Intelligent control method, device and equipment of flywheel array and storage medium

Abstract

The present application relates to the technical field of power control, and discloses an intelligent control method, device and equipment of a flywheel array and a storage medium, comprising: obtaining multi-dimensional health state indexes of flywheels in the flywheel array; evaluating and processing the health degrees of the flywheels according to the multi-dimensional health state indexes to obtain the health degrees of the flywheels; obtaining multi-dimensional running state indexes of the flywheels; evaluating and processing the scheduling priorities of the flywheels according to the multi-dimensional running state indexes to obtain the scheduling priorities of the flywheels; and in response to a power scheduling instruction, selecting target flywheels from the flywheel array according to the health degrees and the scheduling priorities to participate in power scheduling. The present application can significantly improve the power response speed of the flywheel array, while ensuring the balance of the service life distribution of the flywheel array, so as to improve the long-term reliability and stability of the flywheel array.

Description

Technical Field

[0001] This invention relates to the field of power control technology, and in particular to an intelligent control method, device, equipment, and storage medium for a flywheel array. Background Technology

[0002] A flywheel array energy storage system is a power energy management system with high power density and fast response capabilities. It mainly consists of multiple flywheel energy storage systems (which can be simply referred to as flywheels) connected in parallel on the AC or DC side, and these flywheel energy storage systems are integrated in an array. The core operational requirements of a flywheel array energy storage system are to achieve rapid power distribution and stable control, while ensuring the safe operation and balanced lifespan of each flywheel in the array.

[0003] Related technologies offer operation control strategies based on State of Charge (SOC). However, this strategy has limitations and struggles to meet the core operational requirements of flywheel array energy storage systems. Specifically, SOC-based operation control strategies typically prioritize scheduling flywheels with higher SOC to handle greater discharge power, while flywheels with lower SOC receive more charging power. This "one-size-fits-all" power allocation method forces all flywheels in the array to participate in power scheduling synchronously, severely ignoring the inherent differences in factory performance, material properties, and real-time operating status among flywheels. This results in some flywheels failing to perform at their optimal level, leading to inefficient operation and affecting the overall power response speed of the flywheel array.

[0004] Related technologies also offer operation control strategies based on health assessments. However, these strategies also have many limitations and cannot meet the core operational requirements of flywheel array energy storage systems. Specifically, these health assessment-based operation control strategies often employ a flywheel component weighting method (i.e., linearly summing the health weight coefficients of components such as the motor, bearings, and maglev of the flywheel), prioritizing the scheduling of flywheels with higher health indicators for power dispatch. This approach is overly simplistic, failing to consider the coupling relationships between components and resulting in significant deviations from the actual health status of the flywheels. For example, the attenuation of levitation force in the maglev component may cause the bearing component to bear excessive loads, thereby exacerbating the mechanical wear of the bearing component and leading to an increase in the bearing component's temperature. The temperature change of the bearing component may then affect the stability of the maglev component, causing flywheel rotor instability and ultimately flywheel damage. This chain reaction is difficult to quantify using a simplified weighting method. This deviation directly leads to persistently high loss rates in individual flywheels and can also cause delayed or false alarms in fault warnings, affecting the long-term reliability of the flywheel array energy storage system.

[0005] Furthermore, operation control strategies based on health assessments rely on a single health indicator, which may trigger a vicious cycle of "whipping the fast ox," meaning that flywheels with higher health indicators are prioritized for scheduling, resulting in longer operating times and prolonged high-speed operation. This overuse accelerates the deterioration of their health, ultimately reducing the redundancy of the flywheel array, increasing the risk of failure, and affecting the stability of the flywheel array. Summary of the Invention

[0006] This invention provides an intelligent control method, device, equipment, and storage medium for flywheel arrays, aiming to solve the technical problems caused by existing operation control strategies, which result in low power response speed and uneven lifespan of flywheel arrays during actual operation, affecting the long-term reliability and stability of flywheel arrays.

[0007] Firstly, a smart control method for a flywheel array is provided, including: Obtain multi-dimensional health status indicators of flywheels in a flywheel array; The health status of the flywheel is evaluated based on the multi-dimensional health status indicators to obtain the health status of the flywheel. Obtain multi-dimensional operating status indicators of the flywheel; Based on the multi-dimensional operating status indicators, the scheduling priority of the flywheel is evaluated to obtain the scheduling priority of the flywheel. In response to a power scheduling command, a target flywheel is selected from the flywheel array to participate in power scheduling based on the health status and the scheduling priority.

[0008] Secondly, embodiments of the present invention also provide an intelligent control device for a flywheel array, comprising: The health status indicator acquisition module is used to acquire multi-dimensional health status indicators of the flywheels in the flywheel array; The health assessment module allows users to evaluate the health of the flywheel based on the multi-dimensional health status indicators, thereby obtaining the health score of the flywheel. The operation status indicator acquisition module is used to acquire multi-dimensional operation status indicators of the flywheel; The priority evaluation module is used to evaluate the scheduling priority of the flywheel based on the multi-dimensional operating status indicators, and obtain the scheduling priority of the flywheel. The flywheel scheduling module is used to respond to power scheduling commands and select target flywheels from the flywheel array to participate in power scheduling based on the health status and the scheduling priority.

[0009] Thirdly, embodiments of the present invention also provide a computer device, the computer device including a processor, a memory, a computer program stored in the memory and executable by the processor, and a data bus for realizing communication between the processor and the memory, wherein when the computer program is executed by the processor, it implements the intelligent control method of the flywheel array as described in the first aspect.

[0010] Fourthly, embodiments of the present invention also provide a storage medium for computer-readable storage, wherein the storage medium stores one or more programs that can be executed by one or more processors to implement the intelligent control method for the flywheel array as described in the first aspect.

