Frequency modulation optimization method and device of automatic power generation control system, and electronic equipment

Abstract

The invention provides a frequency modulation optimization method and device for an automatic power generation control system and electronic equipment, and the method comprises the steps: carrying out the index improvement processing of an obtained performance index of a to-be-optimized control system, and obtaining a first control system; the performance indexes of the to-be-optimized control system at least comprise thermotechnical control system parameters, adjusting speed, response time and adjusting precision, and the performance index of the first control system meets a first preset design condition; and loop optimization processing is carried out on the primary frequency modulation adjusting loop of the first control system, a target control system is obtained, and the primary frequency modulation adjusting loop of the target control system meets a second preset design condition. According to the embodiment of the invention, the performance indexes such as the thermotechnical control system parameters, the adjustment rate, the response time and the adjustment precision of the to-be-optimized system are firstly improved, and then the loop optimization processing is performed on the system after the performance indexes are improved, so that the frequency modulation efficiency and the frequency modulation precision of the frequency modulation link can be improved when the target control system is subjected to frequency modulation.

Description

Technical Field

[0001] The present disclosure relates to the field of electrical processing technology, and in particular to a frequency modulation optimization method and device for an automatic power generation control system, and electronic equipment. Background Art

[0002] Automatic Generation Control (AGC) is an important part of modern power systems. Its main function is to automatically adjust the output power of the generator according to the changes in the grid load to maintain the stability of the grid frequency. The AGC system usually includes the following parts: measurement unit, control unit, execution unit and communication unit. In the automatic generation control system, the frequency regulation link plays a vital role. The main task of the frequency regulation link is to adjust the speed of the generator so that the output frequency of the generator is consistent with the grid frequency.

[0003] The frequency modulation link is the core of the AGC system. Its purpose is to control the frequency of the power grid by adjusting the speed of the generator. The application of the frequency modulation method enables the power system to respond quickly to load fluctuations and maintain frequency stability. However, in the prior art, the frequency modulation link often relies on fixed control parameters and is difficult to adapt to rapidly changing load demands. When the load changes suddenly, the response time of the existing frequency modulation link is long, resulting in large frequency fluctuations. At the same time, due to the limitations of the control algorithm, the existing frequency modulation link has deficiencies in regulation accuracy and is difficult to meet the requirements of high-precision frequency control.

[0004] Therefore, how to optimize the existing frequency modulation link to improve the frequency modulation efficiency and frequency modulation accuracy of the frequency modulation link is a problem that needs to be solved urgently. Summary of the invention

[0005] The present invention provides a frequency modulation optimization method and device and electronic equipment for an automatic power generation control system, and its main purpose is to solve the problem of how to optimize the existing frequency modulation link to improve the frequency modulation efficiency and frequency modulation accuracy of the frequency modulation link.

[0006] According to a first aspect of the present disclosure, a frequency regulation optimization method for an automatic power generation control system is provided, comprising:

[0007] Performing an index improvement process on the obtained performance index of the control system to be optimized to obtain a first control system; wherein the performance index of the control system to be optimized at least includes a thermal control system parameter, a regulation rate, a response time, and a regulation accuracy, and the performance index of the first control system meets a first preset design condition;

[0008] A loop optimization process is performed on the primary frequency modulation regulation loop of the first control system to obtain a target control system, wherein the primary frequency modulation regulation loop of the target control system satisfies a second preset design condition.

[0009] Optionally, performing an indicator improvement process on the acquired performance indicator of the control system to be optimized to obtain the first control system includes:

[0010] Performing parameter optimization processing on the thermal control system parameters in the performance index to obtain target thermal control system parameters; wherein the target thermal control system parameters meet preset thermal parameter conditions;

[0011] Performing differentiated design processing on the regulation rate in the performance indicator to obtain a target regulation rate; wherein the target regulation rate satisfies a preset regulation rate condition;

[0012] Performing response optimization processing on the response time in the performance indicator to obtain a target response time; wherein the target response time satisfies a preset response time condition;

[0013] Performing precision optimization processing on the regulation precision in the performance index to obtain a target regulation precision; wherein the target regulation precision satisfies a preset regulation precision condition;

[0014] The control system to be optimized is subjected to system optimization processing according to the target thermal control system parameters, the target regulation rate, the target response time and the target regulation accuracy to obtain the first control system.

[0015] Optionally, performing parameter optimization processing on the thermal control system parameters in the performance indicators to obtain target thermal control system parameters includes:

[0016] The K1 value, K2 value and K3 value of the thermal control system parameters are optimized by a first preset optimization algorithm to obtain the target thermal control system parameters; wherein the K1 value is a proportional gain, the K2 value is an integral gain, and the K3 value is a differential gain;

[0017] The target thermal control system parameter satisfies the preset thermal parameter conditions including: the comprehensive index KP of the target thermal control system parameter is ≥2.3, and the minimum index of the target thermal control system parameter is ≥1.8.

[0018] Optionally, performing differentiated design processing on the regulation rate in the performance indicator to obtain a target regulation rate includes:

[0019] Determine the equipment unit controlled by the control system to be optimized; wherein the control system to be optimized controls a plurality of the equipment units;

[0020] The load regulation range corresponding to each of the equipment units is determined respectively, and the regulation rate of each of the equipment units is subjected to differentiated design processing according to the load regulation range to obtain the target regulation rate corresponding to each of the equipment units.

[0021] Optionally, performing response optimization processing on the response time in the performance indicator to obtain a target response time includes:

[0022] Based on the target adjustment rate, the response time is subjected to response optimization processing by a second preset optimization algorithm to obtain the target response time;

[0023] The target response time satisfies the preset response time condition including: if the target adjustment rate is greater than or equal to 50% Pe, the target response time should be less than 60 seconds;

[0024] If the target regulation rate is less than 50% Pe, the target response time should be less than 75 seconds.

[0025] Optionally, performing precision optimization processing on the regulation precision in the performance indicator to obtain a target regulation precision includes:

[0026] Based on the target adjustment rate, the adjustment accuracy is optimized by a third preset optimization algorithm to obtain the target adjustment accuracy;

[0027] The target regulation accuracy satisfies the preset regulation accuracy condition including: if the target regulation rate corresponding to the target equipment unit is greater than or equal to 50%Pe, the target regulation accuracy should be less than 1% of the rated power of the target equipment unit; wherein the target equipment unit is any unit among all the equipment units;

[0028] If the target regulation rate corresponding to the target equipment group is less than 50% Pe, the target regulation accuracy should be less than 1.25% of the rated power of the target equipment group.

