Micro-grid distributed secondary control method and system based on virtual synchronous machine

Abstract

The invention discloses a micro-grid distributed secondary control method and system based on a virtual synchronous machine, which is applied to the technical field of micro-grid control, and comprises the following steps: designing a micro-grid primary control strategy based on the virtual synchronous machine, and combining a speed regulator equation of the virtual synchronous machine to obtain a micro-grid secondary control strategy; establishing a micro-grid distributed secondary control model based on the virtual synchronous machine; designing a linearized microgrid distributed secondary control strategy based on the virtual synchronous machine based on a deterministic equivalence principle by considering the nonlinear characteristic of the virtual synchronous machine; based on a deterministic equivalence principle and a Lyapunov theory, the accuracy of frequency recovery of the linearized microgrid distributed secondary control strategy based on the virtual synchronous machine is proved. According to the method, inertia support is provided, communication and computing resources are remarkably reduced, and safe and stable operation of the micro-grid is facilitated.

Description

Technical Field

[0001] The present invention relates to the field of microgrid control technology, and in particular to a microgrid distributed secondary control method and system based on a virtual synchronous machine. Background Art

[0002] As large-scale renewable energy is integrated into microgrids, the inertia of the power grid drops sharply, posing a huge challenge to power quality. Traditional droop control strategies will lead to greater frequency deviations, threatening the operation of the system, thus seriously deteriorating power quality, while traditional centralized control requires the central controller to communicate with each renewable energy one by one, resulting in unnecessary communication and computing burdens.

[0003] Therefore, how to provide a microgrid distributed secondary control method and system based on virtual synchronous machine that can provide inertia support for microgrid, reduce the frequency change rate and response time under load switching, and significantly reduce communication and computing resources is an urgent problem to be solved by technicians in this field. Summary of the invention

[0004] In view of this, the present invention proposes a microgrid distributed secondary control method and system based on virtual synchronous machine.

[0005] In order to achieve the above object, the present invention adopts the following technical solution:

[0006] A microgrid distributed secondary control method based on a virtual synchronous machine, comprising:

[0007] Step 1: Design a microgrid primary control strategy based on virtual synchronous machine, and combine the speed regulator equation of virtual synchronous machine to establish a microgrid distributed secondary control model based on virtual synchronous machine;

[0008] Step 2: Considering the nonlinear characteristics of the virtual synchronous machine, based on the deterministic equivalence principle, a linearized distributed secondary control strategy for the microgrid based on the virtual synchronous machine is designed;

[0009] Step 3: Based on the deterministic equivalence principle and Lyapunov theory, the accuracy of the linearized virtual synchronous machine-based microgrid distributed secondary control strategy for frequency recovery is proved.

[0010] Optionally, in step 1, the primary control strategy of the microgrid based on the virtual synchronous machine is as follows:

[0011]

[0012] Among them, P in (t), P i (t) are the mechanical input active power and output active power of the virtual synchronous machine i respectively; J Mi , DMi are the moment of inertia and damping coefficient of the virtual synchronous machine i respectively; ω i (t),ω ni (t) are the output frequency and frequency setting value of virtual synchronous machine i respectively; is the measured angular frequency of the virtual synchronous machine i.

[0013] Optionally, in step 1, the speed regulator equation of the virtual synchronous machine is as follows:

[0014]

[0015] Among them, k ωi is the adjustment coefficient; ω i (t),ω ni (t) are the output frequency and frequency setting value of virtual synchronous machine i respectively; P in (t) is the mechanical input active power of the virtual synchronous machine i; is the rated active power of the virtual synchronous machine i.

