Control method of pneumatic conveying system in abnormal state of coal-fired unit

Abstract

The invention relates to the field of coal-fired power plant control, in particular to a control method for a pneumatic conveying system under the abnormal state of a coal-fired unit. The method comprises the steps that judgment is conducted according to real-time operation parameters and a dynamic threshold model of the coal-fired unit, when operation abnormity occurs, abnormal dry ash is marked, and the duration time of the abnormal state is recorded. Calculating the time when the abnormal dry ash reaches the ash bucket, and calculating the ratio of the abnormal dry ash in the ash bucket according to the abnormal state duration. And performing quality detection on the abnormal dry ash, matching a quality detection result with customer demand parameters, and adjusting valves of ash storage warehouses of corresponding types. And according to the ratio of the abnormal dry ash in the ash hopper and the real-time pressure value of the air compressor station mother pipe, the compressed air demand quantity of the pneumatic conveying system is calculated, and grading control is conducted on the air compressor set according to the compressed air demand quantity. According to the invention, timely detection is carried out when the coal-fired unit is abnormal, effective treatment from monitoring to isolation is formed on dry ash in an abnormal state, and energy conservation and high efficiency of the system are ensured.

Description

Technical Field

[0001] This application relates to the field of coal-fired power plant control, and particularly to a control method for a pneumatic conveying system under abnormal conditions of a coal-fired unit. Background Technique

[0002] A coal-fired power plant is a factory that uses coal as fuel to produce electric energy. After the coal is burned, the flue gas flows to the rear chimney and is finally discharged into the atmosphere. However, the flue gas contains a large amount of dust that must be filtered and removed. Various devices are installed in the process of the flue gas flowing to the chimney, including economizers, air preheaters, dust collectors, etc. These devices collect the dust in the flue gas and store it in their respective ash hoppers. At present in China, for the pollution of these dry ashes, a closed pipeline pneumatic conveying system is used to transport them from each ash hopper to a centralized ash storage bin, and then transported out by vehicles.

[0003] However, in the actual production stage, the following problems will occur: due to the change in the source of coal and the uneven quality, the coal-fired unit may have abnormal operations such as too high oxygen content and too high temperature under the operating parameters set according to standard coal. Or the coal-fired unit may also have abnormal operations for other reasons during continuous operation. There are obvious differences in the quality parameters between the dry ash obtained under abnormal conditions and the dry ash under normal conditions. There is no corresponding method in the prior art to effectively process the abnormal dry ash when the coal-fired unit has an abnormality. Summary of the Invention

[0004] In order to solve the problem that the prior art lacks a method for processing abnormal dry ash when a coal-fired unit has an abnormality, this application provides a control method for a pneumatic conveying system under abnormal conditions of a coal-fired unit. The method provided by this application includes the following steps:

[0005] According to the real-time operating parameters of the coal-fired unit and the dynamic threshold model, judge the operating state of the coal-fired unit. When an abnormal operation occurs, mark the dry ash as abnormal dry ash and record the duration of the abnormal state;

[0006] Calculate the time for the abnormal dry ash to reach the ash hopper according to the flue gas flow rate and the particle sedimentation rate of the coal system, and calculate the ratio of the abnormal dry ash in the ash hopper according to the duration of the abnormal state;

[0007] Conduct a quality inspection on the abnormal dry ash, match the result of the quality inspection with the customer demand parameters, and adjust the valves of the corresponding type of ash storage bin according to the matching result and the duration of the abnormal state. The types of the ash storage bin include: coarse ash bin, fine ash bin and raw ash bin;

[0008] Calculate the compressed air demand of the pneumatic conveying system according to the ratio of the abnormal dry ash in the ash hopper and the real-time pressure value of the main pipe of the air compressor station, and perform hierarchical control on the air compressor unit according to the compressed air demand. The hierarchical control includes: adjusting the operating parameters of the operating air compressor; starting the hot standby air compressor; starting the cold standby air compressor.

[0009] Specifically, the real-time operating parameters of the coal-fired unit include: furnace temperature, working current, and flue gas oxygen concentration. The dynamic threshold model is an LSTM model based on the furnace temperature, the working current, and the flue gas oxygen concentration. When the real-time operating parameters of the coal-fired unit exceed the dynamic threshold for three consecutive sampling periods, it is determined that the operation is abnormal.

