Flywheel energy storage array coordination control method and system

Abstract

The invention relates to the technical field of energy dispatching, in particular to a flywheel energy storage array coordination control method and system, which are used for collecting flywheel rotating speed data, analyzing an energy release trend, evaluating response adaptive capacity, distributing power, optimizing voltage recovery and adjusting flywheel release configuration. According to the method, interval judgment, derivative calculation and frequency statistics are carried out on the trend state of the flywheel rotating speed sequence, abnormal behaviors in the energy release process can be recognized in time, and response errors caused by system misjudgment are avoided. A risk sensitive correction factor is applied to an individual with abnormal energy release, and an entropy weight method is fused for weight calculation, so that hierarchical scheduling optimization under the background of unbalanced adaptive capacity is realized. According to the multi-section proportional distribution strategy, fine power configuration is carried out according to the response capability of a flywheel, boundary-crossing values are eliminated through release boundary verification, and the stability and controllability of the power release process are enhanced.

Description

Technical Field

[0001] This invention relates to the field of energy dispatching technology, and in particular to a method and system for coordinated control of a flywheel energy storage array. Background Technology

[0002] The field of energy dispatch technology includes research on the coordinated operation, optimized control and resource allocation of various energy units in the power system, including the dispatch management of traditional power sources and new energy storage devices, especially in the context of grid load fluctuations and the increasing proportion of renewable energy access, to achieve the design and control implementation of strategies to balance energy supply and demand.

[0003] Among them, the flywheel energy storage array coordination control method refers to the control means designed for an array system composed of multiple flywheel energy storage devices to achieve their coordinated operation. It includes key control matters such as energy distribution, power response sequence, speed management and operation state switching of the flywheel group in parallel operation.

[0004] Existing technologies for scheduling flywheel energy storage arrays rely heavily on static parameter settings and unified control logic for individual flywheel states, lacking a dynamic identification mechanism for changes in behavioral characteristics during operation. This results in an inability to intervene effectively and promptly when speed abnormalities or release trends become unbalanced. For example, when some flywheels exhibit frequent fluctuations in release rate or slow speed changes, the system still includes them in the regular scheduling path, easily leading to power release instability. In terms of response capability assessment, average or fixed index comparison methods are commonly used, failing to reflect individual differences and actual operating performance. This causes some performance boundary individuals to be overburdened, accelerating performance degradation. Furthermore, voltage rebound is judged solely by instantaneous voltage values, ignoring the trajectory changes during voltage recovery, easily leading to missed voltage deviations and subsequent unreasonable scheduling. The lack of a power compensation mechanism means that the power gaps left by risky individuals after they exit scheduling are not properly allocated, affecting the overall power output balance and the response consistency of the array system. These shortcomings are even more pronounced in frequent charging and discharging in multiple scenarios and mixed multi-task operation, not only reducing system efficiency but also increasing maintenance and management costs. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and to propose a coordinated control method and system for flywheel energy storage arrays.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a flywheel energy storage array coordinated control method, comprising the following steps: S1: Collect the rotational speed sequence of each flywheel in the flywheel energy storage array, determine the range of flywheel energy release trend, and mark flywheels with abnormal energy release trends; S2: Based on the individual flywheels with abnormal energy release trends, the scheduling adaptability of all flywheels in the flywheel energy storage array is evaluated in a hierarchical manner, and the response adaptability information of all flywheels is output. S3: The release power of each flywheel is proportionally allocated to multiple segments based on the response and adaptability information of all flywheels, and the target release power of each segment is calculated. S4: Obtain voltage rebound records for a specified period, perform error analysis on voltage recovery deviation in conjunction with the segmented release target power, and mark individual flywheels with voltage recovery risk. S5: Based on the individual flywheel with voltage recovery risk and the corresponding segmented release target power, dynamically adjust the release configuration of the remaining flywheels and output the corrected coordinated release command in the flywheel energy storage array.

[0007] As a further aspect of the present invention, the individual flywheels with abnormal energy release trends are specifically flywheels within the trend identification interval, flywheels with excessive fluctuation frequency, and flywheels with abnormal derivative rate of change. The response adaptability information includes adaptability values, scheduling priority levels, and scheduling suppression status markers. The segmented release target power includes release power configuration values, release power grading intervals, and judgment results of allowable release upper limits. The individual flywheels with voltage recovery risk specifically refer to flywheels with excessive deviation errors, voltage recovery delays, and voltage rebound offsets. The coordinated release command includes release configuration correction values, release load rollback ratios, and power adjustment allocation results.

[0008] As a further aspect of the present invention, the step of obtaining the individual flywheel with abnormal energy release trend is specifically as follows: S111: Collect the rotational speed time series of each flywheel in the flywheel energy storage array, calculate the first and second derivatives of the rotational speed series at continuous time points, which are expressed as the rate of change of rotational speed and the acceleration of rotational speed, respectively, extract the distribution interval of extreme points in the rotational speed series, count the number of fluctuations and generate the rotational speed fluctuation frequency; S112: Calculate the moving average of the rotational speed change rate, determine whether the average is lower than the lower limit threshold of the set derivative change rate, and at the same time determine whether the rotational speed fluctuation frequency data is higher than the set upper limit threshold. If both conditions are met, it is confirmed that the abnormal trend state conditions are met, and trend state determination data is generated. S113: Call the trend status determination data to mark and classify each flywheel, and classify the flywheels that meet the trend abnormality conditions into the abnormality identification range to obtain individual flywheels with abnormal energy release trends.

