Flywheel array energy control method and device for auxiliary thermal power secondary frequency modulation, medium and product

Abstract

The invention discloses a flywheel array energy control method and device for auxiliary thermal power secondary frequency modulation, a medium and a product, and relates to the field of electric power frequency modulation, and the method comprises the steps that a turbine-boiler coordination control system cooperatively controls a steam turbine and a boiler according to a power instruction and an operation deviation. The energy management system carries out sorting according to the charge states of the flywheel groups, and dynamically selects an optimal group based on energy requirements in different frequency modulation periods; and when the optimal group does not meet the requirement, the suboptimal groups are put into use in sequence, and instructions are distributed according to the maximum chargeable and dischargeable power proportion. In the flywheel array, an improved weighted consistency algorithm is adopted, adaptive power distribution is carried out based on the state difference of adjacent units, a weight coefficient is associated with the state of charge, a state variable is converged to weighted average through iterative calculation, and a power instruction and the state of charge are updated. According to the invention, the charging and discharging frequency of the flywheel is reduced, the group calling process is optimized, the state-of-charge consistency of the flywheel monomers is enhanced, the continuous frequency modulation capability is improved, and the loss is reduced.

Description

Technical Field

[0001] This application relates to the field of power frequency regulation, and in particular to a flywheel array energy control method, device, medium and product for auxiliary thermal power secondary frequency regulation. Background Technology

[0002] Among various energy storage methods, flywheel energy storage systems (FESS) have broad application scenarios in auxiliary frequency regulation due to their rapid and efficient energy storage and release capabilities, high power density, and long lifespan. Due to the capacity limitations of a single flywheel and to improve system redundancy and reliability, multiple flywheels are typically connected in parallel to form a flywheel energy storage array for use in power systems. Under prolonged charge-discharge operation, the parameters and operating states of each unit within the flywheel array will inevitably become inconsistent, leading to differences in individual unit performance. Simply using an equal power distribution strategy will affect the overall power output characteristics of the flywheel, and may even cause premature aging of a single flywheel unit due to overuse. Improving the system's output characteristics and promoting the convergence of SOE (Power Output Equivalent) of each unit to its optimal range through reasonable array coordinated control methods is currently a research hotspot in energy storage array control.

[0003] In some situations, current flywheel energy storage arrays, when assisting in frequency regulation of thermal power plants, generally suffer from rigid group dispatch strategies that are difficult to adapt to dynamic frequency regulation requirements, leading to frequent charging and discharging of flywheel units. Simultaneously, the lack of an effective energy balancing mechanism within the array causes the differences in the state of charge of individual units to gradually widen. These problems not only exacerbate system losses but also restrict the ability of flywheel energy storage to continuously provide reliable frequency regulation services, affecting its overall operational economy and lifespan. Summary of the Invention

[0004] The purpose of this application is to provide a flywheel array energy control method, device, medium and product for auxiliary thermal power secondary frequency regulation, which can reduce the flywheel charging and discharging frequency, optimize the group calling process, enhance the consistency of the charge state of individual flywheels, improve the continuous frequency regulation capability and reduce losses.

[0005] To achieve the above objectives, this application provides the following solution: Firstly, this application provides an energy control method for flywheel arrays for auxiliary secondary frequency regulation of thermal power plants. The control method is applied to a load dynamic control model and an energy management system. The load dynamic control model and the energy management system control the thermal power unit and the flywheel energy storage unit, respectively. The load dynamic control model includes a digital electro-hydraulic control system, a boiler-turbine coordination control system, a boiler, and a steam turbine. The control method includes: acquiring power commands and sending them to the load dynamic control model and the boiler-turbine coordination control system; the boiler-turbine coordination control system determines the thermal power ratio weights based on the power commands and operating deviations, and uses these weights to control the operation of the steam turbine and the boiler, respectively; the energy management system autonomously sorts each flywheel group based on its state of charge and determines the required output energy during the target frequency regulation period. The optimal charge / discharge group is selected for frequency regulation. The flywheel group includes: optimal charge / discharge group, secondary charge / discharge group, basic charge / discharge group, and lowest charge / discharge group. When the optimal charge / discharge group cannot meet the demand, the subsequent secondary charge / discharge group, basic charge / discharge group, and lowest charge / discharge group are added sequentially, and instructions are allocated according to the maximum charge / discharge power ratio. The energy management system uses an improved weighted consensus algorithm within the flywheel energy storage array to perform adaptive power allocation based on the state difference between its own unit and adjacent units. The energy management system defines the diagonal elements of the weighting matrix as the flywheel power ratio weight associated with the state of charge of the energy storage unit, and iteratively calculates until the state variables converge to the weighted average. The energy management system updates the power instructions of each flywheel unit according to the frequency regulation period and synchronously refreshes the state of charge to dynamically control the flywheel energy storage array.

