Distributed reactor coordinated control method and device

Abstract

The present invention discloses a method and device for coordinated control of distributed reactors, and relates to the field of electric power technology. The method comprises: taking electric power equipment as network nodes, constructing a distributed topology based on edge connection relationships, wherein the nodes have unique labels, and the edges include physical edges and virtual edges. Dividing distributed clusters through community cluster detection, wherein the clusters contain at least one reactor node. Constructing an event database, covering coordinated event classes and reactor parameter control information. Based on the topology, cluster and event databases, supervising the training of a cascade decision module. Collecting electrical data, combining the decision module to perform cluster greedy decision-making and boundary sharing interaction, determining a cascade coordination strategy, and realizing coordinated control of distributed reactors. Thereby achieving the technical effect of improving control responsiveness and improving the efficiency of the power system.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power, and particularly to a coordinated control method and device for distributed reactors. Background Art

[0002] With the expansion of the scale of the power system and the rapid development of distributed energy, the number and complexity of power equipment have increased significantly. As one of the important power equipment, reactors play an important role in regulating the grid voltage and reactive power. Existing reactor control schemes mostly rely on a centralized control system, which is globally managed by a central control center. This method is suitable for traditional centralized power systems, but for distributed power systems, due to the high real-time requirements between nodes, centralized control is prone to problems such as data transmission delay and slow decision response. In addition, some methods adopt independent reactor control, failing to fully utilize the potential of overall system coordination and optimization, resulting in low system operation efficiency. In summary, the existing technologies have technical problems of slow control response and low coordination efficiency. Summary of the Invention

[0003] The present invention provides a coordinated control method and device for distributed reactors to solve the technical problems of slow control response and low coordination efficiency in the existing technologies, and achieve the technical effects of improving control responsiveness and enhancing the efficiency of the power system.

[0004] In a first aspect, the present invention provides a coordinated control method for distributed reactors, wherein the method includes:

[0005] For a distributed power system, taking power equipment as network nodes, a distributed topology is constructed based on edge connection relationships, wherein each network node based on a reactor has a unique label, and the edge connection includes an entity edge based on electrical connection and a virtual edge based on a control relationship.

[0006] Based on the distributed topology, by performing community cluster detection and division, distributed clusters are determined, wherein each distributed cluster includes at least one reactor network node.

[0007] An event database is constructed, and the event database covers coordination event classes - information pairs based on a predetermined schedule and event status - reactor parameter control.

[0008] According to the distributed topology, the distributed clusters, and the event database, a cascade decision module is supervised and trained.

[0009] An acquisition unit obtains the electrical data of the distributed power system, and in combination with the cascade decision module, performs cluster greedy decision-making and necessary boundary sharing interaction between clusters to determine a cascade coordination strategy.

[0010] Based on the cascade coordination strategy, coordinated control of distributed reactors is performed.

[0011] In a second aspect, the present invention further provides a coordinated control device for distributed reactors. Among them, the device includes:

[0012] A topology connection component, which is used for a distributed power system, with power equipment as network nodes, to construct a distributed topology based on edge connection relationships. Among them, each network node based on the reactor has a unique label, and the edge connection includes an entity edge based on electrical connection and a virtual edge based on control relationship.

[0013] A cluster division component, which is used to determine distributed clusters by performing community cluster detection and division based on the distributed topology. Among them, each distributed cluster includes at least one reactor network node.

[0014] An event organization component, which is used to construct an event database that covers coordination event classes - information pairs based on a predetermined schedule and event status - reactor parameter control.

[0015] A decision shaping component, which is used to supervise and train a cascade decision module according to the distributed topology, the distributed clusters, and the event database.

[0016] An acquisition and decision component, which is used for an acquisition unit to obtain electrical data of the distributed power system, and in combination with the cascade decision module, perform cluster greedy decision-making and necessary boundary sharing interaction between clusters to determine a cascade coordination strategy.

[0017] A distribution and execution component, which is used to perform coordinated control of distributed reactors based on the cascade coordination strategy.

[0018] The present invention discloses a coordinated control method and device for distributed reactors, including: for a distributed power system, using power equipment as network nodes, constructing a distributed topology based on edge connection relationships, where each reactor network node has a unique label, and the edge connection relationships include physical edges based on electrical connections and virtual edges based on control relationships; through the distributed topology, performing community cluster detection and dividing distributed clusters, each cluster containing at least one reactor network node; establishing an event database that covers coordinated event categories, information pairs based on a predetermined schedule and event status, and relevant data on reactor participation and control; according to the distributed topology, distributed clusters, and event database, supervising and training a cascade decision-making module; a collection unit for obtaining electrical data of the distributed power system, combining with the cascade decision-making module, performing greedy decision-making within the cluster and boundary sharing interaction between clusters to determine a cascade coordination strategy; based on the cascade coordination strategy, coordinating and controlling the distributed reactors. The coordinated control method and device for distributed reactors disclosed by the present invention solve the technical problems of slow control response and low coordination efficiency, and achieve the technical effects of improving control responsiveness and power system efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic flow chart of the coordinated control method for distributed reactors of the present invention;

[0020] Figure 2 It is a schematic structural diagram of the coordinated control device for distributed reactors of the present invention.

