hybrid potential function model is verified: ; Therefore, the established mixed potential function is correct.

[0026] According to the general expression of the mixed potential function: ; in, represents the current potential function, B ( v ) represents the voltage potential function, Determined by the circuit topology, it represents the energy of the capacitor and some non-energy storage components in the circuit.

[0027] We can get: ; therefore: ; in is the current potential function The second-order partial derivative of the current is is the voltage potential function B ( v ) with respect to the voltage.

[0028] so: ; According to the previous analysis, if all voltages and currents in the system meet the following conditions: ,Right now: ; The system can run stably.

[0029] 4. Derivation of large signal stability criteria for DC microgrid systems based on VDCM control To obtain the stability criterion formula (16) It is necessary to Figure 3 The VDCM control strategy shown in the figure is analyzed. Figure 3 The control block diagram of the virtual DC motor part is simplified as follows: Take torque T m As input, the reference value of the inductor current can be obtained I ref for: ; in R a is the armature resistance, CT is the gain coefficient, is the magnetic flux, is the rated angular frequency, D For damping, J is the inertia, s Represents the integral link, T m Can be based on Figure 3 The DC bus voltage regulator module obtains: ; in, M 1 It is the integral link of the voltage regulation part of the energy storage unit. k vp The proportionality coefficient of the voltage regulation part of the energy storage unit, k vi is the integral coefficient of the voltage regulation part of the energy storage unit, U dcref is the bus voltage reference value; I ref The integral part is M 2 according to Figure 3 The current tracking module can obtain the duty cycle of the bidirectional converter d for: ; in, k ii is the integral coefficient of the current tracking link, k ip is the proportional coefficient of the current tracking link, T e is the electromagnetic torque.

[0030] In order to facilitate the use of mixed potential function analysis, the inductor current reference value is ignored. I ref The integration module, M 1 The integral model where the torque is located and the integral link where the torque is located, and substitute equation (17) into equation (1) to obtain the inductor current i bat for: ; Ignoring the time-varying terms, we can get: ; Therefore, the stability criterion of the system is: ; When the control parameters satisfy the stability criterion shown in formula (20), the system can meet the large disturbance stability. Therefore, the influence of the control parameters on the large disturbance stability of the system can be analyzed according to the above expression, so as to determine the value range of the control parameters.

[0031] Example In order to verify the correctness of the above conclusion, the present invention is based on Figure 1 The system shown is an example, and an electromagnetic transient simulation model is built on the Matlab / Simulink platform. The relevant control parameters are preliminarily determined by the previous small signal stability analysis and large signal stability analysis, and the specific parameters are shown in Table 1.

[0032] Table 1 DC microgrid system simulation and experimental parameters ; Substitute the above parameters into the stability criterion (20) and plot the proportional coefficient of the outer loop at different voltages k vp The critical stable power under the condition is compared with the critical stable power fitted by the circuit simulation results, as shown in Fig.12 shown.

[0033] According to Fig.12 It can be seen that the stability boundary obtained by the stability criterion derived by the theory of the present invention has the same change trend as the stability boundary obtained by simulation, and the curves of the two are almost coincident. Therefore, the stability criterion derived by the method of the present invention can accurately characterize the stability boundary.

[0034] like Fig.13 As shown, different k vp The comparison chart of system stability is given by Fig.13 It can be seen that under the same load disturbance, when k vp =3, the system is unstable, and when k vp When it increases to 7.5, the system is stable and the simulation results are consistent with the theory.

[0035] Draw different k ip The stability boundary of the system is Fig.14 As shown, the current tracking link proportional coefficient k ip It has almost no impact on the stability of the system. Fig.15 The simulation result of the circuit is shown in Figure 2. The load steps from 1MW to 1.65MW at 0.4 seconds. It can be seen from the simulation results that as k ipThe DC bus voltage waveform is almost unaffected by the change, and the system stability does not change, which corresponds to the result of the stability criterion.

[0036] According to the stability criterion of formula (20), the damping coefficient D The influence on system stability is not monotonic. According to the stability criterion, four groups of different k vp Plotting the damping coefficient D The influence of the system stability, such as Fig.16 As shown, in k vp When it is small, the system will D The increase in system stability improves. k vp When it is larger, as the damping D As the value of increases, the system stability decreases. And set the corresponding parameters for the simulation circuit, respectively select k vp =3 and k vp =7.5 The simulation is verified by Matlab / simulink, and the simulation waveform is as follows Fig.17 shown.