[0006] Secondly, this application provides a computer device, including: 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 above-described flywheel array energy control method for auxiliary thermal power secondary frequency regulation.

[0007] Thirdly, this application provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described flywheel array energy control method for secondary frequency modulation of auxiliary thermal power plants.

[0008] Fourthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the above-described flywheel array energy control method for secondary frequency modulation in auxiliary thermal power plants.

[0009] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application achieves precise joint control of thermal power units and flywheel energy storage units by coordinating a load dynamic control model with an energy management system (EMS). First, the Coordination Control System (CCS) receives power commands and, based on power and steam pressure deviations, uses preset proportional weights to coordinate the control of the turbine and boiler, ensuring rapid response of the thermal power unit to load changes. Simultaneously, the energy management system autonomously sorts the entire array based on the state of charge (SOC) of each flywheel unit, forming four charging and discharging groups from best to worst. According to the energy and power demands during different frequency regulation periods, the group with the best SOC is prioritized for frequency regulation; if its capacity is insufficient, subsequent groups are sequentially deployed. Commands are allocated proportionally based on the maximum chargeable and dischargeable power of each group, reducing the charging and discharging frequency of the flywheel groups, utilizing high-performance groups, and alleviating the pressure on low-performance groups. Within the flywheel array, the energy management system employs an improved weighted consensus algorithm, performing adaptive power allocation based on the difference in state of charge (SOC) between each individual unit and its neighboring units. By defining the diagonal elements of the weighting matrix as dynamic weights associated with the SOC, and through iterative calculation, the state variables converge to a weighted average. This approach not only completes the frequency modulation task but also promotes rapid convergence of the SOC among the individual units within the group. This application effectively reduces overall system losses and enhances the reliability and durability of the joint frequency modulation system while improving the continuous frequency modulation capability of the flywheel array and optimizing system operating economy. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart illustrating a flywheel array energy control method for secondary frequency regulation in auxiliary thermal power plants, provided in an embodiment of this application.

[0012] Figure 2 This is a schematic diagram of thermal power coordinated control provided in an embodiment of this application.

[0013] Figure 3 The diagram shows the frequency modulation results of the combined system during the 60-minute high-frequency period provided in this application embodiment.

[0014] Figure 3 (a1) in the figure is the output power curve of the four energy storage groups under the strategy of this application.

[0015] Figure 3 (a2) in the figure is the output power curve of the four energy storage groups under the comparison strategy.

[0016] Figure 3 (b1) in the figure is the SOC output curve of the four energy storage groups under the strategy of this application.

[0017] Figure 3 (b2) in the comparison strategy is the SOC output curve of the four energy storage groups.

[0018] Figure 3 (c1) is a graph showing the SOC variation of the nine flywheel units within group 1 under the strategy of this application.

[0019] Figure 3 (c2) is a curve showing the SOC change of the nine flywheel units within group 1 under the comparison strategy.

[0020] Figure 4 A comparison chart of the frequency modulation results of the 4h joint system provided in the embodiments of this application.

[0021] Figure 4 (a1) in the figure is the output power curve of the four energy storage groups under the strategy of this application.

[0022] Figure 4 (a2) in the figure is the output power curve of the four energy storage groups under the comparison strategy.

[0023] Figure 4 (b1) in the figure is the SOC output curve of the four energy storage groups under the strategy of this application.

[0024] Figure 4 (b2) in the comparison strategy is the SOC output curve of the four energy storage groups.

[0025] Figure 4 (c1) is a graph showing the SOC variation of the nine flywheel units within group 1 under the strategy of this application.

[0026] Figure 4 (c2) is a curve showing the SOC change of the nine flywheel units within group 1 under the comparison strategy.

