A control method and system for a module parallel type energy storage converter

Abstract

The present invention proposes a control method and system for a module parallel energy storage converter, which relates to the technical field of energy storage converters, collects the state information of the energy storage converter; constructs an initial topology network model according to the connection state information and working state information of all energy storage converters, and synchronizes the working state information of each energy storage converter to the control node corresponding to the energy storage converter in the initial topology network model; constructs an input control function based on the working state information and the PID gain parameter corresponding to each energy storage converter, and embeds the input control function into the control node of the initial topology network model to obtain the topology network model; inputs the real-time working state information of the energy storage converter into the topology network model, generates the regulation state information, and dynamically adjusts the output state of the energy storage converter according to the regulation state information. The present invention helps to improve the operating efficiency and reliability of the energy storage converter.

Description

Technical Field

[0001] The present invention relates to the technical field of energy storage converters, and in particular to a control method and system for a module parallel type energy storage converter. Background Art

[0002] With the growth of energy demand and the increasing reliance on renewable energy, the research on energy storage inverters is crucial to solving the reliability of energy supply, balancing the power system, improving energy utilization efficiency and promoting sustainable development. Energy storage inverters can improve energy utilization efficiency. Traditional energy systems have the problem of energy waste, especially in the process of power transmission and distribution. Energy storage inverters can convert electrical energy into storage energy, store excess electrical energy, and release it when needed, which can avoid energy waste and improve energy utilization efficiency. Energy storage inverters can also be combined with renewable energy power generation equipment to provide continuous and stable power output by storing the electricity they generate, reducing dependence on traditional energy.

[0003] A Chinese patent with announcement number CN105515027B discloses a load curve configurable energy storage microgrid control method. In the grid-connected state, the load curve of the microgrid where the energy storage array is located is configured on demand through an orderly charging and discharging strategy, so that the microgrid grid-connected power is controllable. The specific steps are: according to the power regulation requirements and key characteristics of energy storage, with the minimum energy storage regulation amount as the goal, and with the time-divided load curve as the constraint, a full-time control strategy is automatically generated. However, the solution provided by the above application has a delay in real-time acquisition and synchronization of the connection status and working status information of each energy storage inverter, and cannot respond to the dynamic changes of the system in time, affecting the stability and reliability of the system. Moreover, with the increase in the number of energy storage inverters and control nodes, it is difficult to achieve efficient data transmission and management. Therefore, it is very necessary to provide a control method and system for a modular parallel energy storage inverter to improve the operating efficiency and reliability of the energy storage inverter. Summary of the invention

[0004] In view of this, the present invention proposes a control method and system for a modular parallel energy storage converter. By real-time acquisition and synchronization of the connection status information and working status information of the energy storage converter, and the topological network model realizes the coordinated control between the energy storage converters, the operating efficiency and reliability of the energy storage converter in the topological network model are optimized.

[0005] The present invention provides a control method for a module parallel type energy storage converter, the method comprising:

[0006] Collecting status information of an energy storage converter, wherein the status information includes connection status information and working status information, and the energy storage converter includes a plurality of power conversion modules connected in parallel;

[0007] According to the connection status information and working status information of all energy storage converters, an initial topology network model is constructed, and the working status information of each energy storage converter is synchronized to the control node corresponding to the energy storage converter in the initial topology network model;

[0008] Based on the working state information and the PID gain parameters corresponding to each energy storage converter, an input control function is constructed, and the input control function is embedded in the control node of the initial topology network model to obtain a topology network model;

[0009] The real-time working status information of the energy storage converter is input into the topological structure network model to generate regulation status information, and the output status of the energy storage converter is dynamically adjusted according to the regulation status information.

[0010] On the basis of the above technical solution, preferably, the construction of the initial topological structure network model specifically includes:

[0011] Mapping each energy storage converter to a network node, and establishing a network connection relationship between the network nodes according to the connection status information of each energy storage converter;

[0012] Associating the network node corresponding to each energy storage converter with the control node, and constructing a node mapping relationship between the control node and the corresponding energy storage converter;

[0013] The initial topology network model is constructed according to the network connection relationship, the node mapping relationship and the connection status information.

[0014] On the basis of the above technical solution, preferably, synchronizing the working status information of each energy storage converter to the control node corresponding to the energy storage converter in the initial topology network model specifically includes:

[0015] Encode all energy storage converters in sequence, use the encoding information as the identity code of the energy storage converter and assign the identity code to the corresponding network node;

[0016] and collecting verification information between the plurality of energy storage converters, wherein the verification information includes location information of the energy storage converters;

[0017] Binding the verification information with the identity code of the corresponding energy storage converter to obtain the identity information;

[0018] The real-time working status information of the energy storage converter is collected, the corresponding network node is identified according to the identity information, and the real-time working status information is transmitted to the network node, and the network node forwards the real-time working status information to the corresponding control node.

