Flywheel and thermal power unit combined frequency modulation optimization control method and system based on device wear minimization

Abstract

This application discloses a method and system for joint frequency regulation optimization control of flywheel and thermal power units based on minimizing equipment wear. The method includes: real-time data acquisition; establishing a dynamic wear cost model for thermal power units based on thermomechanical theory and calibrating parameters using historical operation and maintenance data; setting the energy state update equation and energy recovery conditions for flywheel energy storage; constructing a joint optimization frequency regulation control model with the objective of minimizing the sum of frequency regulation error cost and equipment wear cost, and setting error cost weights and wear cost weights; adjusting the two weights in real time according to the flywheel energy update equation and engineering constraints; and finally solving for the optimal power command of thermal power units and flywheel energy storage under power balance conditions, dynamically adjusting their power sharing ratio. This method utilizes an adaptive weighting mechanism to enable the power system to automatically adjust the control strategy according to the intensity of grid disturbances and the degree of equipment wear, providing an efficient and reliable solution for joint frequency regulation of thermal power and energy storage.

Description

Technical Field

[0001] This application pertains to power system control methods, and more particularly to control methods for the coordinated operation of traditional energy and new energy power equipment. Background Technology

[0002] Driven by dual carbon targets, my country's new energy power generation industry has experienced explosive growth. Wind and solar power, with their core advantages of being clean and low-carbon, have seen their installed capacity and power generation share in the national power system continue to climb. However, the inherent technical characteristics of new energy power generation pose significant challenges to the power system: on the one hand, wind and solar power rely on power electronic converters for grid connection, lacking the rotational inertia of traditional synchronous generators, and thus cannot provide natural inertial support for the power grid; on the other hand, their output is affected by natural environmental factors, exhibiting strong randomness and uncertainty, leading to a continuous decrease in grid inertia levels and a significant increase in frequency fluctuation amplitude and frequency. This poses a serious threat to the frequency security and operational stability of the power system, and may even trigger a chain reaction, affecting power supply reliability.

[0003] Traditional thermal power units, as the largest existing adjustable power source in the current power grid, have long served as the core support for grid frequency regulation. However, in new power systems, the inherent characteristics of thermal power units are no longer suitable for the rapid power shortage demand caused by fluctuations in new energy sources—their internal structure is extremely complex and their own heat demand is large, resulting in long response times, slow load change rates, and low response accuracy. Gradually, they are unable to meet the grid frequency support requirements, affecting the safe and stable operation of the power system.

[0004] The increasing demand for frequency regulation has spurred the rapid development of energy storage technology. Utilizing its dynamic characteristics, energy storage technology can respond quickly and accurately to grid frequency regulation commands, making it highly feasible for assisting thermal power units in frequency regulation. In recent years, the energy storage technology market has seen rapid growth, with a wide variety of energy storage products and numerous research and applications of various energy storage methods. Flywheel energy storage, as a relatively new technology, stores electrical energy in the form of mechanical energy within a flywheel rotor. It features high power density, low environmental pollution, high conversion efficiency, long service life, low operating temperature requirements, and fewer charge / discharge cycles, demonstrating significant technical strength in the field of grid frequency regulation and enabling it to quickly compensate for the response shortcomings of thermal power units.

[0005] However, current traditional control methods for joint frequency regulation of flywheel energy storage and thermal power units still have significant limitations. Existing control strategies mostly focus on virtual droop control or virtual inertial control, or only on the real-time state-of-charge balance of the flywheel energy storage subsystem, taking the minimization of frequency regulation error as the single core objective, neglecting the mechanical wear and lifespan costs of thermal power units during frequent ramp-up processes, which has certain limitations. Therefore, there is an urgent need for a joint optimization control method that comprehensively considers the mechanical wear of thermal power units, so as to achieve synergistic optimization of equipment lifespan and operating economy while ensuring frequency regulation accuracy. Summary of the Invention

[0006] The purpose of this application is to overcome the shortcomings of the existing technology and propose a frequency regulation control method that can break through the limitation of traditional joint frequency regulation focusing only on a single objective, adapt to the rapid frequency regulation needs in the high-fluctuation scenario of new energy, and effectively reduce the life loss caused by frequent ramping of thermal power units.

