Data center transient voltage governance flywheel energy storage system

Abstract

The present application relates to the technical field of voltage management, in particular to a data center transient voltage management flywheel energy storage system, the system comprises a disturbance time recognition module, a load mutation determination module, a capacity correction distribution module, a scheduling sequence adjustment module and a state change tracking module, based on the voltage change rate and amplitude of the data center, the voltage curve of the flywheel energy storage monitoring node in each period is analyzed. The present application, through multi-dimensional data synchronous capture of the coupling relationship between voltage disturbance and load change, real-time mining of the influence of server running dynamics on flywheel energy state, adjustment of energy distribution structure combined with friction loss trend, dynamic optimization of flywheel priority through load proportional fluctuation and main loop state, realizes node energy fluctuation rapid screening and change tracking, refines the response strategy of flywheel energy storage system to short-time voltage disturbance, improves the pertinence and flexibility of energy storage scheduling under data center operation scene, and enhances the stability level and risk protection ability of the overall power supply system.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of voltage management, in particular to a flywheel energy storage system for transient voltage management of a data center. BACKGROUND

[0002] The field of voltage management involves monitoring, adjusting and controlling the voltage level in a power system, aiming to ensure the voltage stability and quality of power supply. This technical field mainly includes detecting and analyzing voltage fluctuation transient disturbances in power networks, and taking measures such as energy storage compensation and reactive power adjustment to ensure the reliable operation of power supply systems in various critical power consumption scenarios. The flywheel energy storage system for transient voltage management of a data center refers to the use of high-speed rotating flywheels to store energy in the form of mechanical energy when the voltage changes temporarily due to load fluctuations or power grid disturbances in the operation of a data center. When a voltage transient occurs, the energy is quickly released to achieve immediate compensation of the voltage, realizing fast bidirectional conversion of energy and injection of electrical energy, and completing the management of transient voltage fluctuations in the data center.

[0003] In the existing technology, it is difficult to distinguish the linkage effect of multi-node load response and energy state in the voltage fluctuation discrimination process. A single parameter or static strategy is used, which is difficult to adapt to variable working conditions. When large-scale load switching or concurrent energy supply occurs, some energy storage units are not dispatched in time or energy regulation is delayed, which may cause local energy supply shortage and equipment state deviation, affecting the reliability of short-time voltage management and limiting the dynamic adaptation range of the data center power supply system. SUMMARY

[0004] The purpose of the present application is to solve the problems existing in the prior art and to provide a flywheel energy storage system for transient voltage management of a data center.

[0005] In order to achieve the above-mentioned purpose, the application adopts the following technical scheme: a flywheel energy storage system for transient voltage management of a data center, the system comprising:

[0006] The disturbance time recognition module analyzes the voltage curve of the flywheel energy storage monitoring node at each time period based on the voltage change rate and amplitude of the data center, compares the synchronicity of the rate and amplitude change, judges the correlation between the fluctuation time and the operation state of the flywheel energy storage system, and obtains the time sequence characteristics of the fluctuation event;

[0007] The load mutation determination module determines the flywheel energy storage operation change in the server cluster log according to the time sequence characteristics of the fluctuation event, analyzes the instantaneous power change, compares the load switching rate and the number of concurrent energy supply nodes before and after the disturbance, identifies the key interval, and obtains the key interval of the load disturbance;

[0008] The capacity correction distribution module compares the current rotating speed of the flywheel with the mechanical friction rate trend based on the load disturbance key interval, judges the rotating speed and friction coordination between the motorized bearing and the energy, adjusts the available energy distribution, calculates the capacity change, and obtains the energy storage distribution correction feature.

[0009] The scheduling sequence adjustment module compares the main loop total operating power with the flywheel data based on the energy storage distribution correction feature, analyzes the server area load proportion change caused by the voltage offset, judges the influence of the parameter change on the scheduling sequence, and obtains the energy storage priority ranking index.

[0010] The application improves that the fluctuation event timing feature includes event occurrence time, fluctuation distribution feature and association mark, the load disturbance key interval includes interval time information, load disturbance type and disturbance event identification, the energy storage distribution correction feature includes corrected capacity distribution, energy storage dynamic coefficient and energy distribution structure, and the energy storage priority ranking index includes ranking sequence, priority number and distribution weight.

[0011] The application improves that the disturbance time recognition module includes:

[0012] The rate fluctuation recognition submodule analyzes the voltage curve recorded by the monitoring node based on the data center voltage change rate and amplitude, judges the mutation of the voltage change rate in the continuous time period, screens the concentrated time period of the fluctuation occurrence in combination with the node distribution characteristics, aggregates the associated change interval, and obtains the rate fluctuation interval distribution.

[0013] The amplitude offset recognition submodule calls the rate fluctuation interval distribution, analyzes the voltage data of each node in the corresponding time period, compares the difference between the data and the rated voltage, screens the time slice with the key voltage fluctuation duration and amplitude change, and obtains the amplitude offset section parameter.

[0014] The fluctuation feature extraction submodule analyzes the overlapping time slice according to the amplitude offset section parameter, judges the relevance of the time slice and the flywheel energy storage system start-stop time, identifies the associated fluctuation event, and obtains the fluctuation event timing feature.

[0015] The application improves that the load mutation determination module includes:

[0016] The energy supply rate extraction submodule extracts the instantaneous energy supply power before and after the disturbance according to the fluctuation event timing feature, and compares the instantaneous energy supply power and the load switching rate in the same time period based on the server cluster log and the voltage change rate data collected by the flywheel energy storage monitoring node, and obtains the energy supply change rate feature.

[0017] The node fluctuation quantification submodule monitors and calculates the fluctuation of the number of energy supply nodes in the difference disturbance stage based on the energy supply change rate feature, identifies the key time period of parameter change, and obtains the load disturbance key interval.

[0018] The capacity correction distribution module comprises:

[0019] The coordination gradient analysis submodule analyzes the synchronization of the flywheel speed change and the mechanical friction rate based on the load disturbance key interval, compares the change gradients of the two in each period, judges whether the fluctuations of the two show a coordination trend, and calculates the fluctuation coordination degree of the difference section to obtain the coordination gradient amplitude.