[0021] Description of reference numerals: Topology connection component 11, cluster division component 12, event organization component 13, decision shaping component 14, collection and decision component 15, sending and execution component 16. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] In the embodiments of the present invention, the overall idea adopted for solving the technical problems of slow control response and low coordination efficiency existing in the prior art is as follows:

[0023] First, taking power equipment as network nodes, a distributed topology is constructed based on edge connection relationships. Among them, each network node of the reactor has a unique label, and the edge connections include physical edges based on electrical connections and virtual edges based on control relationships. Then, based on the distributed topology, community cluster detection and division are carried out to determine distributed clusters, and each distributed cluster contains at least one reactor network node. Then, an event database is constructed, covering coordination event classes, information pairs based on a predetermined schedule and event status, and reactor parameter control. Next, combining the distributed topology, distributed clusters, and event database, a cascade decision-making module is supervised and trained. Furthermore, the acquisition unit obtains electrical data of the distributed power system and performs cluster greedy decision-making and necessary boundary sharing interaction between clusters through the cascade decision-making module to determine a cascade coordination strategy. Finally, based on this cascade coordination strategy, coordinated control of the distributed reactor is carried out.

[0024] The above technical solutions will be described in detail below in conjunction with the accompanying drawings of the specification and specific embodiments to better understand the above technical solutions. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments of the present invention. It should be understood that the present invention is not limited to the example embodiments used to explain the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention. In addition, it should be noted that for the sake of description, only parts related to the present invention are shown in the drawings rather than all.

[0025] Embodiment 1

[0026] Figure 1 It is a flowchart of the method for coordinated control of distributed reactors according to the present invention. Among them, the method includes:

[0027] For a distributed power system, taking power equipment as network nodes, a distributed topology is constructed based on edge connection relationships. Among them, each network node based on the reactor has a unique label, and the edge connections include physical edges based on electrical connections and virtual edges based on control relationships.

[0028] Specifically, first, a distributed topology of the target distributed power system is established. This distributed topology is used to represent the connection relationships of multiple power equipment in the target distributed power system. Among them, the connection relationships include physical connection relationships (based on electrical connections) and logical connection relationships (based on control relationships). The physical edges and virtual edges in the distributed topology together constitute a complete system connection model, which helps to accurately understand and analyze the physical and control relationships in the target distributed power system.

[0029] Specifically, various power equipment in the distributed power system (such as generators, transformers, reactors, loads, etc.) are abstracted as network nodes, which are the basic units for operation and dispatch in the system. These nodes represent the roles and positions of power equipment in the system and form a distributed topology through various connection relationships (such as electrical connections, control relationships).

[0030] Specifically, in the distributed topology, according to the layout of the reactors, multiple network nodes are traversed for unique labeling. In other words, the unique label is the reactor label, which is used to identify the specific location, equipment type, and its role in the system of the node.

[0031] Specifically, the physical edges represent the physical connection relationships between power equipment, usually directly connected through transmission lines, cables, etc. These physical connections form the current and voltage transmission paths of the power system and are the basis for ensuring the normal operation of the power system. In the topological model, the physical edges need to consider parameters such as voltage levels, current capacities, and impedances between equipment. The actual operating parameters of the power system, such as current flow and load distribution, depend on the electrical characteristics of the physical edge connections.

[0032] Specifically, the virtual edges represent the control relationships between nodes and are mainly used for dispatch, monitoring, and protection in the power system. Through the virtual edges, remote monitoring devices, intelligent control devices, and the system dispatch center can be connected to physical nodes. Different from physical edges, virtual edges do not involve physical electrical transmission but manage the operating states of power equipment through information and signal transmission. For example, through the virtual edges, the dispatch center can adjust the reactance to control the current and voltage changes of the transmission line to ensure the stability of the system.

[0033] Specifically, the reactor can be regarded as an adjustment element on the physical edge, and by adjusting the reactance, it can control the current and voltage changes of the transmission line to ensure the stability of the system.

[0034] In some embodiments, constructing a distributed topology includes:

[0035] Traversing the network nodes, determining the distributed nodes based on the reactors as the topology main body, and performing unique label identification for each node; identifying the topology main body and backgrounding the non-distributed main body topology part; traversing the distributed topology and performing edge weight marking based on the control relevance of the connections.

[0036] Specifically, first traverse the nodes in the entire power network, and according to the distribution characteristics of the reactors, determine those nodes with reactors as the main body nodes of the distributed topology, and output as the topology main body. Reactors are used to adjust current and voltage in the power system, so the control and management of the main body nodes corresponding to the reactors are crucial for the stability of the system. In other words, the topology main body and the multiple main body nodes it contains are the control target objects.

[0037] Specifically, for those topological parts of non-distributed entities (i.e., nodes without reactors), they are backgrounded. This means that these nodes will not be the direct objects of control, but their data flow states will still be monitored and analyzed to reflect the system's power load, power changes, etc., and help optimize the regulation of reactors. For example, if the load of a non-reactor node suddenly increases, the operating state of the associated reactor node can be adjusted accordingly to avoid system overload or imbalance.