[0011] In the above-mentioned intelligent control method, device, equipment, and storage medium for flywheel arrays, the following steps are taken: acquiring multi-dimensional health status indicators of the flywheels in the flywheel array; evaluating the health of the flywheels based on the multi-dimensional health status indicators to obtain the flywheel health level; acquiring multi-dimensional operating status indicators of the flywheels; evaluating the scheduling priority of the flywheels based on the multi-dimensional operating status indicators to obtain the flywheel scheduling priority; and, in response to power scheduling commands, selecting target flywheels from the flywheel array to participate in power scheduling based on the health level and scheduling priority. In this way, on the one hand, based on multi-dimensional health status indicators that can comprehensively and accurately reflect the entire life cycle of the flywheel, the health level reflecting the overall health of the flywheel can be finely evaluated, thus achieving a comprehensive and accurate quantification of the flywheel's lifespan. On the other hand, based on multi-dimensional operating status indicators that can comprehensively reflect the flywheel's operating performance, the scheduling priority reflecting the overall usage intensity of the flywheel can be finely evaluated, thus achieving a comprehensive and accurate quantification of the flywheel's operating capability. Furthermore, in response to power scheduling commands, target flywheels are rationally selected from the flywheel array to participate in power scheduling based on health and scheduling priority. This achieves a dual balance control of health and scheduling priority at the flywheel scheduling and usage level, thereby achieving balanced scheduling and usage of the flywheels. This not only ensures the long-term health of the flywheels but also maintains the response speed of the flywheel array, while ensuring the uniformity of the flywheel array's lifespan distribution, thereby improving the long-term reliability and stability of the flywheel array. Attached Figure Description

[0012] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart illustrating an intelligent control method for a flywheel array according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the health assessment architecture involved in one embodiment of the present invention; Figure 3 yes Figure 1 A schematic diagram of a specific implementation method for step S50; Figure 4 This is a schematic block diagram of the structure of an intelligent control device for a flywheel array provided in an embodiment of the present invention; Figure 5 This is a schematic block diagram of the structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] The fixed operation control strategy provided in related technologies leads to a triple dilemma of efficiency, lifespan and reliability for flywheel arrays in actual operation: response delay, high energy loss rate of some flywheels and frequent failures, making it difficult to resolve the contradiction between resource utilization and flywheel loss.

[0016] To address this, embodiments of the present invention provide an intelligent control method, apparatus, device, and storage medium for a flywheel array. The intelligent control method for the flywheel array involves: acquiring multi-dimensional health status indicators of the flywheels in the flywheel array; evaluating the health of the flywheels based on these multi-dimensional health status indicators to obtain their health level; acquiring multi-dimensional operating status indicators of the flywheels; evaluating the scheduling priority of the flywheels based on these multi-dimensional operating status indicators to obtain their scheduling priority; and, in response to a power scheduling command, selecting target flywheels from the flywheel array to participate in power scheduling based on their health level and scheduling priority. In this way, on the one hand, based on multi-dimensional health status indicators that can comprehensively and accurately reflect the entire life cycle of the flywheel, the health level reflecting the overall health of the flywheel can be finely evaluated, thus achieving a comprehensive and accurate quantification of the flywheel's lifespan. On the other hand, based on multi-dimensional operating status indicators that can comprehensively reflect the flywheel's operating performance, the scheduling priority reflecting the overall usage intensity of the flywheel can be finely evaluated, thus achieving a comprehensive and accurate quantification of the flywheel's operating capability. Furthermore, in response to power scheduling commands, target flywheels are rationally selected from the flywheel array to participate in power scheduling based on health and scheduling priority. This achieves a dual balance control of health and scheduling priority at the flywheel scheduling and usage level, thereby achieving balanced scheduling and usage of the flywheels. This not only ensures the long-term health of the flywheels but also maintains the response speed of the flywheel array, while ensuring the uniformity of the flywheel array's lifespan distribution, thereby improving the long-term reliability and stability of the flywheel array.

[0017] The intelligent control method for flywheel arrays provided in this application can be applied to terminals, servers, or software running on either the terminal or server, and can also be applied to flywheel array controllers. Terminals can be vehicle-mounted terminals, smartphones, tablets, laptops, desktop computers, etc.; servers can be configured as independent physical servers, server clusters or distributed systems composed of multiple physical servers, or cloud servers providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; software can be applications implementing the intelligent control method for flywheel arrays, but is not limited to the above forms.

[0018] Please see Figure 1 , Figure 1 This is a flowchart illustrating an intelligent control method for a flywheel array provided in an embodiment of the present invention, which includes steps S10 to S50.

[0019] S10: Obtain multi-dimensional health status indicators of the flywheels in the flywheel array.

[0020] The intelligent control method for flywheel arrays provided by this invention designs a more precise, dynamic, and intelligent innovative control mechanism, forming a closed-loop control logic of data acquisition, evaluation calculation, and scheduling execution. It aims to improve the overall performance of the flywheel array, optimize power scheduling and health management, and achieve more refined and balanced operation control of the flywheel array.

[0021] The intelligent control method for flywheel arrays provided in this invention mainly includes three stages: Stage 1, evaluating the health of each flywheel in the flywheel array based on multi-dimensional health status indicators; Stage 2, evaluating the scheduling priority of each flywheel in the flywheel array based on multi-dimensional operating status indicators; Stage 3, combining health and scheduling priority to perform flywheel scheduling, making flywheel scheduling faster, more targeted and intelligent, ensuring balanced use of flywheels to extend flywheel lifespan, while ensuring fault tolerance and rapid recovery capability, realizing intelligent power balance scheduling and sustainable operation of the flywheel array energy storage system.

[0022] The following is a detailed explanation of Phase One.

