Distributed model predictive control method for DC microgrid considering voltage recovery and SoC balance

Abstract

The present invention provides a distributed model predictive control method for a DC microgrid that considers voltage recovery and SOC balance, comprising the following steps: determining an island DC microgrid containing a distributed power source and an energy storage system, and determining the topological structure of the island DC microgrid; constructing a bus voltage prediction model for the island DC microgrid and a SOC dynamic prediction model for the energy storage system, and predicting the bus voltage of the island DC microgrid and the SOC information of the energy storage system at a set future time; determining a current control set for bus voltage regulation and an energy storage current control set for SOC balance regulation of the energy storage system, and controlling the bus voltage of the island DC microgrid at the set future time to be consistent with the predicted bus voltage based on the control information contained in the current control set for bus voltage regulation and the energy storage current control set for SOC balance regulation of the energy storage system, and balancing the SOC of the energy storage systems of each node of the island DC microgrid.

Description

Technical Field

[0001] The present invention relates to a microgrid control method, and in particular to a DC microgrid distributed model predictive control method considering voltage recovery and SoC balance. Background Art

[0002] Microgrids can be categorized as DC microgrids, AC microgrids, and AC / DC hybrid microgrids. In comparison, DC microgrids do not require frequency considerations and are unaffected by harmonics and the skin effect, resulting in superior power quality. Furthermore, DC microgrids do not require synchronization between distributed power sources, making coordinated operation more convenient. These microgrids are being extensively studied and widely applied. Due to the high degree of randomness and uncertainty associated with renewable energy, microgrids typically require the installation of energy storage systems to maintain power balance between the source and the load. Considering the operating life of energy storage systems, overcharging and over-discharging should be avoided, and consistency in the SoC between each energy storage system is required. Therefore, there is an urgent need to explore safe, reliable, and effective coordinated control methods to achieve DC bus voltage stability and SoC balance within the energy storage system.

[0003] The most commonly used control methods for microgrids include centralized control, decentralized control, and distributed control. Distributed control combines the advantages of centralized and decentralized control, achieving information sharing and global optimization based on local information exchange. Therefore, distributed control better meets the requirements of microgrids and has attracted widespread attention and in-depth research. The hierarchical control framework for microgrids consists of three main levels, each corresponding to different response time scale requirements. The goal of primary control is to achieve dynamic regulation of power and voltage. Secondary control is used to compensate for power distribution and voltage deviations caused by primary control. Tertiary control achieves economical operation through energy management and optimized scheduling.

[0004] To achieve voltage recovery and SoC balance in islanded DC microgrids, currently used methods include distributed finite-time consensus control and distributed control based on SoC weighted adjustment. While these methods can achieve voltage recovery and SoC balance to a certain extent, they do not consider the constraints of the energy storage system's charge / discharge current. Because the control input is positively correlated with the degree of difference in the state variable, the control input will be larger when the state difference is severe and smaller when the state is close to consistency. Therefore, in the early stages of the convergence process, the energy storage system current difference is often large, which will inevitably generate surge currents. In the later stages of the convergence process, the energy storage system current difference will be very small, which will have a significant impact on the overall convergence speed. In short, existing control methods cannot balance the operational safety and convergence speed of the energy storage system.

[0005] Therefore, in order to solve the above technical problems, it is urgent to propose a new technical means. Summary of the Invention

[0006] In view of this, the purpose of the present invention is to provide a distributed model predictive control method for a DC microgrid taking into account voltage recovery and SoC balance, which can effectively avoid the existence of inrush current during the operation control process of the island DC microgrid, effectively improve the convergence speed of the entire control algorithm, and make the various energy storage systems in the microgrid well balanced, thereby effectively improving the operation stability and service life of the island DC microgrid.

[0007] The present invention provides a DC microgrid distributed model predictive control method considering voltage recovery and SoC balance, comprising the following steps:

[0008] S1. Identify an islanded DC microgrid containing distributed generation and energy storage systems, and determine the topology of the islanded DC microgrid.

[0009] S2. Construct a bus voltage prediction model for the islanded DC microgrid and a dynamic SOC prediction model for the energy storage system, and predict the bus voltage of the islanded DC microgrid and the SOC information of the energy storage system at a set future time;

[0010] S3. Determine the current control set for bus voltage regulation and the energy storage current control set for SOC balancing regulation of the energy storage system, and based on the control information contained in the current control set for bus voltage regulation and the energy storage current control set for SOC balancing regulation of the energy storage system, control the bus voltage of the island DC microgrid at a set future moment to be consistent with the predicted bus voltage, and balance the SOC of the energy storage system at each node of the island DC microgrid.