[0009] As a further aspect of the present invention, the step of obtaining the response adaptability information of all flywheels specifically includes: S211: Obtain the release behavior data record of each flywheel in the flywheel energy storage array, extract the energy release duration and maximum release rate, and use the entropy weight method to calculate and normalize the information entropy of the numerical distribution of the two parameters on all flywheels in the array to generate scheduling capability parameter weight coefficients. S212: Based on the scheduling capability parameter weighting coefficient, the energy release duration and maximum release rate of each flywheel are weighted and calculated, and a risk-sensitive correction factor is applied to the flywheels with abnormal energy release trends to generate a list of response adaptability values. S213: Based on the response adaptability value list, perform adaptability grouping and state classification operations on all flywheels, including scheduling suppression state and priority release state, to obtain the response adaptability information of all flywheels.

[0010] As a further aspect of the present invention, the step of obtaining the segmented release target power specifically comprises: S311: Obtain the response adaptability value and corresponding maximum release rate of each flywheel from the response adaptability information of all flywheels, and construct a power adjustment factor; S312: Based on the power adjustment factor, construct a multi-segment release ratio range, combine the current release power of each flywheel, locate the adjustment range in the ratio range, and obtain segmented release power distribution data; S313: Based on the segmented release power distribution data, perform release boundary verification on the release configuration of each flywheel to confirm whether the configuration meets the set range, retain the power value that meets the set range, and obtain the segmented release target power.

[0011] As a further aspect of the present invention, the step of obtaining the voltage recovery risk flywheel individual specifically includes: S411: Obtain voltage rebound records that match the segmented release target power within a specified period, filter the voltage rise phase data formed under the same release conditions, and establish a target power voltage rebound sequence. S412: Based on the target power voltage rebound sequence and the voltage response trajectory under the current segmented release of target power, calculate the point offset and mean square error value of each sampling point on the same time axis of the two sets of data, and obtain the voltage recovery deviation error data. S413: Based on the voltage recovery deviation error data, determine whether the deviation exceeds the set recovery error threshold. If it does, mark the status of the flywheel, classify it into the risk identification range, and generate a voltage recovery risk flywheel individual.

[0012] As a further aspect of the present invention, the step of obtaining the modified coordinated release command in the flywheel energy storage array specifically includes: S511: Obtain the segmented release target power corresponding to the individual flywheel with voltage recovery risk, calculate the proportion of the target power in the total release power of all flywheels, and obtain the release load back-off ratio; S512: Based on the released load back-off ratio, the total released power to be compensated is distributed among the remaining unmarked flywheels according to the power adjustment factor to construct power compensation allocation data; S513: The power compensation allocation data is superimposed with the original release power to form an adjusted release configuration set, which is then integrated into an array-level scheduling output format to obtain the corrected coordinated release command in the flywheel energy storage array.