[0038] Furthermore, traverse the already constructed distributed topological structure and assign edge weights to each connection edge (whether it is a physical edge or a virtual edge) according to the control relevance between nodes. Among them, the control relevance reflects the degree of mutual influence between two nodes during the power transmission and regulation process. The higher the relevance, the stronger the association between the two nodes in the control process, and adjusting one node may have a greater impact on the other node. Exemplarily, the weight of a physical edge reflects the physical and electrical relationship between nodes, such as the intensity of current flow, the power distribution situation, the voltage difference, etc.; the weight of a virtual edge reflects the association between control signals, such as the priority and influence range of control commands.

[0039] By marking the edge weights, high-weight node connections can be given priority in the control process. For example, when the control relevance between certain nodes is high, the system can preferentially adjust these nodes to improve the overall stability and power regulation efficiency.

[0040] Based on the distributed topology, determine distributed clusters by performing community cluster detection and division, where each distributed cluster contains at least one reactor network node.

[0041] Specifically, a distributed cluster is the clustering result of multiple reactor network nodes in the distributed topology, used to divide multiple distributed and discrete reactors into multiple distributed clusters according to the topological relationship. Among them, multiple reactor network nodes within each distributed cluster have a relatively close association relationship (such as nodes with strong electrical connections or control relevance).

[0042] Specifically, a distributed cluster contains at least one reactor network node. In other words, an isolated single reactor network node can also be regarded as a distributed cluster and be controlled relatively independently.

[0043] Optionally, performing community cluster detection and division includes implementation paths based on the Louvain algorithm, Girvan - Newman algorithm, and spectral clustering algorithm. Among them, cluster division based on the Laplacian matrix of the graph is suitable for dealing with non-linear cluster structures.

[0044] By identifying each distributed cluster, independent control and optimization can be carried out for each cluster, reducing the complexity of the whole network regulation. Furthermore, it helps to improve the reliability, flexibility and control efficiency of the system.

[0045] In some embodiments, by performing community cluster detection and division, including:

[0046] Based on the distributed topology, construct a Laplacian matrix; traverse the Laplacian matrix, calculate the eigenvalues and eigenvectors. Among them, calculate the eigenvalues according to the eigenvalue equation |λE - L| = 0, and calculate the eigenvector by solving the system of equations (L - λE)v = 0, where λ is the eigenvalue, E is the identity matrix, L is the Laplacian matrix, and v is the eigenvector; based on the eigenvalues and the eigenvectors, perform spectral clustering processing to determine the distributed clusters.

[0047] Specifically, the Laplacian matrix is a matrix used to represent a graph (in this case, the distributed power topology), which can effectively describe the connection relationship between nodes and the structural characteristics of the network, laying a foundation for subsequent eigenvalue and eigenvector calculations. Among them, the Laplacian matrix is constructed by the adjacency matrix and the degree matrix, representing the structural characteristics of nodes and edges in the entire distributed power system.

[0048] Specifically, after constructing the Laplacian matrix, calculate the eigenvalues and eigenvectors of the Laplacian matrix through eigenvalue decomposition technology. The obtained eigenvalues and eigenvectors are the basis for further cluster division. Among them, the eigenvalue is a scalar describing the properties of the matrix. In spectral clustering, the eigenvalue can reflect the number and tightness of the cluster structures in the distributed topology. The eigenvector is a vector related to the eigenvalue, which represents the direction related to the eigenvalue.

[0049] Specifically, first calculate the eigenvalues of the Laplacian matrix by solving the following eigenvalue equation:

[0050] ;

[0051] Among them, λ is the eigenvalue, E is the identity matrix, and L is the previously constructed Laplacian matrix.

[0052] After obtaining the eigenvalues, calculate the corresponding eigenvectors by solving the following system of equations:

[0053] ;

[0054] Among them, v is the eigenvector, representing the direction corresponding to each eigenvalue. By traversing each element of the Laplacian matrix, the eigenvector is gradually solved.

[0055] Specifically, centrality indices, such as betweenness centrality and degree centrality, are calculated through the eigenvalues and eigenvectors of the Laplacian matrix, so as to understand the important nodes and connection methods in the distributed topology.

[0056] Furthermore, spectral clustering is performed on the eigenvalues and eigenvectors of the Laplacian matrix. Spectral clustering projects the original high-dimensional network node data into a low-dimensional space by selecting the eigenvector corresponding to the smallest eigenvalue of the Laplacian matrix. In the low-dimensional space, it is easier to identify the cluster structure. Then, through the eigenvector, the similarity between each pair of nodes in the low-dimensional space is calculated. The higher the similarity between nodes, the more likely they belong to the same cluster. Therefore, these nodes can be classified by k-means or other clustering algorithms, and the clustering results reflect the tightly connected node groups in the network.

[0057] The above method steps make the nodes within the cluster have a high connection density through spectral clustering, while the connections between clusters are relatively few, which helps the modular management of the power system and simplifies the control and optimization of complex networks.