[0011] Furthermore, in step S2, the bus voltage of the island DC microgrid is predicted using the following method:

[0012] Constructing bus voltage prediction model:

[0013]

[0014] in:

[0015] V(k+p)=[v bus.1 (k+p)Lv bus.i (k+p)L v bus.n (k+p)] T (2);

[0016] V(k)=[v bus.1 (k)Lv bus.i (k)L v bus.n (k)] T (3);

[0017] V bus(k)=diag[v bus.1 (k)Lv bus.i (k)L v bus.n (k)](4);

[0018] V batt (k)=diag[v batt.1 (k)Lv batt.i (k)L v batt.n (k)](5);

[0019] I pv (k)=[i pv.1 (k)L i pv.i (k)L i pv.n (k)] T (6);

[0020] I batt (k)=[i batt.1 (k)L i batt.i (k)L i batt.n (k)] T (7);

[0021] I load (k)=[i load.1 (k)L i load.i (k)L i load.n (k)] T (8);

[0022]

[0023]

[0024] Where: Y represents the node admittance matrix, T s1 represents the model predictive control period, v bus,i (k+p) represents the bus voltage prediction value of the ith node of the island DC microgrid at time t=k+p, p represents the prediction step, i=1,2,L,n, n represents the total number of nodes in the island DC microgrid, v bus,i (k) represents the bus voltage value of the i-th node of the island DC microgrid at time t=k, v batt,i (k) represents the voltage value of the energy storage system of the i-th node of the island DC microgrid at time t=k, i pv,i (k) represents the bus output current of the i-th node of the island DC microgrid at time t=k, i batt,i (k) represents the energy storage current of the i-th node of the island DC microgrid at time t=k, i load,i (k)t = the input current of the local load of the ith node of the islanded DC microgrid at time k, C irepresents the DC bus filter capacitor of the i-th node;

[0025] Substituting equations (2) to (10) into equation (1), the final bus voltage prediction model of the islanded DC microgrid is obtained as follows:

[0026]

[0027] Furthermore, in step S2, the SOC information of the energy storage system of the island DC microgrid is predicted using the following method:

[0028] Constructing the SOC prediction model of the energy storage system:

[0029]

[0030] in:

[0031] SoC(k+p)=[SoC1(k+p)L SoC i (k+p)L SoC n (k+p)] T (13);

[0032] SoC(k)=[SoC1(k)L SoC i (k)L SoC n (k)] T (14);

[0033] I batt (k)=[i batt.1 (k)L i batt.i (k)L i batt.n (k)] T (15);

[0034]

[0035] Among them: SoC i (k+p) represents the SOC prediction value of the energy storage system of the i-th node of the island DC microgrid at time t=k+p; SoC i (k) represents the SOC value of the energy storage system of the i-th node of the island DC microgrid at time t=k; i batt,i (k) represents the current output value of the energy storage system of the i-th node of the island DC microgrid at time t=k, represents the maximum capacity of the energy storage system of the i-th node of the islanded DC microgrid;

[0036] Substitute equations (13) to (16) into equation (12) to obtain the final SOC prediction model:

[0037]

[0038] Furthermore, the current control set for bus voltage regulation is determined as follows:

[0039]

[0040] Where: i basic.i (k)=[i basic,1 (k),L,i basic,i (k),L,i basic,n (k)] T (19);

[0041] v nom represents the rated voltage value of node i, r i represents the droop coefficient of the energy storage system at the i-th node; is the control set of the secondary voltage adjustment term for bus voltage regulation, and:

[0042]

[0043] in: represents the maximum output current allowed by the energy storage system at the i-th node, represents the minimum output current allowed by the energy storage system at the i-th node, Indicates the maximum voltage deviation allowed by the microgrid system, is the voltage secondary control set interval of the energy storage system at the i-th node.