[0023] For step S10, multi-dimensional health status indicators of each flywheel in the flywheel array can be obtained. These multi-dimensional health status indicators can comprehensively and accurately reflect the entire life cycle status of the flywheel, thus providing very important data support for the optimized scheduling of the flywheel array.

[0024] S20: The health of the flywheel is evaluated based on multi-dimensional health status indicators to obtain the flywheel's health score.

[0025] For step S20, for each flywheel in the flywheel array, its health is comprehensively and meticulously evaluated based on multi-dimensional health status indicators. The health status can better characterize the overall health level of the flywheel.

[0026] In step S20 of some embodiments, the multi-dimensional health status indicators include initial health status indicators, real-time health status indicators, and historical health status indicators. The initial health status of the flywheel can be calculated based on the initial health status indicators to obtain the initial health status of the flywheel; the real-time health status of the flywheel can be calculated based on the real-time health status indicators to obtain the real-time health status of the flywheel; the historical health status of the flywheel can be calculated based on the historical health status indicators to obtain the historical health status of the flywheel; and a weighted summation of the initial health status, real-time health status, and historical health status is performed to obtain the overall health status.

[0027] Please see Figure 2 , Figure 2 This is a schematic diagram of the health assessment architecture. Figure 2In the illustration, health assessment mainly includes initial health assessment based on initial health status indicators, real-time health assessment based on real-time health status indicators, and historical health assessment based on historical health status indicators.

[0028] (a) Initial health assessment: The initial health status indicators are mainly based on testing and evaluation in the factory environment, reflecting the performance standards achieved by each flywheel in the flywheel array at the time of leaving the factory. These indicators mainly include sub-indicators such as factory test pass rate, bearing assembly performance, magnetic levitation assembly performance, auxiliary assembly performance, motor assembly performance, housing assembly performance, and converter assembly performance.

[0029] For each flywheel in the flywheel array, its initial health status is calculated based on the initial health status index, denoted as SOH. o In order to comprehensively assess its health status at the time of leaving the factory.

[0030] Specifically, considering that the sub-indicators included in the initial health status index may have different dimensions, each sub-indicator in the initial health status index can be normalized first to obtain the standard value of each sub-indicator; then, the standard values ​​of each sub-indicator are weighted and summed, that is, for each sub-indicator, its standard value is multiplied by its preset weight to obtain its weight score; then, the weight scores of all sub-indicators in the initial health status index are added together to obtain the initial health score.

[0031] The weight of each sub-indicator can be flexibly set based on practical experience, industry standards, or expert opinions (the sum of all sub-indicators is 1). For example, the weight of the factory test pass rate is 0.15, the weight of the bearing component performance is 0.15, the weight of the magnetic levitation component performance is 0.15, the weight of the auxiliary component performance is 0.15, the weight of the motor component performance is 0.20, the weight of the housing component performance is 0.10, and the weight of the converter component performance is 0.10.

[0032] (ii) Real-time health assessment: Real-time health status indicators can be acquired in real time through sensors, reflecting the current working status of each flywheel in the flywheel array. These indicators mainly include the real-time status of the system (such as whether the overall flywheel is operating normally), the status of the bearing assembly (such as the current temperature or current speed of the bearing assembly), the status of the magnetic levitation assembly (such as the current current or current magnetic field of the magnetic levitation assembly), the status of the auxiliary components (such as whether the cooling and lubrication functions of the auxiliary components are normal), the status of the motor assembly (such as the current temperature, current load, or current efficiency of the motor assembly), the status of the housing assembly (such as whether the housing assembly is worn), and the status of the converter assembly (such as the output waveform or efficiency of the converter assembly), among other sub-indicators.

[0033] For each flywheel in the flywheel array, its real-time health status is calculated based on real-time health indicators and denoted as SOH. This is to comprehensively assess their current health status. The calculation process can refer to the initial health status calculation process, which will not be repeated here.

[0034] (III) Historical health assessment: Historical health status indicators mainly include sub-indicators that reflect fault conditions and usage status, such as total historical failure count, total historical charge and discharge amount, total historical operating cycles, and total historical operating time.

[0035] For each flywheel in the flywheel array, its historical health status is calculated based on historical health status indicators, denoted as SOH. h This is to comprehensively assess their past health status. The calculation process can refer to the calculation process of the initial health status, and will not be repeated here.

[0036] Finally, using a preset health calculation formula, the initial health, real-time health, and historical health are weighted and summed to obtain the health score, denoted as SOH. The health calculation formula is shown below: SOH=SOH o ×K1 +SOH ×K2 + SOH h ×K3 Here, K1, K2, and K3 represent the weighting coefficients corresponding to the initial health level, real-time health level, and historical health level, respectively. These coefficients can be flexibly set according to the actual importance of the initial health level, real-time health level, and historical health level, and K1+K2+K3=1. The higher the health level, the higher the overall health status of the flywheel.

[0037] In this way, for each flywheel in the flywheel array, by evaluating the initial health level that reflects the current health level, the real-time health level that reflects the current health level, and the historical health level that reflects the past health level, the overall health level of the flywheel can be evaluated based on the initial health level, the initial health level, and the historical health level. This enables a comprehensive and accurate quantification of the flywheel's lifespan, providing a more valuable basis for the optimized operation and scheduling of the flywheel array.

[0038] The following is a detailed explanation of Phase Two.

[0039] S30: Obtain multi-dimensional operating status indicators of the flywheel.

[0040] For step S30, multi-dimensional operating status indicators of each flywheel in the flywheel array can be obtained. These multi-dimensional operating status indicators can comprehensively reflect the operating performance of the flywheel, thus providing very important data support for the optimized scheduling of the flywheel array.

[0041] Specifically, the multi-dimensional operating status indicators include elements such as high-speed equivalent operating time (T_Speed), high-power equivalent operating time (T_Power), and fault status level.

