Multi-source typical organic solid waste co-pyrolysis resource simulation method

Abstract

The application discloses a kind of multi-source typical organic solid waste synergic pyrolysis resource simulation methods, including system simulation flow chart establishment, component setting and physical property method selection, parameter input and simulation operation, analysis tool application, model verification five steps, for analyzing agricultural and forestry source, industrial source, city source multiple complex source typical organic solid waste Synergic proportion, pyrolysis temperature, the influence of the moisture content of raw material after drying on biomass charcoal yield, carbon dioxide production, pollution gas production, optimizes the multi-source organic solid waste synergic pyrolysis process, reduces resource input, improves the utilization efficiency of resources, improves solid waste resource efficiency, increases system economic benefit.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of solid waste pyrolysis, and particularly relates to a multi-source typical organic solid waste synergistic pyrolysis resource simulation method. BACKGROUND

[0002] Organic solid waste contains rich biomass energy, which is one of the most promising substitutes for traditional fossil energy. Effective resource utilization of organic solid waste can greatly reduce carbon emissions. A large number of studies have shown that biomass energy has outstanding emission reduction effect in power generation, ethanol, aviation oil, diesel, new solid fuel and biogas production. Pine, as a kind of biomass resource, has good pyrolysis effect. Part of the pine is dead and needs to be treated due to insect infestation every year. Chinese medicine residue has good pyrolysis potential, and has the characteristics of high calorific value and high volatile content. Municipal sludge is a representative solid waste in urban solid waste, and has good universality. The sludge has good economy for pyrolysis.

[0003] The history of pyrolysis process technology has been 200 years. The research on this technology is relatively mature, but there are still some problems to be optimized. For example, most of the pyrolysis equipment is large in scale, high in economic cost and high in research threshold. Therefore, software simulation can be used to optimize the pyrolysis process. Common simulation software mainly includes OpenFOAM, GMD-Reax and Aspen plus. Among them, Aspen plus is widely used, simple to operate and has a perfect and rich database. The chemical process simulation software Aspen plus can realize the prediction simulation of the pyrolysis process. Through model operation and analysis, an optimization scheme can be provided for the pyrolysis process, the research difficulty is reduced, and the economic cost is reduced. The predecessors mainly use Aspen plus software to simulate the pyrolysis and gasification process of organic solid waste. Based on the properties of organic solid waste and the research purpose, different reactor modules and property methods in the software are selected to build the model. By changing different parameters of the process, the process is optimized, and the yield of the target product is improved. However, there are few studies on the pyrolysis and carbonization of organic solid waste. Due to the complexity of the input components and reaction conditions of multi-source organic solid waste synergistic pyrolysis and the challenge of modeling and simulation optimization technology, there are few studies at present. Commonly, the research is limited to a single pyrolysis object. SUMMARY

[0004] In order to solve the limitations and defects of the prior art, the present application provides a multi-source typical organic solid waste synergistic pyrolysis resource simulation method, which comprises the following steps:

[0005] Step S1, selecting corresponding unit operation modules according to the actual pyrolysis process, device and operation mechanism of the organic solid waste, connecting the modules by means of material and heat flow, taking the module connection as the relationship between material and heat or work in the process, and establishing a complete system simulation flowchart;

[0006] Step S2, according to the input and output substances of the process, input the corresponding chemical component name, the simulation system automatically retrieves the property data of the substance from the database, and the property method selection is to select the method for calculating the pyrolysis process and the equilibrium reaction;

[0007] Step S3, according to the reaction conditions of the actual process and the operation requirements of the equipment, the parameters in the corresponding unit operation module are set, including the reactor temperature, pressure, material and energy flow of different streams, after the input of the parameters is completed, the simulation is run;

[0008] Step S4, according to the simulation of different needs, add corresponding model analysis tools on the basis of the model that has been established, the model analysis tools include calculator tools, sensitivity analysis tools and working condition analysis tools, the model analysis tools are used for optimization research on the simulated process;

[0009] Step S5, set the input feed property data of the model and the reactor operation parameters of different modules to be consistent with the actual production parameters, compare the simulation results with the actual production results to verify the accuracy of the model;

[0010] The simulation method uses modules including drying module, pyrolysis module and combustion module;

[0011] The drying module is used to simulate the physical change process of the raw material during the drying process in the dryer;

[0012] The pyrolysis module is used to simulate the process of pyrolysis of the dried raw material into biomass charcoal and pyrolysis volatile matter under specific conditions in the pyrolysis furnace;

[0013] The combustion module is used to simulate the process of combustion of pyrolysis volatile matter in the hot blast furnace to produce high-temperature flue gas to heat the pyrolysis furnace.