[0044] Furthermore, when the elements in the current control set for bus voltage regulation are used for bus voltage regulation control, a control cost function needs to be satisfied, where the control cost function is:

[0045]

[0046] Furthermore, the energy storage current control set for balancing regulation of the energy storage system SoC is determined as follows:

[0047]

[0048] Where: i basic.i (k)=[i basic,1 (k),L,i basic,i (k),L,i basic,n (k)] T (twenty two);

[0049] v nom represents the rated voltage value of node i, r i represents the droop coefficient of the energy storage system at the i-th node; Indicates the secondary SoC adjustment item, and:

[0050]

[0051] in: is the SoC secondary control set interval of the i-th energy storage system, represents the maximum output current allowed by the energy storage system at the i-th node, represents the minimum output current allowed by the energy storage system at the i-th node, Indicates the maximum voltage deviation allowed in the microgrid system.

[0052] Furthermore, when the elements in the energy storage current control set for SoC balancing regulation of the energy storage system are subjected to SoC balancing regulation control, a control cost function needs to be satisfied, where the control cost function is:

[0053] in:

[0054]

[0055] L(i) represents the i-th row of the Laplacian matrix L.

[0056] Furthermore, the Laplace matrix L is determined by the following method:

[0057] Based on the topological structure of the island DC microgrid, the adjacent nodes of the island DC microgrid are determined, and the adjacent nodes exchange information through the communication network. The communication network is represented by an undirected graph, and the communication weight is in is a node set, represents the edge set;

[0058] The communication neighbor nodes of node i are represented as The adjacency matrix of node i is expressed as:

[0059]

[0060] Among them: a ij Represents the communication weight, then the Laplace matrix of the undirected graph can be obtained according to the following formula:

[0061]

[0062] in: represents the degree of freedom of the communication network, then the Laplace matrix can be expressed as

[0063]

[0064] The beneficial effects of the present invention are as follows: Through the present invention, the existence of inrush current during the operation and control process of the isolated DC microgrid can be effectively avoided, and the convergence speed of the entire control algorithm can be effectively improved, and the balance of each energy storage system in the microgrid can be good, thereby effectively improving the operation stability and service life of the isolated DC microgrid. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0066] Figure 1 Flowchart of the present invention.

[0067] Figure 2 Schematic diagram of an island DC microgrid system according to a specific example of the present invention.

[0068] Figure 3 for Figure 2 The power flow diagram of node i in the specific example is shown in FIG.

[0069] Figure 4 A distributed model predictive control framework for bus voltage restoration and SoC balancing is considered for the present invention.

[0070] Figure 5 This is a working mode diagram of the energy storage converter of the present invention. DETAILED DESCRIPTION

[0071] The present invention is further described in detail below:

[0072] The present invention provides a DC microgrid distributed model predictive control method considering voltage recovery and SoC balance, comprising the following steps:

[0073] S1. Determine an island DC microgrid containing a distributed power supply and an energy storage system, and determine the topology of the island DC microgrid; the topology of the island DC microgrid system of the specific example given in the present invention is as follows Figure 2 As shown;

[0074] S2. Construct a bus voltage prediction model for the islanded DC microgrid and a dynamic SOC prediction model for the energy storage system, and predict the bus voltage of the islanded DC microgrid and the SOC information of the energy storage system at a set future time;

[0075] S3. Determine the current control set for bus voltage regulation and the energy storage current control set for SOC balancing regulation of the energy storage system, and control the bus voltage of the island DC microgrid at a set future moment to be consistent with the predicted bus voltage based on the control information contained in the current control set for bus voltage regulation and the energy storage current control set for SOC balancing regulation of the energy storage system, and balance the SOC of the energy storage systems of each node of the island DC microgrid. Through the present invention, it is possible to effectively avoid the existence of impact current during the operation control process of the island DC microgrid, and effectively improve the convergence speed of the entire control algorithm, and make the balance of each energy storage system in the microgrid good, thereby effectively improving the operation stability and service life of the island DC microgrid.

[0076] In this embodiment, in step S2, the bus voltage of the island DC microgrid is predicted using the following method:

[0077] Constructing bus voltage prediction model:

[0078]

[0079] in:

[0080] V(k+p)=[v bus.1 (k+p)Lv bus.i (k+p)L v bus.n (k+p)] T (2);

[0081] V(k)=[v bus.1 (k)Lv bus.i (k)L v bus.n (k)] T (3);

[0082] V bus (k)=diag[v bus.1 (k)Lv bus.i (k)L v bus.n (k)](4);

[0083] V batt (k)=diag[v batt.1 (k)Lv batt.i (k)L v batt.n (k)](5);

[0084] I pv (k)=[i pv.1 (k)L i pv.i (k)L i pv.n (k)] T (6);

