Energy-saving optimization system of heat exchanger unit circulating pump based on fuzzy PID control

Abstract

The present invention discloses an energy-saving optimization system for a heat exchanger unit circulating pump based on fuzzy PID control, which relates to the field of automatic control technology and aims to solve the technical problems of high energy consumption, inaccurate adjustment, and large equipment loss in traditional control strategies. The system comprises: a model identification module, which identifies a simulation control object through field experiments, wherein the simulation control object includes a heat exchanger unit and its unit heat network system; a simulation heat network model, which is established with the simulation control object as a 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, valve opening, pressure, and temperature. The present invention uses the multi-order fuzzy controller linkage of the heat network fuzzy PID module to avoid the "large flow difference and continuous energy consumption" problem caused by the slow response of traditional fixed parameter PID, and directly reduces the basic operating energy consumption of the circulating pump.

Description

Technical Field

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

[0002] During the operation of heat exchanger network systems, the limitations of traditional control strategies are becoming increasingly apparent. Existing systems often employ fixed-parameter PID control or open-loop control with a hysteresis response, making it difficult to adapt to the dynamic characteristics of heat network flow in real time. When the heat network load fluctuates due to factors such as user demand fluctuations and ambient temperature changes, the circulating pump is unable to quickly and accurately adjust the flow rate, resulting in the system operating in an inefficient state of "high flow, small temperature difference" for a long time. Field data shows that under traditional control methods, the energy consumption of the circulating pump is 20% to 35% higher than the theoretical optimal value, resulting in significant energy waste, increased equipment wear, and significantly shortened system life. This extensive operating mode is seriously out of step with the energy conservation, consumption reduction, and intelligent control requirements of modern heating systems, and urgently needs to be optimized and upgraded through technological innovation. In view of this, we propose an energy-saving optimization system for heat exchanger circulating pumps 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 circulation pump of a heat exchanger unit based on fuzzy PID control to solve the technical problems of high energy consumption, inaccurate adjustment and large equipment loss in traditional control strategies.

[0004] To solve the above technical problems, the present invention provides the following technical solutions: a heat exchange unit circulating pump energy-saving optimization system based on fuzzy PID control, comprising:

[0005] A model identification module identifies a simulation control object through field experiments, wherein the simulation control object includes a heat exchange unit and its heat network system;

[0006] 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 main steam pressure, unit load, flow, valve opening, pressure and temperature;

[0007] The simulation adjustment module runs on the real-time simulation platform, takes the set value of the unit heating network system of the simulation data input object as the input of the simulation heating network model, and compares it with the actual value of the unit heating network system. The deviation is generated by the difference between the set value and the actual value, and the deviation is used for simulation data output control;

[0008] The heat network coordination module adjusts the heat network system flow of the unit in real time according to the simulation data output control;

[0009] The heating network fuzzy PID module performs real-time dynamic control on the heat exchanger unit and its heating network system according to the simulation data output.

[0010] Preferably, the model identification module includes a model identification experiment module, a data entry module and an identification module. The identification module performs unit thermal network system identification, simulation data input object identification, simulation data output identification and model verification. After the model verification is qualified, the identification module outputs the simulation identification model.

[0011] Preferably, the model identification module identifies the simulation control object through field experiments, including the following steps:

[0012] A1: Under the condition that the load of the heat exchanger unit remains unchanged, the pressure and temperature parameters of the heat exchanger unit and its heating system, as well as the main steam temperature and temperature are collected;

[0013] A2: The collected unit heat network system pressure and temperature parameters, main steam temperature and temperature are pre-processed before modeling on the real-time simulation platform;

[0014] Among them, the preprocessing includes normalizing all collected parameters. The processed parameters serve as input data of the heating system identification model, and the heat exchanger unit load serves as output data of the identification model.

[0015] 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 value 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 value into the simulation heat network model. The first simulation experiment module outputs the main steam flow, steam pressure, main steam temperature of the economizer inlet, high-pressure heater outlet temperature, No. 1 high-pressure heater outlet temperature, No. 2 high-pressure heater outlet temperature, unit load and unit power. The second simulation experiment module outputs the inlet temperature of No. 1 intermediate pressure cylinder, the saturated steam flow of No. 1 high-pressure heater, No. 2 high-pressure heater outlet temperature and No. 2 high-pressure heater pre-drain temperature. The operating status 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 input parameters of the simulation optimization module. The simulation optimization module optimizes the simulation heat network model according to the feedback parameters.