[0042] The high-speed equivalent running time (T_Speed) is used to evaluate the duration of the flywheel's high-speed operation. The process of obtaining the high-speed equivalent running time (T_Speed) includes: calculating the speed difference between the flywheel's real-time speed and a preset reference speed; normalizing the speed difference to obtain a normalized speed difference; processing the normalized speed difference using the Sigmoid function to obtain the first function output value; and performing sliding time window integration on the first function output value to obtain the flywheel's high-speed equivalent running time (T_Speed). The high-speed equivalent running time (T_Speed) is crucial for determining the flywheel's high-speed operating capability and its impact on its lifespan, and helps optimize flywheel operation scheduling and utilization efficiency.

[0043] The high-power equivalent operating time (T_Power) is used to evaluate the duration of the flywheel's operation under high-power conditions. The process of obtaining the high-power equivalent operating time (T_Power) includes: calculating the power difference between the flywheel's real-time power and a preset reference power; normalizing the power difference to obtain a normalized power difference; performing calculations on the normalized power difference using the Sigmoid function to obtain the output value of a second function; and performing sliding-time window integration on the output value of the second function to obtain the high-power equivalent operating time (T_Power). The high-power equivalent operating time (T_Power) is crucial for determining the flywheel's capability and sustainability under high-load conditions, helping to ensure the flywheel's safety and stability under these conditions.

[0044] The sliding time window can be flexibly set according to the actual situation, and a suitable sliding time window of the appropriate length should be set to balance the computational complexity and accuracy.

[0045] Fault states refer to various abnormal situations that may occur during flywheel operation, affecting its performance, safety, or normal operation. Fault states can be categorized into multiple levels, such as levels one to five. Levels one and two are the most urgent, requiring immediate shutdown; level three requires derated or reduced speed operation; level four requires immediate maintenance; and level five requires an alarm but can recover automatically. Therefore, level one and two fault states are assigned the highest priority; level three fault states are assigned 3N additional priority levels (base priority N + 3N); level four fault states are assigned 2N additional priority levels (base priority N + 2N); and level five fault states are assigned N priority levels (i.e., base priority N), where N is the base value for defining priorities (e.g., 50) used to calculate the priority differences between different fault state levels. The flywheel's priority will be adjusted accordingly based on the fault state level.

[0046] S40: Based on multi-dimensional operating status indicators, the scheduling priority of the flywheel is evaluated and processed to obtain the scheduling priority of the flywheel.

[0047] For step S40, for each flywheel in the flywheel array, its scheduling priority is comprehensively and meticulously evaluated based on multi-dimensional operating status indicators. Based on the scheduling priority, the order in which the flywheels participate in power scheduling can be dynamically adjusted to avoid the rapid decline in lifespan of flywheels with high health due to overuse.

[0048] In step S30 of some embodiments, the scheduling priority of the flywheel can be calculated and processed using a preset scheduling priority calculation formula based on the high-speed equivalent operating time, the high-power equivalent operating time, and the fault state level to obtain the scheduling priority.

[0049] Scheduling priorities include discharge priority and charging priority. Discharge priority takes into account the effects of high-speed equivalent operating time, power equivalent operating time, and fault state level. Charging priority also takes into account the effects of high-speed equivalent operating time, power equivalent operating time, and fault state level.

[0050] The preset scheduling priority calculation formulas include discharge priority calculation formulas and charging priority calculation formulas. The discharge priority calculation formula is as follows: Discharge priority (Prio_D) = round(T_Speed / △T1) + round(T_Power / △T2) + A The formula for calculating charging priority is as follows: Charging priority (Prio_C) = -(round(T_Speed / △T1) + round(T_Power / △T2) + A) Where △T1 represents the minimum time period for high-speed operation, △T2 represents the minimum time period for high-power operation, round() function represents the rounding function, and A represents the priority of the fault state level.

[0051] Based on this, for each flywheel in the flywheel array, its high-speed equivalent operating time, power equivalent operating time, and fault state level priority can be substituted into the discharge priority calculation formula to calculate its discharge priority; similarly, its high-speed equivalent operating time, power equivalent operating time, and fault state level priority can be substituted into the charging priority calculation formula to calculate its charging priority.

[0052] For example, suppose the first i The equivalent high-speed running time of the flywheel is 0.68 hours (i.e., T_Speed ​​= 0.68 hours), ΔT1 = 1 minute; the equivalent high-power running time is 0.5 hours (i.e., T_Power = 0.5 hours), ΔT2 = 1 minute; and the fault state level is five (A = N = 50). Then, the fault level is... i The discharge priority of the flywheel is: Prio_D ( i ) = round(0.68h / 1min) + round(0.5h / 1min) + 50 = 120 No. i The discharge priority of the flywheel is: Prio_C ( i )=-(round(0.68h / 1min) + round(0.5h / 1min) + 50)=-120 Flywheels with higher discharge priority should participate in discharge first; flywheels with negative charging priority and lower charging priority may not participate in charging scheduling (that is, flywheels with lower charging priority are ranked lower in power scheduling and may not be selected to participate in power output), thereby avoiding overcharging that leads to a decline in flywheel health (such as abnormal speed increase after overcharging, increasing the risk of mechanical wear and reducing flywheel lifespan).

[0053] For flywheels with zero equivalent high-speed operating time and zero equivalent high-power operating time and no faults, the charging and discharging priority is zero, and they do not need to participate in the charging and discharging operation.

[0054] In this way, for each flywheel in the flywheel array, the scheduling priority of the flywheel is evaluated by multi-dimensional operating status indicators. The information of each element and its interaction effect in the multi-dimensional operating status indicators is fully considered, which makes the evaluation of scheduling priority more detailed and accurate, provides a scientific basis for dynamic scheduling of flywheels, and helps to extend the service life of flywheels.

