Microgrid cooperative control method and system

Abstract

This invention relates to the field of microgrid technology, providing a microgrid collaborative control method and system. The method includes: constructing a microgrid topology model based on microgrid nodes; acquiring real-time state parameters of the microgrid; calculating the node criticality index of the collaborative controller in the microgrid based on the real-time state parameters and the microgrid topology model; and configuring controller redundancy in the microgrid based on the node criticality index. This invention enables dynamic adjustment of the collaborative controller's role, allowing collaborative controllers on different microgrid nodes to be redundant and interact in real time, ensuring full resource utilization and reducing the cost of redundancy configuration. When the main controller fails or the microgrid state changes, the role of the collaborative controller can be reallocated based on the node criticality index. The redundancy configuration offers high flexibility, facilitating dynamic recovery, updating, and expansion of the microgrid. The redundancy switching time is short, effectively ensuring the stable operation of the microgrid.

Description

Technical Field

[0001] This invention relates to the field of microgrid technology, and more specifically to a microgrid collaborative control method and system. Background Technology

[0002] The stable operation of a microgrid highly depends on the reliability of its coordinating controller. To ensure high reliability, most microgrids employ controller redundancy configurations to achieve N+M redundancy in the overall controller computing resources (where N represents the minimum computing resources required for normal operation of the microgrid, and M represents the additional backup computing resources beyond N). Traditional controller redundancy configurations mostly employ static primary-backup configurations. For example, the invention patent with patent number "CN201010623243.2" entitled "Microgrid Central Controller" discloses a dual-CPU redundant coordinating controller configuration. By periodically synchronizing data between the primary and backup controllers, it ensures reliable operation of the coordinating controller through redundancy switching in the event of hardware errors, logical operation errors, or communication network errors.

[0003] While this hardware and network redundancy configuration can effectively cope with the failure of the main controller, it is difficult to cope with other hardware failures, communication interruptions, or software anomalies in the microgrid, which may lead to critical changes in the node where the controller is located. It requires a high degree of customization of the control system and lacks scalability. If the main controller and the backup controller adopt a dual-machine cold standby or dual-machine warm standby redundancy configuration, it will result in excessively long redundancy switching time, making it difficult to ensure the stable operation of the microgrid. If the main controller and the backup controller adopt a dual-machine hot standby redundancy configuration, although the redundancy switching time is shortened, it will result in low utilization of computing resources. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a microgrid collaborative control method and system. This system enables dynamic adjustment of the collaborative controller's role, allowing collaborative controllers on different microgrid nodes to be redundant and interact in real time, ensuring full resource utilization and reducing the cost of redundant configuration. When the main controller fails or the microgrid state changes, the collaborative controller's role can be reallocated based on the latest node criticality index. The redundancy configuration offers high flexibility, facilitating dynamic recovery, updating, and expansion of the microgrid. The redundancy switching time is short, effectively ensuring the stable operation of the microgrid.

[0005] The technical solution adopted in this invention is as follows:

[0006] A microgrid collaborative control method is disclosed, wherein the microgrid includes A microgrid nodes, and B of the A microgrid nodes are equipped with collaborative controllers, where A and B are both integers greater than 1, and A is greater than or equal to B. The method includes the following steps: constructing a microgrid topology model of the microgrid based on the microgrid nodes; obtaining real-time state parameters of the microgrid; calculating the node criticality index of the collaborative controller in the microgrid based on the real-time state parameters and the microgrid topology model; and configuring controller redundancy in the microgrid based on the node criticality index, wherein the controller redundancy configuration includes assigning the collaborative controller as a primary controller or a backup controller.

[0007] According to one embodiment of the present invention, the other AB microgrid nodes among the A microgrid nodes are equipped with key electrical units or independent control units.

[0008] According to one embodiment of the present invention, the microgrid topology model includes an electrical topology model and a communication topology model, the real-time state parameters include electrical parameters of the electrical topology model and communication parameters of the communication topology model, the node criticality index is obtained based on the fusion of electrical criticality and communication criticality of the co-controller, the electrical criticality is calculated based on the electrical topology model, and the communication criticality index is calculated based on the communication topology model.

[0009] According to an embodiment of the present invention, the steps of constructing the microgrid topology model specifically include: defining the key electrical unit, the independent control unit, and the microgrid node where the cooperative controller is located as physical nodes, and defining the microgrid node where the cooperative controller is located as a communication node; constructing an electrical topology and an electrical admittance matrix based on the physical nodes to obtain the electrical topology model; and constructing a communication topology and a communication Laplace matrix based on the communication nodes to obtain the communication topology model.