[0029] Optionally, performing loop optimization processing on the primary frequency modulation regulation loop of the first control system to obtain a target control system includes:

[0030] Acquire grid parameters of a target grid, and perform loop optimization processing on a primary frequency regulation loop of the first control system through a fourth preset optimization algorithm based on the grid parameters to obtain the target control system; wherein the target grid is a grid connected to the first control system;

[0031] The primary frequency modulation regulation loop of the target control system meets the second preset design condition including: the response lag time of the primary frequency modulation regulation loop of the target control system should be less than 2 seconds, and the stabilization time of the primary frequency modulation of the primary frequency modulation regulation loop of the target control system should be less than 60 seconds;

[0032] The time for the primary frequency regulation loop of the target control system to achieve 75% of the target load should be no more than 15 seconds, and the time for the primary frequency regulation loop of the target control system to achieve 90% of the target load should be no more than 30 seconds;

[0033] The primary frequency modulation speed inequality rate of the primary frequency modulation regulation loop of the target control system should be greater than or equal to 4% and less than or equal to 5%.

[0034] According to a second aspect of the present disclosure, a frequency regulation optimization device for an automatic power generation control system is provided, comprising:

[0035] An improving unit is used to perform an indicator improvement process on the obtained performance indicators of the control system to be optimized to obtain a first control system; wherein the performance indicators of the control system to be optimized at least include thermal control system parameters, adjustment rate, response time, and adjustment accuracy, and the performance indicators of the first control system meet the first preset design conditions;

[0036] The optimization unit is used to perform loop optimization processing on the primary frequency modulation regulation loop of the first control system to obtain a target control system, wherein the primary frequency modulation regulation loop of the target control system meets a second preset design condition.

[0037] Optionally, the lifting unit includes:

[0038] An optimization module, used for performing parameter optimization processing on the thermal control system parameters in the performance index to obtain target thermal control system parameters; wherein the target thermal control system parameters meet preset thermal parameter conditions;

[0039] A processing module, used for performing a differentiated design process on the regulation rate in the performance indicator to obtain a target regulation rate; wherein the target regulation rate satisfies a preset regulation rate condition;

[0040] The optimization module is also used to perform response optimization processing on the response time in the performance indicator to obtain a target response time; wherein the target response time satisfies a preset response time condition;

[0041] The optimization module is further used to perform precision optimization processing on the adjustment precision in the performance index to obtain a target adjustment precision; wherein the target adjustment precision satisfies a preset adjustment precision condition;

[0042] The optimization module is also used to perform system optimization processing on the control system to be optimized according to the target thermal control system parameters, the target adjustment rate, the target response time and the target adjustment accuracy to obtain the first control system.

[0043] Optionally, the optimization module is further used for:

[0044] The K1 value, K2 value and K3 value of the thermal control system parameters are optimized by a first preset optimization algorithm to obtain the target thermal control system parameters; wherein the K1 value is a proportional gain, the K2 value is an integral gain, and the K3 value is a differential gain;

[0045] The target thermal control system parameter satisfies the preset thermal parameter condition including: the comprehensive index KP of the target thermal control system parameter is ≥2.3, and the minimum index of the target thermal control system parameter is ≥1.8.

[0046] Optionally, the processing module is further used for:

[0047] Determine the equipment unit controlled by the control system to be optimized; wherein the control system to be optimized controls a plurality of the equipment units;

[0048] The load regulation range corresponding to each of the equipment units is determined respectively, and the regulation rate of each of the equipment units is subjected to differentiated design processing according to the load regulation range to obtain the target regulation rate corresponding to each of the equipment units.

[0049] Optionally, the optimization module is further used for:

[0050] Based on the target adjustment rate, the response time is subjected to response optimization processing by a second preset optimization algorithm to obtain the target response time;

[0051] The target response time satisfies the preset response time condition including: if the target adjustment rate is greater than or equal to 50% Pe, the target response time should be less than 60 seconds;

[0052] If the target regulation rate is less than 50% Pe, the target response time should be less than 75 seconds.

[0053] Optionally, the optimization module is further used for:

[0054] Based on the target adjustment rate, the adjustment accuracy is optimized by a third preset optimization algorithm to obtain the target adjustment accuracy;

[0055] The target regulation accuracy satisfies the preset regulation accuracy condition including: if the target regulation rate corresponding to the target equipment unit is greater than or equal to 50%Pe, the target regulation accuracy should be less than 1% of the rated power of the target equipment unit; wherein the target equipment unit is any unit among all the equipment units;

[0056] If the target regulation rate corresponding to the target equipment group is less than 50% Pe, the target regulation accuracy should be less than 1.25% of the rated power of the target equipment group.

[0057] Optionally, the optimization unit includes:

[0058] An acquisition module, used for acquiring grid parameters of a target grid;

[0059] an optimization module, configured to perform loop optimization processing on the primary frequency regulation loop of the first control system through a fourth preset optimization algorithm based on the power grid parameters to obtain the target control system; wherein the target power grid is a power grid connected to the first control system;

[0060] The primary frequency modulation regulation loop of the target control system meets the second preset design condition including: the response lag time of the primary frequency modulation regulation loop of the target control system should be less than 2 seconds, and the stabilization time of the primary frequency modulation of the primary frequency modulation regulation loop of the target control system should be less than 60 seconds;

[0061] The time for the primary frequency regulation loop of the target control system to achieve 75% of the target load should be no more than 15 seconds, and the time for the primary frequency regulation loop of the target control system to achieve 90% of the target load should be no more than 30 seconds;

[0062] The primary frequency modulation speed inequality rate of the primary frequency modulation regulation loop of the target control system should be greater than or equal to 4% and less than or equal to 5%.

[0063] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0064] at least one processor; and

[0065] a memory communicatively connected to the at least one processor; wherein,

[0066] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect.

[0067] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the first aspect.

[0068] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method as described in the first aspect above.