[0010] Specifically, the calculation formula for calculating the time when the abnormal dry ash reaches the ash hopper according to the flue gas flow velocity and the particle sedimentation velocity of the coal combustion system is:

[0011]

[0012] where t is the duration required for the abnormal dry ash to reach the ash hopper, L is the flue length, v is the flue gas flow velocity, and u s is the particle sedimentation velocity, obtained through Stokes' law and corrected based on the pressure gradient data at the ash hopper inlet.

[0013] Specifically, when correcting based on the pressure gradient data at the ash hopper inlet, the correction formula used is:

[0014]

[0015] where u s ’ is the corrected particle sedimentation velocity, △P is the pressure difference at the ash hopper inlet, P reference is the reference pressure, η is the eddy current loss compensation coefficient, and d 灰粒 is the dry ash particle size, measured in real time by a particle size sensor in the flue, and d 标准 is the standard dry ash particle size.

[0016] Specifically, the results of the quality inspection include: fineness, loss on ignition, and ammonia odor concentration. When the results of the quality inspection match the customer demand parameters, they are matched according to the weight priority of fineness > loss on ignition > ammonia odor concentration.

[0017] Specifically, the method for adjusting the valves of the corresponding category of ash storage silos according to the matching result and the abnormal state duration includes:

[0018] Judge according to the time when the operation abnormality occurs. When the abnormal dry ash reaches the valve, open the valve of the ash storage silo corresponding to the matching result;

[0019] Judgment is made according to the abnormal state duration. When normal dry ash reaches the valve, the ash storage bin valve corresponding to the category of normal dry ash is opened.

[0020] Specifically, the calculation formula for the compressed air demand of the pneumatic conveying system is:

[0021] Q = α·R·V pipe +β(P 母管 -P 基准 )

[0022] where Q is the compressed air demand, α and β are the system characteristic parameters of the pneumatic conveying system, Vpipe is the volume of the conveying pipeline of the pneumatic conveying system, P 母管 is the real-time pressure value of the main pipe of the air compressor station, P 基准 is the set pressure value of the main pipe of the air compressor station, and R is the ratio of the abnormal dry ash in the ash hopper.

[0023] Specifically, the air compressor unit is hierarchically controlled according to the compressed air demand and the grading threshold. When the compressed air demand is less than the first grading threshold, the frequency conversion frequency of the operating air compressor is adjusted;

[0024] When the compressed air demand is greater than or equal to the first grading threshold and less than the second grading threshold, the hot standby air compressor is started;

[0025] When the compressed air demand is greater than or equal to the second grading threshold, the cold standby air compressor is started and preheated for 10 minutes and then loaded to full load.

[0026] Specifically, the customer demand parameters are updated through the cloud interface. After the quality of the abnormal dry ash is detected, it is matched with the latest customer demand parameters.

[0027] Specifically, when the ammonia odor concentration ≥ 20 ppm or the ratio of the abnormal dry ash in the ash hopper > 70%, all the dry ash in the ash hopper is conveyed to the abnormal ash storage bin and a first-level abnormal alarm signal is sent.

[0028] The present application has the following technical effects:

[0029] It realizes timely detection when an abnormality occurs in the coal-fired unit, effectively processes the dry ash in the abnormal state from monitoring to isolation, eliminates the influence of the abnormal dry ash on the pneumatic conveying system through hierarchical control, and ensures the energy-saving and high-efficiency of the system. Description of the Drawings

[0030] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features, and advantages of the exemplary embodiments of the present application will become readily understandable. In the drawings, several embodiments of the present application are shown in an exemplary but not restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts.

[0031] Figure 1 It is a flowchart of a control method for a pneumatic conveying system under abnormal conditions of a coal-fired unit in an embodiment of the present application. Specific embodiments

[0032] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application.

[0033] During the construction stage of a coal-fired power plant, a type of coal to be burned is determined, and the operating parameters of the coal-fired unit are designed around the quality parameters of this coal to make the system reach the most economical state. Under the most economical state of the system, the dry ash generated during coal combustion can be provided as a by-product to customers in need. Therefore, the quality of the generated dry ash is also considered during the construction of the coal-fired unit and needs to meet the requirements of customers. However, during actual operation, due to changes in the source of coal, it may not be compatible with the operating parameters of the coal-fired unit, resulting in abnormal operation. In addition, during the continuous operation of the coal-fired unit, there is a small probability of abnormal operation itself. The present application aims to propose a control method for a pneumatic conveying system under abnormal conditions of a coal-fired unit, which can effectively identify and isolate abnormal dry ash and reduce the operating impact of abnormal dry ash on the air compressor unit. As Figure 1 shown, the control method of the present application can be implemented according to the steps of the following embodiments. The steps are specifically as follows:

[0034] S1. According to the real-time operating parameters of the coal-fired unit and the dynamic threshold model, judge the operating state of the coal-fired unit. When an abnormal operation occurs, mark the dry ash as abnormal dry ash and record the duration of the abnormal state.

