Automatic switching method and device for water feeding pump of supercritical unit of thermal power plant

Abstract

The embodiment of the invention provides an autonomous switching method and device for a water feeding pump of a supercritical unit of a thermal power plant, and the method comprises the steps: collecting the operation parameters of the water feeding pump in real time; inputting the running parameters collected in real time into a pre-trained running state evaluation model of the water feeding pump and the unit, evaluating the current health state of the water feeding pump through the running state evaluation model, and judging whether the whole running condition of the unit needs to switch the water feeding pump or not; when the operation state evaluation model judges that the feed pump needs to be switched, determining an optimal switching strategy according to the current unit operation condition and the feed pump state; and according to the optimal switching strategy and a preset switching process, sequentially executing operations of starting a standby feed pump and stopping running the feed pump.

Description

Technical Field

[0001] This document relates to the field of equipment automation technology, and in particular to a method and device for autonomous switching of feedwater pumps in supercritical units of thermal power plants. Background Technology

[0002] In the operation of supercritical units in thermal power plants, the stable operation of feedwater pumps is crucial. Feedwater pumps are responsible for providing the boiler with feedwater at appropriate pressure and flow rates to meet the unit's operational needs under different loads. When a feedwater pump malfunctions, requires regular maintenance, or experiences a significant change in unit load, a feedwater pump switching operation is necessary.

[0003] Currently, traditional feedwater pump switching methods mainly rely on manual operation. Operators need to closely monitor the unit's operating parameters, manually start the standby feedwater pump at the appropriate time, and gradually shut down the operating feedwater pump. This manual operation method has many problems: On the one hand, manual judgment and operation are easily affected by the operator's experience and mental state, posing a risk of inaccurate judgment and untimely operation. Once an operational error occurs, it may lead to excessive fluctuations in feedwater flow, affecting the normal operation of the boiler, or even causing a safety accident; on the other hand, the manual switching process is relatively cumbersome, requiring operators to perform multiple steps, which is time-consuming and not conducive to the unit's rapid response and stable operation.

[0004] Furthermore, while some existing automatic switching methods can achieve a certain degree of automation, they often suffer from simple control logic and poor adaptability. They struggle to provide precise and flexible switching control based on the complex and ever-changing operating conditions of the unit, such as different load levels, steam parameters, and the health status of the feedwater pumps themselves, thus failing to meet the requirements for efficient, safe, and stable operation of supercritical units. Therefore, there is an urgent need for an autonomous switching method for feedwater pumps in supercritical thermal power plants that can achieve autonomous, precise, and efficient switching. Summary of the Invention

[0005] The purpose of this invention is to provide a method and device for autonomous switching of feedwater pumps in supercritical units of thermal power plants, aiming to solve the above-mentioned problems in the prior art.

[0006] This invention provides a method for autonomous switching of feedwater pumps in supercritical units of thermal power plants, comprising: Real-time acquisition of operating parameters of the water supply pump; The real-time collected operating parameters are input into a pre-trained operating status assessment model for the feedwater pumps and the unit. The operating status assessment model is used to assess the current health status of the feedwater pumps and determine whether the overall operating condition of the unit requires switching the feedwater pumps. When the operating status assessment model determines that a feedwater pump switch is required, the optimal switching strategy is determined based on the current unit operating conditions and feedwater pump status.

[0007] According to the optimal switching strategy, the operations of starting the standby water pump and stopping the running water pump are executed sequentially according to the preset switching procedure.

[0008] This invention provides an autonomous switching device for feedwater pumps in supercritical units of thermal power plants, comprising: The data acquisition module is used to collect the operating parameters of the water supply pump in real time. The evaluation module is used to input the real-time collected operating parameters into a pre-trained operating status evaluation model for the feedwater pump and the unit. The operating status evaluation model is used to evaluate the current health status of the feedwater pump and determine whether the overall operating condition of the unit requires switching the feedwater pump. The determination module is used to determine the optimal switching strategy based on the current unit operating conditions and feedwater pump status when the operating status assessment model determines that feedwater pump switching is required.

[0009] The operation module is used to sequentially execute the operations of starting the standby water pump and stopping the running water pump according to the optimal switching strategy and the preset switching process.