[0007] Therefore, some embodiments of this application propose a joint frequency regulation optimization control method for flywheel and thermal power unit based on minimizing equipment wear, which includes the following steps:

[0008] Step S1: Collect AGC power commands from the power grid dispatch center in real time. Real-time output power of thermal power units is collected from the distributed control system of the thermal power units. And the state of charge of the flywheel energy storage subsystem is collected from the flywheel energy storage controller of the flywheel energy storage subsystem. The value of t, where t is the current control time;

[0009] Step S2: Establish a mathematical model of the dynamic wear cost of the thermal power unit based on thermomechanical theory;

[0010] Step S3: Use historical operation and maintenance data to calibrate the parameters of the dynamic wear cost mathematical model in order to dynamically adjust the dynamic wear cost mathematical model of the thermal power unit.

[0011] Step S4: Set the energy state update equation and energy recovery conditions for the flywheel energy storage subsystem;

[0012] Step S5: Based on the mathematical model of frequency modulation error cost and the mathematical model of wear cost, construct a joint optimization frequency modulation control objective function with the goal of minimizing the total cost W. As the objective function of the dual-objective optimization joint power allocation model, As the frequency modulation error cost weight, As the wear cost weight, and satisfying ; This represents the rate of change in power output of thermal power units. This refers to the real-time output power of the thermal power unit. The second-order change in the power of a thermal power unit is expressed as: ; α is the weighting coefficient of wear penalty for thermal power units in the primary term, β is the weighting coefficient of wear penalty for thermal power units in the secondary term, and Δt is the solution step size;

[0013] Step S6: Based on the energy state update equation of the flywheel energy storage subsystem, set the engineering boundary of the dual-objective optimization joint power allocation model as the operating constraint condition, and redetermine the frequency regulation error cost weight and wear cost weight in real time according to the dual-objective optimization joint power allocation model and the operating constraint condition.

[0014] Step S7: Based on the redefined frequency regulation error cost weight and wear cost weight, solve for the optimal power command of the thermal power unit and the flywheel energy storage subsystem under the premise of satisfying power balance, so as to dynamically adjust the power sharing ratio of the thermal power unit and the flywheel energy storage.

[0015] Other embodiments of this application provide a flywheel and thermal power unit joint frequency regulation optimization control system based on minimizing equipment wear, which includes a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0016] The technical effects of this invention include: The method is based on a dual-objective joint power allocation model considering both frequency regulation error cost and wear cost. The wear cost of thermal power units is a weighted function of the power change rate and the second-order power change. Therefore, when thermal power units experience rapid power fluctuations, their wear cost increases significantly. During the optimization process, to minimize wear cost while meeting frequency regulation accuracy constraints, the optimization strategy prioritizes assigning high-frequency regulation tasks with larger change rates to the flywheel energy storage subsystem, while assigning low-frequency power regulation tasks with gentler changes to the thermal power units. This naturally forms a collaborative regulation mechanism during system operation, where thermal power units handle low-frequency smooth regulation, and the flywheel handles high-frequency rapid regulation. This allows for dynamic adjustment of the collaborative division of labor between the thermal power units and the flywheel energy storage subsystem while ensuring frequency regulation quality. This significantly reduces unit ramp-up wear and effectively extends the lifespan of critical equipment. Furthermore, in the dual-objective joint power allocation model, an adaptive adjustment mechanism for the frequency regulation error weight and the wear cost weight is introduced. This allows for the dynamic adjustment of the weight ratio of the two components in the joint optimization model based on operating state parameters such as the AGC command change rate, real-time frequency regulation error, and the state of charge of the flywheel energy storage subsystem. When grid disturbances are large or frequency regulation errors increase, the frequency regulation error weight is increased to prioritize frequency regulation accuracy. When the grid is operating smoothly or the flywheel energy storage subsystem is approaching its energy boundary, the wear cost weight is increased to ensure smoother operation of the thermal power units, thereby achieving dynamic coordination between frequency regulation performance and equipment lifespan. Overall, this invention utilizes an adaptive weighting mechanism to enable the power system to automatically adjust its control strategy based on the intensity of grid disturbances and the degree of equipment aging, providing an efficient, reliable, and sustainable solution for joint frequency regulation of thermal power and energy storage systems. Attached Figure Description

