Adjustable steam extraction and heat supply intelligent scheduling method, system and equipment and storage medium

Abstract

The invention discloses an adjustable steam extraction and heat supply intelligent scheduling method, system and equipment and a storage medium, and relates to the technical field of thermoelectric steam extraction and heat supply scheduling and control, and the method comprises the steps: collecting operation parameters of a steam turbine, analyzing response characteristics under different steam extraction paths, and obtaining a basic capability boundary; establishing a steam extraction control strategy, and performing steam extraction path screening and steam extraction path parameter configuration according to the basic capability boundary; the steam extraction control strategy is decomposed into control signals, and the control signals are issued to an execution unit of the steam extraction adjusting device. According to the method, the adjusting capability of each steam extraction path under different load conditions is realized, path screening and parameter configuration are performed based on the capability boundary, dynamic judgment of the optimal steam extraction path under the current operation state is realized, matching and optimal response between scheduling logic and physical equipment behaviors are guaranteed, and the scheduling efficiency is improved. The adjusting efficiency and the control precision of the steam extraction behavior are improved, and the operability, the execution efficiency and the system consistency of the control instruction are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of thermoelectric extraction steam heating scheduling and control, and in particular to an adjustable extraction steam heating intelligent scheduling method, system, equipment and storage medium. Background Art

[0002] With the deepening transformation of the energy system towards clean and efficient, cogeneration systems have become an important technical path for centralized heating in cities in my country and even around the world due to their characteristics of synergistic output of heat and electricity and high energy utilization efficiency. In a typical cogeneration system, steam extraction from the steam turbine is used as a means of providing heat source, and the response to heat load demand is achieved by adjusting the flow of different steam extraction stages of the steam turbine. At present, a large number of cogeneration power plants in my country, especially small and medium-sized units mainly used for industrial steam supply or regional heating, generally face the coupling contradiction between improving the peak-shaving capacity of the power grid and stabilizing the demand for heating: on the one hand, the units need to adapt to the large-scale deep adjustment requirements during the off-peak period of the power grid; on the other hand, the heating system requires a stable and continuous heat source, especially during the heating season, which places higher demands on the rapid adjustment capability and scheduling accuracy of the steam extraction path.

[0003] Early solutions often used static extraction steam condition control or manually set switching points to adjust the steam source. These solutions relied primarily on operator experience or heuristic control strategies. Modeling the response time, steam quality, and flow regulation characteristics of different extraction steam paths (such as medium-pressure extraction, hot re-extraction, and cold re-extraction) was inaccurate, resulting in switching lag and significant regulation deviation. In recent years, with the convergence of information technology and automation, some research has begun to introduce scheduling optimization methods such as model-based predictive control (MPC), fuzzy control, and expert systems, to some extent achieving a transition from empirical to rule-based extraction steam control. However, existing solutions commonly suffer from the following bottlenecks: incomplete understanding of the dynamic response characteristics of extraction steam paths and a lack of accurate data-driven modeling methods, resulting in insufficient adaptability and robustness of regulation strategies. Extraction steam control strategies mostly use static preset parameters, making it difficult to automatically generate optimal path selection and parameter setting logic based on dynamic load changes. There is also a lack of a unified mapping mechanism between control signal generation and the physical interface of the regulation device, resulting in lags, errors, and even inconsistencies between strategy issuance and equipment response, affecting overall thermal power matching efficiency. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problems solved by the present invention are: insufficient understanding of the response characteristics of the extraction path in the existing cogeneration system, lack of pertinence and adaptability of the extraction control strategy, delays and inconsistencies in the decomposition and execution of the control signal, and how to establish a dynamic response extraction path screening and parameter configuration mechanism by constructing an extraction capacity boundary model driven by operating parameters, and efficiently mapping the control strategy into a control signal that can be recognized by the execution device, so as to achieve coordinated control and dynamic optimization scheduling between the heating side and the power side.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: an intelligent scheduling method for adjustable steam extraction heating, comprising collecting the operating parameters of the steam turbine, analyzing the response characteristics under different steam extraction paths, and obtaining the basic capacity boundary; establishing a steam extraction control strategy, screening the steam extraction paths and configuring the steam extraction path parameters according to the basic capacity boundary; decomposing the steam extraction control strategy into control signals, and sending them to the execution unit of the steam extraction regulation device.

