Heat exchange unit circulating pump energy-saving optimization system based on fuzzy PID (Proportion Integration Differentiation) control

Abstract

The invention discloses a heat exchange unit circulating pump energy-saving optimization system based on fuzzy PID control, relates to the technical field of automatic control, and aims at solving the technical problems that a traditional control strategy is high in energy consumption, inaccurate in adjustment and large in equipment loss, and the heat exchange unit circulating pump energy-saving optimization system comprises a model identification module which identifies a simulation control object through a field experiment, the simulation control object comprises a heat exchange unit and a unit heat supply network system thereof; the simulation heat supply network model is established by taking a simulation control object as a boundary, a simulation data input object of the simulation heat supply network model comprises a unit heat supply network system, and simulation data output of the simulation heat supply network model comprises main vapor pressure, unit load, flow, valve opening, pressure and temperature. Linkage is achieved through a multi-order fuzzy controller of the heat supply network fuzzy PID module. The problem of large flow difference continuous energy consumption caused by slow response of a traditional fixed parameter PID is avoided, and the basic operation energy consumption of the circulating pump is directly reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic control, and more specifically, to an energy-saving optimization system for the circulating pump of a heat exchange unit based on fuzzy PID control. Background Art

[0002] During the operation of the heat network system of a heat exchange unit, the limitations of traditional control strategies have become increasingly prominent. Most existing systems adopt fixed-parameter PID control or open-loop control modes with lagging response, making it difficult to match the dynamic change characteristics of the heat network flow in real time. When the heat network load changes due to factors such as fluctuations in user-side demand and changes in environmental temperature, the circulating pump cannot achieve rapid and accurate adjustment of the flow rate, resulting in the system being in an inefficient operation state of "large flow rate and small temperature difference" for a long time. Measured data shows that the energy consumption of the circulating pump under traditional control methods is 20% to 35% higher than the theoretical optimal value, which not only causes a large amount of electric energy waste, but also aggravates equipment wear and significantly shortens the service life of the system. This extensive operation mode is seriously out of line with the requirements of modern heating systems for energy conservation and consumption reduction, as well as intelligent control, and urgently needs to be optimized and upgraded through technological innovation. In view of this, we propose an energy-saving optimization system for the circulating pump of a heat exchange unit based on fuzzy PID control. Summary of the Invention

[0003] The purpose of the present invention is to provide an energy-saving optimization system for the circulating pump of a heat exchange unit based on fuzzy PID control, so as to solve the technical problems of high energy consumption, inaccurate regulation, and large equipment loss of traditional control strategies.

[0004] To solve the above technical problems, the present invention provides the following technical solutions: An energy-saving optimization system for the circulating pump of a heat exchange unit based on fuzzy PID control, comprising: A model identification module that identifies a simulation control object through on-site experiments, wherein the simulation control object includes a heat exchange unit and its unit heat network system; A simulation heat network model established with the simulation control object as the boundary, the simulation data input object of the simulation heat network model includes the unit heat network system, and the simulation data output of the simulation heat network model includes main steam pressure, unit load, flow rate, valve opening, pressure, and temperature; A simulation adjustment module running on a real-time simulation platform, taking the set value of the unit heat network system of the simulation data input object as the input of the simulation heat network model, comparing it with the actual value of the unit heat network system, generating a deviation through the difference between the set value and the actual value, and using the deviation for simulation data output control; A heat network coordination module that adjusts the flow rate of the unit heat network system in real time according to the simulation data output control; A heat network fuzzy PID module that performs real-time dynamic control on the heat exchange unit and its unit heat network system according to the simulation data output.

[0005] Preferably, the model identification module includes a model identification experiment module, a data entry module, and an identification module. The identification module performs identification of the unit heat network system, identification of the simulation data input object, identification of the simulation data output, and model verification. After the model verification is qualified, the identification module outputs a simulation identification model.