[0010] According to one embodiment of the present invention, the electrical criticality index of the collaborative controller is obtained by performing virtual fault simulation based on the electrical topology model.

[0011] According to one embodiment of the present invention, the virtual fault simulation includes the following steps: obtaining the steady-state operating state of the microgrid; simulating the failure of the coordinating controller, calculating the electrical impact index when the coordinating controller fails based on the electrical admittance matrix, and obtaining the electrical criticality index of the coordinating controller, wherein the electrical criticality index is calculated based on one or more electrical impact indices.

[0012] According to one embodiment of the present invention, the communication criticality index of the cooperative controller is obtained by calculating the communication network damage caused by the communication interruption of the cooperative controller based on the communication topology model in the current state and the communication topology model reconstructed after the cooperative controller is removed.

[0013] According to one embodiment of the present invention, the communication network impairment is obtained by comparing the algebraic connectivity of the communication Laplace matrix in the current state and the reconstructed communication Laplace matrix.

[0014] According to one embodiment of the present invention, the step of configuring controller redundancy for the microgrid based on the node criticality index specifically includes: when the microgrid is in a steady-state operation, periodically updating the node criticality index of all cooperating controllers, and selecting the cooperating controller with the lowest node criticality index as the main controller or standby controller; when the main controller in the microgrid fails, generating a candidate set based on all standby controllers, simulating the node criticality index of each standby controller in the candidate set after becoming the main controller, and selecting the standby controller with the lowest simulated node criticality index as the main controller.

[0015] In addition, to address the above problems, this invention also proposes a microgrid collaborative control system.

[0016] A microgrid collaborative control system, wherein the microgrid includes A microgrid nodes, and B of the A microgrid nodes are equipped with collaborative controllers, where A and B are both integers greater than 1, and A is greater than or equal to B. The system includes: a modeling module, which constructs a microgrid topology model of the microgrid based on the microgrid nodes; an acquisition module, which acquires real-time state parameters of the microgrid; a calculation module, which calculates the node criticality index of the collaborative controllers in the microgrid based on the real-time state parameters and the microgrid topology model; and a configuration module, which performs controller redundancy configuration of the microgrid based on the node criticality index, wherein the controller redundancy configuration includes assigning the collaborative controllers as a primary controller or a backup controller.

[0017] The beneficial effects of this invention are:

[0018] The microgrid collaborative control method of this invention constructs a microgrid topology model including the microgrid nodes where the collaborative controllers reside, serving as the basis for collaborative control. Based on the real-time state parameters of the microgrid and the microgrid topology model, it calculates the node criticality index of the collaborative controllers within the microgrid. Based on this index, it performs controller redundancy configuration, enabling dynamic adjustment of the collaborative controllers' roles. This allows collaborative controllers on different microgrid nodes to be mutually redundant and interact in real time, ensuring full resource utilization. This eliminates the need for additional hardware backups on the same microgrid node, reducing the cost of redundancy configuration. When a main controller failure or microgrid state change causes significant changes in the node criticality index of each controller, the collaborative controllers' roles in the controller redundancy configuration can be reallocated based on the latest node criticality index. This redundancy configuration offers high flexibility, facilitating dynamic recovery, updating, and expansion of the microgrid. Furthermore, collaborative controllers located on other microgrid nodes inherently possess control functions and are already operational, resulting in short redundancy switching times. This effectively ensures stable microgrid operation, and equipment in the faulty area will not be affected by fault and communication recovery, maintaining the microgrid's continuous and stable operation. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of a microgrid structure according to a specific embodiment of the present invention;

[0020] Figure 2 This is a flowchart of a microgrid collaborative control method according to an embodiment of the present invention;

[0021] Figure 3 This is a block diagram of a microgrid collaborative control system according to an embodiment of the present invention;

[0022] Figure 4 This is a block diagram of a microgrid collaborative control system according to an embodiment of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] The microgrid in this embodiment of the invention includes A microgrid nodes, wherein B of the A microgrid nodes are equipped with a cooperative controller, where A and B are both integers greater than 1, and A is greater than or equal to B.

[0025] Understandably, the collaborative controller, as the main device participating in the collaborative control of the microgrid, can be placed on one or both sides of the critical electrical unit or independent control unit to avoid affecting the stable operation of the microgrid if the critical electrical unit or independent control unit fails. The critical electrical unit can be a distributed power source (such as photovoltaic, wind turbine, diesel generator, energy storage unit), load, etc., while the independent control unit can be an STS (Static Transfer Switch), circuit breaker, tie switch, etc.