[0007] As a preferred solution of the adjustable extraction steam heating intelligent scheduling method described in the present invention, the collection of turbine operating parameters includes real-time collection of main steam pressure, main steam temperature, extraction steam pressure and extraction steam temperature of each extraction stage through sensors, and collection of the displacement position signal of the rotating partition.

[0008] As a preferred solution of the adjustable steam extraction heating intelligent scheduling method described in the present invention, the analysis of the response characteristics under different steam extraction paths includes analyzing the transient change trends of steam pressure and main steam temperature based on the operating parameters of the turbine, evaluating the sensitivity of the steam extraction flow to load disturbances and the execution structure action delay.

[0009] As a preferred solution of the adjustable steam extraction heating intelligent scheduling method described in the present invention, the basic capacity boundary is obtained, which includes setting the steam pressure threshold, steam temperature stability range, action threshold of the regulating device and dynamic response time according to different steam extraction paths based on transient change trends and evaluation results.

[0010] As a preferred solution of the adjustable steam extraction heating intelligent scheduling method described in the present invention, the steam extraction control strategy includes comparing and screening candidate steam extraction paths based on the basic capacity boundary, and screening out the target steam extraction path with the shortest dynamic response time and meeting the basic capacity boundary.

[0011] Based on the target extraction path, the extraction flow set value, adjustment rate coefficient and path switching holding time are determined according to the current turbine load state and the boundary value in the basic capacity boundary, and the control parameter set of the control execution unit is obtained.

[0012] As a preferred solution of the adjustable steam extraction heating intelligent scheduling method described in the present invention, the decomposition of the steam extraction control strategy into control signals includes converting the steam extraction flow set value in the control parameter set of the control execution unit into an opening control signal of the regulating device according to the control function, converting the regulation rate coefficient into an action frequency control signal, and converting the path switching holding time into a timing execution control signal.

[0013] As a preferred solution of the adjustable steam extraction heating intelligent scheduling method described in the present invention, the execution unit sent to the steam extraction regulating device includes packaging the control signal into a control instruction frame according to a preset communication protocol, and transmitting it to the steam extraction regulating device interface. After the interface receives the instruction frame, it drives the corresponding execution component.

[0014] Another object of the present invention is to provide an intelligent scheduling system for adjustable steam extraction heating, which can operate collaboratively through three modules: parameter modeling, strategy generation and control execution, thereby solving the problems in existing systems such as the lack of a basis for modeling steam extraction capacity, the lack of dynamic path screening, and the disconnection between strategy control signals and the responses of regulating devices.

[0015] As an optimal solution of the adjustable steam extraction heating intelligent scheduling system described in the present invention, it includes: a parameter modeling module, a strategy generation module, and a control execution module; the parameter modeling module includes a data acquisition unit and a boundary modeling unit, the data acquisition unit is used to collect the operating parameters of the turbine, and the boundary modeling unit is used to analyze the response characteristics under different steam extraction paths and output the capacity boundary parameters of each path; the strategy generation module includes a path determination unit and a parameter configuration unit, the path determination unit is used to screen the steam extraction paths that meet the requirements according to the capacity boundary and heat load conditions, and the parameter configuration unit is used to set the target steam extraction flow, adjustment opening, rate and switching time to generate a parameter set; the control execution module includes a signal conversion unit and an instruction issuing unit, the signal conversion unit is used to convert the parameter set into an executable control signal through a control function, and the instruction issuing unit is used to send the control signal to the execution unit of the steam extraction device to drive the adjustment action.

[0016] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement a step of an intelligent scheduling method for adjustable steam extraction heating.