[0006] Preferably, the model identification module identifies the simulation control object through on-site experiments, including the following steps: A1: Collect the pressure and temperature parameters of the heat exchange unit and its heat supply system, the main steam temperature and temperature under the condition that the load of the heat exchange unit remains unchanged; A2: Preprocess the collected pressure and temperature parameters of the unit heat network system, the main steam temperature and temperature before modeling on the real-time simulation platform. Among them, the preprocessing includes normalizing all the collected parameters, and the processed parameters are used as the input data of the heat supply system identification model, and the load of the heat exchange unit is used as the output data of the identification model.

[0007] Preferably, the simulation adjustment module includes a first simulation experiment module, a second simulation experiment module, a comparison module, a simulation optimization module, and a first simulation model. The first simulation experiment module and the second simulation experiment module set the input values of the simulation data input object according to the simulation data input object. The first simulation experiment module and the second simulation experiment module input the input values into the simulation heat network model. The first simulation experiment module outputs the main steam flow rate, steam pressure, main steam temperature at the inlet of the economizer, temperature at the outlet of the high-pressure heater, temperature at the outlet of the No. 1 high-pressure heater, temperature at the outlet of the No. 2 high-pressure heater, unit load, and unit power. The second simulation experiment module outputs the inlet temperature of the No. 1 intermediate pressure cylinder, the saturated steam flow rate of the No. 1 high-pressure heater, the temperature at the outlet of the No. 2 high-pressure heater, and the drain temperature before the No. 2 high-pressure heater. The operating states of the first simulation experiment module and the second simulation experiment module are the same. The output parameters of the first simulation experiment module and the second simulation experiment module are input into the comparison module. The comparison module compares the simulation data output with the actual parameters of the unit heat network system. The output parameters of the comparison module are transmitted back to the simulation optimization module as the input parameters of the simulation optimization module. The simulation optimization module optimizes the simulation heat network model according to the feedback parameters.

[0008] Preferably, the optimization objective function for optimizing the simulation heat network model according to the feedback parameters can be expressed as: ; In the formula, is the output value of the simulation model at the moment, is the actual measured value of the heat network system at the moment, is the total number of sampling data points.

[0009] Preferably, the heat network coordination module includes: The heat network parameter acquisition module takes the flow rate, flow difference, temperature difference, main steam temperature, and heating flow rate of the unit's heat network system collected as the input of the heat network coordinated control module; The heat network coordinated control module calculates and outputs the valve opening according to the set heat network coordinated control law, and the valve opening is used as the input of the heat network coordinated logic module; The heat network coordinated logic module performs variable frequency speed regulation control on the circulating pump according to the valve opening.

[0010] Preferably, the valve opening is calculated and output according to the set heat network coordinated control law, and the valve opening calculation logic is: ; In the formula, 、 are the minimum and maximum values of the valve opening, 、 are the proportional and integral control parameters respectively, is the flow deviation of the unit's heat network system.

[0011] Preferably, the law of the variable frequency speed regulation control is specifically: If the flow rate of the unit's heat network system is lower than the heat network demand flow rate , or the flow deviation of the unit's heat network system , the flow difference and the temperature difference , then the output flow gradually increases according to the set value, that is .

[0012] Preferably, the heat network fuzzy PID module includes a first fuzzy controller, a second fuzzy controller, a third fuzzy controller, and a heat network parameter acquisition module; The heat network parameter acquisition module is used to collect the flow rate, flow difference, temperature difference, main steam temperature, and heating flow rate of the unit's heat network system. After the heat exchange unit adjusts the system flow rate in real time in the heat network coordination module, the heat network parameter acquisition module takes the collected flow rate, flow difference, temperature difference, main steam temperature, and heating flow rate of the unit's heat network system as the input of the first fuzzy controller, and the first fuzzy controller outputs the duty cycle of the frequency converter, and the duty cycle of the frequency converter is output according to the fuzzy logic rule; The output of the first fuzzy controller is used as the input of the second fuzzy controller, and the second fuzzy controller outputs the boiler feed water flow rate, and the boiler feed water flow rate is output according to the fuzzy logic rule; The output boiler feed water flow rate of the second fuzzy controller is used as the input of the third fuzzy controller, and the third fuzzy controller outputs the high-pressure feed water flow rate, and the high-pressure feed water flow rate is output according to the fuzzy logic rule.

