Microgrid cluster hierarchical distributed control method and equipment based on heterogeneous batteries

Abstract

The present invention relates to a microgrid energy storage system control technology, and specifically to a hierarchical distributed control method and device for a microgrid cluster based on heterogeneous batteries. The method includes a first-level droop control, a two-layer voltage regulation control, and a two-layer power management control, and can solve the voltage regulation problem within the subgrid and between microgrid groups and the power economic distribution problem among multiple heterogeneous batteries. Physically, the incremental cost of heterogeneous batteries is uniformly defined as the partial derivative of battery energy loss with respect to output power, and a collaborative control method for the incremental cost of heterogeneous multi-battery units is proposed, which can achieve power economic distribution among multiple heterogeneous battery units while satisfying charging / discharging power constraints, SoC constraints, and power balance constraints. The method proposed in the present invention combines battery types related to charging efficiency and charging power with battery types related to charging efficiency and SoC, is easy to expand, and can still be effective even if a new type of battery is used in a microgrid cluster.

Description

Technical Field

[0001] The present invention belongs to the technical field of microgrid energy storage system control, and in particular relates to a hierarchical distributed control method and device for a microgrid cluster based on heterogeneous batteries. Background Art

[0002] In the microgrid sector, strategies for voltage regulation and power balancing within individual microgrid systems have been extensively developed through active power sharing, maximizing energy efficiency, dynamic supply and demand balancing, DC bus voltage regulation, communication reliability under multiple heterogeneous delays, and rolling optimization methods for power fluctuations. However, with the continuous expansion of application scenarios, interconnecting different microgrids can form a multi-microgrid cluster system. Numerous research efforts have been conducted in areas such as network reconfiguration based on local energy markets, demand response services and transacted energy markets across multiple microgrids, optimal energy management frameworks under mixed timescales, voltage setpoint management, and load sharing solutions across microgrid clusters. However, the current power management and operational control strategies for these microgrid clusters all utilize the same type of energy storage components.

[0003] In practical microgrid clusters, it's relatively unlikely that all microgrids will be equipped with the same type of energy storage components. The expansion of a microgrid cluster often requires the integration of multiple battery types to meet diverse power demand scenarios. Current research focuses primarily on the coordination between batteries and supercapacitors to achieve autonomous power sharing. In recent years, hybrid energy storage systems combining vanadium flow batteries (VFBs) and lithium batteries have emerged as a solution to address the diverse power demands of microgrid clusters. By leveraging the unique characteristics of each component, hybrid energy storage systems composed of VFBs and lithium batteries can leverage the advantages of both technologies while mitigating their respective disadvantages. However, power distribution among hybrid battery cells is crucial. Improper coordination can lead to additional power losses, which become significant as the microgrid cluster scales. Existing economic management methods for VFB and lithium battery hybrid systems primarily focus on optimizing the energy costs of the tertiary control layer over large timescales, neglecting the power losses at the secondary control layer over smaller timescales. Therefore, hybrid energy storage systems for microgrid clusters, specifically studying the economic operation of power management and voltage regulation control between heterogeneous batteries within the microgrid cluster over different timescales, are both challenging and of practical engineering significance. Summary of the Invention

[0004] This paper provides a hierarchical distributed control method for microgrid clusters based on heterogeneous batteries, addressing existing issues with economical power allocation and voltage regulation control between hybrid energy storage systems in DC microgrid clusters. This method achieves economical power allocation and voltage regulation within a microgrid energy storage system and between different microgrid energy storage systems.

[0005] The present invention provides a hierarchical distributed control method for a microgrid cluster based on heterogeneous batteries, comprising:

[0006] S1. In order to solve the economic operation and voltage regulation problems between microgrid energy storage systems at different time scales, the present invention constructs a two-layer control structure, such as Figure 1 As shown in FIG, the two-layer control structure adopts a first-level droop control, a two-layer voltage regulation control and a two-layer power management control to realize the economical power distribution and voltage regulation within the microgrid energy storage system and between different microgrid energy storage systems.