[0010] This invention also provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the above-described method for autonomous switching of feedwater pumps in supercritical units of thermal power plants.

[0011] This invention also provides a computer-readable storage medium storing an information transmission implementation program, which, when executed by a processor, implements the steps of the above-described method for autonomous switching of feedwater pumps in supercritical units of thermal power plants.

[0012] By employing the embodiments of the present invention, the switching of feedwater pumps can be automated and intelligent, improving the accuracy and timeliness of switching, reducing the impact of human factors, ensuring the stable and safe operation of supercritical units under various operating conditions, and reducing operating risks and maintenance costs. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a flowchart of the autonomous switching method for feedwater pumps in supercritical units of thermal power plants according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the autonomous switching device for feedwater pumps of supercritical units in thermal power plants according to an embodiment of the present invention; Figure 3 This is a schematic diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0015] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this document.

[0016] Method Implementation Examples According to embodiments of the present invention, a method for autonomous switching of feedwater pumps in supercritical units of thermal power plants is provided. Figure 1 This is a flowchart of the autonomous switching method for feedwater pumps in supercritical units of thermal power plants according to an embodiment of the present invention, as follows: Figure 1 As shown, the autonomous switching method for feedwater pumps of supercritical units in thermal power plants according to an embodiment of the present invention specifically includes: Step S101: Real-time acquisition of the operating parameters of the water supply pump; specifically including: By installing pressure sensors, flow sensors, temperature sensors, and vibration sensors in the feedwater pumps, boilers, and turbines of supercritical units, the operating parameters of the feedwater pumps (inlet and outlet pressure, flow rate, motor current, bearing temperature, vibration amplitude), boilers (steam pressure, steam flow rate, water level), and turbine load are collected in real time.

[0017] Step S102: Input the real-time collected operating parameters into the pre-trained operating status assessment model of the feedwater pump and the unit. The operating status assessment model is used to assess the current health status of the feedwater pump and determine whether the overall operating condition of the unit requires switching the feedwater pump. For example, it can determine whether there are potential faults in the feedwater pump or whether the unit load change has reached the switching threshold.

[0018] It should be noted that before performing the above processing, a model for evaluating the operating status of the water pump and the unit was established based on machine learning algorithms using historical operating data of the water pump. Step S103: When the operating status assessment model determines that a feedwater pump switch is required, the optimal switching strategy is determined based on the current unit operating conditions and feedwater pump status. Specifically, this includes: Based on the current unit operating conditions and feedwater pump status, an optimal switching strategy is formulated. The current unit operating conditions specifically include: current unit load, steam parameters, standby feedwater pump start-up preparation time, and the type of fault in the operating feedwater pump. For example, when the unit is operating at high load and steam parameters fluctuate significantly, the standby feedwater pump with more stable start-up performance and faster response speed is prioritized. If the operating feedwater pump needs to be switched due to mechanical failure, the standby feedwater pump is quickly started, and corresponding emergency shutdown measures are taken.

[0019] Step S104: According to the optimal switching strategy, and following the preset switching procedure, the operations of starting the standby feedwater pump and stopping the operating feedwater pump are executed sequentially. When starting the standby feedwater pump, the starting current and speed of the motor are precisely controlled to achieve a smooth start-up of the feedwater pump, avoiding impact on the power grid and the generating unit. When stopping the operating feedwater pump, its speed and flow rate are gradually reduced to ensure a smooth transition of pressure and flow in the water supply system, preventing water hammer.

[0020] After performing the above processing, the technical solution of this embodiment of the invention further includes: continuously monitoring key parameters such as pressure, flow rate, and temperature of the water supply system during the water pump switching process. Once abnormal fluctuations in parameters are detected, such as sudden pressure changes or a significant drop in flow rate, the automatic control system immediately activates the adjustment mechanism. By fine-tuning the speed of the water pump, valve opening, etc., the switching process is optimized and adjusted in real time to ensure the safety and stability of the switching process. As can be seen from the above technical solutions, in the embodiments of the present invention: 1. Multi-dimensional real-time monitoring and data acquisition: Various types of sensors, such as pressure, flow, temperature, and vibration sensors, are installed in key parts of the supercritical unit, such as feedwater pumps, boilers, and steam turbines, to comprehensively collect operating parameters in real time, providing a rich and accurate data foundation for subsequent analysis and decision-making.