[0013] Preferably, the real-time dynamic control logic of the heat network fuzzy PID module is as follows. First, the boiler feed water flow is adjusted by the second fuzzy controller, and then the high-pressure feed water flow is adjusted by the third fuzzy controller. The first fuzzy controller adjusts the duty cycle of the frequency converter and controls the set speed of the circulating pump through the valve opening. When the inlet flow of the unit's heat network system is less than the flow set value, the frequency of the circulating pump is increased to increase the flow of the unit's heat network system. After reaching the flow set value, the valve opening is adjusted to control the flow at the set value. During the flow adjustment process, when the fluctuation values of the heating flow and the outlet temperature are less than 0.6 - 0.8 tons per hour and the absolute value of the heat network inlet deviation is less than 1 - 3°, the first fuzzy controller is closed. Among them, the fuzzy control rule for the circulating pump frequency is based on the absolute value of the heat network inlet flow deviation being less than 0.6 - 0.8 tons per hour and the motor current of the circulating pump.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. Through the linkage of multi-stage fuzzy controllers of the heat network fuzzy PID module in the present invention, combined with the real-time calculation of the flow deviation by the simulation heat network model, the dynamic and precise adjustment of the circulating pump flow is realized. When the inlet flow of the unit's heat network system is lower than the set value, the flow is quickly replenished by increasing the frequency of the circulating pump, avoiding the problem of "continuous energy consumption with large flow difference" caused by the slow response of the traditional fixed-parameter PID, and directly reducing the basic operating energy consumption of the circulating pump.

[0015] 2. Also, in response to the pressure and temperature coupling problems accompanied by the heat network flow regulation, the present invention realizes the decoupling control of flow, pressure, and temperature through the "variable frequency speed regulation + valve opening linkage control" mechanism of the heat network coordination module, combined with the real-time comparison of multiple parameters such as the main steam flow and the unit load by the simulation adjustment module. This strategy solves the problem of adjustment oscillation caused by variable coupling in traditional single-loop control. During the flow adjustment process, when the fluctuation value of the heating flow is less than 0.6 - 0.8 tons per hour and the absolute value of the heat network inlet deviation is less than 1 - 3°, the first fuzzy controller is automatically closed to avoid over-adjustment, further improving the system stability and control accuracy.

[0016] 3. The present invention also collects on-site experimental data through the model identification module, combined with the iterative correction of the simulation optimization module, enabling the simulation heat network model to dynamically adapt to the system characteristics under different loads and temperatures. When the heat network load suddenly changes or parameters deviate due to external interference, the model can be quickly optimized based on real-time error feedback, providing more reliable parameter support for fuzzy PID control, solving the problem of adjustment lag of traditional fixed models under changing working conditions, enhancing the robustness of the system to complex working conditions, and reducing energy consumption anomalies and equipment losses caused by model mismatch. Description of the Drawings

[0017] Figure 1This is the system architecture diagram of the present invention. Detailed implementation manners

