Pressure control method for combined heat and power generation main steam mother pipe system

Abstract

The invention discloses a combined heat and power generation main steam mother pipe system pressure control method, and relates to the technical field of combined heat and power generation. Main steam mother pipe pressure data, fuel flow data, flue gas component data and exhaust gas temperature data are collected, combustion efficiency dynamic calculation is carried out based on the collected data, and the combustion efficiency is output; the method comprises the following steps of: constructing a main steam main pipe pressure dynamic model, outputting a pressure change rate, generating a fuel adjustment strategy according to a pressure prediction result and combustion efficiency data, executing the fuel adjustment strategy and monitoring pressure change. According to the method, smoke components and fuel data are monitored in real time, the combustion sufficiency degree is calculated, and the fuel flow and the excess air coefficient are dynamically adjusted; the combustion efficiency is improved, and the fuel utilization is optimized. And meanwhile, the emission content is reduced, the environmental protection requirement is met, problems are found in time through a model prediction control strategy, the combined heat and power generation stability is enhanced, an early warning mechanism is used for guaranteeing that the fuel is planned to be added or replaced, the efficiency of the main steam main pipe is maximized, and efficient and environment-friendly operation is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of cogeneration, and particularly to a method for controlling the pressure of the main steam header system in cogeneration. Background Art

[0002] In a cogeneration system, the pressure control of the main steam header is a key link to ensure the efficient and stable operation of the system. Traditional pressure control methods often rely on simple PID control strategies, which are difficult to cope with the changes in the dynamic characteristics of the system and the optimization requirements under complex working conditions. With the development of industrial automation and intelligent technologies, higher requirements are put forward for the control of cogeneration systems. It is not only necessary to maintain stable pressure, but also necessary to consider multiple factors such as combustion efficiency, environmental emissions, and system economy.

[0003] Currently, the Chinese patent with the application number CN202011065801.8 discloses a monitoring system for a cogeneration unit suitable for controlling the extraction steam pressure of a butterfly valve. The system includes: a temperature measurement module for detecting the temperature of the cogeneration unit monitoring device and uploading the data to the data acquisition and control module; a desuperheating by spraying module for preventing the overheating of the last-stage blades of the low-pressure cylinder and uploading the data to the data acquisition and control module; a vibration measurement module for monitoring the vibration on both sides of the low-pressure cylinder and uploading the data to the data acquisition and control module; a differential expansion measurement module for detecting the change of the differential expansion parameter of the low-pressure cylinder and uploading the data to the data acquisition and control module; a pressure measurement module for measuring the pressure and uploading the data to the data acquisition and control module; and a data acquisition and control module for online monitoring of the unit operation data, and for the on-off control and adjustment of the valves.

[0004] The related technologies are difficult to estimate the degree of combustion completion by combining the composition and content of the discharged waste, and plan to increase fuel or give an early warning to replace fuel, and it is difficult to achieve the state where the pressure value is maintained at the maximum efficiency of the main steam header. Summary of the Invention

[0005] The technical problem solved by the present invention is that the above-mentioned technologies are difficult to estimate the degree of combustion completion by combining the composition and content of the discharged waste, and plan to increase fuel or give an early warning to replace fuel, and it is difficult to achieve the state where the pressure value is maintained at the maximum efficiency of the main steam header.

[0006] To solve the above technical problem, the present invention provides the following technical solution:

[0007] A method for controlling the pressure of the main steam header system in cogeneration includes the following steps:

[0008] Step S1, collecting the main steam header pressure data, fuel flow data, flue gas composition data, and exhaust gas temperature data;

[0009] Step S2, perform dynamic calculation of combustion efficiency based on the collected data and output the combustion efficiency;

[0010] Step S3, construct a dynamic model of the main steam header pressure and output the pressure change rate;

[0011] Step S4, generate a fuel adjustment strategy based on the pressure prediction result and the combustion efficiency data;

[0012] Step S5, execute the fuel adjustment strategy and monitor the pressure change.