[0019] More preferably, the dynamically adjusting the output state of the energy storage converter according to the regulation state information specifically includes:

[0020] The regulation state information is sent to the control node corresponding to each energy storage converter through the topological structure network model, so that each energy storage converter dynamically adjusts the output state according to the regulation state information.

[0021] More preferably, the control state information includes basic control parameters, dynamic adjustment parameters and protection limit parameters, wherein:

[0022] The basic control parameters include one or more of the output voltage setting value, the output current limit value, the power setting value, the power factor adjustment value, the working mode identification and the operation status flag;

[0023] The dynamic adjustment parameters include one or more of a proportional coefficient, an integral coefficient, a differential coefficient, a dynamic response time, an adjustment dead zone range, an overshoot limit value, and a stability requirement;

[0024] The protection limit parameters include one or more of an overvoltage protection value, an undervoltage protection value, an overcurrent protection value, an overpower protection value, a device temperature upper limit, an ambient temperature range, and a temperature rise change rate limit.

[0025] More preferably, the expression of the input control function is:

[0026]

[0027] u(t)=u I (t)+u V (t)+u P (t)

[0028] Among them, u I (t) represents the current control function at time t, K P,I represents the current proportional gain parameter, e I (t) represents the current error function, K I,I represents the current integral gain parameter, represents the current nonlinear compensation function, I out Represents the output current of the energy storage converter, represents the state vector of the energy storage converter, u V (t) represents the voltage control function at time t, K P,V represents the voltage proportional gain parameter, e V (t) represents the voltage error function, K I,V Represents the voltage integral gain parameter, K D,V represents the voltage differential gain parameter, represents the voltage feedforward compensation function, Vout Indicates the output voltage of the energy storage converter, u P (t) represents the power control function at time t, argmin() represents the minimum value function, P ref Indicates the reference power value, P out (t) represents the actual output power of the energy storage converter at time t, λ represents the power control weight coefficient, j represents the switch modulation signal, and u(t) represents the control input function at time t.

[0029] More preferably, the expression of the topological structure network model is:

[0030]

[0031] Where V(t) represents the output voltage function of the energy storage converter, μ 11 Represents the first voltage dynamic coefficient, μ 12 represents the second voltage dynamic coefficient, γ 1 represents the voltage control input coefficient, α represents the first nonlinear compensation coefficient, ω V (t) represents the voltage process noise function, I(t) represents the output current function of the energy storage converter, μ 21 Represents the first current dynamic coefficient, μ 22 represents the second current dynamic coefficient, γ 2 represents the current control input coefficient, β represents the second nonlinear compensation coefficient, ω I (t) represents the current process noise function, θ(t) represents the system phase angle function of the energy storage converter, μ 31 Represents the first phase angle dynamic coefficient, μ 32 represents the second phase angle dynamic coefficient, γ 3 represents the phase angle control input coefficient, ω θ (t) represents the phase process noise function, y(t) represents the observable output function of the topological network model, and v(t) represents the measurement noise function.

[0032] In a second aspect of the present application, a HBase spatiotemporal data storage indexing system based on spatiotemporal short codes is provided, wherein the control system includes a data acquisition module, a model building module and a dynamic control module, wherein:

[0033] The data acquisition module is used to collect status information of the energy storage converter, wherein the status information includes connection status information and working status information;

[0034] The model building module is used to build an initial topology network model according to the connection status information and working status information of all energy storage converters, and synchronize the working status information of each energy storage converter to the control node corresponding to the energy storage converter in the initial topology network model, and build an input control function based on the working status information and the PID gain parameter corresponding to each energy storage converter, and embed the input control function into the control node of the initial topology network model to obtain a topology network model;

[0035] The dynamic control module is used to input the real-time working status information of the energy storage converter into the topology network model, generate control status information, and dynamically adjust the output state of the energy storage converter according to the control status information.

[0036] In a third aspect of the present application, an electronic device is provided, comprising a processor, a memory, a user interface and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory.

[0037] In a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored. The computer program is executed by a processor to implement steps of a control method for a module parallel-type energy storage converter.

[0038] The control method and system of a module parallel type energy storage converter provided by the present invention have the following beneficial effects compared with the prior art:

[0039] (1) By collecting and synchronizing the connection status information and working status information of the energy storage inverter in real time, a complete initial topology network model is formed, which helps to enhance the response speed of the topology network model. At the same time, based on the PID control algorithm, the input control function is embedded to achieve accurate real-time dynamic regulation of the energy storage inverter. Through the topology network model, the coordinated control between the energy storage inverters is realized, the operating efficiency and reliability of the energy storage inverter in the topology network model are optimized, and the working status information is synchronized to the control node, thereby optimizing the data processing process, reducing communication delays, and achieving efficient control instruction generation and transmission.