[0026] When A=B, each microgrid node is equipped with a coordination controller. The parameters of key electrical units and independent control units under the control of the coordination controller can be fed back through the coordination controller and participate in the microgrid coordination control. When A>B, the other AB microgrid nodes among the A microgrid nodes can be equipped with key electrical units or independent control units. When the coordination controller or equipment fails and the microgrid topology model needs to be reconstructed, the impact of key electrical units and independent control units on the microgrid coordination control can be fully considered.

[0027] like Figure 1 As shown, in a specific embodiment of the present invention, the key electrical units of the microgrid include a regular charging pile a1, a load a2, a diesel generator a3, a V2G charging pile a4, a wind turbine a4, a photovoltaic a5, and an energy storage a6. Each key electrical unit can be connected to a corresponding co-controller via a switch. The hollow circle between the switch and the key electrical unit represents the microgrid node corresponding to the key electrical unit. The co-controllers corresponding to the regular charging pile a1, load a2, diesel generator a3, V2G (Vehicle-to-Grid) charging pile a4, wind turbine a5, photovoltaic a6, and energy storage a7 are v1 to v7, respectively. The independent control unit of the microgrid includes an incoming line switch and an STS switch. Since co-controllers v8 and v9 are respectively located on both sides of the incoming line switch connecting the microgrid to the grid, and co-controllers v10 and v11 are also respectively located on both sides of the STS switch on the microgrid bus, each co-controller can correspond to a microgrid node. Therefore, these switches themselves do not need to be repeatedly defined as separate microgrid nodes. In the figure, the hollow circle corresponding to each co-controller represents the microgrid node it corresponds to. Figure 1 The microgrid in the illustrated embodiment includes 18 microgrid nodes, 11 of which are equipped with a cooperative controller.

[0028] It is understandable that, in order to avoid long-term full-load operation, most collaborative controllers will reserve a certain margin of computing resources. Therefore, even without additional static backup controller redundancy in the microgrid, the computing resources among multiple collaborative controllers can be reasonably allocated by adjusting the roles of multiple collaborative controllers in the controller redundancy configuration, thus satisfying the N+M redundancy of the microgrid.

[0029] like Figure 2 As shown, the microgrid cooperative control method of this invention includes the following steps:

[0030] S1, a microgrid topology model based on microgrid nodes to construct a microgrid.

[0031] S2, obtain the real-time status parameters of the microgrid.

[0032] S3 calculates the node criticality index of the cooperative controller in the microgrid based on real-time state parameters and microgrid topology model.

[0033] S4, based on the node criticality index, configures controller redundancy for the microgrid. Controller redundancy configuration includes assigning the coordinating controller to the master controller or the standby controller.

[0034] According to the microgrid collaborative control method of the present invention, a microgrid topology model containing the microgrid node where the collaborative controller is located is constructed as the basis for collaborative control. Based on the real-time state parameters of the microgrid and the microgrid topology model, the node criticality index of the collaborative controller in the microgrid is calculated. Based on the node criticality index, the controller redundancy configuration of the microgrid is performed, realizing the dynamic adjustment of the role of the collaborative controller. This allows collaborative controllers on different microgrid nodes to be redundant with each other and interact in real time, ensuring full utilization of resources. As a result, additional hardware backup is not required on the same microgrid node, reducing the cost of redundancy configuration.

[0035] When the main controller fails, or other hardware failures, communication interruptions, or software anomalies occur in the microgrid, causing significant changes in the node criticality indices of each controller, the role of the co-controller originally assigned to the main controller can be cancelled based on the latest node criticality indices. The co-controllers on other microgrid nodes that were originally in the role of backup controllers can be assigned to the main controller to achieve redundancy switching. Redundancy configuration is highly flexible, facilitating the dynamic recovery, updating, and expansion of the microgrid. Moreover, the co-controllers on other microgrid nodes themselves have control functions, i.e., they are in working state. Therefore, the redundancy switching time is short, which can effectively ensure the stable operation of the microgrid. The equipment in the faulty area will not affect the continuous and stable operation of the microgrid during the fault and communication recovery.

[0036] In one embodiment of the present invention, the microgrid topology model includes an electrical topology model and a communication topology model. Step S1, the step of constructing the microgrid topology model, specifically includes the following steps S11-S13:

[0037] S11 defines the microgrid nodes containing key electrical units, independent control units, and collaborative controllers as physical nodes, and the microgrid nodes containing collaborative controllers as communication nodes. It is understood that the microgrid node containing the collaborative controller has dual functions of electrical transmission and communication transmission; therefore, the microgrid node containing the collaborative controller has a dual definition as both a physical node and a communication node.

[0038] S12, construct the electrical topology and electrical admittance matrix based on physical nodes to obtain the electrical topology model.