[0014] Optionally, the step S1 comprises:

[0015] According to the simplified process flow of biomass charcoal production by pyrolysis, the drying process is simulated by using RStoic reactor;

[0016] The substance raw material is decomposed into elements and inert components ash by using RYield reactor according to the elemental analysis data;

[0017] The decomposed elements are input into the RGibbs reactor for pyrolysis recombination, and the pyrolysis volatile matter and biomass charcoal are obtained after recombination;

[0018] The produced pyrolysis volatile is separated into two phases by the SSplit splitter, and then sent to the combustion module as fuel of the combustion device hot blast furnace, air is introduced for combustion support, the combustion module selects the simulation of the RGibbs reactor for combustion reaction, and the high-temperature flue gas generated after combustion is sent to the drying module and the pyrolysis module through the heat exchanger.

[0019] Optionally, the step S2 comprises:

[0020] According to the industrial and elemental analysis of pine, traditional Chinese medicine residues and municipal source sludge treated by different processes, the input components are set;

[0021] The RK-SOAVE state equation is selected as the basic property method of the model;

[0022] According to the solid raw materials and the inert component ash, the global flow type MCINCPSD is selected, the enthalpy and density calculation methods HCOALGEN and DCOALIGT are selected as the enthalpy and density calculation methods of the raw materials according to the energy calculation of the system involving the heat calculation of the materials.

[0023] Optionally, in the step S3, the parameters include: the raw material feeding speed is 1000 kg / h, the air temperature is 20-30℃, the drying reactor temperature is 120-140℃, the pyrolysis temperature is 400-600℃, and the pressure in the process is 1.01-1.02 bar.

[0024] Optionally, the step S4 comprises:

[0025] Different substances and their actual water conversion rates are identified by the calculator module and the RStoic reactor to simulate the entire drying process;

[0026] The specific decomposition yield of biomass is calculated by the calculator module and the RYield reactor.

[0027] Optionally, the step S5 comprises:

[0028] The pyrolysis product yield is calculated, and the calculation formula of the pyrolysis product yield is as follows:

[0029]

[0030]

[0031]

[0032] Y CHAR , Y OIL , Y GAS are the yields of the pyrolysis three-phase products, respectively, W CHAR , WOIL , W GAS Respectively, the mass flow of pyrolysis three-phase product, W0 is the mass flow of pyrolysis feed, the mass flow is the mass flow of feed after drying, A is the proportion of ash in the feed in the dry basis.

[0033] Optionally, the simulation method forms a synergistic pyrolysis model for synergistic pyrolysis of the pine wood, the traditional Chinese medicine residue and the municipal source sludge of different treatment processes, and also for analyzing the influence of synergistic ratio, pyrolysis temperature and moisture content of dried raw material on the pyrolysis result.

[0034] The pyrolysis result includes biomass charcoal yield, CO2 yield and pollution gas yield, and the pollution gas includes carbon monoxide, nitrogen oxide and sulfur oxide.

[0035] Optionally, the condition parameters of the simulation method include: selecting 550 DEG C of pyrolysis temperature and 10% of moisture content of feed after drying as basic parameter conditions, mixing the traditional Chinese medicine residue and the municipal source sludge of different treatment processes into the pine wood for pyrolysis, the proportion of the traditional Chinese medicine residue and the municipal source sludge of different treatment processes is increased from 0% to 100% with a preset step, and the influence of the synergistic ratio on the pyrolysis result is studied.

[0036] Optionally, the condition parameters of the simulation method also include: selecting 400 DEG C to 600 DEG C of pyrolysis temperature according to actual production conditions, and increasing with a preset step, to study the influence of the pyrolysis temperature on the pyrolysis result.