[0085] I batt(k)=[i batt.1 (k)L i batt.i (k)L i batt.n (k)] T (7);

[0086] I load (k)=[i load.1 (k)L i load.i (k)L i load.n (k)] T (8);

[0087]

[0088]

[0089] Among them: Y node admittance matrix, T s1 Model predictive control period, v bus,i (k+p) represents the bus voltage prediction value of the ith node of the island DC microgrid at time t=k+p, p represents the prediction step, i=1,2,L,n, n represents the total number of nodes in the island DC microgrid, v bus,i (k) represents the bus voltage value of the i-th node of the island DC microgrid at time t=k, v batt,i (k) represents the voltage value of the energy storage system of the i-th node of the island DC microgrid at time t=k, i pv,i (k) represents the bus output current of the i-th node of the island DC microgrid at time t=k, i batt,i (k) represents the energy storage current of the i-th node of the island DC microgrid at time t=k, i load,i (k)t = the input current of the local load of the ith node of the islanded DC microgrid at time k, C i represents the DC bus filter capacitor of the i-th node;

[0090] Substituting equations (2) to (10) into equation (1), the final bus voltage prediction model of the islanded DC microgrid is obtained as follows:

[0091]

[0092] In the above, the bold letter parameter represents a matrix; diag[] represents a diagonal matrix.

[0093] In this embodiment, in step S2, the SOC information of the energy storage system of the island DC microgrid is predicted using the following method:

[0094] Constructing the SOC prediction model of the energy storage system:

[0095]

[0096] in:

[0097] SoC(k+p)=[SoC1(k+p)L SoC i (k+p)L SoC n (k+p)] T (13);

[0098] SoC(k)=[SoC1(k)L SoC i (k)L SoC n (k)] T (14);

[0099]

[0100] Among them: SoC i (k+p) represents the SOC prediction value of the energy storage system of the i-th node of the island DC microgrid at time t=k+p; SoC i (k) represents the SOC value of the energy storage system of the i-th node of the island DC microgrid at time t=k; i batt,i (k) represents the current output value of the energy storage system of the i-th node of the island DC microgrid at time t=k, represents the maximum capacity of the energy storage system of the i-th node of the islanded DC microgrid;

[0101] Substitute equations (13) to (16) into equation (12) to obtain the final SOC prediction model:

[0102]

[0103] In this embodiment, the current control set for bus voltage regulation is determined as follows:

[0104]

[0105] Where: i basic.i (k)=[i basic,1 (k),L,i basic,i (k),L,i basic,n (k)] T (19);

[0106] v nom represents the rated voltage value of node i, r i represents the droop coefficient of the energy storage system at the i-th node; is the control set of the secondary voltage adjustment term for bus voltage regulation, and:

[0107]

[0108] in: represents the maximum output current allowed by the energy storage system at the i-th node, represents the minimum output current allowed by the energy storage system at the i-th node, Indicates the maximum voltage deviation allowed by the microgrid system, is the voltage secondary control set interval of the energy storage system at the i-th node, where i i.basic (k) represents the primary control variable, with the energy storage system's energy storage current as the control input. All possible control inputs are given in the control set above. However, the optimal control input needs to be found, that is, to satisfy its control cost function. Specifically:

[0109] When the elements in the current control set for bus voltage regulation are used for bus voltage regulation control, the control cost function needs to be satisfied, where the control cost function is:

[0110]

[0111] In this embodiment, the energy storage current control set used for balancing regulation of the energy storage system SoC is determined by:

[0112]

[0113] Where: i basic.i (k)=[i basic,1 (k),L,i basic,i (k),L,i basic,n (k)] T (twenty two);

[0114] v nom represents the rated voltage value of node i, r i represents the droop coefficient of the energy storage system at the i-th node; Indicates the secondary SoC adjustment item, and:

[0115]

[0116] in: is the SoC secondary control set interval of the i-th energy storage system, represents the maximum output current allowed by the energy storage system at the i-th node, represents the minimum output current allowed by the energy storage system at the i-th node, Indicates the maximum voltage deviation allowed by the microgrid system. In the above, the control set gives all possible control inputs, but the optimal control input needs to be optimized, that is, to satisfy its control cost function. Specifically:

[0117] When performing SoC balancing regulation control on the elements in the energy storage current control set for SoC balancing regulation of the energy storage system, a control cost function needs to be satisfied, where the control cost function is:

[0118] in:

[0119]

[0120] L(i) represents the i-th row of the Laplacian matrix L.