[0018] As Figure 1 shown, an energy-saving optimization system for the circulating pump of a heat exchange unit based on fuzzy PID control according to the present invention includes a model identification module, a simulation heat network model, a simulation adjustment module, a heat network coordination module or a heat network fuzzy PID module; The model identification module identifies the simulation control object through on-site experiments; In an embodiment of the present invention, the model identification module includes a model identification experiment module, a data entry module and an identification module; The identification module performs identification of the unit heat network system, identification of the simulation data input object, identification of the simulation data output, and model verification. After the model verification is qualified, the identification module outputs a simulation identification model; In an embodiment of the present invention, the model identification module identifies the simulation control object through on-site experiments, including the following steps: A1: Collect the pressure and temperature parameters of the heat exchange unit and its heating system, the main steam temperature and temperature under the condition that the load of the heat exchange unit remains unchanged; A2: Preprocess the collected pressure and temperature parameters of the unit heat network system, the main steam temperature and temperature before modeling on the real-time simulation platform; Among them, the preprocessing includes normalizing all the collected parameters, and the processed parameters are used as the input data of the heating system identification model, and the load of the heat exchange unit is used as the output data of the identification model; In an embodiment of the present invention, the simulation control object includes a heat exchange unit and its unit heat network system; The simulation heat network model is established with the simulation control object as the boundary. The simulation data input object of the simulation heat network model includes the unit heat network system, and the simulation data output of the simulation heat network model includes the main steam pressure, unit load, flow rate, valve opening, pressure and temperature; The simulation adjustment module runs on the real-time simulation platform. The simulation adjustment module uses the set value of the unit heat network system of the simulation data input object as the input of the simulation heat network model, and compares it with the actual value of the unit heat network system. The simulation adjustment module generates a deviation through the difference between the set value and the actual value, and the deviation is used for simulation data output control; In an embodiment of the present invention, the simulation adjustment module includes a first simulation experiment module, a second simulation experiment module, a comparison module, a simulation optimization module, and a first simulation model. The first simulation experiment module and the second simulation experiment module set input values of the simulation data input object according to the simulation data input object. The first simulation experiment module and the second simulation experiment module input the input values into the simulation heat network model. The first simulation experiment module outputs the main steam flow rate, steam pressure, main steam temperature at the inlet of the economizer, outlet temperature of the high-pressure heater, outlet temperature of the No. 1 high-pressure heater, outlet temperature of the No. 2 high-pressure heater, unit load, and unit power. The second simulation experiment module outputs the inlet temperature of the No. 1 intermediate-pressure cylinder, saturated steam flow rate of the No. 1 high-pressure heater, outlet temperature of the No. 2 high-pressure heater, and drain temperature before the No. 2 high-pressure heater. The operating states of the first simulation experiment module and the second simulation experiment module are the same. The output parameters of the first simulation experiment module and the second simulation experiment module are input into the comparison module. The comparison module compares the output with the actual parameters of the unit heat network system according to the simulation data. The output parameters of the comparison module are fed back to the simulation optimization module as input parameters of the simulation optimization module. The simulation optimization module optimizes the simulation heat network model according to the feedback parameters; Among them, the optimization objective function for optimizing the simulation heat network model according to the feedback parameters can be expressed as: ; In the formula, is the output value of the simulation model at the th moment, is the actual measured value of the heat network system at the th moment, is the total number of sampling data points. The model is optimized by minimizing the sum of squared errors. This formula adjusts the model parameters iteratively to make approach the minimum value, thereby improving the accuracy of the simulation model and providing a reliable virtual environment for subsequent control strategies.