[0017] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of an intelligent scheduling method for adjustable steam extraction heating.

[0018] The beneficial effects of the present invention are as follows: by collecting the operating parameters of the steam turbine and analyzing the response characteristics under different extraction paths, quantitative modeling of the regulation capacity, steam quality range and response dynamics of each extraction path under different load conditions is realized, and the capacity boundary of the extraction system under different operating states is clarified; by constructing an extraction control strategy and performing path screening and parameter configuration based on the capacity boundary, dynamic judgment of the optimal extraction path under the current operating state and adaptive setting of the corresponding regulation parameters are realized, thereby ensuring the matching and optimal response between the scheduling logic and the physical equipment behavior, and improving the regulation efficiency and control accuracy of the extraction behavior; by decomposing the extraction control strategy into standardized control signals and sending them to the execution unit, the abstract control parameters are accurately mapped to valve opening control signals, action frequency signals and path switching instructions, thereby driving the rotary partition, center door and other extraction regulation devices to execute actions, and constructing a closed-loop chain from control logic to physical regulation, thereby improving the feasibility, execution efficiency and system consistency of the control instructions. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 This is an overall flow chart of an intelligent scheduling method for adjustable steam extraction heating provided by the first embodiment of the present invention.

[0021] Figure 2 This is an overall flow chart of an adjustable steam extraction heating intelligent scheduling system provided in the second embodiment of the present invention. DETAILED DESCRIPTION

[0022] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0023] Example 1, with reference to Figure 1 , which is an embodiment of the present invention, provides an adjustable extraction steam heating intelligent scheduling method, comprising:

[0024] S1: Collect the operating parameters of the steam turbine, analyze the response characteristics under different steam extraction paths, and obtain the basic capacity boundary.

[0025] Furthermore, the collection of operating parameters of the steam turbine includes real-time collection of main steam pressure, main steam temperature, extraction pressure and extraction temperature of each extraction stage through sensors, and collection of displacement position signals of the rotating partition.

[0026] Furthermore, the response characteristics under different extraction paths are analyzed, including the transient change trends of steam pressure and main steam temperature based on the operating parameters of the turbine, and the evaluation of the sensitivity of the extraction flow rate to load disturbances and the delay of the execution structure action.

[0027] It should be noted that based on the operating parameters collected by the sensor, the transient change trend of the steam pressure is calculated and expressed as:

[0028]

[0029] in, represents the transient rate of change of steam pressure at the i-th extraction stage, The actual steam pressure value of the i-th extraction stage at the current time t, It represents the historical value of steam pressure of the i-th extraction stage at the previous sampling time t-Δt, where t is the current sampling time point and Δt is the sampling period.

[0030] Calculate the transient change trend of the main steam temperature, which is expressed as:

[0031]

[0032] Where, ΔT s (t) is the transient rate of change of main steam temperature at time t, T s (t) is the real-time collected value of the main steam temperature at time t, T s (t-Δt) is the historical collected value of the main steam temperature at the previous moment.

[0033] A preferred solution for the transient rate of change is: And ΔT s (t)<0.05%, it is judged to be in a stable state.

[0034] like And ΔT s If (t)≥0.05%, it is judged to be a disturbance state.

[0035] The sensitivity coefficient is used to evaluate the responsiveness of the extraction steam path to load disturbances, which is expressed as:

[0036]

[0037] Among them, γ i is the adjustment sensitivity coefficient of the i-th extraction steam path, The change in steam extraction flow rate of path i within the disturbance window, ΔL is the change in load disturbance during the evaluation period from the moment the load disturbance occurs to the time when the system reaches steady state.

[0038] A preferred solution for adjusting the sensitivity coefficient of the extraction steam path is: if γ i If ≥0.4, it is judged as high sensitivity.

[0039] If γ i If <0.4, it is judged as low sensitivity.

