A state feedback control method for a flywheel energy storage array

Abstract

The present application relates to the technical field of flywheel energy storage, and particularly relates to a state feedback control method for a flywheel energy storage array, which comprises: obtaining operation parameters of the flywheel energy storage array, classifying the obtained operation parameters based on a monitoring task, and judging the state of the flywheel energy storage array by using the classified parameters; optimizing a state information feedback process by using a dynamic feedback control method, so that an upper system makes a quick response to the state information; managing and node-controlling the state of a single flywheel energy storage unit in the flywheel energy storage array based on the state information feedback; and coordinating the overall state of the flywheel energy storage array based on the grid demand and the state of the single flywheel energy storage unit.

Description

Technical Field

[0001] The present invention relates to the technical field of flywheel energy storage, and in particular to a state feedback control method for a flywheel energy storage array. Background Art

[0002] A flywheel energy storage array (FESA) is a clustered energy storage system composed of multiple flywheel storage units (single flywheel systems) connected in parallel or coordinated. This scalability allows for expanded system capacity and power output, making it suitable for scenarios requiring high power output, such as large-scale grid services and industrial applications.

[0003] During operation, flywheel energy storage arrays require real-time monitoring of operating parameters (such as flywheel speed, bearing temperature, bearing vibration frequency, input and output power, etc.) to determine whether the operating status is normal. In the event of anomalies, appropriate solutions must be implemented to ensure the safe operation of individual flywheel energy storage units and the entire flywheel energy storage matrix. This requires a complete control loop, encompassing data acquisition, state assessment, state feedback, and control based on state feedback. Controlling state feedback efficiency and reducing control lag are key to improving the control efficiency of flywheel energy storage arrays.

[0004] To this end, the present invention proposes a method for improving the efficiency of state feedback control of a flywheel energy storage array. Summary of the Invention

[0005] The present invention optimizes the state feedback process by dynamically adjusting the frequency of state feedback of each flywheel energy storage unit to adapt to load scenarios where the flywheel load and state are constantly changing. At the same time, a rapid response strategy for the upper system is constructed to achieve rapid response to flywheel state feedback and reduce control lag.

[0006] The technical solution proposed by the present invention is: a state feedback control method for a flywheel energy storage array, the method comprising:

[0007] Obtaining operating parameters of the flywheel energy storage array, classifying the obtained operating parameters based on the monitoring task, and using the classified parameters to determine the state of the flywheel energy storage array;

[0008] Optimize the state information feedback process through dynamic feedback control method to enable the upper system to respond quickly to the state information;

[0009] Based on status information feedback, the status of individual flywheel energy storage units in the flywheel energy storage array is managed and node controlled;

[0010] The overall state of the flywheel energy storage array is coordinated and controlled based on grid demand and the state of individual flywheel energy storage units.

[0011] Preferably, the obtaining of operating parameters of the flywheel energy storage array, classifying the obtained operating parameters based on the monitoring task, and using the classified parameters to determine the state of the flywheel energy storage array includes:

[0012] According to the monitoring task, the physical state parameters, electrical state parameters and system state parameters of each flywheel in the flywheel energy storage array are collected at the preset collection frequency, and the identification tag of the corresponding flywheel is added;

[0013] The physical state parameters, electrical state parameters and system state parameters are pre-processed to form an original parameter set;

[0014] Extract multiple parameters from the original parameter set to construct the state judgment input feature set ;in, They represent the operating state parameter set, the healthy state parameter set and the safe state parameter set respectively;

[0015] The operating state parameter set includes speed, charge and discharge power, and SOC; the health state parameter set includes bearing temperature, vacuum degree, and vibration frequency; the safety state parameter set includes heating rate and vacuum leakage rate;

[0016] Conduct node-level status judgment of a single flywheel energy storage unit;

[0017] Perform system-level status judgment on the flywheel energy storage array.