[0040] (2) By mapping each energy storage inverter to a network node and establishing a connection relationship between network nodes based on their connection status information, the energy storage inverter and the network model are accurately corresponded. By using the network nodes as a transit, efficient data transmission between the energy storage inverter and the control node is achieved. The network nodes can quickly and accurately forward the real-time working status information to the corresponding control node, reducing the delay in data transmission. Through accurate identity recognition, real-time status monitoring and feedback mechanism, the topological structure network model can promptly detect and handle abnormal situations, which helps to improve the stability and reliability of the topological structure network model. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 A schematic flow chart of a control method for a module parallel type energy storage converter provided by the present invention;

[0043] Figure 2 A schematic diagram of the framework of the control system provided by the present invention;

[0044] Figure 3 This is a schematic structural diagram of an electronic device provided by the present invention.

[0045] Explanation of the accompanying drawings: 1. control system; 11. data acquisition module; 12. model building module; 13. dynamic control module; 2. electronic device; 21. processor; 22. communication bus; 23. user interface; 24. network interface; 25. memory. DETAILED DESCRIPTION

[0046] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] The present invention discloses a control method for a module parallel type energy storage converter, referring to Figure 1 The method includes steps S1 to S4.

[0048] Step S1, collecting status information of an energy storage converter, wherein the status information includes connection status information and working status information, and the energy storage converter includes a plurality of power conversion modules connected in parallel.

[0049] In this step, each power conversion module of the energy storage inverter is equipped with an independent data acquisition circuit to collect electrical parameters, temperature and connection status information in real time, and transmit the data of each module to the data acquisition unit through a standardized communication protocol (such as Modbus, CAN bus or Ethernet).

[0050] In one example, each parallel power conversion module has a built-in voltage, current and temperature acquisition circuit, an Ethernet switch is configured, all power conversion modules are connected to a central controller, and network parameters are set to ensure real-time data transmission between the power conversion modules.

[0051] Step S2, constructing an initial topology network model according to the connection status information and working status information of all energy storage converters, and synchronizing the working status information of each energy storage converter to the control node corresponding to the energy storage converter in the initial topology network model.

[0052] This step also includes S11 to S13.

[0053] Step S11, mapping each energy storage converter to a network node, and establishing a network connection relationship between the network nodes according to the connection status information of each energy storage converter.

[0054] In this step, all energy storage converters are encoded in sequence, the encoding information is used as the identity code of the energy storage converter and the identity code is assigned to the corresponding network node; and verification information between multiple energy storage converters is collected, wherein the verification information includes the location information of the energy storage converter; the verification information is bound to the identity code of the corresponding energy storage converter to obtain the identity information. The real-time working status information of the energy storage converter is collected, the corresponding network node is identified according to the identity information, and the real-time working status information is transmitted to the network node, and the network node forwards the real-time working status information to the corresponding control node.

[0055] In one example, a unique identifier (ID) is assigned to each energy storage inverter, for example, using a UUID (universally unique identifier) ​​or other standardized encoding method. In the initial topology network model, a corresponding network node is created for each energy storage inverter. Each node should contain the following attributes: node ID, device type, and location attribute. The node ID corresponds to the unique identifier of the energy storage inverter, the device type identifies the type of device represented by the node, and the location attribute indicates the geographical location of the energy storage inverter or its physical location in the system.

[0056] The connection status information should include the following:

[0057] Connection status: Indicates whether the energy storage converter is currently connected (such as "connected", "unconnected"). Connection type (optional): Describes the specific type of connection (such as parallel, series, standby, etc.). Connection object: Lists the IDs of other energy storage converters that are connected to this energy storage converter.

[0058] According to the collected connection status information, determine which other converters each energy storage converter has a connection relationship with. For example, if energy storage converter A is in a connection state with energy storage converter B, a connection should be established between node A and node B in the initial topology network model.

[0059] Step S12: associate the network node corresponding to each energy storage converter with the control node, and construct a node mapping relationship between the control node and the corresponding energy storage converter.

[0060] In this step, the mapping strategy includes: allocating energy storage inverters that are geographically close to each other to the same control node to reduce latency, or evenly distributing the inverters according to the processing capacity of the control node to prevent overload of a single control node, or allocating devices with similar functions to the same control node according to the function or type of the energy storage inverter.

[0061] In the network node properties of each energy storage converter, add the control node ID or name to indicate its corresponding control node. In the configuration of the control node, add the list of energy storage converter nodes it manages to ensure that the control node can correctly receive and process data from these nodes.