[0021] 2. Machine Learning-Based Operational Status Assessment Model: Utilizing extensive historical operational data, an assessment model is established using machine learning algorithms (such as neural networks). This model can accurately determine the health status of the feedwater pumps and whether the overall unit operation requires feedwater pump switching, solving the problems of inaccuracy and delay in manual judgment and providing intelligent judgment basis for automated switching.

[0022] 3. Comprehensive switching decision-making based on multiple factors: When the evaluation model determines that a switching is necessary, the switching decision module comprehensively considers factors such as the current unit load, steam parameters, standby feedwater pump start-up preparation time, and operating feedwater pump failure type to formulate the optimal switching strategy and achieve precise and flexible switching control.

[0023] 4. Precise Autonomous Switching Execution: The automatic control system executes the start-up of the standby pump and the shutdown of the running pump sequentially according to the established switching strategy and preset procedures. By precisely controlling the motor starting current, speed, and speed regulation device, it ensures smooth start-up and shutdown of the feedwater pumps, guarantees a smooth transition of pressure and flow in the feedwater system, and prevents impact on the power grid and generating units, as well as water hammer phenomena.

[0024] 5. Full-process monitoring and dynamic adjustment: During the switching process, key parameters of the water supply system are continuously monitored. Once abnormal fluctuations occur in the parameters, the automatic control system quickly activates the adjustment mechanism, and optimizes the switching process in real time by fine-tuning the water supply pump speed, valve opening, etc., to ensure that the switching is carried out safely and stably.

[0025] The technical solutions described above in the embodiments of the present invention will be explained in detail below.

[0026] 1. Real-time monitoring and data acquisition implementation: High-precision pressure and flow sensors are installed on the inlet and outlet pipes of each feedwater pump; temperature and vibration sensors are installed on the motor housing and bearing housing; pressure, flow, and water level sensors are installed on the boiler drum, superheater, reheater, and other components; and speed, vibration, and temperature sensors are installed on key components of the turbine shaft system and cylinder block. These sensors transmit the collected real-time data to the unit's monitoring system via industrial fieldbus or wireless transmission.

[0027] 2. Establish and implement an operational status assessment model: Collect historical data from the long-term operation of supercritical units in thermal power plants, including operating parameters under normal operating conditions and various fault conditions. Use deep learning algorithms, such as neural networks, to train this data and construct an operational status assessment model. After training, deploy the model on the monitoring system's server to receive the collected operating parameters in real time and assess the operational status of the feedwater pumps and units.

[0028] 3. Switching Decision Formulation and Implementation: When the operating status assessment model determines that a feedwater pump switch is necessary, the switching decision module first obtains information such as the current unit load, steam parameters, and the status of each feedwater pump. Then, based on pre-set switching rules and optimization algorithms, it calculates the optimal switching scheme, including which standby feedwater pump to start, when to start it, and the control parameters during the startup process.

[0029] 4. Autonomous Switching Implementation: Based on the plan formulated by the switching decision module, the automatic control system sends a start command to the motor controller of the standby feedwater pump. The motor controller gradually increases the motor current and speed according to the preset start-up curve, ensuring a smooth start-up of the feedwater pump. Simultaneously, it sends a deceleration command to the speed control device of the operating feedwater pump, gradually reducing its speed and flow rate. During the switching process, the pressure and flow rate of the feedwater system are maintained stable by adjusting the valve openings on the feedwater pipeline.

[0030] 5. Monitoring and Adjustment of the Switching Process: During the switching of the water supply pump, the monitoring system collects parameters such as pressure, flow rate, and temperature of the water supply system in real time and compares them with the preset normal range. Once an abnormality is detected, such as a pressure deviation exceeding the set threshold, the automatic control system immediately adjusts the speed of the water supply pump or the valve opening to optimize the switching process and ensure its smooth completion.

