Novel quality integrated combined cooling heating and power system and parameter optimization method thereof

Abstract

The invention discloses a novel quality-integrated combined cooling heating and power system and a parameter optimization method thereof, and relates to the technical field of combined cooling heating and power, the system comprises an ORC module, a compression heat pump module, a jet refrigeration module, a heat exchanger and a working medium pump; a first working medium inlet of the ORC module is used for inputting first working fluid; the first working fluid carries industrial waste heat, and the ORC module is used for generating electric energy by utilizing the industrial waste heat and outputting saturated steam and waste liquid fluid at a first working medium outlet and a second working medium outlet of the ORC module respectively; the compression type heat pump module conducts heating through waste liquid fluid and saturated steam and outputs second working fluid, the second working fluid enters the heat exchanger, the heat exchanger conducts heat exchange on the second working fluid and then outputs third working fluid, and the jet refrigeration module conducts refrigeration through the third working fluid. The complexity of the system is reduced, and the energy efficiency of the system is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of combined cooling, heat and power, in particular to a novel mass-integrated combined cooling, heat and power system and a parameter optimization method thereof. BACKGROUND

[0002] Organic Rankine Cycle (ORC) plays a key role in the efficient operation of combined cooling, heat and power (CCHP) systems. The ejector jet refrigeration system uses high-pressure fluid injection cooling, which has the advantages of no need for a compressor, simplified design, and improved reliability. The compression heat pump uses a small amount of electrical energy to upgrade the fluid entering the compressor and output high-grade heat energy, achieving cascade utilization of energy. However, when the traditional ORC system, the ejector jet refrigeration system and the compression heat pump are combined, the flow paths of the three systems are generally connected in series. However, this application method requires separate fluid circuits for each system, which increases the complexity of the overall CCHP system, greatly increasing the system equipment investment cost and the cost of subsequent system maintenance and operation. In addition, the separate fluid circuits of the ORC system, the ejector jet refrigeration system and the compression heat pump system only utilize industrial waste heat for the recovery of a certain type of energy, for example, the fluid circuit of the ORC system can only utilize industrial waste heat for power generation, which greatly reduces the energy efficiency of the CCHP system. SUMMARY

[0003] The purpose of the present application is to provide a novel mass-integrated combined cooling, heat and power system and a parameter optimization method thereof, which can reduce the complexity of the system and improve the energy efficiency of the system.

[0004] To achieve the above-mentioned purpose, the present application provides the following solutions. In a first aspect, the present application provides a novel mass-integrated combined cooling, heat and power system, comprising: an ORC module, a compression heat pump module, an ejector refrigeration module, a heat exchanger and a working fluid pump. The first working fluid carries industrial waste heat; the first working fluid outlet of the ORC module is in communication with the first inlet of the compression heat pump module, and the second working fluid outlet of the ORC module is in communication with the second inlet of the compression heat pump module, the ORC module is used to generate electrical energy by utilizing the industrial waste heat, and to output saturated steam and waste liquid fluid; The outlet of the compression heat pump module is in communication with the first inlet of the heat exchanger, the compression heat pump module utilizes the waste liquid fluid and the saturated steam to generate heat and outputs a second working fluid; the temperature of the first working fluid is greater than the temperature of the second working fluid; The first outlet of the heat exchanger is connected to the working fluid inlet of the jet refrigeration module, the working fluid outlet of the jet refrigeration module is connected to the inlet of the working fluid pump, the outlet of the working fluid pump is connected to the second inlet of the heat exchanger, and the second outlet of the heat exchanger is connected to the second working fluid inlet of the ORC module; the heat exchanger exchanges heat with the second working fluid and outputs a third working fluid, wherein the temperature of the third working fluid is lower than the temperature of the second working fluid, and the jet refrigeration module uses the third working fluid for refrigeration.

[0005] Secondly, this application provides a parameter optimization method based on a novel quality-integrated combined cooling, heating and power system, including: Multiple sets of simulation data were obtained for the novel integrated cogeneration system. These simulation data were obtained by simulating the recovery of industrial waste heat using the novel integrated cogeneration system under different combinations of operating parameter values. The simulation data included operating parameter values, including the power generation parameters of the ORC module, the heat generation parameters of the compression heat pump module, the refrigeration parameters of the jet refrigeration module, and the outlet pressure of the working fluid pump. A multi-objective function is constructed with the objectives of maximizing the effective energy efficiency, return on investment, and carbon dioxide equivalent emission reduction of the new quality-integrated cogeneration system. Based on the aforementioned multiple sets of simulation data, a target space for a multi-objective function is constructed. Based on the target space, the non-dominated sorting genetic algorithm III is used to solve the multi-objective function to obtain the optimal parameter combination.

