Sewage waste heat recovery heating control method and system based on digital twin heat pump

Abstract

The invention discloses a sewage waste heat recovery heating control method and system based on a digital twinning heat pump. The method comprises the steps that a digital twinning platform of a sewage waste heat recovery heating system is constructed; based on the operation parameters of the entity equipment of the sewage waste heat recovery heating system, establishing a digital twinborn model of the sewage waste heat recovery heating system; deploying the established digital twinborn model of the sewage waste heat recovery heating system in the established digital twinborn platform of the sewage waste heat recovery heating system; based on the physical equipment operation parameters of the sewage waste heat recovery heating system and the virtual data of the digital twinborn model, an optimization target model of the sewage waste heat recovery heating system is constructed, and an optimal control strategy is obtained; dynamic optimization control is carried out on the heating system entity equipment according to the optimal control strategy; the prediction precision is improved through real-time data calibration, model prediction control is fused, second-level response and multivariable cooperative regulation and control are achieved, and the problems that a traditional sewage waste heat recovery heating system is low in energy efficiency, slow in response and high in maintenance cost are effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of heating control systems, and in particular to a sewage waste heat recovery heating control method and system for a heat pump based on digital twin. Background Art

[0002] With the increasingly severe global energy crisis and environmental pollution problems, sewage waste heat, as a low-grade renewable energy source, has attracted much attention for its efficient recovery and utilization.

[0003] Existing sewage waste heat recovery heating systems mainly absorb sewage waste heat through a heat pump evaporator, and after compression and temperature rise, it is transported to the heating pipe network. The sewage waste heat recovery heating system is limited by the drastic fluctuations of sewage parameters (flow rate, temperature, suspended solid concentration), which easily leads to unstable coefficient of performance (COP) of the heat pump; at the same time, existing sewage waste heat recovery heating systems lack real-time monitoring and predictive maintenance of equipment status (such as heat exchanger fouling), resulting in high operation and maintenance costs and lagging fault response; in addition, most sewage waste heat recovery heating systems adopt preset fixed operating parameters (such as compressor speed, valve opening), which cannot respond to the dynamic changes of the sewage heat source in real time, easily causing energy waste and equipment loss, and restricting the large-scale application of sewage waste heat recovery. Summary of the Invention

[0004] In order to overcome the above-mentioned disadvantages of the prior art, the present invention provides a sewage waste heat recovery heating control method and system for a heat pump based on digital twin.

[0005] The technical solution adopted by the present invention to solve its technical problems is: A sewage waste heat recovery heating control method for a heat pump based on digital twin, comprising:

[0006] Constructing a digital twin platform for the sewage waste heat recovery heating system, the digital twin platform being used for two-way data interaction between the digital twin model of the sewage waste heat recovery heating system and the physical equipment of the sewage waste heat recovery heating system;

[0007] Based on the operating parameters of the physical equipment of the sewage waste heat recovery heating system, establishing a digital twin model of the sewage waste heat recovery heating system;

[0008] Deploying the established digital twin model of the sewage waste heat recovery heating system into the constructed digital twin platform of the sewage waste heat recovery heating system;

[0009] Based on the operating parameters of the physical equipment of the sewage waste heat recovery heating system and the virtual data of the digital twin model, constructing an optimization target model for the sewage waste heat recovery heating system to obtain an optimal control strategy;

[0010] Implementing dynamic optimization control on the physical equipment of the heating system according to the optimal control strategy.

[0011] As a further improvement of the present invention: based on the operating parameters of the physical equipment of the sewage waste heat recovery heating system and the virtual data of the digital twin model, an optimization target model of the sewage waste heat recovery heating system is constructed to obtain an optimal control strategy, including: taking the maximization of the system comprehensive energy efficiency ratio of the sewage waste heat recovery heating system as the core optimization target, combining sewage physical property parameters, environmental parameters and heating load prediction data, and performing optimization calculations using the digital twin model of the sewage waste heat recovery heating system under the condition of ensuring that the heating demand of users is met.

[0012] As a further improvement of the present invention: the digital twin platform includes a physical equipment layer, a data capture layer, an intelligent computing layer, a communication transmission layer, and a decision-making and control layer;

[0013] The physical equipment layer includes a sewage tank, a magnetic levitation heat pump unit, a heat exchange station, an optical fiber temperature sensor, a water pump group, a flow meter, a turbidity meter and corresponding control equipment; the sewage tank is connected to the magnetic levitation heat pump unit, the magnetic levitation heat pump unit is connected to the heat exchange station, a water pump group, a flow meter, a turbidity meter and an optical fiber temperature sensor are installed on the connecting pipeline between the sewage tank and the magnetic levitation heat pump unit, and a water pump group is installed between the magnetic levitation heat pump unit and the heat exchange station;