[0027] Figure 5 The diagram shows the adaptive consistency control structure of the lower-level flywheel energy storage array SOC provided in the embodiments of this application.

[0028] Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0029] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0030] Current research mainly focuses on schemes such as proportional allocation based on SOE or loss indicators, and consistency allocation. These schemes allocate frequency regulation power proportionally based on the SOE of each energy storage unit to prevent overcharging and over-discharging of individual energy storage cells. With the goal of achieving consistency in the marginal cost of frequency regulation for each group of energy storage batteries, a balanced control strategy for energy storage arrays based on the equal loss micro-growth rate criterion has been developed, improving the sustainability and economy of energy storage participation in frequency regulation. Basic weights for energy storage units are set based on SOE, and consensus algorithms are further used to allocate the output of each unit, promoting the gradual convergence of SOE among the energy storage units. Some studies have added periodic event triggering and self-triggering control mechanisms to the average consensus, improving the stability and robustness of the system.

[0031] However, while current power allocation methods based on consensus and other algorithms have achieved state convergence at the information layer, they have failed to delve into the issue of controlling convergence by studying key physical quantities (such as SOE). Furthermore, they have failed to select groups according to the power and energy requirements of different frequency modulation periods to reduce energy storage losses, thus limiting their practical value in actual engineering projects.

[0032] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0033] Example 1, such as Figure 1 As shown, this embodiment provides a flywheel array energy control method for auxiliary thermal power secondary frequency regulation. The control method is applied to a load dynamic control model and an energy management system. The load dynamic control model and the energy management system are used to control the thermal power unit and the flywheel energy storage unit, respectively. The load dynamic control model includes: a digital electric hydraulic control system (DEH), a boiler-turbine coordination control system, a boiler, and a steam turbine. The control method includes the following steps.

[0034] S1. Obtain power commands and send them to the load dynamic control model and the boiler-turbine coordination control system.

[0035] Furthermore, the power command is a command issued based on the optimal thermal power and flywheel output allocation scheme.

[0036] In practical applications, based on the grid frequency regulation AGC requirements, the ramp-up rates of thermal power units and energy storage groups are estimated. Based on objectives such as frequency regulation performance and cost, output commands (power commands) for the thermal power units and flywheel arrays are obtained at various stages of secondary frequency regulation and are respectively sent to the CCS system of the thermal power units and the EMS system of the flywheel array. The EMS system of the flywheel energy storage array performs power distribution control on the lower-level systems.

[0037] S2. The turbine-boiler coordinated control system determines the thermal power ratio weight based on the power command and operating deviation, and uses the thermal power ratio weight to control the operation of the turbine and the boiler respectively.

[0038] In practical applications, the DEH, boiler, and turbine models adopt the typical structure of a 600MW supercritical unit. After the dispatch center sends the frequency regulation signal to the thermal power unit control center, the boiler-turbine coordinated control system (CCS) typically receives the AGC command and issues turbine commands TM and boiler commands BM to the turbine, DEH, and boiler control systems, respectively. A dynamic model of thermal power load using the integrated coordinated control system is constructed as follows: Figure 2 As shown in the figure, k1~k4 represent power commands. and actual output power Deviation, main steam pressure and actual value The deviation of the proportional weight of TM and BM collaborative control, the introduction of k5 can further accelerate the dynamic adjustment process, improve the output power response speed, and reduce the fluctuation of main steam pressure.

[0039] S3. The energy management system autonomously sorts each flywheel group based on the state of charge, and selects the optimal charge / discharge group to participate in frequency regulation according to the output energy required during the target frequency regulation period; the flywheel group includes: the optimal charge / discharge group, the secondary charge / discharge group, the basic charge / discharge group, and the least efficient charge / discharge group.

[0040] Furthermore, the formula for calculating the required output energy during the target frequency modulation period is as follows.

[0041] .

[0042] in, For the target frequency period The flywheel energy storage system requires output energy. For the target frequency period The ideal output power of the combined system; For thermal power Constant output power; and The target frequency modulation period The start and end times.

[0043] S4. When the optimal charge / discharge group cannot meet the demand, the subsequent secondary charge / discharge group, basic charge / discharge group and lowest charge / discharge group are added in sequence, and the instructions are allocated according to the ratio of the maximum chargeable / discharge power.