[0007] S2. To implement the two-tier control structure in S1, a microgrid energy storage system with a mix of multiple batteries with different characteristics is designed to meet the needs of different scenarios. Therefore, the physical definition of the incremental cost of heterogeneous battery cells is unified to achieve economic power allocation among different battery cells.

[0008] S3. Based on the two-layer control structure proposed in S1, PV first-level droop control is adopted to ensure that the output voltage of the i-th converter quickly tracks the nominal voltage value.

[0009] S4. Based on the double-layer control structure proposed in S1, a double-layer voltage regulation controller is designed. When the control time satisfies 0<τ / T<ψ V and When the voltage is regulated, the two-layer voltage regulation control algorithm can achieve the following control objectives:

[0010]

[0011]

[0012] Among them, τ and is the lower control time indicating the response speed, T and is the upper control time, marked as s for lithium batteries and k for vanadium flow batteries. in, and V rated is the rated value.

[0013] S5. Based on the two-tier control structure proposed in S1 and the unified physical definition of the incremental cost of heterogeneous battery cells in S2, a two-tier power management controller is designed. By designing an appropriate positive condition coefficient γ, the two-tier power management control algorithm can achieve the following control objectives:

[0014]

[0015] Among them, the one with lithium battery (LB) is marked as s, and the one with vanadium redox flow battery (VRB) is marked as k. represents the incremental cost.

[0016] According to the hierarchical distributed control method for a microgrid cluster based on heterogeneous batteries provided by the present invention, the two-layer control structure described in S1 includes:

[0017] S11. Divide all nodes in the microgrid cluster system into representative nodes and non-representative nodes. All representative nodes constitute the upper control structure, and non-representative nodes constitute the lower control structure.

[0018] S12. The two-layer control structure selects a representative node from each subnet through the communication network with the upper layer Distributed consensus control is performed, while other nodes in the lower layer can coordinate their own states through leader-follower control through the communication network G. For example, voltage is adjusted and power is distributed between the lithium battery microgrid group and the vanadium liquid flow battery microgrid group, such as Figure 2 shown.

[0019] S13. The lower network of the two-layer control structure adopts a leader-follower approach to ensure that the steady state of each node is consistent with that of the representative node, thereby achieving voltage recovery, incremental cost coordination, and power balance within a single microgrid.

[0020] S14. The operation of the upper network of the two-layer control structure can be divided into two cases: when an external node sends a reference state value to the upper network, the upper network adopts a leader-follower control method to force the stable state of the representative node to be equal to the reference value; otherwise, the upper network adopts a distributed consensus control method to force the stable state of the representative node to be equal to the average of the total initial values.

[0021] According to the hierarchical distributed control method for a microgrid cluster based on heterogeneous batteries provided by the present invention, the step of unifying the physical definition of the incremental cost of heterogeneous battery units in S2 includes:

[0022] S21. First, focusing on the physical quantities that are common to all types of batteries, the SoC evaluation method for different types of batteries can be expressed as:

[0023]

[0024] Among them, v C SoC is a set of converters connected to batteries in a DC microgrid group. i 、P B，i ,η B，i and They represent the state of charge (SoC), controllable charging power, charging efficiency and rated capacity of the i-th battery respectively.

[0025] S22. In addition, different types of batteries have different charging efficiencies. For traditional batteries, such as lithium-ion batteries, the charging efficiency η B，i It can be simplified to a simple equation related to the charging power. For flow batteries, such as vanadium flow batteries, the charging efficiency η B，i It can be simplified into a simple equation related to SoC and charging power. Therefore, the charging efficiency of lithium-ion batteries and vanadium flow batteries can be expressed as:

[0026]

[0027] S23. To achieve economical operation of hybrid battery charging control method, propose optimization objectives to reduce actual total power consumption:

[0028]

[0029] Among them, P L =∑P L，i is the total load demand, and ∑P G，i is the total generated power.