[0014] The data capture layer is used to monitor the operating parameters and working status of the physical equipment layer in real time and provide data sources for the digital twin model;

[0015] The intelligent computing layer is used to implement heterogeneous data integration, feature extraction and intelligent analysis and provide data streams for the digital twin model;

[0016] The communication transmission layer adopts a hybrid networking technology of wired network and wireless sensors to realize low-latency information interaction between the physical equipment layer, the data capture layer, the intelligent computing layer and the decision-making and control layer, and provides signal streams for the digital twin model;

[0017] The decision-making and control layer relies on the digital twin model of the sewage waste heat recovery heating system, compares the operating parameters and working status of the physical equipment layer with the simulation deduction results, continuously calibrates the parameter accuracy of the digital twin model of the sewage waste heat recovery heating system, and obtains the optimal control strategy that meets the maximization of the system comprehensive energy efficiency ratio (COP) according to the simulation deduction results of the digital twin model of the sewage waste heat recovery heating system, and provides instruction streams for the digital twin model.

[0018] As a further improvement of the present invention: establishing a digital twin model of the sewage waste heat recovery heating system, specifically including:

[0019] After mapping and reconstructing the physical equipment in the virtual space, a digital twin model of the sewage waste heat recovery heating system is established. Real-time data synchronization between the physical equipment and the virtual model is achieved through the OPC UA protocol to ensure that the model state is consistent with the actual system. The sewage temperature is collected in real time through fiber optic temperature sensors.

[0020] Establish an energy efficiency model for the magnetic levitation heat pump unit of the sewage waste heat recovery heating system:

[0021]

[0022] Among them, COP is the system comprehensive energy efficiency ratio, N is the rotational speed of the magnetic levitation heat pump compressor established, η comp is the efficiency coefficient of the magnetic levitation heat pump compressor, N max is the maximum rotational speed, T cond is the condensation temperature, T evap is the evaporation temperature.

[0023] As a further improvement of the present invention: Establishing the digital twin model of the sewage waste heat recovery heating system further includes:

[0024] Collect the sewage suspended solid concentration in real time through a turbidimeter, classify the suspended solid types (grease, fiber, sediment) in real time through the YOLOv5 algorithm, and construct a fouling rate prediction model:

[0025]

[0026] Among them, R fouling is the fouling rate, C ss is the suspended solid concentration, v is the flow velocity, E a is the activation energy, T is the absolute temperature; k is an empirical coefficient, which is fitted through experimental data;

[0027] Construct a magnetic levitation heat pump efficiency decay model:

[0028]

[0029] Among them, U0 is the heat transfer coefficient in the clean state, t is the operation duration; combined with the backwashing frequency of the online cleaning system, the maintenance period is dynamically optimized.

[0030] As a further improvement of the present invention: Establishing the digital twin model of the sewage waste heat recovery heating system further includes: Accessing the API of the meteorological bureau to obtain the predicted temperature data for the next 24 hours, combining with the building thermal inertia model, predicting the heating load demand curve, and establishing a non-linear compensation function for the temperature-heat pump outlet water temperature, and the expression is:

[0031] T supply = T base +α·(T out -Tdesign )

[0032] Among them, T supply is the dynamically adjusted water supply temperature, T base is the designed water supply temperature, a is the compensation coefficient, T out is the real-time ambient temperature, T design is the designed reference temperature.

[0033] As a further improvement of the present invention: The optimization objective model of the constructed sewage waste heat recovery heating system is obtained to obtain the optimal control strategy, specifically including:

[0034] Taking the maximization of the system comprehensive energy efficiency ratio (COP) of the sewage waste heat recovery heating system as the core optimization objective, taking into account the minimization of pipeline network heat loss and the equalization of equipment life, a target function is constructed for the dynamic optimization control of the sewage waste heat recovery heating system. The target function is:

[0035] max(w1·COP - w2·Q loss - w3·∑ΔL device )

[0036] Among them, the weight coefficients are w1 = 0.6, w2 = 0.3, w3 = 0.1, Q loss is the pipeline network heat loss, ΔL device is the equipment life attenuation index;

[0037] Based on the model predictive control algorithm, the real-time operation results of the digital twin model are obtained, the target function is solved, and the optimal control strategy for maximizing the system comprehensive energy efficiency ratio of the sewage waste heat recovery heating system is determined according to the solution results.

[0038] As a further improvement of the present invention: The dynamic optimization control of the heating system physical equipment according to the optimal control strategy includes: Implementing dynamic optimization control of the heating system physical equipment according to the optimal control strategy. When the ambient temperature suddenly changes by ΔT > 5°C / 10 min or the suspended solid concentration exceeds the standard C ss > 2000 NTU, the adaptive adjustment mode is triggered, and the standby magnetic levitation heat pump is automatically switched to and the backwashing program is started.