[0020] The energy distribution adjustment submodule analyzes the cooperation of the flywheel energy storage unit in energy release according to the coordination gradient amplitude, compares the balance relationship between energy allocation and dynamic power output among each energy supply node, adjusts the energy output order, and obtains the energy distribution structure information.

[0021] The energy storage distribution correction submodule calls the energy distribution structure information, analyzes the difference between the current speed and the upper limit speed of each flywheel, and combines the moment of inertia, friction coefficient and power release difference to obtain the energy storage distribution correction feature.

[0022] The scheduling order adjustment module comprises:

[0023] The main loop comparison submodule analyzes the synchronous change of the total operating power curve of the power distribution main loop and the output power curve of the flywheel energy storage system based on the energy storage distribution correction feature, judges the synchronous offset of the power curve in the monitoring period, selects the period with key synchronization characteristics, and obtains the power offset period.

[0024] The load proportion analysis submodule compares the energy supply distribution of the flywheel energy storage system and the current load state of each server area based on the power offset period, calculates the mean square deviation of the power change rate of each server area, identifies the number of server areas with key change rate amplitude, and obtains the load fluctuation normalization.

[0025] The scheduling order generation submodule judges the energy output efficiency and the proportion of residual energy of the flywheel energy storage device according to the load fluctuation normalization, calculates the difference of the scheduling order in the target period, adjusts the scheduling priority, and obtains the energy storage priority ranking index.

[0026] The system further comprises:

[0027] The state change tracking module analyzes the first item flywheel number change according to the energy storage priority ranking index, compares the residual energy change amplitude in the continuous period, judges the energy change stability, identifies the key number, marks as a state jump object, updates the data list, and obtains state jump tracking data.

[0028] The state jump tracking data includes a jump flag, number information, and a change history record.

[0029] The state change tracking module includes:

[0030] The energy fluctuation analysis submodule analyzes the residual available energy change of the flywheel number in the continuous period based on the energy storage priority ranking index, compares the energy fluctuation amplitude between each monitoring period, judges whether the change has an abnormal deviation, and generates a period energy fluctuation amplitude.

[0031] The stability discrimination submodule calls the period energy fluctuation amplitude, judges the fluctuation persistence in the time sequence, analyzes whether there is regular fluctuation or sudden change in the energy change process, identifies the continuity feature of the energy change, and obtains the energy response stable trend.

[0032] The number jump screening submodule analyzes the fluctuation continuity reflected by the energy response stable trend, screens the data sequence with prominent changes in the flywheel number, judges whether the fluctuation feature conforms to the state jump feature, and synchronously updates to the data list to obtain the state jump tracking data.

[0033] Compared with the prior art, the advantages and positive effects of the present application are:

[0034] In the present application, the coupling relationship between voltage disturbance and load change is captured through multi-dimensional data synchronization, the influence of server running dynamics on flywheel energy state is mined in real time, the energy distribution structure is adjusted in combination with the friction loss trend, the flywheel priority is optimized through load proportional fluctuation and main loop state, the node energy fluctuation is quickly screened and changed, the response strategy of the flywheel energy storage system to short-time voltage disturbance is refined, the pertinence and flexibility of energy storage scheduling under data center running scenarios are improved, and the stability level and risk protection capability of the overall power supply system are enhanced. BRIEF DESCRIPTION OF DRAWINGS

[0035] Figure 1 The system flowchart of the present application;

[0036] Figure 2 The flowchart of the disturbance time identification module in the present application;

[0037] Figure 3 The flowchart of the load mutation determination module in the present application;

[0038] Figure 4 Flow chart for the capacity correction distribution module in the present application;

[0039] Figure 5 Flow chart for the scheduling sequence adjustment module in the present application;

[0040] Figure 6 Flow chart for the state change tracking module in the present application. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0042] In the description of the present application, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and therefore cannot be understood as indicating or implying that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, in the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0043] EMBODIMENT

[0044] Please refer to Figure 1 The present application provides a technical scheme: a data center transient voltage management flywheel energy storage system comprises:

[0045] The disturbance time identification module analyzes the voltage curve of the flywheel energy storage monitoring node in the different time periods based on the voltage change rate and amplitude of the data center, compares whether the rate change time and the amplitude offset time appear at the same time, judges the relevance of each fluctuation time and the flywheel energy storage system operation state, and summarizes the fluctuation event information to obtain the fluctuation event timing characteristics;

[0046] The load mutation determination module judges the operation change of the flywheel energy storage in the server cluster log corresponding to the time period according to the fluctuation event timing characteristics, analyzes the variation process of the instantaneous power supply power, compares the load switching rate and the change of the number of concurrent power supply nodes before and after the disturbance, identifies the key time period highlighted by each parameter change, and obtains the load disturbance key interval;

[0047] The capacity correction distribution module compares the change trend of the current speed of the flywheel and the mechanical friction rate based on the load disturbance key interval, judges the speed and friction coordination between the motorized bearing and the energy, adjusts the available energy distribution of the flywheel, and calculates the capacity change parameter to obtain the energy storage distribution correction feature;

[0048] The dispatching sequence adjustment module compares the total operating power of the power distribution main circuit with the flywheel data based on the energy storage allocation correction feature, analyzes the load proportion change of the server area caused by voltage transient deviation, judges the influence of parameter changes in the continuous period on the dispatching sequence of the flywheel energy storage system, adjusts the dispatching sequence, and obtains an energy storage priority ranking index;

[0049] The state change tracking module analyzes the change of the flywheel number corresponding to the first item in the ranking according to the energy storage priority ranking index, compares the change amplitude of the residual available energy of the number in the continuous period, judges the stability in the energy parameter change process, identifies the number that changes critically as a state jump object, and synchronously updates to the data list to obtain state jump tracking data.

[0050] The fluctuation event timing feature includes the event occurrence time, fluctuation distribution feature, and association marker, the load disturbance key interval includes interval time information, load disturbance type, and disturbance event identifier, the energy storage allocation correction feature includes the corrected capacity distribution, energy storage dynamic coefficient, and energy allocation structure, the energy storage priority ranking index includes the ranking sequence, priority number, and allocation weight, and the state jump tracking data includes the jump flag, number information, and change history record.