[0039] Specifically, the node model in power system analysis can be referenced to accurately depict the topological connections between physical nodes. Physical connection units such as transmission lines and transformers between physical nodes are used as edge sets, and physical parameters such as line impedance, capacity limitations, and power flow are used as edge weight sets to construct the electrical topology. The electrical admittance matrix Y is then constructed based on Kirchhoff's current law and network element parameters. bus Among them, the electrical admittance matrix Y bus The diagonal element Y in ii The self-admittance is defined as follows: The self-admittance of node i is equal to the sum of the admittances of all branches connected to that node, plus the admittance of the node's branches to ground (such as capacitors, reactors, etc.), reflecting the "electrical connection strength" of node i with the entire electrical topology. Its calculation formula is as follows:

[0040]

[0041] Among them, y ik It is the branch admittance connecting node i to other nodes k, y i,sh It is the ground branch admittance of node i.

[0042] Electrical admittance matrix Y bus The off-diagonal element y in ij The mutual admittance is defined as follows: the mutual admittance between node i and node j is equal to the negative of the sum of the admittances of all branches connecting these two nodes, in order to reflect the strength of the direct electrical coupling between nodes i and j.

[0043] S13. Based on the communication nodes, construct the communication topology and communication Laplace matrix to obtain the communication topology model. Similar to the electrical topology, the links that directly communicate between the various coordinating controllers, which act as communication nodes, can be used as the set of edges to construct the communication topology. The communication Laplace matrix is ​​used as a mathematical tool to describe the communication topology.

[0044] Specifically, the communication topology can be described by the adjacency matrix, the degree matrix can be used to reflect the tightness of the connection between each communication node, and the graph Laplace matrix of the communication topology (i.e., the communication Laplace matrix) can be obtained by operating on the adjacency matrix and the degree matrix, as shown in the following formula:

[0045]

[0046] Where L represents the communication Laplace matrix, D represents the degree matrix, and A represents the adjacency matrix. The spectral properties of the communication Laplace matrix (such as eigenvalues) can reveal important information about the graph's connectivity and algebraic connectivity, reflecting network dynamics and design consistency. The second smallest eigenvalue of L is denoted as... This is called the algebraic connectivity of the graph. The larger the value, the tighter the network connection, and the faster the information spreads and converges within the network.

[0047] In step S2, the real-time status parameters of the microgrid are obtained, including electrical parameters of the electrical topology model (such as node voltage, current, frequency, power, etc.) and communication parameters of the communication topology model (such as circuit breaker open / close status, generator operating status, energy storage SOC, etc.), which are used to calculate the electrical criticality index and communication criticality index of the co-controller based on the electrical topology model and the communication topology model.

[0048] In one embodiment of the present invention, in step S3, the node criticality index is obtained by fusing the electrical criticality index and the communication criticality index of the collaborative controller.

[0049] In one embodiment of the present invention, the electrical criticality index of the cooperative controller is obtained by virtual fault simulation based on an electrical topology model. Specifically, the virtual fault simulation may include the following steps S31 and S32:

[0050] S31 obtains the steady-state operating status of the microgrid, including electrical parameters such as voltage V0, active power P0, and reactive power Q0 of all physical nodes.

[0051] S32, Simulate the failure of the coordinated controller, calculate the electrical impact index when the coordinated controller fails based on the electrical admittance matrix, and obtain the electrical criticality index of the coordinated controller. The electrical criticality index can be calculated based on one or more electrical impact indices.

[0052] It is understandable that different types of faults in co-controllers with different locations and functions will have different impacts on the electrical admittance matrix. When the co-controller is in normal condition, the microgrid operates in steady state, and each element in the electrical admittance matrix constructed in step S12 can be obtained based on power flow calculations. When the co-controller fails in its static redundancy with other co-controllers (e.g., due to software or hardware failure), the redundant co-controllers can take over the relevant functions of the failed part without directly causing power disturbances. Therefore, the electrical criticality index of the co-controller at this time can be defined as 0 or a custom minimum value. When the part of the distributed generation controlled by the co-controller fails, and the failed part does not have static redundancy, the control commands received by the distributed generation will change, resulting in unreasonable power fluctuations.

[0053] The following specific embodiment illustrates how, when the cooperative controller directly connected to the distributed power source fails, the electrical admittance matrix Y... bus The specific calculation process for the electrical criticality index.

[0054] When the co-controller is directly connected to the distributed power source via a switch, simulating the failure of the co-controller results in the most direct consequence being that the output of the distributed power source it controls becomes zero, or it is disconnected from the grid. When the distributed power source is a power generation device (such as a photovoltaic, wind turbine, or diesel generator), if the co-controller communicating with the power generation device malfunctions, the corresponding power generation device will generally go into standby or stop. This is equivalent to applying a power disturbance of equal magnitude but opposite direction to the physical node i where the simulated failed co-controller is located.