[0039] The present invention also provides a sewage waste heat recovery heating control system based on a digital twin heat pump, including:

[0040] A digital twin platform construction module for constructing a digital twin platform for the sewage waste heat recovery heating system;

[0041] A digital twin model establishment module for establishing a digital twin model of the sewage waste heat recovery heating system;

[0042] Deployment module, which deploys the established digital twin model of the sewage waste heat recovery heating system to the digital twin platform of the constructed sewage waste heat recovery heating system;

[0043] Optimal control strategy construction module, which constructs an optimization objective model of the sewage waste heat recovery heating system based on the operating parameters of the physical equipment of the sewage waste heat recovery heating system and the virtual data of the digital twin model to obtain the optimal control strategy;

[0044] Dynamic optimization control module, which implements dynamic optimization control of the physical equipment of the heating system according to the optimal control strategy.

[0045] The present invention also provides a sewage waste heat recovery heating control system for a heat pump based on digital twins, including a digital twin platform, and the digital twin platform includes a physical equipment layer, a data capture layer, an intelligent computing layer, a communication transmission layer, and a decision-making control layer;

[0046] The physical equipment layer includes a sewage tank, a magnetic levitation heat pump unit, a heat exchange station, an optical fiber temperature sensor, a water pump group, a flow meter, a turbidity meter, and corresponding control equipment; the sewage tank is connected to the magnetic levitation heat pump unit, the magnetic levitation heat pump unit is connected to the heat exchange station, a water pump group, a flow meter, a turbidity meter, and an optical fiber temperature sensor are installed on the connecting pipeline between the sewage tank and the magnetic levitation heat pump unit, and a water pump group is installed between the magnetic levitation heat pump unit and the heat exchange station;

[0047] The data capture layer is used to monitor the operating parameters and working status of the physical equipment layer in real time and provide a data source for the digital twin model;

[0048] The intelligent computing layer is used to implement heterogeneous data integration, feature extraction, and intelligent analysis and provide a data flow for the digital twin model;

[0049] The communication transmission layer adopts a hybrid networking technology of wired networks and wireless sensors to achieve low-latency information interaction between the physical equipment layer, the data capture layer, the intelligent computing layer, and the decision-making control layer and provide a signal flow for the digital twin model;

[0050] The decision-making control layer relies on the digital twin model of the sewage waste heat recovery heating system, compares the operating parameters and working status of the physical equipment layer with the simulation deduction results, continuously calibrates the parameter accuracy of the digital twin model of the sewage waste heat recovery heating system, and obtains the optimal control strategy that satisfies the maximization of the system comprehensive energy efficiency ratio (COP) according to the simulation deduction results of the digital twin model of the sewage waste heat recovery heating system, and provides an instruction flow for the digital twin model.

[0051] Compared with the prior art, the beneficial effects of the present invention are:

[0052] 1. A heat pump sewage waste heat recovery heating control method and system based on digital twin proposed by the present invention constructs a digital twin platform and a digital twin model, combines the operating parameters of the physical equipment of the sewage waste heat recovery heating system and the virtual data of the digital twin model, constructs an optimization target model for the sewage waste heat recovery heating system to obtain an optimal control strategy, and implements dynamic optimization control on the physical equipment of the heating system according to the optimal control strategy, dynamically adjusting the rotational speed of the heat pump compressor, the flow rate of the circulating pump, and the valve opening, improving the system's comprehensive energy efficiency ratio; improving the prediction accuracy through real-time data calibration, integrating model predictive control, achieving second-level response and multi-variable coordinated control, and effectively solving the problems of low energy efficiency, slow response, and high maintenance cost of traditional sewage waste heat recovery heating systems.

[0053] 2. The present invention analyzes the suspended solid concentration in real time through a turbidimeter, establishes a fouling rate prediction model to predict the fouling rate of the magnetic levitation heat pump, combines the backwashing frequency of the on-line cleaning system to optimize the cleaning cycle; the magnetic levitation heat pump compressor adopts IGBT DC frequency modulation technology and combines the PID algorithm to achieve precise rotational speed control; by accessing the API of the meteorological bureau to obtain the predicted temperature data for the next 24 hours, the heating outlet water temperature can be dynamically adjusted; the present invention can be widely applied to urban sewage treatment plants, industrial parks, and regional central heating projects, providing a standardized solution for the efficient utilization of low-grade energy and contributing to the realization of the "dual carbon" goal.

[0054] 2. The present invention establishes a non-linear compensation function between the air temperature and the heat pump outlet water temperature, enabling the sewage waste heat recovery heating system to achieve the dual goals of on-demand heating and energy-saving operation under complex climate conditions. By introducing a fouling rate prediction model, the fouling rate of the magnetic levitation heat pump is dynamically predicted based on the sewage composition, temperature, and flow rate, optimizing the cleaning cycle, and reducing the equipment maintenance cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 is a flowchart of the heat pump sewage waste heat recovery heating control method based on digital twin of the present invention.