[0030] S24. Then the Lagrange multiplier method is used for optimization, where the Lagrange function can be expressed as:

[0031]

[0032] Then, taking the partial derivative we get:

[0033]

[0034] in, is the Lagrange multiplier of the i-th battery to be designed, so economic operation can be achieved by collaboratively designing the Lagrange multipliers of different batteries. In physical terms, It is also the incremental cost of the i-th battery. Therefore, the incremental cost of heterogeneous batteries is the partial derivative of the energy loss of each battery unit with respect to the output power, so it has a unified physical meaning.

[0035] According to the hierarchical distributed control method for a microgrid cluster based on heterogeneous batteries provided by the present invention, the PV primary droop control described in S3 includes:

[0036] The relationship between voltage and power output for S31.PV primary droop control can be expressed as:

[0037] V i -V i * =D i (P i * -P i ), i∈v C

[0038] Among them, v C is the set of converters connected to the battery in the DC microgrid group, V i and D i are the output voltage and droop coefficient, V i * and P i * Indicates the nominal voltage and nominal active power, the active power injection P i Satisfy P i =P G，i -P B，i , where P G，i and P B，i are the power generation and charging power of the battery respectively.

[0039] S32.PV first-level droop control will cause voltage deviation, so second-level control is required to eliminate the voltage deviation, that is, by driving the charging power P B，i Equal to the reference power generated by the secondary control Then the voltage deviation can be restored to zero, that is:

[0040]

[0041] According to the hierarchical distributed control method for a microgrid cluster based on heterogeneous batteries provided by the present invention, the two-layer voltage regulation controller described in S4 includes:

[0042] S41. Lower layer single microgrid MG s / MG k Voltage regulation algorithm within:

[0043]

[0044] Among them, τ and Is the lower control time that represents the response speed. When a ij >0, the i-th node can receive data from neighboring nodes; when a i0 When >0, the i-th node can receive data from the representative node.

[0045] S42. Voltage regulation algorithm between upper-level microgrid clusters:

[0046]

[0047] Among them, T and is the upper layer control time, when When , the s / kth representative node in the s / kth microgrid can receive data from neighboring nodes; when When the s / kth representative node can receive the set rating value V from the virtual leader node rated .

[0048] According to the hierarchical distributed control method for a microgrid cluster based on heterogeneous batteries provided by the present invention, the two-layer power management controller described in S5 includes:

[0049] S51. Two-tier economic operation control method for clusters of microgrids containing lithium batteries:

[0050] The lower power controller is:

[0051]

[0052] in, and Represents the network link relationship and leader node connection relationship in the lithium battery microgrid.

[0053] The upper power controller is:

[0054]

[0055] in, Indicates the upper-layer network link relationship.

[0056] S52. Two-tier economic operation control method for clusters of vanadium-containing redox flow battery microgrids:

[0057]

[0058] According to the hierarchical distributed control method for microgrid clusters based on heterogeneous batteries provided by the present invention, the design steps of the two-layer economic operation control algorithm between the lithium battery microgrid clusters include:

[0059] S511. Consider the cost function of lithium batteries. Lithium batteries are batteries whose charging efficiency is related to output power. Their operating cost function can be expressed using a traditional quadratic cost function:

[0060]

[0061] Among them, α s，i , β s，i 、c s，i , α re，s , β re，s and c re，s is the charging fitting coefficient of the ith battery in the lower network and the sth representative battery in the upper network.

[0062] S512. The proposed two-tier power management control method aims to minimize the total operating cost, so the control objectives are:

[0063]

[0064] in, and are the load power of the upper and lower networks respectively, and are the minimum / maximum output power and minimum / maximum SoC of the ith battery in the sth microgrid, and Then it is the minimum / maximum output power and minimum / maximum SoC of the battery in the sth representative node.