[0018] Preferably, the node-level status determination of a single flywheel energy storage unit includes:

[0019] Construct state classification rules, that is, judge the elements in the input feature set through logical combination of states, and define the operating state in combination with thresholds, including:

[0020] The state of each flywheel in the flywheel energy storage array, that is, the node-level state ,in, represents the input power, Indicates the bearing temperature, Indicates the temperature rise rate of the bearing, Indicates bearing vibration energy; Indicates the speed fluctuation rate;

[0021] if , judge that the flywheel is in normal charging state;

[0022] if , it is judged that the flywheel is in the bearing overheating state;

[0023] if , it is judged that the flywheel is in a rotor imbalance state.

[0024] Preferably, the system-level status determination of the flywheel energy storage array includes:

[0025] Gather the operating parameters of all flywheels to generate a global characteristic parameter set ;in, Respectively represent the average SOC, maximum temperature value, number of faulty flywheels, and power imbalance;

[0026] in, , represents the average input power; Indicates the number of flywheels; Indicates the Input power to the flywheel;

[0027] System-level status ;

[0028] if , judging that the flywheel energy storage array is in a normal state;

[0029] if , determining that the flywheel energy storage array is in a local fault state;

[0030] if , determining that the flywheel energy storage array is in an overload state;

[0031] if , it is determined that the flywheel energy storage array is in an emergency shutdown state.

[0032] Preferably, the state information feedback process is optimized by a dynamic feedback control method so that the upper system can quickly respond to the state information, including:

[0033] Prioritize node-level status and assign priority values, giving priority feedback to status with high priority values, including:

[0034] Priority value for normal charging status ;

[0035] Priority value for bearing overheat status ;

[0036] Priority value for rotor imbalance status ;in, ;

[0037] Dynamically adjust the state feedback frequency, that is, adjust the state feedback frequency according to the flywheel load and state change rate, including:

[0038] Set dynamic feedback frequency ;in, They represent the basic feedback frequency, adjustment coefficient, feedback sensitivity coefficient, maximum allowable parameter change range and absolute value of parameter change respectively.

[0039] Preferably, the state information feedback process is optimized by a dynamic feedback control method so that the upper system can quickly respond to the state information, and further includes:

[0040] Set up event triggering mechanisms to avoid invalid feedback, including:

[0041] Set event trigger conditions ;in, Indicates the parameter value collected last time. represents the static threshold; Indicates the dynamic change rate threshold; Indicates the parameter value collected at the current moment;

[0042] A fast response strategy for the upper system is constructed by using pre-caching and preloading, state machine jump prediction, and lightweight decision trees to achieve a fast response to flywheel status feedback.

[0043] Preferably, the use of pre-caching and pre-loading, state machine jump prediction and lightweight decision tree to build a high-level system fast response strategy includes:

[0044] Pre-store key data and model parameters, including:

[0045] Define a fixed-size memory area locally and store data in a loop;

[0046] Adopt the least recently used algorithm LRU to dynamically eliminate infrequently accessed data;

[0047] Constructing a flywheel dynamics model and preloading the flywheel dynamics model into the CPU cache L1 or L2;

[0048] Precompile the pre-trained decision tree model and state transition matrix and store them in the memory reserved area, including:

[0049] Construct a Markov chain model, use the historical state statistical data obtained from the database to train the Markov chain model, and calculate the state transition probability;

[0050] State transition probability ,in, Indicates the current state The next time and space becomes a state Statistics of Indicates status Statistics of

[0051] Predict the next state ;in, ;

[0052] According to the predicted next state, pre-load the preset control logic into the memory, wherein the control logic includes cooling, reducing the speed, and shutting down;

[0053] A lightweight decision tree is constructed, and speed, bearing temperature, and vibration frequency are selected as split nodes. The split nodes are selected using the information gain maximization criterion.

[0054] Limit the depth to 3 to prevent overfitting;

[0055] Convert decision data into a bit mask lookup table and achieve fast response through FPGA;

[0056] The management and node control of the state of a single flywheel energy storage unit in the flywheel energy storage array based on state information feedback includes:

[0057] Get status feedback information of the flywheel;

[0058] A single edge controller is deployed for each flywheel to control the flywheel system parameters based on status feedback information, specifically:

[0059] Use PID controller to control the flywheel speed:

[0060] Motor output torque ;in, Indicates PID gain; Indicates the target speed, Indicates the flywheel speed.