[0013] Preferably, the step S1 includes the following sub-steps:

[0014] Step S101, collect the main steam header pressure data through a pressure sensor, record the time stamp and output it as a pressure time series;

[0015] Step S102, collect the fuel flow data, monitor the fuel supply data through a mass flow meter, and synchronously obtain the fuel element analysis data, where the fuel element analysis data includes carbon content data, hydrogen content data and sulfur content data;

[0016] Step S103, use an infrared gas analyzer to collect the flue gas composition data, where the flue gas composition data includes oxygen concentration data, carbon monoxide concentration data and nitrogen oxide concentration data;

[0017] Step S104, measure the exhaust gas temperature data through a thermocouple and synchronously collect the ambient temperature data.

[0018] Preferably, the step S2 includes the following sub-steps:

[0019] Step S201, calculate the theoretical air volume data based on the fuel element analysis data, and the mathematical expression of the theoretical air volume data is:

[0020]

[0021] where, V0 is the theoretical air volume data, C% is the carbon content data, H% is the hydrogen content data, and S% is the sulfur content data;

[0022] Step S202, calculate the excess air coefficient according to the oxygen concentration data, and the mathematical expression of the excess air coefficient is:

[0023]

[0024] where, α is the excess air coefficient, O 2,dry % is the dry flue gas oxygen concentration, CO ppm is the carbon monoxide concentration.

[0025] Preferably, the step S2 further includes the following sub-steps:

[0026] Step S203, calculate the chemical unburned loss, and the mathematical expression of the chemical unburned loss is:

[0027]

[0028] where Q loss,CO is the chemical unburned loss, V gas is the flue gas volume flow rate, and 283 is the calorific value of carbon monoxide combustion;

[0029] Calculate the heat loss of the exhaust gas, and the mathematical expression of the heat loss of the exhaust gas is:

[0030] Q flue = m gas × c p × (T flue - T ambient );

[0031] where Q flue is the heat loss of the exhaust gas, m gas is the flue gas mass flow rate, c p is the specific heat capacity at constant pressure of the flue gas, T flue is the exhaust gas temperature data, and T ambient is the ambient temperature data;

[0032] Step S204, comprehensively calculate the combustion efficiency, and the mathematical expression of the combustion efficiency is:

[0033]

[0034] where η is the combustion efficiency, Q radiation is the radiant heat loss, H flue is the fuel calorific value, and F is the fuel flow rate data.

[0035] Preferably, the step S3 includes the following sub-steps:

[0036] Step S301, establish a dynamic model of the main steam header pressure, and the dynamic model of the main steam header pressure is:

[0037]

[0038] where is the pressure change rate, D gen is the steam generation rate, D load is the load demand, and α is the system inertia constant;

[0039] Step S302, the steam generation rate is calculated based on the combustion efficiency and the fuel flow rate data, and the mathematical expression of the steam generation rate is:

[0040]

[0041] Among them, h steam is the specific enthalpy of steam;

[0042] Step S303: Discretize the pressure model and construct a state-space expression for model predictive control.

[0043] Preferably, the step S4 includes the following sub-steps:

[0044] Step S401: Define the model predictive control objective function, and the model predictive control objective function is:

[0045]

[0046] Among them, P set is the target pressure value of the main steam header, P k is the main steam header pressure data, η max is the maximum combustion efficiency, ΔF is the fuel flow adjustment amount, w1 is the efficiency weight coefficient, and w2 is the fuel adjustment weight coefficient;

[0047] Define the constraint conditions, and the constraint conditions are:

[0048] The fuel flow data is within the preset combustion flow threshold, the excess air coefficient is within the preset excess air coefficient threshold, and the absolute value of the fuel flow adjustment amount is less than or equal to the maximum fuel flow adjustment amount.

[0049] Step S402: Convert the model predictive control objective function into the standard QP form, obtain the objective function, decompose and combine the objective function, and obtain the fuel flow adjustment amount ΔF for the next N steps k and the excess air coefficient adjustment amount α k for the next N steps, and obtain the first-step fuel flow adjustment amount ΔF1 and the first-step excess air coefficient adjustment amount α1;

[0050] Step S403: Send the first-step fuel flow adjustment amount ΔF1 and the first-step excess air coefficient adjustment amount α1 to the actuator.