[0035] S2. Calculate the time for abnormal dry ash to reach the ash hopper according to the flue gas flow rate and particle sedimentation velocity of the coal combustion system, and calculate the ratio of abnormal dry ash in the ash hopper according to the duration of the abnormal state.

[0036] S3. Conduct quality detection on the abnormal dry ash, match the results of the quality detection with the customer demand parameters, and adjust the valves of the corresponding types of ash storage silos according to the matching results and the duration of the abnormal state. The types of ash storage silos include: coarse ash silo, fine ash silo, and raw ash silo.

[0037] S4. Calculate the compressed air demand of the pneumatic conveying system based on the ratio of abnormal dry ash in the ash hopper and the real-time pressure value of the main pipe of the air compressor station, and perform hierarchical control on the air compressor units according to the compressed air demand. The hierarchical control includes: adjusting the operating parameters of the air compressors in operation; starting the hot standby air compressors; starting the cold standby air compressors.

[0038] In this embodiment, the construction of the dynamic threshold model adopts a neural network algorithm based on LSTM (Long Short-Term Memory Network). The input parameters include three core parameters: furnace temperature, working current, and flue gas oxygen concentration. The sampling period of these three parameters is set to 10 seconds and is trained with historical abnormal operating condition data, which covers 20 typical scenarios such as deep peak shaving, co-firing of kerosene and coal, and sudden change of coal quality. When the above three parameters exceed the dynamic threshold range for 3 consecutive sampling periods, that is, 30 seconds, the system determines that the operation is abnormal and triggers the abnormal dry ash marking program. To eliminate instantaneous interference, the model also introduces a sliding window filtering algorithm to perform secondary verification on abnormal data with a fluctuation amplitude exceeding the set value.

[0039] It takes a certain amount of time for abnormal dry ash to be generated and finally settle in the ash hopper, which is closely related to the flue gas velocity and the physical properties of ash particles. In the ash flow tracking link, the flue gas velocity is calculated using the real-time monitoring data of a thermal flowmeter, and the time for abnormal dry ash to reach the ash hopper is calculated in combination with the flue duct specifications. Considering the influence of the pressure gradient at the ash hopper inlet on the movement of ash particles, the calculation result is dynamically corrected using the eddy current loss compensation coefficient. The specific calculation formula is:

[0040]

[0041] where t is the time required for the abnormal dry ash to reach the ash hopper, L is the length of the flue duct, v is the flue gas velocity, and u s is the particle settling velocity, which is obtained through Stokes' law and corrected based on the pressure gradient data at the ash hopper inlet. When correcting based on the pressure gradient data at the ash hopper inlet, the correction formula is:

[0042]

[0043] where u s ’ is the corrected particle settling velocity, △P is the pressure difference at the ash hopper inlet, P reference is the reference pressure, η is the eddy current loss compensation coefficient, and d 灰粒 is the dry ash particle size, which is measured in real time by a particle size sensor in the flue duct, and d 标准 is the standard dry ash particle size. In a usage scenario of this embodiment, η is taken as 0.68, and d 标准Set to 45μm, it can control the prediction error of the ash particle arrival time within ±5%. Compared with the model before correction, it improves the model accuracy, and compared with the traditional algorithm, it greatly improves the model accuracy. Through the flue length, the corrected settling velocity, and the real-time flue gas velocity, the system can accurately calculate the time window for abnormal dry ash to reach the ash hopper. Combining with the duration of the abnormal state, the system further calculates the mixing ratio of abnormal dry ash and normal dry ash in the ash hopper, and this ratio will become the key basis for subsequent pneumatic conveying control.