[0013] A flywheel energy storage array coordinated control system is provided, the flywheel energy storage array coordinated control system being used to execute the above-described flywheel energy storage array coordinated control method, the system comprising: The energy release monitoring module collects the rotational speed sequence of each flywheel in the flywheel energy storage array, performs interval judgment on the energy release trend of the flywheel, and marks individual flywheels with abnormal energy release trends. The scheduling adaptability assessment module combines the individual flywheels with abnormal energy release trends to perform a hierarchical assessment of the scheduling adaptability of all flywheels in the flywheel energy storage array, and outputs the response adaptability information of all flywheels. The power distribution module allocates the power of each flywheel in multiple segments based on the response and adaptability information of all flywheels, and calculates the target power for segmented release. The voltage recovery deviation analysis module acquires voltage rebound records for a specified period, and performs error analysis on the voltage recovery deviation in conjunction with the segmented release target power, marking individual flywheels with voltage recovery risk. The dynamic adjustment and coordination module dynamically adjusts the release configuration of the remaining flywheels based on the individual flywheels with voltage recovery risk and the corresponding segmented release target power, and outputs the corrected coordinated release command in the flywheel energy storage array.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by performing interval judgment, derivative calculation, and frequency statistics on the trend state of the flywheel speed sequence, abnormal behavior during energy release can be identified in a timely manner, avoiding response errors caused by system misjudgment. Applying risk-sensitive correction factors to individuals with abnormal energy release and integrating entropy weighting calculations enables hierarchical scheduling optimization under unbalanced adaptability. A multi-segment proportional allocation strategy performs fine-tuned power configuration based on the flywheel's response capability and eliminates out-of-bounds values ​​through release boundary checks, enhancing the stability and controllability of the power release process. In the voltage rebound stage, individuals with deviation trends are identified by comparing the error between the historical power response sequence and the current trajectory, accurately defining potentially risky flywheels and improving the reliability of voltage recovery. In the response adjustment stage, the release load allocation data is reconstructed based on the target power proportion, forming a dynamic adjustment mechanism that ensures the system maintains scheduling continuity and power output stability even when there are voltage deviations or flywheel performance fluctuations. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the workflow of the present invention; Figure 2 This is a flowchart of step S1 of the present invention; Figure 3 This is a flowchart of step S2 of the present invention; Figure 4 This is a flowchart of step S3 of the present invention; Figure 5 This is a flowchart of step S4 of the present invention; Figure 6 This is a flowchart of step S5 of the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0017] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0018] Please see Figure 1This invention provides a technical solution: a coordinated control method for a flywheel energy storage array, comprising the following steps: S1: Collect the rotational speed sequence of each flywheel in the flywheel energy storage array, determine the range of flywheel energy release trend, and mark flywheels with abnormal energy release trends; S2: Combine the individual flywheels with abnormal energy release trends to perform a hierarchical evaluation of the scheduling adaptability of all flywheels in the flywheel energy storage array, and output the response adaptability information of all flywheels; S3: The release power of each flywheel is proportionally allocated to multiple segments based on the response and adaptability information of all flywheels, and the target release power of each segment is calculated. S4: Obtain voltage rebound records for a specified period, combine them with the segmented release of target power to perform error analysis on voltage recovery deviation, and mark individual flywheels with voltage recovery risk. S5: Based on the individual flywheel with voltage recovery risk and the corresponding segmented release target power, dynamically adjust the release configuration of the remaining flywheels and output the corrected coordinated release command in the flywheel energy storage array; The flywheels with abnormal energy release trends are specifically flywheels within the trend identification range, flywheels with excessive fluctuation frequency, and flywheels with abnormal derivative rate of change. The response and adaptability information includes the adaptability value, scheduling priority level, and scheduling suppression status flag. The segmented release target power includes the release power configuration value, release power grading range, and the judgment result of the allowable release upper limit. The flywheels with voltage recovery risk specifically refer to flywheels with excessive deviation error, voltage recovery delay, and voltage rebound offset. The coordinated release command includes the release configuration correction value, release load back-off ratio, and power adjustment allocation result.

[0019] Please see Figure 2 The specific steps for obtaining an individual flywheel with an abnormal energy release trend are as follows: S111: Collect the rotational speed time series of each flywheel in the flywheel energy storage array, calculate the first and second derivatives of the rotational speed series at continuous time points, which are expressed as the rate of change of rotational speed and the acceleration of rotational speed, respectively, extract the distribution interval of extreme points in the rotational speed series, count the number of fluctuations and generate the rotational speed fluctuation frequency; When collecting the rotational speed time series of each flywheel in the flywheel energy storage array, the data sampling frequency and duration must be uniformly set. For example, sampling can be set to 5 times per second for 300 seconds, generating an ordered rotational speed array of length 1500. This array is used to extract the dynamic characteristics of energy release during flywheel operation. First, to identify the trend of rotational speed changes, the rotational speed sequence should be subjected to first-order differencing to calculate the rate of change of rotational speed between any given time point and its previous time point. The first-order differencing formula is as follows: ;in, Indicates the first The rotational speed value at each sampling point is expressed in revolutions per minute. It is the rotational speed value of its previous sampling point. This represents the rate of change of rotational speed between two adjacent sampling points. If the rotational speed of a flywheel at the 101st sampling point is... The rotational speed at the 100th point is The rate of change is This indicates that the flywheel speed decreased by 10 revolutions per minute during that period. Next, the first-order difference result is subjected to another difference operation to obtain the acceleration trend, that is, the magnitude of the change in the current rate of change compared to the previous rate of change. This process is the second-order difference for calculating the rotational speed, expressed by the formula: ;in, Indicates in The rotational speed values ​​at the two time points before the point. This represents the rotational acceleration at that point, in revolutions per minute (rpm). 2 This reflects whether the flywheel speed change is accelerating or slowing down. If , , ,but This indicates that the speed decrease trend remained stable during this period, without acceleration or deceleration. While obtaining the derivative data, it is also necessary to assess whether there are periodic disturbances in the flywheel speed. To do this, it is necessary to identify the maxima and minima from the original speed sequence, statistically analyze the distribution intervals between the extreme values, and calculate the number of extreme value pairs occurring per unit time. The speed fluctuation frequency is obtained by dividing the total number of extreme values ​​over the time period by the time length, and is defined as: ;in, The fluctuation frequency (Hz) The number of extreme value pairs. This corresponds to the time length (in seconds). For example, if 27 extreme value pairs are detected within a 300-second time period, the frequency is... This frequency value serves as an important input for subsequent trend anomaly detection, ultimately outputting the rotational speed fluctuation frequency.