[0044] Furthermore, step S4 specifically includes the following steps.

[0045] S41. The energy management system determines whether the optimal charging and discharging group can independently meet the power and energy requirements of the current frequency regulation.

[0046] S42. If the optimal charge / discharge group is not satisfied, then the secondary charge / discharge group, the basic charge / discharge group, and the worst charge / discharge group are put into operation in sequence until the requirement is met.

[0047] S43. Each charging and discharging group participating in the output shall allocate instructions according to the proportion of maximum chargeable and dischargeable power, and respond to the frequency modulation requirements with the optimal array combination.

[0048] S5. The energy management system inside the flywheel energy storage array adopts an improved weighted consensus algorithm to perform adaptive power allocation based on the state difference between its own unit and adjacent units.

[0049] Furthermore, the expression for the improved weighted consensus algorithm is as follows.

[0050] .

[0051] In the formula, For the first Control variables for each flywheel group ; For the first Control variables for each flywheel group ; This is the iteration step size; It is a non-negative row random matrix; It is a weighted matrix; When the matrix is ​​an identity matrix, it is the standard average discrete consensus algorithm; for An identity matrix of order 1; For the corresponding The first-order Laplace matrix, For array adjacency matrix of order, for Rank matrix.

[0052] Furthermore, the expression for the maximum chargeable / dischargeable power ratio is as follows.

[0053] .

[0054] In the formula, This represents the output power of flywheel energy storage array 1; This is the output power of the flywheel energy storage array 2; This is the output power of the flywheel energy storage array 3; This is the output power of the flywheel energy storage array 4; The charge / discharge power of the optimal charge / discharge group; The charge / discharge power of this charge / discharge group; This refers to the charge / discharge power of the basic charge / discharge assembly. This represents the charge / discharge power of the lowest charge / discharge group. This is a power command.

[0055] In practical applications, the time scale and frequency modulation energy requirements vary significantly across different frequency modulation periods, resulting in different numbers of flywheel groups required. Furthermore, under prolonged charge-discharge operation, individual flywheels within each group inevitably exhibit performance differences, and the State of Charge (SOC) variations among individual units gradually increase. Therefore, this application designs an adaptive uniform power allocation strategy for the flywheel array. The control block diagram is shown below. Figure 5 As shown, the EMS receives power commands from the upper-level flywheel energy storage system, autonomously sorts the state of charge (SOC) of each individual unit, and selects the flywheel group with the optimal state to participate in frequency regulation based on the energy and power requirements of different frequency regulation periods. The local controller adaptively adjusts the participation ratio of each flywheel unit through an improved consistency algorithm, so that the flywheel group participates in frequency regulation while adjusting the state of charge of the individual units to be more consistent.

[0056] To illustrate the array control strategy, this application designs a flywheel energy storage system consisting of four flywheel arrays, each array consisting of nine flywheel units.

[0057] First, each flywheel array consists of nine individual flywheels, and the array's output characteristics are a combination of the characteristics of the nine flywheels. Based on the SOC value of each flywheel and its corresponding charge / discharge power constraints, the current stored energy and maximum charge / discharge power of each flywheel array can be obtained. By sorting the flywheel arrays accordingly, four groups of arrays are obtained: optimal charge / discharge group, secondary charge / discharge group, basic charge / discharge group, and lowest charge / discharge group, with stored energy arranged from highest to lowest. , , , The corresponding maximum charge and discharge powers are as follows: , , , The required energy storage capacity varies during different frequency regulation periods, thus the required number of flywheel arrays also varies. This application provides an approximate estimate of the energy required by the flywheel energy storage system during different frequency regulation periods based on the TPU output power and the ideal system output power curves.

[0058] in, The output energy required by the flywheel energy storage system during the startup, ramp-up, and steady-state phases are listed in order. For ideal output power, , This refers to the start and end times of the frequency modulation period.

[0059] Energy required for different frequency modulation periods and power commands First, it is determined whether the optimal charge / discharge group can meet the energy and power requirements. If the optimal charge / discharge group can meet both requirements, then that array alone will handle the frequency modulation power requirement. If it cannot meet the requirements, then the next three groups will be added sequentially until the energy and power requirements are met. For example, if three arrays—the optimal charge / discharge group, the secondary charge / discharge group, and the basic charge / discharge group—are required to meet the requirements, then the corresponding array will allocate power commands proportionally according to the current maximum discharge (charge) power, and the lowest charge / discharge group will not contribute power.