[0062] Step S13, constructing an initial topology network model according to the network connection relationship, node mapping relationship and connection status information.

[0063] In this step, the basic information of all energy storage converters is collected and sorted, including the unique identifier, device type, physical location and other attribute information of each energy storage converter. At the same time, the information of all control nodes is confirmed, including the identifier, location and management scope of the control node. The connection relationship between the energy storage converters is established. According to the collected connection status information, the connection mode (such as parallel or series) and the connection status (such as connected or not connected) between each energy storage converter are determined. These connection relationships constitute the basic structure of the network. A mapping relationship is established between the energy storage converter and its corresponding control node. According to the node mapping relationship determined previously, the corresponding control node is specified for each energy storage converter to ensure that each energy storage converter can be correctly managed and controlled. The above information is integrated into a complete network model. In this model, the energy storage converter and the control node are used as nodes of the network, and the connection relationship between them is used as the edge of the network. Each node contains its unique attribute information, and each edge is marked with the connection type and status information.

[0064] In this step, by mapping each energy storage inverter to a network node and establishing a connection relationship between network nodes based on their connection status information, the accurate correspondence between the energy storage inverter and the network model is achieved. By using the network nodes as a transit, efficient data transmission between the energy storage inverter and the control node is achieved. The network nodes can quickly and accurately forward the real-time working status information to the corresponding control node, reducing the delay in data transmission. Through accurate identity recognition, real-time status monitoring and feedback mechanism, the topological structure network model can promptly detect and handle abnormal situations, which helps to improve the stability and reliability of the topological structure network model.

[0065] Step S3, constructing an input control function based on the working state information and the PID gain parameters corresponding to each energy storage converter, and embedding the input control function into the control node of the initial topology network model to obtain the topology network model.

[0066] In this step, the working status information includes real-time parameters of the energy storage inverter, such as voltage, current, temperature and power, which are used to monitor and control the operation of the equipment in real time. PID gain parameters include proportional (P), integral (I) and differential (D) gains, which are used to design a PID controller to achieve precise control of the output of the energy storage inverter. The input control function is based on the PID algorithm and combines the working status information to generate a control signal to adjust the operating state of the energy storage inverter. Ensure that the working status data of each energy storage inverter can be collected in real time and transmitted to the control node in real time. At the same time, configure appropriate PID gain parameters for each energy storage inverter and adjust and optimize them according to the equipment characteristics and control requirements.

[0067] The process of designing the input control function is based on the PID control algorithm. First, the control objective needs to be defined, such as voltage regulation, current control, or power management. Subsequently, a PID controller is designed, whose basic formula is that the control output is equal to the sum of the proportional term, the integral term, and the differential term. When implementing it, a PID controller can be written using a programming language such as Python or control system development software such as MATLAB / Simulink. For example, using Python, you can create a class that contains the PID calculation logic, through which the control signal is calculated and applied to the energy storage inverter to adjust its output.

[0068] The constructed input control function is embedded into the control node to realize the centralized management and control of the energy storage converter. First, the functional module of the control node is updated to enable it to have the ability to receive data, execute control algorithms, and send control signals. Then, the PID control function is integrated into the management software of the control node by instantiating the control node class and adding the corresponding PID controller for each energy storage converter. In addition, a communication mechanism needs to be established to ensure that the control node can communicate bidirectionally with the corresponding energy storage converter to receive working status information and send control signals. This can be achieved by using communication protocols such as MQTT, HTTP, or Modbus, while ensuring the security of the communication process, and using encryption and authentication mechanisms to prevent data leakage and illegal access.

[0069] The initial topology network model will contain energy storage converter nodes and control nodes, and reflect the connection relationship between them through edges. The energy storage converter nodes include attributes such as unique identifiers, device types, and locations, while the control nodes contain control modules, which are responsible for running PID control functions and managing the corresponding energy storage converters. In order to ensure the accuracy of the model, it is necessary to verify the node integrity of the topology structure, the accuracy of the edge relationship, and whether the control module functions properly.

[0070] For example, assume that there are three energy storage converters (A, B, C) and two control nodes (CN1, CN2). First, collect the working status information and PID gain parameters of the energy storage converters A, B, and C, and confirm that the control node CN1 is responsible for managing A and B, and CN2 is responsible for managing C. Then, design and implement the corresponding PID controller for each converter. Embed the PID control function for controlling A and B in the control node CN1, and embed the PID control function for controlling C in CN2. Next, build a topology model, with A, B, and C as energy storage converter nodes, CN1 and CN2 as control nodes, and establish edge relationships between them through parallel and direct connections. Finally, verify the effectiveness of the control function through simulation or actual operation, and adjust the PID parameters to optimize system performance.