[0017] Figure 1 This is a schematic diagram illustrating the principle of a flywheel and thermal power unit joint frequency regulation optimization control method based on minimizing equipment wear, according to an embodiment of this application.

[0018] Figure 2 This is a flowchart of a flywheel and thermal power unit joint frequency regulation optimization control method based on minimizing equipment wear, according to an embodiment of this application. Detailed Implementation

[0019] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0020] like Figure 1 , Figure 2 As shown, the flywheel and thermal power unit joint frequency regulation optimization control method based on minimizing equipment wear according to an embodiment of this application includes the following main steps:

[0021] Step S1: Collect signals from multiple sources, including the power grid dispatch center, the distributed control system (DCS) of the thermal power unit, and the flywheel energy storage controller.

[0022] Step S2: Establish a mathematical model of the dynamic wear cost of the thermal power unit based on thermomechanical theory;

[0023] Step S3: Use the historical operation and maintenance data of the thermal power unit to calibrate the parameters of the mathematical model of the dynamic wear cost in order to dynamically adjust the mathematical model of the wear cost of the thermal power unit.

[0024] Step S4: Set the energy state update equation and energy recovery conditions for the flywheel energy storage subsystem;

[0025] Step S5: Construct a joint optimization objective function for frequency modulation control based on the mathematical model of frequency modulation error cost and the mathematical model of wear cost, with the goal of minimizing the total cost W. As a dual-objective optimization joint power allocation model; where and These are the frequency modulation error cost weight and the wear cost weight, respectively, satisfying... ;

[0026] Step S6: Set the engineering boundary of the dual-objective optimization joint power allocation model as the operating constraint condition, and adjust the frequency modulation error cost weight and wear cost weight in real time according to the dual-objective optimization joint power allocation model and the operating constraint condition.

[0027] Step S7, online solution and frequency regulation execution, includes solving the optimal power command of the thermal power unit and the flywheel energy storage subsystem under the premise of satisfying power balance based on the re-determined frequency regulation error cost weight and wear cost weight, so as to dynamically adjust the power sharing ratio of the thermal power unit and the flywheel energy storage.

[0028] Step S1 further includes: collecting the following signals in real time through the power grid dispatch center, the distributed control system (DCS) of the thermal power unit, and the flywheel energy storage controller: Automatic Generation Control Command (AGC power command). Real-time output power of thermal power units State of charge of flywheel energy storage subsystem .

[0029] According to the AGC power command issued by the power grid dispatch center Calculate the rate of change of AGC power commands. ,Right now

[0030] .

[0031] Step S2 further includes the following: During frequency regulation, thermal power units mainly suffer from equipment wear due to frequent load disturbances, changes in boiler combustion rate leading to changes in metal temperature gradient, and mechanical stress cycles in the turbine, shaft system, and pipelines caused by power ramp-up. Therefore, based on thermomechanical theory, the mathematical model of the wear cost of thermal power units is established as a weighted integral of the power change rate and the power change acceleration, i.e.

[0032]

[0033] in, For the wear calculation time window, Let be the wear coefficient, where This represents the rate of change in power output of thermal power units. This represents the second-order change in the power output of thermal power units. These are the primary term thermal power unit wear penalty weighting coefficients and the secondary term thermal power unit wear penalty weighting coefficients, respectively.

