Dry and wet state automatic switching control optimization method for generator set

Abstract

The invention discloses a dry and wet state automatic switching control optimization method for a generator set, which comprises the following steps of: 1, optimizing in a preparation stage and setting conditions, thoroughly analyzing the existing control logic, and evaluating the performance and response characteristics of the existing control logic; the conversion process can be ensured to be more efficient and accurate through a clear control logic and a parameter adjustment formula. Accurate control over the fuel quantity and the water level can reduce unnecessary energy waste, improve the conversion efficiency and monitor changes of key parameters, control strategies are dynamically adjusted according to needs, the stability of the system in the whole conversion process can be ensured, potential safety risks can be reduced, the reliability of the system is improved, and the economic benefits of the system are improved. And the operation can be more normalized and standardized. An operator can operate according to a clear guide, so that the possibility of human errors is reduced, the operation efficiency and accuracy are improved, and the dry-wet state conversion control and the operation efficiency and stability are enhanced when the generator set runs in a wide-load peak regulation mode.

Description

Technical Field

[0001] The invention relates to the technical field of electric power production, and in particular to a dry-wet state automatic conversion control optimization method for a generator set. Background Art

[0002] In the process of power production, the automatic conversion of the dry and wet state of the thermal power generating unit refers to the automatic adjustment of the water content and humidity content of the inlet and outlet air of the unit according to the needs of the unit operation during the thermal power generation process to achieve the conversion between the wet state and the dry state. This conversion is of great significance to ensure the safe and stable operation of the unit under low load. In the process of thermal power generation, the dry and wet state of the unit is closely related to the humidity and temperature of the air. In the wet state, the inlet and outlet air of the unit contains moisture, the moisture content in the air is high, the relative humidity is high, and the temperature is low. In the dry state, the inlet and outlet air of the unit does not contain moisture, the moisture content in the air is low, the relative humidity is low, and the temperature is high. In order to achieve the automatic conversion of the dry and wet state, the thermal power generating unit is usually equipped with advanced control systems and sensors, which can monitor the humidity and temperature of the inlet and outlet air of the unit in real time, and automatically adjust the operating state of the unit according to the preset conversion conditions.

[0003] However, during wide load peak-shaving operation, the generator sets face control difficulties when frequently switching between dry and wet states, which affects the operating efficiency and stability, so they need to be improved and optimized. Summary of the invention

[0004] To this end, the present invention provides a method for optimizing the control of automatic dry-wet state conversion of a generator set, so as to solve the problem in the prior art that the generator set is faced with control difficulties when frequently performing dry-wet state conversion during wide load peak-shaving operation, which affects the operating efficiency and stability.

[0005] In order to achieve the above object, the present invention provides the following technical solution: According to the first aspect of the present invention,

[0006] A dry-wet state automatic conversion control optimization method for a generator set, comprising:

[0007] Step 1: Preparatory stage optimization and condition setting: thoroughly analyze the existing control logic and evaluate its performance and response characteristics;

[0008] Step 2: Control logic design and configuration optimization, set reasonable parameter range and change rate to meet the needs of different loads and working conditions;

[0009] Step 3: Automatic conversion implementation, including:

[0010] Wet-to-dry state conversion: when the conditions are met, the system automatically switches the control logic and starts the wet-to-dry state conversion process;

[0011] Dry to wet state conversion, after meeting the conditions, the system automatically switches the control logic and starts execution

[0012] The conversion process from dry state to wet state;

[0013] Step 4: Safety and security measures: optimize the corresponding protection logic to ensure safe operation of the unit.

[0014] Further, step 1, preparatory stage optimization and condition setting, includes:

[0015] System evaluation and data collection: Collect historical operating data, including load changes, dry-wet state conversion records, and key parameter fluctuations;

[0016] Demand analysis: Analyze the actual demand for wide load peak regulation in thermal power plants, including improving conversion efficiency, reducing energy consumption, and increasing safety. Determine the key parameters in the dry-wet state conversion process according to demand, including feed water flow, fuel volume, steam pump speed, temperature, and pressure;

[0017] Solution formulation: Determine the switching conditions for automatic dry-wet state conversion, system operation mode, load conditions, fluctuation range, feedwater pump speed, control algorithm and response rate, including:

[0018] Data analysis: Collect data during the automatic dry-wet state conversion process, including changes in load, feed water flow, steam flow, intermediate point temperature and other parameters;

[0019] Algorithm adjustment: adjust and optimize the control algorithm based on data analysis results;

[0020] Response rate optimization: adjust the response rate of the control system according to unit characteristics and operating requirements;

[0021] Experimental verification: Conduct an on-site dry-wet state automatic conversion experiment to verify the effects of the optimized switching conditions, control algorithm, and response rate;

[0022] Continuous improvement: During the actual operation, we will continue to pay attention to the effect of automatic conversion between dry and wet states, and make continuous improvements and optimizations based on actual conditions.

[0023] Further, step 2, control logic design and configuration optimization, includes:

[0024] Control logic development: design rate control algorithms to ensure a smooth and reliable conversion process;

[0025] Parameter optimization: set a reasonable parameter range and change rate to meet the needs of different loads and working conditions;

[0026] Logical testing: Make necessary adjustments and optimizations based on the test results, including:

[0027] Analyze test results and identify logical errors: First, carefully analyze the results of the logic test to identify logical errors and potential problems in the AI ​​system and determine the error type: classify the identified logical errors and determine what type of error they belong to;

[0028] Adjust steps, correct conditional judgment errors, and fix variable assignment errors: For variable assignment errors, you need to find the wrong assignment statement and correct the assignment operation. Optimize algorithm logic: If there is a problem with the algorithm logic, you need to re-examine the design and implementation of the algorithm. Correct data logic errors: For errors in data processing or operations, you need to find the wrong data processing logic and correct the relevant code.

[0029] Further, the wet state to dry state conversion includes:

[0030] Condition confirmation: confirm that the water supply is sufficient, the fuel supply is stable, and the separator water level and superheat meet the wet state conversion conditions;

[0031] Start conversion: After confirmation by the operator, the fuel quantity gradually increases at the preset rate, the water supply remains stable, and the temperature rise rate is automatically adjusted according to temperature changes;

[0032] Conversion completed: When the superheat exceeds the set threshold and the separator water level is controlled within the specified range, it switches to the dry control logic and starts the water-coal ratio automatic control and coordination / TF control.

[0033] Further, the dry-to-wet conversion includes:

[0034] Condition confirmation: confirm that the fuel quantity, water flow rate, and separator water level meet the conditions for dry-to-wet state conversion; start conversion: gradually reduce the fuel quantity to lower the temperature, and increase the water flow rate appropriately until the appropriate water level, temperature, water flow, and fuel quantity required for wet state operation are met;

[0035] Restore control: After the conversion is completed, reset the control command to the wet control mode and restore coordinated control.

[0036] Further, safety and security measures include:

[0037] Optimization of low-load protection logic: Optimize the corresponding protection logic to ensure the safe operation of the unit in response to problems that occur during low-load operation. Perform detailed diagnosis of problems that occur during low-load operation, including analyzing historical data, operation logs, and on-site operation records to determine the root cause of the problem, sort out the existing low-load protection logic, clarify the role and triggering conditions of each protection link, and set the goal of optimizing the low-load protection logic based on the problem diagnosis results to improve the accuracy of protection, reduce the false operation rate, and enhance adaptability. According to the optimization goals, perform specific optimization of the low-load protection logic;

[0038] Protection logic sorting: sort out and optimize the existing protection logic to avoid false operation and abnormal tripping of auxiliary equipment after RB failure, collect all documents, drawings, and operation records related to the protection logic, understand the design principle, trigger conditions, and action results of the protection logic, conduct in-depth analysis of the protection logic, identify possible logical errors, redundancies, and conflicts, simulate various operating conditions in a simulation environment, test the reaction and action of the protection logic, verify the correctness and reliability of the logic, locate specific problem points based on the results of sorting and analysis, formulate corresponding optimization plans for each problem point, and verify the optimized protection logic in a simulation environment.