[0056] Figure 2 is a schematic block diagram of the heat pump sewage waste heat recovery heating control system based on digital twin of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present invention and the corresponding drawings.

[0058] Please refer to Figure 1 , the heat pump sewage waste heat recovery heating control method based on digital twin includes:

[0059] Build a digital twin platform for the sewage waste heat recovery heating system, which is used for two-way data interaction between the digital twin model of the sewage waste heat recovery heating system and the physical equipment of the sewage waste heat recovery heating system;

[0060] Based on the operating parameters of the physical equipment of the sewage waste heat recovery heating system, establish a digital twin model of the sewage waste heat recovery heating system;

[0061] Deploy the established digital twin model of the sewage waste heat recovery heating system into the built digital twin platform of the sewage waste heat recovery heating system;

[0062] Based on the operating parameters of the physical equipment of the sewage waste heat recovery heating system and the virtual data of the digital twin model, construct an optimization target model for the sewage waste heat recovery heating system to obtain the optimal control strategy;

[0063] Implement dynamic optimization control on the physical equipment of the heating system according to the optimal control strategy.

[0064] As an embodiment of the present invention, the constructing an optimization target model for the sewage waste heat recovery heating system to obtain the optimal control strategy based on the operating parameters of the physical equipment of the sewage waste heat recovery heating system and the virtual data of the digital twin model includes: taking the maximization of the system comprehensive energy efficiency ratio of the sewage waste heat recovery heating system as the core optimization target, combining sewage physical property parameters, environmental parameters and heating load prediction data, and performing optimization calculations using the digital twin model of the sewage waste heat recovery heating system under the condition of ensuring that the heating demand of users is met.

[0065] As an embodiment of the present invention, the digital twin platform includes a physical equipment layer, a data capture layer, an intelligent computing layer, a communication transmission layer, and a decision-making control layer;

[0066] The physical equipment layer includes a sewage tank, a magnetic levitation heat pump unit, a heat exchange station, fiber optic temperature sensors, a water pump group, a flow meter, a turbidimeter and corresponding control equipment; the sewage tank is connected to the magnetic levitation heat pump unit, the magnetic levitation heat pump unit is connected to the heat exchange station, and a water pump group, a flow meter, a turbidimeter and fiber optic temperature sensors are installed on the connecting pipe between the sewage tank and the magnetic levitation heat pump unit, and a water pump group is installed between the magnetic levitation heat pump unit and the heat exchange station;

[0067] The data capture layer is used to monitor the operating parameters and working status of the physical equipment layer in real time and provide data sources for the digital twin model;

[0068] The intelligent computing layer is used to implement heterogeneous data integration, feature extraction and intelligent analysis, and provide data streams for the digital twin model;

[0069] The communication transmission layer adopts a hybrid networking technology of wired network and wireless sensors to achieve low-latency information interaction between the entity device layer, data capture layer, intelligent computing layer, and decision control layer, providing a signal flow for the digital twin model;

[0070] The decision control layer relies on the digital twin model of the sewage waste heat recovery heating system, compares the operating parameters and working status of the entity device layer with the simulation deduction results, continuously calibrates the parameter accuracy of the digital twin model of the sewage waste heat recovery heating system, and obtains the optimal control strategy that maximizes the system's comprehensive energy efficiency ratio (COP) according to the simulation deduction results of the digital twin model of the sewage waste heat recovery heating system, providing an instruction flow for the digital twin model.

[0071] As an embodiment of the present invention, establishing the digital twin model of the sewage waste heat recovery heating system specifically includes:

[0072] (1) After mapping and reconstructing the entity device in the virtual space, a digital twin model of the sewage waste heat recovery heating system is established. Real-time data synchronization between the entity device and the virtual model is achieved through the OPC UA protocol to ensure that the model state is consistent with the actual system; the sewage temperature and suspended solid concentration are collected in real-time through fiber optic temperature sensors and turbidity meters;

[0073] (2) Classify the types of suspended solids (grease, fiber, sediment) in real-time through the YOLOv5 algorithm and construct a fouling rate prediction model:

[0074]

[0075] Among them, R fouling is the fouling rate, C ss is the suspended solid concentration, v is the flow velocity, E a is the activation energy, T is the absolute temperature; k is an empirical coefficient, which is fitted through experimental data;

[0076] In a specific application case, the parameters of a certain sewage system:

[0077] C ss = 1500mg / L, v = 1.2m / s, T = 318K, k = 2.5×10 -5 , E a = 60kJ / mol,

[0078] Then the fouling rate is:

[0079] R fouling = 2.5×10 -5 ·1500 1.2 ·1.2 -0.8 ·e -60000 / (8.314·318) ≈ 0.15mm / year;