[0016] Optionally, in step 1, a microgrid distributed secondary control model based on a virtual synchronous machine is as follows:

[0017]

[0018] Among them, θ i (t) is the phase of virtual synchronous machine i; ω i (t),ω ni (t) are the output frequency and frequency setting value of virtual synchronous machine i respectively; J i =J Mi ω ni (t), is the improved moment of inertia of the virtual synchronous machine i; D i =k ωi +D Mi , is the improved damping coefficient of virtual synchronous machine i; J Mi , D Mi are the moment of inertia and damping coefficient of the virtual synchronous machine i respectively; k ωi is the adjustment coefficient; is the rated active power of virtual synchronous machine i; P i (t) is the mechanical output active power of the virtual synchronous machine i; Ω i (t) are the error tracking auxiliary control coefficient and the auxiliary frequency control coefficient of the virtual synchronous machine i respectively;

[0019] ω ni (t), as follows:

[0020]

[0021] in, is the derivative of the quadratic compensation;

[0022] ψi(t), as follows:

[0023]

[0024] Optionally, in step 2, the distributed secondary control strategy of the microgrid based on the virtual synchronous machine is linearized as follows:

[0025]

[0026] Among them, z i (t) is the estimation error; ω i (t) is the estimated value; ω i (t) is the output frequency of virtual synchronous machine i; is the control variable for reference value tracking; Ω i (t) is the error tracking auxiliary control coefficient of virtual synchronous machine i; γ i is the control gain; ψ i (t), as follows:

[0027]

[0028] Among them, J i =J Mi ω ni (t), is the improved moment of inertia of the virtual synchronous machine i; D i =k ωi +D Mi , is the improved damping coefficient J of virtual synchronous machine i Mi , D Mi are the moment of inertia and damping coefficient of the virtual synchronous machine i respectively; k ωi is the adjustment coefficient; is the rated active power of virtual synchronous machine i; P i (t) is the mechanical output active power of the virtual synchronous machine i; ω ni (t) is the frequency setting value of virtual synchronous machine i;

[0029] as follows:

[0030]

[0031] Among them, σ ω is the control gain; i (t) is the auxiliary control variable;

[0032] λ i (t), as follows:

[0033]

[0034] Among them, N i is the set of neighbors of virtual synchronization machine i; a ij is the connection gain; g i0 =1 means the virtual synchronous machine i is connected to the reference value; is the frequency reference value; βi is the consensus control gain;

[0035] as follows:

[0036]

[0037] Among them, i=1, 2,…, n.

[0038] Optionally, in step 3, based on the deterministic equivalence principle and Lyapunov theory, the accuracy of the frequency recovery of the linearized microgrid distributed secondary control strategy based on virtual synchronous machines is proved, specifically:

[0039] Step 3.1: Prove the frequency ω i (t) approaches the frequency estimate

[0040] Step 3.2: Justify the frequency estimate Approaching the frequency reference value

[0041] Optionally, in step 3.1, prove that the frequency ω i (t) approaches the frequency estimate Specifically:

[0042] Derivative estimation error z i (t), as follows:

[0043]

[0044] Define the Lyapunov function V1(t) as follows:

[0045]

[0046] Where z = [z1, z2, …, z n ] T ; T is transpose;

[0047] Deriving the Lyapunov function V1(t), we get:

[0048]

[0049] in, γi is the control gain; In parameter form;

[0050] When γ i >0 when satisfied, Frequencyω i (t) approaches the frequency estimate

[0051] Optionally, in step 3.2, justify the frequency estimate Approaching the frequency reference value Specifically:

[0052] definition χ i (t) as follows:

[0053]

[0054]

[0055] The linearized distributed secondary control strategy of the microgrid based on virtual synchronous machine is expressed in matrix form as follows:

[0056]

[0057] Among them, ω is in matrix form; L+B is the matrix form of the connection status; In matrix form;

[0058] Define the Lyapunov function V2(t) as follows:

[0059]

[0060] Among them, χ = [χ1, χ2,…, χ N ] T ;

[0061] Deriving the Lyapunov function V2(t), we get:

[0062]

[0063] Based on χ=ω and (L+B) T =(L+B), we get:

[0064]

[0065] Zoom get:

[0066]

[0067] Since the convergence parameter μi satisfies and μi>1, we get:

[0068]

[0069] Strictly negative semidefinite, frequency estimate Approaching the frequency reference value

[0070] The present invention also provides a microgrid distributed secondary control system based on a virtual synchronous machine using a microgrid distributed secondary control method based on a virtual synchronous machine, comprising:

[0071] Microgrid distributed secondary control model establishment module based on virtual synchronous machine: used to design the microgrid primary control strategy based on virtual synchronous machine, and combine the speed regulator equation of virtual synchronous machine to establish the microgrid distributed secondary control model based on virtual synchronous machine;

[0072] Linearized microgrid distributed secondary control strategy design module based on virtual synchronous machine: used to consider the nonlinear characteristics of virtual synchronous machine and design linearized microgrid distributed secondary control strategy based on virtual synchronous machine based on the deterministic equivalence principle;

[0073] Frequency recovery accuracy proof module: used to prove the accuracy of frequency recovery of the linearized microgrid distributed secondary control strategy based on virtual synchronous machine based on the deterministic equivalence principle and Lyapunov theory.

[0074] It can be seen from the above technical solutions that compared with the prior art, the present invention proposes a distributed secondary control method and system for a microgrid based on a virtual synchronous machine. On the basis of constructing a virtual synchronous machine model, the present invention designs a distributed secondary control strategy based on a virtual synchronous machine to provide inertia support for the operation of the microgrid and reduce the frequency change rate and response time under load switching. Based on the traditional centralized communication strategy, the present invention designs a distributed control strategy to significantly reduce communication and computing resources. In summary, compared with the traditional centralized secondary control strategy, the present invention provides inertia support, significantly reduces communication and computing resources, and helps the microgrid to operate safely and stably. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0076] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0077] Figure 2 It is a schematic diagram of the structure of the isolated island microgrid system of the present invention.

[0078] Figure 3 It is a schematic diagram of the frequencies of each virtual synchronous machine under the distributed secondary control strategy of the microgrid based on virtual synchronous machine of the present invention.

[0079] Figure 4 It is a schematic diagram of the active power of each virtual synchronous machine under the distributed secondary control strategy of the microgrid based on virtual synchronous machine of the present invention. DETAILED DESCRIPTION

[0080] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0081] Embodiment 1:

[0082] Embodiment 1 of the present invention discloses a microgrid distributed secondary control method and system based on a virtual synchronous machine.

[0083] In order to achieve the above object, the present invention adopts the following technical solution:

[0084] A microgrid distributed secondary control method based on a virtual synchronous machine, comprising:

[0085] Step 1: Design a microgrid primary control strategy based on virtual synchronous machines to provide inertia support for microgrid operation and achieve rapid balancing of each virtual synchronous machine under load changes. Combined with the speed regulator equation of the virtual synchronous machine, a microgrid distributed secondary control model based on virtual synchronous machines is established to provide inertia support for microgrid operation and reduce instantaneous frequency offset.

[0086] The primary control strategy of the microgrid based on virtual synchronous machine is as follows:

[0087]

[0088] Among them, P in (t), P i (t) are the mechanical input active power and output active power of the virtual synchronous machine i respectively; J Mi , D Mi are the moment of inertia and damping coefficient of the virtual synchronous machine i respectively; ω i (t),ω ni (t) are the output frequency and frequency setting value of virtual synchronous machine i respectively; is the measured angular frequency of the virtual synchronous machine i, where

[0089] The speed regulator equation of the virtual synchronous machine is as follows:

[0090]

[0091] Among them, k ωi is the adjustment coefficient; ω i (t),ω ni (t) are the output frequency and frequency setting value of virtual synchronous machine i respectively; P in (t) is the mechanical input active power of the virtual synchronous machine i; is the rated active power of the virtual synchronous machine i.