[0039] The present invention has the following advantages:

[0040] Through clear control logic and parameter adjustment formulas, the conversion process can be ensured to be more efficient and accurate. Accurate control of fuel quantity and water level can reduce unnecessary energy waste and improve conversion efficiency. Monitoring changes in key parameters and dynamically adjusting control strategies as needed can ensure the stability of the system throughout the conversion process, which helps reduce potential safety risks, improve system reliability, and make operations more standardized. Operators can operate according to clear guidelines, reduce the possibility of human errors, improve operational efficiency and accuracy, and enhance dry-wet state conversion control, operational efficiency and stability during wide load peak-shaving operation of generator sets. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A flow chart of a dry-wet state automatic conversion control optimization method for a generator set according to the present invention;

[0042] Figure 2 It is a flowchart of the automatic conversion implementation in step 3 of the automatic dry-wet state conversion control optimization method of a generator set of the present invention;

[0043] Figure 3 It is one of the logic diagrams of a dry-wet state automatic conversion control optimization method of a generator set of the present invention;

[0044] Figure 4 This is the second logic diagram of a dry-wet state automatic conversion control optimization method for a generator set of the present invention;

[0045] Figure 5 This is the third logic diagram of a dry-wet state automatic conversion control optimization method for a generator set of the present invention;

[0046] Figure 6 This is the fourth logic diagram of a dry-wet state automatic conversion control optimization method for a generator set of the present invention;

[0047] Figure 7This is the fifth logic diagram of a dry-wet state automatic conversion control optimization method for a generator set of the present invention;

[0048] Figure 8 This is the sixth logic diagram of the dry-wet state automatic conversion control optimization method of a generator set according to the present invention. DETAILED DESCRIPTION

[0049] The following is a description of the implementation of the present invention by specific embodiments. People familiar with the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] like Figures 1 to 8 As shown, a method for optimizing control of automatic dry-wet state conversion of a generator set in an embodiment of the first aspect of the present invention includes:

[0051] Step 1: Preparatory stage optimization and condition setting: thoroughly analyze the existing control logic and evaluate its performance and response characteristics;

[0052] Step 2: Control logic design and configuration optimization, set reasonable parameter range and change rate to meet the needs of different loads and working conditions;

[0053] Step 3: Automatic conversion implementation, including:

[0054] Wet-to-dry state conversion: when the conditions are met, the system automatically switches the control logic and starts the wet-to-dry state conversion process;

[0055] Dry-to-wet conversion: When the conditions are met, the system automatically switches the control logic and starts the dry-to-wet conversion process;

[0056] Step 4: Safety and security measures: optimize the corresponding protection logic to ensure safe operation of the unit.

[0057] In this embodiment, through clear control logic and parameter adjustment formulas, the conversion process can be ensured to be more efficient and accurate. Accurate control of fuel quantity and water level can reduce unnecessary energy waste, improve conversion efficiency, monitor changes in key parameters, and dynamically adjust control strategies as needed to ensure the stability of the system throughout the conversion process, which helps to reduce potential safety risks, improve system reliability, and make operations more standardized. Operators can operate according to clear guidelines, reduce the possibility of human errors, improve operational efficiency and accuracy, and enable the generator set to enhance dry-wet state conversion control during wide load peak-shaving operation, and enhance operational efficiency and stability.

[0058] Step 1: Preparatory stage optimization and condition setting, including:

[0059] System evaluation and data collection: Collect historical operating data, including load changes, dry-wet state conversion records, and key parameter fluctuations;

[0060] Demand analysis: Analyze the actual demand for wide load peak regulation in thermal power plants, including improving conversion efficiency, reducing energy consumption, and increasing safety. Determine the key parameters in the dry-wet state conversion process according to demand, including feed water flow, fuel volume, steam pump speed, temperature, and pressure;

[0061] Solution formulation: Determine the switching conditions for automatic dry-wet state conversion, system operation mode, load conditions, fluctuation range, feedwater pump speed, control algorithm and response rate, including:

[0062] Data analysis: Collect data during the automatic dry-wet state conversion process, including changes in load, feed water flow, steam flow, intermediate point temperature and other parameters;

[0063] Algorithm adjustment: adjust and optimize the control algorithm based on data analysis results;

[0064] Response rate optimization: adjust the response rate of the control system according to unit characteristics and operating requirements;

[0065] Experimental verification: Conduct an on-site dry-wet state automatic conversion experiment to verify the effects of the optimized switching conditions, control algorithm, and response rate;

[0066] Continuous improvement: During the actual operation, we will continue to pay attention to the effect of automatic conversion between dry and wet states, and make continuous improvements and optimizations based on actual conditions.