[0065] S513. The KKT condition for running the cost function is:

[0066]

[0067] S514. The optimal solution is:

[0068]

[0069] According to the hierarchical distributed control method for heterogeneous battery-based microgrid clusters provided by the present invention, the design steps of the two-layer economic operation control algorithm between the vanadium-containing redox flow battery microgrid clusters include:

[0070] S521. Consider the cost function of the vanadium flow battery. The cost function of the vanadium flow battery is determined by SoC and charging power and can be expressed as:

[0071]

[0072] in, is the charging power of the vanadium flow battery, Indicates the state of charge of the vanadium flow battery, is the rated charging power of the vanadium flow battery, a VRB，c 、b VRB，c 、c VRB，c and d VRB，c is the charging efficiency parameter that can be obtained by the nonlinear least squares regression method.

[0073] S522. The control objectives of the two-layer power management algorithm for vanadium flow batteries in a microgrid cluster are:

[0074]

[0075] in, and The load power of the double-layer network containing vanadium redox flow battery microgrid groups, and are the minimum / maximum output power and minimum / maximum SoC of the i-th battery in the k-th microgrid, and is the minimum / maximum output power and minimum / maximum SoC of the battery in the kth representative node.

[0076] S523. The KKT conditions for vanadium flow batteries are:

[0077]

[0078] S524. The optimal solution is:

[0079]

[0080] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the hierarchical distributed control method for a microgrid cluster based on heterogeneous batteries as described above is implemented.

[0081] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for hierarchical distributed control of a microgrid cluster based on heterogeneous batteries as described above is implemented.

[0082] Compared with the prior art, the beneficial effects of the present invention are as follows: in order to reduce the operating losses of different batteries in a microgrid cluster, the present invention proposes a hierarchical distributed control framework, while meeting the economic power sharing requirements within each microgrid, realizing economic power management between different batteries in the microgrid cluster, and being able to solve the voltage regulation problem and power distribution problem within the subgrid and between microgrid groups under the interference of communication delay. At the same time, in order to solve the control problem of a microgrid group system containing different types of batteries, the present invention uniformly defines the incremental cost of heterogeneous batteries from a physical perspective as the partial derivative of battery energy loss with respect to output power, and proposes a collaborative control method for the incremental cost of heterogeneous multi-battery units, which can realize the economic distribution of power among multiple heterogeneous battery units while meeting the charging / discharging power constraints, SoC constraints and power balance constraints. Among them, the method of combining heterogeneous batteries is scalable. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0084] Figure 1 This is a diagram of a dual-layer control structure of heterogeneous batteries in a DC microgrid cluster provided by an embodiment of the present invention;

[0085] Figure 2 This is a diagram of a heterogeneous battery double-layer information system provided by an embodiment of the present invention;

[0086] FIG3( a ) is a physical structure diagram of a double-layer structure according to an embodiment of the present invention;

[0087] FIG3( b ) is a diagram of a double-layer communication network according to an embodiment of the present invention;

[0088] FIG4( a ) is a schematic diagram of incremental cost variables when switching modes according to an embodiment of the present invention;

[0089] FIG4( b ) is a schematic diagram of SoC variables when mode switching is performed according to an embodiment of the present invention;

[0090] FIG4( c ) is a schematic diagram of charging power variables during mode switching according to an embodiment of the present invention;

[0091] FIG4( d ) is a schematic diagram of node voltage variations during mode switching according to an embodiment of the present invention;

[0092] FIG5( a ) is a schematic diagram of incremental cost variables under load changes according to an embodiment of the present invention;

[0093] FIG5( b ) is a schematic diagram of SoC variables under load changes according to an embodiment of the present invention;

[0094] FIG5( c ) is a schematic diagram of charging power variables under load changes according to an embodiment of the present invention;

[0095] FIG5( d ) is a schematic diagram of node voltage variations under load changes according to an embodiment of the present invention;

[0096] FIG6( a ) is a schematic diagram of incremental cost variables for plug-and-play according to an embodiment of the present invention;

[0097] FIG6( b ) is a schematic diagram of SoC variables under plug-and-play according to an embodiment of the present invention;