[0031] In summary, the beneficial effects of the embodiments of the present invention are as follows: 1. Improve the accuracy and timeliness of switching: Through real-time monitoring and intelligent evaluation models, the timing of switching the feedwater pump can be accurately determined, avoiding errors and delays caused by manual judgment, greatly improving the accuracy and timeliness of switching, and ensuring the stable operation of the unit.

[0032] 2. Enhanced unit operation safety: Reduced risks caused by human error, and real-time monitoring and adjustment during switching effectively prevented safety issues such as water hammer and pressure fluctuations caused by improper switching, thus improving the safety of unit operation.

[0033] 3. Improve unit operating efficiency: The rapid and stable switching of feedwater pumps enables the unit to adapt to load changes more quickly, reduces the time of unstable unit operation caused by the switching process, improves the overall operating efficiency of the unit, and reduces energy consumption.

[0034] 4. Reduced operation and maintenance costs: The automated switching process reduces reliance on manual operation, lowers labor costs and maintenance workload, while timely fault diagnosis and handling extend the service life of water pumps and unit equipment, further reducing operation and maintenance costs.

[0035] Device Example 1 According to embodiments of the present invention, an autonomous switching device for feedwater pumps in supercritical units of thermal power plants is provided. Figure 2 This is a schematic diagram of the autonomous switching device for feedwater pumps in a supercritical unit of a thermal power plant, according to an embodiment of the present invention. Figure 2 As shown, the autonomous switching device for feedwater pumps of supercritical units in thermal power plants according to an embodiment of the present invention specifically includes: The data acquisition module 20 is used to acquire the operating parameters of the water supply pump in real time; specifically, it is used for: By installing pressure sensors, flow sensors, temperature sensors, and vibration sensors in the feedwater pumps, boilers, and turbines of supercritical units, the operating parameters of the feedwater pumps (inlet and outlet pressure, flow rate, motor current, bearing temperature, vibration amplitude), boilers (steam pressure, steam flow rate, water level), and turbine load are collected in real time.

[0036] The evaluation module 22 is used to input the real-time collected operating parameters into the pre-trained operating status evaluation model of the feedwater pump and the unit, and to evaluate the current health status of the feedwater pump and determine whether the overall operating condition of the unit requires feedwater pump switching. The determination module 24 is used to determine the optimal switching strategy based on the current unit operating conditions and feedwater pump status when the operating status assessment model determines that a feedwater pump switching is required. Specifically, it is used for: Based on the current operating conditions of the unit and the status of the feedwater pumps, an optimal switching strategy is formulated. The current operating conditions of the unit specifically include: the current unit load, steam parameters, the start-up preparation time of the standby feedwater pump, and the fault type of the operating feedwater pump.

[0037] Operation module 26 is used to sequentially execute the operations of starting the standby water pump and stopping the running water pump according to the optimal switching strategy and the preset switching process.

[0038] The device further includes: A module is established to use historical operating data of the feedwater pumps to build an operating status assessment model for the feedwater pumps and units based on machine learning algorithms. The adjustment module is used to continuously monitor parameters such as pressure, flow rate, and temperature of the water supply system during the switching process of the water pump. If abnormal fluctuations in parameters are detected, the adjustment mechanism is activated to optimize and adjust the switching process in real time by fine-tuning the speed of the water pump and the valve opening.

[0039] The embodiments of the present invention are device embodiments corresponding to the above method embodiments. The specific operation of each module can be understood with reference to the description of the method embodiments, and will not be repeated here.

[0040] Device Example 2 This invention provides an electronic device, such as... Figure 3 As shown, it includes: a memory 30, a processor 32, and a computer program stored in the memory 30 and executable on the processor 32, wherein the computer program, when executed by the processor 32, performs the steps as described in the method embodiment.

[0041] Device Example 3 This invention provides a computer-readable storage medium storing an information transmission implementation program, which, when executed by a processor 32, performs the steps described in the method embodiment.

[0042] The computer-readable storage media described in this embodiment include, but are not limited to, ROM, RAM, disk, or optical disk.