[0061] Preferably, the coordinated control of the overall state of the flywheel energy storage array based on grid demand and the state of a single flywheel energy storage unit includes:

[0062] Receive grid instructions and parse them to obtain frequency modulation signals, power adjustment amounts, and target output power;

[0063] Get the real-time output power of the flywheel energy storage array , calculate the total power that needs to be adjusted ;in, Indicates the power adjustment amount;

[0064] Get the operating parameters of each flywheel to form the node operating parameter vector ,in, Respectively represent The speed, temperature, vibration frequency and power of each flywheel;

[0065] Dynamically allocate output power to each flywheel, that is, when the target output power is met while minimizing fault propagation and life loss, including:

[0066] The available output power per flywheel is:

[0067] ;

[0068] in, Indicates the flywheel rated power, represents the SOC correction factor, Indicates the maximum output power of the battery. Indicates the power adjustment period;

[0069] Assign priority weights based on flywheel health , prioritize the use of healthy flywheels; ;in, They respectively represent the number of charge and discharge times completed by the flywheel and the total number of designed charge and discharge times;

[0070] While meeting grid demand, the load on each flywheel in the flywheel energy storage array is balanced to extend its service life. Specifically:

[0071] Build the optimization model:

[0072] ,in, represents the life protection weight; Indicates the number of working flywheels in the flywheel energy storage array;

[0073] The alternating direction multiplier method ADMM is used to solve the optimization model and obtain the final distribution ;

[0074] Will sent to the controller of each flywheel;

[0075] Monitor the status of each flywheel, that is, the node-level status, and when the status changes, reset to zero and trigger power redistribution.

[0076] The present invention also provides an electronic device, comprising a processor, a memory connected to the processor, and a communication module, wherein the electronic device is used to execute the state feedback control method for a flywheel energy storage array.

[0077] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the state feedback control method for a flywheel energy storage array.

[0078] Beneficial effects of the present invention:

[0079] 1. This invention adaptively adjusts the frequency of state feedback based on the flywheel energy storage system's real-time operating parameters, load, and state change rate. Furthermore, based on an event-triggered mechanism, feedback is triggered only when a true state change occurs (e.g., exceeding a set threshold), thus avoiding invalid reporting and reducing bandwidth usage. Through pre-caching, state transition prediction, and lightweight decision tree encoding, the upper system can quickly respond to feedback status, thereby reducing control latency of the flywheel energy storage array.

[0080] 2. This invention adjusts the state of the flywheel energy storage array based on grid demand and the real-time status of each flywheel. Specifically, it adjusts the distribution of total power demand among multiple flywheel energy storage units, assigning corresponding output power according to their respective priority weights. This allows the system to adapt to fluctuations in grid demand and changes in the status of flywheel energy storage units, ensuring the safe operation of the flywheel energy storage array. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 The present invention is a flow chart of a state feedback control method for a flywheel energy storage array. DETAILED DESCRIPTION

[0082] The following description is intended to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are for illustrative purposes only, and those skilled in the art will readily appreciate other obvious variations. The basic principles of the present invention defined in the following description may be applied to other embodiments, variations, improvements, equivalents, and other technical solutions that do not depart from the spirit and scope of the present invention.

[0083] It is understandable that the term "one" should be understood as "at least one" or "one or more", that is, in one embodiment, the number of an element may be one, while in another embodiment, the number of the element may be multiple, and the term "one" should not be understood as a limitation on the quantity.

[0084] refer to Figure 1 The technical solution provided by the present invention is: a state feedback control method for a flywheel energy storage array, comprising the following steps:

[0085] Step 1: Obtain the operating parameters of the flywheel energy storage array, classify the obtained operating parameters based on the monitoring task, and use the classified parameters to determine the status of the flywheel energy storage array. The following steps are included:

[0086] Step 1.1: According to the monitoring task, collect the physical state parameters, electrical state parameters, and system state parameters of each flywheel in the flywheel energy storage array at a preset collection frequency, and add an identification tag to the corresponding flywheel;

[0087] Step 1.2, pre-processing the physical state parameters, electrical state parameters and system state parameters to form an original parameter set;

[0088] Step 1.3: Extract multiple parameters from the original parameter set to construct the state judgment input feature set ;in, They represent the operating status parameter set, healthy status parameter set and safe status parameter set respectively.