[0044] After the abnormal dry ash reaches the ash hopper, the system will start the on-line quality detection module. The laser particle size analyzer scans the ash sample at a sampling frequency of thousands of times per second to accurately measure the residue on a 45-micron sieve; the near-infrared spectrometer quickly analyzes the loss on ignition through the molecular absorption characteristics; the electrochemical sensor monitors the ammonia odor concentration in real time with a sensitivity of up to 0.1 ppm. These detection data are transmitted to the central controller through the industrial bus and are intelligently matched with the customer demand parameters stored in the cloud database. The matching process adopts a multi-level weight decision-making mechanism. The fineness index occupies a weight priority of 50%, the loss on ignition accounts for 30%, and the ammonia odor concentration accounts for 20%. When performing the matching, the deviation degrees of the fineness and the standard fineness of the coarse ash bin and the fine ash bin are calculated respectively, and at the same time, the deviation degrees of the loss on ignition and the loss on ignition of the coarse ash bin and the fine ash bin are calculated respectively. The deviation degree of the ammonia odor concentration and the standard ammonia odor concentration is also calculated, and all the deviation degrees are accumulated according to the corresponding weight priorities, and finally the category of the ash storage bin to which the abnormal dry ash belongs is judged to ensure that the abnormal dry ash can also be reasonably utilized and will not pollute the high-value ash bin. In extreme cases, such as when the ammonia odor concentration suddenly rises to 20 ppm or the proportion of abnormal dry ash in the ash hopper exceeds 70%, the system will start the emergency protocol. All conveying valves are immediately switched to the bypass pipeline, and the dry ash in the ash hopper is directly sent to the isolation ash bin. At the same time, the central control room will receive a first-level warning signal to remind the maintenance personnel to intervene and handle. This multi-level protection mechanism enables the system to still operate stably in the face of sudden abnormalities.

[0045] The core power of the pneumatic conveying system comes from the air compressor unit, and its operating state directly affects the conveying efficiency and energy consumption. The system collects the main pipe pressure data in real time through the pressure transmitter, and combines the proportion of abnormal dry ash in the ash hopper to calculate the required compressed air volume at present by using a specific formula. The specific formula is:

[0046] Q = α·R·V pipe +β(P 母管 -P 基准 )

[0047] Among them, Q is the required compressed air volume, α and β are the system characteristic parameters of the pneumatic conveying system, Vpipe is the conveying pipeline volume of the pneumatic conveying system, P 母管 is the real-time pressure value of the main pipe of the air compressor station, P基准 is the set main pipe pressure value of the air compressor station, and R is the ratio of the abnormal dry ash in the ash hopper. In recent years, due to the commissioning of wind power systems and photovoltaic systems, coal-fired power plants are often operated at low load, which causes the pneumatic ash conveying system to operate in an unstable state and the main pipe pressure at the air compressor outlet fluctuates greatly. This formula not only takes into account the volume characteristics of the conveying pipeline, but also introduces a pressure compensation coefficient, so that the calculation results can dynamically adapt to the pressure fluctuations at the main pipe at the air compressor outlet. Combined with the three-level control strategy, the working efficiency of the air compressor unit can be guaranteed to the maximum extent and the working energy consumption can be reduced.

[0048] In this embodiment, the three-level control strategy is specifically as follows: when the compressed air demand is lower than 70% of the rated value, the frequency conversion frequency of the running air compressor is adjusted in the range of 30-50Hz through the PID controller; when the demand is 70-100%, the hot standby unit is started and the frequency is adjusted to 80% of the rated value; when it exceeds 100%, the cold standby unit is loaded to full load after 10 minutes of preheating.

[0049] To realize the above control logic, the hardware system adopts a modular design. The pressure, temperature, flue gas analysis and other data are uploaded to the cloud platform through the industrial Ethernet through the high-temperature resistant and high-precision data acquisition layer. The power plant managers can view the ash storage status and dry ash quality report in real time through the web page, and access customer demand parameters through the RESTful API interface, supporting real-time updates and version traceability to ensure that after the quality inspection of the abnormal dry ash, it matches the latest customer demand parameters. This architecture not only supports the transformation and upgrading of existing power plants, but can also be seamlessly integrated into the DCS system of the whole plant of a new power plant.

[0050] Obviously, the embodiments described above are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0051] It should be understood that when the terms "first", "second", etc. are used in the claims, specification and drawings of the present application, they are only used to distinguish different objects, rather than to describe a specific order. The terms "include" and "comprise" used in the specification and claims of the present application indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their collections.