[0069] The frequency modulation optimization method, device, and electronic device of the automatic power generation control system provided by the present disclosure perform index improvement processing on the performance indicators of the control system to be optimized to obtain a first control system; wherein the performance indicators of the control system to be optimized include at least thermal control system parameters, regulation rate, response time, and regulation accuracy, and the performance indicators of the first control system meet the first preset design conditions; the primary frequency modulation regulation loop of the first control system is optimized to obtain a target control system, wherein the primary frequency modulation regulation loop of the target control system meets the second preset design conditions. Compared with the related art, the embodiment of the present disclosure first improves the performance indicators such as the thermal control system parameters, regulation rate, response time, and regulation accuracy of the system to be optimized, and then optimizes the primary frequency modulation regulation loop of the system after the performance indicators are improved, i.e., the first control system, so that the target control system finally obtained can improve the frequency modulation efficiency and frequency modulation accuracy of the frequency modulation link when performing frequency modulation.

[0070] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0072] Figure 1 A flow chart of a frequency regulation optimization method of an automatic power generation control system provided by an embodiment of the present disclosure;

[0073] Figure 2 A schematic diagram of a process flow for improving an indicator provided by an embodiment of the present disclosure;

[0074] Figure 3 A schematic diagram of the structure of a frequency regulation optimization device of an automatic power generation control system provided by an embodiment of the present disclosure;

[0075] Figure 4 A structural schematic diagram of another frequency regulation optimization device of an automatic power generation control system provided by an embodiment of the present disclosure;

[0076] Figure 5 A schematic block diagram of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0077] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0078] The frequency regulation optimization method and device and electronic equipment of the automatic power generation control system according to the embodiments of the present disclosure are described below with reference to the accompanying drawings.

[0079] Figure 1 A flow chart of a frequency regulation optimization method for an automatic power generation control system provided in an embodiment of the present disclosure.

[0080] like Figure 1 As shown, the method comprises the following steps:

[0081] Step 101, perform index improvement processing on the obtained performance indicators of the control system to be optimized to obtain a first control system; wherein the performance indicators of the control system to be optimized include at least thermal control system parameters, adjustment rate, response time, and adjustment accuracy, and the performance indicators of the first control system meet the first preset design conditions.

[0082] In the disclosed embodiments, the performance indicators of the control system to be optimized include but are not limited to: Thermal control system parameters: These parameters include PID control parameters such as proportion (K1), integration (K2), and differentiation (K3), which determine the dynamic behavior and stability of the control system. Regulation rate: refers to the speed at which the control system regulates load changes. Different types of generator sets may require different AGC regulation rates. Response time: The time required for the control system to actually reach the target load after receiving a load change instruction, including the time to reach 75% and 90% of the target load. Regulation accuracy: The accuracy of the control system when regulating the load, that is, the size of the load error during the regulation process.

[0083] Index improvement processing refers to optimizing and adjusting the performance indicators of the control system to be optimized to improve the overall performance of the system. The process of index improvement processing can be implemented in the following ways, but not limited to: Adjust PID parameters (K1, K2, K3) to optimize the response speed and stability of the control system. According to the characteristics and operating conditions of the unit, set the appropriate adjustment rate to ensure fast and effective load adjustment. By optimizing the control system logic and algorithm, reduce the response time to meet the requirements of fast frequency regulation. Improve the adjustment accuracy, reduce the adjustment error, and ensure the accuracy of the system during load adjustment.

[0084] The first control system is a control system obtained after the control system to be optimized has been processed to improve its indicators. The performance indicators of the first control system have been optimized compared to the control system to be optimized, and can better meet the operation requirements of the power system.

[0085] The first preset design condition is a custom designed condition, which is the performance standard that the optimized control system (i.e., the first control system) needs to meet. It is a set of pre-set goals, including but not limited to: the KP value after the thermal control system parameters are optimized should reach 2.3, and the minimum should not be less than 1.8. The regulation rate should adapt to the load regulation range of different units. The response time should meet the requirement that the time to reach 75% of the target load is no more than 15 seconds, and the time to reach 90% of the target load is no more than 30 seconds. The regulation accuracy should be less than 1.25% of the rated power of the unit when it is below 50% Pe.

[0086] The performance of the first control system obtained through the index improvement process will be significantly improved, and it can participate in automatic generation control (AGC) more effectively, thereby maintaining the stability and reliability of the power grid.

[0087] Step 102: performing loop optimization processing on the primary frequency modulation regulation loop of the first control system to obtain a target control system, wherein the primary frequency modulation regulation loop of the target control system satisfies a second preset design condition.

[0088] In the disclosed embodiment, the primary frequency regulation loop of the first control system refers to the regulation part in the first control system specifically used for primary frequency regulation, which is responsible for automatically adjusting the output power of the generator when the grid frequency deviates from the rated value to restore the grid frequency to the set range.

[0089] Among them, the loop optimization processing of the primary frequency regulation loop aims to improve the performance of the primary frequency regulation loop and ensure that the primary frequency regulation loop can better meet the frequency regulation requirements of the power grid. Regarding the loop optimization processing, the following methods can be used but are not limited to: Parameter adjustment: Optimize PID control parameters (K1, K2, K3) or other related control parameters to improve the dynamic response and stability of the regulation loop. Logic improvement: Improve the control logic, reduce delays and fluctuations in the regulation process, and improve the regulation efficiency. Algorithm optimization: Use more advanced control algorithms to improve regulation accuracy and response speed. Hardware upgrade: If necessary, it may include upgrading hardware such as actuators and sensors to improve the physical performance of the regulation loop.

[0090] The target control system is a control system obtained after loop optimization processing of the first control system. Compared with the first control system, the primary frequency modulation regulation loop of the target control system has been optimized according to preset design conditions and can perform frequency modulation tasks more effectively.

[0091] The second preset design condition is some pre-customized conditions, which are the performance standards that the optimized primary frequency regulation loop needs to meet, including but not limited to: Response lag time: The response lag time of primary frequency regulation should be less than 2 seconds to ensure that the system can quickly detect frequency changes and start regulation. Stabilization time: The stabilization time of primary frequency regulation should be less than 60 seconds, that is, the system can reach a stable state within 60 seconds after adjustment. Load response speed: The time to reach 75% of the target load is no more than 15 seconds, and the time to reach 90% of the target load is no more than 30 seconds, ensuring that the system can quickly reach the predetermined load level. Speed ​​​​inequality rate: The speed inequality rate of primary frequency regulation should be 4% to 5%. This is to ensure that the fluctuation of the generator speed during the adjustment process is within a reasonable range.