[0051] Preferably, the step S5 includes the following sub-steps:

[0052] Step S501: If the combustion efficiency is lower than the preset low combustion efficiency for 3 consecutive times, trigger a primary warning signal;

[0053] Step S502: If the combustion efficiency continues to drop to the preset dangerous combustion efficiency and the excess air coefficient adjustment amount has reached the lower limit, trigger a high-level warning signal;

[0054] Step S503: Upload the primary warning signal and the advanced warning signal to the central monitoring system and push them to the operator's mobile terminal.

[0055] Preferably, step S5 further includes:

[0056] Step S504: Set the safety limit of the pressure change rate. If the pressure change rate exceeds the safety limit of the pressure change rate, switch to the manual control mode.

[0057] Step S505: Set the automatic calibration frequency and automatically calibrate the sensor data.

[0058] Preferably, step S3 further includes:

[0059] Step S304: Verify the model prediction error through historical data. If the error exceeds the preset error threshold, trigger the self-tuning of model parameters.

[0060] Preferably, step S4 further includes:

[0061] Step S404: Dynamically adjust the efficiency weight coefficient and the fuel adjustment weight coefficient of the model predictive control objective function. Increase the efficiency weight coefficient by the first percentage when the pressure deviation is greater than the preset pressure deviation threshold, and increase the fuel adjustment weight coefficient by the second percentage when the combustion efficiency is less than the preset combustion efficiency threshold.

[0062] Advantages of the present invention: By real-time monitoring of flue gas components and fuel data, calculating the degree of combustion sufficiency, dynamically adjusting the fuel flow rate and the excess air coefficient, the present invention improves the combustion efficiency and optimizes fuel utilization. At the same time, it reduces the content of emissions, meets the environmental protection requirements, enhances the stability of cogeneration through the model predictive control strategy, the warning mechanism ensures timely detection of problems, plans to increase or replace fuel, maintains the maximum efficiency of the main steam header, and realizes efficient and environmentally friendly operation. Description of the Drawings

[0063] Figure 1 It is a step flow chart of a pressure control method for a main steam header system of a cogeneration provided by an embodiment of the present invention. Detailed Embodiments

[0064] To make the above objects, features and advantages of the present invention more obvious and understandable, the following detailed description of the specific embodiments of the present invention is given in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of them.

[0065] Embodiment, referring to Figure 1 , provides a pressure control method for a main steam header system of a cogeneration, including the following steps:

[0066] Step S1, collect the main steam header pressure data, fuel flow data, flue gas composition data, and exhaust gas temperature data.

[0067] Step S2, perform dynamic calculation of combustion efficiency based on the collected data and output the combustion efficiency.

[0068] Step S3, construct a dynamic model of the main steam header pressure and output the pressure change rate.

[0069] Step S4, generate a fuel adjustment strategy according to the pressure prediction result and combustion efficiency data.

[0070] Step S5, execute the fuel adjustment strategy and monitor the pressure change.

[0071] Step S1 includes the following sub-steps:

[0072] Step S101, collect the main steam header pressure data through a pressure sensor, record the timestamp, and output it as a pressure time series.

[0073] Step S101 has collected the main steam header pressure data in real time and accurately, recorded the timestamp, and formed a pressure time series, providing data support for subsequent pressure change analysis and system stability evaluation.

[0074] Step S102, collect the fuel flow data, monitor the fuel supply data through a mass flow meter, and synchronously obtain the fuel elemental analysis data, which includes carbon content data, hydrogen content data, and sulfur content data.

[0075] Step S102 has accurately monitored the fuel flow and synchronously obtained the elemental analysis data of the fuel, including carbon, hydrogen, and sulfur contents, providing key information for fuel quality assessment and combustion efficiency calculation.