[0037] Optionally, the condition parameters of the simulation method also include: selecting 2% to 20% of moisture content of dried raw material according to actual production conditions, and increasing with a preset step, to study the influence of the moisture content of dried raw material on the pyrolysis result.

[0038] The present application has the following beneficial effects:

[0039] The present application discloses a multi-source typical organic solid waste synergistic pyrolysis resource simulation method, which comprises five steps of system simulation flow chart establishment, component setting, physical property method selection, parameter input and simulation running, analysis tool application and model verification, and is used for analyzing the influence of synergistic ratio, pyrolysis temperature and moisture content of dried raw material on biomass charcoal yield, carbon dioxide yield and pollution gas yield of typical organic solid waste of various complex sources such as agricultural and forestry sources, industrial sources and municipal sources, optimizing the multi-source organic solid waste synergistic pyrolysis process, reducing resource input, improving resource utilization efficiency, improving solid waste resource efficiency and increasing system economic benefits. BRIEF DESCRIPTION OF DRAWINGS

[0040] Figure 1This is a schematic diagram of the modules used in the multi-source typical organic solid waste synergistic pyrolysis resource utilization simulation method provided in Embodiment 1 of the present invention.

[0041] Figure 2 This is a flowchart of a simulated pyrolysis char production process according to Embodiment 1 of the present invention.

[0042] Figures 3a-3c This is a schematic diagram of the influence curve of the proportion of two sources working together on the pyrolysis results provided in Embodiment 1 of the present invention.

[0043] Figures 4a-4b This is a schematic diagram showing the influence of the proportion of three sources working together on the pyrolysis results, provided in Embodiment 1 of the present invention.

[0044] Figures 5a-5c This is a schematic diagram of the effect of different pyrolysis temperatures on the pyrolysis results provided in Embodiment 2 of the present invention.

[0045] Figures 6a-6c This is a schematic diagram of the effect of the moisture content of the raw material on the pyrolysis results after drying with different ratios of the two-source synergistic process, as provided in Embodiment 3 of the present invention. Detailed Implementation

[0046] To enable those skilled in the art to better understand the technical solution of the present invention, the following detailed description of the multi-source typical organic solid waste synergistic pyrolysis resource utilization simulation method provided by the present invention is given in conjunction with the accompanying drawings.

[0047] Example 1

[0048] This embodiment discloses a simulation method for the synergistic pyrolysis resource utilization of typical organic solid waste from multiple sources. The method comprises five steps: establishing a system simulation flowchart, setting components and selecting physical property methods, inputting parameters and running the simulation, applying analytical tools, and validating the model. It can be used to analyze the impact of factors such as the synergistic ratio, pyrolysis temperature, and moisture content of the raw materials after drying on the biochar yield, CO2 production, and the production of pollutant gases (CO, nitrogen oxides, and sulfur oxides) of typical organic solid waste from various complex sources, including agricultural and forestry sources (such as waste pine wood), industrial sources (such as medicinal herb residue), and urban sources (such as sludge from different treatment processes). This method solves problems in existing technologies such as modeling and simulating the process flow of multi-source synergistic pyrolysis resource utilization of organic solid waste based on actual production, product generation control, multi-scenario material flow analysis, and energy efficiency sensitivity analysis of the synergistic pyrolysis system. It provides valuable guidance for optimizing the synergistic pyrolysis process of multi-source organic solid waste, reducing resource input, improving resource utilization efficiency, enhancing solid waste resource utilization efficiency, and increasing system economic benefits.

[0049] The embodiment aims to provide a simulation method for organic solid waste synergistic pyrolysis, which can analyze the influence of factors such as the synergistic proportion of multiple sources of typical organic solid waste, pyrolysis temperature, and moisture content of raw materials after drying, and solve the problems in the prior art such as modeling simulation of the organic solid waste multi-source synergistic pyrolysis process based on actual production, product generation control, multi-scenario setting material flow analysis, and energy efficiency sensitivity analysis of the synergistic pyrolysis system, which has good guiding significance for optimizing the multi-source organic solid waste pyrolysis process, reducing resource investment, improving the utilization efficiency of resources, and improving the solid waste resource utilization.