[0080] (3) Establish the energy efficiency model of the magnetic levitation heat pump unit for the sewage waste heat recovery heating system:

[0081]

[0082] Among them, COP is the comprehensive energy efficiency ratio of the system, N is the rotational speed of the magnetic levitation heat pump compressor established, η comp is the efficiency coefficient of the magnetic levitation heat pump compressor, N max is the maximum rotational speed, T cond is the condensation temperature, T evap is the evaporation temperature;

[0083] (4) Magnetic levitation heat pump efficiency decay model:

[0084]

[0085] Among them, U0 is the heat transfer coefficient in the clean state, t is the operation duration; combined with the backwash frequency of the online cleaning system, dynamically optimize the maintenance period;

[0086] (5) Access the API of the meteorological bureau to obtain the predicted temperature data for the next 24 hours. Combine the building thermal inertia model to predict the heating load demand curve and establish a non-linear compensation function for temperature - heat pump outlet water temperature, and the expression is:

[0087] T supply = T base +α·(T out - T design )

[0088] Among them, T supply is the dynamically adjusted water supply temperature, T base is the designed water supply temperature, a is the compensation coefficient, T out is the real-time ambient temperature, T design is the designed reference temperature.

[0089] In another specific application case, the system parameters are:

[0090] T design = -10 °C, T base = 45 °C, a = 0.4 °C / °C,

[0091] When T out = -15 °C, then T supply = 45 + 0.4·(-15 - (-10)) = 43 °C;

[0092] When T out = 5 °C, then T supply = 45 + 0.4·(5 - (-10)) = 51 °C.

[0093] The magnetic levitation heat pump compressor of the present invention adopts IGBT DC frequency modulation technology and combines the PID algorithm to achieve precise control of the rotational speed.

[0094] By establishing a non-linear compensation function of air temperature - heat pump outlet water temperature, the present invention enables the sewage waste heat recovery heating system to achieve the dual goals of heating on demand and energy-saving operation under complex climate conditions.

[0095] By introducing a fouling rate prediction model, the present invention dynamically predicts the fouling rate of the magnetic levitation heat pump based on sewage composition, temperature, and flow rate, and optimizes the cleaning cycle.

[0096] As an embodiment of the present invention, the optimization target model of the sewage waste heat recovery heating system is constructed to obtain the optimal control strategy, which specifically includes:

[0097] (1) Taking the maximization of the system comprehensive energy efficiency ratio (COP) of the sewage waste heat recovery heating system as the core optimization target, taking into account the minimization of pipeline network heat loss and the equalization of equipment life, a target function is constructed for the dynamic optimization control of the sewage waste heat recovery heating system. The target function is:

[0098] max(w1·COP - w2·Q loss - w3·∑ΔL device )

[0099] Wherein, the weight coefficients are w1 = 0.6, w2 = 0.3, w3 = 0.1, Q loss is the pipeline network heat loss, and ΔL device is the equipment life attenuation index;

[0100] (2) Based on the model predictive control (MPC) algorithm, the real-time operation results of the digital twin model are obtained, the target function is solved, and the optimal control strategy for maximizing the system comprehensive energy efficiency ratio (COP) of the sewage waste heat recovery heating system is determined according to the solution results. The physical equipment of the heating system is dynamically optimized and controlled according to the optimal control strategy; the control variables within the next 15 minutes are optimized in a rolling manner, such as: the rotational speed of the magnetic levitation heat pump compressor, the flow rate of the circulation pump, and the valve opening degree, and the control instruction is updated every 30 seconds;

[0101] (3) When the environmental temperature suddenly changes by ΔT > 5°C / 10 min or the suspended solid concentration exceeds the standard C ss > 2000 NTU, the adaptive adjustment mode is triggered, and the standby magnetic levitation heat pump is automatically switched to and the backwashing program is started.

[0102] As an embodiment of the present invention, the environmental parameters include the real-time air temperature and the user room temperature. The sewage waste heat recovery heating system can access the API of the meteorological bureau to obtain the real-time air temperature and the weather forecast for the next 24 hours, and combine the user room temperature data to predict the heating load demand; among them, the user room temperature data can be obtained through a ZigBee wireless thermostat.

[0103] As an embodiment of the present invention, a sewage waste heat recovery heating control method for a heat pump based on digital twin includes the following steps:

[0104] Step S101: Real-time monitor the sewage thermodynamic and water quality parameters through an optical fiber temperature sensor and a turbidimeter;

[0105] Step S102: The digital twin model calculates the current system's theoretical optimal COP, and combines the fouling rate prediction model to output the cleaning suggestion for the magnetic levitation heat pump;

[0106] Step S103: Dynamic control execution: When the sewage temperature drops suddenly by 5°C, start the magnetic levitation heat pump;

[0107] Step S104: Automatically control the rotation speed of the magnetic levitation heat pump compressor, the flow rate of the circulation pump, and the opening degree of the valve according to the optimal solution of COP.