[0006] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a novel integrated combined cooling, heating, and power (CCHP) system and its parameter optimization method. The system connects an ORC module and a compression heat pump module in series via a heat exchanger, allowing them to share a single fluid loop. Compared to traditional systems where ORC and compression heat pump modules have separate fluid loops for waste heat recovery, this reduces the number of devices and lowers system complexity. Furthermore, the heat exchanger and working fluid pump input the second working fluid output from the compression heat pump module to the jet refrigeration module for cooling. The second working fluid output from the compression heat pump module has a certain pressure, but the heat exchanger has little impact on this pressure. Therefore, the jet refrigeration module does not require an additional compressor to pressurize the working fluid, further reducing the number of devices and system complexity. The entire system sequentially recovers industrial waste heat for electricity, heating, and cooling, significantly improving the overall system energy efficiency. Attached Figure Description

[0007] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0008] Figure 1 This is a schematic diagram of the workflow of a novel integrated quality control combined cooling, heating and power system according to one embodiment of this application.

[0009] Figure 2 This is a flowchart illustrating a parameter optimization method for a novel quality-integrated combined cooling, heating and power system, as provided in an embodiment of this application.

[0010] Figure 3 This is a detailed flowchart illustrating a parameter optimization method for a novel quality-integrated combined cooling, heating and power system, provided as an embodiment of this application.

[0011] Figure 4 A schematic diagram showing the fitting results used to verify the calculation formula for the power generation efficiency of the working fluid.

[0012] Figure 5 This is a schematic diagram of the structure of a PINN model provided in an embodiment of this application.

[0013] Figure 6 This is a detailed flowchart of the non-dominated sorting genetic algorithm III provided in an embodiment of this application. Detailed Implementation

[0014] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0015] To make the objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0016] like Figure 1 As shown in the embodiment of this application, a novel quality-integrated combined cooling, heating and power system is provided. The system includes an ORC module 1, a compression heat pump module 2, a jet refrigeration module 3, a heat exchanger IHX, and a working fluid pump PUMP.

[0017] The first working fluid inlet of the ORC module 1 is used to input a first working fluid, which carries industrial waste heat. The first working fluid outlet of the ORC module 1 is connected to the first inlet of the compression heat pump module 2, and the second working fluid outlet of the ORC module 1 is connected to the second inlet of the compression heat pump module 2. The ORC module 1 is used to generate electricity using the industrial waste heat and output saturated steam and waste liquid fluid.

[0018] In one exemplary embodiment, ORC module 1 specifically includes: a first evaporator EVA01 and a turbine TUR.

[0019] The first inlet of the first evaporator EVA01 is used to input the first working fluid; the second inlet of the first evaporator EVA01 is connected to the second outlet of the heat exchanger TUR; the first outlet of the first evaporator EVA01 is connected to the inlet of the turbine TUR; and the outlet of the turbine TUR is connected to the first inlet of the compression heat pump module 2.

[0020] The first outlet of the first evaporator EVA01 outputs saturated steam, and the second outlet of the first evaporator EVA01 outputs waste liquid fluid. The turbine TUR uses the saturated steam to generate electricity.

[0021] Specifically, industrial waste heat (first working fluid, stream S15) first enters the first evaporator EVA01. Stream S15 undergoes waste heat vaporization in the first evaporator EVA01, outputting stream S2 and waste liquid fluid (stream S16). Specifically, it absorbs the waste heat from stream S1 and completely vaporizes it. The first evaporator EVA01 is not additionally heated; it is only used for waste heat vaporization. Stream S2 then enters the turbine TUR for desuperheating and pressure reduction, driving the turbine to rotate and generate electricity. The saturated steam at the outlet of the turbine TUR is stream S3.

[0022] The outlet of the compression heat pump module 2 is connected to the first inlet of the heat exchanger. The compression heat pump module 2 uses the waste liquid fluid and the saturated steam to generate heat and output a second working fluid. The temperature of the first working fluid is greater than the temperature of the second working fluid.

[0023] In one exemplary embodiment, the compression heat pump module 2 specifically includes: a second evaporator EVA02, a compressor COM, and a first condenser CON01.

[0024] The first inlet of the second evaporator EVA02 is connected to the first working fluid outlet of the ORC module, the second inlet of the second evaporator EVA02 is connected to the second working fluid outlet of the ORC module, the first outlet of the second evaporator EVA02 is connected to the inlet of the compressor COM; the outlet of the compressor COM is connected to the inlet of the first condenser CON01; and the outlet of the first condenser CON01 is connected to the first inlet of the heat exchanger IHX.