[0020] S112: Calculate the moving average of the speed change rate, determine whether the average is lower than the lower limit threshold of the set derivative change rate, and at the same time determine whether the speed fluctuation frequency data is higher than the set upper limit threshold. If both conditions are met, it is confirmed that the abnormal trend condition is met, and trend state judgment data is generated. When analyzing the speed change rate sequence, the average speed change rate should be calculated using a sliding time window based on its time distribution to eliminate the interference of short-term noise on the overall trend identification. The time length of the sliding average can be set according to the field operation data. It is generally recommended to select no less than 10 sampling points as the sliding window length. The calculated average value represents the average speed change of the speed change within the current time period. To determine whether the trend is abnormal, a set of judgment criteria for identifying trend instability needs to be set, including a lower threshold for the speed change rate and an upper threshold for the fluctuation frequency. When the sliding average of the speed change rate of the flywheel in a certain period is continuously lower than the set lower threshold, and at the same time its fluctuation frequency exceeds the set upper frequency limit, it is considered that the current state of the flywheel has entered the abnormal range of energy release trend. This judgment is based on the superposition of stable speed decay and excessively dense fluctuation. Both conditions must be met simultaneously to trigger the trend abnormality judgment logic. The judgment result finally generates the trend state judgment data corresponding to each flywheel.

[0021] S113: Call the trend status judgment data to mark and classify each flywheel, and classify the flywheels that meet the trend abnormality conditions into the abnormality identification range to obtain individual flywheels with abnormal energy release trends. After determining the trend status, the results for each flywheel should be uniformly categorized and managed. Flywheels judged as abnormal should be grouped into independent categories, and an abnormality identifier list should be established. This categorization is based on the status markers in the determination results. If a flywheel's status marker is abnormal, its number should be registered in the abnormal flywheel list, and its abnormality occurrence time and status description fields should be recorded to form a structured data table to support filtering operations in the scheduling logic. Flywheels identified as being in an abnormal state will be restricted from participating in the initial power release during the scheduling phase, or set as low-priority release units. Therefore, after marking, this list should be pushed to the subsequent adaptive assessment and power configuration phases for reference. The final identifier information obtained is the individual flywheel with abnormal energy release trend.

[0022] Please see Figure 3 The specific steps for obtaining the response and adaptability information of all flywheels are as follows: S211: Obtain historical release behavior data of each flywheel in the flywheel energy storage array, extract the energy release duration and maximum release rate, and use the entropy weight method to calculate and normalize the information entropy of the numerical distribution of the two parameters on all flywheels in the array to generate scheduling capability parameter weight coefficients. When acquiring historical energy release behavior data for each flywheel in a flywheel energy storage array, two metrics should be collected: energy release duration and maximum release rate. The former represents the continuous output time of the flywheel during a single continuous release process, measured in seconds; the latter represents the maximum power release reached by the flywheel during that process, measured in kilowatts. Assume the array contains... The flywheels, numbered flywheel 1, flywheel 2, and flywheel 3, have the following two raw data points: Energy release duration (seconds): , , Maximum release rate (kW): , , .

[0023] The range normalization of each indicator is performed using the following formula: , in, Indicates the first Taiwan Flywheel in the Normalized values ​​under each indicator and They represent the first The minimum and maximum values ​​of this indicator among all flywheels.

[0024] After normalizing the above data, we get: , , , , , .

[0025] Calculate the first value of each indicator in the normalized data. The proportion of each sample in its corresponding column : ; Here The proportion of normalized values ​​reflects the relative position of each flywheel in a certain indicator, and the result is: , , , , , .

[0026] Calculate the information entropy of each indicator. Information entropy reflects the uncertainty of a certain indicator, and its calculation formula is: , ; in: : No. Information entropy of each indicator; The natural logarithm function, i.e., the function of natural logarithm. The logarithm to the base (Euler's number, approximately 2.718); The range of values ​​used to normalize information entropy is: .because and According to convention, Set to 0 to avoid undefined numerical fields.

[0027] Information entropy is calculated as follows: ; Similarly, (Due to data symmetry).

[0028] Calculate redundancy : ,but .

[0029] Calculate indicator weights : That is, the weights for both the duration of energy release and the maximum release rate are 0.5.

[0030] The final output is: Weight of energy release duration : Weight of the maximum release rate. The above values ​​constitute the weighting coefficients of the scheduling capability parameter in this section's results.

[0031] S212: The energy release duration and maximum release rate of each flywheel are weighted based on the scheduling capability parameter weight coefficient, and a risk-sensitive correction factor is applied to flywheels with abnormal energy release trends to generate a list of response adaptability values. Based on the scheduling capability parameter weighting coefficients, the normalized energy release duration and normalized maximum release rate of each flywheel should be weighted and calculated to form a response adaptability value. Taking flywheel 1 as an example, its normalized energy release duration is: The maximum release rate is According to the aforementioned weights , Adaptability value The calculation formula is: ; Substitution ; Similarly, the normalized data for flywheel 2 is ,but: ; The normalized data for flywheel 3 is ,but: ; The values ​​calculated above For flywheel The initial response adaptability score, of which This corresponds to three flywheels. Next, for the flywheels marked as having abnormal energy release trends in the previous stage, a risk-sensitive correction should be applied to their adaptability values. Let the correction factor be... This indicates that the scheduling priority of the abnormal flywheel is reduced by 15%. If flywheel 2 has been determined to have an abnormal trend, its adaptability value will be adjusted as follows: ; Flywheel 1 and flywheel 3 were not marked as abnormal, therefore their adaptability values ​​remain unchanged. , .