[0098] FIG6( c ) is a schematic diagram of charging power variables in plug-and-play mode according to an embodiment of the present invention;

[0099] FIG6( d ) is a schematic diagram of node voltage variables in plug-and-play mode according to an embodiment of the present invention;

[0100] FIG7( a ) is a schematic diagram of incremental cost variables under communication delay according to an embodiment of the present invention;

[0101] FIG7( b ) is a schematic diagram of SoC variables under communication delay according to an embodiment of the present invention;

[0102] FIG7( c ) is a schematic diagram of charging power variables under communication delay according to an embodiment of the present invention;

[0103] FIG7( d ) is a schematic diagram of node voltage variables under communication delay according to an embodiment of the present invention;

[0104] Figure 8 is a schematic structural diagram of an electronic device provided by an embodiment of the present invention;

[0105] Reference numerals:

[0106] Among them: 810 - processor, 820 - communication interface, 830 - memory, 840 - communication bus. DETAILED DESCRIPTION

[0107] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0108] This embodiment is based on a hierarchical distributed control method for a microgrid cluster of heterogeneous batteries, including: a microgrid hierarchical distributed control framework, whose structure includes a first-level droop control, a two-layer voltage regulation control, and a two-layer power management control, which can solve the voltage regulation problem within the subgrid and between microgrid clusters and the power economic allocation problem among multiple heterogeneous batteries. Secondly, the incremental cost of heterogeneous batteries is uniformly defined physically as the partial derivative of battery energy loss with respect to output power, and a collaborative control method for the incremental cost of heterogeneous multi-battery units is proposed, which can achieve power economic allocation among multiple heterogeneous battery units while satisfying charging / discharging power constraints, SoC constraints, and power balance constraints. Finally, the proposed method combines battery types whose charging efficiency is related to charging power (such as lithium batteries) and battery types whose charging efficiency is related to SoC (such as vanadium liquid flow batteries), and is easy to expand. Even if a new type of battery is adopted in the microgrid cluster, the proposed method can still be effective.

[0109] Example 1

[0110] In this embodiment 1, multiple DC microgrid groups containing lithium batteries and vanadium redox flow batteries are simulated. The physical structure and communication links of the heterogeneous batteries in the microgrid group are shown in Figure 3 (a) and Figure 3 (b). The parameters of the double-layer structure are shown in Table 1 and Table 2. Include and Include and Vanadium-containing redox flow battery microgrid Include and Include In the double-layer control structure, the lithium battery node and vanadium flow battery nodes is selected as the representative node. The status can be followed status, and The status can be followed In a vanadium-containing flow battery microgrid, and Follow state.

[0111] In addition, define the leader adjacency matrix B S =diag{1,0,1,0},B K =diag{1,1,0,1}, And the remaining adjacency matrix is ​​designed to be A S =[0,1,0,0;1,0,0,0;0,0,0,1;0,0,1,0],A K =[0,1,1,0;1,0,1,0;1,1,0,0;0,0,0,0], Then the eigenvalues ​​of the corresponding matrix are λ min (L K +B K )=0.382,λ min (L S +B S )=0.382, In addition, this embodiment sets the control time coefficient of the lithium battery microgrid group to τ = 0.2, T = 10, and sets the control time coefficient of the vanadium redox flow battery microgrid group to Thus we can get Obviously, the control time constant ratio constraint is satisfied and And realize the voltage regulation in the double-layer structure. Let the control gain coefficient be K li =3,K li ，up =0.8, K van =1,K van，up =0.5. Therefore, we can get Therefore, in this example, the conditional coefficient γ is set to 8 to ensure the stability of the control system.

[0112] Table 1 Parameters of microgrid containing lithium batteries

[0113]

[0114] Table 2 Parameters of vanadium-containing liquid flow microgrid

[0115]

[0116] Example 2

[0117] When switching from island mode to networking mode, as shown in Figure 4(a), Figure 4(b), Figure 4(c), and Figure 4(d), the control process is divided into two parts.