[0092] Through loop optimization processing, the primary frequency regulation loop of the target control system will be able to respond to changes in grid frequency more accurately and quickly, thereby improving the frequency quality of the grid and ensuring stable operation of the grid.

[0093] The frequency regulation optimization method of the automatic power generation control system provided by the present disclosure performs an index improvement process on the performance index of the control system to be optimized to obtain a first control system; wherein the performance index of the control system to be optimized includes at least thermal control system parameters, regulation rate, response time, and regulation accuracy, and the performance index of the first control system meets the first preset design condition; the primary frequency regulation regulation loop of the first control system is subjected to loop optimization processing to obtain a target control system, wherein the primary frequency regulation regulation loop of the target control system meets the second preset design condition. Compared with the related art, the embodiment of the present disclosure first performs an improvement process on the performance indexes such as the thermal control system parameters, regulation rate, response time, and regulation accuracy of the system to be optimized, and then performs a frequency regulation regulation loop optimization process on the system after the performance index is improved, i.e., the first control system, so that the target control system finally obtained can improve the frequency regulation efficiency and frequency regulation accuracy of the frequency regulation link when performing frequency regulation.

[0094] In one possible implementation of the embodiment of the present disclosure, regarding the indicator improvement processing of the performance indicator of the control system to be optimized, the embodiment of the present disclosure provides a flowchart of the indicator improvement processing, such as Figure 2 As shown, including:

[0095] Step 201 , performing parameter optimization processing on the thermal control system parameters in the performance index to obtain target thermal control system parameters; wherein the target thermal control system parameters meet preset thermal parameter conditions.

[0096] In the disclosed embodiment, the thermal control system parameters refer to the PID (proportional-integral-differential) parameters used for regulating and controlling the process in the thermal control system, including: proportional gain (K1), integral time (K2), differential time (K3), etc. The thermal control system parameters directly affect the response speed, stability and regulation accuracy of the control system.

[0097] Parameter optimization is a systematic project, which involves the adjustment and optimization of the existing thermal control system parameters, with the purpose of improving the overall performance of the control system. Regarding the parameter optimization process, the following methods can be used but are not limited to: Step 1: System data analysis: Extract thermal control system parameters, including but not limited to key process parameters such as temperature, pressure, flow, and speed. Analyze historical data to identify performance bottlenecks and unstable factors of the system during the adjustment process. Step 2: Establish a mathematical model: Establish a mathematical model for the thermal control system parameters (including: the process flow and control logic of the thermal control system), including the dynamic model of the controlled object and the mathematical model of the controller. Determine the model parameters, such as time constant, gain, lag, etc. Step 3: Parameter sensitivity analysis: Perform parameter sensitivity analysis on the established mathematical model, and determine the parameters that have the greatest impact on system performance as key parameters. By changing the values ​​of key parameters, observe the changes in system performance, and provide a basis for subsequent optimization. Step 4: Set the optimization goal: According to the system performance requirements, set the optimization goal, that is, the preset thermal parameter conditions, for example: increase the K1 (proportional gain), K2 (integral gain), K3 (differential gain) values ​​to ensure that the comprehensive average index KP ≥ 2.3, and the minimum index is not less than 1.8. Determine the priority and weight of the optimization goal in order to make a trade-off in multi-objective optimization. Step 5: Select the optimization algorithm: According to the complexity of the system and the optimization goal, select a suitable optimization algorithm, such as: particle swarm optimization (PSO), genetic algorithm (GA), simulated annealing (SA), etc. Step 6: Implement parameter optimization: Use the selected optimization algorithm to optimize the thermal control system parameters. Step 7: Verify the optimization results: Apply the optimized parameter values, that is, the target thermal control system parameters, to the mathematical model, perform simulation tests, and verify whether the system performance reaches the optimization goal.

[0098] The target thermal control system parameters are thermal control system parameters that have been optimized, and the target thermal control system parameters have been adjusted to a level that can better meet the control system performance requirements.

[0099] The preset thermal parameter conditions are custom set conditions, which are the performance standards that the optimized thermal control system parameters need to meet. For example, the comprehensive average index KP of the target thermal control system parameters should not be less than 2.3, and the minimum index should not be less than 1.8, which can reflect the overall performance level of the control system.

[0100] The target thermal control system parameters obtained through parameter optimization will be able to more effectively control the power generation process, improve the system's regulation efficiency, reduce response time, and increase regulation accuracy, thereby ensuring the stability and reliability of the power system. These optimized parameters will help the control system better cope with changes in grid load and keep grid frequency and tie line power within the specified range.

[0101] Step 202: Perform differentiated design processing on the regulation rate in the performance indicator to obtain a target regulation rate; wherein the target regulation rate satisfies a preset regulation rate condition.

[0102] In the disclosed embodiment, the regulation rate in the performance index refers to the speed at which the control system to be optimized regulates the output power of the generator in response to load changes. Under different power system operating conditions, the demand for the regulation rate may be different. The speed of the regulation rate directly affects the recovery speed of the grid frequency and the stability of the system.

[0103] Differentiated design processing of the regulation rate refers to customized design and adjustment of the regulation rate according to different generator set characteristics, grid requirements and environmental conditions. The process of differentiated design processing can be adopted but not limited to the following methods: Demand analysis: Analyze the roles and tasks of different generator sets in the grid to determine their requirements for the regulation rate. Characteristic evaluation: Evaluate the technical characteristics of each generator set, such as response speed, stability and maximum regulation capacity. Rate setting: Set appropriate regulation rates for different generator sets based on the results of demand analysis and characteristic evaluation. Dynamic adjustment: Design a dynamic adjustment mechanism so that the regulation rate can be adjusted in real time according to the actual operating conditions of the grid.

[0104] The target regulation rate is the regulation rate after the differentiated design processing, and the target regulation rate has been optimized to adapt to the specific generator set and power grid operating conditions.

[0105] The preset regulation rate conditions are custom set conditions, which are performance standards that the regulation rate needs to meet after optimization, including but not limited to: Fast response: When the grid frequency deviates, the regulation rate should be able to respond quickly to reduce the frequency deviation. Stability: While the regulation rate responds quickly, it should not cause system instability or excessive oscillation. Differentiation: For different generator sets, the regulation rates should be different to give full play to their respective advantages and adapt to different operating modes. Flexibility: The regulation rate should have a certain degree of flexibility and be able to be adjusted appropriately according to changes in the grid load.

