Inter-group cooperative control method and system for dc microgrid based on tab converter

Abstract

The application relates to the technical field of direct-current micro-grid groups, and provides a method and system for cooperative control between direct-current micro-grid groups based on TAB converters, which comprises the following steps: for each direct-current micro-grid, a consistency algorithm is adopted, the average voltage of the direct-current bus of each node is estimated, the first control item of the node is calculated, the port output current value of each node in the direct-current micro-grid is controlled, and then control is exerted on each node; for each TAB converter port, a consistency algorithm is adopted, the average voltage of the direct-current bus of the port is estimated, the first control item of the port is calculated, the port output current value of each node which is communicatively connected to the port is controlled, and then control is exerted on each port; wherein the consistency algorithm adopts multiple communication weight factors and response time scale parameters to adjust the voltage convergence speed of each direct-current micro-grid or port to different degrees. The energy of each source in the sub-grid is mutual, and the convergence speed of the energy mutualism between the sub- grids is adjustable and controllable.

Description

Technical Field

[0001] This invention belongs to the field of DC microgrid technology, and particularly relates to a collaborative control method and system for DC microgrid groups based on TAB converters. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] For multi-DC microgrids connected by three active bridge DC converters (TAB), in future new energy systems, the user load characteristics of each subgrid in the multi-DC microgrid are different. For example, subgrid 1 is for industrial users, and this type of load places more stringent requirements on the convergence speed and other indicators within the subgrid. Subgrid 2 is for residential users, and this type of load does not place as stringent requirements on the convergence speed and other indicators within the subgrid.

[0004] This paper addresses the technical problem of inflexible energy sharing in existing collaborative control methods for DC microgrids with users accessing subnets of varying operating characteristics. Current control methods for different ports of the TAB converter are based on classical consensus control. Adjusting the convergence speed of different subnets depends on adjusting the communication weight factor. However, the value of the communication factor simultaneously affects the system's global stability and convergence accuracy. Therefore, the adjustment of the communication weight factor in classical consensus algorithms is constrained by other factors, resulting in limited adjustment capabilities and an inflexible adjustment process. This easily affects the system's global stability and convergence accuracy, making it difficult to achieve flexible energy sharing for DC microgrids with users accessing subnets of varying operating characteristics.

[0005] In addition, when the distributed energy supply in industrial areas is insufficient, whether residential users can use TAB converters to provide rapid and flexible energy to industrial users is a key technical issue. Summary of the Invention

[0006] To address the technical problems mentioned above, this invention provides a collaborative control method and system for DC microgrid groups based on TAB converters. Starting with collaborative control within and between subgrids, it employs an improved consensus algorithm with multiple time scales to achieve adjustable and controllable convergence speeds for energy mutual assistance among sources within and between subgrids.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] The first aspect of the present invention provides a method for coordinated control among DC microgrid groups based on a TAB converter, comprising:

[0009] For each DC microgrid, the output voltage of each distributed power source port is obtained, and the average DC bus voltage of each node is estimated using a consensus algorithm. Then, the first control term of the node is calculated. The output current value of each node's port is controlled to obtain the second control term of the node. Finally, the first control term of the node is combined with the first control term of the node to apply control to each node.

[0010] For each TAB converter port, intermediate variables are obtained, and the average DC bus voltage of the port is estimated using a consensus algorithm. Then, the first control term of the port is calculated. The output current value of each node with communication link to the port is controlled to obtain the second control term of the port. Finally, the control term of the port is combined with the first control term of the port to apply control to each port.

[0011] The consensus algorithm employs multiple communication weight factors and response time scale parameters to adjust the voltage convergence speed of each DC microgrid to different degrees, or to adjust the voltage convergence speed of each port to different degrees.

[0012] Furthermore, the method for estimating the average DC bus voltage of each node is as follows:

[0013]

[0014]

[0015]

[0016] In the formula, and Let represent the average DC bus voltage of node i in the k-th DC microgrid and its derivative with respect to time, respectively. and All of these are intermediate variables of node i within the k-th DC microgrid. and All of these are intermediate variables of node j within the k-th DC microgrid. and These are all intermediate variables at the k-th TAB converter port. and Let be the time derivative of the intermediate variable at the k-th TAB converter port; j∈N, where N represents the set of neighboring nodes of node i; a ij and b ij Both are communication weight factors between node i and node j, b il The communication weighting factor between node i and TAB converter port k; and Let represent the output voltage of each distributed power source port in the k-th DC microgrid and its time derivative, respectively; ε k and β kAll of these are response time scale parameters.