[0040] The action response characteristics of the rotating diaphragm are analyzed, and the time delay required for the regulating structure to complete the target displacement from receiving the instruction is calculated, which is expressed as:

[0041]

[0042] in, is the delay of the regulating structure action corresponding to the i-th path, t resp is the time when the control command is issued, t cmd The time point when the rotating diaphragm reaches the target displacement.

[0043] A preferred solution for delaying the action of the regulating structure corresponding to the path is: It is judged as a quick response.

[0044] like It is judged as a hysteresis response.

[0045] Furthermore, the basic capability boundary is obtained, including setting the steam pressure threshold, steam temperature stability range, action threshold of the regulating device and dynamic response time according to different steam extraction paths based on transient change trends and evaluation results.

[0046] It should also be noted that when it is judged to be in a stable state, the steam pressure threshold is set to: The steam temperature stability range is set to

[0047] When it is judged to be a disturbance state, the steam pressure threshold is set to: The steam temperature stability range is set to

[0048] in, is the average steam pressure of the i-th extraction path under steady-state conditions, Indicates the average sampling temperature value of the main steam temperature under steady-state conditions.

[0049] When it is determined to be in a high-sensitivity state, the action threshold of the regulating device is preferably set so that the relative displacement of the rotating diaphragm does not exceed 2.5% of the rated opening.

[0050] When it is determined to be in a low sensitivity state, the action threshold of the regulating device is preferably set so that the relative displacement of the rotating diaphragm is not less than 6% of the rated opening.

[0051] When the fast response state is determined, the response time is set to be less than or equal to 3 seconds.

[0052] When the response is judged to be in a hysteresis state, the response time is set to be greater than or equal to 6s.

[0053] S2: Establish a steam extraction control strategy, and select and configure steam extraction paths based on basic capacity boundaries.

[0054] Furthermore, the steam extraction control strategy includes comparing and screening candidate steam extraction paths based on the basic capability boundary, and screening out the target steam extraction path with the shortest dynamic response time and meeting the basic capability boundary.

[0055] Based on the target extraction path, the extraction flow set value, adjustment rate coefficient and path switching holding time are determined according to the current turbine load state and the boundary value in the basic capacity boundary, and the control parameter set of the control execution unit is obtained.

[0056] It should be noted that the following indicators of each candidate steam extraction path are obtained respectively: steam pressure change rate, steam temperature change rate, adjustment sensitivity coefficient, structural action response delay, and the current operating state of each path is compared with the preset multi-threshold criteria (stable state, disturbance state, high / low sensitivity, fast / hysteresis response) to determine the category to which the current state of each path belongs. The real-time boundary parameters of each candidate path are compared with the boundary performance requirements required by the current scheduling target: if all parameters of the path meet the criterion interval corresponding to the target state, it will be marked as an "available path"; if any parameter of the path exceeds the corresponding criterion tolerance upper limit, the path will be excluded from participating in the current scheduling, and among all the "available paths" that meet the criterion conditions, their dynamic response performance is further compared, that is, If the response time is the smallest, the path with the shortest response time is selected as the target steam extraction path. Based on the selected target path, control parameters such as steam flow set value, adjustment speed coefficient and path switching holding time are extracted from its historical operation boundary data to complete the closed loop from path selection to strategy parameter generation.

[0057] S3: Decompose the steam extraction control strategy into control signals and send them to the execution unit of the steam extraction regulating device.

[0058] Furthermore, decomposing the steam extraction control strategy into control signals includes converting the steam extraction flow set value in the control parameter set of the control execution unit into an opening control signal of the regulating device according to the control function, converting the regulation rate coefficient into an action frequency control signal, and converting the path switching holding time into a timing execution control signal.

[0059] It should also be noted that the extraction steam flow setpoint control function is expressed as:

[0060]

[0061] Among them, θ i is the target opening control signal of the regulating device, f Q (.) is the extraction steam flow set value control function, which is the mapping function that converts the thermal load response demand into the physical opening instruction. is the extraction steam flow set value of path i, k Q is the linear response coefficient of the path adjustment device, b Q It is the response offset or initial opening bias of the path adjustment device.