[0106] The target regulation rate obtained through differentiated design processing will be able to better adapt to the dynamic changes of the power grid, improve the regulation efficiency of the power system, reduce frequency fluctuations, and ensure the stable operation of the power grid. This design method helps to improve the overall performance of the power system, especially in dealing with sudden load changes and maintaining the stability of the power grid frequency.

[0107] Step 203, performing response optimization processing on the response time in the performance indicator to obtain a target response time; wherein the target response time satisfies a preset response time condition.

[0108] In the disclosed embodiment, the response time in the performance indicator refers to the time required for the control system to be optimized to detect load changes or frequency deviations and start taking regulatory measures. It is a key indicator to measure the rapidity of the control system to be optimized and is crucial to the stable operation of the power system.

[0109] Response optimization of response time refers to reducing the response time of the system to load changes or frequency deviations by adjusting the configuration, parameters or algorithms of the control system to be optimized. The process of response optimization of response time can be adopted but not limited to the following methods: System diagnosis: Analyze the response time of the control system to be optimized and identify factors that may cause delays. Parameter adjustment: Optimize PID control parameters, especially proportional gain and differential gain, to speed up the response speed of the system. Algorithm improvement: Improve the control algorithm, such as: adopt advanced control strategies such as predictive control and fuzzy control to reduce response time. Hardware upgrade: Upgrade the hardware of the control system to be optimized when necessary, such as: use a faster data processing unit or a more efficient sensor.

[0110] The target response time is the response time after response optimization processing, and is the expected performance indicator of the control system to be optimized after optimization.

[0111] The preset response time conditions are custom set conditions, which are performance standards that the optimized response time needs to meet, including but not limited to: Minimize delay: The response time should be as short as possible to meet the needs of fast frequency regulation. Specific time requirements: For example, the time to reach 75% of the target load is no more than 15 seconds, and the time to reach 90% of the target load is no more than 30 seconds. Balance between stability and speed: While reducing the response time, it is necessary to ensure that the stability and regulation accuracy of the system are not affected.

[0112] The target response time obtained through response optimization processing will be able to meet the dual requirements of the power system for rapidity and stability. The optimized control system will be able to respond to changes in the power grid load more quickly, thereby effectively maintaining the stability of the power grid frequency and improving the overall performance and reliability of the power system. This optimization is of great significance for improving the dynamic performance of the power system and its ability to respond to emergencies.

[0113] Step 204, performing precision optimization processing on the regulation precision in the performance index to obtain a target regulation precision; wherein the target regulation precision satisfies a preset regulation precision condition.

[0114] In the disclosed embodiment, the regulation accuracy in the performance index refers to the accuracy of the control system to be optimized to reach the expected set value during the regulation process. In the power system, the regulation accuracy directly affects the stability of the grid frequency and the accuracy of the output power of the generator set.

[0115] The purpose of the precision optimization processing of the regulation accuracy is to improve the accuracy of the regulation result of the control system to be optimized through a series of measures. Regarding the process of precision optimization processing of the regulation accuracy, the following methods can be adopted but are not limited to: Data analysis: Collect and analyze the regulation data of the control system to be optimized to identify the source of the regulation error. Parameter fine-tuning: Fine-tune the PID control parameters, including proportional gain, integral time and differential time, to reduce the regulation error. Filtering algorithm: Apply or optimize the filtering algorithm to reduce the impact of noise and interference on the regulation accuracy. Feedback correction: Improve the feedback mechanism to ensure the accuracy and real-time performance of the feedback signal, thereby improving the regulation accuracy. Control logic optimization: Optimize the control logic to reduce delays and errors in the logic judgment and execution process.

[0116] The target regulation accuracy is the regulation accuracy after the accuracy optimization process, and is the expected performance indicator of the control system to be optimized after optimization.

[0117] The preset adjustment accuracy conditions are custom set conditions, which are performance standards that the adjustment accuracy needs to meet after optimization, including but not limited to: Error range: The adjustment accuracy should be within a specific error range. For example, when the adjustment accuracy is below 50% Pe, it should be less than 1.25% of the rated power of the unit. Stability: While improving the adjustment accuracy, it is necessary to maintain the stability of the system to avoid system oscillation caused by over-adjustment. Consistency: Under different operating conditions, the adjustment accuracy should remain consistent and not be affected by external factors such as temperature and humidity.

[0118] The target regulation accuracy obtained through precision optimization processing will be able to better meet the power system's requirements for regulation accuracy. The optimized control system will be able to more accurately control the generator's output power, reduce frequency fluctuations, and improve the operation quality of the power grid. This optimization is of great significance for improving the regulation performance of the power system and ensuring the safe and stable operation of the power grid.

[0119] Step 205 , performing system optimization processing on the control system to be optimized according to the target thermal control system parameters, the target regulation rate, the target response time, and the target regulation accuracy to obtain the first control system.

[0120] In the disclosed embodiment, the basis for optimizing the control system to be optimized is that the optimized system, i.e., the first control system, includes the following performances: Target thermal control system parameters: PID control parameters after parameter optimization can improve the control efficiency and stability of the system. Target regulation rate: The regulation rate after differentiated design can meet the regulation requirements under different working conditions. Target response time: The response time after response optimization can ensure that the system responds quickly to load changes. Target regulation accuracy: The regulation accuracy after accuracy optimization can improve the accuracy of system regulation.

[0121] Therefore, compared with the control system to be optimized, the first control system has the following characteristics: higher control efficiency and control accuracy. Faster response speed and more appropriate adjustment rate. Good stability and reliability can be maintained under different operating conditions. It can better meet the requirements of the power system for automatic generation control (AGC) and ensure the stable operation of the power grid.

[0122] The first control system obtained through system optimization processing will be able to improve the overall performance and operating efficiency of the system while ensuring the safe, stable and efficient operation of the power system.

[0123] In one implementable manner of the embodiment of the present disclosure, when performing parameter optimization processing on the thermal control system parameters, it can also be implemented in but not limited to the following manner: optimizing the K1 value, K2 value and K3 value of the thermal control system parameters by a first preset optimization algorithm to obtain the target thermal control system parameters; wherein the K1 value is the proportional gain, the K2 value is the integral gain, and the K3 value is the differential gain; the target thermal control system parameters satisfying the preset thermal parameter conditions include: the comprehensive index KP of the target thermal control system parameters is ≥2.3, and the minimum index of the target thermal control system parameters is ≥1.8.