[0071] In this embodiment, the expression of the input control function is:

[0072]

[0073] u P (t) = argmin[(P ref -P out (t)) 2 +λ||j|| 2 ]

[0074] u(t)=u I (t)+u V (t)+u P (t)

[0075] Among them, u I (t) represents the current control function at time t, K P,I represents the current proportional gain parameter, e I (t) represents the current error function, K II represents the current integral gain parameter, represents the current nonlinear compensation function, I out Represents the output current of the energy storage converter, represents the state vector of the energy storage converter, u V (t) represents the voltage control function at time t, K P,V represents the voltage proportional gain parameter, e V (t) represents the voltage error function, K I,V Represents the voltage integral gain parameter, K D,V represents the voltage differential gain parameter, represents the voltage feedforward compensation function, V out Indicates the output voltage of the energy storage converter, u P (t) represents the power control function at time t, argmin() represents the minimum value function, P ref Indicates the reference power value, P out (t) represents the actual output power of the energy storage converter at time t, λ represents the power control weight coefficient, j represents the switch modulation signal, and u(t) represents the control input function at time t.

[0076] In this embodiment, the expression of the topological structure network model is:

[0077]

[0078] Where V(t) represents the output voltage function of the energy storage converter, μ 11 Represents the first voltage dynamic coefficient, μ 12 represents the second voltage dynamic coefficient, γ 1 represents the voltage control input coefficient, α represents the first nonlinear compensation coefficient, ωV (t) represents the voltage process noise function, I(t) represents the output current function of the energy storage converter, μ 21 Represents the first current dynamic coefficient, μ 22 represents the second current dynamic coefficient, γ 2 represents the current control input coefficient, β represents the second nonlinear compensation coefficient, ω I (t) represents the current process noise function, θ(t) represents the system phase angle function of the energy storage converter, μ 31 Represents the first phase angle dynamic coefficient, μ 32 represents the second phase angle dynamic coefficient, γ 3 represents the phase angle control input coefficient, ω θ (t) represents the phase process noise function, y(t) represents the observable output function of the topological network model, and v(t) represents the measurement noise function.

[0079] Step S4, inputting the real-time working status information of the energy storage converter into the topological structure network model, generating control status information, and dynamically adjusting the output state of the energy storage converter according to the control status information.

[0080] In this embodiment, the regulation state information is sent to the control node corresponding to each energy storage converter through the topological network model, so that each energy storage converter dynamically adjusts the output state according to the regulation state information.

[0081] Select the appropriate communication protocol according to system requirements, such as MQTT for IoT environments, HTTP / HTTPS for Web-based, Modbus widely used in industrial automation, or TCP / IP protocol that provides stable two-way communication. Make sure all control nodes and energy storage converters support the selected protocol to achieve efficient data transmission.

[0082] Use JSON or XML to ensure that information is transmitted and parsed correctly in the network. For example, the JSON format can be used to structure the parameters such as voltage, current, and power contained in the control signal, which is convenient for each node to parse and process. In the control node, the control status information is generated based on the real-time working status information and the PID control algorithm. This process includes collecting real-time data from the energy storage inverter, such as voltage, current, temperature, and power, and using the PID controller to calculate the control signal to be sent. In specific implementation, the control logic can be written in a programming language such as Python. For example, a PID controller class is used to adjust the output state of the energy storage inverter by calculating the error and generating the control output.

[0083] After the control message is generated, it is sent to the corresponding control node through the topological network model using the selected communication protocol. In this process, the target node must be determined first, that is, the control node corresponding to the energy storage inverter that needs to receive the control signal must be identified. Then, an active communication connection is established, and the message is sent according to the protocol used, such as publishing a message to a specified topic through MQTT, or sending a POST request to the API endpoint of the energy storage inverter through HTTP.

[0084] After receiving the control status information sent by the control node, the energy storage converter needs to parse and process it. The message is received through a predetermined communication protocol, and the parameters in the control signal, such as the set voltage, current, and power, are parsed. Then, according to these parameters, its output state is dynamically adjusted, such as adjusting the voltage and current settings, to achieve precise control of the system.

[0085] In order to ensure the execution effect of the control command and the stable operation of the system, a feedback and monitoring mechanism needs to be established. After adjusting the output state, the energy storage converter should feed back the new working state information to the control node to form a closed-loop control system. The control node monitors the feedback data to detect whether it reaches the expected state. If an abnormality is found, it will trigger an alarm or readjust the control parameters in time.

[0086] In addition, it is also crucial to ensure the security of the communication process and the reliability of data transmission. This includes using TLS / SSL for data encryption to ensure the confidentiality and integrity of communication data; using identity authentication mechanisms to ensure that only authorized devices and nodes can participate in communication; establishing redundant communication paths to maintain smooth communication in the event of partial network failures; and implementing error handling mechanisms such as message confirmation and retry to ensure that control signals can be transmitted reliably.