[0017] Furthermore, the method for estimating the port voltage is as follows:

[0018]

[0019]

[0020]

[0021] in, and Let represent the output voltage of the k-th TAB converter port and its derivative with respect to time, respectively. and Let represent the average DC bus voltage at the k-th TAB converter port and its derivative with respect to time, respectively. and All are intermediate variables of the k-th TAB converter port; M represents the set of nodes that have communication links with the k-th TAB port; and This indicates the communication weight between the port of the k-th TAB converter and node j; and All of these are response time scale parameters. and All of these are intermediate variables of node j within the k-th DC microgrid.

[0022] Furthermore, with the goal of stabilizing the average DC bus voltage of each node at the rated value, a proportional-integral controller is used to control the average DC bus voltage of each node to obtain the first control term of the node.

[0023] Alternatively, with the goal of stabilizing the average DC bus voltage at each port to the rated value, a proportional-integral controller is used to control the average DC bus voltage at each port to obtain the first control term for the port.

[0024] Furthermore, with the proportional distribution of power from each source within the DC microgrid as the control objective, the port output current value of each node within the DC microgrid is controlled.

[0025] Alternatively, the output current value of each node with a communication link to the port can be controlled by using the proportional distribution of power among the sources in the DC microgrid as the control objective.

[0026] Furthermore, when applying control to each node, droop control is adopted.

[0027] Furthermore, when applying control to each port, phase-shift control is employed.

[0028] A second aspect of the present invention provides a cooperative control system for DC microgrid groups based on a TAB converter, comprising:

[0029] The microgrid control module is configured to: for each DC microgrid, acquire the output voltage of each distributed power source port, use a consensus algorithm to estimate the average DC bus voltage of each node, calculate the first control term of the node; control the port output current value of each node in the DC microgrid, obtain the second control term of the node, and apply control to each node in combination with the first control term of the node.

[0030] The microgrid inter-control module is configured to: for each TAB converter port, obtain intermediate variables, use a consensus algorithm to estimate the average DC bus voltage of the port, calculate the first control term of the port; and control the port output current value of each node that has a communication link with the port to obtain the second control term of the port, and then apply control to each port in combination with the first control term of the port.

[0031] The consensus algorithm employs multiple communication weight factors and response time scale parameters to adjust the voltage convergence speed of each DC microgrid to different degrees, or to adjust the voltage convergence speed of each port to different degrees.

[0032] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-described TAB converter-based DC microgrid group cooperative control method.

[0033] A fourth aspect of the present invention provides a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the above-described collaborative control method for DC microgrid groups based on a TAB converter.

[0034] Compared with the prior art, the beneficial effects of the present invention are:

[0035] This invention starts with the collaborative control within and between subnets, and adopts an improved consensus algorithm with multiple time scales to achieve adjustable and controllable convergence speed of energy mutual assistance among sources within a subnet and energy mutual assistance between subnets.

[0036] This invention addresses the future novel energy systems accessed by users in subnets with different operating characteristics. It enables flexible energy sharing and port customization, greatly improving the energy sharing efficiency within and between subnets, and expanding the application scope of multi-DC microgrid groups connected by three active bridge DC converters (TAB).

[0037] This invention enables residential users to quickly and flexibly supply energy to industrial users when distributed energy supply is insufficient in industrial plant areas. It adopts a collaborative control method with different operating time scales within and between subgrids with different operating characteristics. The operating time scale needs to be flexible and adjustable with a large range of values, so as to achieve rapid and efficient energy mutual assistance among DC microgrid groups with multiple operating characteristics. Attached Figure Description

[0038] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0039] Figure 1 This is a diagram of a multi-DC microgrid cluster structure connected by a three-active-bridge DC-DC converter according to Embodiment 1 of the present invention.

[0040] Figure 2 This is a diagram of the flexible collaborative control architecture within a subnet according to Embodiment 1 of the present invention;

[0041] Figure 3 This is a diagram of the flexible collaborative control architecture between DC microgrids according to Embodiment 1 of the present invention. Detailed Implementation

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

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

[0044] Example 1

[0045] This embodiment provides a collaborative control method for DC microgrid groups based on TAB converters.

[0046] The collaborative control method for DC microgrid groups based on TAB converters provided in this embodiment solves the technical problem of inflexible energy exchange in existing collaborative control methods for DC microgrid groups with different operating characteristics and user access.

[0047] The collaborative control method for DC microgrid groups based on TAB converters provided in this embodiment is based on an improved consensus algorithm. This algorithm has two time scale parameters, which can simultaneously adjust the system convergence speed to different degrees, greatly improving the energy mutual assistance efficiency between DC microgrid groups under the access of subgrids with different operating characteristics.