[0025] The second evaporator EVA02 uses the waste liquid fluid to heat the saturated steam. The first outlet of the second evaporator EVA02 outputs the heated saturated steam. The compressor COM pressurizes the heated saturated steam and outputs the pressurized working fluid. The first condenser CON01 uses the pressurized working fluid for heating. The outlet of the first condenser CON01 outputs the second working fluid.

[0026] Specifically, stream S3 is reheated by the waste heat of stream S16 in the second evaporator EVA02 to increase its superheat, and then outputs stream S4. Stream S4 enters the compressor COM for compression and quality improvement, and outputs stream S5. Stream S5 is cooled and heated in the first condenser CON01, but the pressure of stream S5 is not significantly affected, and then outputs stream S6 (second working fluid), which is high-grade thermal energy.

[0027] The first outlet of the heat exchanger IHX is connected to the working fluid inlet of the jet refrigeration module 3, the working fluid outlet of the jet refrigeration module 3 is connected to the inlet of the working fluid pump, the outlet of the working fluid pump is connected to the second inlet of the heat exchanger IHX, and the second outlet of the heat exchanger IHX is connected to the second working fluid inlet of the ORC module 1. The heat exchanger IHX exchanges heat with the second working fluid and outputs a third working fluid, wherein the temperature of the third working fluid is lower than the temperature of the second working fluid, and the jet refrigeration module 3 uses the third working fluid for refrigeration.

[0028] In one exemplary embodiment, the jet refrigeration module 3 specifically includes: an ejector INJECTOR, a second condenser CON02, a valve, and a third evaporator EVA03.

[0029] The first inlet of the ejector INJECTOR is connected to the first outlet of the heat exchanger IHX; the second inlet of the ejector INJECTOR is connected to the outlet of the third evaporator, and the outlet of the ejector INJECTOR is connected to the inlet of the second condenser CON02; the outlet of the second condenser CON02, the inlet of the working fluid pump PUMP, and one end of the valve are connected; the other end of the valve VALVE is connected to the inlet of the third evaporator EVA03.

[0030] The third working fluid is input from the first inlet of the ejector INJECTOR and serves as the ejector fluid of the ejector INJECTOR. The fourth working fluid is output from the outlet of the ejector INJECTOR. A portion of the fourth working fluid passes sequentially through the third evaporator EVA03 and the valve VALVE to output a fifth working fluid. The second condenser CON02 uses the fifth working fluid for refrigeration.

[0031] Specifically, stream S6 enters heat exchanger IHX01 for heat exchange. Stream S7 (the third working fluid) output from heat exchanger IHX01 has little impact on the pressure of stream S6. Therefore, stream S7 is a vapor stream with higher temperature and pressure. This vapor stream is used as the ejector stream for the ejector JNJECTOR to increase the pressure of stream S14. Stream S8, after being mixed with stream S7 and stream S14, enters condenser CON02. After being cooled by condensate, stream S8 is output as stream S9 (the fourth working fluid). A portion of stream S9 is circulated to the working fluid pump PUM for pressurization and output as a cold stream (stream S11). Stream S11 enters heat exchanger IHX01 and recirculates to evaporator EVA01, completing the heat pump and power generation cycle. Another portion of stream S9 is depressurized by valve VALVE and its temperature decreases. It then undergoes refrigeration in evaporator EVA03, outputting cooling capacity. The cooled outlet stream (stream S14) is a low-pressure stream, which enters the ejector JNJECTOR as the ejector to increase its pressure, thus completing the refrigeration cycle. The hot stream (stream S6) at the outlet of condenser CON01 still has high energy, and subsequent processes require condensate cooling before refrigeration. Therefore, this hot stream is introduced into heat exchanger IHX01 to preheat the cold stream at the outlet of PUMP01. This saves cooling water consumption and increases the initial temperature of stream S1, allowing stream S2, which is subsequently used for power generation, to have a higher superheat, thereby further improving the overall thermal efficiency of the system.

[0032] In one exemplary embodiment, such as Figure 2 and Figure 3As shown, a parameter optimization method based on a novel quality-integrated combined cooling, heating, and power (CCHP) system is provided. This method includes steps 201 to 204. Wherein: Step 201: Obtain multiple sets of simulation data for the novel integrated cogeneration system; the multiple sets of simulation data are obtained by simulating the recovery of industrial waste heat using the novel integrated cogeneration system under different combinations of operating parameter values; the simulation data includes operating parameter values; the operating parameters include the power generation parameters of the ORC module, the heat generation parameters of the compression heat pump module, the refrigeration parameters of the jet refrigeration module, and the outlet pressure of the working fluid pump.