[0043] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for autonomous switching of feed water pumps of supercritical units of thermal power plants, characterized in that, The method comprises the steps of: real-time acquisition of operation parameters of the feed water pump; inputting the real-time acquired operation parameters into a pre-trained operation state evaluation model of the feed water pump and the unit, evaluating the current health state of the feed water pump through the operation state evaluation model, and judging whether the overall operation condition of the unit needs to be switched to the feed water pump; when the operation state evaluation model judges that the feed water pump needs to be switched, determining an optimal switching strategy according to the current operation condition of the unit and the state of the feed water pump; according to the optimal switching strategy, sequentially performing the operations of starting the standby feed water pump and stopping the operation of the feed water pump according to a preset switching process.

2. The method of claim 1, wherein, The real-time acquisition of the operation parameters of the feed water pump specifically comprises: real-time acquisition of the inlet and outlet pressure, flow, motor current, bearing temperature, vibration amplitude of the feed water pump, and the steam pressure, steam flow, water level of the boiler, and the operation parameters of the load of the steam turbine through the pressure sensor, flow sensor, temperature sensor, and vibration sensor installed on the feed water pump, boiler, and steam turbine of the supercritical unit.

3. The method of claim 1, wherein, The method further comprises: establishing an operation state evaluation model of the feed water pump and the unit based on a machine learning algorithm by using historical operation data of the feed water pump; in the process of switching the feed water pump, continuously monitoring the pressure, flow, and temperature parameters of the feed water system, starting an adjustment mechanism to optimize and adjust the switching process in real time by fine-tuning the rotating speed and valve opening of the feed water pump if abnormal fluctuations of the parameters are found.

4. The method of claim 1, wherein, The determination of the optimal switching strategy according to the current operation condition of the unit and the state of the feed water pump specifically comprises: formulating an optimal switching strategy according to the current operation condition of the unit and the state of the feed water pump, wherein the current operation condition of the unit specifically comprises the current unit load, steam parameters, startup preparation time of the standby feed water pump, and fault type of the operating feed water pump.

5. A supercritical unit feed water pump autonomous switching device for a thermal power plant, characterized in that, The device comprises: an acquisition module configured to acquire operation parameters of the feed water pump in real time; an evaluation module configured to input the real-time acquired operation parameters into a pre-trained operation state evaluation model of the feed water pump and the unit, evaluate the current health state of the feed water pump through the operation state evaluation model, and judge whether the overall operation condition of the unit needs to be switched to the feed water pump; a determination module configured to, when the operation state evaluation model judges that the feed water pump needs to be switched, determine an optimal switching strategy according to the current operation condition of the unit and the state of the feed water pump. an operation module configured to, according to the optimal switching strategy, sequentially perform the operations of starting the standby feed water pump and stopping the operation of the feed water pump according to a preset switching process.

6. The apparatus of claim 5, wherein, The acquisition module is specifically configured to: acquire the inlet and outlet pressure, flow, motor current, bearing temperature, vibration amplitude of the feed water pump, and the steam pressure, steam flow, water level of the boiler, and the operation parameters of the load of the steam turbine through the pressure sensor, flow sensor, temperature sensor, and vibration sensor installed on the feed water pump, boiler, and steam turbine of the supercritical unit in real time.

7. The apparatus of claim 5, wherein, The device further comprises: an establishment module configured to establish an operation state evaluation model of the feed water pump and the unit based on a machine learning algorithm by using historical operation data of the feed water pump; An adjusting module is configured to monitor the pressure, flow rate and temperature of the feedwater system during the feedwater pump switching process, and start an adjusting mechanism to optimize and adjust the switching process in real time by fine-tuning the rotating speed of the feedwater pump and the opening degree of the valve if abnormal fluctuations of the parameters are found.

8. The apparatus of claim 5, wherein, The determining module is specifically configured to: formulate an optimal switching strategy according to the current unit operating condition and the feedwater pump state, wherein the current unit operating condition specifically includes the current unit load, the steam parameter, the starting preparation time of the standby feedwater pump and the fault type of the operating feedwater pump.

9. An electronic device, comprising: comprise: a memory, a processor and a computer program stored in the memory and executable on the processor, and the computer program, when executed by the processor, implements the steps of the supercritical unit feedwater pump autonomous switching method of the thermal power plant according to any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores an information transmission implementation program, and the program, when executed by the processor, implements the steps of the supercritical unit feedwater pump autonomous switching method of the thermal power plant according to any one of claims 1 to 4.

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