[0051] In module 1, the monitoring node refers to a voltage collection point installed on the flywheel energy storage system or the busbar connected thereto, and the node is used for judging whether the system has abnormal voltage change by collecting real-time voltage data; the voltage curve refers to the record of the voltage collected by each monitoring node within a period of time, which can be used to observe the fluctuation and trend of the voltage; the rate change time refers to the specific time when the voltage change rate in the voltage curve fluctuates obviously, such as the time when the voltage suddenly rises or falls; the amplitude deviation time refers to the time when the voltage value in the voltage curve deviates from the rated value, which represents the abnormal fluctuation of the voltage; the fluctuation time generally refers to the set of all times corresponding to the rate change or amplitude deviation, which is used for subsequent disturbance event judgment.

[0052] In module 2, the change process of the instantaneous power supply refers to the change of the power output or compensated by each node (parallel power supply point) of the flywheel energy storage system within a unit of time, which reflects the response ability of the instantaneous load change; the load switching rate refers to the frequency of the load (such as servers, air conditioners, etc.) switching on or off in the data center, which affects the overall power fluctuation; the concurrent energy supply node refers to the number of flywheel energy storage units or branches actually participating in power supply (energy storage discharge) at the same time, which reflects the concurrent energy supply capability of the system.

[0053] In module 3, the trend of change refers to the change direction and amplitude of the flywheel device in a period of time, the speed or the mechanical friction rate, which is an important basis for judging the energy storage state; the electric bearing and the energy electric bearing: the bearing system that supports the high-speed rotation of the flywheel and tries to reduce the friction loss, energy: here refers to the kinetic energy stored by the flywheel in a rotating manner, and the so-called "between the electric bearing and the energy" actually refers to the corresponding relationship between the operation condition of the flywheel (bearing friction condition) and the kinetic energy that can be stored and released by the flywheel; the speed and friction coordination refers to whether the current speed of the flywheel matches the bearing friction condition. If the friction is too large but the speed is not reduced, there is an abnormality. Normally, an increase in friction will cause a decrease in speed, and the two should change synchronously.

[0054] In module 4, the load proportion change of the area refers to the change of the power load proportion of each power distribution area of the data center with factors such as voltage disturbance and equipment switching, which is an important data affecting the scheduling and distribution of flywheel energy storage; the influence of scheduling sequence refers to the influence of changes in multiple parameters (such as energy storage capacity, load proportion, voltage change, etc.) on the ordering weight of the priority scheduling (i.e. which flywheel is preferred to participate in compensation) of the flywheel energy storage system.

[0055] In module 5, the change of the flywheel number refers to the change of the operating state, energy state and other parameters of a specific flywheel number in the process of scheduling and energy release; the change amplitude of available energy refers to the difference between the energy that can be released by a flywheel device in two monitoring periods, which is used to determine the energy storage health or the degree of change; the state jump object refers to the flywheel number whose operating state has changed suddenly, which needs to be tracked for its behavior and state data.

[0056] Please refer to Figure 2 , the disturbance time recognition module includes:

[0057] The rate fluctuation recognition submodule analyzes the voltage curve recorded by the monitoring node based on the voltage change rate and amplitude of the data center, judges the mutation of the voltage change rate in the continuous period, combines the node distribution characteristics, selects the concentrated time period of the fluctuation, and obtains the rate fluctuation interval distribution by summarizing the associated change interval.

[0058] The voltage time series is collected from the monitoring nodes installed at the flywheel energy storage system access point or distributed on the key power bus, the sampling period is usually set to 10 milliseconds, then the instantaneous change rate of voltage is obtained by traversing the continuous voltage data of each node and sequentially performing difference division on the voltage values of each two adjacent time points, and in all results, whether there is a rate mutation greater than the set reference value is compared, the reference value can be set to the value ranked in the top 5% in the rate data in the past month, for example, set to 5 volts per second, if the current data rate is greater than the reference value, it is determined as a mutation point, then a set of mutation time points is formed independently at each node, and a sliding time window statistical analysis method is used, for example, each 0.2 seconds is a window, and whether the number of mutation points in the window exceeds 3 is counted, if it exceeds, it is marked as a concentrated fluctuation time period, and then the fluctuation time periods in all nodes are compared horizontally, if the interval between adjacent fluctuation time periods is less than 0.1 seconds, they are merged into a longer fluctuation interval, finally the concentrated mutation time period is collected to form a set of time period of rate fluctuation interval, for example, at 12:01:34 noon, 5 nodes frequently appear rate mutation in the same second, concentrated in the same time window, the window is identified as a rate fluctuation interval distribution result.

[0059] The amplitude offset identification submodule calls the rate fluctuation interval distribution, analyzes the voltage data of each node in the corresponding time period, compares the difference between the data and the rated voltage, selects the time segment with sustained voltage fluctuation and critical amplitude change, and obtains the amplitude offset section parameter;

[0060] The time range of the previously obtained rate fluctuation interval is called, the original voltage data of all monitoring nodes in the time period is obtained, and the difference between the data and the standard voltage value set under normal working conditions is calculated to obtain the offset amplitude at each time point, then the average value of all offset values in each time period is taken, and compared with the preset amplitude reference value, the amplitude reference value can be set to about 10 volts according to the offset distribution in the historical data, if the average offset value of the current time period exceeds the reference value, and the offset state exists for more than 0.15 seconds, that is, a plurality of data points are in the offset state and cover at least 150 milliseconds, it is judged as an effective segment of voltage amplitude abnormal fluctuation, then all segments meeting the conditions are recorded according to the start and end time, the maximum offset value, the number of nodes involved, etc. Form a set of amplitude offset section parameters, for example, in the time period from 12:01:34 to 12:01:34.29 at noon, the voltage of 5 nodes is 12 volts higher than the rated value, and this high state maintains more than 0.17 seconds, so the time period is selected as the amplitude offset section.