[0033] Step 202: Construct a multi-objective function with the objectives of maximizing the effective energy efficiency, return on investment, and carbon dioxide equivalent emission reduction of the new quality integrated combined cooling, heating and power system.

[0034] Step 203: Based on the multiple sets of simulation data, construct the target space of the multi-objective function.

[0035] Step 204: Based on the target space, the non-dominated sorting genetic algorithm III is used to solve the multi-objective function to obtain the optimal parameter combination.

[0036] By implementing steps 201 to 204 above, this application can obtain the optimal parameter combination of the novel quality integrated cogeneration system. Based on the optimal parameter combination, the energy efficiency of the novel quality integrated cogeneration system can be improved, while reducing equipment operation and maintenance costs and increasing the return on investment of equipment.

[0037] In an exemplary embodiment, step 201 specifically includes steps 21-23: Step 21: Determine the comprehensive score of each type of working fluid by using the power generation efficiency, environmental impact indicators, and safety indicators of the working fluid.

[0038] The working fluid was screened and selected from 58 candidate working fluids, covering both traditional and novel environmentally friendly working fluids. A working fluid selection model based on Python for the ORC system was developed to screen the 58 commonly used working fluids. The optimal result selected was R1233ZD(E).

[0039] This working fluid screening and selection process integrates thermodynamic, environmental, and safety parameters of the working fluid, and features automatic optimization and scalability, enabling rapid evaluation of both traditional and unexplored working fluids.

[0040] The power generation efficiency of the working fluid can be quickly preliminarily screened using the calculation formula. Specifically, the calculation formula for the power generation efficiency of the working fluid is: Among them, T c T is the critical temperature (K) of the working fluid. w The waste heat temperature (K) after waste heat recovery of the working fluid, C p The heat capacity of the working fluid is (kJ / (kg·K)).

[0041] However, different working fluids exhibit varying thermodynamic properties, resulting in different optimal operating parameters (such as evaporation pressure and condensation pressure) for different cogeneration systems. Therefore, in practical screening, evaporation pressure and condensation pressure should be used as the core operating variables. Within a specific temperature range of 363.15K-423.15K, the actual power generation efficiency of different working fluids should be accurately evaluated. This evaluation should then be combined with environmental impact indicators (such as pollutant emissions) and safety indicators (such as working fluid stability and toxicity) to ultimately determine the comprehensive score for each type of working fluid, achieving a working fluid selection that better meets the actual operational needs of the system.

[0042] Based on the analysis of parameter and performance data of 58 working fluids, the formula for calculating the power generation efficiency of the working fluid reveals the correlation between system performance and the physical properties of the working fluid. The fitting results are as follows: Figure 4 As shown, the predicted values ​​closely match the actual values ​​along the best-fit line, R0 2 =0.98. This indicates that the method for calculating the power generation efficiency of the working fluid effectively characterizes the interaction between fluid properties and ORC system performance, providing a reliable tool for fluid selection and performance prediction.

[0043] Environmental impact indicators include ozone depletion potential (ODP) and global warming potential (GWP). The ODP and GWP values ​​were obtained from relevant references. Safety indicators refer to the safety of the working fluid. The safety level is determined based on the fluid's physical properties, with different safety levels corresponding to different safety values. These values ​​are determined through experience. See Table 1 for specific values ​​for each indicator.

[0044] Table 1

[0045] Among them, A1, A2, A2L, A3, B1 and B3 represent different safety levels.

[0046] Specifically, a comprehensive score for each working fluid is obtained by weighted summation of its ODP, GWP, and safety indicators, with the weight of each indicator determined through human experience.

[0047] Step 22: Use the working fluid with the highest overall score as the input for the novel quality-integrated cogeneration system in the recovery simulation.

[0048] Step 23: Obtain multiple sets of operating parameter values ​​during the industrial waste heat recovery simulation process.