[0055] Power disturbances can cause electrical impacts on microgrids, including voltage shifts and line overloads. In one embodiment of the present invention, this impact can be mitigated by utilizing an electrical admittance matrix Y. bus The power flow sensitivity analysis method calculates electrical impact indicators such as the global voltage deviation index and the line overload risk index. By weighted fusion of these electrical impact indicators, the impact of power disturbances on the microgrid is obtained, namely the electrical criticality index.

[0056] Specifically, the global voltage offset index I Vdec The formula for calculating (i) is:

[0057]

[0058] Where, ΔV j The voltage offset of physical node j caused by the failure of the co-controller where physical node i resides can be expressed by the system's Jacobian matrix (which can be derived from the electrical admittance matrix Y). bus (Derived) Approximate calculation, where N represents the total number of physical nodes in the electrical topology. The load importance weight relative to voltage can be set by considering the impact of the load of physical node j on voltage under line failure.

[0059] Line overload risk index I Lovi The formula for calculating (i) is:

[0060]

[0061] in, This represents the power flow of the k-th line (i.e., the edge in the electrical topology) after the failure of the cooperative controller where physical node i resides. M represents the maximum transmission capacity of this line, and M represents the total number of lines in the electrical topology. This represents the load importance weight relative to the line, and can be set to consider the impact of the load of physical node j on power in the event of line failure.

[0062] In a specific embodiment of the present invention, the electrical criticality index ECI(i) of physical node i may include only the two impact indicators mentioned above, and its calculation formula is as follows:

[0063]

[0064] In the formula, α1 and α2 represent the weights of the global voltage deviation index and the line overload risk index, respectively, and can be adjusted according to specific needs. As can be seen from the formula, the higher the value of the electrical criticality index ECI(i), the greater the impact on the stable operation of the microgrid electrical system if the coordinating controller of physical node i fails, and therefore its electrical criticality is higher. In some other embodiments of the present invention, only one electrical impact index, such as the global voltage deviation index or the line overload risk index, can be selected as the electrical criticality index; this embodiment does not limit this.

[0065] In one embodiment of the present invention, the communication criticality index of the cooperative controller can be obtained by calculating the communication network damage caused by the communication interruption of the cooperative controller based on the communication topology model in the current state and the communication topology model reconstructed after the cooperative controller is removed.

[0066] In one embodiment of the present invention, communication network impairment can be obtained by comparing the algebraic connectivity of the current state communication Laplace matrix and the reconstructed communication Laplace matrix. The specific calculation process is described in steps S33-S35:

[0067] S33, Calculate the algebraic connectivity of the current state based on the communication Laplace matrix of the current state. .

[0068] S34. Calculate the reconstructed algebraic connectivity based on the reconstructed communication Laplace matrix after removing communication node i. .

[0069] S35, the Communication Criticality Index (CCI(i)) is defined as the degree or rate of decline of algebraic connectivity (i.e., communication network impairment), and is calculated. When the Communication Criticality Index is defined as the degree of decline of algebraic connectivity, its calculation formula is as follows:

[0070]

[0071] When the communication criticality index is defined as the rate of decline of algebraic connectivity, its calculation formula is:

[0072]

[0073] The calculation of CCI(i) aims to more clearly characterize the degradation changes in the communication network. To make CCI(i) more accurately characterize... The difference in change, when When the value is large, the comparison of the descent rate is more direct; when When the value is small, the rate of decline is more pronounced than the degree of decline. Therefore, the calculation method of the communication criticality index can be dynamically adjusted according to the number of collaborative controllers, for example:

[0074]

[0075] Where B represents the total number of collaborative controllers, and n represents the preset switching value, which can be set based on experience.

[0076] Understandably, if removing the coordinating controller of communication node i has little impact on algebraic connectivity, it indicates that the coordinating controller is located at the "edge" of the communication topology, or its connection has high redundancy, and its failure will not seriously affect the coordination of overall control information. If removing the coordinating controller of communication node i causes a significant drop in algebraic connectivity, even approaching or equaling 0, it indicates that communication node i is a critical node of a cut vertex or bridge. Once the coordinating controller on this node fails, it will cause the communication topology to split into multiple inaccessible islands, causing the coordinating control mechanism to collapse. Therefore, the communication criticality of this coordinating controller is extremely high.