[0089] Among them, the operating status parameter set includes speed, charge and discharge power, and SOC; the health status parameter set includes bearing temperature, vacuum degree, and vibration frequency; and the safety status parameter set includes heating rate and vacuum leakage rate.

[0090] Step 1.4: Node-level status determination of a single flywheel energy storage unit, specifically:

[0091] Construct state classification rules, that is, judge the elements in the input feature set through logical combination of states, and define the operating state in combination with thresholds, including:

[0092] The state of each flywheel in the flywheel energy storage array, that is, the node-level state ,in, represents the input power, Indicates the bearing temperature, Indicates the temperature rise rate of the bearing, Indicates bearing vibration energy; Indicates the speed fluctuation rate;

[0093] if , judge that the flywheel is in normal charging state;

[0094] if , it is judged that the flywheel is in the bearing overheating state;

[0095] if , it is judged that the flywheel is in a rotor imbalance state.

[0096] Step 1.5: Determine the system-level status after multiple flywheels form an array. Specifically:

[0097] Gather the operating parameters of all flywheels to generate a global characteristic parameter set ;in, Respectively represent the average SOC, maximum temperature value, number of faulty flywheels, and power imbalance;

[0098] in, , represents the average input power; Indicates the number of flywheels; Indicates the Input power to the flywheel;

[0099] System-level state ;

[0100] If , the flywheel energy storage array is in a normal state;

[0101] If , the flywheel energy storage array is in a local fault state;

[0102] If , the flywheel energy storage array is in an overload state;

[0103] If , the flywheel energy storage array is in an emergency shutdown state.

[0104] Step 2, optimize the state information feedback process through a dynamic feedback control method, so that the upper system responds quickly to the state information, including the following steps:

[0105] Step 2.1, prioritize the node-level state and assign a priority value, and preferentially feedback the state with a high priority value, including:

[0106] Priority value of normal charging state ;

[0107] Priority value of bearing overheating state ;

[0108] Priority value of rotor imbalance state ; wherein ;

[0109] Adjust the state feedback frequency dynamically, that is, adjust the state feedback frequency according to the load and state change rate of the flywheel, including:

[0110] Set the dynamic feedback frequency ; wherein respectively represent the basic feedback frequency, the adjustment coefficient, the feedback sensitivity coefficient, the maximum allowed parameter change range, and the parameter change absolute value.

[0111] For example, when the bearing temperature rises at a temperature rise rate of 3℃ / min, the maximum temperature rise rate allowed by the system is 5℃ / min;

[0112] At this time, The priority state feedback frequency is:

[0113] .

[0114] Step 2.2, set an event triggering mechanism to avoid invalid feedback, including:

[0115] Set event trigger conditions ;in, Indicates the parameter value collected last time. represents the static threshold; Indicates the dynamic change rate threshold; Indicates the parameter value collected at the current moment;

[0116] Step 2.3: Utilize pre-caching and preloading, state machine jump prediction, and lightweight decision trees to build a high-level system fast response strategy to achieve a fast response to flywheel status feedback, including the following steps:

[0117] Pre-store key data and model parameters, including:

[0118] Define a fixed-size memory area locally and store data in a loop;

[0119] Adopt LRU (Least Recently Used) algorithm to dynamically eliminate infrequently accessed data;

[0120] Constructing a flywheel dynamics model and preloading the flywheel dynamics model into the CPU cache L1 or L2;

[0121] Precompile the pre-trained decision tree model and state transition matrix and store them in the memory reserved area, including:

[0122] Construct a Markov chain model, use the historical state statistical data obtained from the database to train the Markov chain model, and calculate the state transition probability;

[0123] State transition probability ,in, Indicates the current state The next time and space becomes a state Statistics of Indicates status Statistics of

[0124] Predict the next state ;in, ;

[0125] According to the predicted next state, the preset control logic is loaded into the memory in advance, and the control logic includes cooling, reducing the speed, and shutting down.

[0126] For example, through historical status data, when the flywheel is in the charging state and When the current state is charging and the bearing temperature is 75°C, the flywheel is predicted to enter the bearing overheat state. The cooling control logic is loaded into the memory in advance for quick access.