[0049] Process simulation software was used to construct a steady-state mechanism model for a novel Mass Integration OVJ Combined Cooling Heating and Power (MI-OVJCCHP) system. Here, OVJ represents the subsystem names: Organic Rankine Cycle, Vapor Compression Heat Pump, and Jet Refrigeration Cycle. Figure 3 As shown, the process involves calling Aspen Plus for initialization optimization, inputting variable values, running simulations, and convergence verification. This workflow completes the construction of the steady-state mechanism model and data output. The MI-OVJCCHP system includes a compressor (COM), a working fluid pump (PUM), a turbine (TUR), a heat exchanger (IHX), a first evaporator (EVA01), a second evaporator (EVA02), a third evaporator (EVA03), a first condenser (CON01), a second condenser (CON02), and a valve (VALVE). The power generation parameter of the ORC module in the operating parameters of the MI-OVJCCHP system is the compression ratio of the compressor. The heat production parameter of a compression heat pump module is the turbine outlet pressure. The refrigeration parameters of the jet refrigeration module are the refrigeration evaporation pressure of the third evaporator. and the outlet pressure of the working fluid pump .

[0050] In one exemplary embodiment, step 202 includes: Energy loss assessment, economic research, and environmental benefit assessment of novel integrated cooling, heating, and power systems are conducted to ensure energy utilization and effective waste heat recovery without significant capital expenditure and with minimal environmental damage. A multi-objective function is constructed.

[0051] Specifically, the multi-objective functions include the energy efficiency objective function, the return on investment objective function, and the carbon dioxide equivalent emission reduction objective function.

[0052] The construction process of the multi-objective function is explained using the MI-OVJCCHP system, which includes compressor COM, working fluid pump PUM, turbine TUR, heat exchanger IHX, first evaporator EVA01, second evaporator EVA02, third evaporator EVA03, first condenser CON01, second condenser CON02, and valve VALVE.

[0053] (1) Thermodynamic analysis of the streams and components in the MI-OVJCCHP system based on thermodynamic models is crucial for understanding energy flow and conversion mechanisms. By conducting energy analysis on the streams and components of the MI-OVJCCHP system, establishing energy analysis models and effective energy analysis models, and then evaluating energy loss, conversion efficiency and their interrelationships, it is helpful to optimize energy utilization.

[0054] Energy analysis model: Under steady-state conditions, the total inlet mass flow rate and the total outlet mass flow rate of the system satisfy the following equation: ; in, Mass flow rate, unit: The subscripts 'in' and 'out' refer to the inlet and outlet flow rates, respectively, to achieve system mass balance analysis and describe the flow and transformation process of the working fluid under different operating conditions. For the MI-OVICCHP system, the general energy balance of each device satisfies the equation: ; in, Heat load (kW); enthalpy (h) is the heat load. ; Electricity consumption, unit: kW.

[0055] By utilizing the general energy balance of each component, the expression for the energy balance of each component is obtained, as shown in Table 2. The energy consumption of each component is calculated using this expression, or the outlet flow status of the heat exchanger is calculated. In this embodiment, the heat exchanger includes a heat exchanger, a first evaporator, a second evaporator, and a third evaporator.

[0056] Table 2

[0057] In this context, the subscript 'c' indicates the cold flow stream and 'h' indicates the hot flow stream.

[0058] Overall energy efficiency of the MI-OVJCCHP system The calculation formula is: in, and These are the electricity consumed by the compressor and the working fluid pump, respectively. The electricity generated by the turbine, , , and The heat loads are respectively the heat loads of the first evaporator, the second evaporator, the third evaporator, the first condenser, and the second condenser.

[0059] Used to evaluate the overall energy efficiency of a system under multi-energy complementarity conditions This performance provides a theoretical basis for system optimization and operation methods.

[0060] Effectiveness analysis model: The effective energy of the working fluid consists of physical effective energy and chemical effective energy, satisfying the equation: ; in, The effective energy of the working fluid is represented by "ph" (unit: kW), where "ph" represents physical effective energy and "ch" represents chemical effective energy. Since the MI-OVJCCHP system only involves simple thermodynamic processes involving phase change, chemical effective energy is not considered. In this case, the effective energy is determined by the following equation: in, i Number the input and output streams of each component. Represents ambient temperature, h represents enthalpy, unit: ; S Represents the entropy value. and These are the enthalpy and entropy values ​​under the reference conditions, respectively.

[0061] Irreversible processes in the system lead to energy loss. This stems from friction, turbulence, imperfect heat transfer, and component friction losses, resulting in effective energy loss. Calculate according to the following equation: in, and These are the performance parameters of the component's input stream and output stream, respectively. The effective energy generated by heat exchange in the components and These represent the electricity consumed and generated by the component, respectively. If a component cannot perform its function, the corresponding value is 0. For example, if the turbine does not perform heat exchange, then... If the value is 0, then the turbine does not consume electricity. It is 0.