[0124] In the embodiment of the present disclosure, the first preset optimization algorithm is an algorithm customized according to actual conditions, such as: Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Simulated Annealing (SA), etc. Specifically, the embodiment of the present disclosure does not limit the first preset optimization algorithm.

[0125] In one implementable manner of the embodiment of the present disclosure, when performing differentiated design processing on the regulation rate, it can also be implemented in but not limited to the following manner: determine the equipment unit controlled by the control system to be optimized; wherein the control system to be optimized controls multiple equipment units; respectively determine the load regulation range corresponding to each of the equipment units, and perform differentiated design processing on the regulation rate of each of the equipment units according to the load regulation range to obtain the target regulation rate corresponding to each of the equipment units.

[0126] In the disclosed embodiment, each equipment unit will have different load regulation capabilities due to differences in its technical characteristics, operating status, design parameters and other factors. Therefore, it is necessary to set a load regulation range for each equipment unit, and the load regulation range defines the limit within which the unit can safely and effectively regulate the load under normal operating conditions. Since the load regulation range of each equipment unit is different, the regulation rates of different equipment units also need to be designed accordingly. The differentiated design process includes but is not limited to: adjusting the PID parameters of the control system, optimizing the control strategy, introducing advanced control algorithms, etc., to ensure that each equipment unit can respond quickly and accurately to load changes within its load regulation range.

[0127] The equipment units include but are not limited to: direct-blowing pulverizing system drum boiler units, intermediate storage pulverizing system units, circulating fluidized bed units and units burning special types of coal (such as: inferior coal, high-moisture and low-calorific value lignite, etc.), supercritical constant pressure operation direct current furnace units, etc.

[0128] Among them, considering the differences in the load regulation ranges of deep peak load regulation units (i.e., different equipment units have different load regulation ranges), different types of units correspond to different regulation rate requirements. The regulation rate requirements corresponding to different types of units can be shown in Table 1:

[0129] Table 1

[0130]

[0131] In one implementable manner of the embodiment of the present disclosure, when performing response optimization processing on the response time, it can also be implemented in but not limited to the following manner: based on the target regulation rate, the response time is response optimized by a second preset optimization algorithm to obtain the target response time; the target response time satisfies the preset response time condition including: if the target regulation rate is greater than or equal to 50% Pe, then the target response time should be less than 60 seconds; if the target regulation rate is less than 50% Pe, then the target response time should be less than 75 seconds.

[0132] In an embodiment of the present disclosure, the second preset optimization algorithm is a custom-set algorithm, such as: Model Predictive Control algorithm (MPC), fuzzy logic control algorithm (FLC), PID parameter self-tuning algorithm, gain scheduling control (Gain Scheduling Control), etc. Specifically, with respect to the second preset optimization algorithm, the present disclosure does not impose any restrictions.

[0133] In one implementable manner of the embodiment of the present disclosure, when the precision optimization processing is performed on the regulation accuracy, it can also be implemented in but not limited to the following manner: based on the target regulation rate, the precision optimization processing is performed on the regulation accuracy through a third preset optimization algorithm to obtain the target regulation accuracy; the target regulation accuracy satisfies the preset regulation accuracy conditions including: if the target regulation rate corresponding to the target equipment unit is greater than or equal to 50% Pe, then the target regulation accuracy should be less than 1% of the rated power of the target equipment unit; wherein the target equipment unit is any unit among all the equipment units; if the target regulation rate corresponding to the target equipment unit is less than 50% Pe, then the target regulation accuracy should be less than 1.25% of the rated power of the target equipment unit.

[0134] In the embodiment of the present disclosure, the third preset optimization algorithm is a custom-set algorithm, such as: Recursive Least Squares (RLS), H-Infinity Control, Adaptive Control, etc. Specifically, the embodiment of the present disclosure does not limit the third preset optimization algorithm.

[0135] In an implementable manner of the embodiment of the present disclosure, when performing loop optimization processing on the primary frequency modulation regulation loop of the first control system, it can also be implemented in but not limited to the following manner: obtaining the grid parameters of the target grid, and performing loop optimization processing on the primary frequency modulation regulation loop of the first control system based on the grid parameters through a fourth preset optimization algorithm to obtain the target control system; wherein the target grid is a grid connected to the first control system; the primary frequency modulation regulation loop of the target control system satisfies the second preset design condition including: the response lag time of the primary frequency modulation regulation loop of the target control system should be less than 2 seconds, and the primary frequency stabilization time of the primary frequency modulation of the primary frequency modulation regulation loop of the target control system should be less than 60 seconds; the time for the primary frequency modulation regulation loop of the target control system to reach 75% of the target load by frequency modulation should be no more than 15 seconds, and the time for the primary frequency modulation regulation loop of the target control system to reach 90% of the target load by frequency modulation should be no more than 30 seconds; the primary frequency modulation speed inequality rate of the primary frequency modulation regulation loop of the target control system should be greater than or equal to 4% and less than or equal to 5%.

[0136] In the embodiment of the present disclosure, the fourth preset optimization algorithm is a custom set algorithm, for example: Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Simulated Annealing (SA), Fuzzy Logic Control (FLC), etc. Specifically, the embodiment of the present disclosure does not limit the fourth preset optimization algorithm.

[0137] In summary, the embodiments of the present disclosure can achieve the following effects:

[0138] The disclosed embodiment first improves the thermal control system parameters, regulation rate, response time, regulation accuracy and other performance indicators of the system to be optimized, and then performs a frequency regulation loop optimization process on the system after the performance indicators are improved, i.e., the first control system. This can improve the frequency regulation efficiency and frequency regulation accuracy of the frequency regulation link when the target control system is finally frequency modulated.

[0139] Corresponding to the above-mentioned frequency regulation optimization method of the automatic power generation control system, the present invention also proposes a frequency regulation optimization device of the automatic power generation control system. Since the device embodiment of the present invention corresponds to the above-mentioned method embodiment, the details not disclosed in the device embodiment can be referred to the above-mentioned method embodiment, and will not be repeated in the present invention.