[0067] In this embodiment, the existing control logic is comprehensively evaluated, and its performance under different loads and working conditions is analyzed, including response speed, stability, and accuracy. The historical operation data of the thermal power plant during the wide load peak regulation process, especially the data during the dry-wet state conversion, are collected. These data will be used to analyze the problems in the conversion process and provide a basis for subsequent optimization. The needs of the wide load peak regulation of the thermal power plant are analyzed in detail, including improving conversion efficiency, reducing energy consumption, and increasing safety. The key parameters in the dry-wet state conversion process, such as feed water flow, fuel volume, steam pump speed, temperature, and pressure, are determined according to the needs. Based on the evaluation results and demand analysis, a detailed optimization plan is formulated, including control logic, parameter settings, and switching conditions.

[0068] Step 2: Control logic design and configuration optimization, including:

[0069] Control logic development: design rate control algorithms to ensure a smooth and reliable conversion process;

[0070] Parameter optimization: set a reasonable parameter range and change rate to meet the needs of different loads and working conditions;

[0071] Logical testing: Make necessary adjustments and optimizations based on the test results, including:

[0072] Analyze test results and identify logical errors: First, carefully analyze the results of the logic test to identify logical errors and potential problems in the AI ​​system and determine the error type: classify the identified logical errors and determine what type of error they belong to;

[0073] Adjust steps, correct conditional judgment errors, and fix variable assignment errors: For variable assignment errors, you need to find the wrong assignment statement and correct the assignment operation. Optimize algorithm logic: If there is a problem with the algorithm logic, you need to re-examine the design and implementation of the algorithm. Correct data logic errors: For errors in data processing or operations, you need to find the wrong data processing logic and correct the relevant code.

[0074] In this embodiment, according to the optimization plan, a new control logic code is written to implement the judgment logic and rate control of dry-wet state switching. Possible abnormal situations are considered in the control logic, and corresponding processing measures are set to ensure the safe and stable operation of the system. Through the analysis of historical data, the optimal range and adjustment strategy of parameter settings are found. According to the analysis results, a reasonable parameter range and change rate are set to meet the needs under different loads and working conditions.

[0075] Wet to dry conversion, including:

[0076] Condition confirmation: confirm that the water supply is sufficient, the fuel supply is stable, and the separator water level and superheat meet the wet state conversion conditions;

[0077] Start conversion: After the operator confirms, the fuel quantity gradually increases at a preset rate, the feed water is maintained stable, and at the same time, the temperature rise rate is automatically adjusted according to the temperature change;

[0078] Conversion completed: When the superheat exceeds the set threshold and the separator water level is controlled within the specified range, switch to the dry state control logic and start the automatic control of the water-to-coal ratio and coordinated / TF control.

[0079] Dry-to-wet state conversion, including:

[0080] Condition confirmation: Confirm that the fuel quantity, feed water flow rate, and separator water level meet the conditions for dry-to-wet state conversion; Start conversion: Gradually reduce the fuel quantity to lower the temperature, and at the same time, appropriately increase the feed water flow rate until the appropriate water level, temperature, feed water quantity, and fuel quantity required for wet state operation are met;

[0081] Restore control: After the conversion is completed, reset the control command to the wet state control mode and restore the coordinated control.

[0082] In this embodiment, for the wet-to-dry state conversion, it is necessary to confirm that parameters such as sufficient feed water, stable fuel supply, separator water level, and superheat meet the wet-to-dry state conversion conditions. After the operator confirms, the fuel quantity gradually increases at a preset rate, the feed water is maintained stable, and at the same time, the temperature rise rate is automatically adjusted according to the temperature change. When the superheat exceeds the set threshold and the separator water level is controlled within the specified range, switch to the dry state control logic and start the automatic control of the water-to-coal ratio and coordinated / TF control; for the dry-to-wet state conversion, confirm that parameters such as the fuel quantity, feed water flow rate, and separator water level meet the conditions for dry-to-wet state conversion, gradually reduce the fuel quantity to lower the temperature, and at the same time, appropriately increase the feed water flow rate until the wet state operation conditions are met. After the conversion is completed, reset the control command to the wet state control mode and restore the coordinated control;