[0058] In some implementation manners, based on the distributed topology, a Laplacian matrix is constructed, including:

[0059] Traverse the distributed topology to construct an adjacency matrix, where the adjacency matrix is constructed based on the nodes of the topology main body, and the matrix entries represent the weights of the edges between the nodes; traverse the distributed topology to construct a degree matrix, where the degree matrix is a diagonal matrix, and the diagonal matrix entries represent the sum of the weights of the edges connected to the nodes; subtract the degree matrix from the adjacency matrix to determine the Laplacian matrix.

[0060] Specifically, the adjacency matrix is a symmetric matrix representing the connection situation between nodes in the topology. If there is an edge between node i and node j, then A i,j = 1, otherwise A i,j = 0. Exemplarily, for the distributed topology of the power system, the adjacency matrix reflects the electrical or control connection relationship between power equipment. Specifically, the degree matrix is a diagonal matrix used to represent the degree of each node (i.e., the sum of the weights connected to it). Exemplarily, the diagonal element of the degree matrix is equal to the sum of the weights of the edges connected to node i.

[0061] Construct an event database, and the event database covers coordination event classes - information pairs based on a predetermined schedule and event status - reactor parameter control.

[0062] Specifically, the event database includes multiple groups of associated coordinated event classes, information pairs based on a predetermined schedule and event status, and reactor parameter control. The event database is constructed based on the reactor parameter control history records of the target power grid system or a power grid system similar to the target power grid system. Exemplarily, it includes the parsing of historical parameter control records, data cleaning based on data integrity and data quality, data structuring, etc.

[0063] Specifically, the coordinated event classes contain various operation events related to the reactor, involving key tasks such as the operation scheduling of the power system, control strategy adjustment, and load balancing, for achieving efficient control of the reactor. Exemplarily, the coordinated event classes include timed scheduling events, event-driven operations, and control adjustment events.

[0064] Specifically, the information pair based on the predetermined schedule and event status determines when and in what way to control the reactor. In other words, this information pair is the trigger condition for the coordinated event classes. By means of the information pair based on the predetermined schedule and event status, it can be ensured that the system triggers events according to the planned or desired logic to control the operation of the reactor in the best way.

[0065] Among them, the predetermined schedule is a set of time rules set in advance, which defines the operations that the reactor needs to perform at a certain future time point or time period. This schedule can be formulated based on the historical data of the power system, load prediction, or the demands of the power market.

[0066] Specifically, when an event is triggered, a participation control (parameter control) operation is performed on the reactor. The reactor parameter control is the specific control logic and control parameters for performing the participation control. Among them, the reactor parameter control includes: by adjusting the reactance in power transmission, helping to balance the load of the system to reduce voltage fluctuations; controlling the reactive power of the system, optimizing the power factor, and improving the transmission efficiency and stability of the power grid; when the system is overloaded or fails, by adjusting the current flow path through the reactor to reduce system pressure and protect the equipment from damage.

[0067] By constructing an event database covering the coordinated event classes, precise participation control (parameter control) of the reactor can be carried out based on the information pair of the predetermined schedule and event status. Thus, the automated scheduling and control of the distributed power system can be realized, ensuring the stable operation of the system under complex loads and emergencies.

[0068] Supervise and train the cascade decision module according to the distributed topology, the distributed cluster, and the event database.

[0069] Specifically, a cascaded decision-making module is constructed and trained to adjust the inductance characteristics and capacitance characteristics of the reactor to ensure the efficient operation and control of the reactor in the distributed power system. Among them, the cascaded decision-making module is constructed through supervised training by combining information in the distributed topology, distributed cluster, and event database.

[0070] In some embodiments, constructing the cascaded decision-making module includes:

[0071] Based on the inductance characteristics of the reactor, determine the first adjustment mode; based on the capacitance characteristics of the reactor, determine the second adjustment mode; based on the first adjustment mode, construct the first cascaded decision-making unit, and based on the second adjustment mode, construct the second cascaded decision-making unit, and parallelize the first cascaded decision-making unit and the second cascaded decision-making unit to generate the cascaded decision-making module.

[0072] Specifically, the inductance characteristics of the reactor are mainly used to adjust the current in the system. The basic characteristic of inductance is to impede the change of current. Especially in alternating current, it can buffer the current and prevent sudden large current impacts. Among them, the inductance characteristics of the reactor are determined by the spiral coil of its conductor. When the current passing through the coil changes, the inductance will generate a reverse current through electromagnetic induction, thereby impeding the rapid change of current.

[0073] Specifically, the first adjustment mode is used to adjust the smoothness of current flow and reduce high-frequency fluctuations. This mode controls the value of the inductance (such as by adjusting the spiral coil structure or material of the reactor) to achieve current control. For example, in the case of sudden load increase or decrease, the system enables the first adjustment mode to adjust the inductance value of the reactor and mitigate the impact of current fluctuations on the power grid system.

[0074] Specifically, the capacitance characteristics of the reactor are mainly used to adjust the voltage. The capacitor can store charge to adjust voltage fluctuations. Especially in the power system, the capacitance characteristics of the reactor can help balance reactive power and optimize voltage stability.