[0092] The distributed secondary control model of microgrid based on virtual synchronous machine is as follows:

[0093]

[0094] Among them, θ i (t) is the phase of virtual synchronous machine i; ω i (t),ω ni (t) are the output frequency and frequency setting value of virtual synchronous machine i respectively; J i =J Mi ω ni (t), is the improved moment of inertia of the virtual synchronous machine i; D i =k ωi +D Mi , is the improved damping coefficient of virtual synchronous machine i; J Mi , D Mi are the moment of inertia and damping coefficient of the virtual synchronous machine i respectively; k ωi is the adjustment coefficient; is the rated active power of virtual synchronous machine i; P i (t) is the mechanical output active power of the virtual synchronous machine i; Ω i (t) are the error tracking auxiliary control coefficient and the auxiliary frequency control coefficient of the virtual synchronous machine i respectively;

[0095] Definition of secondary compensation dP i (t), as follows:

[0096]

[0097] Derivative of the secondary compensation dP i (t), as follows:

[0098]

[0099] definition Therefore, the frequency setting value ω ni (t), as follows:

[0100]

[0101]

[0102] in, is the derivative of the quadratic compensation;

[0103] ψi(t), as follows:

[0104]

[0105] Step 2: Considering the nonlinear characteristics of the virtual synchronous machine, based on the deterministic equivalence principle, a linearized distributed secondary control strategy for the microgrid based on the virtual synchronous machine is designed to achieve accurate frequency recovery. Among them, considering the nonlinear characteristics of the virtual synchronous machine, the deterministic equivalence principle is used to realize the linearization of the virtual synchronous machine, and the distributed frequency recovery control strategy of the virtual synchronous machine is designed to restore the frequency of each virtual synchronous machine to the rated reference value.

[0106] The secondary frequency control objective is to restore the frequency of each virtual synchronous machine to the frequency reference value, as follows:

[0107]

[0108] Wherein, i=1, 2, ..., n; is the frequency reference value.

[0109] Considering the nonlinear characteristics of the virtual synchronous machine, the deterministic equivalence principle is used to realize the linearization of the virtual synchronous machine. The linearization of the distributed secondary control strategy of the microgrid based on the virtual synchronous machine is as follows:

[0110]

[0111] Among them, z i (t) is the estimation error; ω i (t) is the estimated value; ω i (t) is the output frequency of virtual synchronous machine i; is the control variable for reference value tracking; Ω i (t) is the error tracking auxiliary control coefficient of virtual synchronous machine i; γ i is the control gain; ψ i (t), as follows:

[0112]

[0113] Among them, Ji =J Mi ω ni (t), is the improved moment of inertia of the virtual synchronous machine i; D i =k ωi +D Mi , is the improved damping coefficient J of virtual synchronous machine i Mi , D Mi are the moment of inertia and damping coefficient of the virtual synchronous machine i respectively; k ωi is the adjustment coefficient; is the rated active power of virtual synchronous machine i; P i (t) is the mechanical output active power of the virtual synchronous machine i; ω ni (t) is the frequency setting value of virtual synchronous machine i;

[0114] as follows:

[0115]

[0116] Among them, σ ω is the control gain; i (t) is the auxiliary control variable;

[0117] λ i (t), as follows:

[0118]

[0119] Among them, N i is the set of neighbors of virtual synchronization machine i; a ij is the connection gain; g i0 =1 means the virtual synchronous machine i is connected to the reference value; is the frequency reference value; βi is the consensus control gain;

[0120] as follows:

[0121]

[0122] Among them, i=1, 2,…, n.

[0123] Step 3: Based on the deterministic equivalence principle and Lyapunov theory, the accuracy of the linearized virtual synchronous machine-based microgrid distributed secondary control strategy for frequency recovery is proved to provide inertia support.