[0083] Among them, for the wet-to-dry state conversion, some conditions need to be met, such as the feed water state, fuel control, water level, and superheat. These conditions are usually determined based on a series of thresholds or ranges. For example, assuming that T_superheat is the measured value of the superheat and T_superheat_threshold is the minimum superheat threshold required for conversion to the dry state, then one of the conditions can be expressed as:

[0084] If T_superheat < T_superheat_threshold, the dry state condition is not met;

[0085] Control Logic Switching When the control logic switches, it is necessary to keep the water flow rate stable while increasing the fuel amount. This is usually achieved by adjusting the set points of the water and fuel control loops. For example, assuming Q_water is the water flow rate, Q_fuel is the fuel amount, and rate_increase is the rate at which the fuel increases, the increase in the fuel amount can be expressed as;

[0086] In each control cycle: Q_fuel = Q_fuel + rate_increase * Δt, where Δt is the time interval of the control cycle;

[0087] At the same time, the feed water flow rate remains constant:

[0088] Q_water = constant value;

[0089] Parameter Monitoring and Adjustment During the conversion process, key parameters such as superheat and water level need to be monitored and the control strategy needs to be adjusted as needed.

[0090] Safety and security measures, including:

[0091] Optimization of low-load protection logic: Optimize the corresponding protection logic to ensure the safe operation of the unit in response to problems that occur during low-load operation. Perform detailed diagnosis of problems that occur during low-load operation, including analyzing historical data, operation logs, and on-site operation records to determine the root cause of the problem, sort out the existing low-load protection logic, clarify the role and triggering conditions of each protection link, and set the goal of optimizing the low-load protection logic based on the problem diagnosis results to improve the accuracy of protection, reduce the false operation rate, and enhance adaptability. According to the optimization goals, perform specific optimization of the low-load protection logic;

[0092] Protection logic combing: combing and optimizing the existing protection logic to avoid false operation and abnormal tripping of auxiliary equipment after RB failure, collecting all documents, drawings, and operation records related to the protection logic, understanding the design principle, trigger conditions, and action results of the protection logic, and conducting in-depth analysis of the protection logic to identify possible logical errors, redundancies, and conflicts. Simulating various operating conditions in a simulation environment, testing the reaction and action of the protection logic, and verifying the correctness and reliability of the logic. Based on the results of combing and analysis, locating specific problem points, formulating corresponding optimization plans for each problem point, and verifying the optimized protection logic in a simulation environment;

[0093] In this embodiment, the protection requirements under special circumstances such as low-load operation are analyzed, the protection logic is optimized, reasonable safety boundaries and restrictions are set, the risk of false operation is reduced, the safety of the system is improved, and the system is ensured to operate within the permitted range to prevent accidents.

Claims

1. A method for optimizing the automatic dry-wet state conversion control of a generator set, characterized in that: include: Step 1: Preparatory stage optimization and condition setting: thoroughly analyze the existing control logic and evaluate its performance and response characteristics; Step 2: Control logic design and configuration optimization, set reasonable parameter range and change rate to meet the needs of different loads and working conditions; Step 3: Automatic conversion implementation, including: Wet-to-dry state conversion: when the conditions are met, the system automatically switches the control logic and starts the wet-to-dry state conversion process; Dry-to-wet conversion: When the conditions are met, the system automatically switches the control logic and starts the dry-to-wet conversion process; Step 4: Safety and security measures: optimize the corresponding protection logic to ensure safe operation of the unit.