[0037] according to Fig.17 The simulation results show that in k vp =3, as the damping coefficient increases, the system gradually becomes stable. k vp =7.5, as the damping coefficient increases, the system gradually becomes unstable, which is consistent with Fig.15 Therefore, the stability criterion obtained by the present invention can correctly reflect the damping coefficient under different control parameters. D The influence on stability can be appropriately increased or decreased according to the criteria under different control parameters to improve the stability of the system, which has better universality. Fig.17 It can be seen that with D As the voltage of the system increases, the voltage drop increases during the transient process, which is the same as the result of small signal analysis.

[0038] In order to verify the influence of armature resistance on stability, we first plot the stability criterion of different armature resistances according to equation (20). R a The corresponding stable boundary is Fig.18 As shown by Fig.18 It can be seen that as the armature resistance R a The increase of , the system stability weakens.

[0039] Then verify it through simulation. The circuit simulation results are as follows Fig.19 As shown, within a certain range, as R a As the value of increases, the system gradually becomes unstable, which is consistent with the result of theoretical analysis. Therefore, by appropriately reducing R a To improve the stability of the system.

[0040] In summary, it can be appropriately increased k vp ,exist k vp When the damping coefficient D is small, k vp When the damping coefficient is large, it will decrease D And appropriately reduce the armature resistance R a To improve the large disturbance stability of the system.

[0041] The contents not described in detail in this specification belong to the prior art known to professional and technical personnel in this field.

[0042] Finally, it should be noted that the above description is only a preferred example of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for designing control parameters of a DC microgrid controlled by a virtual DC motor, characterized in that: The steps include: S1. Determine the control strategy, establish the basic model of the DC microgrid system, and simplify and equalize the basic model of the system; the simplified equivalent model includes a virtual DC motor controlled energy storage unit and a constant power load unit; the control strategy includes a DC bus voltage regulation link, a virtual DC generator link, and a current tracking link; S2. Based on the simplified equivalent model obtained in S1, a small signal model of the DC microgrid system is established. The small signal analysis is performed through the zero-pole and dynamic response methods to analyze the control parameter inertia. J and damping D The influence of small disturbance stability and dynamic characteristics of the system, and the determination of control parameter inertia J and damping D scope; S3. Based on the simplified equivalent system of S1, the energy storage power source is equivalent to a controlled current source, and a large signal equivalent model of the system is established; S4. Based on the large signal equivalent model established in S3, the mixed potential function of the system is preliminarily derived; S5. Using the mixed potential function of the system obtained in S4, the stability criterion of the DC microgrid under large disturbance controlled by the virtual DC motor is derived, and the current loop proportional parameters of the energy storage unit are obtained considering the voltage tracking link and the control parameters of the virtual DC motor link. k ip , Energy storage unit voltage loop ratio parameters k vp , Damping D、 Armature resistance The large signal stability criterion of the system is used to analyze the control parameter energy storage unit current loop proportional parameter according to the obtained stability criterion. k ip , Energy storage unit voltage loop ratio parameters k vp , Damping D、 Armature resistance The impact on system stability, and then optimize the control parameters of the energy storage unit current loop proportional parameters k ip , Energy storage unit voltage loop ratio parameters k vp , Damping D、 Armature resistance , combined with the control parameter inertia determined by S2 J and damping D , which makes the system have better dynamic response characteristics and large disturbance stability.

2. The method for designing control parameters of a DC microgrid controlled by a virtual DC motor according to claim 1, characterized in that: In S1: The DC-DC converter used in the energy storage unit works in the BUCK circuit mode. R b is the equivalent resistance of the energy storage converter 、L is the filter inductor of the energy storage converter, and the duty cycle of the circuit is d , the input voltage is U bat , the DC bus voltage is u dc , the simplified equivalent model is: ; in, C is the DC bus capacitor, i bat is the inductor current, i CPL is the current of the constant power load unit, t A variable describing time.