[0127] A lightweight decision tree is constructed, and speed, bearing temperature, and vibration frequency are selected as split nodes. The split nodes are selected using the information gain maximization criterion.

[0128] Limit the depth to 3 to prevent overfitting;

[0129] Convert decision data into a bit mask lookup table to achieve rapid response through the FPGA. For example, compile common fault response strategies into binary instruction sets and pre-store them in memory to reduce the overhead of instruction interpretation and execution.

[0130] For example, when charging, the flywheel suddenly experiences excessive vibration frequency. The vibration frequency is written to the memory cache, and based on historical data, the next state is predicted to be the rotor imbalance state, and the "vibration suppression" strategy is pre-loaded.

[0131] The decision tree triggers the "vibration suppression" strategy and obtains the "load reduction 30% and active damping start" instruction, which is sent to the magnetic bearing through the FPGA.

[0132] The upper system here refers to the core control and management system of the flywheel energy storage matrix, including edge control systems, cloud servers, local control systems, etc.

[0133] Step 3: Based on the status information feedback, the status of a single flywheel energy storage unit in the flywheel energy storage array is managed and node controlled, including the following steps:

[0134] Get status feedback information of the flywheel;

[0135] A single edge controller is deployed for each flywheel to control the flywheel system parameters based on status feedback information, specifically:

[0136] Use PID controller to control the flywheel speed:

[0137] Motor output torque ;in, Indicates PID gain; Indicates the target speed, Indicates the flywheel speed.

[0138] Step 4: Coordinate and control the overall state of the flywheel energy storage array based on grid demand and the state of each flywheel energy storage unit, including the following steps:

[0139] Receive grid instructions and parse them to obtain frequency modulation signals, power adjustment amounts, and target output power;

[0140] Get the real-time output power of the flywheel energy storage array , calculate the total power that needs to be adjusted ;in, represents the power adjustment amount;

[0141] Obtain the operating parameters of each flywheel to form a node operating parameter vector wherein, represents the rotation speed, temperature, vibration frequency and power of the i-th flywheel, respectively;

[0142] Dynamically allocate the output power for each flywheel, that is, minimize the fault propagation and life loss while meeting the target output power , including:

[0143] The output power available for each flywheel is:

[0144] ;

[0145] wherein, represents the rated power of the flywheel, represents the SOC correction factor, represents the maximum output power of the battery, represents the power adjustment period;

[0146] According to the flywheel health state, assign a priority weight , and prefer to use healthy flywheels; ; wherein, represents the number of completed charge-discharge cycles of the flywheel and the designed total number of charge-discharge cycles, respectively;

[0147] Balance the load of each flywheel in the flywheel energy storage array while meeting the grid demand, to prolong the service life, specifically:

[0148] Build an optimization model:

[0149] wherein, represents the life protection weight; represents the number of flywheels working in the flywheel energy storage array;

[0150] Solve the optimization model by using the alternating direction multiplier method (ADMM) to obtain the final allocated ;

[0151] Send to the controller of each flywheel;

[0152] Monitor the state of each flywheel, that is, the node-level state, when the state changes, set to zero and trigger power reallocation.

[0153] For example, the grid demand ​, the flywheel energy storage array has 100 flywheels, 5 of which are faulty and the remaining 95 are normal; among the 95 normal flywheels, 10% are aging flywheels ( Small), 90% is healthy flywheel ( Large), the rated output power of each flywheel is 1MW, SOC=81%.

[0154] Node-level failures , system-level status (Partial fault), the available output power of the faulty node (faulty flywheel) is cleared to zero, and the remaining nodes bear the power output.

[0155] At this time, the available power is MW, after allocation through ADMM, healthy flywheels take on more power (0.4 to 0.58 MW), and aging flywheels take on less power (0 to 0.4 MW).

[0156] The present invention also provides an electronic device, comprising a processor, a memory connected to the processor, and a communication module, wherein the electronic device is used to execute the state feedback control method for a flywheel energy storage array.

[0157] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the state feedback control method for a flywheel energy storage array.