[0032] The final output is a structured list containing all flywheel numbers and their corresponding response capability values: flywheel 1: 0, flywheel 2: 0.425 (after anomaly correction), flywheel 3: 1. This structure is the response adaptability value list, which will serve as the input for subsequent scheduling classification, guiding the execution of power configuration and scheduling ranking logic. Each value is a comprehensive evaluation result based on historical operating performance and anomaly correction, reflecting the flywheel's scheduling adaptability in the current cycle.

[0033] S213: Based on the list of response adaptability values, perform adaptability grouping and state classification operations on all flywheels, including scheduling suppression state and priority release state, to obtain the response adaptability information of all flywheels. All flywheels undergo a unified adaptive capability grouping and state classification operation to construct a hierarchical structure for the scheduling phase. First, hierarchical boundary values ​​for adaptive capability values ​​need to be set to form clear classification criteria. In practice, three intervals can be set: when the adaptive capability value is less than or equal to 0.50, it is classified as a scheduling suppression state; when the adaptive capability value is greater than or equal to 0.70, it is classified as a priority release state; and values ​​in between are classified as normal release states. Based on this standard, each record in the adaptive capability value list is classified. For example, if flywheel 1's value is 0, it is obviously less than 0.50 and is marked as "suppressed"; flywheel 2's value is 0.425, which, although corrected, is still below the classification threshold and is also marked as "suppressed"; flywheel 3's value is 1, higher than 0.70, and should be marked as "priority". After completing the classification, a state label is assigned to each flywheel and mapped one-to-one with the flywheel number to establish a structured record format. This structure should include three fields: flywheel number, response adaptability value, and scheduling status identifier. These fields are summarized into a data list according to a unified standard and used as the basis for subsequent multi-stage power release configuration. At this point, the adaptability status of all flywheels has been clearly defined, constituting the final result of this stage, namely, the response adaptability information of all flywheels.

[0034] Please see Figure 4 The specific steps for obtaining the segmented release target power are as follows: S311: Obtain the response adaptability value and corresponding maximum release rate of each flywheel from the response adaptability information of all flywheels, and construct the power adjustment factor; When obtaining the response adaptability value and maximum release rate of each flywheel in the response adaptability information of all flywheels, the adaptability value obtained after the previous stage evaluation and the corresponding maximum release rate value from the historical operation record should be read from the structured data. The response adaptability value is a dimensionless standardized value ranging from 0 to 1, and the maximum release rate is in kilowatts. For example, three flywheels are numbered flywheel 1, flywheel 2, and flywheel 3, with corresponding response adaptability values ​​of... , , The maximum release rates are respectively , , To establish a unified scheduling basis, the two parameters should be integrated to construct a power adjustment factor. The formula for calculating the power adjustment factor is: ,in, : indicates the first The power regulation factor of the flywheel is expressed in kilowatts. : indicates the first The response adaptability value of the flywheel (unitless); : indicates the first The maximum release rate of the flywheel, measured in kilowatts; : Indicates the index of the flywheel in the array, for example Let's perform the calculation using the example data: , , The calculations above show that flywheel 3 has the highest regulation factor, reflecting its strongest overall release capability, while flywheel 1 has the lowest regulation factor, indicating its weakest ability to be used for regulation. This result constitutes the power regulation factor for each flywheel in the current scheduling cycle.

[0035] S312: Construct a multi-segment release ratio range based on the power adjustment factor, combine the current release power of each flywheel, locate the adjustment range in the ratio range, and obtain segmented release power distribution data; Based on the power adjustment factor, multiple release ratio ranges should be further constructed, and the adjustment range should be determined by combining the current release power of each flywheel, generating distribution data of segmented release power. First, according to the power adjustment factor of all flywheels... The values ​​are sorted and appropriate segmentation intervals are set to rationally allocate the released power according to the flywheel's adjustment factor strength. Assume the minimum adjustment factor is... The maximum value is It is divided into three segments: the low-regulation zone ( ), medium regulation zone ( ), high regulation zone ( According to the adjustment factors of flywheel 1, flywheel 2 and flywheel 3, flywheel 1 ( ) is placed in the low adjustment zone, flywheel 2 ( ) is placed in the middle adjustment zone, flywheel 3 ( This is then placed in the high-adjustment zone. Then, based on the current release power of each flywheel... Determine its adjustment range based on its position within the segmented interval. For example, if the current power output of flywheel 2 is... This value falls within the middle adjustment range, indicating that its power output needs to be adjusted appropriately. The power output of flywheel 3 is... If the released power is near the upper limit of the high adjustment range, a larger adjustment ratio may be required. Based on the above segmentation and adjustment, the segmented released power distribution data of each flywheel is calculated, and its corresponding release range and adjustment value are recorded.