[0016] Preferably, the optimization objective function of optimizing the simulated heating network model according to the feedback parameters can be expressed as: ;

[0017] Where, For the The output value of the simulation model at time For the The actual measured value of the heating network system at all times, is the total number of sampling data points.

[0018] Preferably, the heating network coordination module includes:

[0019] The heat network parameter acquisition module uses the collected heat network system flow, flow difference, temperature difference, main steam temperature and heating flow as input to the heat network coordination control module;

[0020] The heating network coordination control module calculates and outputs the valve opening according to the set heating network coordination control law. The valve opening serves as the input of the heating network coordination logic module;

[0021] The heat network coordination logic module performs variable frequency speed control on the circulation pump according to the valve opening.

[0022] Preferably, the valve opening is calculated and output according to the set heat network coordinated control law, and the valve opening calculation logic is:

[0023] ;

[0024] Where, 、 is the minimum and maximum value of valve opening, 、 are proportional and integral control parameters respectively, It is the flow deviation of the unit's heating network system.

[0025] Preferably, the variable frequency speed control rule is specifically:

[0026] If the unit's heat network system flow Lower than the required flow of the heating network , or the unit heat network system flow deviation , flow rate difference And the temperature difference , then the output flow Gradually increase the set value, i.e. .

[0027] Preferably, the heating network fuzzy PID module includes a first fuzzy controller, a second fuzzy controller, a third fuzzy controller and a heating network parameter acquisition module;

[0028] The heating network parameter acquisition module is used to collect the unit's heating network system flow, flow difference, temperature difference, main steam temperature and heating flow. After the heat exchange unit adjusts the system flow in real time by the heating network coordination module, the heating network parameter acquisition module uses the collected unit's heating network system flow, flow difference, temperature difference, main steam temperature and heating flow as inputs to the first fuzzy controller. The first fuzzy controller outputs the inverter duty cycle, and the inverter duty cycle is output according to fuzzy logic rules.

[0029] 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, which is output according to fuzzy logic rules;

[0030] 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, which is output according to fuzzy logic rules.

[0031] 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;

[0032] The first fuzzy controller adjusts the duty cycle of the frequency converter and controls the set speed of the circulation pump through the valve opening. When the flow rate at the inlet of the unit's heating network system is less than the flow rate setting value, the circulation pump frequency is increased to increase the flow rate of the unit's heating network system. After the flow rate setting value is reached, the valve opening is adjusted to control the flow rate at the set value. During the flow regulation process, if the fluctuation value of the heating flow rate and the outlet temperature is less than 0.6-0.8 tons / hour and the absolute value of the deviation at the heating network inlet is less than 1-3 degrees, the first fuzzy controller is turned off.

[0033] Among them, the circulation pump frequency takes the absolute value of the heat network inlet flow deviation less than 0.6-0.8 tons / hour and the circulation pump motor current as the fuzzy control rule.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] 1. This invention achieves dynamic and precise regulation of the circulating pump flow rate by linking the multi-order fuzzy controller of the heating network fuzzy PID module and combining it with the real-time calculation of flow deviation by the simulated heating network model. When the inlet flow rate of the unit's heating network system falls below the set value, the circulating pump frequency is increased to quickly replenish the flow rate, avoiding the "large flow difference and continuous energy consumption" problem caused by the slow response of traditional fixed-parameter PID, and directly reducing the basic operating energy consumption of the circulating pump.

[0036] 2. This invention also addresses the pressure and temperature coupling associated with heat network flow regulation. By leveraging the "variable frequency speed regulation + valve opening linkage control" mechanism of the heat network coordination module, combined with real-time comparison of multiple parameters such as main steam flow and unit load in the simulation adjustment module, this method achieves decoupled control of flow, pressure, and temperature. This strategy addresses the regulation oscillation problem caused by the coupling of dependent variables in traditional single-loop control. During the flow regulation process, when the heating flow fluctuation value is less than 0.6-0.8 tons / hour and the absolute value of the heat network inlet deviation is less than 1-3 degrees, the first fuzzy controller is automatically disabled to avoid overregulation, further improving system stability and control accuracy.