[0124] Based on the deterministic equivalence principle and Lyapunov theory, the accuracy of the linearized virtual synchronous machine-based microgrid distributed secondary control strategy for frequency recovery is proved, specifically:

[0125] Step 3.1: Prove the frequency ω i(t) approaches the frequency estimate

[0126] Proof frequency ω i (t) approaches the frequency estimate Specifically:

[0127] Derivative estimation error z i (t), as follows:

[0128]

[0129] Define the Lyapunov function V1(t) as follows:

[0130]

[0131] Where z = [z1, z2, …, z n ] T ; T is transpose;

[0132] Deriving the Lyapunov function V1(t), we get:

[0133]

[0134] in, γ i To control the gain; It is a parameter form, which is for the convenience of writing;

[0135] When γ i >0 when satisfied, Frequencyω i (t) approaches the frequency estimate

[0136] Step 3.2: Justify the frequency estimate Approaching the frequency reference value

[0137] Proving the frequency estimate Approaching the frequency reference value Specifically:

[0138] definition χ i (t) as follows:

[0139]

[0140] The linearized distributed secondary control strategy of the microgrid based on virtual synchronous machine is expressed in matrix form as follows:

[0141]

[0142] Among them, ω is in matrix form; L+B is the matrix form of the connection status; In matrix form;

[0143] Define the Lyapunov function V2(t) as follows:

[0144]

[0145] Among them, χ = [χ1, χ2,…, χ N ] T ;

[0146] Deriving the Lyapunov function V2(t), we get:

[0147]

[0148] Based on χ=ω and (L+B) T =(L+B), we get:

[0149]

[0150] Zoom get:

[0151]

[0152] Since the convergence parameter μi satisfies and μi>1, we get:

[0153]

[0154] Strictly negative semidefinite, frequency estimate Approaching the frequency reference value

[0155] Embodiment 2:

[0156] Embodiment 2 of the present invention discloses a specific application of a microgrid distributed secondary control method based on a virtual synchronous machine, as follows:

[0157] Island microgrid systems, such as Figure 2 The system parameters are shown in Table 1.

[0158] Table 1 Island microgrid system parameters

[0159]

[0160] In order to verify the effectiveness of the proposed distributed secondary control strategy for microgrids based on virtual synchronous machines, the simulation process is designed as follows:

[0161] 1) t = 0s, the microgrid enters the island operation mode;

[0162] 2) t = 1.5s, using the proposed distributed secondary control strategy for microgrids based on virtual synchronous machines;

[0163] 3) t = 4s, load 1 increases by 3kW;

[0164] 4) t=6s, load 1 reduces load by 3kW.

[0165] The total simulation time is 8s.

[0166] The schematic diagrams of the frequency and active power of each virtual synchronous machine under the distributed secondary control strategy of the microgrid based on virtual synchronous machine proposed in the present invention are shown as follows: Figure 3 ,like Figure 4 As shown. It can be seen that during the period of 0–1.5s, the output frequency of each virtual synchronous machine is lower than 50Hz. When t=1.5s, the distributed secondary control strategy of the microgrid based on the virtual synchronous machine proposed in the present invention is used, and the frequency of each virtual synchronous machine is accurately restored to 50Hz, and active power distribution is achieved at the same time. This performance verifies the effectiveness of the distributed secondary control strategy of the microgrid based on the virtual synchronous machine proposed in the present invention.

[0167] Embodiment 3:

[0168] Embodiment 3 of the present invention discloses a microgrid distributed secondary control system based on a virtual synchronous machine using a microgrid distributed secondary control method based on a virtual synchronous machine, comprising:

[0169] Microgrid distributed secondary control model establishment module based on virtual synchronous machine: used to design the microgrid primary control strategy based on virtual synchronous machine, and combine the speed regulator equation of virtual synchronous machine to establish the microgrid distributed secondary control model based on virtual synchronous machine;

[0170] Linearized microgrid distributed secondary control strategy design module based on virtual synchronous machine: used to consider the nonlinear characteristics of virtual synchronous machine and design linearized microgrid distributed secondary control strategy based on virtual synchronous machine based on the deterministic equivalence principle;

[0171] Frequency recovery accuracy proof module: used to prove the accuracy of frequency recovery of the linearized microgrid distributed secondary control strategy based on virtual synchronous machine based on the deterministic equivalence principle and Lyapunov theory.