[0087] Furthermore, the regulation status information includes basic control parameters, dynamic adjustment parameters and protection limit parameters, wherein the basic control parameters include one or more of the output voltage setting value, the output current limit, the power setting value, the power factor adjustment value, the working mode identification and the operation status flag; the dynamic adjustment parameters include one or more of the proportional coefficient, the integral coefficient, the differential coefficient, the dynamic response time, the adjustment dead zone range, the overshoot limit value and the stability requirement; the protection limit parameters include one or more of the overvoltage protection value, the undervoltage protection value, the overcurrent protection value, the overpower protection value, the device temperature upper limit, the ambient temperature range and the temperature rise change rate limit.

[0088] By collecting and synchronizing the connection status information and working status information of the energy storage inverter in real time, a complete initial topology network model is formed, which helps to enhance the response speed. At the same time, based on the PID control algorithm, the input control function is embedded to achieve accurate real-time dynamic regulation of the energy storage inverter. The topology network model is used to achieve coordinated control among the energy storage inverters, optimize the operating efficiency and reliability of the energy storage inverter in the topology network model, and synchronize the working status information to the control node, thereby optimizing the data processing process, reducing communication delays, and achieving efficient control instruction generation and transmission.

[0089] Based on the above method, a control system of a module parallel type energy storage converter is described. Figure 2 The control system 1 includes a data acquisition module 11, a model building module 12 and a dynamic control module 13, wherein:

[0090] The data acquisition module 11 is used to collect status information of the energy storage converter, wherein the status information includes connection status information and working status information;

[0091] The model building module 12 is used to build an initial topology network model according to the connection status information and working status information of all energy storage converters, and synchronize the working status information of each energy storage converter to the control node corresponding to the energy storage converter in the initial topology network model, and build an input control function based on the working status information and the PID gain parameter corresponding to each energy storage converter, and embed the input control function into the control node of the initial topology network model to obtain the topology network model;

[0092] The dynamic control module 13 is used to input the real-time working status information of the energy storage converter into the topological structure network model, generate control status information, and dynamically adjust the output state of the energy storage converter according to the control status information.

[0093] In one example, the model building module 12 is used to map each energy storage inverter into a network node, establish a network connection relationship between network nodes based on the connection status information of each energy storage inverter; associate the network node corresponding to each energy storage inverter with the control node, and build a node mapping relationship between the control node and the corresponding energy storage inverter; and build an initial topology network model based on the network connection relationship, node mapping relationship and connection status information.

[0094] In one example, the model building module 12 is used to encode all energy storage inverters in sequence, use the encoded information as the identity code of the energy storage inverter and assign the identity code to the corresponding network node; and collect verification information between multiple energy storage inverters, wherein the verification information includes the location information of the energy storage inverter; bind the verification information with the identity code of the corresponding energy storage inverter to obtain the identity information; collect the real-time working status information of the energy storage inverter, identify the corresponding network node according to the identity information, and transmit the real-time working status information to the network node, and the network node forwards the real-time working status information to the corresponding control node.

[0095] In one example, the dynamic control module 13 is used to send control state information to the control node corresponding to each energy storage converter through the topological network model, so that each energy storage converter dynamically adjusts the output state according to the control state information.

[0096] In one example, the control state information includes basic control parameters, dynamic adjustment parameters and protection limit parameters, wherein:

[0097] The basic control parameters include one or more of the output voltage setting value, the output current limit value, the power setting value, the power factor adjustment value, the working mode identification and the operation status flag;

[0098] The dynamic adjustment parameters include one or more of a proportional coefficient, an integral coefficient, a differential coefficient, a dynamic response time, an adjustment dead zone range, an overshoot limit value, and a stability requirement;

[0099] The protection limit parameters include one or more of an overvoltage protection value, an undervoltage protection value, an overcurrent protection value, an overpower protection value, a device temperature upper limit, an ambient temperature range, and a temperature rise change rate limit.

[0100] In one example, the expression for the input control function is:

[0101]

[0102]

[0103] u P (t) = argmin[(P ref -P out (t)) 2 +λ||j|| 2 ]

[0104] u(t)=u I (t)+u V (t)+u P (t)

[0105] Among them, u I(t) represents the current control function at time t, K P,I represents the current proportional gain parameter, e I (t) represents the current error function, K I,I represents the current integral gain parameter, represents the current nonlinear compensation function, I out Represents the output current of the energy storage converter, represents the state vector of the energy storage converter, u V (t) represents the voltage control function at time t, K P,V represents the voltage proportional gain parameter, e V (t) represents the voltage error function, K I,V Represents the voltage integral gain parameter, K D,V represents the voltage differential gain parameter, represents the voltage feedforward compensation function, V out Indicates the output voltage of the energy storage converter, u P (t) represents the power control function at time t, argmin() represents the minimum value function, P ref Indicates the reference power value, P out (t) represents the actual output power of the energy storage converter at time t, λ represents the power control weight coefficient, j represents the switch modulation signal, and u(t) represents the control input function at time t.