[0118] In the initial part t∈[0,0.2)s, the eight node-based distributed generation units with batteries operate in island mode, and their incremental costs, SoC, charging power, and voltage do not interact. Then, the islanded DC microgrid cluster system can be connected to the grid at t=0.2s.

[0119] In the second part, t∈[0.2, 2)s, the addition of a lower-level controller allows eight nodes containing distributed generation units with batteries to form four independent microgrids. This allows for consistent incremental costs, coordinated SoCs, economical charging power allocation, and voltage regulation within each microgrid. Simultaneously, the upper-level controller enables state interaction between microgrids containing different batteries, coordinating incremental costs, balancing SoCs, allocating charging power, and eliminating voltage deviations.

[0120] In the control process of the lithium battery microgrid group, and Follower controller in the can track and The leader controller in . Meanwhile, the representative node and The state of the entire lithium battery microgrid group can be coordinated by exchanging information with each other and receiving external rated reference information. and The incremental cost, SoC and node voltage can be controlled to be equivalent to The corresponding parameters.

[0121] Furthermore, the vanadium redox flow battery microgrid cluster utilizes a distributed collaborative control approach, while the lithium battery microgrid cluster employs a leader-follower control approach at the upper control layer. It is important to emphasize that the current leader defined in the lithium battery microgrid cluster is essentially based on steady-state information obtained from the vanadium redox flow battery microgrid cluster. By applying power balancing constraints to the hybrid battery microgrid cluster, the designed algorithm achieves voltage regulation and economic power management.

[0122] Example 3

[0123] Considering the load change, in t∈[0.6,0.8)s, a 2.5kW load Slave nodes The load is cut off at t = 0.8s and then reapplied at t = 0.8s. At t=1s, the slave node The battery is removed and added at t = 1.4s. After networking at t = 0.2s, Figure 5(a) shows that the incremental cost of all battery units converges to a consistent value. Load changes in the vanadium redox flow battery microgrid also change the SoC increase rate of each vanadium redox flow battery, as shown in Figure 5(b).

[0124] Figure 5(c) shows the charging power of all batteries. In a single microgrid, the representative node The status of the non-representative node will affect the status of the non-representative node. Power allocation is performed through information exchange to achieve power balance. At t = 0.6s, The removal of the 2.5kW load increases the charging power of each lithium battery node. When the load is added again at t = 0.8s, the charging power returns to its previous value. For the microgrid group containing vanadium redox flow batteries, a 15kW load In t∈[1,1.4)s from The charging power variation shown in Figure 5(c) demonstrates the robustness of the present invention under load fluctuations. Since the actual charging power follows the reference value provided by the controller, the voltage fluctuation caused by load changes can be eliminated, and the system can return to steady state, as shown in Figure 5(d).

[0125] Example 4

[0126] This embodiment demonstrates plug-and-play capability, as shown in FIG6( a ), FIG6( b ), FIG6( c ), and FIG6( d ).

[0127] Six distributed generation units containing batteries form a microgrid at t = 0.2s. The insertion of a battery at t = 0.6s disrupted the steady state of the microgrid cluster, which originally consisted of six distributed generation units containing batteries. At this point, the designed two-layer controller was applied to the system, eliminating the fluctuations caused by the insertion operation. It then coordinated incremental costs, balanced the SoC, shared charging power, and restored voltage. After a short period of transient evolution, the system was able to return to a stable state.

[0128] Depend on Microgrid cluster It is cut off at t=1.6s, disconnecting other microgrid clusters from However, when removing After that, the remaining microgrid clusters and Economical power sharing and voltage regulation can still be achieved, which demonstrates the plug-and-play capability of the proposed two-tier control structure.

[0129] Example 5

[0130] When there is a variable communication delay of 0.008(sin(25t)+π / 4)+0.022, as shown in Figures 7(a), 7(b), 7(c), and 7(d). Due to the control time constraints between the microgrid cluster containing lithium batteries and the microgrid cluster containing vanadium redox flow batteries, the two-layer control scheme of the present invention is very sensitive to the system response speed. However, the sparse communication matrix can cover a wide range of low-bandwidth communication networks and is therefore robust to the delay on the communication link. The impact is not significant, so the system can still achieve incremental cost alignment, SoC balancing, charging power distribution, and voltage regulation.