[0121] Wherein: the Laplace matrix L is determined by the following method:

[0122] Based on the topological structure of the island DC microgrid, the adjacent nodes of the island DC microgrid are determined, and the adjacent nodes exchange information through the communication network. The communication network is represented by an undirected graph, and the communication weight is in is a node set, represents the edge set;

[0123] The communication neighbor nodes of node i are represented as The adjacency matrix of node i is expressed as:

[0124]

[0125] Among them: a ij Represents the communication weight, then the Laplace matrix of the undirected graph can be obtained according to the following formula:

[0126]

[0127] in: represents the degree of freedom of the communication network, then the Laplace matrix can be expressed as

[0128]

[0129] From the above and Figure 4 As can be seen from the figure, the distributed model predictive secondary control in the present invention consists of two parts: one is the outer loop MPC-I, which ensures that the bus voltage of each node can be restored; the other is the outer loop MPC-II, which ensures that the SoC of the energy storage system of each node reaches a balanced state. When both the bus voltage recovery and the SoC reaching a balanced state need to be satisfied, the control set is:

[0130]

[0131] As for the current inner loop control, it is an existing technology. The current inner loop control process is briefly described below:

[0132] The working mode of the energy storage converter is as follows: Figure 4 shown.

[0133] Among them, D and 1-D represent the switching states of the switches S1 and S2 respectively, which can be expressed as

[0134]

[0135] Assume that the energy storage is in a positive state when in discharge state, and the inductor voltage and inductor current are related reference directions. The state equation of the bidirectional DC-DC converter can be expressed as

[0136]

[0137]

[0138] Then, the current reference directions in equations (25a) and (25b) are opposite, so the two equations are equivalent. To simplify the expression, the state equation in the Boost mode is used for unification, and the output current prediction value of the energy storage system can be expressed as

[0139]

[0140] Among them, i batt.i (k) represents the output current of the i-th energy storage system at the current moment; i batt.i (k+1) represents the output current prediction value of the i-th energy storage system at the next moment; L i represents the inductance of the bidirectional DC-DC converter connected to the i-th energy storage system; T s2 Represents the control period.

[0141] When p-step prediction is used, the cost function of the i-th inner loop controller at time t = k can be designed as

[0142]

[0143] in, Indicates the current reference value calculated by the outer loop control at the current moment. batt.i (k+p) represents the predicted value of the energy storage output current.