[0076] Step S103, use an infrared gas analyzer to collect the flue gas composition data, and the flue gas composition data includes oxygen concentration data, carbon monoxide concentration data, and nitrogen oxide concentration data.

[0077] Step S103 has accurately collected the oxygen, carbon monoxide, and nitrogen oxide concentration data in the flue gas using an infrared gas analyzer, providing a direct basis for environmental protection performance assessment and judgment of combustion sufficiency.

[0078] Step S104, measure the exhaust gas temperature data through a thermocouple and synchronously collect the ambient temperature data.

[0079] Step S104 has measured the exhaust gas temperature and synchronously collected the ambient temperature data, providing necessary information for calculating heat loss, evaluating combustion efficiency, and formulating energy-saving measures.

[0080] Step S1 comprehensively collects key data such as the main steam header pressure, fuel flow rate, elemental analysis, flue gas composition, and stack gas temperature, providing comprehensive and accurate basic information for combustion efficiency analysis, environmental performance evaluation, and subsequent control strategy formulation.

[0081] Step S2 includes the following sub-steps:

[0082] In step S201, the theoretical air volume data is calculated based on the fuel elemental analysis data. The mathematical expression for the theoretical air volume data is:

[0083]

[0084] where V0 is the theoretical air volume data, C% is the carbon content data, H% is the hydrogen content data, and S% is the sulfur content data.

[0085] Based on the fuel elemental analysis data, step S201 calculates the theoretical air volume data, providing basic data for subsequent calculation of the excess air coefficient and combustion efficiency.

[0086] In step S202, the excess air coefficient is calculated according to the oxygen concentration data. The mathematical expression for the excess air coefficient is:

[0087]

[0088] where α is the excess air coefficient, O 2,dry % is the dry flue gas oxygen concentration, and CO ppm is the carbon monoxide concentration.

[0089] According to the oxygen concentration data, step S202 calculates the excess air coefficient, which reflects the ratio of the actual air volume to the theoretical air volume and is used to evaluate the air excess situation during the combustion process.

[0090] Step S2 also includes the following sub-steps:

[0091] In step S203, the chemical unburned loss is calculated. The mathematical expression for the chemical unburned loss is:

[0092]

[0093] where Q loss,CO is the chemical unburned loss, V gas is the flue gas volume flow rate, and 283 is the calorific value of carbon monoxide combustion.

[0094] Calculate the heat loss of the exhaust gas. The mathematical expression for the heat loss of the exhaust gas is:

[0095] Q flue = m gas × c p × (T flue × Tambient );

[0096] Among them, Q flue is the heat loss due to flue gas discharge, m gas is the mass flow rate of flue gas, c p is the specific heat capacity of flue gas at constant pressure, T flue is the flue gas discharge temperature data, T ambient is the ambient temperature data.

[0097] Step S203 calculates the chemical unburned loss to evaluate the energy loss caused by incomplete combustion of fuel, and calculates the heat loss due to flue gas discharge to evaluate the heat loss carried away during the flue gas discharge process. Both together provide the necessary loss data for comprehensively calculating the combustion efficiency.

[0098] Step S204, comprehensively calculates the combustion efficiency. The mathematical expression of the combustion efficiency is:

[0099]

[0100] Among them, η is the combustion efficiency, Q radiation is the radiant heat loss, H flue is the calorific value of fuel, and F is the fuel flow rate data.

[0101] Step S204 comprehensively considers factors such as chemical unburned loss and heat loss due to flue gas discharge, calculates the combustion efficiency, intuitively reflects the energy utilization efficiency of the combustion process, and provides a clear indicator for combustion optimization.

[0102] Step S2 obtains the key parameters and efficiency indicators in the combustion process through comprehensive calculations of a series of sub-steps, providing data support for the optimization and adjustment of the combustion process.

[0103] Step S3 includes the following sub-steps:

[0104] Step S301, establishes a dynamic model of the main steam header pressure. The dynamic model of the main steam header pressure is:

[0105]

[0106] Among them, is the pressure change rate, D gen is the steam generation rate, D load is the load demand, and α is the system inertia constant.