[0019] The heat network coordination module adjusts the flow rate of the unit heat network system in real time according to the simulation data output; In an embodiment of the present invention, the heat network coordination module includes a heat network parameter acquisition module, a heat network coordination control module, and a heat network coordination logic module; The heat network parameter acquisition module inputs the flow rate, flow difference, temperature difference, main steam temperature, and heating flow rate of the unit heat network system collected as inputs to the heat network coordination control module; The heat network coordination control module calculates and outputs the valve opening according to the set heat network coordination control law. The valve opening is used as an input to the heat network coordination logic module; Among them, according to the set heat network coordination control law, the valve opening is calculated and output. The valve opening calculation logic is: ; In the formula, , 、 are the minimum and maximum values of the valve opening degree, 、 are the proportional and integral control parameters respectively, which are used to quickly respond to the deviation and eliminate the static error respectively, is the flow deviation of the unit's heat network system. The control objective of this formula is to dynamically adjust the valve opening degree according to the flow deviation to achieve stable control of the heat network system flow. Its significance is to combine the rapidity of PI control and the integral action to avoid the oscillation or static deviation that may be caused by pure proportional control, and it is applicable to the dynamic adjustment of the heat network flow; , The heat network coordination logic module performs variable frequency speed regulation control on the circulating pump according to the valve opening degree; Among them, the law of the variable frequency speed regulation control is specifically as follows: If the flow of the unit's heat network system is lower than the heat network demand flow , or the flow deviation of the unit's heat network system , the flow difference and the temperature difference , then the output flow gradually increases according to the set value, that is: ; Among them, the control logic is to preferentially increase the flow through variable frequency speed regulation (adjusting the speed of the circulating pump) to avoid mechanical wear caused by frequent valve adjustment, and combine the temperature difference parameter to avoid lag adjustment caused by solely relying on the flow deviation and improve the sensitivity of the system response; The heat network fuzzy PID module performs real-time dynamic control on the heat exchange unit and its unit heat network system according to the simulation data; In the embodiment of the present invention, the heat network fuzzy PID module includes a first fuzzy controller, a second fuzzy controller, a third fuzzy controller and a heat network parameter acquisition module; The heat network parameter acquisition module is used to collect the flow, flow difference, temperature difference, main steam temperature and heating flow of the unit's heat network system. After the heat exchange unit adjusts the system flow in real time by the heat network coordination module, the heat network parameter acquisition module takes the collected flow, flow difference, temperature difference, main steam temperature and heating flow of the unit's heat network system as the input of the first fuzzy controller, and the first fuzzy controller outputs the duty cycle of the frequency converter, and the duty cycle of the frequency converter is output according to the fuzzy logic rule; The output of the first fuzzy controller is used as the input of the second fuzzy controller, and the second fuzzy controller outputs the boiler feed water flow, and the boiler feed water flow is output according to the fuzzy logic rule; The output boiler feed water flow of the second fuzzy controller is used as the input of the third fuzzy controller, and the third fuzzy controller outputs the high-pressure feed water flow, and the high-pressure feed water flow is output according to the fuzzy logic rule; In an embodiment of the present invention, the real-time dynamic control logic of the heat network fuzzy PID module is as follows: First, the second fuzzy controller is used to adjust the boiler feed water flow rate, and then the third fuzzy controller is used to adjust the high-pressure feed water flow rate; The first fuzzy controller adjusts the duty cycle of the frequency converter and controls the set speed of the circulating pump through the valve opening. When the inlet flow rate of the unit's heat network system is less than the flow rate set value, the frequency of the circulating pump is increased to increase the flow rate of the unit's heat network system. After reaching the flow rate set value, the valve opening is adjusted to control the flow rate at the set value. During the flow rate adjustment process, when the fluctuation values of the heating flow rate and the outlet temperature are less than 0.6 - 0.8 tons per hour and the absolute value of the deviation at the heat network inlet is less than 1 - 3°, the first fuzzy controller is turned off; Among them, the fuzzy control rule for the circulating pump frequency is based on the absolute value of the deviation of the heat network inlet flow rate being less than 0.6 - 0.8 tons per hour and the current of the circulating pump motor; The deviation of the heat network inlet flow rate refers to the difference between the actual flow rate and the set flow rate at the heat network inlet. Its absolute value reflects the degree of deviation of the flow rate from the target value. When the absolute value of the flow rate deviation is within the range of 0.6 - 0.8 tons per hour, a specific fuzzy control rule is triggered. This range is the key threshold for the system to judge whether the flow rate is close to the stable state; The magnitude of the current of the circulating pump motor directly reflects the load condition of the circulating pump. As an auxiliary control parameter for the flow rate deviation, it makes up for the lag of single flow rate feedback and realizes the dual dynamic matching of "load - flow rate"; This fuzzy control rule constructs a control logic with both fast response and fine adjustment capabilities through a dual-parameter mechanism of "flow rate deviation threshold division + motor current auxiliary feedback". It not only solves the problem of adjustment lag of traditional PID in the small deviation interval but also avoids equipment overload through real-time monitoring of the motor current, realizing the multi-objective optimization of "energy saving - stability - protection" of the heat network system. The technical core lies in transforming the non-linear dynamic characteristics of the heat network flow rate into fuzzy logic rules and enhancing the system's adaptability to complex working conditions through multi-parameter coupling control.