[0062] The control function of the adjustment rate coefficient is expressed as:

[0063]

[0064] Among them, f i is the frequency of the device's regulating action, f λ (.) is the rate control function, λ i represents the adjustment rate coefficient corresponding to the i-th path, k λ is the action frequency coefficient factor, is the power adjustment factor.

[0065] The path switching hold time control function is expressed as:

[0066]

[0067] Among them, φ i (t) is the switching execution trigger signal of path i. When the value is 1, it means that the system meets the minimum holding time of path switching. When the value is 0, it means that the holding time has not been met and immediate switching is prohibited to ensure system stability. Path switching can be executed. start Indicates the time point when the path switching logic starts timing. Indicates the path switching holding time of the i-th path.

[0068] Furthermore, the execution unit sent to the steam extraction regulating device includes packaging the control signal into a control instruction frame according to a preset communication protocol, transmitting it to the steam extraction regulating device interface, and driving the corresponding execution component after receiving the instruction frame.

[0069] It should also be noted that, according to the PROFIBUS industrial communication protocol, control signals are packaged and encapsulated into standardized control command frames. Each control command frame contains an operation instruction code, parameter field, address field, and checksum field. These packaged command frames are centrally dispatched by the command issuing unit in the control execution module and transmitted to the interface module of the extraction steam control device according to the specified data link protocol. The interface module supports asynchronous reception of control command frames and parses the command content after completing data verification. After parsing, the control command content is translated into low-level drive electrical signals by the built-in microcontroller unit (MCU), which directly acts on actuator components such as servo motors, rotary diaphragms, and electric control valves to achieve the physical operation of the control device. To prevent control execution delays or false triggering, the system is equipped with a command confirmation mechanism. After each control action is completed, the actuator unit automatically sends a confirmation signal back to the control module for closed-loop verification of the control signal execution status. If the receiving end does not send back a valid response signal within a specified time, the system automatically resends the control command frame and records the abnormal status to facilitate operation management and fault tracing.

[0070] Example 2, reference Figure 2 , which is an embodiment of the present invention, provides an adjustable steam extraction heating intelligent scheduling system, including a parameter modeling module 100, a strategy generation module 200, and a control execution module 300.

[0071] Among them, S4: the parameter modeling module 100 includes a data acquisition unit 101 and a boundary modeling unit 102. The data acquisition unit 101 is used to collect the operating parameters of the steam turbine, and the boundary modeling unit 102 is used to analyze the response characteristics under different steam extraction paths and output the capacity boundary parameters of each path.

[0072] It should also be noted that the data collection unit 101 transmits the collected operating parameters to the boundary modeling unit 102 , and the capability boundary parameters output by the boundary modeling unit 102 are passed as input to the path determination unit 201 .

[0073] S5: The strategy generation module 200 includes a path determination unit 201 and a parameter configuration unit 202. The path determination unit 201 is used to select a steam extraction path that meets the requirements based on the capacity boundary and heat load conditions. The parameter configuration unit 202 is used to set the target steam extraction flow rate, adjust the opening, rate and switching time, and generate a parameter set.

[0074] It should also be noted that the target steam extraction path determined by the path determination unit 201 is transmitted as input to the parameter configuration unit 202 , and the control parameter set generated by the parameter configuration unit 202 is transmitted as input to the signal conversion unit 301 .

[0075] S6: The control execution module 300 includes a signal conversion unit 301 and an instruction issuing unit 302. The signal conversion unit 301 is used to convert the parameter set into an executable control signal through a control function. The instruction issuing unit 302 is used to send the control signal to the execution unit of the steam extraction device to drive the adjustment action.

[0076] It should also be noted that the control signal generated by the signal conversion unit 301 is transmitted to the instruction issuing unit 302, and the instruction issuing unit 302 issues the control signal to the execution unit of the steam extraction regulating device.

[0077] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program code.

[0078] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0079] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0080] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having logic gate circuits for implementing logical functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc. It should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention and are not intended to be limiting. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced with equivalents without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications should be encompassed by the claims of the present invention.