[0131] Example 6

[0132] Figure 8 An example of a physical structure diagram of an electronic device is shown below. Figure 8 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other via the communication bus 840. The processor 810 may call the logic instructions in the memory 830 to execute the hierarchical distributed control method for a microgrid cluster based on heterogeneous batteries.

[0133] In addition, the logic instructions in the above-mentioned memory 830 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0134] On the other hand, this embodiment also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the hierarchical distributed control method for a microgrid cluster based on heterogeneous batteries provided by the above methods.

[0135] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0136] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0137] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A hierarchical distributed control method for microgrid clusters based on heterogeneous batteries, characterized in that: The following steps are involved: Establish a two-tier control structure; Includes one-level droop control, two-layer voltage regulation control, and two-layer power management control; The double-layer control structure includes: S11. Divide all nodes in the microgrid cluster system into representative nodes and non-representative nodes; all representative nodes constitute an upper control structure, and non-representative nodes constitute a lower control structure; S12. The two-layer control structure selects a representative node from each subnet through the communication network with the upper layer Conduct distributed consensus control, while other nodes in the lower layer coordinate their own states through leader-follower control via the communication network G; S13. The lower network of the two-tier control structure uses a leader-follower approach to ensure that the stable state of each node is consistent with that of the representative node, achieving voltage recovery, incremental cost coordination, and power balancing within a single microgrid. S14. The operation of the upper network of the two-layer control structure is divided into two cases: when an external node sends a reference state value to the upper network, the upper network adopts a leader-follower control method to make the stable state of the representative node equal to the reference value; otherwise, the upper network adopts a distributed consensus control method to make the stable state of the representative node equal to the average of the total initial values; Unified physical definition of incremental cost of heterogeneous battery cells; the unified physical definition of incremental cost of heterogeneous battery cells includes: S21. For different types of batteries, the SoC evaluation method is expressed as follows: Among them, v C SoC is a set of converters connected to batteries in a DC microgrid group. i 、P B,i ,η B,i and They represent the state of charge SoC, controllable charging power, charging efficiency and rated capacity of the i-th battery respectively; S22. Different types of batteries have different charging efficiencies. The charging efficiencies of lithium-ion batteries and vanadium flow batteries are expressed as: S23. Optimization goal: Among them, P L =∑P L,i is the total load demand, ∑P G,i is the total power generation; S24. Use the Lagrange multiplier method for optimization, where the Lagrange function is expressed as: Taking partial derivatives we get: in, is the Lagrange multiplier of the i-th battery to be designed, and economic operation is achieved by collaboratively designing the Lagrange multipliers of different batteries; in the physical sense, is the incremental cost of the i-th battery. The incremental cost of heterogeneous batteries is the partial derivative of the energy loss of each battery unit with respect to the output power; The PV first-level droop control is used to achieve the output voltage of the i-th converter to quickly track the nominal voltage value; Use a double-layer voltage regulation controller; when the control time satisfies 0<τ / T<ψ V and When , the two-layer voltage regulation control algorithm achieves the following control objectives: Among them, τ and is the lower control time indicating the response speed, T and is the upper control time, marked as s for lithium batteries and k for vanadium flow batteries; in, and V rated is the rated value; By unifying the physical definition of the incremental cost of heterogeneous battery cells, a two-layer power management controller is derived. The positive condition coefficient γ is established, and the two-layer power management control algorithm achieves the following control objectives: and Among them, the one with lithium battery is marked as s, and the one with vanadium flow battery is marked as k. represents the incremental cost.