[0107] Step S301 establishes a dynamic model of the main steam header pressure, describes the law of pressure change with time, and provides a theoretical basis for subsequent steam generation rate calculation and pressure control.

[0108] Step S302, calculates the steam generation rate based on the combustion efficiency and fuel flow rate data. The mathematical expression of the steam generation rate is:

[0109]

[0110] Among them, h steam is the specific enthalpy of steam.

[0111] Step S302 calculates the steam production based on the combustion efficiency and fuel flow data, realizes the association between the steam production and the combustion process, and provides data support for the energy balance and efficiency analysis of the system.

[0112] Step S303 discretizes the pressure model and constructs a state - space expression for model predictive control.

[0113] Step S303 discretizes the pressure model and constructs a state - space expression to make the model applicable to digital control systems, providing a feasible mathematical model for model predictive control.

[0114] Step S3 also includes:

[0115] Step S304 verifies the model prediction error through historical data. If the error exceeds the preset error threshold, it triggers the self - tuning of model parameters.

[0116] Step S304 verifies the model prediction error through historical data, evaluates the accuracy of the model. If the error exceeds the preset error threshold, it triggers the self - tuning of model parameters, automatically adjusts the model parameters to improve the prediction accuracy, ensures the reliability and stability of the model in practical applications, and provides guarantee for the long - term operation of the system.

[0117] Step S3 establishes and optimizes the dynamic model of the main steam header pressure, realizes the accurate calculation of steam production, constructs a state - space expression applicable to model predictive control, and at the same time ensures the prediction accuracy of the model, providing a basis for stable operation and efficient control.

[0118] Step S4 includes the following sub - steps:

[0119] Step S401 defines the model predictive control objective function, and the model predictive control objective function is:

[0120]

[0121] Among them, P set is the target pressure value of the main steam header, P k is the main steam header pressure data, η max is the maximum combustion efficiency, ΔF is the fuel flow adjustment amount, w1 is the efficiency weight coefficient, and w2 is the fuel adjustment weight coefficient.

[0122] Define the constraint conditions, and the constraint conditions are:

[0123] The fuel flow data is within the preset combustion flow threshold, the excess air coefficient is within the preset excess air coefficient threshold, and the absolute value of the fuel flow adjustment amount is less than or equal to the maximum fuel flow adjustment amount.

[0124] Step S401 defines the objective function of model predictive control, provides a clear goal for the subsequent optimization process, sets constraint conditions, including limitations on fuel flow data, excess air coefficient, and fuel flow adjustment amount, ensuring safety and feasibility during the adjustment process.

[0125] In step S402, the model predictive control objective function is transformed into the standard QP form to obtain the objective function. The objective function is decomposed and combined, and the fuel flow adjustment amounts ΔF for the next N steps k and the excess air coefficient adjustment amounts α for the next N steps k are obtained, and the first-step fuel flow adjustment amount ΔF1 and the first-step excess air coefficient adjustment amount α1 are obtained.

[0126] Step S402 transforms the model predictive control objective function into the standard QP form, which is convenient for solving using a QP solver. By decomposing and combining the objective function, the fuel flow adjustment amounts and excess air coefficient adjustment amounts for the next N steps are obtained, providing a basis for long-term optimization. The first-step fuel flow adjustment amount and the first-step excess air coefficient adjustment amount are extracted, providing execution instructions for immediate control.

[0127] In step S403, the first-step fuel flow adjustment amount ΔF1 and the first-step excess air coefficient adjustment amount α1 are sent to the actuator.

[0128] Step S403 sends the first-step adjustment amounts to the actuator, realizing the immediate adjustment of the combustion process and improving the response speed and accuracy of control.

[0129] Step S4 also includes:

[0130] In step S404, the efficiency weight coefficient and the fuel adjustment weight coefficient of the model predictive control objective function are dynamically adjusted. When the pressure deviation is greater than the preset pressure deviation threshold, the efficiency weight coefficient is increased by the first percentage. When the combustion efficiency is less than the preset combustion efficiency threshold, the fuel adjustment weight coefficient is increased by the second percentage.