[0061] The fluctuation feature extraction submodule analyzes the overlapping time segments according to the amplitude excursion section parameters, judges the relevance of the time segments to the flywheel energy storage system start-stop time, identifies the associated fluctuation events, and obtains the fluctuation event timing characteristics;

[0062] The start and end time information of the section is extracted, then the operation record of the flywheel energy storage system is accessed, the time points of flywheel start and stop recorded in all records are found, whether each amplitude excursion section is close to the flywheel start-stop time is compared, the close standard is that the time difference is not more than 0.1 second, if the condition is met, it is considered that the fluctuation of this section is associated with the operation state of the flywheel, then the overlapping of multiple associated time segments is checked, if they overlap each other for more than 0.05 seconds, they are merged into a longer event time segment, and the corresponding flywheel number and voltage fluctuation are recorded, finally the start point, end point, duration, flywheel number involved and voltage excursion degree of the time segment are output as the timing characteristics of the fluctuation event, for example, if flywheel No. 12 is started at 12:01:34.20, and a voltage fluctuation with an excursion value of 13 volts occurs from 12:01:34.12 to 12:01:34.29, then this fluctuation event is recorded as being associated with the start of flywheel No. 12, and the time segment and characteristic parameters are constructed into the fluctuation event timing characteristic information.

[0063] Please refer to Figure 3 The load mutation determination module includes:

[0064] The energy supply rate extraction submodule extracts the instantaneous energy supply power of each period before and after the disturbance according to the fluctuation event timing characteristics, and compares the instantaneous energy supply power and the load switching rate in the same period according to the voltage change rate data collected by the server cluster log and the flywheel energy storage monitoring node, to obtain the energy supply change rate characteristics.

[0065] The start and end time of the fluctuation event, the associated flywheel number and its trigger type are determined, the voltage change rate data recorded by the flywheel energy storage monitoring node is read as an analysis window with the time segment as the analysis window, the server cluster operation log matching the time segment is read, the load state record and power supply request record are extracted, and then a certain observation time window is set before and after the fluctuation event, for example, each time window length is set to 1 second, the instantaneous power output by the flywheel energy storage system to the server cluster power supply node in the two windows is calculated, the power value is obtained by multiplying the output voltage and current data in the energy storage discharge branch, for example, the flywheel F-07 outputs 220 volts and 8 amperes in 12:02:10.00-12:02:11.00, then the instantaneous power supply power is 1760 watts, the power at each time point is collected to form a time sequence, and the data is time-aligned, the average power supply power and the fluctuation amplitude are compared in the two time windows before and after the fluctuation event, the power change trend is judged, the load switching behavior marked in the server cluster log is called, the number and quantity of servers powered on or powered off at each time point are extracted to form a load switching rate time sequence, in the example, if 6 servers are switched from shutdown state to running state in one second after the fluctuation, the load switching rate is recorded as 6 per second, then the flywheel output power and the load switching rate are time-corresponded to judge whether the power supply output changes rapidly in the period with high load switching rate, the judgment reference value is set as power mutation rate greater than 200 watts per second and duration more than 0.2 seconds, if the condition is met, the time segment is marked as a significant power supply change segment, the power supply difference before and after the disturbance, the mutation segment duration and the time alignment result of the load switching behavior are extracted to form the power supply change rate feature.

[0066] The node fluctuation quantification submodule monitors and calculates the fluctuation of the number of power supply nodes in the difference disturbance stage based on the power supply change rate feature, and uses the formula:

[0067] ;

[0068] Identify the key time period of parameter change, and obtain the key interval of load disturbance , wherein, represents the number of concurrent power supply nodes in the time period after the disturbance, represents the number of concurrent power supply nodes in the time period before the disturbance, represents the power supply change rate feature in the time period after the disturbance, represents the power supply change rate feature in the time period before the disturbance, represents the number of time periods of disturbance analysis.

[0069] The load disturbance key interval refers to a continuous time interval in which the most obvious changes and the most concentrated fluctuations of parameters (such as instantaneous power supply power, load switching rate, and concurrent power supply node number) are identified by analyzing the operation data of the flywheel energy storage system and the server cluster during the voltage fluctuation or load mutation of the data center. The interval can reflect the main period of the load disturbance event, thereby guiding the energy storage system scheduling and response of the data center under power fluctuation.

[0070] The running records of each flywheel sub-node at different stages before and after the disturbance are called in sequence, and the number of nodes participating in power supply in each sub-period before the disturbance and after the disturbance response is extracted respectively, and the corresponding power supply rate characteristics are paired and operated item by item. In actual operation, the disturbance event start time is May 10, 2025, 14:00, and the analysis period is set to 3 stages, each stage length is 2 minutes, then to The corresponding pre-disturbance period is to The corresponding post-disturbance period is, the number of concurrent power supply nodes recorded during the collection period is 5, 6, and 7 before the disturbance, and 11, 10, and 12 after the disturbance, the power supply rate characteristics are 3.2kW / node, 3.9kW / node, and 4.1kW / node before the disturbance, and 6.5kW / node, 5.8kW / node, and 6.2kW / node after the disturbance, to unify the dimension and ensure the reasonableness of the calculation, the number of nodes is normalized to the interval 0.00-1.00, and the normalized results are:

[0071] 6→0.60, 4→0.40, 5→0.50;

[0072] At the same time, the power supply rate is normalized to the interval 0.00-1.00, and the normalized results are:

[0073] 3.3→0.66, 1.9→0.38, 2.1→0.42, after normalization, the difference is input into the following formula:

[0074] ;

[0075] ;

[0076] ;

[0077] The obtained disturbance response intensity is , indicating that there is a moderate intensity of synchronous response relationship between the change of the power supply node number and its corresponding rate characteristics during the disturbance, which is used to mark to The key period needs to be scheduled resource priority response in this disturbance; the value can also be compared with other period disturbance results, if , it is identified as a sensitive section that needs to be adjusted in the scheduling sequence, if , it is excluded from the priority scheduling sequence. The formula is to normalize the product of the node change and the energy supply rate change, and take the average of all periods to form a quantitative expression of the degree of synchronization of the node dynamic response and energy adjustment in the overall disturbance event.