[0140] Figure 3 A schematic diagram of the structure of a frequency modulation optimization device of an automatic power generation control system provided by an embodiment of the present disclosure, such as Figure 3As shown, including:

[0141] The improvement unit 31 is used to perform an indicator improvement process on the obtained performance indicators of the control system to be optimized to obtain a first control system; wherein the performance indicators of the control system to be optimized at least include thermal control system parameters, adjustment rate, response time, and adjustment accuracy, and the performance indicators of the first control system meet the first preset design conditions;

[0142] The optimization unit 32 is used to perform loop optimization processing on the primary frequency modulation regulation loop of the first control system to obtain a target control system, wherein the primary frequency modulation regulation loop of the target control system meets a second preset design condition.

[0143] The frequency regulation optimization device of the automatic power generation control system provided by the present disclosure performs an index improvement process on the performance index of the control system to be optimized, and obtains a first control system; wherein the performance index of the control system to be optimized includes at least thermal control system parameters, regulation rate, response time, and regulation accuracy, and the performance index of the first control system meets the first preset design condition; the primary frequency regulation regulation loop of the first control system is subjected to loop optimization processing to obtain a target control system, wherein the primary frequency regulation regulation loop of the target control system meets the second preset design condition. Compared with the related art, the embodiment of the present disclosure first performs an improvement process on the performance indexes such as the thermal control system parameters, regulation rate, response time, and regulation accuracy of the system to be optimized, and then performs a frequency regulation regulation loop optimization process on the system after the performance index is improved, i.e., the first control system, so that the target control system finally obtained can improve the frequency regulation efficiency and frequency regulation accuracy of the frequency regulation link when performing frequency regulation.

[0144] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 4 As shown, the lifting unit 31 includes:

[0145] The optimization module 311 is used to perform parameter optimization processing on the thermal control system parameters in the performance index to obtain target thermal control system parameters; wherein the target thermal control system parameters meet the preset thermal parameter conditions;

[0146] The processing module 312 is used to perform a differentiated design process on the regulation rate in the performance indicator to obtain a target regulation rate; wherein the target regulation rate satisfies a preset regulation rate condition;

[0147] The optimization module 311 is also used to perform response optimization processing on the response time in the performance indicator to obtain a target response time; wherein the target response time satisfies a preset response time condition;

[0148] The optimization module 311 is also used to perform precision optimization processing on the adjustment precision in the performance index to obtain a target adjustment precision; wherein the target adjustment precision satisfies a preset adjustment precision condition;

[0149] The optimization module 311 is further used to perform system optimization processing on the control system to be optimized according to the target thermal control system parameters, the target regulation rate, the target response time and the target regulation accuracy to obtain the first control system.

[0150] Furthermore, in a possible implementation of the embodiment of the present disclosure, the optimization module 311 is further configured to:

[0151] The K1 value, K2 value and K3 value of the thermal control system parameters are optimized by a first preset optimization algorithm to obtain the target thermal control system parameters; wherein the K1 value is a proportional gain, the K2 value is an integral gain, and the K3 value is a differential gain;

[0152] The target thermal control system parameter satisfies the preset thermal parameter condition including: the comprehensive index KP of the target thermal control system parameter is ≥2.3, and the minimum index of the target thermal control system parameter is ≥1.8.

[0153] Furthermore, in a possible implementation of the embodiment of the present disclosure, the processing module 312 is further configured to:

[0154] Determine the equipment unit controlled by the control system to be optimized; wherein the control system to be optimized controls a plurality of the equipment units;

[0155] The load regulation range corresponding to each of the equipment units is determined respectively, and the regulation rate of each of the equipment units is subjected to differentiated design processing according to the load regulation range to obtain the target regulation rate corresponding to each of the equipment units.

[0156] Furthermore, in a possible implementation of the embodiment of the present disclosure, the optimization module 311 is further configured to:

[0157] Based on the target adjustment rate, the response time is subjected to response optimization processing by a second preset optimization algorithm to obtain the target response time;

[0158] The target response time satisfies the preset response time condition including: if the target adjustment rate is greater than or equal to 50% Pe, the target response time should be less than 60 seconds;

[0159] If the target regulation rate is less than 50% Pe, the target response time should be less than 75 seconds.

[0160] Furthermore, in a possible implementation of the embodiment of the present disclosure, the optimization module 311 is further configured to:

[0161] Based on the target adjustment rate, the adjustment accuracy is optimized by a third preset optimization algorithm to obtain the target adjustment accuracy;

[0162] The target regulation accuracy satisfies the preset regulation accuracy condition including: if the target regulation rate corresponding to the target equipment unit is greater than or equal to 50%Pe, the target regulation accuracy should be less than 1% of the rated power of the target equipment unit; wherein the target equipment unit is any unit among all the equipment units;

[0163] If the target regulation rate corresponding to the target equipment group is less than 50% Pe, the target regulation accuracy should be less than 1.25% of the rated power of the target equipment group.

[0164] Furthermore, in a possible implementation of the embodiment of the present disclosure, as Figure 4 As shown, the optimization unit 32 includes:

[0165] An acquisition module 321 is used to acquire grid parameters of a target grid;

[0166] The optimization module 322 is used to perform loop optimization processing on the primary frequency regulation loop of the first control system through a fourth preset optimization algorithm based on the power grid parameters to obtain the target control system; wherein the target power grid is a power grid connected to the first control system;

[0167] The primary frequency modulation regulation loop of the target control system meets the second preset design condition including: the response lag time of the primary frequency modulation regulation loop of the target control system should be less than 2 seconds, and the stabilization time of the primary frequency modulation of the primary frequency modulation regulation loop of the target control system should be less than 60 seconds;

[0168] The time for the primary frequency regulation loop of the target control system to achieve 75% of the target load should be no more than 15 seconds, and the time for the primary frequency regulation loop of the target control system to achieve 90% of the target load should be no more than 30 seconds;

[0169] The primary frequency modulation speed inequality rate of the primary frequency modulation regulation loop of the target control system should be greater than or equal to 4% and less than or equal to 5%.

[0170] It should be noted that the above explanation of the method embodiment is also applicable to the device of the embodiment of the present disclosure, and the principle is the same, which is no longer limited in the embodiment of the present disclosure.

[0171] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0172] Figure 5 A schematic block diagram of an example electronic device 500 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0173] like Figure 5 As shown, the device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 502 or a computer program loaded from a storage unit 508 to a RAM (Random Access Memory) 503. In the RAM 503, various programs and data required for the operation of the device 500 can also be stored. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An I / O (Input / Output) interface 505 is also connected to the bus 504.