[0048] The TAB converter-based inter-group cooperative control method for DC microgrids provided in this embodiment is applicable to, for example, Figure 1The diagram shows a multi-DC microgrid group connected by a three-active-bridge DC-DC converter (TAB).

[0049] The TAB converter-based inter-group cooperative control method for DC microgrids provided in this embodiment includes flexible cooperative control within subgrids (DC microgrids) and flexible cooperative control between DC microgrids.

[0050] Step 1, as follows Figure 2 As shown, flexible collaborative control within a subnet includes the following steps:

[0051] Step 101: To meet the control objective of DC bus voltage regulation within the DC subgrid, it is necessary to control the voltage of each unit in the subgrid system. Specifically, in a multi-DC microgrid group connected by a three-active-bridge DC-DC converter (TAB), for the k-th DC microgrid, the intermediate variables of the TAB converter port, the output voltage of each distributed power source port within the DC microgrid, and the intermediate variables of each node within the DC microgrid are obtained. A consensus algorithm with multiple time scales (improved consensus algorithm) is used to estimate the average DC bus voltage of each node. A PI controller (proportional-integral controller) is then used to control the average DC bus voltage of each node within the k-th DC microgrid, resulting in the first control term for the node.

[0052] In step 101, the consensus algorithm uses multiple communication weight factors and response time scale parameters to adjust the voltage convergence speed of each DC microgrid to different degrees.

[0053] In this embodiment, an improved consensus algorithm is used to estimate the average DC bus voltage:

[0054]

[0055] In the formula, represents the subnet (port) k: This represents the average observed DC bus voltage at node i. Its derivative with respect to time; and Let i and j represent the intermediate variables of nodes i and j, respectively. and These are intermediate variables for port k of the TAB converter; they are used to generate reference variables and have no practical significance. and Its time derivative; where j∈N, N represents the set of neighboring nodes of node i; a ij ,b ij Let b be the communication weight factor between nodes i and j. il The communication weighting factor between node i and TAB converter port k; This indicates the output voltage of each distributed power source port within the subnet. ε represents its time derivative;k For fast dynamic response timescale parameters, this parameter controls the dynamic generation rate of the reference value; β k This is a slow dynamic response timescale parameter used to control the tracking speed of each source to the reference value. For example, for an industrial park with high requirements for system convergence speed and dynamic response, ε can be adjusted. k The parameter is a relatively large value; for a residential area where there are no high requirements for system convergence speed and dynamic response, β can be adjusted. k The parameters are relatively small values. It should also be noted that the two dynamic processes described above occur almost simultaneously, and the magnitudes of the parameters have virtually no impact on system stability. Therefore, the proposed control method significantly improves the energy exchange efficiency between DC microgrid groups with subgrids exhibiting different operating characteristics.

[0056] The system voltage control objective is to stabilize the average DC bus voltage at each node at its rated value. Therefore, a PI controller is used to control it, resulting in the first control term for each node:

[0057]

[0058] in, This represents the control equation for a PI controller, v ref This is the reference value for the bus voltage.

[0059] Step 102: To meet the control objective of proportional power distribution among sources within the DC subgrid, it is necessary to control the output current in the subgrid system. Specifically, for the k-th DC microgrid, the port output current values ​​of each node are obtained, and the second control term for the node is calculated.

[0060] The calculation method for the second control item of the node is as follows:

[0061]

[0062] in, and These represent the port output current values ​​at nodes i and j, respectively. and Let i and j represent the rated output current values ​​of the ports, respectively. and These represent the per-unit values ​​of the port output current at nodes i and j, respectively. This represents the control equation of the PI controller. δ2 is the second control term of the system node, which adjusts the per-unit value of the output current of each node in the subnet to be consistent through the PI controller. Since δ1 makes the output voltage of each node in the system the same, the adjustment of δ2 can make the power of each node distributed proportionally.

[0063] Step 103: The underlying control of each distributed energy source within the subnet adopts droop control, which applies control to each node based on the two node control terms δ1 and δ2 mentioned above:

[0064]

[0065] in, r is the reference value for the output voltage of each node. i k These are the droop control coefficients for each node.

[0066] Step 2, as follows Figure 3 As shown, the flexible collaborative control between DC microgrids includes the following steps:

[0067] DC microgrids rely on TAB converters as energy bridging devices, and each port can be regarded as a node in the communication network.

[0068] Step 201: For the k-th port of the TAB converter, obtain the intermediate variables of the TAB converter port, calculate the TAB converter port voltage, and then use a PI controller to control it to obtain the first control term of the port.