[0037] 3. This invention also dynamically adapts the simulated heating network model to system characteristics at varying loads and temperatures through field experimental data collection in the model identification module, combined with iterative corrections in the simulation optimization module. When sudden load changes or external disturbances cause parameter deviations in the heating network, the model can be rapidly optimized based on real-time error feedback, providing more reliable parameter support for fuzzy PID control. This addresses the adjustment lag of traditional fixed models when operating conditions change, enhances the system's robustness to complex operating conditions, and reduces energy consumption anomalies and equipment losses caused by model mismatch. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a system architecture diagram of the present invention. DETAILED DESCRIPTION

[0039] like Figure 1 As shown, the present invention relates to a heat exchange unit circulating pump energy-saving optimization system based on fuzzy PID control, including 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;

[0040] The model identification module identifies the simulation control object through field experiments;

[0041] 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;

[0042] The identification module performs unit heat network system identification, simulation data input object identification, simulation data output identification and model verification. After the model verification is qualified, the identification module outputs the simulation identification model;

[0043] In an embodiment of the present invention, the model identification module identifies the simulation control object through field experiments, including the following steps:

[0044] A1: Under the condition that the load of the heat exchanger unit remains unchanged, the pressure and temperature parameters of the heat exchanger unit and its heating system, as well as the main steam temperature and temperature are collected;

[0045] A2: The collected unit heat network system pressure and temperature parameters, main steam temperature and temperature are pre-processed before modeling on the real-time simulation platform;

[0046] Among them, preprocessing includes normalizing all collected parameters. The processed parameters serve as input data for the heating system identification model, and the heat exchanger unit load serves as the output data of the identification model.

[0047] In an embodiment of the present invention, the simulation control object includes a heat exchange unit and its heat network system;

[0048] 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. The simulation data output of the simulation heat network model includes main steam pressure, unit load, flow, valve opening, pressure and temperature.

[0049] The simulation adjustment module runs on a real-time simulation platform. The simulation adjustment module uses the set value of the unit heating network system of the simulation data input object as the simulation heating network model input, and compares it with the actual value of the unit heating network system. The simulation adjustment module generates a deviation based on the difference between the set value and the actual value, and the deviation is used for simulation data output control;

[0050] 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 the input value 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 value into the simulation heating network model. The first simulation experiment module outputs the main steam flow, steam pressure, main steam temperature of the economizer inlet, high-pressure heater outlet temperature, No. 1 high-pressure heater outlet temperature, No. 2 high-pressure heater outlet temperature, unit load and unit power. The second simulation experiment module outputs the inlet temperature of No. 1 intermediate pressure cylinder, the saturated steam flow of No. 1 high-pressure heater, No. 2 high-pressure heater outlet temperature and No. 2 high-pressure heater pre-drain temperature. 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 heating network system. The output parameters of the comparison module are transmitted back to the simulation optimization module as input parameters of the simulation optimization module. The simulation optimization module optimizes the simulation heating network model according to the feedback parameters.

[0051] Among them, the optimization objective function of the simulation heating network model based on the feedback parameters can be expressed as:

[0052] ;

[0053] Where, For the The output value of the simulation model at time For the The actual measured value of the heating network system at all times, is the total number of sampling data points, and the model is optimized by minimizing the sum of squared errors. This formula adjusts the model parameters iteratively so that It approaches the minimum value, thereby improving the accuracy of the simulation model and providing a reliable virtual environment for subsequent control strategies.

[0054] The heat network coordination module adjusts the heat network system flow of the unit in real time according to the simulation data output control;

[0055] In an embodiment of the present invention, the heating network coordination module includes a heating network parameter acquisition module, a heating network coordination control module and a heating network coordination logic module;

[0056] The heat network parameter acquisition module uses the collected heat network system flow, flow difference, temperature difference, main steam temperature and heating flow as inputs to the heat network coordination control module;

[0057] The heat network coordination control module calculates and outputs the valve opening according to the set heat network coordination control law, and the valve opening serves as the input of the heat network coordination logic module;

[0058] Among them, the valve opening is calculated and output according to the set heat network coordinated control law. The valve opening calculation logic is:

[0059] ;

[0060] Where, , 、 is the minimum and maximum value of valve opening, 、 are proportional and integral control parameters, respectively, used for rapid response to deviations and elimination of static errors. is the flow deviation of the unit heat network system. The control target of this formula is based on the flow deviation Dynamic adjustment of valve opening , to achieve stable control of the flow rate of the heating network system. Its significance is to combine the rapidity and integral effect of PI control to avoid oscillation or static deviation that may be caused by simple proportional control, and is suitable for dynamic regulation of the flow rate of the heating network;

[0061] The heat network coordination logic module performs variable frequency speed control on the circulation pump according to the valve opening;

[0062] The specific rule of the variable frequency speed regulation control is: if the flow rate of the unit heating network system is Lower than the required flow of the heating network , or the unit heat network system flow deviation , flow rate difference And the temperature difference , then the output flow Gradually increase according to the set value, that is: ;

[0063] The control logic prioritizes increasing flow through variable frequency speed regulation (adjusting the circulation pump speed) to avoid mechanical wear caused by frequent valve adjustments. It also incorporates temperature difference parameters to avoid hysteresis caused by relying solely on flow deviation, thereby improving system response sensitivity.