[0034] Step S3 further includes, using historical operation and maintenance data of thermal power units, determining the parameters of a mathematical model for wear and tear costs. Calibration: Extract data from previous maintenance procedures of the thermal power unit. and sequence, This represents the rate of change in power output of thermal power units. For the second-order change of power of the thermal power unit, based on the wear cost J of the thermal power unit wear The mathematical model calculates the cumulative wear cost of the thermal power unit. The cumulative wear cost is established by associating the actual wear of components measured during the maintenance cycle corresponding to the cumulative wear cost. The mapping relationship between the actual wear amount and the cumulative wear cost is fitted using the least squares method to obtain the optimal primary term thermal power unit wear penalty weight coefficient, the secondary term thermal power unit wear penalty weight coefficient, and the wear coefficient. This allows for the dynamic adjustment of the mathematical model of the wear cost of the thermal power unit based on the wear degree of different equipment. The cumulative wear cost constitutes the latter half of the joint optimization frequency regulation control objective function.

[0035] The above model parameter calibration uses historical operation and maintenance data from different maintenance cycles for periodic updates. For example, after each maintenance, the latest calibration results are called for real-time calculation during frequency regulation operation.

[0036] Step S4 defines the energy state update equation and energy recovery condition of the flywheel energy storage subsystem, further including:

[0037] The energy state update equation for the flywheel energy storage subsystem is defined as follows:

[0038] Where Δt is the solution step size, The power command received by the flywheel energy storage subsystem. This refers to the rated energy of the flywheel energy storage subsystem.

[0039] The energy recovery conditions are set as follows: To prevent the flywheel from entering an overcharged / over-discharged state, the state of charge of the flywheel energy storage subsystem is set. The safety response range is ,like If the flywheel energy storage subsystem stops responding, it will perform low-power charging recovery; if If the flywheel energy storage subsystem stops responding, it will perform a low-power discharge recovery until... The value enters the safe response range.

[0040] Step S5: The objective function for the frequency modulation error cost satisfies: , This refers to the real-time output power of thermal power units. The power command received by the flywheel energy storage subsystem is used as the objective function for the frequency modulation error cost, which is defined as follows:

[0041]

[0042] Then, the joint optimization frequency modulation control objective function based on the objective function of frequency modulation error cost and the wear cost, with the goal of minimizing the total cost W, can be constructed as follows:

[0043] This is used as the objective function of the dual-objective optimization joint power allocation model;

[0044] in, For the wear calculation time window, and These are the frequency modulation error cost weight and the wear cost weight, respectively, satisfying... When the AGC power command change rate At that time, among them The maximum ramp rate of the unit represents the higher the system frequency regulation pressure and the more drastic the changes, the more appropriate the wear cost weight can be. This allows the flywheel energy storage subsystem to take on more frequency regulation tasks and achieve equipment protection.

[0045] Step S6 sets the running constraints, including:

[0046] Based on the energy state update equation of the flywheel energy storage subsystem defined above, the following engineering boundary conditions are added as constraints to the bi-objective optimization joint power allocation model to ensure the reliable operation of the power system:

[0047] ,in, This is the unit's maximum ramp rate. , These represent the lower and upper limits of the safe response range for the state of charge of the flywheel energy storage subsystem, respectively. This is the rated power of the flywheel energy storage subsystem.

[0048] If any constraint condition approaches triggering, the bi-objective optimization joint power allocation model will dynamically reduce the weight of the corresponding component, i.e., adjust the frequency modulation error cost weight. Or wear and tear cost weight The proportion of wear is reduced, thereby decreasing the equipment's involvement in frequency regulation power allocation. For example, when the AGC command change rate is large, the wear weight is dynamically increased, causing the flywheel to undertake more rapid adjustment tasks; when the thermal power unit's ramp rate... near At that time, the wear cost weight of the thermal power unit will be dynamically increased. Or reduce the frequency modulation error cost weight For example, when the flywheel energy storage subsystem... near or In this case, the contribution of the flywheel's frequency modulation error cost weight is dynamically reduced, or adjusted. and The proportion.