[0078] Please refer to Figure 4 , the capacity correction distribution module includes:

[0079] The coordination gradient analysis submodule analyzes the synchronization of flywheel speed change and mechanical friction rate based on the key interval of load disturbance, compares the change gradients of the two at each time period, judges whether the fluctuations of the two show a coordinated trend, and calculates the fluctuation coordination degree of the difference section to obtain the coordination gradient amplitude;

[0080] From the sensor data of the flywheel energy storage system, the real-time speed and electric bearing friction rate of each flywheel in the disturbance interval are extracted, and they are sorted in time sequence into two independent sequences. Then the two sequences are respectively subjected to difference processing to obtain the speed change amplitude and friction rate change amplitude at each time point. Then a fixed length time window is used for sliding scanning, and the change direction of the two in each time period is compared. If the direction is consistent and the amplitude difference is within the set limit, it is determined that the change is synchronous. In the specific implementation, the change direction coincidence rate is greater than 80%, and the change difference is not more than 20% of the original value, which are set as the coordination determination basis. For example, during 12:12:00 to 12:12:05 on June 6, 2025, the speed of flywheel No. F-09 decreased by 120 revolutions per minute in 1 second, and the friction rate increased by 6 units, the change direction was opposite, and it did not constitute coordination. However, the speed of flywheel No. F-03 decreased by 80 revolutions per minute, and the friction rate increased by 6 units, the direction was consistent, and the amplitude was similar, that is, it constituted a coordination segment. The proportion of time in the entire disturbance interval that is determined to be coordinated is calculated to form a synchronization rate evaluation result. Then the fluctuation distribution of the speed and friction rate in each difference section is extracted. The average of the absolute difference of the gradient offset of the two is calculated as the fluctuation coordination difference value. Then 1 is subtracted from the proportion of the maximum gradient difference occupied by the value, which is converted into a coordination gradient amplitude index between 0 and 1. If the coordination gradient amplitude is above 0.75, it is considered to be highly coordinated, between 0.5 and 0.75, it is considered to be moderately coordinated, and below 0.5, it is considered to be not coordinated. In the example, if the coordination gradient amplitude of flywheel F-03 in the disturbance section is 0.82, the speed change and friction rate change have significant synchronization, and the coordination gradient amplitude corresponding to each flywheel number is output.

[0081] The energy distribution adjustment submodule analyzes the cooperation of the flywheel energy storage unit in energy release according to the coordination gradient amplitude, compares the balance relationship between energy distribution and dynamic power output among each energy supply node, adjusts the energy output order, and obtains energy distribution structure information;

[0082] According to the flywheel number, the energy supply record and the energy release amount of each flywheel unit in the disturbance section are read, and the flywheel and the power supply node where it is located are corresponded, the dynamic power output sequence of each node and the flywheel energy release time sequence are time-aligned, then the energy release proportion of each flywheel in the same time period is counted, and the proportion is compared with the actual energy supply power proportion of the node in the time period, if it is found that the release proportion is significantly high and the output power proportion is low, it shows that the flywheel has poor cooperation in this section, on the contrary, it shows that the energy supply response is good and the cooperation is high, then the priority of all flywheels is sorted according to the coordination gradient amplitude, the higher the coordination amplitude, the higher the sorting, for example, the coordination amplitude of F-03 is 0.82, the coordination amplitude of F-07 is 0.65, and the coordination amplitude of F-12 is 0.49, then the order is F-03, F-07, F-12, then the energy release plan is adjusted according to the sorting order, the high-priority flywheel is set as the front discharge object in the energy supply time period, the low-priority flywheel is pushed back or empty, and the target flywheel number of each power supply task is redistributed, for example, the time period of 12:12:04 to 12:12:05 originally discharged by F-12 is adjusted to F-03 to supply energy after the sorting, and the structured data of flywheel number, start and end time, released energy value and corresponding node number in each power supply time period is generated to form new energy distribution structure information.

[0083] The energy storage distribution correction submodule calls the energy distribution structure information, analyzes the difference between the current speed and the upper limit speed of each flywheel, combines the moment of inertia, friction coefficient and power release difference, and uses the formula:

[0084] ;

[0085] obtains the energy storage distribution correction feature , wherein, represents the total number of flywheels participating in concurrent scheduling in the current period, represents the moment of inertia of the th flywheel, reflecting the response ability of the flywheel unit to the change of rotational speed in the energy storage process, represents the difference between the current speed and the upper limit speed of the th flywheel, reflecting the remaining dynamic release space of the unit, represents the bearing friction coefficient of the th flywheel, used to measure the energy loss level of the flywheel in the rotation process, represents the bearing friction coefficient of the The power release difference of a flywheel in the current period is used to identify the change amount of the power output per unit time of the flywheel in the current period.

[0086] The energy storage allocation correction feature is a composite data structure generated based on the flywheel operation state and the optimization result of the scheduling structure in the energy storage system scheduling process, and is used to measure the dynamic energy supply capability change trend of each flywheel energy storage unit under the current scheduling configuration. It is used to guide the sorting and participation degree evaluation of the flywheel in the dynamic energy supply scheduling, and is used as the basis for priority sorting and dynamic scheduling adjustment.

[0087] For each flywheel unit participating in scheduling in the current period, six types of operation parameters, including the number, moment of inertia, current speed, upper limit speed, bearing friction coefficient and power release change amount, are compared and calculated one by one. First, the difference between the current speed and the set upper limit speed of each flywheel unit is analyzed to obtain the remaining interval of its release capacity. For example, the current speed of flywheel F1 is 4600 rad / s, the set upper limit is 4800 rad / s, and the difference is 200 rad / s. Then, the moment of inertia of the flywheel is 0.85 kg·m 2 , the bearing friction coefficient is 0.018, and the power release change amount is 11 kW. They are uniformly used in the operation with normalized scale, respectively recorded as: inertia 0.68, speed difference 0.83, friction coefficient 0.69, and power release 0.71. Substituting them into the formula, when calculating, taking the four flywheels F1-F4 as an example, the parameter normalized values are as follows:

[0088] F1: , , , ;

[0089] F2: , , , ;

[0090] F3: , , , ;

[0091] F4: , , , ;

[0092] Substituting the formula and calculating as follows:

[0093] ;

[0094] ;

[0095] ;

[0096] ;

[0097] Obtained:

[0098] ;

[0099] The results show that the flywheel energy supply system in the current period under the adjusted energy structure scheduling, the energy storage release coordination correction amplitude is , the value can be used for comparison analysis with the average correction amplitude of historical operation, so as to provide calculation basis for subsequent scheduling priority sorting, the formula by introducing , , , Four kinds of parameters and composite ratio operation and square root conversion, not only consider the flywheel energy release capacity, but also its friction consumption and dynamic power output characteristics are integrated into the correction calculation, so as to form the comprehensive quantitative standard of flywheel scheduling performance, so that the energy storage system scheduling has the adaptability and responsiveness of the comprehensive trade-off basis.