[0064] The heat network fuzzy PID module performs real-time dynamic control on the heat exchange unit and its heat network system according to the simulation data output;

[0065] In an embodiment of the present invention, the heating network fuzzy PID module includes a first fuzzy controller, a second fuzzy controller, a third fuzzy controller and a heating network parameter acquisition module;

[0066] The heating network parameter acquisition module is used to collect the unit's heating network system flow, flow difference, temperature difference, main steam temperature and heating flow. After the heat exchange unit adjusts the system flow in real time by the heating network coordination module, the heating network parameter acquisition module uses the collected unit's heating network system flow, flow difference, temperature difference, main steam temperature and heating flow as inputs to the first fuzzy controller. The first fuzzy controller outputs the inverter duty cycle, and the inverter duty cycle is output according to fuzzy logic rules.

[0067] 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, which is output according to fuzzy logic rules;

[0068] 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, which is output according to fuzzy logic rules;

[0069] In an embodiment of the present invention, the real-time dynamic control logic of the thermal network fuzzy PID module is as follows:

[0070] 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;

[0071] The first fuzzy controller adjusts the duty cycle of the frequency converter and controls the set speed of the circulation pump through the valve opening. When the flow rate at the inlet of the unit's heating network system is less than the flow rate setting value, the circulation pump frequency is increased to increase the flow rate of the unit's heating network system. After the flow rate setting value is reached, the valve opening is adjusted to control the flow rate at the set value. During the flow regulation process, if the fluctuation value of the heating flow rate and the outlet temperature is less than 0.6-0.8 tons / hour and the absolute value of the deviation at the heating network inlet is less than 1-3 degrees, the first fuzzy controller is turned off.

[0072] Among them, the circulation pump frequency is controlled by the absolute value of the heat network inlet flow deviation less than 0.6 to 0.8 tons / hour and the circulation pump motor current as the fuzzy control rule;

[0073] The heat network inlet flow deviation refers to the difference between the actual flow at the heat network inlet and the set flow. Its absolute value reflects the degree to which the flow deviates from the target value. When the absolute value of the flow deviation is between 0.6 and 0.8 tons / hour, a specific fuzzy control rule is triggered. This range is the key threshold for the system to determine whether the flow is close to a stable state.

[0074] The magnitude of the circulating pump motor current directly reflects the load condition of the circulating pump. As an auxiliary control parameter of flow deviation, it compensates for the hysteresis of single flow feedback and realizes the dual dynamic matching of "load-flow";

[0075] This fuzzy control rule utilizes a dual-parameter mechanism of "flow deviation threshold division + motor current auxiliary feedback" to create a control logic that combines rapid response with fine-tuning capabilities. This not only addresses the hysteresis of traditional PID control in small deviation ranges, but also prevents equipment overload through real-time motor current monitoring, achieving multi-objective optimization of the heating network system's "energy conservation, stability, and protection" objectives. The core technology lies in transforming the nonlinear dynamic characteristics of the heating network flow into fuzzy logic rules, enhancing the system's adaptability to complex operating conditions through multi-parameter coupled control.

[0076] The embodiments disclosed in the present invention are preferred embodiments, but are not limited to them. Ordinary technicians in this field can easily understand the spirit of the present invention based on the above embodiments and make different extensions and changes. As long as they do not deviate from the spirit of the present invention, they are all within the scope of protection of the present invention.