[0049] The aforementioned dual-objective optimization joint power allocation model is used to dynamically adjust the power sharing ratio between thermal power units and flywheel energy storage subsystems based on weight changes, while ensuring power balance. Through this continuous and adaptive weight adjustment mechanism, the model can dynamically adjust the power sharing ratio between thermal power units and flywheel energy storage subsystems, thereby achieving an optimal balance between frequency regulation performance and equipment lifespan loss while ensuring system safety and the feasibility of the optimization problem.

[0050] Step S7 may further include employing an online rolling optimization algorithm, according to the newly determined frequency modulation error cost weights. and wear and tear cost weight The joint optimization frequency regulation control objective function is solved in real time with a predetermined solution step size, such as h seconds, to obtain the optimal thermal power unit output. and flywheel energy storage subsystem target power Then, the target power of the flywheel energy storage subsystem obtained by the solution is... The power is transmitted to the flywheel converter controller for optimal thermal power unit output. The data is transmitted to the DCS of the thermal power unit for system regulation.

[0051] Other embodiments of this application provide a flywheel and thermal power unit joint frequency regulation optimization control system based on minimizing equipment wear, which includes a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program to implement any of the methods described above.

Claims

1. A flywheel and thermal power unit joint frequency regulation optimization control method based on minimizing equipment wear, characterized in that: Includes the following steps: Step S1: Collect AGC power commands from the power grid dispatch center in real time. Real-time output power of thermal power units is collected from the distributed control system of the thermal power units. And the state of charge of the flywheel energy storage subsystem is collected from the flywheel energy storage controller of the flywheel energy storage subsystem. The value of t is the current control time; Step S2: Establish a mathematical model of the dynamic wear cost of the thermal power unit based on thermomechanical theory; Step S3: Use historical operation and maintenance data to calibrate the parameters of the dynamic wear cost mathematical model in order to dynamically adjust the dynamic wear cost mathematical model of the thermal power unit. Step S4: Set the energy state update equation and energy recovery conditions for the flywheel energy storage subsystem; Step S5: Based on the mathematical model of frequency modulation error cost and the mathematical model of wear cost, construct a joint optimization frequency modulation control objective function with the goal of minimizing the total cost W. As the objective function of the dual-objective optimization joint power allocation model, As the frequency modulation error cost weight, As the wear cost weight, and satisfying ; This represents the rate of change in power output of thermal power units. This refers to the real-time output power of the thermal power unit. The second-order change in the power of a thermal power unit is expressed as: ; α is the weighting coefficient of wear penalty for thermal power units in the primary term, β is the weighting coefficient of wear penalty for thermal power units in the secondary term, and Δt is the solution step size; Step S6: Based on the energy state update equation of the flywheel energy storage subsystem, set the engineering boundary of the dual-objective optimization joint power allocation model as the operating constraint condition, and redetermine the frequency regulation error cost weight and wear cost weight in real time according to the dual-objective optimization joint power allocation model and the operating constraint condition. Step S7: Based on the redefined frequency regulation error cost weight and wear cost weight, solve for the optimal power command of the thermal power unit and the flywheel energy storage subsystem under the premise of satisfying power balance, so as to dynamically adjust the power sharing ratio of the thermal power unit and the flywheel energy storage.

2. The flywheel and thermal power unit joint frequency regulation optimization control method based on minimizing equipment wear according to claim 1, characterized in that: Step S1 further includes: according to the AGC power command issued by the power grid dispatch center. Based on the formula Calculate the rate of change of the AGC power command. .

3. The flywheel and thermal power unit joint frequency regulation optimization control method based on minimizing equipment wear according to claim 1, characterized in that: Step S2 further includes calculating the wear cost J of the thermal power unit. wear The mathematical model is established as a weighted integral of the rate of change of power and the acceleration of the change of power. ,in, For the wear calculation time window, Let be the wear coefficient, where This represents the rate of change in power output of thermal power units. This represents the second-order change in the power output of thermal power units. These are the primary term thermal power unit wear penalty weighting coefficients and the secondary term thermal power unit wear penalty weighting coefficients, respectively.