[0075] Specifically, based on the capacitance characteristics, determine the second adjustment mode. The second adjustment mode is used for voltage regulation and reactive power management. For example, according to the voltage change situation in the power system, dynamically adjust the capacitance value of the reactor to ensure voltage stability. For example, in the case of unstable or frequently fluctuating grid voltage, enable the second adjustment mode to adjust the capacitance value of the reactor to stabilize the voltage and optimize the power factor.

[0076] Specifically, based on the inductance and capacitance characteristics of the reactor respectively, construct two cascaded decision-making units, namely the first cascaded decision-making unit and the second cascaded decision-making unit. The two decision-making units jointly form the cascaded decision-making module through parallel processing, thereby simultaneously realizing control decisions for voltage and current and providing a more comprehensive reactor control strategy.

[0077] The acquisition unit obtains the electrical data of the distributed power system, combines with the cascade decision-making module, conducts cluster greedy decision-making and necessary boundary sharing interaction between clusters, and determines the cascade coordination strategy.

[0078] Specifically, the acquisition unit is responsible for real-time monitoring and obtaining electrical data such as current, voltage, power, and load in the distributed power system. These data will be used for subsequent decision-making and control processes. Among them, the acquisition unit is composed of sensors (including current sensors, voltage sensors, temperature sensors, etc.) arranged in the power system.

[0079] Specifically, the acquired data is input into the cascade decision-making module, which executes cluster greedy decision-making, performs optimization operations within each cluster, and finds the best reactor regulation scheme for each distributed cluster in the current state. Through the greedy decision-making algorithm, the regulation parameters of the current reactor can be gradually optimized, quickly respond when the system load fluctuates greatly, reduce the response delay, and ensure the stability of the local cluster.

[0080] Specifically, the greedy decision-making only searches for the optimal solution within a local range and may not be able to find the global optimal solution. Therefore, the overall system performance is further optimized through boundary sharing interaction between clusters. Among them, the necessary boundary sharing interaction includes sharing key data such as power and load between clusters to ensure cross-cluster optimization. Exemplarily, after obtaining the data of the boundary nodes, a comprehensive evaluation of the power flow and load of adjacent clusters will be carried out to ensure the coordinated operation between clusters. For example, when a certain cluster has an excessive load, through the boundary sharing mechanism, part of the load will be transferred to the neighboring cluster to avoid local overload.

[0081] Optionally, in the first cascade decision-making unit, the operation data of the reactor is processed step by step to dynamically adjust the inductance of the reactor to ensure the accuracy of current control. For example, first adjust the basic parameters of the reactor according to the scheduling plan in the event database, and then make fine-tuning according to the real-time data.

[0082] Optionally, the second cascade decision-making unit conducts multi-level adjustment of the capacitance of the reactor through hierarchical decision-making to ensure that the voltage fluctuation is within a reasonable range. For example, first make a preliminary adjustment according to the voltage scheduling plan in the event database, and then conduct more refined control of the reactor through real-time voltage data.

[0083] Obtain electrical data in the distributed power system through the acquisition unit, and combine this data with the cascade decision-making module to perform cluster greedy decision-making and boundary sharing interaction between clusters, and finally determine the optimized cascade coordination strategy to ensure that each cluster in the distributed power system can work efficiently and cooperatively. The cascade coordination strategy combines local optimization and global optimization to ensure that the load, current, and voltage of the system are balanced among different clusters.

[0084] In some embodiments, before determining the cascade coordination strategy, it includes:

[0085] Determine the switching position and reactor capacity, and coordinate and constrain the cluster strategy. Among them, the hardware structure is regulated by the series-parallel relationship of the reactors, the installation and idleness of the reactors. Predict the transient impact at the moment of switching. If the transient impact exceeds the limit, perform multi-step strategy conversion, where the preset impact is used as a constraint.

[0086] Specifically, the switching position and capacity of the reactor determine its regulation effect and regulation ability in the power system. Therefore, it is necessary to determine the switching point of the reactor and the required regulation capacity according to the current power demand, load conditions, and voltage level to achieve the stable operation of the power system. Among them, the switching position refers to the specific position where the reactor is installed and operates in the power system. Usually, the reactor will be installed at nodes with high load, prone to current fluctuations or voltage instability. The capacity of the reactor determines the range of current or voltage that it can regulate, and the reactor capacity is dynamically adjusted according to the load conditions and system requirements. For example, if the load is large and fluctuates frequently, the capacity of the reactor can be increased to provide stronger current or voltage regulation ability; on the contrary, if the system is in a low-load state, the capacity of the reactor can be appropriately reduced to save costs.

[0087] Furthermore, after determining the switching position and capacity of the reactor, coordinate and constrain the cluster strategy to ensure that the regulation of the reactor within or between clusters can operate in a coordinated manner, avoiding problems such as system instability or equipment overload. Preferably, the coordination constraints include the adjustment of the series-parallel relationship of the reactors, the regulation of the installation and idleness states. By adjusting the series-parallel relationship of the reactors, the installation or idleness states, optimize the hardware structure of the power regulation to ensure that the capacity and position of the reactor can meet the power system requirements during load fluctuations.