[0108] The present invention analyzes the suspended solid concentration in real time through a turbidimeter, establishes a fouling rate prediction model, predicts the fouling rate of the magnetic levitation heat pump, and optimizes the cleaning cycle in combination with the backwashing frequency of the on-line cleaning system; the magnetic levitation heat pump compressor adopts IGBT DC frequency modulation technology and combines the PID algorithm to achieve precise control of the rotation speed; by accessing the API of the meteorological bureau to obtain the temperature prediction data for the next 24 hours, the heating outlet temperature can be dynamically adjusted; the present invention can be widely applied to urban sewage treatment plants, industrial parks, and regional central heating projects, providing a standardized solution for the efficient utilization of low-grade energy and contributing to the realization of the "dual carbon" goal.

[0109] The present invention can increase the annual average COP from 3.1 to 4.2, with the energy saving rate increased by 31%; the unplanned shutdown rate is reduced from 12% to 3%, and the maintenance cost is reduced by 45%.

[0110] Please refer to Figure 2 , the present invention also provides a sewage waste heat recovery heating control system for a heat pump based on digital twin, including:

[0111] A digital twin platform construction module for constructing a digital twin platform for the sewage waste heat recovery heating system;

[0112] A digital twin model establishment module for establishing a digital twin model of the sewage waste heat recovery heating system;

[0113] Deployment module, which deploys the established digital twin model of the sewage waste heat recovery heating system into the digital twin platform of the constructed sewage waste heat recovery heating system;

[0114] Optimal control strategy construction module, which constructs an optimization target model of the sewage waste heat recovery heating system based on the operating parameters of the physical equipment of the sewage waste heat recovery heating system and the virtual data of the digital twin model to obtain the optimal control strategy;

[0115] And a dynamic optimization control module, which implements dynamic optimization control on the physical equipment of the heating system according to the optimal control strategy.

[0116] As an embodiment of the present invention, the sewage waste heat recovery heating control system based on digital twin further includes a digital twin platform, and the digital twin platform includes a physical equipment layer, a data capture layer, an intelligent computing layer, a communication transmission layer, and a decision-making control layer;

[0117] The physical equipment layer includes a sewage tank, a magnetic levitation heat pump unit, a heat exchange station, an optical fiber temperature sensor, a water pump group, a flow meter, a turbidity meter, and corresponding control equipment; the sewage tank is connected to the magnetic levitation heat pump unit, the magnetic levitation heat pump unit is connected to the heat exchange station, a water pump group, a flow meter, a turbidity meter, and an optical fiber temperature sensor are installed on the connecting pipeline between the sewage tank and the magnetic levitation heat pump unit, and a water pump group is installed between the magnetic levitation heat pump unit and the heat exchange station;

[0118] The data capture layer is used to monitor the operating parameters and working status of the physical equipment layer in real time and provide data sources for the digital twin model;

[0119] The intelligent computing layer is used to implement heterogeneous data integration, feature extraction, and intelligent analysis and provide data streams for the digital twin model;

[0120] The communication transmission layer adopts a hybrid networking technology of wired network and wireless sensors to realize low-latency information interaction between the physical equipment layer, the data capture layer, the intelligent computing layer, and the decision-making control layer and provide signal streams for the digital twin model;

[0121] The decision-making control layer relies on the digital twin model of the sewage waste heat recovery heating system, compares the operating parameters and working status of the physical equipment layer with the simulation deduction results, continuously calibrates the parameter accuracy of the digital twin model of the sewage waste heat recovery heating system, and obtains the optimal control strategy that meets the maximization of the system comprehensive energy efficiency ratio (COP) according to the simulation deduction results of the digital twin model of the sewage waste heat recovery heating system, and provides instruction streams for the digital twin model.

[0122] The main functions of the present invention:

[0123] A heat pump sewage waste heat recovery heating control method and system based on digital twin proposed by the present invention constructs a digital twin platform and a digital twin model, combines the operating parameters of the physical equipment of the sewage waste heat recovery heating system and the virtual data of the digital twin model, constructs an optimization target model of the sewage waste heat recovery heating system to obtain an optimal control strategy, and implements dynamic optimization control on the physical equipment of the heating system according to the optimal control strategy; improves the prediction accuracy through real-time data calibration, integrates model predictive control, realizes second-level response and multi-variable coordinated regulation, and effectively solves the problems of low energy efficiency, slow response and high maintenance cost of the traditional sewage waste heat recovery heating system.

[0124] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered by the scope of the claims and the description of the present invention.