[0131] Step S404 dynamically adjusts the efficiency weight coefficient and the fuel adjustment weight coefficient of the model predictive control objective function, enabling the control system to make adaptive adjustments according to the current operating conditions. When the pressure deviation is greater than the preset threshold, the efficiency weight coefficient is increased to prioritize ensuring the pressure stability of the system. When the combustion efficiency is less than the preset threshold, the fuel adjustment weight coefficient is increased to prioritize improving the combustion efficiency, thereby optimizing energy utilization and reducing emissions.

[0132] In step S4, the fuel flow rate and the excess air coefficient are adjusted through a model predictive control method to optimize the combustion process. This step takes into account the constraints of the fuel flow rate, the excess air coefficient, and the fuel flow rate adjustment amount. By converting it into a standard quadratic programming form for solution, the adjustment amounts for the next N steps are obtained, and the adjustment amount for the first step is sent to the actuator. In addition, the weight coefficients of the objective function are dynamically adjusted according to the pressure deviation and the combustion efficiency to adapt to different operating conditions.

[0133] Step S5 includes the following sub-steps:

[0134] In step S501, if the combustion efficiency is lower than the preset low combustion efficiency for three consecutive times, a primary warning signal is triggered.

[0135] When the combustion efficiency is lower than the preset low combustion efficiency for three consecutive times, triggering a primary warning signal helps the operator to promptly discover the problem of the decreasing combustion efficiency and take corresponding adjustment measures to prevent the further decrease of the combustion efficiency.

[0136] In step S502, if the combustion efficiency continues to drop to the preset dangerous combustion efficiency and the adjustment amount of the excess air coefficient has reached the lower limit, a high-level warning signal is triggered.

[0137] In step S502, if the combustion efficiency continues to drop to the preset dangerous combustion efficiency and the adjustment amount of the excess air coefficient has reached the lower limit, a high-level warning signal is triggered, indicating that the combustion system has been in a relatively dangerous state and the operator needs to take immediate emergency measures to avoid possible failures or accidents.

[0138] In step S503, the primary warning signal and the high-level warning signal are uploaded to the central monitoring system and pushed to the operator's mobile terminal.

[0139] In step S503, uploading the primary warning signal and the high-level warning signal to the central monitoring system and pushing them to the operator's mobile terminal ensures that the warning signals can be conveyed to the operator in a timely and accurate manner. No matter where they are, the operator can quickly respond and handle the warning situation.

[0140] Step S5 also includes:

[0141] In step S504, a safety limit for the pressure change rate is set. If the pressure change rate exceeds the safety limit for the pressure change rate, the manual control mode is switched.

[0142] In step S504, setting a safety limit for the pressure change rate and switching to the manual control mode if the pressure change rate exceeds this limit helps to prevent system instability or damage caused by too rapid pressure changes. By switching to the manual control mode, the operator can respond more flexibly to emergencies.

[0143] Step S505: Set the automatic calibration frequency and automatically calibrate the sensor data.

[0144] Step S505 sets the automatic calibration frequency and automatically calibrates the sensor data, ensuring the accuracy and reliability of the sensor data and providing accurate basic data for the monitoring and control of the combustion system. At the same time, the automatic calibration also reduces the burden on the operator and improves work efficiency.

[0145] Step S5 realizes the real-time monitoring, early warning and safety control of the combustion process, ensuring the stable operation of the combustion system and the timely response of the operator. This step not only focuses on the change of combustion efficiency, but also considers the safety of the pressure change rate and the accuracy of the sensor, providing strong support for the comprehensive monitoring and management of combustion.