[0088] Optionally, after optimizing the hardware structure of the power regulation, it further includes updating the operation parameters (such as inductance, capacitance values) constraints (coordination constraints) of each reactor according to the optimized hardware structure to ensure that the power system performs parameter control as expected.

[0089] Specifically, when controlling the reactor, it is necessary to predict the transient impact at the moment of switching. If the impact exceeds the limit, a multi-step conversion strategy is required to avoid equipment damage or grid instability through multiple, small-scale adjustments. Among them, transient impact is used to quantify the pressure caused by parameter control on the reactor, such as instantaneous drastic fluctuations in current or voltage.

[0090] For example, the first step size adjustment is performed based on the initial parameters of the reactor, and the current and voltage changes in the power system are monitored in real time. The transient impact intensity after the initial adjustment is analyzed to determine whether to make subsequent adjustments. After the initial adjustment, if the transient impact is still large, the step size is further reduced and a second or multiple adjustments are made. By making small adjustments one by one, power fluctuations can be effectively alleviated to avoid large impacts on equipment and systems.

[0091] Furthermore, the cascade coordination strategy includes an inner loop strategy and an outer loop strategy, wherein the inner loop strategy is a direct parameter control for the reactor, and the outer loop strategy is a linear regulation relationship based on the control parameters, and the outer loop strategy is used to perform feedback regulation to map the response of the inner loop strategy.

[0092] Specifically, the cascade coordination strategy is divided into an inner loop strategy and an outer loop strategy to form a hierarchical cascade control structure, so that more precise regulation and response feedback can be achieved when executing reactor regulation.

[0093] Among them, the inner loop strategy is the direct control of the reactor to adjust its key parameters (such as inductance, capacitance, switching position, capacity, etc.). These direct control operations ensure that the power system can respond quickly in a short time to adjust load, voltage or current fluctuations.

[0094] Among them, the outer loop strategy monitors the control results of the inner loop strategy, analyzes the response deviation (i.e. the difference between the actual output and the expected output), and performs feedback adjustment based on the linear control relationship. The outer loop strategy is used to ensure that the response deviation can be corrected in time, thereby improving the stability and accuracy of the overall control.

[0095] Based on the cascade coordination strategy, coordinated control of distributed reactors is performed.

[0096] Exemplarily, the inner - loop strategy first directly controls the inductance, capacitance, or switching operation of the reactor according to the actual load and power fluctuations of the power system, quickly responding to changes in the power system. Then, the outer - loop strategy monitors the regulation results of the inner - loop strategy, evaluates the difference between the actual output and the desired output (response deviation). If there is a deviation, the outer - loop strategy calculates the compensation parameters through a linear regulation relationship and gradually adjusts the input of the inner - loop to reduce the deviation. Finally, with the inner - and outer - loop strategies working in a cycle, the inner - loop makes a quick response and the outer - loop conducts long - term optimization to ensure the stable operation of the power system in the short term and maintain accuracy and efficiency in the long term.

[0097] In summary, the distributed reactor coordinated control method provided by the present invention has the following technical effects:

[0098] For a distributed power system, using power equipment as network nodes, a distributed topology is constructed based on edge connection relationships, where each reactor network node has a unique label, and the edge connection relationships include physical edges based on electrical connections and virtual edges based on control relationships; through the distributed topology, community cluster detection is carried out to divide the distributed clusters, and each cluster contains at least one reactor network node; an event database is established, which covers coordination event categories, information pairs based on a predetermined schedule and event status, and relevant data of reactor participation and control; according to the distributed topology, distributed clusters, and event database, a cascade decision - making module is supervised and trained; an acquisition unit is used to obtain the electrical data of the distributed power system, and in combination with the cascade decision - making module, greedy decision - making within the cluster and boundary - sharing interaction between clusters are carried out to determine the cascade coordination strategy; based on the cascade coordination strategy, the distributed reactors are coordinated and controlled. Thus, the technical effects of improving control responsiveness and enhancing the efficiency of the power system are achieved.

[0099] Embodiment 2

[0100] Figure 2 It is a schematic structural diagram of the distributed reactor coordinated control device of the present invention. For example, Figure 1 The flow schematic diagram of the distributed reactor coordinated control method in the present invention can be implemented through a structure as shown in Figure 2 shown.

[0101] Based on the same concept as the distributed reactor coordinated control method in the above - mentioned embodiment, the distributed reactor coordinated control device provided by the present invention further includes:

[0102] A topology connection component 11, which is used to construct a distributed topology for a distributed power system with power equipment as network nodes based on edge connection relationships. Among them, each network node based on the reactor has a unique label, and the edge connection includes a physical edge based on electrical connection and a virtual edge based on control relationship.

[0103] The cluster division component 12 is used to determine the distributed clusters by performing community cluster detection and division based on the distributed topology, where each distributed cluster includes at least one reactor network node.

[0104] The event organization component 13 is used to construct an event database that covers coordinated event classes - information pairs based on a predetermined schedule and event status - reactor parameter control.

[0105] The decision shaping component 14 is used to supervise and train the cascade decision module according to the distributed topology, the distributed clusters, and the event database.