[0174] A number of components in the device 500 are connected to the I / O interface 505, including: an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0175] The computing unit 501 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Units), various dedicated AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, a DSP (Digital Signal Processor), and any appropriate processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above, such as a frequency modulation optimization method for an automatic power generation control system. For example, in some embodiments, the frequency modulation optimization method for an automatic power generation control system may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to execute the aforementioned frequency regulation optimization method of the automatic power generation control system in any other appropriate manner (for example, by means of firmware).

[0176] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System On Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor that may be a special purpose or general purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0177] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0178] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a RAM, a ROM, an EPROM (Electrically Programmable Read-Only-Memory) or a flash memory, an optical fiber, a CD-ROM (Compact Dis sc Read-Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0179] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball), through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0180] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0181] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0182] It should be noted that artificial intelligence is a discipline that studies how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), and includes both hardware-level and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, as well as machine learning / deep learning, big data processing technology, knowledge graph technology, and other major directions.

[0183] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0184] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A frequency modulation optimization method for an automatic power generation control system, characterized in that: include: Performing an index improvement process on the obtained performance index of the control system to be optimized to obtain a first control system; wherein the performance index of the control system to be optimized at least includes a thermal control system parameter, a regulation rate, a response time, and a regulation accuracy, and the performance index of the first control system meets a first preset design condition; A loop optimization process is performed on the primary frequency modulation regulation loop of the first control system to obtain a target control system, wherein the primary frequency modulation regulation loop of the target control system satisfies a second preset design condition.

2. The method according to claim 1, characterized in that The step of performing an index improvement process on the obtained performance index of the control system to be optimized to obtain a first control system includes: Performing parameter optimization processing on the thermal control system parameters in the performance index to obtain target thermal control system parameters; wherein the target thermal control system parameters meet preset thermal parameter conditions; Performing differentiated design processing on the regulation rate in the performance indicator to obtain a target regulation rate; wherein the target regulation rate satisfies a preset regulation rate condition; Performing response optimization processing on the response time in the performance indicator to obtain a target response time; wherein the target response time satisfies a preset response time condition; Performing precision optimization processing on the regulation precision in the performance index to obtain a target regulation precision; wherein the target regulation precision satisfies a preset regulation precision condition; The control system to be optimized is subjected to system optimization processing according to the target thermal control system parameters, the target regulation rate, the target response time and the target regulation accuracy to obtain the first control system.

3. The method according to claim 2, characterized in that The performing parameter optimization processing on the thermal control system parameters in the performance index to obtain target thermal control system parameters includes: The K1 value, K2 value and K3 value of the thermal control system parameters are optimized by a first preset optimization algorithm to obtain the target thermal control system parameters; wherein the K1 value is a proportional gain, the K2 value is an integral gain, and the K3 value is a differential gain; The target thermal control system parameter satisfies the preset thermal parameter conditions including: the comprehensive index KP of the target thermal control system parameter is ≥2.3, and the minimum index of the target thermal control system parameter is ≥1.

8.

4. The method according to claim 2, characterized in that: The performing differentiated design processing on the regulation rate in the performance indicator to obtain a target regulation rate includes: Determine the equipment unit controlled by the control system to be optimized; wherein the control system to be optimized controls a plurality of the equipment units; The load regulation range corresponding to each of the equipment units is determined respectively, and the regulation rate of each of the equipment units is subjected to differentiated design processing according to the load regulation range to obtain the target regulation rate corresponding to each of the equipment units.

5. The method according to claim 2, characterized in that The performing response optimization processing on the response time in the performance indicator to obtain the target response time comprises: Based on the target adjustment rate, the response time is subjected to response optimization processing by a second preset optimization algorithm to obtain the target response time; The target response time satisfies the preset response time condition including: if the target adjustment rate is greater than or equal to 50% Pe, the target response time should be less than 60 seconds; If the target regulation rate is less than 50% Pe, the target response time should be less than 75 seconds.

6. The method according to claim 4, characterized in that The performing precision optimization processing on the regulation precision in the performance index to obtain the target regulation precision comprises: Based on the target adjustment rate, the adjustment accuracy is optimized by a third preset optimization algorithm to obtain the target adjustment accuracy; The target regulation accuracy satisfies the preset regulation accuracy condition including: if the target regulation rate corresponding to the target equipment unit is greater than or equal to 50%Pe, the target regulation accuracy should be less than 1% of the rated power of the target equipment unit; wherein the target equipment unit is any unit among all the equipment units; If the target regulation rate corresponding to the target equipment group is less than 50% Pe, the target regulation accuracy should be less than 1.25% of the rated power of the target equipment group.

7. The method according to claim 1, characterized in that The performing loop optimization processing on the primary frequency modulation regulation loop of the first control system to obtain the target control system comprises: Acquire grid parameters of a target grid, and perform loop optimization processing on a primary frequency regulation loop of the first control system through a fourth preset optimization algorithm based on the grid parameters to obtain the target control system; wherein the target grid is a grid connected to the first control system; The primary frequency modulation regulation loop of the target control system meets the second preset design condition including: the response lag time of the primary frequency modulation regulation loop of the target control system should be less than 2 seconds, and the stabilization time of the primary frequency modulation of the primary frequency modulation regulation loop of the target control system should be less than 60 seconds; The time for the primary frequency regulation loop of the target control system to achieve 75% of the target load should be no more than 15 seconds, and the time for the primary frequency regulation loop of the target control system to achieve 90% of the target load should be no more than 30 seconds; The primary frequency modulation speed inequality rate of the primary frequency modulation regulation loop of the target control system should be greater than or equal to 4% and less than or equal to 5%.

8. A frequency modulation optimization device for an automatic power generation control system, characterized in that: include: An improving unit is used to perform an indicator improvement process on the obtained performance indicators of the control system to be optimized to obtain a first control system; wherein the performance indicators of the control system to be optimized at least include thermal control system parameters, adjustment rate, response time, and adjustment accuracy, and the performance indicators of the first control system meet the first preset design conditions; The optimization unit is used to perform loop optimization processing on the primary frequency modulation regulation loop of the first control system to obtain a target control system, wherein the primary frequency modulation regulation loop of the target control system meets a second preset design condition.

9. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

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