Claims

1. A method for controlling the sewage waste heat recovery heating of a heat pump based on digital twin, characterized in that: Including: Constructing a digital twin platform for a sewage waste heat recovery heating system, which is used for two-way data interaction between the digital twin model of the sewage waste heat recovery heating system and the physical equipment of the sewage waste heat recovery heating system; Based on the operation parameters of the physical equipment of the sewage waste heat recovery heating system, establishing a digital twin model of the sewage waste heat recovery heating system; Deploying the established digital twin model of the sewage waste heat recovery heating system into the constructed digital twin platform of the sewage waste heat recovery heating system; Based on the operation parameters of the physical equipment of the sewage waste heat recovery heating system and the virtual data of the digital twin model, constructing an optimization target model of the sewage waste heat recovery heating system to obtain an optimal control strategy; Implementing dynamic optimization control on the physical equipment of the heating system according to the optimal control strategy.

2. The sewage waste heat recovery heating control method of the heat pump based on digital twin according to claim 1, characterized in that: The constructing an optimization target model of the sewage waste heat recovery heating system to obtain an optimal control strategy based on the operation parameters of the physical equipment of the sewage waste heat recovery heating system and the virtual data of the digital twin model includes: taking the maximization of the system comprehensive energy efficiency ratio of the sewage waste heat recovery heating system as the core optimization target, combining sewage physical property parameters, environmental parameters and heating load prediction data, and performing optimization calculations using the digital twin model of the sewage waste heat recovery heating system under the condition of ensuring that the heating demand of users is met.

3. The sewage waste heat recovery heating control method of the heat pump based on digital twin according to claim 1, characterized in that: The digital twin platform includes a physical equipment layer, a data capture layer, an intelligent computing layer, a communication transmission layer, and a decision-making control layer; The physical equipment layer includes a sewage tank, a magnetic levitation heat pump unit, a heat exchange station, fiber optic temperature sensors, a water pump group, a flow meter, a turbidity meter and corresponding control equipment; the sewage tank is connected to the magnetic levitation heat pump unit, the magnetic levitation heat pump unit is connected to the heat exchange station, and a water pump group, a flow meter, a turbidity meter and fiber optic temperature sensors are installed on the connecting pipe between the sewage tank and the magnetic levitation heat pump unit, and a water pump group is installed between the magnetic levitation heat pump unit and the heat exchange station; The data capture layer is used to monitor the operation parameters and working status of the physical equipment layer in real time and provide data sources for the digital twin model; The intelligent computing layer is used to implement heterogeneous data integration, feature extraction and intelligent analysis and provide data streams for the digital twin model; The communication transmission layer adopts a hybrid networking technology of wired network and wireless sensors to realize low-latency information interaction between the physical equipment layer, the data capture layer, the intelligent computing layer and the decision-making control layer and provide signal streams for the digital twin model; The decision-making control layer relies on the digital twin model of the sewage waste heat recovery heating system, compares the operation parameters and working status of the physical equipment layer with the simulation deduction results, continuously calibrates the parameter accuracy of the digital twin model of the sewage waste heat recovery heating system, and obtains the optimal control strategy that meets the maximization of the system comprehensive energy efficiency ratio (COP) according to the simulation deduction results of the digital twin model of the sewage waste heat recovery heating system, and provides instruction streams for the digital twin model.

4. The sewage waste heat recovery heating control method of the heat pump based on digital twin according to claim 1, characterized in that: Establishing the digital twin model of the sewage waste heat recovery heating system specifically includes: After mapping and reconstructing the physical equipment in the virtual space, a digital twin model of the sewage waste heat recovery heating system is established. Real-time data synchronization between the physical equipment and the virtual model is achieved through the OPC UA protocol to ensure that the model state is consistent with the actual system. The sewage temperature is collected in real time through fiber optic temperature sensors; Establish an energy efficiency model for the magnetic levitation heat pump unit of the sewage waste heat recovery heating system: Among them, COP is the system comprehensive energy efficiency ratio, N is the rotational speed of the magnetic levitation heat pump compressor, η comp is the efficiency coefficient of the magnetic levitation heat pump compressor, N max is the maximum rotational speed, T cond is the condensation temperature, T evap is the evaporation temperature.

5. The sewage waste heat recovery heating control method of the digital twin-based heat pump according to claim 4, characterized in that: Establishing the digital twin model of the sewage waste heat recovery heating system further includes: Collect the sewage suspended solid concentration in real time through a turbidimeter, classify the suspended solid types (oil, fiber, sediment) in real time through the YOLOv5 algorithm, and construct a fouling rate prediction model: Among them, R fouling is the fouling rate, C ss is the suspended solid concentration, v is the flow velocity, E a is the activation energy, T is the absolute temperature; k is an empirical coefficient, which is fitted through experimental data; Construct a magnetic levitation heat pump efficiency decay model: Among them, U0 is the heat transfer coefficient in the clean state, and t is the operating duration; combined with the backwashing frequency of the on-line cleaning system, the maintenance period is dynamically optimized.