[0020] The embodiments disclosed in the present invention are preferred embodiments, but are not limited thereto. Those of ordinary skill in the art can easily understand the spirit of the present invention based on the above embodiments and make different extensions and changes. However, as long as they do not depart from the spirit of the present invention, they are within the protection scope of the present invention.

Claims

1. A circulating pump energy-saving optimization system for a heat exchange unit based on fuzzy PID control, characterized in that, Including: A model identification module that identifies a simulation control object through on-site experiments. The simulation control object includes a heat exchange unit and its unit heat network system. A simulation heat network model established with the simulation control object as the boundary. The input object of the simulation data of the simulation heat network model includes the unit heat network system, and the output of the simulation data of the simulation heat network model includes main steam pressure, unit load, flow rate, valve opening, pressure, and temperature. A simulation adjustment module that runs on a real-time simulation platform. It takes the set value of the unit heat network system of the simulation data input object as the input of the simulation heat network model, compares it with the actual value of the unit heat network system, generates a deviation based on the difference between the set value and the actual value, and the deviation is used for controlling the output of the simulation data. A heat network coordination module that adjusts the flow rate of the unit heat network system in real time according to the output control of the simulation data. A heat network fuzzy PID module that performs real-time dynamic control on the heat exchange unit and its unit heat network system according to the output of the simulation data.

2. The energy-saving optimization system for the circulating pump of the heat exchange unit based on fuzzy PID control according to claim 1, characterized in that, The model identification module includes a model identification experiment module, a data entry module, and an identification module. The identification module conducts identification of the unit heat network system, identification of the input object of the simulation data, identification of the output of the simulation data, and model verification. After the model verification is qualified, the identification module outputs a simulation identification model.

3. The energy-saving optimization system for the circulating pump of the heat exchange unit based on fuzzy PID control according to claim 2, wherein The model identification module identifies the simulation control object through on-site experiments, including the following steps: A1: Collect the pressure and temperature parameters of the heat exchange unit and its heating system, main steam temperature and temperature under the condition that the load of the heat exchange unit remains unchanged. A2: Preprocess the collected pressure and temperature parameters of the unit heat network system, main steam temperature and temperature before modeling on the real-time simulation platform. Among them, the preprocessing includes normalizing all the collected parameters. The processed parameters are used as the input data of the heating system identification model, and the load of the heat exchange unit is used as the output data of the identification model.

4. An energy-saving optimization system for the circulating pump of a heat exchange unit based on fuzzy PID control according to claim 1, characterized in that The simulation adjustment module includes a first simulation experiment module, a second simulation experiment module, a comparison module, a simulation optimization module, and a first simulation model. The first simulation experiment module and the second simulation experiment module set the input values of the simulation data input object according to the simulation data input object. The first simulation experiment module and the second simulation experiment module input the input values into the simulation heat network model. The first simulation experiment module outputs the main steam flow rate, steam pressure, main steam temperature at the inlet of the economizer, temperature at the outlet of the high-pressure heater, temperature at the outlet of the No. 1 high-pressure heater, temperature at the outlet of the No. 2 high-pressure heater, unit load, and unit power. The second simulation experiment module outputs the inlet temperature of the No. 1 intermediate pressure cylinder, the saturated steam flow rate of the No. 1 high-pressure heater, the temperature at the outlet of the No. 2 high-pressure heater, and the drain temperature before the No. 2 high-pressure heater. The operating states of the first simulation experiment module and the second simulation experiment module are the same. The output parameters of the first simulation experiment module and the second simulation experiment module are input into the comparison module. The comparison module compares the simulation data output with the actual parameters of the unit heat network system. The output parameters of the comparison module are passed back to the simulation optimization module as the input parameters of the simulation optimization module. The simulation optimization module optimizes the simulation heat network model according to the feedback parameters.