2. A method for optimizing dry-wet state automatic conversion control of a generator set according to claim 1, characterized in that: Step 1: Preparatory stage optimization and condition setting, including: System evaluation and data collection: Collect historical operating data, including load changes, dry-wet state conversion records, and key parameter fluctuations; Demand analysis: Analyze the actual demand for wide load peak regulation in thermal power plants, including improving conversion efficiency, reducing energy consumption, and increasing safety. Determine the key parameters in the dry-wet state conversion process according to demand, including feed water flow, fuel volume, steam pump speed, temperature, and pressure; Solution formulation: Determine the switching conditions for automatic dry-wet state conversion, system operation mode, load conditions, fluctuation range, feedwater pump speed, control algorithm and response rate, including: Data analysis: Collect data during the automatic dry-wet state conversion process, including changes in load, feed water flow, steam flow, intermediate point temperature and other parameters; Algorithm adjustment: adjust and optimize the control algorithm based on data analysis results; Response rate optimization: adjust the response rate of the control system according to unit characteristics and operating requirements; Experimental verification: Conduct an on-site dry-wet state automatic conversion experiment to verify the effects of the optimized switching conditions, control algorithm, and response rate; Continuous improvement: During the actual operation, we will continue to pay attention to the effect of automatic conversion between dry and wet states, and make continuous improvements and optimizations based on actual conditions.

3. The method for optimizing dry-wet state automatic conversion control of a generator set according to claim 1, characterized in that: Step 2: Control logic design and configuration optimization, including: Control logic development: design rate control algorithms to ensure a smooth and reliable conversion process; Parameter optimization: set a reasonable parameter range and change rate to meet the needs of different loads and working conditions; Logical testing: Make necessary adjustments and optimizations based on the test results, including: Analyze test results and identify logical errors: First, carefully analyze the results of the logic test to identify logical errors and potential problems in the AI ​​system and determine the error type: classify the identified logical errors and determine what type of error they belong to; Adjust steps, correct conditional judgment errors, and fix variable assignment errors: For variable assignment errors, you need to find the wrong assignment statement and correct the assignment operation. Optimize algorithm logic: If there is a problem with the algorithm logic, you need to re-examine the design and implementation of the algorithm. Correct data logic errors: For errors in data processing or operations, you need to find the wrong data processing logic and correct the relevant code.

4. The method for optimizing dry-wet state automatic conversion control of a generator set according to claim 1, characterized in that: Wet to dry conversion, including: Condition confirmation: confirm that the water supply is sufficient, the fuel supply is stable, and the separator water level and superheat meet the wet state conversion conditions; Start conversion: After confirmation by the operator, the fuel quantity gradually increases at the preset rate, the water supply remains stable, and the temperature rise rate is automatically adjusted according to temperature changes; Conversion completed: When the superheat exceeds the set threshold and the separator water level is controlled within the specified range, it switches to the dry control logic and starts the water-coal ratio automatic control and coordination / TF control.

5. The method for optimizing dry-wet state automatic conversion control of a generator set according to claim 1, characterized in that: Dry to wet conversion, including: Condition confirmation: confirm that the fuel quantity, water flow rate, and separator water level meet the conditions for dry-to-wet state conversion; start conversion: gradually reduce the fuel quantity to lower the temperature, and increase the water flow rate appropriately until the appropriate water level, temperature, water flow, and fuel quantity required for wet state operation are met; Restore control: After the conversion is completed, reset the control command to the wet control mode and restore coordinated control.

6. The method for optimizing dry-wet state automatic conversion control of a generator set according to claim 1, characterized in that: Safety and security measures, including: Optimization of low-load protection logic: Optimize the corresponding protection logic to ensure the safe operation of the unit in response to problems that occur during low-load operation. Perform detailed diagnosis of problems that occur during low-load operation, including analyzing historical data, operation logs, and on-site operation records to determine the root cause of the problem, sort out the existing low-load protection logic, clarify the role and triggering conditions of each protection link, and set the goal of optimizing the low-load protection logic based on the problem diagnosis results to improve the accuracy of protection, reduce the false operation rate, and enhance adaptability. According to the optimization goals, perform specific optimization of the low-load protection logic; Protection logic sorting: sort out and optimize the existing protection logic to avoid false operation and abnormal tripping of auxiliary equipment after RB failure, collect all documents, drawings, and operation records related to the protection logic, understand the design principle, trigger conditions, and action results of the protection logic, conduct in-depth analysis of the protection logic, identify possible logical errors, redundancies, and conflicts, simulate various operating conditions in a simulation environment, test the reaction and action of the protection logic, verify the correctness and reliability of the logic, locate specific problem points based on the results of sorting and analysis, formulate corresponding optimization plans for each problem point, and verify the optimized protection logic in a simulation environment.

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