[0106] In one example, the expression of the topology network model is:

[0107]

[0108] Where V(t) represents the output voltage function of the energy storage converter, μ 11 Represents the first voltage dynamic coefficient, μ 12 represents the second voltage dynamic coefficient, γ 1 represents the voltage control input coefficient, α represents the first nonlinear compensation coefficient, ω V (t) represents the voltage process noise function, I(t) represents the output current function of the energy storage converter, μ 21 Represents the first current dynamic coefficient, μ 22 represents the second current dynamic coefficient, γ 2 represents the current control input coefficient, β represents the second nonlinear compensation coefficient, ω I (t) represents the current process noise function, θ(t) represents the system phase angle function of the energy storage converter, μ 31 Represents the first phase angle dynamic coefficient, μ 32 represents the second phase angle dynamic coefficient, γ 3 represents the phase angle control input coefficient, ω θ(t) represents the phase process noise function, y(t) represents the observable output function of the topological network model, and v(t) represents the measurement noise function.

[0109] See also Figure 3 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 3 As shown, the electronic device 2 may include: at least one processor 21 , at least one network interface 24 , a user interface 23 , a memory 25 , and at least one communication bus 22 .

[0110] The communication bus 22 is used to realize the connection and communication between these components.

[0111] The user interface 23 may include a display screen (Display) and a camera (Camera), and the optional user interface 23 may also include a standard wired interface and a wireless interface.

[0112] The network interface 24 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0113] Among them, the processor 21 may include one or more processing cores. The processor 21 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 25, and calling data stored in the memory 25. Optionally, the processor 21 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 21 can integrate one or more combinations of a central processing unit (Central Processing Unit, CPU), a graphics processor (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 21, and it can be implemented separately through a chip.

[0114] Among them, the memory 25 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 25 includes a non-transitory computer-readable storage medium. The memory 25 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 25 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned method embodiments, etc.; the data storage area may store data involved in the above-mentioned method embodiments, etc. The memory 25 may also be optionally at least one storage device located away from the aforementioned processor 21. As Figure 3 As shown, the memory 25 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program of a control method for a module parallel type energy storage converter.

[0115] exist Figure 3 In the electronic device 2 shown, the user interface 23 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 21 can be used to call an application program stored in the memory 25 for a control method of a modular parallel energy storage inverter. When executed by one or more processors, the electronic device executes one or more methods in the above-mentioned embodiments.

[0116] A computer-readable storage medium stores instructions, which, when executed by one or more processors, enable the computer to execute one or more methods in the above-mentioned embodiments.

[0117] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0118] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0119] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0120] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0121] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0122] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0123] The above are only exemplary embodiments of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, it will be easy for those skilled in the art to think of other embodiments of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary techniques in the technical field that are not recorded in the present disclosure.

[0124] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A control method for a module parallel type energy storage converter, characterized in that: The method comprises: Collecting status information of an energy storage converter, wherein the status information includes connection status information and working status information, and the energy storage converter includes a plurality of power conversion modules connected in parallel; According to the connection status information and working status information of all energy storage converters, an initial topology network model is constructed, and the working status information of each energy storage converter is synchronized to the control node corresponding to the energy storage converter in the initial topology network model; Based on the working state information and the PID gain parameters corresponding to each energy storage converter, an input control function is constructed, and the input control function is embedded in the control node of the initial topology network model to obtain a topology network model; The real-time working status information of the energy storage converter is input into the topological structure network model to generate regulation status information, and the output status of the energy storage converter is dynamically adjusted according to the regulation status information.

2. The control method of the module parallel type energy storage converter according to claim 1, characterized in that: The construction of the initial topology network model specifically includes: Mapping each energy storage converter to a network node, and establishing a network connection relationship between the network nodes according to the connection status information of each energy storage converter; Associating the network node corresponding to each energy storage converter with the control node, and constructing a node mapping relationship between the control node and the corresponding energy storage converter; The initial topology network model is constructed according to the network connection relationship, the node mapping relationship and the connection status information.