[0106] The acquisition decision component 15 is used for the acquisition unit to obtain the electrical data of the distributed power system, combine with the cascade decision module, perform cluster greedy decision and necessary boundary sharing interaction between clusters, and determine the cascade coordination strategy.

[0107] The issuing and execution component 16 is used to perform coordinated control of the distributed reactors based on the cascade coordination strategy.

[0108] Among them, the topology connection component 11 includes:

[0109] The distributed node determination unit is used to traverse the network nodes, determine the distributed nodes based on the reactors as the topology main body, and perform unique label identification for each node.

[0110] The topology main body identification unit is used to identify the topology main body and background the non-distributed main body topology part.

[0111] The edge weight marking unit is used to traverse the distributed topology and perform edge weight marking based on the control relevance of the connection.

[0112] In some embodiments, the cluster division component 12 includes:

[0113] The Laplacian matrix construction unit is used to construct a Laplacian matrix based on the distributed topology.

[0114] The eigenvalue and eigenvector calculation unit is used to traverse the Laplacian matrix and calculate the eigenvalues and eigenvectors. Among them, the eigenvalues are calculated according to the eigenvalue equation |λE - L| = 0, and the eigenvector is calculated by solving the system of equations (L - λE)v = 0, where λ is the eigenvalue, E is the identity matrix, L is the Laplacian matrix, and v is the eigenvector.

[0115] The spectral clustering processing unit is used to perform spectral clustering processing based on the eigenvalues and eigenvectors to determine the distributed clusters.

[0116] In some implementations, the Laplacian matrix construction unit in the cluster partitioning component 12 is further configured to:

[0117] Traverse the distributed topology to construct an adjacency matrix, where the adjacency matrix is constructed based on the nodes of the topology main body, and the matrix entries represent the weights of the edges between the nodes.

[0118] Traverse the distributed topology to construct a degree matrix, where the degree matrix is a diagonal matrix, and the diagonal matrix entries represent the sum of the weights of the connected edges of the nodes.

[0119] Subtract the degree matrix from the adjacency matrix to determine the Laplacian matrix.

[0120] In some embodiments, the decision-making shaping component 14 includes:

[0121] An inductance characteristic adjustment mode determination unit, configured to determine a first adjustment mode based on the inductance characteristic of the reactor.

[0122] A capacitance characteristic adjustment mode determination unit, configured to determine a second adjustment mode based on the capacitance characteristic of the reactor.

[0123] A first cascade decision unit construction unit, configured to construct a first cascade decision unit based on the first adjustment mode.

[0124] A second cascade decision unit construction unit, configured to construct a second cascade decision unit based on the second adjustment mode.

[0125] A cascade decision module generation unit, configured to parallelize the first cascade decision unit and the second cascade decision unit to generate the cascade decision module.

[0126] In some implementations, the acquisition decision-making component 15 further includes:

[0127] A coordination constraint unit, configured to determine the switching position and the reactor capacity, and perform coordination and constraint on the cluster strategy, where the hardware structure is regulated based on the series-parallel relationship of the reactors, the installation and idleness of the reactors.

[0128] An impact constraint unit, configured to predict the transient impact at the moment of switching. If the transient impact exceeds the limit, perform a multi-step conversion of the strategy, where a preset impact is used as the constraint.

[0129] Furthermore, the cascade coordination strategy includes an inner loop strategy and an outer loop strategy, where the inner loop strategy is a direct parameter control for the reactor, and the outer loop strategy is a linear regulation relationship based on control parameters. The outer loop strategy is used to perform feedback regulation for mapping the response of the inner loop strategy.

[0130] It should be understood that the embodiments mentioned in this specification focus on their differences from other embodiments. The specific embodiments in the foregoing Embodiment 1 are equally applicable to the distributed reactor coordinated control device described in Embodiment 2. For the sake of brevity of the specification, no further elaboration will be made here.

[0131] It should be understood that the embodiments and the above descriptions disclosed in the present invention enable those skilled in the art to implement the present invention using the present invention. At the same time, the present invention is not limited to the part of the embodiments mentioned above. It should be understood that those of ordinary skill in the art can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A coordinated control method for distributed reactors, characterized in that: The method comprises: For distributed power systems, power equipment is used as network nodes, and a distributed topology is constructed based on edge connection relationships. Each network node based on the reactor has a unique label, and the edge connection includes physical edges based on electrical connections and virtual edges based on control relationships. Based on the distributed topology, a distributed cluster is determined by performing community cluster detection and division, wherein each distributed cluster includes at least one reactor network node; Constructing an event database, the event database covers coordination event classes - information pairs based on a predetermined schedule and event status - reactor parameter control; Constructing a cascade decision module, and supervising training the cascade decision module according to the distributed topology, the distributed cluster and the event database; The collection unit acquires the electrical data of the distributed power system, combines with the cascade decision module, performs cluster greedy decision and necessary boundary sharing interaction between clusters, and determines the cascade coordination strategy; Based on the cascade coordination strategy, coordinated control of distributed reactors is performed; Construct a cascade decision-making module, including: Based on the inductance characteristics of the reactor, determining a first regulation mode, wherein the first regulation mode is used to regulate the smoothness of current flow and reduce high-frequency fluctuations; Based on the capacitance characteristics of the reactor, determining a second regulation mode, wherein the second regulation mode is used for voltage regulation and reactive power management; Based on the first regulation mode, a first cascade decision unit is constructed, based on the second regulation mode, a second cascade decision unit is constructed, and the first cascade decision unit and the second cascade decision unit are connected in parallel to generate the cascade decision module; Before determining the cascade coordination strategy, include: Determine the switching position and reactor capacity, and coordinate the cluster strategy. In particular, the hardware structure is regulated based on the series and parallel relationship of the reactors, and the installation and idleness of the reactors. Predict the transient impact at the switching moment. If the transient impact exceeds the limit, perform a multi-step strategy conversion, in which the preset impact is used as a constraint.