[0060] Secondly, considering the charging and discharging characteristics of the flywheel unit under different SOCs, the adjustment direction is based on the state difference between its own unit and the adjacent units, and the internal power of the array is adaptively allocated based on the weighted consensus algorithm.

[0061] S6. The energy management system defines the diagonal elements of the weighting matrix as the flywheel power ratio weights associated with the state of charge of the energy storage unit, and iterates the calculation until the state variables converge to the weighted average.

[0062] Furthermore, the expression for the diagonal elements of the weighted matrix is ​​as follows.

[0063] .

[0064] In the formula, For flywheel groups The diagonal elements of the weighted matrix; for Time Flywheel Group The internal flywheel's individual charge state is at its minimum; for Time Flywheel Group Maximum charge state of the inner flywheel unit; for Time Flywheel Group Internal flywheel unit charge state; This is a power command.

[0065] In practical applications, the model can perform iterative calculations to optimize state variables. Converging to the initial state The weighted average value is used, and the diagonal elements of the weighted matrix are defined as weighting coefficients related to the state of charge (SOC) of the energy storage unit. This allows the charging and discharging reference power of each energy storage unit to be determined by the amount of dischargeable or absorbable electricity, thereby improving the balance of utilization of each energy storage unit and realizing adaptive power allocation of each unit.

[0066] During charging, if the rated capacity of the energy storage unit is large and the SOC is low, it will have a larger weight and will bear a greater charging power; during discharging, if the rated capacity of the energy storage unit is large and the SOC is high, it will have a larger weight and will bear a greater discharging power.

[0067] Initial values ​​of the energy storage unit during each control cycle As shown in the following formula.

[0068] .

[0069] in, for 3D column vector; superscript Indicates the first One energy storage unit.

[0070] Will Substituting the values ​​into the model, the convergence value can be obtained. Then, the power command of each flywheel unit is calculated. As shown in the formula, the SOC of the corresponding flywheel unit is updated.

[0071] .

[0072] S7. The energy management system updates the power commands of each flywheel unit according to the frequency regulation period and refreshes the state of charge synchronously to dynamically control the flywheel energy storage array.

[0073] As an optional implementation, to verify the effectiveness of the strategy in this application, comparative strategy 1 is selected. The upper power optimization layer is consistent with this application, and the lower layer allocates the array power of each group according to the remaining frequency regulation energy of each group, while the output of each individual unit is allocated according to the SOC size within each group. Outlier processing and K-means clustering analysis were performed on the flywheel-thermal power combined AGC frequency regulation data of a power plant from July 2023 to March 2024. Simulations were conducted on typical time periods of 60 minutes and 4 hours, and the results are as follows: Figures 3-4 As shown.

[0074] Depend on Figure 3 (a1), 3 (a2) Figure 3 (b1) Figure 3 (b2) Figure 4 (a1) Figure 4 (a2) Figure 4(b1) Figure 4 (b2) It can be seen that the control strategy proposed in this application can reasonably call the corresponding flywheel groups according to the SOC sorting rules, promote the SOC of each group to tend to the optimal range, ensure the continuity of system power point tracking, and reduce the start-stop frequency of flywheel groups, thereby reducing system losses; while the four arrays under control strategy 3, which outputs power according to the remaining frequency modulation energy, need to frequently start and stop in response to AGC commands. At the same time, under the SOC allocation rules, the high frequency modulation capability groups are not fully utilized, and the lower frequency modulation capability groups may further deteriorate, resulting in SOC that is too low or too high. Figure 3 (c1), 3 (c2) Figure 4 (c1) Figure 4 (c2) As can be seen, compared with strategy 3, the SOC of each individual unit within the group under the improved consistent load allocation strategy based on SOC change rate proposed in this application tends to be consistent faster, that is, it approaches the optimal range faster and provides greater frequency regulation capability.