[0077] The node criticality index GCI(i) of the collaborative controller can be obtained by weighted fusion of the electrical criticality index ECI(i) and the communication criticality index CCI(i) in the above embodiments:

[0078]

[0079] In the formula, Welec W comm These represent the weights of ECI(i) and CCI(i), respectively, and can be adjusted according to the microgrid's operating strategy and security requirements. In a microgrid with extremely high voltage quality requirements, W can be increased. elec The proportion of W should be increased. In a microgrid with a complex topology that highly relies on cooperative control to suppress oscillations, the proportion of W should be increased. comm The higher the GCI(i) index, the more critical the co-controller is to the stable operation of the entire microgrid system.

[0080] In one embodiment of the present invention, step S4 may specifically include the following steps S41-S42:

[0081] S41. When the microgrid is in steady-state operation, the node criticality index of all coordinating controllers is periodically updated (the update frequency can be on a minute or hourly basis or adjusted according to the specific situation) to facilitate active management. Coordinating controllers with low node criticality indexes are selected as the main controller or backup controller.

[0082] As discussed above, a low node criticality index means that even if the controller fails, the overall impact on the system is smaller, and the cost of sacrificing it is lower. After calculating the node criticality indices of all coordinating controllers, the coordinating controller with the lowest node criticality index can be selected as the master controller. When the microgrid is divided into multiple regions, the coordinating controller with the lowest node criticality index in each region can be selected as the master controller for that region. At the same time, among the other coordinating controllers in the same region, a coordinating controller with a low node criticality index and a significant difference in physical and communication location from the selected master controller can be selected as a backup controller to achieve dynamic optimization of redundant resources.

[0083] After updating the node criticality index of all coordinating controllers, risk warnings can also be issued for each coordinating controller. If a node criticality index of a certain controller suddenly increases, an early warning can be issued to remind the operation and maintenance personnel that the node where the controller is located is a sudden weak point in the microgrid and needs to be closely monitored or its physical / communication link redundancy configuration should be enhanced.

[0084] S42, when the main controller in the microgrid fails (e.g., heartbeat loss, data anomaly, etc.), a candidate set is generated based on all backup controllers, the node criticality index of each backup controller in the candidate set after becoming the main controller is simulated, and the backup controller with the lowest node criticality index after simulation is selected as the main controller.

[0085] Specifically, a candidate set can be generated by filtering out healthy and available collaborative controllers from the pool of all backup controllers. ,in, Represents the 1st, 2nd to kth backup controllers in the candidate set; for candidate set S backup Each standby controller in the system undergoes a virtual "pre-switchover" simulation to calculate the node criticality index (ECI) under the new controller redundancy configuration if the standby controller were to take over the primary controller's operation. new (b j Select ECI; new (b j The lowest-ranking backup controller is selected as the primary controller, thus preserving other "more important" redundant resources to ensure the stable operation of the microgrid. Once the primary controller is selected, the corresponding activation command can be sent to it, and commands can be sent to other relevant devices in the microgrid (such as switches) to complete the switching of electrical and communication links, allowing it to seamlessly take over the functions of the faulty primary controller.

[0086] Therefore, in the above embodiments, the electrical topology model and the communication topology model are treated as parallel models. The node criticality index is obtained by fusing the electrical and communication criticality indices of the cooperating controller in both models, and dynamic controller redundancy configuration is achieved based on the node criticality index. In some other embodiments of the present invention, controller redundancy configuration of the microgrid can be further implemented by comprehensively considering parameters such as the computational resource margin and communication quality of the cooperating controller itself, based on the node criticality index (for example, when the computational resource margin and communication quality of the cooperating controller are low, avoid assigning the cooperating controller as the master controller or backup controller, and only allow it to perform its original work tasks). The microgrid topology model can also be a model where the communication topology formed by the microgrid node where the cooperating controller is located is the upper-layer model, and the electrical topology model formed by other microgrid nodes controlled by each microgrid node in the communication topology is the lower-layer model. This connects the communication layer and the physical layer of the microgrid, and calculates the node criticality index of the cooperating controller in the microgrid from bottom to top. This embodiment does not impose any limitations on this.

[0087] Corresponding to the microgrid collaborative control method described above, this invention also proposes a microgrid collaborative control system. Since the system embodiments of this invention correspond to the method embodiments described above, details not disclosed in the system embodiments can be found in the method embodiments described above, and will not be repeated here.