[0158] In the embodiments disclosed in the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. The embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part, and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU), the above-mentioned functions defined in the method of the present application are performed. It should be noted that the computer-readable medium mentioned above in the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more wire segments, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this application, a computer-readable storage medium may be any tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a propagated data signal, either in baseband or as part of a carrier wave, embodying computer-readable program code. Such a propagated data signal may take various forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the foregoing. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, electrical wire, optical fiber cable, RF, etc., or any suitable combination thereof.

[0159] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of the systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or portion of code that contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from that marked in the accompanying drawings. For example, two boxes shown in succession can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, as well as combinations of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified functions or operations, or can be implemented using a combination of dedicated hardware and computer instructions.

[0160] Those skilled in the art should understand that the embodiments of the present invention described above and shown in the accompanying drawings are only examples and do not limit the present invention. The objectives of the present invention have been fully and effectively achieved. The functional and structural principles of the present invention have been demonstrated and explained in the embodiments. Without departing from the principles, the implementation methods of the present invention may be subject to any changes or modifications.

Claims

1. A state feedback control method for a flywheel energy storage array, characterized in that: The method comprises: Obtaining operating parameters of the flywheel energy storage array, classifying the obtained operating parameters based on the monitoring task, and using the classified parameters to determine the state of the flywheel energy storage array; Optimize the state information feedback process through dynamic feedback control method to enable the upper system to respond quickly to the state information; Based on status information feedback, the status of individual flywheel energy storage units in the flywheel energy storage array is managed and node controlled; Coordinated control of the overall state of the flywheel energy storage array based on grid demand and the state of individual flywheel energy storage units, including: Receive grid instructions and parse them to obtain frequency modulation signals, power adjustment amounts, and target output power; Get the real-time output power of the flywheel energy storage array , calculate the total power that needs to be adjusted ;in, Indicates the power adjustment amount; Get the operating parameters of each flywheel to form the node operating parameter vector ,in, Respectively represent The speed, temperature, vibration frequency and power of each flywheel; Dynamically allocate output power to each flywheel, that is, when the target output power is met while minimizing fault propagation and life loss, including: The available output power per flywheel is: ; in, Indicates the flywheel rated power, represents the SOC correction factor, Indicates the maximum output power of the battery. Indicates the power adjustment period; Assign priority weights based on flywheel health , prioritize the use of healthy flywheels; ;in, They respectively represent the number of charge and discharge times completed by the flywheel and the total number of designed charge and discharge times; While meeting grid demand, the load on each flywheel in the flywheel energy storage array is balanced to extend its service life. Specifically: Build the optimization model: ,in, represents the life protection weight; Indicates the number of working flywheels in the flywheel energy storage array; The alternating direction multiplier method ADMM is used to solve the optimization model and obtain the final distribution ; Will sent to the controller of each flywheel; Monitor the status of each flywheel, that is, the node-level status, and when the status changes, reset to zero and trigger power redistribution.

2. A state feedback control method for a flywheel energy storage array according to claim 1, characterized in that: The obtaining of operating parameters of the flywheel energy storage array, classifying the obtained operating parameters based on the monitoring task, and determining the state of the flywheel energy storage array using the classified parameters include: According to the monitoring task, the physical state parameters, electrical state parameters and system state parameters of each flywheel in the flywheel energy storage array are collected at the preset collection frequency, and the identification tag of the corresponding flywheel is added; The physical state parameters, electrical state parameters and system state parameters are pre-processed to form an original parameter set; Extract multiple parameters from the original parameter set to construct the state judgment input feature set ;in, They represent the operating state parameter set, the healthy state parameter set and the safe state parameter set respectively; The operating state parameter set includes speed, charge and discharge power, and SOC; the health state parameter set includes bearing temperature, vacuum degree, and vibration frequency; the safety state parameter set includes heating rate and vacuum leakage rate; Conduct node-level status judgment of a single flywheel energy storage unit; Perform system-level status judgment on the flywheel energy storage array.