[0100] Please refer to Figure 5 , the scheduling sequence adjustment module includes:

[0101] The main loop comparison submodule is based on the energy storage allocation correction characteristics, analyzes the synchronous change of the total operation power curve of the power distribution main loop and the output power curve of the flywheel energy storage system, judges the synchronous offset of the power curve in the monitoring period, selects the period segment with synchronous characteristics, and obtains the power offset period segment;

[0102] The total running power time series of the power distribution main loop in the monitoring period is extracted, which can be composed of the real-time voltage and current product collected by the total power supply monitoring point. At the same time, the output power time series of each discharge node of the flywheel energy storage system is extracted and summarized to obtain the total output power curve of the flywheel. Then, the two power curves are aligned according to the same time step, and the sliding time window is used for segment division, for example, each 10 seconds is a segment to construct a synchronous comparison unit, and then the change trend is analyzed segment by segment. The change direction of the two power sequences in each segment is calculated and the same or opposite direction mark is recorded. The time period corresponding to the synchronous direction ratio reaching more than 80% is marked as consistent trend. Then, the average value of the absolute value of the instantaneous power difference of the two curves in each segment is calculated, and the value is compared with the proportion of the average level of the main loop power. If the difference ratio is less than 10%, it is determined that the fluctuation amplitude is synchronized. The segments that meet the two conditions at the same time are screened as the power synchronous deviation period. In the example, if the average power of the main loop is 18000 watts and the flywheel output is 17500 watts in the time period from 12:15:00 to 12:15:10 on June 6, 2025, the change direction is consistent and the average difference is 400 watts, accounting for about 2.2%, then this segment is included in the power deviation period. Finally, the start and end time, the average power of the main loop, the average power of the flywheel output, the difference percentage, the trend consistency mark and other data are extracted to construct the power deviation period.

[0103] The load ratio analysis submodule compares the power supply distribution of the flywheel energy storage system with the current load state of each server area based on the power deviation period, calculates the mean square deviation of the power change rate of each server area, identifies the number of server areas with critical change rate amplitude, and obtains the load fluctuation normalization quantity.

[0104] Call the load record data of the server area within the cycle period, extract the current power consumption time series of each physical area one by one, and simultaneously extract the flywheel energy supply record, establish the mapping relationship between the flywheel power supply node and the server area, re-project the flywheel energy supply distribution to each area, calculate the power change rate series of each server area by time segment in each power offset segment, and then perform mean square error calculation on the power change rate series of all areas to characterize the distribution of the degree of fluctuation in each area, and then set the benchmark threshold to judge whether the change rate amplitude is prominent, and set the mean square error with reference to the data change range of the past week. The difference threshold is 50 watts per second. The number of regions whose mean square error exceeds the threshold is counted as the identification result. For example, during the offset period from 12:15:00 to 12:15:10, there are 12 server regions, of which 5 regions have a mean square error of more than 50 watts per second. The number of key change regions is recorded as 5. This number is then divided by the total number of regions and rounded to two decimal places to obtain a normalized load fluctuation value of 0.42. This value is used as a normalized indicator representing the degree of load fluctuation imbalance in the server region during the current power offset period, and the normalized value is output.

[0105] The scheduling sequence generation submodule determines the energy output efficiency and residual energy ratio of the flywheel energy storage device based on the load fluctuation normalization amount, and calculates the scheduling sequence difference in the target cycle using the formula:

[0106] ;

[0107] Adjust the dispatch priority to obtain the energy storage priority ranking index, where: Indicates the number The energy storage priority ranking index corresponding to the flywheel energy storage device, Indicates the number The remaining available energy ratio of the flywheel energy storage device in the target cycle, Indicates the number The unit energy supply efficiency of the flywheel energy storage device, Indicates the normalized load fluctuation in the current cycle. Indicates the number The flywheel energy storage device is The current dispatch sequence number of the server region, Indicates the number The flywheel energy storage device is The dispatch number that each server region should be assigned in rotation order, Indicates the number of server regions.

[0108] The energy storage priority ranking index refers to a set of ranking data determined for each flywheel device in the flywheel energy storage system according to the comprehensive operating state, the remaining available energy ratio, the unit energy supply efficiency, the regional scheduling sequence difference and the load fluctuation of each flywheel energy storage device in the current scheduling period. The index is used to reflect the priority order of each flywheel device in the energy storage compensation scheduling, so as to determine which flywheel devices should participate in energy supply and compensation first when the power grid fluctuates or the load mutates, and ensure the dynamic response capability and power supply safety of the overall system operation.