6. The sewage waste heat recovery heating control method of the heat pump based on digital twin according to claim 5, characterized in that: Establishing the digital twin model of the sewage waste heat recovery heating system further includes: accessing the API of the meteorological bureau to obtain the predicted air temperature data for the next 24 hours, combining with the building thermal inertia model, predicting the heating load demand curve, and establishing a non-linear compensation function for the air temperature - heat pump outlet water temperature, and the expression is: T supply = T base + α·(T out - T design ) Among them, T supply is the dynamically adjusted water supply temperature, T base is the designed water supply temperature, a is the compensation coefficient, T out is the real-time ambient temperature, T design is the designed reference temperature.

7. The sewage waste heat recovery heating control method of the digital twin-based heat pump according to claim 4, characterized in that: The construction of the optimization target model of the sewage waste heat recovery heating system to obtain the optimal control strategy specifically includes: Taking the maximization of the system comprehensive energy efficiency ratio (COP) of the sewage waste heat recovery heating system as the core optimization goal, taking into account the minimization of pipeline heat loss and the equalization of equipment life, constructing an objective function for the dynamic optimization control of the sewage waste heat recovery heating system, and the objective function is: max(w1·COP - w2·Q loss - w3·∑ΔL device ) Among them, the weight coefficients are \(w1 = 0.6\), \(w2 = 0.3\), \(w3 = 0.1\), and \(Q\) loss is the heat loss of the pipe network, and \(\Delta L\) device is the equipment life attenuation index; Based on the model predictive control algorithm, obtain the real-time operation results of the digital twin model, solve the objective function, and determine the optimal control strategy for maximizing the system comprehensive energy efficiency ratio of the sewage waste heat recovery heating system according to the solution results.

8. The sewage waste heat recovery heating control method of the digital twin-based heat pump according to claim 7, characterized in that: Implementing dynamic optimization control on the physical equipment of the heating system according to the optimal control strategy includes: implementing dynamic optimization control on the physical equipment of the heating system according to the optimal control strategy. When the ambient temperature suddenly changes by ΔT > 5°C / 10 min or the suspended solid concentration exceeds the standard C ss > 2000 NTU, trigger the adaptive adjustment mode, automatically switch to the standby magnetic levitation heat pump and start the backwashing program.

9. The sewage waste heat recovery heating control system of a heat pump based on digital twin is characterized in that: Including: A digital twin platform construction module for constructing a digital twin platform for the sewage waste heat recovery heating system; A digital twin model establishment module for establishing a digital twin model of the sewage waste heat recovery heating system; A deployment module for deploying the established digital twin model of the sewage waste heat recovery heating system into the constructed digital twin platform of the sewage waste heat recovery heating system; An optimal control strategy construction module for constructing an optimization target model of the sewage waste heat recovery heating system to obtain the optimal control strategy based on the operating parameters of the physical equipment of the sewage waste heat recovery heating system and the virtual data of the digital twin model; A dynamic optimization control module for implementing dynamic optimization control of the physical equipment of the heating system according to the optimal control strategy.

10. The sewage waste heat recovery heating control system of the heat pump based on digital twin according to claim 9, characterized in that: Including a digital twin platform, and the digital twin platform includes a physical equipment layer, a data capture layer, an intelligent computing layer, a communication transmission layer, and a decision-making control layer; The physical equipment layer includes a sewage tank, a magnetic levitation heat pump unit, a heat exchange station, fiber optic temperature sensors, a water pump group, a flow meter, a turbidimeter and corresponding control equipment; the sewage tank is connected to the magnetic levitation heat pump unit, the magnetic levitation heat pump unit is connected to the heat exchange station, a water pump group, a flow meter, a turbidimeter and a fiber optic temperature sensor are installed on the connecting pipeline between the sewage tank and the magnetic levitation heat pump unit, and a water pump group is installed between the magnetic levitation heat pump unit and the heat exchange station; The data capture layer is used to monitor the operating parameters and working status of the physical device layer in real time, providing a data source for the digital twin model; The intelligent computing layer is used to implement heterogeneous data integration, feature extraction and intelligent analysis, providing a data stream for the digital twin model; The communication and transmission layer adopts a hybrid networking technology of wired network and wireless sensors to realize low-latency information interaction among the physical device layer, data capture layer, intelligent computing layer and decision-making and control layer, providing a signal stream for the digital twin model; The decision-making and control layer relies on the digital twin model of the sewage waste heat recovery heating system, compares the operating parameters and working status of the physical device layer with the simulation results, continuously calibrates the parameter accuracy of the digital twin model of the sewage waste heat recovery heating system, and obtains the optimal control strategy that meets the maximization of the system's comprehensive energy efficiency ratio (COP) according to the simulation results of the digital twin model of the sewage waste heat recovery heating system, providing an instruction stream for the digital twin model.

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