[0075] Table 1 shows the SOC (State of Charge) of the flywheel array under the proposed strategy and Strategy 3 during a typical 4-hour frequency modulation period. , The lowest and highest values ​​of SOC for each individual within each group throughout the entire time period are listed in order. The root mean square of the SOC of the nine flywheel units within the group is calculated in each sampling period with a squared deviation of 0.5. Four groups The root mean square of the squared deviation from 0.5 in each sampling period. It can be seen that Strategy 3, which allocates power according to SOC, causes some flywheel cells to exceed the upper and lower limits, with a minimum SOC of 0.056 and a maximum of 0.902, while the minimum SOC of the cells under the strategy of this application is 0.189 and a maximum of 0.870; Meanwhile, under Strategy 3, the SOC of each group... The sum is 4.648, while this application is 2.739, a reduction of 41.07%; furthermore, the differences between the four groups... It also decreased from 0.893 to 0.246, effectively promoting the SOC of each monomer and group. Approaching the optimal range, it significantly improves the safety of energy storage and the sustainability of frequency regulation.

[0076] In summary, the EMS system designed in this application can select the minimum but optimal response frequency-modulated flywheel group based on the frequency modulation capability of each flywheel unit, and allocate the power of each unit within the group based on the consistency algorithm of the SOC change rate. This promotes the consistency of the remaining energy of each flywheel subsystem and the consistency of the SOC of each flywheel unit. In addition, through the self-recovery strategy during the non-test period, the SOC of each flywheel unit can be promoted to approach the optimal range, which improves the sustainability of the flywheel array frequency modulation, reduces system losses, and enhances the robustness of the flywheel energy storage system.

[0077] Table 1 Comparison of SOC equalization effects of flywheel arrays

[0078] The technical effects of this application are as follows.

[0079] This application achieves precise joint control of thermal power units and flywheel energy storage units by coordinating a load dynamic control model with an energy management system. First, the boiler-turbine coordinated control system receives power commands and, based on power and steam pressure deviations, uses preset proportional weights to coordinate the control of the turbine and boiler, ensuring rapid response of the thermal power unit to load changes. Simultaneously, the energy management system autonomously sorts the entire array based on the state of charge of each flywheel unit, forming four charging and discharging groups from best to worst. According to the energy and power demands during different frequency regulation periods, the group with the best state is prioritized for frequency regulation; if its capacity is insufficient, subsequent groups are deployed sequentially. Commands are allocated proportionally based on the maximum chargeable and dischargeable power of each group, reducing the charging and discharging frequency of the flywheel groups, utilizing high-performance groups and alleviating the pressure on low-performance groups. Within the flywheel array, the energy management system employs an improved weighted consensus algorithm, performing adaptive power allocation based on the difference in state of charge (SOC) between each individual unit and its neighboring units. By defining the diagonal elements of the weighting matrix as dynamic weights associated with the SOC, and through iterative calculation, the state variables converge to a weighted average. This approach not only completes the frequency modulation task but also promotes rapid convergence of the SOC among the individual units within the group. This application effectively reduces overall system losses and enhances the reliability and durability of the joint frequency modulation system while improving the continuous frequency modulation capability of the flywheel array and optimizing system operating economy.

[0080] Example 2: This application also provides a computer device, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 6 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores and processes data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements the methods described above.

[0081] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0082] Example 3: This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.

[0083] Example 4: This application also provides a computer program product, including a computer program that, when executed by a processor, implements the methods described above.

[0084] Those skilled in the art will understand that all or part of the processes in 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 described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0085] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0086] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A flywheel array energy control method for auxiliary thermal power secondary frequency modulation, characterized in that, The control method is applied to a load dynamic control model and an energy management system; the load dynamic control model and the energy management system are respectively used for controlling a thermal power unit and a flywheel energy storage unit; The load dynamic control model comprises a digital electro-hydraulic control system, a boiler-turbine coordinated control system, a boiler and a steam turbine; the control method comprises: a power instruction is obtained and is sent to the load dynamic control model and the boiler-turbine coordinated control system; the boiler-turbine coordinated control system determines a thermal power proportion weight according to the power instruction and an operation deviation, and controls the steam turbine and the boiler to operate respectively by using the thermal power proportion weight; the energy management system autonomously sorts each flywheel group based on a state of charge, and selects a state-optimal charging and discharging group to participate in frequency modulation according to required output energy of a target frequency modulation period; the flywheel group comprises an optimal charging and discharging group, a secondary charging and discharging group, a basic charging and discharging group and a last charging and discharging group; when the optimal charging and discharging group cannot meet the requirement, the subsequent secondary charging and discharging group, the basic charging and discharging group and the last charging and discharging group are sequentially added, and a maximum chargeable power proportion distribution instruction is used; the energy management system uses an improved weighted consistency algorithm to perform adaptive power distribution based on a state difference between a self unit and an adjacent unit inside the flywheel energy storage array; the energy management system defines a diagonal element of a weighted matrix as a flywheel power proportion weight associated with a state of charge of the energy storage unit, and performs iterative calculation until the state variable converges to a weighted average; the energy management system updates a power instruction of each flywheel unit according to the target frequency modulation period, and synchronously refreshes the state of charge to dynamically control the flywheel energy storage array.