[0146] The present invention can calculate the degree of combustion sufficiency in real time by collecting flue gas composition data and fuel element analysis data. Combining with the dynamic calculation of combustion efficiency, it can adjust the fuel flow rate and excess air coefficient in a timely manner to ensure that the combustion process is carried out in the best state, thereby improving combustion efficiency. By using flow data to construct a dynamic model of the main steam header pressure, it can accurately predict the pressure change rate and provide a scientific basis for fuel adjustment. Through the model predictive control strategy, the fuel flow rate can be dynamically adjusted to avoid overfeeding or underfeeding, ensuring the full utilization of fuel and reducing the fuel consumption cost. By real-time monitoring the flue gas composition data, problems existing in the combustion process can be found in a timely manner, such as too high carbon monoxide content or excessive nitrogen oxide emissions caused by insufficient combustion. By adjusting the fuel flow rate and excess air coefficient, the combustion process can be optimized and the emission content can be reduced to meet environmental protection requirements. By constructing a dynamic model of the main steam header pressure and combining with the model predictive control strategy, precise control of the system pressure can be achieved, enhancing the stability of the system. Setting the safety limit of the pressure change rate and the automatic calibration frequency can ensure that the system can be switched to the manual control mode in a timely manner under abnormal conditions and ensure the accuracy of the sensor data. When the combustion efficiency is continuously lower than the preset threshold, a primary warning signal is triggered; when the combustion efficiency continues to decline to a dangerous level and the adjustment amount of the excess air coefficient has reached the lower limit, a high-level warning signal is triggered, which helps the operator to detect combustion problems in a timely manner and plan to increase the fuel or change the fuel type to ensure the maximization of the main steam header efficiency and avoid system failures or safety accidents.

[0147] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. Among them, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk. These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured article including an instruction device, and the instruction device implements the functions specified in one process Figure 1 or a plurality of processes and / or boxes Figure 1 or a plurality of boxes.

[0148] 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 preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A method for controlling the pressure of the main steam header system of a combined heat and power plant, characterized in that, It includes the following steps: Step S1, collect the main steam header pressure data, fuel flow data, flue gas composition data, and exhaust gas temperature data; Step S2, perform dynamic calculation of combustion efficiency based on the collected data and output the combustion efficiency; Step S3, construct a dynamic model of the main steam header pressure and output the pressure change rate; Step S4, generate a fuel adjustment strategy according to the pressure prediction result and combustion efficiency data; Step S5, execute the fuel adjustment strategy and monitor the pressure change.

2. The pressure control method of a main steam header system for combined heat and power generation according to claim 1, wherein The said Step S1 includes the following sub-steps: Step S101, collect the main steam header pressure data through a pressure sensor, record the timestamp and output it as a pressure time series; Step S102, collect the fuel flow data, monitor the fuel supply data through a mass flow meter, and synchronously obtain the fuel elemental analysis data, where the fuel elemental analysis data includes carbon content data, hydrogen content data, and sulfur content data; Step S103, use an infrared gas analyzer to collect the flue gas composition data, where the flue gas composition data includes oxygen concentration data, carbon monoxide concentration data, and nitrogen oxide concentration data; Step S104, measure the exhaust gas temperature data through a thermocouple and synchronously collect the ambient temperature data.

3. The pressure control method for the main steam header system of a combined heat and power generation according to claim 2, characterized in that, The said Step S2 includes the following sub-steps: Step S201, calculate the theoretical air volume data based on the fuel elemental analysis data, and the mathematical expression of the theoretical air volume data is: where, V0 is the theoretical air volume data, C% is the carbon content data, H% is the hydrogen content data, and S% is the sulfur content data; Step S202, calculate the excess air coefficient according to the oxygen concentration data, and the mathematical expression of the excess air coefficient is: where α is the excess air coefficient, O 2,dry % is the oxygen concentration in dry flue gas, CO ppm is the carbon monoxide concentration.