[0088] like Figure 3As shown, the microgrid collaborative control system of this embodiment includes: a modeling module 10, an acquisition module 20, a calculation module 30, and a configuration module 40. The modeling module 10 constructs a microgrid topology model based on microgrid nodes; the acquisition module 20 is used to acquire real-time state parameters of the microgrid; the calculation module 30 calculates the node criticality index of the collaborative controller in the microgrid based on the real-time state parameters and the microgrid topology model; the configuration module 40 performs controller redundancy configuration on the microgrid based on the node criticality index. The controller redundancy configuration includes assigning the role of the collaborative controller, such as assigning it as a primary controller or a backup controller. The microgrid node where the collaborative controller is located may have partial redundancy in electrical functions (e.g., set at both ends of the grid connection switch, with partial overlap in control functions). The collaborative controller on the critical microgrid node can be set as primary and backup redundancy. The microgrid collaborative control system of this invention can be deployed at the station or on a cloud platform, and this embodiment does not limit this.

[0089] According to embodiments of the present invention, the microgrid collaborative control system constructs a microgrid topology model including the microgrid nodes where the collaborative controllers reside, serving as the basis for collaborative control. Based on the real-time state parameters of the microgrid and the microgrid topology model, the node criticality index of the collaborative controllers in the microgrid is calculated. Based on this node criticality index, controller redundancy is configured for the microgrid, enabling dynamic adjustment of the collaborative controllers' roles. This allows collaborative controllers on different microgrid nodes to be mutually redundant and interact in real time, ensuring full resource utilization. This eliminates the need for additional hardware backups on the same microgrid node, reducing the cost of redundancy configuration. When the main controller fails or the node criticality indexes of each controller change significantly, the roles of the collaborative controllers in the controller redundancy configuration can be reallocated based on the latest node criticality index. The redundancy configuration offers high flexibility, facilitating dynamic recovery, updating, and expansion of the microgrid. Furthermore, the collaborative controllers located on other microgrid nodes inherently possess control functions, meaning they are already in operation. Therefore, the redundancy switching time is short, effectively ensuring the stable operation of the microgrid. Equipment in the faulty area will not affect the continuous and stable operation of the microgrid during fault and communication recovery.

[0090] In one embodiment of the present invention, the power grid topology model includes an electrical topology model and a communication topology model. The modeling module 10 can construct a microgrid topology model based on steps S11 to S13 in the above embodiment. The acquisition module 20 acquires the real-time state parameters of the microgrid, including electrical parameters of the electrical topology model (e.g., node voltage, current, frequency, power, etc.) and communication parameters of the communication topology model (e.g., circuit breaker opening and closing status, generator operating status, energy storage SOC, etc.), for calculating the electrical criticality index and communication criticality index of the co-controller based on the electrical topology model and the communication topology model. The calculation module 30 can obtain the node criticality of the co-controller based on the fusion of the electrical criticality index and the communication criticality index of the co-controller.

[0091] In one embodiment of the present invention, the electrical criticality index of the cooperative controller is obtained by performing virtual fault simulation based on the electrical topology model. Specifically, the virtual fault simulation may include steps S31-S32 described above; the communication criticality index of the cooperative controller can be obtained by calculating the communication network damage caused by the communication interruption of the cooperative controller based on the communication topology model in the current state and the reconstructed communication topology model after the cooperative controller is removed. The communication network damage can be obtained by comparing the algebraic connectivity of the communication Laplace matrix in the current state and the reconstructed communication Laplace matrix. The specific calculation steps are described in steps S33-S35 described above.

[0092] In one embodiment of the present invention, when the microgrid is in steady state operation, the node criticality index of all cooperating controllers is periodically updated based on the modeling module 10, the acquisition module 20 and the calculation module 30 (the update frequency can be on the order of minutes, hours or adjusted according to the specific situation), so that the configuration module 40 can realize active management. When configuring controller redundancy, the configuration module 40 can select the cooperating controller with low node criticality index as the main controller or the backup controller.

[0093] After obtaining the updated node criticality index of all coordinating controllers, the configuration module 40 can also provide risk warnings for each coordinating controller. If it finds that the node criticality index of a certain controller suddenly increases, it can issue an early warning to remind the operation and maintenance personnel that the node where the controller is located is a sudden weak point of the microgrid, which needs to be closely monitored or its physical / communication link redundancy configuration should be enhanced.

[0094] like Figure 4As shown, the configuration module 40 can also be communicatively connected to the modeling module 10, the acquisition module 20, and the calculation module 30 respectively. When the acquisition module 20 detects a fault in the main controller of the microgrid (such as heartbeat loss, data abnormality, etc.) through the acquired real-time status parameters, the configuration module 40 can generate a candidate set based on all backup controllers. Based on the modeling module 10 and the calculation module 30, it simulates the node criticality index of each backup controller in the candidate set after it becomes the main controller. The backup controller with the lowest node criticality index after simulation is selected as the main controller. The modeling module 10 is used to reconstruct the microgrid topology model in a virtual simulation of "pre-switching" for each backup controller in the candidate set. The calculation module 30 calculates the node criticality index under the new controller redundancy configuration state if the backup controller takes over the work of the main controller. The specific configuration process can be referred to the relevant content in the above method embodiment, and will not be repeated here.