2. The flywheel array energy control method for auxiliary thermal power secondary frequency modulation according to claim 1, characterized in that, The power instruction is an instruction sent based on an optimal thermal power and flywheel output distribution scheme.

3. The flywheel array energy control method for auxiliary thermal power secondary frequency modulation according to claim 1, characterized in that, The energy management system determines required output energy according to the target frequency modulation period, when the optimal charging and discharging group cannot meet the requirement, the subsequent secondary charging and discharging group, the basic charging and discharging group and the last charging and discharging group are sequentially added, and a maximum chargeable power proportion distribution instruction is used, which specifically comprises: the energy management system judges whether the optimal charging and discharging group can independently meet power and energy requirements of current frequency modulation; if the optimal charging and discharging group does not meet the requirement, the secondary charging and discharging group, the basic charging and discharging group and the last charging and discharging group are sequentially added until the requirement is met; each charging and discharging group participating in output uses a maximum chargeable power proportion distribution instruction to respond to frequency modulation requirements in an optimal array combination.

4. The flywheel array energy control method for auxiliary thermal power secondary frequency modulation according to claim 1, characterized in that, A calculation formula of the required output energy of the target frequency modulation period is as follows: ； in, For the target frequency period The power output required by the flywheel energy storage system For the target frequency period The ideal output power of the combined system; For thermal power Constant output power; and The target frequency modulation period The start and end times.

5. The flywheel array energy control method for auxiliary thermal power secondary frequency modulation according to claim 1, characterized in that, An expression of the improved weighted consistency algorithm is as follows: ； wherein is the control variable of the jth flywheel group ; ; is the control variable of the jth flywheel group ; ; is the iteration step size; is a non-negative row stochastic matrix; is a weighting matrix; is the standard average-discrepancy-consensus algorithm when is the identity matrix; is an identity matrix of order ; is the corresponding Laplacian matrix of order , is the adjacency matrix of the array of order , is the degree matrix of order .

6. The flywheel array energy control method for auxiliary thermal power secondary frequency modulation according to claim 1, characterized in that, An expression of the maximum chargeable power proportion is as follows: ； wherein Pout1 is the output power of flywheel energy storage array 1; Pout2 is the output power of flywheel energy storage array 2; Pout3 is the output power of flywheel energy storage array 3; Pout4 is the output power of flywheel energy storage array 4; Pcharge1 is the chargeable power of the optimal chargeable group; Pcharge2 is the chargeable power of the sub-optimal chargeable group; Pcharge3 is the chargeable power of the basic chargeable group; Pcharge4 is the chargeable power of the sub-sub-optimal chargeable group; Pcommand is the power command.

7. The flywheel array energy control method for auxiliary thermal power secondary frequency modulation according to claim 1, characterized in that, An expression of the diagonal element of the weighted matrix is as follows: ； wherein is the diagonal element of the weighting matrix for the flywheel group ; is the minimum state of charge of the flywheel cells within the flywheel group at the time instant ; is the maximum state of charge of the flywheel cells within the flywheel group at the time instant ; is the state of charge of the flywheel cells within the flywheel group at the time instant ; is the power command.

8. A computer device comprising: A memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor executes the computer program to implement the flywheel array energy control method for auxiliary thermal power secondary frequency modulation according to any one of claims 1-7.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the flywheel array energy control method for auxiliary thermal power secondary frequency modulation according to any one of claims 1-7.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to realize the flywheel array energy control method for auxiliary thermal power secondary frequency modulation in any one of claims 1-7.

Images