[0109] The energy output efficiency and the remaining energy ratio of each numbered flywheel energy storage device in the current period are determined, a set of scheduling performance indexes of all numbered devices is established, the product of the unit energy compensation capability and the actual remaining energy ratio of each device is calculated, and the basic output level is obtained. Taking the flywheel device numbered 03 as an example, the remaining energy in the current monitoring period is , the rated energy storage of the device is , the remaining energy ratio is calculated as:

[0110] ;

[0111] The output efficiency is 0.94, which is the normalized output performance value affected by flywheel speed, friction loss and temperature rise, and the product of the two is:

[0112] ;

[0113] The load fluctuation normalization has been determined in advance as 0.60, and the calculation result is:

[0114] ;

[0115] The first part of the index is:

[0116] ;

[0117] Then the scheduling deviation of the flywheel device numbered 03 in the four server areas is analyzed. Assuming that the current numbered sequence is , the rotation sequence is , the deviation is , the square is , the sum is 3, and the number of server areas is , so the second part of the result is:

[0118] ;

[0119] Substitute the above results into the complete formula:

[0120] ;

[0121] In the formula, the first term expresses the comprehensive energy supply capacity of the flywheel in the current cycle and modulates its priority through the square root function of the fluctuation normalization quantity; the second term measures the coordination degree of scheduling by the mean square of the number deviation of the server area. The smaller the value, the more reasonable the number arrangement. The calculation result is This shows that although the flywheel device No. 03 has sufficient energy supply capacity, its scheduling consistency has a large deviation and the overall ranking is relatively backward. It is recommended to be placed in the rear standby queue or participate in non-main load compensation tasks.

[0122] See also Figure 6 , the state change tracking module includes:

[0123] The energy fluctuation analysis submodule analyzes the changes in the remaining available energy of the flywheel number in consecutive cycles based on the energy storage priority ranking index, compares the energy fluctuation amplitude between each monitoring cycle, determines whether there is an abnormal deviation in the change, and generates the cycle energy fluctuation amplitude;

[0124] The remaining available energy data of each flywheel number in multiple consecutive monitoring cycles are extracted in order of priority. Each cycle can be set to 5 minutes, and it is organized into a two-dimensional time series table according to the dual index of number and time. Then, the energy difference between adjacent cycles is calculated for the continuous cycle data of each flywheel number. The absolute change value of the energy remaining between two cycles is calculated by traversal. Then, the average of all cycle differences of each number is calculated to obtain the energy fluctuation amplitude of the flywheel during the observation time. After that, by comparing the difference between the energy change value of each cycle and the historical fluctuation mean of the number, it is judged whether there is an abnormal offset. The offset judgment The basis for diagnosis is set as the single-cycle fluctuation amplitude is more than twice the average fluctuation value of the number in the past 12 hours, and the current remaining energy is less than 30% of its capacity. For example, the remaining energy of number F-15 in cycle T1 is 6.8 kJ, which drops to 3.1 kJ in T2. ​​The average historical fluctuation is 1.5 kJ, and the current decline is 3.7 kJ, which is more than twice the historical average and the remaining ratio is less than 30%. The abnormal offset condition is met, and the cycle is recorded as an abnormal fluctuation segment. All cycle fluctuation differences corresponding to each flywheel number, whether it is abnormal, start and end time and current remaining energy are output to form a cycle energy fluctuation amplitude data set.

[0125] The stability judgment submodule uses the amplitude of periodic energy fluctuations to determine the persistence of fluctuations in the time series, analyzes whether there are regular fluctuations or sudden changes in the energy change process, identifies the coherence characteristics of energy changes, and obtains the stability trend of energy response;

[0126] The energy fluctuation time series is unfolded according to the flywheel number, a complete time series fluctuation graph is constructed for each number, a sliding window method is used to check whether the fluctuation value continuously appears high amplitude deviation between adjacent windows, whether the fluctuation trend has continuity, if three or more consecutive periods meet the abnormal deviation judgment standard, it is considered as a persistent unstable state, whether there is a situation that the fluctuation direction of the two periods before and after is opposite and the value is greatly reversed, if the reverse amplitude exceeds twice the average fluctuation amplitude of the number, it is considered as a sudden change, for example, the number F-10 decreases by 3.2 kilojoules at T1, increases by 2.9 kilojoules at T2, and decreases by 3.5 kilojoules at T3, the direction is repeated and the amplitude is large, that is, it constitutes a sudden feature, then the number of abnormal segments of each flywheel in the fluctuation graph and the ratio of the total period number are counted, the stability rate of the number in the analysis section is calculated, if the stability rate is less than 60%, it is marked as an unstable number, the fluctuation direction sequence, the reverse point position, the continuous abnormal length and the stability rate are output according to the number, and the energy response stability trend data table of each number is formed.

[0127] The number jump screening sub-module analyzes the fluctuation continuity reflected by the energy response stability trend, screens the data sequence with prominent changes in the flywheel number, judges whether the fluctuation characteristics meet the state jump characteristics, and synchronously updates to the data list to obtain the state jump tracking data.

[0128] The number list with a stability rate lower than the set standard is screened, the key points of the energy fluctuation sequence of the number are extracted, the time when the direction is reversed or the amplitude is suddenly increased is identified, and then the key time is compared with the flywheel start-stop events in the historical scheduling record, if the key fluctuation time occurs during the flywheel does not participate in scheduling, it is judged as a non-task-driven change, further excluding the co-time records of environmental interference and power disturbance items, if the external driving factor cannot be identified and the fluctuation form meets the mutation characteristics, the flywheel number is marked as a state jump object, for example, the number F-22 has not been scheduled in the past 12 hours, but the energy remaining value has appeared 3 times of high-frequency sudden drop, the fluctuation form is a decrease of more than 60% within 2 hours, the stability rate is 38%, and there is no corresponding load record, so the number is identified as a state jump target, the number, the jump time, the energy value before and after the change, the historical fluctuation trajectory and the monitoring node number are synchronously written into the data list to constitute the state jump tracking data.

[0129] The above is only a preferred embodiment of the present application, and does not limit the present application in other forms, any skilled person in the art can modify or change the above disclosed technical content to equivalent embodiments applied to other fields, but any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present application without departing from the technical solution content of the present application still belongs to the protection scope of the present application technical solution.