Claims

1. An intelligent scheduling method for adjustable steam extraction heating, characterized in that: include: Collect steam turbine operating parameters, analyze response characteristics under different steam extraction paths, and obtain basic capacity boundaries; Establish steam extraction control strategy, screen steam extraction paths and configure steam extraction path parameters according to basic capacity boundaries; The extraction steam control strategy is decomposed into control signals and sent to the execution unit of the extraction steam regulating device.

2. The intelligent scheduling method for adjustable steam extraction heating according to claim 1, characterized in that: The collection of the operating parameters of the steam turbine includes collecting the main steam pressure, the main steam temperature, the extraction pressure and the extraction temperature of each extraction stage in real time through sensors, and collecting the displacement position signal of the rotating partition.

3. The intelligent scheduling method for adjustable steam extraction heating according to claim 1 or 2, characterized in that: The analysis of response characteristics under different extraction paths includes analyzing transient change trends of steam pressure and main steam temperature based on turbine operating parameters, and evaluating the sensitivity of extraction flow to load disturbances and the delay in executing structural actions.

4. The intelligent scheduling method for adjustable steam extraction heating according to claim 3, characterized in that: Obtaining the basic capability boundary includes setting the steam pressure threshold, steam temperature stability range, action threshold of the regulating device, and dynamic response time according to different steam extraction paths based on transient change trends and evaluation results.

5. The intelligent scheduling method for adjustable steam extraction heating according to any one of claims 1, 2 or 4, characterized in that: The steam extraction control strategy includes comparing and screening candidate steam extraction paths based on the basic capability boundary, and screening out the target steam extraction path with the shortest dynamic response time and meeting the basic capability boundary; Based on the target extraction path, the extraction flow set value, adjustment rate coefficient and path switching holding time are determined according to the current turbine load state and the boundary value in the basic capacity boundary, and the control parameter set of the control execution unit is obtained.

6. The intelligent scheduling method for adjustable steam extraction heating according to claim 5, characterized in that: Decomposing the steam extraction control strategy into control signals includes converting the steam extraction flow rate set value in the control parameter set of the control execution unit into an opening control signal of the regulating device according to the control function, converting the regulation rate coefficient into an action frequency control signal, and converting the path switching holding time into a timing execution control signal.

7. The intelligent scheduling method for adjustable steam extraction heating according to any one of claims 1, 2, 4 or 6, characterized in that: The execution unit sent to the steam extraction regulating device includes packaging the control signal into a control instruction frame according to a preset communication protocol and transmitting it to the steam extraction regulating device interface. After the interface receives the instruction frame, it drives the corresponding execution component.

8. An intelligent scheduling system for adjustable steam extraction heating according to any one of claims 1 to 7, characterized in that: It includes a parameter modeling module (100), a strategy generation module (200), and a control execution module (300); The parameter modeling module (100) includes a data acquisition unit (101) and a boundary modeling unit (102), wherein the data acquisition unit (101) is used to acquire operating parameters of the steam turbine, and the boundary modeling unit (102) is used to analyze response characteristics under different steam extraction paths and output capacity boundary parameters of each path; The strategy generation module (200) includes a path determination unit (201) and a parameter configuration unit (202), wherein the path determination unit (201) is used to select a steam extraction path that meets the requirements according to the capacity boundary and the heat load condition, and the parameter configuration unit (202) is used to set the target steam extraction flow rate, the adjustment opening, the rate and the switching time, and generate a parameter set; The control execution module (300) includes a signal conversion unit (301) and an instruction issuing unit (302). The signal conversion unit (301) is used to convert a parameter set into an executable control signal through a control function, and the instruction issuing unit (302) is used to send the control signal to the execution unit of the steam extraction device to drive the adjustment action.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the adjustable steam extraction heating intelligent scheduling method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the adjustable steam extraction heating intelligent scheduling method according to any one of claims 1 to 7 are implemented.

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