Claims

1. A heat exchange unit circulating pump energy-saving optimization system based on fuzzy PID control, characterized in that: include: A model identification module identifies a simulation control object through field experiments, wherein the simulation control object includes a heat exchange unit and its 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 main steam pressure, unit load, flow, valve opening, pressure and temperature; The simulation adjustment module runs on the real-time simulation platform, takes the set value of the unit heating network system of the simulation data input object as the input of the simulation heating network model, and compares it with the actual value of the unit heating network system. The deviation is generated by the difference between the set value and the actual value, and the deviation is used for simulation data output control; The heat network coordination module adjusts the heat network system flow of the unit in real time according to the simulation data output control; The heat network fuzzy PID module performs real-time dynamic control of the heat exchange unit and its heat network system according to the simulation data output; The heating network coordination module includes: The heat network parameter acquisition module uses the collected heat network system flow, flow difference, temperature difference, main steam temperature and heating flow as input to the heat network coordination control module; The heating network coordination control module calculates and outputs the valve opening according to the set heating network coordination control law. The valve opening serves as the input of the heating network coordination logic module; The heat network coordination logic module performs variable frequency speed control on the circulation pump according to the valve opening; The valve opening is calculated and output according to the set heat network coordinated control law. The valve opening calculation logic is: ； Where, 、 is the minimum and maximum value of valve opening, 、 are proportional and integral control parameters respectively, is the flow deviation of the unit's heat network system; The specific rules of the variable frequency speed control are: If the unit's heat network system flow Lower than the required flow of the heating network , or the unit heat network system flow deviation , flow rate difference And the temperature difference , then the output flow Gradually increase the set value, i.e. .

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

3. The energy-saving optimization system for heat exchanger unit circulating pump based on fuzzy PID control according to claim 2 is characterized in that: The model identification module identifies the simulation control object through field experiments, including the following steps: A1: Under the condition that the load of the heat exchanger unit remains unchanged, the pressure and temperature parameters of the heat exchanger unit and its heating system, as well as the main steam temperature and temperature are collected; A2: The collected pressure and temperature parameters of the unit's heat network system, main steam temperature and temperature are pre-processed before modeling on the real-time simulation platform; Among them, the preprocessing includes normalizing all collected parameters. The processed parameters serve as input data of the heating system identification model, and the heat exchanger unit load serves as output data of the identification model.

4. The energy-saving optimization system for heat exchanger unit circulating pump based on fuzzy PID control according to claim 1 is 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 value 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 value into the simulation heating network model. The first simulation experiment module outputs the main steam flow, steam pressure, main steam temperature of the economizer inlet, high-pressure heater outlet temperature, No. 1 high-pressure heater outlet temperature, No. 2 high-pressure heater outlet temperature, unit load and unit power. The second simulation experiment module outputs the inlet temperature of No. 1 intermediate pressure cylinder, the saturated steam flow of No. 1 high-pressure heater, No. 2 high-pressure heater outlet temperature and No. 2 high-pressure heater pre-drain temperature. The operating status of the first simulation experiment module and the second simulation experiment module is the same. The output parameters of the first simulation experiment module and the second simulation module are input into the comparison module. The comparison module compares the simulation data output with the actual parameters of the unit heating network system. The output parameters of the comparison module are transmitted back to the simulation optimization module as input parameters of the simulation optimization module. The simulation optimization module optimizes the simulation heating network model according to the feedback parameters.

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

6. The energy-saving optimization system for heat exchange unit circulating pump based on fuzzy PID control according to claim 1 is characterized in that: The heating network fuzzy PID module includes a first fuzzy controller, a second fuzzy controller, a third fuzzy controller and a heating network parameter acquisition module; The heating network parameter acquisition module is used to collect the unit's heating network system flow, flow difference, temperature difference, main steam temperature and heating flow. After the heat exchange unit adjusts the system flow in real time by the heating network coordination module, the heating network parameter acquisition module uses the collected unit's heating network system flow, flow difference, temperature difference, main steam temperature and heating flow as inputs to the first fuzzy controller. The first fuzzy controller outputs the inverter duty cycle, and the inverter duty cycle is output according to fuzzy logic rules. 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, which is output according to fuzzy logic rules; 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, which is output according to fuzzy logic rules.

7. The energy-saving optimization system for heat exchange unit circulating pump based on fuzzy PID control according to claim 1 is characterized in that: The real-time dynamic control logic of the heating 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 circulation pump through the valve opening. When the flow rate at the inlet of the unit's heating network system is less than the flow rate setting value, the circulation pump frequency is increased to increase the flow rate of the unit's heating network system. After the flow rate setting value is reached, the valve opening is adjusted to control the flow rate at the set value. During the flow regulation process, if the fluctuation value of the heating flow rate and the outlet temperature is less than 0.6-0.8 tons / hour and the absolute value of the deviation at the heating network inlet is less than 1-3 degrees, the first fuzzy controller is turned off. Among them, the circulation pump frequency takes the absolute value of the heat network inlet flow deviation less than 0.6-0.8 tons / hour and the circulation pump motor current as the fuzzy control rule.

Images