[0055] The following is a detailed explanation of Phase Three.

[0056] Step S50: In response to the power scheduling command, select target flywheels from the flywheel array to participate in power scheduling based on health and scheduling priority.

[0057] Dispatching of flywheel arrays includes external power dispatch, which refers to power dispatch initiated by control centers, operators, or market mechanisms outside the power system; that is, power dispatch commands are issued externally. In the case of external power dispatch, responding to the dispatch commands and considering the health and dispatch priority of each flywheel in the array, better dispatch decisions are made to improve power response speed, ensure the safe and reliable operation of the flywheels, and balance resource utilization and flywheel losses.

[0058] In some embodiments, please refer to Figure 3 Step S50 may include, but is not limited to, the following steps: S51: In response to the power scheduling command, the power scheduling command is parsed and processed to obtain the scheduling power demand; S52: Select candidate flywheels from the flywheel array that meet the scheduling power requirements based on scheduling priority; S53: When the scheduling priority of candidate flywheels is the same, select the minimum number of target flywheels that meet the scheduling power requirements from the candidate flywheels to participate in power scheduling based on the health of the candidate flywheels.

[0059] First, the power scheduling command is parsed to obtain the power scheduling requirement P. PF .

[0060] Then, an array selection mechanism is initiated. This mechanism prioritizes candidate flywheels based on their scheduling priority. If two or more candidate flywheels have the same scheduling priority, the next step is to select target flywheels based on their health status. If the health statuses of candidate flywheels are also the same, they are further sorted according to their initial numbers, until the minimum number of target flywheels that meet the scheduling power requirements are selected for power scheduling. In this array selection mechanism, scheduling priority has a higher weight than health status, and health status has a higher weight than initial number.

[0061] Therefore, candidate flywheels that meet the scheduling power requirements are selected from the flywheel array based on scheduling priority.

[0062] In step S52 of some embodiments, the flywheels can be sorted in descending order according to scheduling priority to obtain a flywheel candidate sequence; and candidate flywheels can be selected from the flywheel candidate sequence in a forward-backward order.

[0063] Specifically, all flywheels in the flywheel array can be sorted in descending order according to scheduling priority to generate a candidate flywheel sequence. Then, candidate flywheels that meet the scheduling power requirements are selected from the candidate flywheel sequence in a forward-to-back order. That is, candidate flywheels are selected from the flywheel array in descending order of scheduling priority until the total power of the selected candidate flywheels meets P. PF This ensures that flywheels with higher scheduling priority can be selected.

[0064] When the scheduling priority of candidate flywheels is ranked from high to low, quickly selecting candidate flywheels as target flywheels for power scheduling can reduce response time delay while meeting scheduling power requirements.

[0065] If candidate flywheels have the same scheduling priority (e.g., identical or both 0), they are sorted in descending order based on their health, generating a first sequence of candidate flywheels. Then, from this first sequence, the minimum number of target flywheels that meet the scheduling power requirements are selected for power scheduling. In other words, candidate flywheels with higher health are prioritized for power scheduling. This approach, considering both priority and health, effectively addresses the issue of multiple candidate flywheels having the same scheduling priority, ensuring the scientific and rational selection of target flywheels.

[0066] If candidate flywheels have the same health status, they are sorted in ascending order according to their initial numbers to generate a second sequence of candidate flywheels. Then, the minimum number of target flywheels that meet the scheduling power requirements are selected from the second sequence of candidate flywheels in a forward-to-back order to participate in power scheduling. In other words, the candidate flywheels with the earlier initial numbers are selected as target flywheels to participate in power scheduling.

[0067] In this way, the scheduling decisions of the flywheel array are optimized from the perspectives of health and priority, which can dynamically balance the load distribution of each flywheel in the flywheel array. This not only improves energy utilization efficiency but also extends the service life of the flywheels, enabling more intelligent and refined flywheel array operation scheduling.

[0068] To better understand the array filtering mechanism provided in the embodiments of the present invention, the following example is given: P PF The positive and negative signs represent the direction of discharge and charge, that is, P. PF When P > 0, it indicates that the power dispatch command indicates discharge (meaning output power), P PF When <0, it indicates that the power dispatch command indicates charging (meaning input power).

[0069] With P PFTaking a value greater than 0 as an example, the flywheels can be sorted in descending order according to their discharge priority to generate a candidate sequence of flywheels. Then, the flywheels that satisfy P can be selected from the candidate sequence in a forward-to-back order. PF Candidate flywheels.

[0070] Given a descending order of discharge priority among candidate flywheels, the candidate flywheels are quickly selected as target flywheels for power output. For example, if the maximum discharge power of each flywheel at the forefront of the candidate sequence (with higher discharge priority) is 1000kW, then when P... PF When the power output is 1800 kW, the two flywheels with the highest discharge priority (total discharge power of 2000 kW) will be selected to perform power output, ensuring that the two flywheels can meet the requirements of the power dispatch command.

[0071] If the discharge priority of the candidate flywheels is the same, then the selection is made by referring to the order of the candidate flywheels' health. The candidate flywheels with higher health are selected to participate in the discharge scheduling first. If the health is also the same, the one with the earlier initial number is selected.

[0072] Understandably, for a flywheel that has completed power output, if its speed and power drop to a preset reference rate and power and remain at that preset time, it means that it has successfully discharged and is in a safe state. Priority recovery processing can then be performed. That is, once its speed and power recover to the reference value, its charging and discharging priority is restored to 0. The recovery process is not performed in a step-like manner, but rather by using the aforementioned method of calculating charging and discharging priority. In other words, after completing power output, the corresponding charging and discharging priority is calculated in each sliding time window, so that the charging and discharging priority of the flywheel that has completed power output can gradually recover to 0, in order to prepare for the next round of power scheduling.