3. A state feedback control method for a flywheel energy storage array according to claim 2, characterized in that: The node-level status determination of a single flywheel energy storage unit includes: Construct state classification rules, that is, judge the elements in the input feature set through logical combination of states, and define the operating state in combination with thresholds, including: The state of each flywheel in the flywheel energy storage array, that is, the node-level state ,in, represents the input power, Indicates the bearing temperature, Indicates the temperature rise rate of the bearing, Indicates bearing vibration energy; Indicates the speed fluctuation rate; if , judge that the flywheel is in normal charging state; if , it is judged that the flywheel is in the bearing overheating state; if , it is judged that the flywheel is in a rotor imbalance state.

4. A state feedback control method for a flywheel energy storage array according to claim 3, characterized in that: The system-level status determination of the flywheel energy storage array includes: Gather the operating parameters of all flywheels to generate a global characteristic parameter set ;in, Respectively represent the average SOC, maximum temperature value, number of faulty flywheels, and power imbalance; in, , represents the average input power; Indicates the number of flywheels; Indicates the Input power to the flywheel; System-level status ; if , judging that the flywheel energy storage array is in a normal state; if , determining that the flywheel energy storage array is in a local fault state; if , determining that the flywheel energy storage array is in an overload state; if , it is determined that the flywheel energy storage array is in an emergency shutdown state.

5. A state feedback control method for a flywheel energy storage array according to claim 4, characterized in that: The state information feedback process is optimized by the dynamic feedback control method so that the upper system can quickly respond to the state information, including: Prioritize node-level status and assign priority values, giving priority feedback to status with high priority values, including: Priority value for normal charging state ; Priority value for bearing overheat status ; Priority value for rotor imbalance status ;in, ; Dynamically adjust the state feedback frequency, that is, adjust the state feedback frequency according to the flywheel load and state change rate, including: Set dynamic feedback frequency ;in, They represent the basic feedback frequency, adjustment coefficient, feedback sensitivity coefficient, maximum allowable parameter change range and absolute value of parameter change respectively.

6. A state feedback control method for a flywheel energy storage array according to claim 5, characterized in that: The state information feedback process is optimized by the dynamic feedback control method so that the upper system can quickly respond to the state information, and further includes: Set up event triggering mechanisms to avoid invalid feedback, including: Set event trigger conditions ;in, Indicates the parameter value collected last time. represents the static threshold; Indicates the dynamic change rate threshold; Indicates the parameter value collected at the current moment; A fast response strategy for the upper system is constructed by using pre-caching and preloading, state machine jump prediction, and lightweight decision trees to achieve a fast response to flywheel status feedback.

7. A state feedback control method for a flywheel energy storage array according to claim 6, characterized in that: The method of using pre-caching and preloading, state machine jump prediction, and lightweight decision trees to build a high-level system rapid response strategy includes: Pre-store key data and model parameters, including: Define a fixed-size memory area locally and store data in a loop; Adopt the least recently used algorithm LRU to dynamically eliminate infrequently accessed data; Constructing a flywheel dynamics model and preloading the flywheel dynamics model into the CPU cache L1 or L2; Precompile the pre-trained decision tree model and state transition matrix and store them in the memory reserved area, including: Construct a Markov chain model, use the historical state statistical data obtained from the database to train the Markov chain model, and calculate the state transition probability; State transition probability ,in, Indicates the current state The next time and space becomes a state Statistics of Indicates status Statistics of Predict the next state ;in, ; According to the predicted next state, pre-load the preset control logic into the memory, wherein the control logic includes cooling, reducing the speed, and shutting down; A lightweight decision tree is constructed, and speed, bearing temperature, and vibration frequency are selected as split nodes. The split nodes are selected using the information gain maximization criterion. Limit the depth to 3 to prevent overfitting; Convert decision data into a bit mask lookup table and achieve fast response through FPGA; The management and node control of the state of a single flywheel energy storage unit in the flywheel energy storage array based on state information feedback includes: Get status feedback information of the flywheel; A single edge controller is deployed for each flywheel to control the flywheel system parameters based on status feedback information, specifically: Use PID controller to control the flywheel speed: Motor output torque ;in, Indicates PID gain; Indicates the target speed, Indicates the flywheel speed.

8. An electronic device comprising a processor, a memory connected to the processor, and a communication module, characterized in that: The electronic device is used to execute the state feedback control method for a flywheel energy storage array as described in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the state feedback control method for a flywheel energy storage array according to any one of claims 1 to 7.

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