2. The hierarchical distributed control method for microgrid clusters based on heterogeneous batteries according to claim 1 is characterized in that: The PV primary droop control includes: S31. The voltage and power output expressions for the PV primary droop control are: V i -V i * =D i (P i * -P i ),i∈v C Among them, v C is the set of converters connected to the battery in the DC microgrid group, V i and D i are the output voltage and droop coefficient, V i * and P i * Indicates the nominal voltage and nominal active power, the active power injection P i Satisfy P i =P G,i -P B,i , where P G,i and P B,i are the power generation and charging power of the battery respectively; S32. Secondary control eliminates voltage deviation; drives charging power P B,i Equal to the reference power generated by the secondary control Voltage deviation Restore to zero:

3. The hierarchical distributed control method for microgrid clusters based on heterogeneous batteries according to claim 1 is characterized in that: The dual-layer voltage regulator controller includes: S41. Lower layer single microgrid MG s / MG k Voltage regulation algorithm within: Among them, τ and Is the lower control time that represents the response speed. When a ij >0, the i-th node receives data from neighboring nodes; when a i0 When >0, the i-th node receives data from the representative node; S42. Voltage regulation algorithm between upper-level microgrid clusters: Among them, T and is the upper layer control time, when When , the s / kth representative node in the s / kth microgrid receives data from the neighboring node; when When the s / kth representative node receives the set rating value V from the virtual leader node rated .

4. The hierarchical distributed control method for microgrid clusters based on heterogeneous batteries according to claim 1 is characterized in that: The dual-layer power management controller includes: S51. Two-tier economic operation control between clusters of lithium battery microgrids includes: Lower power controller: in, and Represents the network link relationship and leader node connection relationship in the lithium battery microgrid; Upper power controller: in, Indicates the upper-layer network link relationship; S52. Two-tier economic operation control between vanadium redox flow battery microgrid clusters includes:

5. The hierarchical distributed control method for microgrid clusters based on heterogeneous batteries according to claim 4 is characterized in that: The algorithm for the two-tier economic operation control between the lithium battery microgrid clusters described in S51 includes: S511. Consider the cost function of lithium batteries. Lithium batteries are batteries whose charging efficiency is related to output power. Their operating cost function is expressed using the traditional quadratic cost function: Among them, α s,i , β s,i 、c s,i , α re,s , β re,s and c re,s is the charging fitting coefficient of the ith battery in the lower network and the sth representative battery in the upper network; S512. The control objectives of the two-tier power management control method are: in, and are the load power of the upper and lower networks respectively, and are the minimum / maximum output power and minimum / maximum SoC of the ith battery in the sth microgrid, and The minimum / maximum output power and minimum / maximum SoC of the battery in the sth representative node; S513. The KKT condition for running the cost function is: S514. The optimal solution is:

6. The hierarchical distributed control method for microgrid clusters based on heterogeneous batteries according to claim 4 is characterized in that: The algorithm for the two-tier economic operation control between the vanadium-containing redox flow battery microgrid clusters described in S52 includes: S521. Consider the cost function of the vanadium flow battery. The cost function of the vanadium flow battery is expressed as: in, is the charging power of the vanadium flow battery, Indicates the state of charge of the vanadium flow battery, is the rated charging power of the vanadium flow battery, a VRB,c 、b VRB,c 、c VRB,c and d VRB,c is the charging efficiency parameter that can be obtained by the nonlinear least squares regression method; S522. The control objectives of the two-layer power management algorithm for vanadium flow batteries in a microgrid cluster are: in, and The load power of the double-layer network containing vanadium redox flow battery microgrid groups, and are the minimum / maximum output power and minimum / maximum SoC of the i-th battery in the k-th microgrid, and The minimum / maximum output power and minimum / maximum SoC of the battery in the kth representative node; S523. The KKT conditions for vanadium flow batteries are: S524. The optimal solution is:

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the hierarchical distributed control method for a microgrid cluster based on heterogeneous batteries as described in any one of claims 1 to 6 is implemented.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the hierarchical distributed control method for a microgrid cluster based on heterogeneous batteries as claimed in any one of claims 1 to 6 is implemented.

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