[0069] In step 201, the consensus algorithm uses multiple communication weight factors and response time scale parameters to adjust the voltage convergence speed of each port to different degrees.

[0070] The calculation method for the voltage at the TAB converter port is as follows:

[0071]

[0072]

[0073]

[0074] in, This represents the output voltage at the port of the k-th TAB converter. This represents its time derivative; This represents the average DC bus voltage at port k of the TAB converter (i.e., subnet k). Its time derivative; and This is an intermediate variable for the TAB converter port k, used to generate reference values ​​but has no practical significance; M represents the set of nodes within subnet k that have communication links with the TAB port. and This indicates the communication weight between the k-th TAB converter port and the j-th node; similar to the cooperative control within the subnet, and These correspond to the fast dynamic response time scale parameters and the slow dynamic response time scale parameters, respectively. The difference is that here... and The control is applied to the convergence speed of the port k voltage, which is the energy power transfer rate between ports. Therefore, the energy flow rate between ports can be effectively and conveniently regulated, enabling flexible energy exchange between multiple microgrids.

[0075] The target for port (subnet) voltage control is to stabilize the average DC bus voltage at each port at its rated value. Therefore, a PI controller is used to control it, resulting in the first control term for the port:

[0076]

[0077] in, This represents the control equation for the PI controller.

[0078] Step 202: To meet the control objective of proportional power distribution among the sources in the DC subnetwork, it is necessary to control the port current. Specifically, for the k-th TAB converter port, obtain the port output current values ​​of each node with a communication link to that port, and calculate the second control term for the port.

[0079] Specifically as follows:

[0080]

[0081]

[0082] Where dM represents the number of nodes in set M, Represent the control equations of the PI controller; and Let B represent the per-unit current values ​​of ports k and j, respectively, and let B represent the set of ports that communicate adjacent to port k.

[0083] Step 203: Based on the first and second control terms of the port, calculate the shift angle and perform phase shift control on the TAB port.

[0084] The underlying control of the TAB port adopts a phase-shift control method, and its shift angle formula is:

[0085]

[0086] The details of phase-shift control will not be elaborated here.

[0087] The TAB converter-based collaborative control method for DC microgrid groups provided in this embodiment starts with collaborative control within and between subgrids. It employs an improved consensus algorithm with multiple time scales to achieve adjustable and controllable convergence speeds for energy exchange between sources within and between subgrids. This function, designed for future new energy systems with users accessing subgrids of different operating characteristics, enables flexible energy exchange and port customization, significantly improving energy exchange efficiency within and between subgrids and expanding the application scope of multi-DC microgrid groups connected by three active bridge DC converters (TAB).

[0088] Example 2

[0089] This embodiment provides a collaborative control system for DC microgrid groups based on a TAB converter, which specifically includes:

[0090] The microgrid control module is configured to: for each DC microgrid, acquire the output voltage of each distributed power source port, use a consensus algorithm to estimate the average DC bus voltage of each node, calculate the first control term of the node; control the port output current value of each node in the DC microgrid, obtain the second control term of the node, and apply control to each node in combination with the first control term of the node.

[0091] The microgrid inter-control module is configured to: for each TAB converter port, obtain intermediate variables, use a consensus algorithm to estimate the average DC bus voltage of the port, calculate the first control term of the port; and control the port output current value of each node that has a communication link with the port to obtain the second control term of the port, and then apply control to each port in combination with the first control term of the port.

[0092] The consensus algorithm employs multiple communication weight factors and response time scale parameters to adjust the voltage convergence speed of each DC microgrid to different degrees, or to adjust the voltage convergence speed of each port to different degrees.

[0093] It should be noted that each module in this embodiment corresponds one-to-one with each step in Embodiment 1, and their specific implementation processes are the same, so they will not be repeated here.

[0094] Example 3

[0095] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the TAB converter-based DC microgrid group cooperative control method described in Embodiment 1 above.

[0096] Example 4

[0097] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the collaborative control method between DC microgrid groups based on the TAB converter described in Embodiment 1 above.