[0036] S313: Based on the segmented release power distribution data, perform release boundary verification on the release configuration of each flywheel to confirm whether the configuration meets the set range, retain the power value that meets the set range, and obtain the segmented release target power; The release configuration of each flywheel is checked for release boundaries to ensure that its release power meets the set range limits. The target release power value of each flywheel cannot exceed its maximum allowable release rate or be lower than the minimum power guarantee value set by the system. Taking flywheel 2 as an example, its segmented release target is... If the maximum allowable power of the flywheel is The minimum guaranteed power is Then its current released power If the target falls within the designated range, it is considered a valid target; the segmented targets of flywheel 1 are... If the minimum guaranteed power is If the target configuration does not meet the lower limit requirement, it needs to be adjusted; the target for flywheel 3 is... If the maximum power is set to If the release target exceeds the upper limit, it also needs to be corrected. Through this series of boundary checks, the release power value of each flywheel that meets the scheduling requirements is finally determined, forming the final segmented release target power. This result provides effective data support for subsequent voltage stability and power optimization scheduling, ensuring the stable operation of the flywheel array and avoiding power overload or underpower situations.

[0037] Please see Figure 5 The specific steps for obtaining the voltage recovery risk flywheel individual are as follows: S411: Obtain voltage rebound records that match the segmented release target power within a specified period, filter the voltage rise phase data formed under the same release conditions, and establish a target power voltage rebound sequence. When acquiring voltage rebound records matching the segmented release target power within a specified period, it is first necessary to obtain the voltage rebound data of each flywheel in the flywheel array under the current power release conditions, ensuring that the selected data is the effective voltage rise phase data recorded under the corresponding release power state. Voltage rebound data reflects the process of voltage gradually recovering from a falling state after a change in flywheel release power. This phase data is crucial for analyzing voltage recovery capability and its stability. For each flywheel, it is first necessary to filter out the voltage rebound data segment matching the previously calculated segmented release target power, i.e., selecting the time period of voltage recovery after a change in release power. To ensure data validity, only data from the voltage rise phase is selected to avoid interference from the voltage fall phase in the calculation process. In this way, a voltage rebound sequence matching the target power can be established.

[0038] S412: Based on the target power voltage rebound sequence and the voltage response trajectory under the current segmented release of target power, calculate the point offset and mean square error value of each sampling point on the same time axis of the two sets of data, and obtain the voltage recovery deviation error data. Based on the target power voltage rebound sequence and the voltage response trajectory under the current segmented release of the target power, the point offset and mean square error value of each sampling point on the same time axis should be calculated for both sets of data. First, the point offset represents the difference between the target power voltage rebound sequence and the current flywheel voltage response trajectory at the same time point. The calculation formula is: ; in, Indicates the first Voltage offset at each time point For the first Voltage values ​​in the voltage rebound sequence at the target power at each time point. Let be the voltage value at the corresponding time point in the current flywheel voltage response trajectory. The mean square error (MSE) is calculated by squaring and summing the offsets of all sampling points, using the following formula: ; in, It is the total number of sampling points. For the first Voltage offset at each time point This represents the mean square error of the two sets of voltage data. Assume the target power voltage rebound sequence for flywheel 2 is... The voltage response trajectory is Then the offset sequence is The mean square error is: ; The obtained mean square error value This will be used as voltage recovery deviation error data.

[0039] S413: Determine whether the deviation exceeds the set recovery error threshold based on the voltage recovery deviation error data. If it does, mark the status of the flywheel, classify it into the risk identification range, and generate a voltage recovery risk flywheel individual. Based on the voltage recovery deviation error data, determine whether the error exceeds the set recovery error threshold. The recovery error threshold is typically set by system stability requirements and the actual application environment, representing the maximum allowable deviation during the voltage recovery process. The recovery error threshold is set as follows: That is, when the mean square error If this value is exceeded, it indicates a significant deviation in the voltage recovery process, which may affect the stable operation of the flywheel. If the value calculated in step S412... Exceeding the set threshold If the voltage recovery status of the flywheel is unstable, it needs to be marked as a "risk flywheel." This risk label will serve as an important basis for subsequent scheduling and control, indicating that the flywheel may require special power allocation or status adjustment. Through this process, individual flywheels with voltage recovery risks can be identified, marked as "risk," and subsequent control strategies can be adjusted.

[0040] Please see Figure 6 The specific steps for obtaining the corrected coordinated release command in the flywheel energy storage array are as follows: S511: Obtain the segmented release target power corresponding to the individual flywheel with voltage recovery risk, calculate the proportion of the target power in the total release power of all flywheels, and obtain the release load back-off ratio; When obtaining the segmented release target power corresponding to the individual flywheel with voltage recovery risk, the segmented release target power should be extracted from the flywheels marked as having voltage recovery risk in the previous steps. Next, the proportion of the target power of this flywheel in the total release power of all flywheels is calculated. Let the segmented release target powers of flywheel 1, flywheel 2, and flywheel 3 be respectively... , , Flywheel 2 is the flywheel with voltage recovery risk. First, calculate the total release power of all flywheels. : ; in, This represents the total power output of all flywheels, expressed in kilowatts. , ,and These represent the segmented target power release of flywheel 1, flywheel 2, and flywheel 3, respectively, in kilowatts.

[0041] Substituting the data, we get: .

[0042] Calculate the proportion of the target power released by flywheel 2 in the total released power: Load rollback ratio ; in, This indicates the segmented release target power of flywheel 2, in kilowatts; This represents the total output power of all flywheels, expressed in kilowatts.