[0144] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A distributed model predictive control method for a DC microgrid considering voltage recovery and SoC balance, characterized by: The following steps are involved: S1. Identify an islanded DC microgrid containing distributed generation and energy storage systems, and determine the topology of the islanded DC microgrid. S2. Construct a bus voltage prediction model for the islanded DC microgrid and a dynamic SOC prediction model for the energy storage system, and predict the bus voltage of the islanded DC microgrid and the SOC information of the energy storage system at a set future time; S3. Determine a current control set for bus voltage regulation and an energy storage current control set for SOC balancing regulation of the energy storage system, and control the bus voltage of the island DC microgrid at a set future time to be consistent with the predicted bus voltage based on the control information contained in the current control set for bus voltage regulation and the energy storage current control set for SOC balancing regulation of the energy storage system, and balance the SOC of the energy storage system at each node of the island DC microgrid; In step S2, the bus voltage of the island DC microgrid is predicted using the following method: Constructing bus voltage prediction model: in: V(k+p)=[v bus.1 (k+p)…v bus.i (k+p)…v bus.n (k+p)] T (2); V(k)=[v bus.1 (k)…v bus.i (k)…v bus.n (k)] T (3); V bus (k)=diag[v bus.1 (k)…v bus.i (k)…v bus.n (k)](4); V batt (k)=diag[v batt.1 (k)…v batt.i (k)…v batt.n (k)](5); I pv (k)=[i pv.1 (k)…i pv.i (k)…i pv.n (k)] T (6); I batt (k)=[i batt.1 (k)…i batt.i (k)…i batt.n (k)] T (7); I load (k)=[i load.1 (k)…i load.i (k)…i load.n (k)] T (8); Where: Y represents the node admittance matrix, T s1 represents the model predictive control period, v bus,i (k+p) represents the bus voltage prediction value of the ith node of the island DC microgrid at time t=k+p, p represents the prediction step, i=1,2,…,n, n represents the total number of nodes in the island DC microgrid, v bus,i (k) represents the bus voltage value of the i-th node of the island DC microgrid at time t=k, v batt,i (k) represents the voltage value of the energy storage system of the i-th node of the island DC microgrid at time t=k, i pv,i (k) represents the bus output current of the i-th node of the island DC microgrid at time t=k, i batt,i (k) represents the energy storage current of the i-th node of the island DC microgrid at time t=k, i load,i (k) represents the input current of the local load of the ith node of the island DC microgrid at time t=k, C i represents the DC bus filter capacitor of the i-th node; Substituting equations (2) to (10) into equation (1), the final bus voltage prediction model of the islanded DC microgrid is obtained as follows: In step S2, the SOC information of the energy storage system of the island DC microgrid is predicted using the following method: Constructing the SOC prediction model of the energy storage system: in: SoC(k+p)=[SoC1(k+p)…SoC i (k+p)…SoC n (k+p)] T (13); SoC(s)=[SoC1(s)…SoC i (k)…SoC n (s)] T (14); I batt (k)=[i batt.1 (k)…i batt.i (k)…i batt.n (k)] T (15); Among them: SoC i (k+p) represents the SOC prediction value of the energy storage system of the i-th node of the island DC microgrid at time t=k+p; SoC i (k) represents the SOC value of the energy storage system of the i-th node of the island DC microgrid at time t=k; i batt,i (k) represents the energy storage current of the i-th node of the island DC microgrid at time t=k, represents the maximum capacity of the energy storage system of the i-th node of the islanded DC microgrid; Substitute equations (13) to (16) into equation (12) to obtain the final SOC prediction model: The current control set for bus voltage regulation is determined as follows: Among them: i basic.i (k)=[i basic,1 (k),…,i basic,i (k),…,i basic,n (k)] T (19); v nom represents the rated voltage value of node i, r i represents the droop coefficient of the energy storage system at the i-th node; is the control set of the secondary voltage adjustment term for bus voltage regulation, and: in: represents the maximum output current allowed by the energy storage system at the i-th node, represents the minimum output current allowed by the energy storage system at the i-th node, Indicates the maximum voltage deviation allowed by the microgrid system, is the voltage secondary control set interval of the energy storage system at the i-th node; The energy storage current control set used for balancing regulation of the energy storage system SoC is determined as follows: Among them: i basic.i (k)=[i basic,1 (k),…,i basic,i (k),…,i basic,n (k)] T (22); v nom represents the rated voltage value of node i, r i represents the droop coefficient of the energy storage system at the i-th node; Indicates the secondary SoC adjustment item, and: in: is the SoC secondary control set interval of the i-th energy storage system, represents the maximum output current allowed by the energy storage system at the i-th node, represents the minimum output current allowed by the energy storage system at the i-th node, Indicates the maximum voltage deviation allowed in the microgrid system.

2. The DC microgrid distributed model predictive control method considering voltage recovery and SoC balance according to claim 1 is characterized by: When the elements in the current control set for bus voltage regulation are used for bus voltage regulation control, the control cost function needs to be satisfied, where the control cost function is:

3. The DC microgrid distributed model predictive control method considering voltage recovery and SoC balance according to claim 1 is characterized by: When performing SoC balancing regulation control on the elements in the energy storage current control set for SoC balancing regulation of the energy storage system, a control cost function needs to be satisfied, where the control cost function is: in: X SoC =[SoC1(s)…SoC i-1 (k)SoC i (k+p)SoC i+1 (k)…SoC n (s)] T ; L(i) represents the i-th row of the Laplacian matrix L.

4. The DC microgrid distributed model predictive control method considering voltage recovery and SoC balance according to claim 3 is characterized by: The Laplace matrix L is determined by the following method: Based on the topological structure of the island DC microgrid, the adjacent nodes of the island DC microgrid are determined, and the adjacent nodes exchange information through the communication network. The communication network is represented by an undirected graph, and the communication weight is in is a node set, represents the edge set; The communication neighbor nodes of node i are represented as The adjacency matrix of node i is expressed as: Among them: a ij Represents the communication weight, then the Laplace matrix of the undirected graph can be obtained according to the following formula: in: represents the degree of freedom of the communication network, then the Laplace matrix can be expressed as L=[l ij ] N×N ,∈R N×N ,

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