[0062] Effective energy generated by heat exchange Calculate according to the following equation: and, in, The logarithmic mean temperature difference of the external fluid. For the outlet temperature, This refers to the inlet temperature.

[0063] The effective energy efficiency of the MI-OVJCCHP system can be obtained using the above formula. The calculation formula is as follows: The objective function for effective energy efficiency is to maximize effective energy efficiency.

[0064] The calculation methods for the effective energy loss and effective energy efficiency of each component are shown in Table 3.

[0065] Table 3

[0066] (2) Economic analysis model: Total investment cost per piece of equipment Satisfying the equation: in, Equipment investment cost (in US dollars). Equipment maintenance and operating costs (in US dollars).

[0067] Equipment investment cost The calculation formula is: in, Baseline cost of equipment (in US dollars). Here are the reference dimensions for the equipment, Q represents the actual dimensions of the equipment, and the superscript M indicates the cost parameter. Calibration coefficients for the effects of materials, pressure, and temperature; equipment maintenance and operating costs. The calculation formula is: in, and These are the electricity consumed by the pump and compressor, respectively. The heat load of the j-th condenser is... For runtime, For electricity price, For cooling water costs In this embodiment, the operating time is 8000 operating hours per year, and the electricity price is... Each component , , The specific calculation method is shown in Table 4. Table 4

[0068] Equivalent economic benefits of the MI-OVJCCHP system The calculation formula is: in, The total equivalent power generation is calculated as follows: in, and These are the temperatures (in K) when the stream enters and leaves the third evaporator, respectively. and These are the temperatures at which the stream enters and exits the first condenser, respectively.

[0069] The formula for calculating Return on Investment (ROI) is: in, The sum of maintenance and operating costs for all devices in the MI-OVJCCHP system. This is the sum of the investment costs of all devices in the MI-OVJCCHP system.

[0070] The objective function for the return on investment is to maximize the rate of return on investment.

[0071] Return on investment (ROI) is used to evaluate the efficiency of system investment. The higher the ROI, the stronger the economic feasibility of the investment.

[0072] (3) Environmental analysis model.

[0073] Given that CO2, as a major greenhouse gas, has a significant impact on global climate change and the ecological environment, this application focuses on energy conservation, emission reduction, and minimizing environmental damage as its core objectives. To more accurately assess its environmental benefits, CO2 equivalent emission reduction (CCER) is used as the core evaluation indicator; the greater the CO2 equivalent emission reduction, the less damage to the environment. The calculation method for this indicator is as follows: in, The conversion factor for CO2 is given in this embodiment. .

[0074] The objective function for carbon dioxide equivalent emission reduction is to maximize the carbon dioxide equivalent emission reduction.

[0075] Step 203 includes steps 31-32: Step 31: Based on the multiple sets of simulation data, the trained PINN model is used to predict the effective energy efficiency, return on investment, and carbon dioxide equivalent emission reduction.

[0076] like Figure 5 As shown, the PINN model includes an input layer, two hidden layers, and an output layer.

[0077] Specifically, the input layer is configured with five features, namely the compressor compression ratio. outlet pressure of the working fluid pump Turbine outlet pressure and refrigeration evaporation pressure .

[0078] The hidden layer employs a two-layer structure, with each layer containing 32 LeakyReLU activation units to enhance the model's ability to fit nonlinear relationships; the output layer has three neurons, each predicting one of the system's three optimization objectives. ROI and CEER.

[0079] The training process of the PINN model is as follows: Based on multiple sets of simulation data, the value ranges of each manipulated variable were determined. These manipulated variables included the compressor compression ratio, the outlet pressure of the working fluid pump, the turbine outlet pressure, and the refrigeration evaporation pressure. A multidimensional variable matrix containing the value ranges of each manipulated variable was generated using the Latin Hypercube Sampling (LHS) method. This matrix comprised a dataset with multiple combinations of different manipulated variables, and the corresponding effective energy efficiency, return on investment, and CO2 equivalent emission reduction were used as labels. A high-quality training dataset was constructed after simulation iterations and convergence verification. The PINN model was then trained using this training dataset.

[0080] The expression for the composite loss function is: ; in, For composite loss function, For weighting coefficients, For the mean squared error loss term, This is the physical loss item.

[0081] The formula for calculating the deviation between the predicted label and the true label using mean squared error loss is as follows: in, For real labels, Let n be the predicted label, and n be the total number of samples in the training dataset.