[0043] Substituting the data, we get: This ratio reflects the share of the total released power by flywheel 2 and is used for subsequent power distribution and adjustment.

[0044] S512: Based on the load return ratio, the total amount of released power to be compensated is distributed among the remaining unmarked flywheels according to the power adjustment factor to construct power compensation allocation data; Based on the load return ratio, the total release power to be compensated is distributed among the remaining flywheels not marked as having voltage recovery risk. First, the total power to be compensated is calculated; this value is the release target power of flywheel 2, i.e. Next, the remaining power load will be distributed according to the power regulation factors of the flywheels not marked as voltage recovery risk. The regulation factors for flywheels 1 and 3 are respectively... and The sum of its adjustment factors is: ,in, and These represent the power regulation factors for flywheel 1 and flywheel 3, respectively, in kilowatts; This represents the total adjustment factor for flywheel 1 and flywheel 3, in kilowatts. Substituting the data, we get: Then, the compensation power will be adjusted according to the adjustment factor ratio. The compensation power is allocated to flywheel 1 and flywheel 3. The compensation power allocated to flywheel 1 is: The compensation power allocated to flywheel 3 is: Through this allocation operation, the compensated power is rationally distributed according to the flywheel's adjustment capability, forming power compensation allocation data.

[0045] S513: The power compensation allocation data is superimposed with the original release power to form an adjusted release configuration set, which is then integrated into an array-level scheduling output format to obtain the corrected coordinated release command in the flywheel energy storage array. The power compensation allocation data is superimposed on the original release power to form an adjusted release configuration set. First, based on the aforementioned calculations, the compensation powers for flywheel 1 and flywheel 3 are respectively... and The original release power of flywheel 1 and flywheel 3 are respectively and The adjusted release power is as follows: ; ; Flywheel 2 is marked as a voltage recovery risk flywheel, and its release power is set to 0, therefore .

[0046] The final adjusted power release set consists of the release configurations of flywheel 1, flywheel 2, and flywheel 3, as follows: , , These adjusted release configuration data will be integrated into an array-level scheduling output format, providing the system with the final coordinated release command. This command can be used for subsequent voltage stability prediction and power scheduling to ensure stable system operation and avoid the negative impact of voltage recovery risks on the flywheel. The final corrected coordinated release command will ensure that the flywheel energy storage array meets stability requirements and performs reasonable power allocation during scheduling.

[0047] A flywheel energy storage array coordinated control system is provided, which is used to execute the above-mentioned flywheel energy storage array coordinated control method. The system includes: The energy release monitoring module collects the rotational speed sequence of each flywheel in the flywheel energy storage array, performs interval judgment on the energy release trend of the flywheel, and marks individual flywheels with abnormal energy release trends. The scheduling adaptability assessment module combines individual flywheels with abnormal energy release trends to perform a hierarchical assessment of the scheduling adaptability of all flywheels in the flywheel energy storage array, and outputs the response adaptability information of all flywheels. The power distribution module allocates the power of each flywheel in multiple segments based on the response and adaptability information of all flywheels, and calculates the target power for segmented release. The voltage recovery deviation analysis module acquires voltage rebound records for a specified period, combines them with the segmented release of target power to perform error analysis on voltage recovery deviation, and marks individual flywheels with voltage recovery risk. The dynamic adjustment and coordination module dynamically adjusts the release configuration of the remaining flywheels based on the individual flywheels with voltage recovery risk and their corresponding segmented release target power, and outputs the corrected coordinated release command in the flywheel energy storage array.

[0048] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A flywheel energy storage array coordinated control method, characterized in that, The method comprises the following steps: S1: Collecting the rotating speed sequence of each flywheel in the flywheel energy storage array, judging the interval of the energy release trend state, and marking the energy release trend abnormal flywheel individual; S2: Combining the energy release trend abnormal flywheel individual to evaluate the hierarchical scheduling adaptability of all flywheels in the flywheel energy storage array, and output the response adaptability information of all flywheels; S3: Through the response adaptability information of all flywheels, the release power of each flywheel is proportionally distributed in multiple segments, and the segmented release target power is calculated; S4: Obtain the voltage rebound record in a specified period, combine the segmented release target power to analyze the error of voltage recovery deviation, and mark the voltage recovery risk flywheel individual; S5: Based on the voltage recovery risk flywheel individual and the corresponding segmented release target power, the release configuration of the remaining flywheels is dynamically adjusted, and the corrected coordination release instruction in the flywheel energy storage array is output.

2. The flywheel energy storage array coordinated control method of claim 1, wherein, The energy release trend abnormal flywheel individual is specifically a trend recognition interval flywheel, a fluctuation frequency over-limit flywheel, and a derivative change rate abnormal flywheel. The response adaptability information includes adaptability value, scheduling priority level, and scheduling inhibition state mark. The segmented release target power includes release power configuration value, release power classification interval, and allowed release upper limit judgment result. The voltage recovery risk flywheel individual specifically refers to a deviation error over-limit flywheel, a voltage recovery delay flywheel, and a voltage rebound offset flywheel. The coordination release instruction includes release configuration correction value, release load rollback ratio, and power adjustment distribution result.