[0073] In some embodiments, the flywheel can also be optimized for standby based on health status and scheduling priority.

[0074] The scheduling of flywheel arrays includes non-external power scheduling. Non-external power scheduling refers to power management and scheduling performed internally by the generator set or flywheel array energy storage system based on its own status, operating strategy, or autonomous decision-making, without relying on external commands.

[0075] Without external power scheduling, the flywheel is optimized for standby by combining its health and scheduling priority, aiming to ensure that the flywheel can maintain good operating condition and lifespan in standby mode.

[0076] In some embodiments, optimizing the flywheel for standby based on health and scheduling priority can be achieved by: matching the flywheel's target standby speed according to health; generating a standby optimization order for the flywheel according to scheduling priority; and sequentially adjusting the flywheel's speed to the target standby speed according to the standby optimization order.

[0077] In the absence of external power scheduling, two objectives need to be achieved. The first objective is to match a suitable ideal standby speed (defined as the target standby speed) for each flywheel in the flywheel array based on its health status.

[0078] To facilitate differentiation and matching, a mapping relationship between health level and standby speed can be pre-established. The higher the health level, the faster the standby speed, and vice versa. Based on this mapping relationship, a target standby speed can be matched for each flywheel. For example, for flywheels with a health level ≥ 0.9, the target standby speed is matched to 7500 rpm; for flywheels with a health level between 0.8 and 0.9, the target standby speed is matched to 7000 rpm; and for flywheels with a health level < 0.8, the target standby speed is matched to 6500 rpm (the minimum sustaining speed).

[0079] This helps flywheels with high health maintain their rapid response capability, while reducing mechanical wear on flywheels with low health.

[0080] The second objective is to employ a rotational scheduling approach, performing SOC (System-on-Chip) active balancing on each flywheel array. Specifically, flywheels are sorted in descending order based on scheduling priority, generating a standby optimization sequence. That is, flywheels with higher scheduling priority are prioritized for optimization. Then, according to this optimization sequence, the speed of each flywheel is adjusted to its corresponding target standby speed. This ensures that flywheels with higher scheduling priority are adjusted to their target standby speed first, matching their health status. This guarantees that flywheels with high health can respond quickly, while protecting flywheels with low health and reducing their mechanical wear.

[0081] If multiple flywheels have the same discharge priority, they can be further sorted based on their speed deviation. Speed ​​deviation refers to the difference between the flywheel's current speed and the target standby speed that matches its health status. A flywheel with a larger speed deviation indicates a greater gap between its current speed and the target standby speed. Such flywheels will be given priority for charge-discharge balancing to restore themselves to their ideal state as quickly as possible.

[0082] This enables efficient SOC balancing operation, which not only improves energy efficiency but also extends the lifespan of the flywheel and maintains the overall health of the flywheel array energy storage system.

[0083] It is evident that the intelligent control method for flywheel arrays provided in this embodiment of the invention can bring the following beneficial effects: On the one hand, it can optimize the flywheel health evaluation system: For flywheel array energy storage systems, by innovatively introducing a dual evaluation mechanism of health and scheduling priority, the scheduling and use of each flywheel can be dynamically balanced, effectively avoiding the problem of accelerated aging caused by overuse of a single flywheel. Furthermore, since health can comprehensively quantify the entire life cycle status of the flywheel, and priority can comprehensively quantify the usage intensity of the flywheel, it can better reflect the actual health level of the flywheel compared to a single health indicator evaluation mechanism, and can effectively optimize the operation of the flywheel array.

[0084] On the other hand, it can solve the problem of "whipping the fast ox": the embodiments of the present invention design a scheduling priority decay mechanism based on the operating status, so that after a flywheel with high health continuously participates in power scheduling, its scheduling priority is automatically reduced, so that it enters a low-load "resting" state. After the scheduling priority is restored, it is reinstated into the high-priority scheduling sequence. This dynamic adjustment mechanism ensures the long-term health of high-performance flywheels and maintains the overall responsiveness and stability of the flywheel array.

[0085] On the other hand, it optimizes the standby control mechanism: in the absence of external scheduling, this embodiment dynamically matches the target standby speed based on the flywheel's health status, achieving a precise balance between response speed and mechanical losses. For flywheels with lower health status, their standby speed is automatically reduced to decrease bearing wear and energy consumption; for flywheels with good health status, a higher standby speed is maintained to ensure rapid response capability. Furthermore, the priority order for individual flywheel adjustments is selected based on scheduling priority, ensuring that the output of the grid connection does not deviate significantly, while allowing flywheels that need to "work" to slow down and rest as quickly as possible. This differentiated standby control mechanism avoids the ineffective losses caused by uniform high-speed standby and prevents response delays caused by low-speed standby, significantly improving the overall performance of the flywheel array under intermittent operating conditions.

[0086] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0087] Please see Figure 4 , Figure 4 This is a schematic block diagram of the structure of an intelligent control device for a flywheel array provided in an embodiment of the present invention.

[0088] like Figure 4 As shown, the intelligent control device 100 for the flywheel array includes: The health status indicator acquisition module 110 is used to acquire multi-dimensional health status indicators of the flywheels in the flywheel array. The health assessment module 120 allows the user to assess the health of the flywheel based on the multi-dimensional health status indicators, thereby obtaining the health status of the flywheel. The operation status indicator acquisition module 130 is used to acquire multi-dimensional operation status indicators of the flywheel; The priority evaluation module 140 is used to evaluate the scheduling priority of the flywheel based on the multi-dimensional operating status indicators to obtain the scheduling priority of the flywheel. The flywheel scheduling module 150 is used to respond to power scheduling commands and select target flywheels from the flywheel array to participate in power scheduling based on the health status and the scheduling priority.