4. The pressure control method for the main steam header system of a combined heat and power generation according to claim 3, wherein, The said Step S2 also includes the following sub-steps: Step S203, calculate the chemical unburned loss, and the mathematical expression of the chemical unburned loss is: Among them, Q loss,CO is the unburned chemical loss, V gas is the flue gas volume flow rate, and 283 is the calorific value of carbon monoxide combustion; Calculate the heat loss of the exhaust gas, and the mathematical expression of the heat loss of the exhaust gas is: Q flue = m gas × c p × (T flue × T ambient ); Among them, Q flue is the heat loss due to flue gas discharge, m gas is the mass flow rate of flue gas, c p is the specific heat capacity at constant pressure of flue gas, T flue is the flue gas discharge temperature data, T ambient is the ambient temperature data; Step S204, comprehensively calculate the combustion efficiency, and the mathematical expression of the combustion efficiency is: Among them, η is the combustion efficiency, Q radiation is the radiant heat loss, H flue is the calorific value of the fuel, and F is the fuel flow rate data.

5. A method for controlling the pressure of the main steam header system in a combined heat and power generation, as described in claim 4, characterized in that, The said Step S3 includes the following sub-steps: Step S301, establish a dynamic model of the main steam header pressure, and the dynamic model of the main steam header pressure is: Among them, is the pressure change rate, D gen is the steam production rate, D load is the load demand, and α is the system inertia constant; Step S302, calculate the steam generation based on the combustion efficiency and fuel flow data, and the mathematical expression of the steam generation is: where h steam is the specific enthalpy of steam; Step S303, discretize the pressure model and construct a state space expression for model predictive control.

6. The pressure control method of a main steam header system for combined heat and power generation according to claim 5, characterized in that, The said Step S4 includes the following sub-steps: Step S401, define the model predictive control objective function, and the model predictive control objective function is: Among them, P set is the target pressure value of the main steam header, P k is the main steam header pressure data, η max is the maximum combustion efficiency, ΔF is the fuel flow adjustment amount, w1 is the efficiency weight coefficient, and w2 is the fuel adjustment weight coefficient; Define the constraint conditions, and the constraint conditions are: The fuel flow data is within the preset combustion flow threshold, the excess air coefficient is within the preset excess air coefficient threshold, and the absolute value of the fuel flow adjustment amount is less than or equal to the maximum fuel flow adjustment amount; Step S402: Transform the model predictive control objective function into the standard QP form, obtain the objective function, decompose and combine the objective function, and obtain the fuel flow adjustment amount ΔF for the next N steps through the QP solver k and the excess air coefficient adjustment amount α for the next N steps k , and obtain the first-step fuel flow adjustment amount ΔF1 and the first-step excess air coefficient adjustment amount α1; Step S403, send the first-step fuel flow adjustment amount ΔF1 and the first-step excess air coefficient adjustment amount α1 to the actuator.

7. A method for controlling the pressure of the main steam header system of a combined heat and power generation, as described in claim 6, wherein The said Step S5 includes the following sub-steps: Step S501, if the combustion efficiency is lower than the preset low combustion efficiency for 3 consecutive times, trigger a primary warning signal; Step S502: If the combustion efficiency continuously drops to the preset dangerous combustion efficiency and the adjustment amount of the excess air coefficient has reached the lower limit, trigger a high-level warning signal; Step S503: Upload the primary warning signal and the high-level warning signal to the central monitoring system and push them to the operator's mobile terminal.

8. The pressure control method of a cogeneration main steam header system according to claim 5, wherein Step S5 further includes: Step S504: Set the safety limit of the pressure change rate. If the pressure change rate exceeds the safety limit of the pressure change rate, switch to the manual control mode; Step S505: Set the automatic calibration frequency and automatically calibrate the sensor data.

9. The pressure control method for the main steam header system of a combined heat and power generation according to claim 5, characterized in that, Step S3 further includes: Step S304: Verify the model prediction error through historical data. If the error exceeds the preset error threshold, trigger the self-tuning of the model parameters.

10. A method for controlling the pressure of the main steam header system in a combined heat and power generation, as described in claim 5, characterized in that, Step S4 further includes: Step S404: Dynamically adjust the efficiency weight coefficient and the fuel adjustment weight coefficient of the model predictive control objective function. Increase the efficiency weight coefficient by the first percentage when the pressure deviation is greater than the preset pressure deviation threshold, and increase the fuel adjustment weight coefficient by the second percentage when the combustion efficiency is less than the preset combustion efficiency threshold.

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