[0172] The embodiment of the present invention discloses a distributed secondary control method and system for a microgrid based on a virtual synchronous machine. On the basis of constructing a virtual synchronous machine model, the present invention designs a distributed secondary control strategy based on a virtual synchronous machine to provide inertia support for the operation of the microgrid and reduce the frequency change rate and response time under load switching. Based on the traditional centralized communication strategy, the present invention designs a distributed control strategy to significantly reduce communication and computing resources. In summary, compared with the traditional centralized secondary control strategy, the present invention provides inertia support, significantly reduces communication and computing resources, and helps the microgrid to operate safely and stably.

[0173] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0174] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A distributed secondary control method for a microgrid based on a virtual synchronous machine, characterized in that: include: Step 1: Design a primary control strategy for a microgrid based on a virtual synchronous machine, and establish a distributed secondary control model for a microgrid based on a virtual synchronous machine by combining the speed regulator equation of the virtual synchronous machine; Step 2: Considering the nonlinear characteristics of the virtual synchronous machine, based on the deterministic equivalence principle, a linearized distributed secondary control strategy for the microgrid based on the virtual synchronous machine is designed; Step 3: Based on the deterministic equivalence principle and Lyapunov theory, the accuracy of the linearized virtual synchronous machine-based microgrid distributed secondary control strategy for frequency recovery is proved.

2. A microgrid distributed secondary control method based on virtual synchronous machine according to claim 1, characterized in that: In step 1, the primary control strategy of the microgrid based on the virtual synchronous machine is as follows: Among them, P in (t), P i (t) are the mechanical input active power and output active power of the virtual synchronous machine i respectively; J Mi , D Mi are the moment of inertia and damping coefficient of the virtual synchronous machine i respectively; ω i (t),ω ni (t) are the output frequency and frequency setting value of virtual synchronous machine i respectively; is the measured angular frequency of the virtual synchronous machine i.

3. A microgrid distributed secondary control method based on virtual synchronous machine according to claim 1, characterized in that: In step 1, the speed regulator equation of the virtual synchronous machine is as follows: Among them, k ωi is the adjustment coefficient; ω i (t),ω ni (t) are the output frequency and frequency setting value of virtual synchronous machine i respectively; P in (t) is the mechanical input active power of the virtual synchronous machine i; is the rated active power of the virtual synchronous machine i.

4. A microgrid distributed secondary control method based on virtual synchronous machine according to claim 1, characterized in that: In step 1, the distributed secondary control model of the microgrid based on the virtual synchronous machine is as follows: Among them, θ i (t) is the phase of virtual synchronous machine i; ω i (t),ω ni (t) are the output frequency and frequency setting value of virtual synchronous machine i respectively; J i =J Mi ω ni (t), is the improved moment of inertia of the virtual synchronous machine i; D i =k ωi +D Mi , is the improved damping coefficient of virtual synchronous machine i; J Mi , D Mi are the moment of inertia and damping coefficient of the virtual synchronous machine i respectively; k ωi is the adjustment coefficient; is the rated active power of virtual synchronous machine i; P i (t) is the mechanical output active power of the virtual synchronous machine i; Ω i (t) are the error tracking auxiliary control coefficient and the auxiliary frequency control coefficient of the virtual synchronous machine i respectively; ω ni (t), as follows: in, is the derivative of the quadratic compensation; ψ i (t), as follows:

5. A microgrid distributed secondary control method based on virtual synchronous machine according to claim 1, characterized in that: In step 2, the distributed secondary control strategy of the microgrid based on virtual synchronous machine is linearized as follows: Among them, z i (t) is the estimation error; ω i (t) is the estimated value; ω i (t) is the output frequency of virtual synchronous machine i; is the control variable for reference value tracking; Ω i (t) is the error tracking auxiliary control coefficient of virtual synchronous machine i; γ i is the control gain; ψ i (t), as follows: Among them, J i =J Mi ω ni (t), is the improved moment of inertia of the virtual synchronous machine i; D i =k ωi +D Mi , is the improved damping coefficient J of virtual synchronous machine i Mi , D Mi are the moment of inertia and damping coefficient of the virtual synchronous machine i respectively; K ωi is the adjustment coefficient; is the rated active power of virtual synchronous machine i; P i (t) is the mechanical output active power of the virtual synchronous machine i; ω ni (t) is the frequency setting value of virtual synchronous machine i; as follows: Among them, σ ω is the control gain; i (t) is the auxiliary control variable; λ i (t), as follows: Among them, N i is the set of neighbors of virtual synchronization machine i; a ij is the connection gain; g i0 =1 means that the virtual synchronous machine i is connected to the reference value; is the frequency reference value; β i Control gains for consensus; as follows: Among them, i=1, 2,…, n.

6. A microgrid distributed secondary control method based on virtual synchronous machine according to claim 5, characterized in that: In step 3, based on the deterministic equivalence principle and Lyapunov theory, the accuracy of the linearized virtual synchronous machine-based microgrid distributed secondary control strategy for frequency recovery is proved, specifically: Step 3.1: Prove the frequency ω i (t) approaches the frequency estimate Step 3.2: Justify the frequency estimate Approaching the frequency reference value 7. A microgrid distributed secondary control method based on virtual synchronous machine according to claim 6, characterized in that: In step 3.1, prove that the frequency ω i (t) approaches the frequency estimate Specifically: Derivative estimation error z i (t), as follows: Define the Lyapunov function V1(t) as follows: where z=[z1,z2,…,z n ] T ; T is transpose; Deriving the Lyapunov function V1(t), we get: in, γ i To control the gain; In parameter form; When γ i >0 satisfies, Frequencyω i (t) approaches the frequency estimate 8. A microgrid distributed secondary control method based on virtual synchronous machine according to claim 6, characterized in that: In step 3.2, prove that the frequency estimate Approaching the frequency reference value Specifically: definition χ i (t),θ i (t), as follows: The linearized distributed secondary control strategy of the microgrid based on virtual synchronous machine is expressed in matrix form as follows: Wherein, ω is in matrix form; θ = -(L+B)χ; L+B is the matrix form of the connection status; In matrix form; Define the Lyapunov function V2(t) as follows: Where, x=[x1,x2,…,x N ] T ; Deriving the Lyapunov function V2(t), we get: Based on χ=ω and (L+B) T =(L+B), we get: Zoom get: Since the convergence parameter μ i satisfy and μ i >1, we get: Strictly negative semidefinite, frequency estimate Approaching the frequency reference value 9. A microgrid distributed secondary control system based on a virtual synchronous machine using a microgrid distributed secondary control method based on a virtual synchronous machine as described in any one of claims 1 to 8, characterized in that: include: A microgrid distributed secondary control model establishment module based on a virtual synchronous machine: used to design a microgrid primary control strategy based on a virtual synchronous machine, and to establish a microgrid distributed secondary control model based on a virtual synchronous machine in combination with a speed regulator equation of the virtual synchronous machine; Linearized virtual synchronous machine-based microgrid distributed secondary control strategy design module: used to consider the nonlinear characteristics of the virtual synchronous machine and design a linearized virtual synchronous machine-based microgrid distributed secondary control strategy based on the deterministic equivalence principle; Frequency recovery accuracy proof module: used to prove the accuracy of frequency recovery of the linearized microgrid distributed secondary control strategy based on virtual synchronous machine based on the deterministic equivalence principle and Lyapunov theory.

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