[0082] Physical loss item By minimizing the sum of squares of the energy conservation residuals, the neural network is forced to obey the physical laws of the system. The calculation formula is as follows: in, and These are the electricity consumed by the compressor and the working fluid pump, respectively. The electricity generated by the turbine, , , and The heat loads are respectively the heat loads of the first evaporator, the second evaporator, the third evaporator, the first condenser, and the second condenser.

[0083] The Adam optimizer is used to update the parameters of the PINN model, and the weight coefficients are set. The optimal value was determined through cross-validation on the validation dataset. An early termination criterion (patience=30) was set to prevent overfitting; the model was considered optimized when there was no significant improvement on the validation set after 30 consecutive iterations and the physical constraint residuals were below a certain threshold. When the model converges, the coefficient of determination is used. The prediction accuracy of the PINN model is evaluated using the following formula: in, Let r be the predicted value of the r-th sample. For the r-th sample, for The average of the predicted values.

[0084] The closer it is to 1, the higher the accuracy of the model's predictions.

[0085] Step 32: Construct the target space based on the predicted results of effective energy efficiency, return on investment, and carbon dioxide equivalent emission reduction.

[0086] See also Figure 3 The non-dominated sorting genetic algorithm III is used to solve the multi-objective function, sorting the individuals in the solution set to generate the Pareto optimal front, thus obtaining the optimal parameter combination. For example... Figure 6 The diagram shows the detailed process of solving the non-dominated sorting genetic algorithm III.

[0087] NSGA-III (Non-dominated sorting genetic algorithm III) is an algorithm for multi-objective optimization. Its processing flow is as follows: First, initialize a population containing candidate solutions (individuals). Calculate the multi-objective function value for each individual (such as the values ​​of the energy efficiency objective function, return on investment objective function, and CO2 equivalent emission reduction objective function). Simultaneously, set uniformly distributed reference points in the multi-objective space (to ensure solution diversity). After generating the initial population, set the number of generations. Merge the parent and offspring populations into a temporary population. Then, use fast non-dominated sorting to prioritize multi-objectives (determined by the magnitude of the corresponding objective function values). The population is stratified (non-dominated solutions are ranked higher) based on the objective function value. Then, high-quality individuals are selected by considering the distance between each individual and the reference point. Individuals in the top dominant layer are selected first. If the size is insufficient, the population is supplemented from the current layer according to the distance from the reference point to form a new parent population. Subsequently, the new parent population is subjected to selection (selecting high-quality parents based on multi-objective performance), crossover (recombining decision variables), and mutation (randomly modifying variables) to generate offspring. The above cycle of fusion, sorting, selection, and genetic operations is repeated until the maximum number of generations is reached. Finally, the set of non-dominated solutions in the population (i.e., the Pareto optimal solution of the multi-objective problem) is output.

[0088] The solutions on the Pareto optimal front all take into account both effective energy efficiency. The optimal design schemes for ROI and CEER provide a scientific basis for the optimized operation and design of the MI-OVJCCHP system.

[0089] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0090] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A novel integrated combined cooling, heating and power system, characterized in that, include: ORC module, compression heat pump module, jet refrigeration module, heat exchanger and working fluid pump; The first working fluid inlet of the ORC module is used to input a first working fluid, which carries industrial waste heat; the first working fluid outlet of the ORC module is connected to the first inlet of the compression heat pump module, and the second working fluid outlet of the ORC module is connected to the second inlet of the compression heat pump module. The ORC module is used to generate electricity using the industrial waste heat and output saturated steam and waste liquid fluid. The outlet of the compression heat pump module is connected to the first inlet of the heat exchanger. The compression heat pump module uses the waste liquid fluid and the saturated steam to generate heat and output a second working fluid. The temperature of the first working fluid is greater than the temperature of the second working fluid. The first outlet of the heat exchanger is connected to the working fluid inlet of the jet refrigeration module, the working fluid outlet of the jet refrigeration module is connected to the inlet of the working fluid pump, the outlet of the working fluid pump is connected to the second inlet of the heat exchanger, and the second outlet of the heat exchanger is connected to the second working fluid inlet of the ORC module; the heat exchanger exchanges heat with the second working fluid and outputs a third working fluid, wherein the temperature of the third working fluid is lower than the temperature of the second working fluid, and the jet refrigeration module uses the third working fluid for refrigeration.

2. The novel integrated combined cooling, heating and power system according to claim 1, characterized in that, The ORC module specifically includes: a first evaporator and a turbine; The first inlet of the first evaporator is used to input the first working fluid; the second inlet of the first evaporator is connected to the second outlet of the heat exchanger; the first outlet of the first evaporator is connected to the inlet of the turbine; the outlet of the turbine is connected to the first inlet of the compression heat pump module. The first outlet of the first evaporator outputs saturated steam, and the second outlet of the first evaporator outputs waste liquid fluid. The turbine uses the saturated steam to generate electricity.