Claims

1. A flywheel energy storage system for transient voltage control in a data center, characterized in that: The system comprises: The disturbance moment identification module analyzes the voltage curves of the flywheel energy storage monitoring node in each time period based on the data center voltage change rate and amplitude, compares the synchronization of rate and amplitude changes, determines the correlation between the fluctuation moment and the operating status of the flywheel energy storage system, and obtains the timing characteristics of the fluctuation event; The load mutation determination module determines the flywheel energy storage operation changes in the server cluster log based on the timing characteristics of the fluctuation event, analyzes the instantaneous power changes, compares the load switching rate and the number of concurrent energy supply nodes before and after the disturbance, identifies the critical interval, and obtains the load disturbance critical interval; The capacity correction distribution module compares the current speed of the flywheel with the trend of the mechanical friction rate based on the load disturbance key interval, determines the speed and friction coordination between the electric bearing and the energy, adjusts the available energy distribution, calculates the capacity change, and obtains the energy storage distribution correction feature; The scheduling sequence adjustment module compares the total operating power of the main circuit with the flywheel data based on the energy storage allocation correction characteristics, analyzes the changes in the server area load ratio caused by voltage offset, determines the impact of parameter changes on the scheduling sequence, and obtains the energy storage priority ranking index.

2. The flywheel energy storage system for transient voltage control in a data center according to claim 1 is characterized in that: The fluctuation event timing characteristics include the time of event occurrence, fluctuation distribution characteristics, and associated marks; the load disturbance key interval includes interval time information, load disturbance type, and disturbance event identifier; the energy storage allocation correction characteristics include corrected capacity distribution, energy storage dynamic coefficient, and energy distribution structure; the energy storage priority ranking indicators include ranking order, priority number, and allocation weight.

3. The flywheel energy storage system for transient voltage control in a data center according to claim 1, characterized in that: The disturbance moment identification module includes: The rate fluctuation identification submodule analyzes the voltage curves recorded by the monitoring nodes based on the voltage change rate and amplitude of the data center, determines the sudden changes in the voltage change rate within a continuous period, and combines the node distribution characteristics to screen the concentrated time periods where fluctuations occur. It summarizes the related change intervals and obtains the rate fluctuation interval distribution; The amplitude offset identification submodule calls the rate fluctuation interval distribution, analyzes the voltage data of each node in the corresponding time period, compares the difference between the data and the rated voltage, selects the time segment with continuous voltage fluctuation and critical amplitude change, and obtains the amplitude offset section parameter; The fluctuation feature extraction submodule analyzes the overlapping time segments according to the amplitude offset segment parameters, determines the correlation between the time segments and the start and stop moments of the flywheel energy storage system, identifies the associated fluctuation events, and obtains the time series characteristics of the fluctuation events.

4. The flywheel energy storage system for transient voltage control in a data center according to claim 1, characterized in that: The load mutation determination module includes: The energy supply rate extraction submodule extracts the instantaneous energy supply power in each period before and after the disturbance based on the timing characteristics of the fluctuation event and the voltage change rate data collected by the server cluster log and the flywheel energy storage monitoring node, and compares the instantaneous energy supply power with the load switching rate in the same period to obtain the energy supply change rate characteristics; The node fluctuation quantification submodule monitors the changes in the number of concurrent energy supply nodes based on the energy supply change rate characteristics, calculates the fluctuation of the number of energy supply nodes in the differential disturbance stage, identifies the key time period with prominent parameter changes, and obtains the load disturbance key interval.

5. The flywheel energy storage system for transient voltage control in a data center according to claim 1, characterized in that: The capacity correction allocation module includes: The coordination gradient analysis submodule analyzes the synchronization of the flywheel speed change and the mechanical friction rate based on the load disturbance key interval, compares the change gradients of the two in each period, determines whether the fluctuations of the two show a coordinated trend, and calculates the degree of fluctuation coordination in the difference section to obtain the coordination gradient amplitude; The energy distribution adjustment submodule analyzes the coordination of the flywheel energy storage unit in energy release according to the coordination gradient amplitude, compares the balance between energy sharing and dynamic power output among the energy supply nodes, adjusts the energy output sequence, and obtains energy distribution structure information; The energy storage distribution correction submodule calls the energy distribution structure information, analyzes the difference between the current speed of each flywheel and the upper limit speed, and obtains the energy storage distribution correction characteristics by combining the moment of inertia, friction coefficient and power release difference.

6. The flywheel energy storage system for transient voltage control in a data center according to claim 1, characterized in that: The scheduling order adjustment module includes: The main circuit comparison submodule analyzes the synchronous changes of the total operating power curve of the distribution main circuit and the output power curve of the flywheel energy storage system based on the energy storage distribution correction characteristics, determines the synchronous offset of the power curve within the monitoring period, selects the cycle segments with key synchronization characteristics, and obtains the power offset cycle segments; The load ratio analysis submodule compares the energy distribution of the flywheel energy storage system with the current load status of each server area based on the power offset period, calculates the mean square error of the power change rate of each server area, identifies the number of server areas with critical change rate amplitudes, and obtains the load fluctuation normalization amount; The scheduling sequence generation submodule determines the energy output efficiency and the remaining energy ratio of the flywheel energy storage device according to the load fluctuation normalization amount, calculates the scheduling sequence difference in the target period, adjusts the scheduling priority, and obtains the energy storage priority ranking index.

7. The flywheel energy storage system for transient voltage control in a data center according to claim 1, characterized in that: The system further comprises: The state change tracking module analyzes the change in the number of the first flywheel in the order according to the energy storage priority ranking index, compares the change amplitude of the residual energy in consecutive cycles, determines the stability of the energy change, identifies the key number, marks it as a state jump object, updates the data list, and obtains the state jump tracking data; The state transition tracking data includes a transition flag, number information, and a change history record.

8. The flywheel energy storage system for transient voltage control in a data center according to claim 7, characterized in that: The state change tracking module includes: The energy fluctuation analysis submodule analyzes the change in the remaining available energy of the flywheel number in consecutive cycles based on the energy storage priority ranking index, compares the energy fluctuation amplitude between each monitoring cycle, determines whether there is an abnormal deviation in the change, and generates the periodic energy fluctuation amplitude; The stability judgment submodule calls the periodic energy fluctuation amplitude, judges its fluctuation persistence in the time series, analyzes whether there are regular fluctuations or sudden changes in the energy change process, identifies the coherence characteristics of the energy change, and obtains the energy response stability trend; The number jump screening submodule analyzes the fluctuation coherence reflected by the stable trend of the energy response, screens the data sequence with prominent changes in the flywheel number, determines whether the fluctuation characteristics meet the state jump characteristics, and synchronously updates the data list to obtain the state jump tracking data.

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