[0089] In some embodiments, the flywheel scheduling module 150 is specifically used for: In response to a power scheduling command, the power scheduling command is parsed and processed to obtain the scheduling power demand; Candidate flywheels that meet the scheduling power requirements are selected from the flywheel array based on the scheduling priority. If the candidate flywheels have the same scheduling priority, the minimum number of target flywheels that meet the scheduling power requirements are selected from the candidate flywheels to participate in power scheduling based on the health status of the candidate flywheels.

[0090] In some embodiments, the flywheel scheduling module 150 is further configured to: In response to a power scheduling command, the power scheduling command is parsed and processed to obtain the scheduling power demand; Candidate flywheels that meet the scheduling power requirements are selected from the flywheel array based on the scheduling priority. Based on the health status of the candidate flywheels, the minimum number of target flywheels that meet the scheduling power requirements are selected from the candidate flywheels to participate in power scheduling.

[0091] In some embodiments, the multi-dimensional health status indicators include initial health status indicators, real-time health status indicators, and historical health status indicators. The health assessment module 120 is specifically used for: Based on the initial health status index, the initial health of the flywheel is calculated to obtain the initial health of the flywheel. The real-time health status of the flywheel is calculated based on the real-time health status indicators to obtain the real-time health status of the flywheel. The historical health status of the flywheel is calculated based on the historical health status indicators to obtain the historical health status of the flywheel. The initial health score, the real-time health score, and the historical health score are weighted and summed to obtain the health score.

[0092] In some embodiments, the multi-dimensional operating status indicators include high-speed equivalent operating time, high-power equivalent operating time, and fault status level. The priority evaluation module 140 is specifically used for: Based on the high-speed equivalent operating time, the high-power equivalent operating time, and the fault state level, the scheduling priority of the flywheel is calculated using a preset scheduling priority calculation formula to obtain the scheduling priority.

[0093] In some embodiments, the intelligent control device for the flywheel array further includes a standby optimization module, which is used for: Based on the health status and the scheduling priority, the flywheel is optimized for standby.

[0094] In some embodiments, the standby optimization module is specifically used for: The target standby speed of the flywheel is matched according to the health status; The standby optimization sequence of the flywheel is generated based on the scheduling priority; The flywheel speed is adjusted to the target standby speed in sequence according to the standby optimization order.

[0095] It should be noted that those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the intelligent control device for the flywheel array described above can be referred to the corresponding process in the aforementioned intelligent control method embodiment of the flywheel array, and will not be repeated here.

[0096] Please see Figure 5 , Figure 5 This is a schematic block diagram of the structure of a computer device provided in an embodiment of the present invention.

[0097] like Figure 5As shown, the computer device 200 includes a processor 201 and a memory 202, which are connected via a bus 203, such as an I2C (Inter-integrated Circuit) bus. Specifically, the processor 101 provides computing and control capabilities to support the operation of the entire computer device. The processor 101 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0098] Specifically, the memory 102 can be a Flash chip, a read-only memory (ROM) disk, an optical disk, a USB flash drive, or a portable hard drive, etc.

[0099] Those skilled in the art will understand that Figure 5 The structures shown are merely block diagrams of some structures related to the embodiments of the present invention, and do not constitute a limitation on the computer devices on which the embodiments of the present invention are applied. Specific computer devices may include more or fewer components than those shown in the figures, or combine certain components, or have different component arrangements.

[0100] The processor 101 is used to run a computer program stored in the memory 102, and to implement any of the intelligent control methods for the flywheel array provided in the embodiments of the present invention when executing the computer program.

[0101] In one embodiment, the processor 101 performs the following steps when executing a computer program: Obtain multi-dimensional health status indicators of flywheels in a flywheel array; The health status of the flywheel is evaluated based on the multi-dimensional health status indicators to obtain the health status of the flywheel. Obtain multi-dimensional operating status indicators of the flywheel; Based on the multi-dimensional operating status indicators, the scheduling priority of the flywheel is evaluated to obtain the scheduling priority of the flywheel. In response to a power scheduling command, a target flywheel is selected from the flywheel array to participate in power scheduling based on the health status and the scheduling priority.

[0102] In one embodiment, when the processor 101 implements the function of selecting target flywheels from the flywheel array to participate in power scheduling based on the health status and the scheduling priority in response to a power scheduling instruction, it is configured to: In response to a power scheduling command, the power scheduling command is parsed and processed to obtain the scheduling power demand; Candidate flywheels that meet the scheduling power requirements are selected from the flywheel array based on the scheduling priority. If the candidate flywheels have the same scheduling priority, the minimum number of target flywheels that meet the scheduling power requirements are selected from the candidate flywheels to participate in power scheduling based on the health status of the candidate flywheels.

[0103] In one embodiment, when the processor 101 selects candidate flywheels from the flywheel array that meet the scheduling power requirements based on the scheduling priority, it is configured to: The flywheels are sorted in descending order according to the scheduling priority to obtain a candidate flywheel sequence. The candidate flywheels are selected from the candidate flywheel sequence in a forward-to-back order.

[0104] In one embodiment, the multi-dimensional health status indicators include initial health status indicators, real-time health status indicators, and historical health status indicators. When the processor 101 evaluates the health of the flywheel based on the multi-dimensional health status indicators to obtain the health status of the flywheel, it performs the following: Based on the initial health status index, the initial health of the flywheel is calculated to obtain the initial health of the flywheel. The real-time health status of the flywheel is calculated based on the real-time health status indicators to obtain the real-time health status of the flywheel. The historical health status of the flywheel is calculated based on the historical health status indicators to obtain the historical health status of the flywheel. The initial health score, the real-time health score, and the historical health score are weighted and summed to obtain the health score.