5. The energy-saving optimization system for the circulating pump of the heat exchange unit based on fuzzy PID control according to claim 4, characterized in that, The optimization objective function for optimizing the simulation heat network model according to the feedback parameters can be expressed as: ； Wherein, is the output value of the simulation model at the th moment, is the actual measured value of the heat network system at the th moment, is the total number of sampling data points.

6. The energy-saving optimization system for the circulating pump of the heat exchange unit based on fuzzy PID control according to claim 1, characterized in that, The heat network coordination module includes: The heat network parameter acquisition module takes the flow rate, flow difference, temperature difference, main steam temperature, and heating flow rate of the unit's heat network system collected as the input of the heat network coordinated control module; The heat network coordinated control module calculates and outputs the valve opening according to the set heat network coordinated control law, and the valve opening is used as the input of the heat network coordinated logic module; The heat network coordinated logic module performs variable frequency speed regulation control on the circulating pump according to the valve opening.

7. The energy-saving optimization system for the circulating pump of a heat exchange unit based on fuzzy PID control according to claim 6, characterized in that, Calculate and output the valve opening according to the set heat network coordinated control law, and the valve opening calculation logic is: ； Wherein, and are the minimum and maximum values of the valve opening, and are the proportional and integral control parameters respectively, is the flow deviation of the unit's heat network system.

8. An energy-saving optimization system for the circulating pump of a heat exchange unit based on fuzzy PID control according to claim 7, characterized in that, The law of the variable frequency speed regulation control is specifically: If the flow rate of the unit's heat network system is lower than the heat network demand flow rate , or the flow rate deviation of the unit's heat network system , the flow rate difference and the temperature difference , then the output flow rate gradually increases according to the set value, that is .

9. The energy-saving optimization system for the circulating pump of the heat exchange unit based on fuzzy PID control according to claim 1, wherein, The heat network fuzzy PID module includes a first fuzzy controller, a second fuzzy controller, a third fuzzy controller, and a heat network parameter acquisition module; The heat network parameter acquisition module is used to collect the flow rate, flow difference, temperature difference, main steam temperature, and heating flow rate of the unit's heat network system. After the heat exchange unit adjusts the system flow rate in real time in the heat network coordination module, the heat network parameter acquisition module takes the collected flow rate, flow difference, temperature difference, main steam temperature, and heating flow rate of the unit's heat network system as the input of the first fuzzy controller, and the first fuzzy controller outputs the duty ratio of the frequency converter, and the duty ratio of the frequency converter is output according to the fuzzy logic rule; The output of the first fuzzy controller is used as the input of the second fuzzy controller, and the second fuzzy controller outputs the boiler feed water flow rate, and the boiler feed water flow rate is output according to the fuzzy logic rule; The output boiler feed water flow rate of the second fuzzy controller is used as the input of the third fuzzy controller, and the third fuzzy controller outputs the high-pressure feed water flow rate, and the high-pressure feed water flow rate is output according to the fuzzy logic rule.

10. The energy-saving optimization system for the circulating pump of the heat exchange unit based on fuzzy PID control according to claim 1, characterized in that, The real-time dynamic control logic of the heat network fuzzy PID module is as follows. First, the boiler feed water flow rate is adjusted by the second fuzzy controller, and then the high-pressure feed water flow rate is adjusted by the third fuzzy controller; The first fuzzy controller adjusts the duty ratio of the frequency converter and controls the set speed of the circulating pump through the valve opening. When the inlet flow rate of the unit's heat network system is less than the flow rate set value, the frequency of the circulating pump is increased to increase the flow rate of the unit's heat network system. After reaching the flow rate set value, the opening of the valve is adjusted to control the flow rate at the set value. During the flow rate adjustment process, when the fluctuation values of the heating flow rate and the outlet temperature are less than 0.6 - 0.8 tons / hour and the absolute value of the heat network inlet deviation is less than 1 - 3 °, the first fuzzy controller is closed; Among them, the frequency of the circulating pump takes the absolute value of the heat network inlet flow deviation less than 0.6 - 0.8 tons / hour and the motor current of the circulating pump as the fuzzy control rule.

Images