Claims

1. A control method for a pneumatic conveying system under abnormal conditions of a coal-fired unit, which is used to control the pneumatic conveying system when the coal-fired unit is abnormal. The control method includes the following steps: Judge the operating state of the coal-fired unit according to the real-time operating parameters of the coal-fired unit and the dynamic threshold model. When an operating abnormality occurs, mark the dry ash as abnormal dry ash and record the duration of the abnormal state; Calculate the time for the abnormal dry ash to reach the ash hopper according to the flue gas flow rate and particle sedimentation rate of the coal system, and calculate the ratio of the abnormal dry ash in the ash hopper according to the duration of the abnormal state; Conduct quality inspection on the abnormal dry ash, match the result of the quality inspection with the customer demand parameters, and adjust the valves of the corresponding category of ash storage silos according to the matching result and the duration of the abnormal state. The categories of the ash storage silos include: coarse ash silo, fine ash silo and raw ash silo; Calculate the compressed air demand of the pneumatic conveying system according to the ratio of the abnormal dry ash in the ash hopper and the real-time pressure value of the main pipe of the air compressor station, and conduct hierarchical control on the air compressor unit according to the compressed air demand. The hierarchical control includes: adjusting the operating parameters of the operating air compressor; starting the hot standby air compressor; starting the cold standby air compressor.

2. The control method according to claim 1, wherein The real-time operating parameters of the coal-fired unit include: furnace temperature, working current and flue gas oxygen concentration. The dynamic threshold model is an LSTM model based on the furnace temperature, the working current and the flue gas oxygen concentration. When the real-time operating parameters of the coal-fired unit exceed the dynamic threshold for 3 consecutive sampling periods, it is determined as an operating abnormality.

3. The control method according to claim 1, characterized in that The calculation formula for calculating the time for the abnormal dry ash to reach the ash hopper according to the flue gas flow rate and particle sedimentation rate of the coal system is: where t is the time required for the abnormal dry ash to reach the ash hopper, L is the flue length, v is the flue gas velocity, and u s is the particle settling velocity, obtained by Stokes' law and corrected based on the pressure gradient data at the ash hopper inlet.

4. The control method according to claim 3, wherein When correcting based on the pressure gradient data at the ash hopper inlet, the correction formula used is: Among them, u s ’ is the corrected particle settling velocity, △P is the ash hopper inlet pressure difference, P reference is the reference pressure, η is the eddy current loss compensation coefficient, d 灰粒 is the dry ash particle size, which is measured in real time by a particle size sensor in the flue, d 标准 is the standard dry ash particle size.

5. The control method according to claim 1, characterized in that The results of the quality inspection include: fineness, loss on ignition, ammonia odor concentration. When the results of the quality inspection match the customer demand parameters, they are matched according to the weight priority of fineness > loss on ignition > ammonia odor concentration.

6. The control method according to claim 5, wherein The method for adjusting the valves of the corresponding category of ash storage silos according to the matching result and the duration of the abnormal state includes: Judge according to the time when the operating abnormality occurs. When the abnormal dry ash reaches the valve, open the valve of the ash storage silo corresponding to the matching result; Judge according to the duration of the abnormal state. When the normal dry ash reaches the valve, open the valve of the ash storage silo corresponding to the category of the normal dry ash.

7. The control method according to claim 1, wherein The calculation formula for calculating the compressed air demand of the pneumatic conveying system is: Q = α·R·V pipe +β(P 母管 -P 基准 ) Wherein, Q is the required amount of compressed air, α and β are the system characteristic parameters of the pneumatic conveying system, Vpipe is the volume of the conveying pipeline of the pneumatic conveying system, P 母管 is the real-time pressure value of the main pipe of the air compressor station, P 基准 is the set pressure value of the main pipe of the air compressor station, and R is the ratio of the abnormal dry ash in the ash hopper.

8. The control method according to claim 1, wherein Conduct hierarchical control on the air compressor unit according to the compressed air demand and the hierarchical threshold. When the compressed air demand is less than the first hierarchical threshold, adjust the frequency conversion frequency of the operating air compressor; When the compressed air demand is greater than or equal to the first hierarchical threshold and less than the second hierarchical threshold, start the hot standby air compressor; When the compressed air demand is greater than or equal to the second hierarchical threshold, start the cold standby air compressor and preheat it for 10 minutes and then load it to full load.

9. The control method according to claim 1, wherein The customer demand parameters are updated through the cloud interface and matched with the latest customer demand parameters after the quality inspection of the abnormal dry ash.

10. The control method according to claim 5, characterized in that, When the ammonia smell concentration ≥ 20 ppm or the ratio of the abnormal dry ash in the ash hopper > 70%, all the dry ash in the ash hopper is transported to the abnormal ash storage bin and a first-level abnormal warning signal is sent.

Images