[0095] In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0096] The execution order of the steps shown in the flowchart is the preferred implementation. In other embodiments of the present invention, the order can be adjusted according to the functions involved in each step, for example, they can be executed simultaneously or in the reverse order.

[0097] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequential list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in connection with, an instruction execution system, apparatus, or device. For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit a program for use by, or in connection with, an instruction execution system, apparatus, or device.

[0098] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0099] Furthermore, the functional units in the various embodiments of the present invention can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

Claims

1. A microgrid collaborative control method, characterized in that, The microgrid includes A microgrid nodes, wherein B of the A microgrid nodes are equipped with a cooperative controller, where A and B are both integers greater than 1, and A is greater than or equal to B. The method includes the following steps: A microgrid topology model of the microgrid is constructed based on the microgrid nodes; Obtain the real-time status parameters of the microgrid; Based on the real-time status parameters and the microgrid topology model, the node criticality index of the cooperative controller in the microgrid is calculated. The microgrid is configured with controller redundancy based on the node criticality index. The controller redundancy configuration includes assigning the coordinating controller to a master controller or a standby controller.

2. The microgrid collaborative control method according to claim 1, characterized in that, The other AB microgrid nodes among the A microgrid nodes are equipped with key electrical units or independent control units.

3. The microgrid collaborative control method according to claim 1 or 2, characterized in that, The microgrid topology model includes an electrical topology model and a communication topology model. The real-time status parameters include electrical parameters of the electrical topology model and communication parameters of the communication topology model. The node criticality index is obtained by fusing the electrical criticality and communication criticality of the co-controller. The electrical criticality is calculated based on the electrical topology model, and the communication criticality index is calculated based on the communication topology model.

4. The microgrid collaborative control method according to claim 3, characterized in that, The steps for constructing the microgrid topology model specifically include: The key electrical units, independent control units, and the microgrid nodes where the collaborative controller is located are defined as physical nodes, and the microgrid nodes where the collaborative controller is located are defined as communication nodes. Based on the physical nodes, an electrical topology and electrical admittance matrix are constructed to obtain the electrical topology model; Based on the communication nodes, a communication topology and a communication Laplace matrix are constructed to obtain the communication topology model.

5. The microgrid collaborative control method according to claim 4, characterized in that, The electrical criticality index of the collaborative controller is obtained by performing virtual fault simulation based on the electrical topology model.

6. The microgrid collaborative control method according to claim 5, characterized in that, The virtual fault simulation includes the following steps: Obtain the steady-state operating status of the microgrid; The failure of the coordinated controller is simulated, and the electrical impact index at the time of the failure is calculated based on the electrical admittance matrix to obtain the electrical criticality index of the coordinated controller. The electrical criticality index is calculated based on one or more of the electrical impact indices.

7. The microgrid collaborative control method according to claim 4, characterized in that, The communication criticality index of the coordinating controller is calculated based on the communication topology model in the current state and the reconstructed communication topology model after the coordinating controller is removed, and is obtained by calculating the communication network damage caused by the communication interruption of the coordinating controller.

8. The microgrid collaborative control method according to claim 7, characterized in that, The damage to the communication network is obtained by comparing the algebraic connectivity of the communication Laplace matrix in the current state with that of the reconstructed communication Laplace matrix.

9. The microgrid collaborative control method according to claim 1, characterized in that, The steps for configuring controller redundancy in the microgrid based on the node criticality index specifically include: When the microgrid is in steady-state operation, the node criticality index of all coordinating controllers is periodically updated, and the coordinating controller with the lowest node criticality index is selected as the main controller or the backup controller. When the main controller in the microgrid fails, a candidate set is generated based on all backup controllers. The node criticality index of each backup controller in the candidate set after becoming the main controller is simulated, and the backup controller with the lowest node criticality index after simulation is selected as the main controller.

10. A microgrid collaborative control system, characterized in that, The microgrid includes A microgrid nodes, wherein B of the A microgrid nodes are equipped with a cooperative controller, where A and B are both integers greater than 1, and A is greater than or equal to B. The system includes: A modeling module that constructs a microgrid topology model of the microgrid based on the microgrid nodes; An acquisition module is used to acquire the real-time status parameters of the microgrid; The calculation module calculates the node criticality index of the cooperative controller in the microgrid based on the real-time status parameters and the microgrid topology model. The configuration module configures controller redundancy for the microgrid based on the node criticality index. The controller redundancy configuration includes assigning the coordinating controller to a primary controller or a backup controller.

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