3. The control method of the module parallel type energy storage converter according to claim 2, characterized in that: The step of synchronizing the working status information of each energy storage converter to the control node corresponding to the energy storage converter in the initial topology network model specifically includes: Encode all energy storage converters in sequence, use the encoding information as the identity code of the energy storage converter and assign the identity code to the corresponding network node; and collecting verification information between the plurality of energy storage converters, wherein the verification information includes location information of the energy storage converters; Binding the verification information with the identity code of the corresponding energy storage converter to obtain the identity information; The real-time working status information of the energy storage converter is collected, the corresponding network node is identified according to the identity information, and the real-time working status information is transmitted to the network node, and the network node forwards the real-time working status information to the corresponding control node.

4. The control method of the module parallel type energy storage converter according to claim 1, characterized in that: The dynamically adjusting the output state of the energy storage converter according to the regulation state information specifically includes: The regulation state information is sent to the control node corresponding to each energy storage converter through the topological structure network model, so that each energy storage converter dynamically adjusts the output state according to the regulation state information.

5. The control method of the module parallel type energy storage converter according to claim 4, characterized in that: The control state information includes basic control parameters, dynamic adjustment parameters and protection limit parameters, wherein: The basic control parameters include one or more of the output voltage setting value, the output current limit value, the power setting value, the power factor adjustment value, the working mode identification and the operation status flag; The dynamic adjustment parameters include one or more of a proportional coefficient, an integral coefficient, a differential coefficient, a dynamic response time, an adjustment dead zone range, an overshoot limit value, and a stability requirement; The protection limit parameters include one or more of an overvoltage protection value, an undervoltage protection value, an overcurrent protection value, an overpower protection value, a device temperature upper limit, an ambient temperature range, and a temperature rise change rate limit.

6. The control method of the module parallel type energy storage converter according to claim 1, characterized in that: The expression of the input control function is: u P (t)=argmin[(P ref -P out (t)) 2 +λ||j|| 2 ] u(t)=u I (t)+u V (t)+u P (t) Among them, u I (t) represents the current control function at time t, K P,I represents the current proportional gain parameter, e I (t) represents the current error function, K I,I represents the current integral gain parameter, represents the current nonlinear compensation function, I out Represents the output current of the energy storage converter, represents the state vector of the energy storage converter, u V (t) represents the voltage control function at time t, K P,V Represents the voltage proportional gain parameter, e V (t) represents the voltage error function, K I,V Represents the voltage integral gain parameter, K D,V represents the voltage differential gain parameter, represents the voltage feedforward compensation function, V out Indicates the output voltage of the energy storage converter, u P (t) represents the power control function at time t, argmin() represents the minimum value function, P ref Indicates the reference power value, P out (t) represents the actual output power of the energy storage converter at time t, λ represents the power control weight coefficient, j represents the switch modulation signal, and u(t) represents the control input function at time t.

7. The control method of the module parallel type energy storage converter according to claim 1, characterized in that: The expression of the topological network model is: Where V(t) represents the output voltage function of the energy storage converter, μ 11 Represents the first voltage dynamic coefficient, μ 12 represents the second voltage dynamic coefficient, γ1 represents the voltage control input coefficient, α represents the first nonlinear compensation coefficient, ω V (t) represents the voltage process noise function, I(t) represents the output current function of the energy storage converter, μ 21 Represents the first current dynamic coefficient, μ 22 represents the second current dynamic coefficient, γ2 represents the current control input coefficient, β represents the second nonlinear compensation coefficient, ω I (t) represents the current process noise function, θ(t) represents the system phase angle function of the energy storage converter, μ 31 Represents the first phase angle dynamic coefficient, μ 32 represents the second phase angle dynamic coefficient, γ3 represents the phase angle control input coefficient, ω θ (t) represents the phase process noise function, y(t) represents the observable output function of the topological network model, and v(t) represents the measurement noise function.

8. A control system for a module parallel type energy storage converter, characterized in that: The control system (1) comprises a data acquisition module (11), a model building module (12) and a dynamic control module (13), wherein: The data acquisition module (11) is used to collect status information of the energy storage converter, wherein the status information includes connection status information and working status information; The model building module (12) is used to build an initial topology network model according to the connection status information and working status information of all energy storage converters, and synchronize the working status information of each energy storage converter to the control node corresponding to the energy storage converter in the initial topology network model, build an input control function based on the working status information and the PID gain parameter corresponding to each energy storage converter, and embed the input control function into the control node of the initial topology network model to obtain the topology network model; The dynamic control module (13) is used to input the real-time working state information of the energy storage converter into the topological structure network model, generate control state information, and dynamically adjust the output state of the energy storage converter according to the control state information.

9. An electronic device, characterized in that: The electronic device (2) comprises a processor (21), a memory (25), a user interface (23) and a network interface (24), wherein the memory (25) is used to store instructions, the user interface (23) and the network interface (24) are used to communicate with other devices, and the processor (21) is used to execute the instructions stored in the memory (25) so that the electronic device (2) executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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