3. The novel integrated combined cooling, heating and power system according to claim 1, characterized in that, The compression heat pump module specifically includes: a second evaporator, a compressor, and a first condenser; The first inlet of the second evaporator is connected to the first working fluid outlet of the ORC module; the second inlet of the second evaporator is connected to the second working fluid outlet of the ORC module; the first outlet of the second evaporator is connected to the inlet of the compressor; the outlet of the compressor is connected to the inlet of the first condenser; and the outlet of the first condenser is connected to the first inlet of the heat exchanger. The second evaporator uses the waste liquid fluid to heat the saturated steam, and the first outlet of the second evaporator outputs the heated saturated steam. The compressor pressurizes the heated saturated steam and outputs the pressurized working fluid. The first condenser uses the pressurized working fluid for heating, and the outlet of the first condenser outputs the second working fluid.

4. The novel integrated combined cooling, heating and power system according to claim 1, characterized in that, The jet refrigeration module specifically includes: an ejector, a second condenser, valves, and a third evaporator; The first inlet of the ejector is connected to the first outlet of the heat exchanger; the second inlet of the ejector is connected to the outlet of the third evaporator, and the outlet of the ejector is connected to the inlet of the second condenser; the outlet of the second condenser, the inlet of the working fluid pump, and one end of the valve are connected; the other end of the valve is connected to the inlet of the third evaporator. The third working fluid is input from the first inlet of the ejector and serves as the ejector's priming fluid. The fourth working fluid is output from the outlet of the ejector. A portion of the fourth working fluid passes sequentially through the third evaporator and the valve to output a fifth working fluid. The second condenser uses the fifth working fluid for refrigeration.

5. A parameter optimization method based on a novel quality-integrated combined cooling, heating and power system, characterized in that, The parameter optimization method based on the novel quality-integrated cogeneration system includes: Obtain multiple sets of simulation data for the novel integrated cogeneration system according to any one of claims 1-4; the multiple sets of simulation data are obtained by simulating the recovery of industrial waste heat using the novel integrated cogeneration system under different combinations of operating parameter values; the simulation data includes operating parameter values; the operating parameters include the power generation parameters of the ORC module, the heat generation parameters of the compression heat pump module, the refrigeration parameters of the jet refrigeration module, and the outlet pressure of the working fluid pump; A multi-objective function is constructed with the objectives of maximizing the effective energy efficiency, return on investment, and carbon dioxide equivalent emission reduction of the new quality-integrated cogeneration system. Based on the aforementioned multiple sets of simulation data, a target space for a multi-objective function is constructed. Based on the target space, the non-dominated sorting genetic algorithm III is used to solve the multi-objective function to obtain the optimal parameter combination.

6. The parameter optimization method based on a novel quality-integrated cogeneration system according to claim 5, characterized in that, The acquisition of multiple sets of simulation data for the novel integrated combined cooling, heating and power system specifically includes: The comprehensive score of each type of working fluid is determined by using its power generation efficiency, environmental impact indicators, and safety indicators; among which, the environmental impact indicators include global warming potential and ozone depletion potential. The working fluid with the highest overall score was used as the input for the novel quality-integrated cogeneration system in the recovery simulation. Multiple sets of operating parameter values ​​were obtained during the industrial waste heat recovery simulation process.

7. The parameter optimization method for a novel quality-integrated combined cooling, heating and power system according to claim 5, characterized in that, The multi-objective function includes an effective energy efficiency objective function, an investment return rate objective function, and a carbon dioxide equivalent emission reduction objective function.

8. The parameter optimization method for a novel quality-integrated cogeneration system according to claim 5, characterized in that, Based on the aforementioned multiple sets of simulation data, a target space for a multi-objective function is constructed, specifically including: Based on the aforementioned sets of simulation data, the trained PINN model is used to predict effective energy efficiency, return on investment, and carbon dioxide equivalent emission reduction. The target space is constructed based on the predicted results of effective energy efficiency, return on investment, and CO2 equivalent emission reduction.

9. The parameter optimization method based on a novel quality-integrated cogeneration system according to claim 8, characterized in that, The loss function used in the training of the PINN model is a composite loss function.

10. The parameter optimization method for a novel quality-integrated cogeneration system according to claim 9, characterized in that, The expression for the composite loss function is: ； in, For composite loss function, For weighting coefficients, For the mean squared error loss term, This is the physical loss item.

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