2. The coordinated control method of distributed reactors according to claim 1, characterized in that: The constructing of a distributed topology includes: Traversing the network nodes, determining distributed nodes based on reactors as topological entities, and uniquely labeling each node; identifying the topological subject and contextualizing the non-distributed subject topological portion; The distributed topology is traversed, and edge weights are marked based on the control relevance of the connections.

3. The coordinated control method of distributed reactors according to claim 1, characterized in that: The community cluster detection and division includes: Based on the distributed topology, construct a Laplace matrix; Traversing the Laplace matrix, calculating eigenvalues ​​and eigenvectors, wherein the eigenvalues ​​are calculated according to the eigenvalue equation |λE-L|=0, and the eigenvalue vectors are calculated by solving the equation system (L-λE)v=0, wherein λ is the eigenvalue, E is the identity matrix, L is the Laplace matrix, and v is the eigenvalue vector; A spectral clustering process is performed based on the eigenvalues ​​and the eigenvectors to determine the distributed clusters.

4. The coordinated control method for distributed reactors according to claim 3, characterized in that: Based on the distributed topology, a Laplace matrix is ​​constructed, including: Traversing the distributed topology to construct an adjacency matrix, wherein the adjacency matrix is ​​constructed based on nodes of the topology subject, and matrix items represent weights of edges between nodes; Traversing the distributed topology to construct a degree matrix, wherein the degree matrix is ​​a diagonal matrix, and the diagonal matrix items represent the weights and edges connecting the nodes; The degree matrix is ​​subtracted from the adjacency matrix to determine a Laplacian matrix.

5. The distributed reactor coordinated control method according to claim 1, characterized in that: The cascade coordination strategy includes an inner loop strategy and an outer loop strategy, wherein the inner loop strategy is a direct parameter control of the reactor, and the outer loop strategy is a linear regulation relationship based on control parameters, and the outer loop strategy is used to perform feedback regulation to map the response of the inner loop strategy.

6. A distributed reactor coordination control device, characterized in that: The device comprises: A topology connection component, wherein the topology connection component is used for constructing a distributed topology based on an edge connection relationship for a distributed power system, with power equipment as network nodes, wherein each network node based on a reactor has a unique label, and the edge connection includes a physical edge based on an electrical connection and a virtual edge based on a control relationship; A cluster partitioning component, the cluster partitioning component is used to determine distributed clusters by performing community cluster detection partitioning based on the distributed topology, wherein each distributed cluster includes at least one reactor network node; An event organization component, the event organization component is used to build an event database, the event database covers the coordination event class - information pairs based on a predetermined schedule and event status - reactor parameter control; A decision forming component, the decision forming component is used to construct a cascade decision module, and supervise the training of the cascade decision module according to the distributed topology, the distributed cluster and the event database; A collection decision component, wherein the collection decision component is used for a collection unit to obtain electrical data of the distributed power system, and in combination with the cascade decision module, performs cluster greedy decision making and necessary boundary sharing interaction between clusters to determine a cascade coordination strategy; Sending an execution component, wherein the sending execution component is used to perform coordinated control of the distributed reactor based on the cascade coordination strategy; The decision-making components include: an inductance characteristic adjustment mode determination unit, configured to determine a first adjustment mode based on the inductance characteristic of the reactor, wherein the first adjustment mode is configured to adjust the smoothness of current flow and reduce high-frequency fluctuations; a capacitance characteristic adjustment mode determination unit, configured to determine a second adjustment mode based on the capacitance characteristic of the reactor, wherein the second adjustment mode is used for voltage regulation and reactive power management; A first cascade decision unit construction unit, configured to construct a first cascade decision unit based on the first adjustment mode; A second cascade decision unit construction unit, configured to construct a second cascade decision unit based on the second adjustment mode; A cascade decision module generating unit, used for parallelizing the first cascade decision unit and the second cascade decision unit to generate the cascade decision module; The acquisition decision component also includes: The coordination constraint unit is used to determine the switching position and reactor capacity, and coordinate the cluster strategy. The hardware structure is regulated based on the series-parallel relationship of the reactors, and the installation and idleness of the reactors. The impact constraint unit is used to predict the transient impact at the switching moment. If the transient impact exceeds the limit, a multi-step strategy conversion is performed, wherein the preset impact is used as a constraint.

Images