3. The flywheel energy storage array coordinated control method of claim 2, wherein, The acquisition step of the energy release trend abnormal flywheel individual is specifically: S111: Collect the rotating speed time sequence of each flywheel in the flywheel energy storage array, calculate the first derivative and the second derivative of the rotating speed sequence at consecutive time points, respectively represented as rotating speed change rate and rotating speed acceleration, extract the distribution interval of the extreme points in the rotating speed sequence, count the fluctuation times and generate the rotating speed fluctuation frequency; S112: Calculate the sliding mean value of the rotating speed change rate, judge whether the mean value is lower than the lower limit threshold of the set derivative change rate, and at the same time, judge whether the rotating speed fluctuation frequency data is higher than the set upper limit threshold. If both conditions are met, it is confirmed that the trend state abnormal condition is met, and the trend state judgment data is generated; S113: Call the trend state judgment data to mark and classify each flywheel, and classify the flywheels meeting the trend abnormal condition into the abnormal identification range to obtain the energy release trend abnormal flywheel individual.

4. The flywheel energy storage array coordinated control method of claim 3, wherein, The acquisition step of the response adaptability information of all flywheels is specifically: S211: Obtain the release behavior data record of each flywheel in the flywheel energy storage array, extract the energy release duration and the maximum release rate, and use the entropy weight method to calculate and normalize the numerical distribution of the two parameters on all flywheels in the array to generate the scheduling capability parameter weight coefficient; S212: Based on the scheduling capability parameter weight coefficient, the energy release duration and the maximum release rate of each flywheel are weighted calculated, and the risk sensitive correction factor is applied to the energy release trend abnormal flywheel individual to generate the response adaptability value list; S213: Grouping and classifying the response adaptability of all flywheels according to the response adaptability value list, including scheduling inhibition state and priority release state, to obtain the response adaptability information of all flywheels.

5. The flywheel energy storage array coordinated control method of claim 4, wherein, The step of obtaining the segmented release target power is specifically: S311: Obtain the response adaptability value and corresponding maximum release rate of each flywheel in the response adaptability information of all flywheels, and construct a power adjustment factor; S312: Based on the power adjustment factor, construct a multi-segment release proportion interval, locate the adjustment range in the proportion interval combined with the current release power of each flywheel, and obtain the segmented release power distribution data; S313: According to the segmented release power distribution data, release boundary check is performed on the release configuration of each flywheel to confirm whether the configuration meets the set range, and the power value meeting the set range is retained to obtain the segmented release target power.

6. The flywheel energy storage array coordinated control method of claim 5, wherein, The step of obtaining the voltage recovery risk flywheel individual is specifically: S411: Obtain the voltage rebound record matched with the segmented release target power in a specified period, filter the voltage rising stage data formed under the same release condition, and establish a target power voltage rebound sequence; S412: Based on the target power voltage rebound sequence and the voltage response trajectory under the current segmented release target power, calculate the point offset and mean square error value of each sampling point on the unified time axis, and obtain the voltage recovery deviation error data; S413: According to the voltage recovery deviation error data, it is judged whether the deviation exceeds the set recovery error threshold, if yes, the state of the flywheel is marked and classified into the risk identification range to generate a voltage recovery risk flywheel individual.

7. The flywheel energy storage array coordinated control method of claim 6, wherein, The step of obtaining the corrected coordinated release instruction in the flywheel energy storage array is specifically: S511: Obtain the segmented release target power corresponding to the voltage recovery risk flywheel individual, calculate the proportion of the target power in the total release power of all flywheels, and obtain the release load rollback proportion; S512: Based on the release load rollback proportion, the total amount of release power that needs to be compensated is allocated to the remaining unmarked flywheels according to the power adjustment factor to construct power compensation allocation data; S513: Superimpose the power compensation allocation data and the original release power to form an adjusted release configuration set, integrate it into an array-level scheduling output format, and obtain the corrected coordinated release instruction in the flywheel energy storage array.

8. A flywheel energy storage array coordinated control system, characterized by, The flywheel energy storage array coordinated control method according to any one of claims 1-7, the system comprises: The energy release monitoring module collects the speed sequence of each flywheel in the flywheel energy storage array, judges the interval of the flywheel energy release trend state, and marks the energy release trend abnormal flywheel individual; The scheduling adaptability evaluation module evaluates the scheduling adaptability of all flywheels in the flywheel energy storage array in combination with the energy release trend abnormal flywheel individual, and outputs the response adaptability information of all flywheels; The release power distribution module performs multi-segment proportion distribution on the release power of each flywheel through the response adaptability information of all flywheels, and calculates the segmented release target power; The voltage recovery deviation analysis module obtains voltage recovery record of a specified period, conducts error analysis on voltage recovery deviation in combination with the segmented release target power, and marks a voltage recovery risk flywheel individual; The dynamic adjustment and coordination module dynamically adjusts the release configuration of the remaining flywheels based on the voltage recovery risk flywheel individual and the corresponding segmented release target power, and outputs a corrected coordinated release instruction in the flywheel energy storage array.

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