3. The method for designing control parameters of a DC microgrid controlled by a virtual DC motor according to claim 1, characterized in that: The S2 is specifically: S2.1 establishes a small signal model of a bidirectional DC-DC converter based on the simplified equivalent model obtained in S1; S2.2 establishes a small signal model of a bidirectional DC-DC converter controlled by VDCM based on the small signal model of the bidirectional DC-DC converter obtained in S2.1; S2.3 Based on the small signal model of the bidirectional DC-DC converter controlled by VDCM obtained in S2.2, plot the different inertia J and different damping D Zero-pole diagram of the control system and analysis of relevant parameters J and D Impact on system stability; S2.4 Based on the small signal model of the bidirectional DC-DC converter controlled by VDCM obtained in S2.2, analyze the relevant parameters J and D Impact on the dynamic response characteristics of the system; S2.5 Determine the control parameter inertia based on the analysis results of S2.3 and S2.4 J and damping D range.

4. The method for designing control parameters of a DC microgrid controlled by a virtual DC motor according to claim 2, characterized in that: The S4 is specifically: The mixed potential function of the large signal equivalent model system is as follows: The current potential function of the battery is: ; The current potential function of the load is: ; The voltage potential function of a DC capacitor is: ; Combining the above formula, the mixed potential function of the system is: ; According to the mixed potential function theory, the correct mixed potential function should satisfy the following relationship: ; in, i represents the inductor current in the circuit, v represents the capacitor voltage in the circuit, is a diagonal matrix composed of all inductors in the circuit, is a diagonal matrix composed of all capacitors in the circuit, is the mixed potential function For current i The partial guide, is the mixed potential function Voltage v The partial derivative of Verify the obtained system mixed potential function model: ; It is concluded that the established mixed potential function is correct; According to the general expression of the mixed potential function: ; in, A ( i ) represents the current potential function, B ( v ) represents the voltage potential function, Determined by the circuit topology, it represents the energy of the capacitor and some non-energy storage components in the circuit; by analyzing the established system, we can get: ; therefore: ; in is the current potential function The second-order partial derivative of the current is is the voltage potential function B ( v ) with respect to the second-order partial derivative of voltage; make The minimum eigenvalue of μ 1, The minimum eigenvalue of μ 2 ,but: ; According to the above analysis, if all voltages and currents in the system meet the following conditions: ,Right now: ; The system can run stably.

5. The method for designing control parameters of a DC microgrid controlled by a virtual DC motor according to claim 4, characterized in that: The S4 derivation of the large signal stability criterion of the system based on virtual DC motor control is specifically: First, simplify the control strategy of the virtual DC motor part: Take mechanical torque T m As input, the reference value of the inductor current can be obtained I ref for: ; in, R a is the armature resistance, C T is the gain coefficient, is the magnetic flux, is the rated angular frequency, D For damping, J is the inertia, s Represents the integral link, T m According to the DC bus voltage regulation link, we can get: ; in, M 1 is the integral link of the voltage regulation part of the energy storage unit. k vp The proportionality coefficient of the voltage regulation part of the energy storage unit, k vi is the integral coefficient of the voltage regulation part of the energy storage unit, U dcref is the bus voltage reference value; make I ref The integral part is M 2. According to the current tracking link, the duty cycle of the bidirectional converter can be obtained d for: ; in, k ii is the integral coefficient of the current tracking link, k ip is the proportional coefficient of the current tracking link, T e is the electromagnetic torque; In order to facilitate the use of mixed potential function analysis, the inductor current reference value is ignored. I ref The integral part, M 1 where the integral model and the integral link where the torque is located, and substitute equation (17) into equation (1) to obtain the inductor current i bat for: ; Ignoring the time-varying term, the derivative of the inductor current with respect to the capacitor voltage can be obtained: for: ; Therefore, the stability criterion of the system is: ; in, P CPL is the power of the constant power load; When the control parameter energy storage unit current loop proportional parameter k ip , Energy storage unit voltage loop ratio parameters k vp , Damping D、 Armature resistance R a When the stability criterion shown in equation (20) is satisfied, the system can satisfy the large disturbance stability; According to formula (20), the influence of control parameters on the large disturbance stability of the system is analyzed to determine the value range of the control parameters.

6. A DC microgrid system controlled by a virtual DC motor, characterized in that: The method is designed by any one of claims 1 to 5.

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