4. The flywheel and thermal power unit joint frequency regulation optimization control method based on minimizing equipment wear according to claim 3, characterized in that: Step S3 further includes using the historical operation and maintenance data to... Calibration: Extract data from previous maintenance procedures of the thermal power unit. and The sequence calculates the cumulative wear cost of the thermal power unit based on a mathematical model of the wear cost of the thermal power unit. The cumulative wear cost is established based on the actual wear of components measured during associated maintenance. The mapping relationship between the actual wear amount and the cumulative wear cost is fitted using the least squares method to obtain the optimal primary term thermal power unit wear penalty weight coefficient, the secondary term thermal power unit wear penalty weight coefficient, and the wear coefficient. This allows for the dynamic adjustment of the wear cost of the thermal power unit based on the wear level of different equipment, using a mathematical model.

5. The flywheel and thermal power unit joint frequency regulation optimization control method based on minimizing equipment wear according to claim 1, characterized in that: Step S4 further includes: Define the energy state update equation for the flywheel energy storage subsystem: ,in, The power command received by the flywheel energy storage subsystem; The power command received by the flywheel energy storage subsystem. This refers to the rated energy of the flywheel energy storage subsystem. The energy recovery condition is defined as: the state of charge of the flywheel energy storage subsystem. The safety response range is , , The states of charge of the flywheel energy storage subsystem are respectively The lower and upper limits of the safety response range; if at any time If the flywheel energy storage subsystem then exits the response and performs low-power charging recovery until... The value enters the safe response range; if at any time... If the flywheel energy storage subsystem then exits the response and performs low-power discharge recovery until any time... Entering the safe response zone.

6. The flywheel and thermal power unit joint frequency regulation optimization control method based on minimizing equipment wear according to claim 1, characterized in that: In step S5, the objective function for the frequency modulation error cost is defined as satisfying ,in, The power command received by the flywheel energy storage subsystem; P is the real-time output power of the thermal power unit. AGC (t) represents the AGC power command.

7. The flywheel and thermal power unit joint frequency regulation optimization control method based on minimizing equipment wear according to claim 1, characterized in that: Step S6 further includes: In the aforementioned dual-objective joint power allocation model, the following engineering boundary conditions are added as constraints to ensure the reliable operation of the power system: ,in, This represents the maximum ramp rate of the thermal power unit. , The states of charge of the flywheel energy storage subsystem are respectively The lower and upper limits of the safety response range; When any engineering boundary is approached, the weight coefficients corresponding to that engineering boundary in the bi-objective optimization joint power allocation model are dynamically adjusted so that the result returns to within the boundary.

8. The flywheel and thermal power unit joint frequency regulation optimization control method based on minimizing equipment wear according to claim 7, characterized in that: When the thermal power unit's ramp rate near At the same time, the wear cost weight of the thermal power unit is dynamically increased. Or reduce the frequency modulation error cost weight. ; When flywheel energy storage near or When this happens, the frequency regulation error cost weight of the flywheel energy storage subsystem is dynamically reduced. .

9. The flywheel and thermal power unit joint frequency regulation optimization control method based on minimizing equipment wear according to claim 1, characterized in that: Step S7 further includes employing an online rolling optimization algorithm to solve for the optimal thermal power unit output in real time according to the frequency regulation error cost objective function with a predetermined solution step size. and flywheel energy storage subsystem target power Then, the target power of the flywheel energy storage subsystem obtained by the solution is... The power is transmitted to the flywheel converter controller for optimal thermal power unit output. The data is transmitted to the distributed control system of the thermal power unit.

10. A flywheel and thermal power unit joint frequency regulation optimization control system based on minimizing equipment wear, characterized in that... It includes a processor and a memory, wherein the memory stores a computer program, and the processor executes the computer program to implement the method of any one of claims 1 to 9.

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