[0105] In one embodiment, the multi-dimensional operating status indicators include high-speed equivalent operating time, high-power equivalent operating time, and fault status level. When the processor 101 evaluates the scheduling priority of the flywheel based on the multi-dimensional operating status indicators to obtain the scheduling priority of the flywheel, it is configured to: Based on the high-speed equivalent operating time, the high-power equivalent operating time, and the fault state level, the scheduling priority of the flywheel is calculated using a preset scheduling priority calculation formula to obtain the scheduling priority.

[0106] In one embodiment, the processor 101 further performs the following steps when executing a computer program: Based on the health status and the scheduling priority, the flywheel is optimized for standby.

[0107] In one embodiment, when the processor 101 performs standby optimization on the flywheel based on the health status and the scheduling priority, it is configured to: The target standby speed of the flywheel is matched according to the health status; The standby optimization sequence of the flywheel is generated based on the scheduling priority; The flywheel speed is adjusted to the target standby speed in sequence according to the standby optimization order.

[0108] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, performs the following steps: Obtain multi-dimensional health status indicators of flywheels in a flywheel array; The health status of the flywheel is evaluated based on the multi-dimensional health status indicators to obtain the health status of the flywheel. Obtain multi-dimensional operating status indicators of the flywheel; Based on the multi-dimensional operating status indicators, the scheduling priority of the flywheel is evaluated to obtain the scheduling priority of the flywheel. In response to a power scheduling command, a target flywheel is selected from the flywheel array to participate in power scheduling based on the health status and the scheduling priority.

[0109] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions on the computer device side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.

[0110] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0111] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0112] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method of intelligent control of a flywheel array, characterized by, include: Obtain multi-dimensional health status indicators of flywheels in a flywheel array; The health status of the flywheel is evaluated based on the multi-dimensional health status indicators to obtain the health status of the flywheel. Obtain multi-dimensional operating status indicators of the flywheel; Based on the multi-dimensional operating status indicators, the scheduling priority of the flywheel is evaluated to obtain the scheduling priority of the flywheel. In response to a power scheduling command, a target flywheel is selected from the flywheel array to participate in power scheduling based on the health status and the scheduling priority.

2. The intelligent control method for a flywheel array as described in claim 1, characterized in that, The step of responding to a power scheduling command and selecting target flywheels from the flywheel array to participate in power scheduling based on the health status and the scheduling priority includes: In response to a power scheduling command, the power scheduling command is parsed and processed to obtain the scheduling power demand; Candidate flywheels that meet the scheduling power requirements are selected from the flywheel array based on the scheduling priority. If the candidate flywheels have the same scheduling priority, the minimum number of target flywheels that meet the scheduling power requirements are selected from the candidate flywheels to participate in power scheduling based on the health status of the candidate flywheels.

3. The intelligent control method for flywheel arrays as described in claim 2, characterized in that, The step of selecting candidate flywheels from the flywheel array that meet the scheduling power requirements based on the scheduling priority includes: The flywheels are sorted in descending order according to the scheduling priority to obtain a candidate flywheel sequence. The candidate flywheels are selected from the candidate flywheel sequence in a forward-to-back order.

4. The intelligent control method for a flywheel array as described in claim 1, characterized in that, The multi-dimensional health status indicators include initial health status indicators, real-time health status indicators, and historical health status indicators. The process of evaluating the flywheel's health based on these multi-dimensional health status indicators to obtain the flywheel's health status includes: Based on the initial health status index, the initial health of the flywheel is calculated to obtain the initial health of the flywheel. The real-time health status of the flywheel is calculated based on the real-time health status indicators to obtain the real-time health status of the flywheel. The historical health status of the flywheel is calculated based on the historical health status indicators to obtain the historical health status of the flywheel. The initial health score, the real-time health score, and the historical health score are weighted and summed to obtain the health score.

5. The intelligent control method for a flywheel array as described in claim 1, characterized in that, The multi-dimensional operating status indicators include high-speed equivalent operating time, high-power equivalent operating time, and fault status level. The process of evaluating the scheduling priority of the flywheel based on these multi-dimensional operating status indicators to obtain the flywheel's scheduling priority includes: Based on the high-speed equivalent operating time, the high-power equivalent operating time, and the fault state level, the scheduling priority of the flywheel is calculated using a preset scheduling priority calculation formula to obtain the scheduling priority.

6. The intelligent control method for a flywheel array as described in claim 1, characterized in that, The method further includes: Based on the health status and the scheduling priority, the flywheel is optimized for standby.

7. The intelligent control method for a flywheel array as described in claim 6, characterized in that, The step of optimizing the flywheel for standby based on the health status and the scheduling priority includes: The target standby speed of the flywheel is matched according to the health status; The standby optimization sequence of the flywheel is generated based on the scheduling priority; The flywheel speed is adjusted to the target standby speed in sequence according to the standby optimization order.

8. An intelligent control device for a flywheel array, characterized in that, include: The health status indicator acquisition module is used to acquire multi-dimensional health status indicators of the flywheels in the flywheel array; The health assessment module allows users to evaluate the health of the flywheel based on the multi-dimensional health status indicators, thereby obtaining the health score of the flywheel. The operation status indicator acquisition module is used to acquire multi-dimensional operation status indicators of the flywheel; The priority evaluation module is used to evaluate the scheduling priority of the flywheel based on the multi-dimensional operating status indicators, and obtain the scheduling priority of the flywheel. The flywheel scheduling module is used to respond to power scheduling commands and select target flywheels from the flywheel array to participate in power scheduling based on the health status and the scheduling priority.

9. A computer device, characterized in that, The computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the intelligent control method for the flywheel array as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent control method for the flywheel array as described in any one of claims 1 to 7.

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