[0098] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

Claims

1. A method for coordinated control among DC microgrid groups based on a TAB converter, characterized in that, include: For each DC microgrid, the output voltage of each distributed power source port is obtained, and the average DC bus voltage of each node is estimated using a consensus algorithm. Then, the first control term of the node is calculated. The output current value of each node's port is controlled to obtain the second control term of the node. Finally, the first control term of the node is combined with the first control term of the node to apply control to each node. For each TAB converter port, intermediate variables are obtained, and the average DC bus voltage of the port is estimated using a consensus algorithm. Then, the first control term of the port is calculated. The output current value of each node with communication link to the port is controlled to obtain the second control term of the port. Finally, the control term of the port is combined with the first control term of the port to apply control to each port. The consensus algorithm uses multiple communication weight factors and response time scale parameters to adjust the voltage convergence speed of each DC microgrid to different degrees, or to adjust the voltage convergence speed of each port to different degrees. The goal is to stabilize the average DC bus voltage of each node at the rated value. A proportional-integral controller is used to control the average DC bus voltage of each node to obtain the first control term of the node. The goal is to stabilize the average DC bus voltage of each port at the rated value. A proportional-integral controller is used to control the average DC bus voltage of each port to obtain the first control term of the port. The method for estimating the average DC bus voltage of each node is as follows: In the formula, and They represent the first k Nodes within a DC microgrid The average DC bus voltage and its time derivative; and All are the first k Nodes within a DC microgrid intermediate variables, and All are the first k Nodes within a DC microgrid intermediate variables, and All are the first k Intermediate variables of a TAB converter port and All are the first k The time derivative of the intermediate variable at each TAB converter port; , Represents a node Set of neighboring nodes; and All are nodes With nodes Communication weight factor, For nodes With TAB converter port Communication weighting factor; and They represent the first k The output voltage of each distributed power source port and its time derivative within a DC microgrid; and All of these are response time scale parameters.

2. The collaborative control method for DC microgrid groups based on TAB converter as described in claim 1, characterized in that, The method for estimating the port output voltage is as follows: in, and Let represent the output voltage of the k-th TAB converter port and its derivative with respect to time, respectively. and They represent the first k The average DC bus voltage at each TAB converter port and its derivative with respect to time. and All are the first k Intermediate variables of a TAB converter port; Indicates the relationship with the first k A set of nodes with communication links on each TAB port; and Indicates the first k TAB converter port and node j The weight of communication between them; and These are all parameters based on the response time scale. and All are the first k Nodes within a DC microgrid Intermediate variables.

3. The collaborative control method for DC microgrid groups based on TAB converter as described in claim 1, characterized in that, The output current value of each node in the DC microgrid is controlled by the proportional distribution of power from each source within the DC microgrid as the control objective. Alternatively, the output current value of each node with a communication link to the port can be controlled by using the proportional distribution of power among the sources in the DC microgrid as the control objective.

4. The collaborative control method for DC microgrid groups based on TAB converter as described in claim 1, characterized in that, When applying control to each node, droop control is used.

5. The collaborative control method for DC microgrid groups based on TAB converter as described in claim 1, characterized in that, When applying control to each port, phase-shift control is used.

6. A collaborative control system for DC microgrid groups based on a TAB converter, characterized in that, include: The microgrid control module is configured to: for each DC microgrid, acquire the output voltage of each distributed power source port, use a consensus algorithm to estimate the average DC bus voltage of each node, calculate the first control term of the node; control the port output current value of each node in the DC microgrid, obtain the second control term of the node, and apply control to each node in combination with the first control term of the node. The microgrid inter-control module is configured to: for each TAB converter port, obtain intermediate variables, use a consensus algorithm to estimate the average DC bus voltage of the port, calculate the first control term of the port; and control the port output current value of each node that has a communication link with the port to obtain the second control term of the port, and then apply control to each port in combination with the first control term of the port. The consensus algorithm uses multiple communication weight factors and response time scale parameters to adjust the voltage convergence speed of each DC microgrid to different degrees, or to adjust the voltage convergence speed of each port to different degrees. The goal is to stabilize the average DC bus voltage of each node at the rated value. A proportional-integral controller is used to control the average DC bus voltage of each node to obtain the first control term of the node. The goal is to stabilize the average DC bus voltage of each port at the rated value. A proportional-integral controller is used to control the average DC bus voltage of each port to obtain the first control term of the port. The method for estimating the average DC bus voltage of each node is as follows: In the formula, and They represent the first k Nodes within a DC microgrid The average DC bus voltage and its time derivative; and All are the first k Nodes within a DC microgrid intermediate variables, and All are the first k Nodes within a DC microgrid intermediate variables, and All are the first k Intermediate variables of a TAB converter port and All are the first k The time derivative of the intermediate variable at each TAB converter port; , Represents a node Set of neighboring nodes; and All are nodes With nodes Communication weight factor, For nodes With TAB converter port Communication weighting factor; and They represent the first k The output voltage of each distributed power source port and its time derivative within a DC microgrid; and All of these are response time scale parameters.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the collaborative control method for DC microgrid groups based on TAB converters as described in any one of claims 1-5.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the collaborative control method for DC microgrid groups based on TAB converter as described in any one of claims 1-5.

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