[0050] The simulation method for multi-source typical organic solid waste synergistic pyrolysis resource provided by the embodiment uses the following modules:

[0051] (1) a drying module, used for simulating the physical change process occurring in the drying process of raw materials in a drying machine;

[0052] (2) a pyrolysis module, used for simulating the process of pyrolysis of the dried raw materials into biomass charcoal and pyrolysis volatile matter under specific conditions in a pyrolysis furnace;

[0053] (3) a combustion module, used for simulating the process of combustion of the pyrolysis volatile matter in a hot blast furnace to generate high-temperature flue gas to heat the pyrolysis furnace.

[0054] The simulation method for multi-source typical organic solid waste synergistic pyrolysis resource provided by the embodiment includes the following steps:

[0055] (1) system simulation flowchart establishment, which is to select the corresponding unit operation module in Aspen plus according to the actual pyrolysis process of waste pine wood, devices (drying machine, pyrolysis furnace, hot blast furnace, etc.), and operation mechanism (Gibbs free energy, mass and energy conservation law, etc.), connect the modules by means of material and heat flow in the software, represent the relationship between material and heat or work in the process, and establish a complete system simulation flowchart;

[0056] (2) component setting and property method selection, which is to input the chemical component name corresponding to the input (pine wood and synergistic substances, air) and output (biomass charcoal, CO2, CO, nitrogen oxides, sulfur oxides, etc.) substances of the process, the system can automatically retrieve the property data of the substances from the database, and select the method for calculating the pyrolysis process and equilibrium reaction by using the Aspen plus software;

[0057] (3) parameter input and simulation running, which is to set the parameters in the module according to the reaction conditions and equipment operation requirements of the actual process, input the parameters such as reactor temperature, pressure, and material and energy flow of different streams, and complete the parameter input, and then run the simulation;

[0058] (4) Analysis tool application, the analysis tool application is according to simulation different demand, adds multiple model analysis tools, such as calculator tool, sensitivity analysis and operating condition analysis on the basis of the model that has been established, to optimize the simulated process.

[0059] Further, in the step (1), the system simulation flow chart is established according to the waste pine pyrolysis process simplified flow, the collected waste pine is sent to the dryer for drying treatment, the heat required for drying treatment is supplied by the medium-temperature flue gas of the pyrolysis furnace, the water vaporized from the raw material is mixed in the flue gas and discharged, the dried raw material is sent to the pyrolysis furnace for thermal decomposition reaction, the heat required for pyrolysis is provided by the high-temperature flue gas of the hot blast furnace, the pyrolysis volatile generated after thermal decomposition of the raw material is used as fuel into the hot blast furnace, and the generated solid biomass charcoal is uniformly collected to build a simulation flow chart; the drying process is simulated by using RStoic reactor (DRYER) in Aspen plus; the decomposed elements are input into RGibbs reactor (PYRO) for pyrolysis recombination, and the pyrolysis volatile and biomass charcoal are obtained after recombination; the generated pyrolysis volatile is sent to the combustion module after two-phase separation by SSplit splitter (SPLIT) to serve as fuel for the hot blast furnace of the combustion device, and air is introduced for combustion support, the RGibbs reactor (HOTWIND) is selected for simulation of the combustion reaction of the combustion module, and the high-temperature flue gas (FLUE-GAS) generated after combustion is sent to the other two modules by the heat exchanger in Aspen plus.

[0060] Further, in the step (2), the component setting and property method selection are set according to the industrial and elemental analysis of the waste pine, the traditional Chinese medicine residue and the municipal source sludge with different treatment processes, and the input components are set, mainly including various elemental components and different gas-liquid-solid product components, such as C, H2, CH4, CO2, C6H6O, etc.; RK-SOAVE is selected as the basic property method of the model; due to the existence of unconventional solid raw materials and inert component ash, the global flow type needs to be selected as MCINCPSD, and the heat calculation of the material needs to be involved in the energy calculation of the system, and the HCOALGEN and DCOALIGT methods in the software are selected as the enthalpy and density calculation methods of the raw material.

[0061] Further, in the step (3), the parameter input is that the raw material feeding speed is 1000 kg / h, the air temperature is set to 20-30℃, the drying reactor temperature is set to 120-140℃, the pyrolysis temperature is set to 400-600℃, and the pressure in the flow is set to 1.01-1.02 bar.

[0062] Further, in the step (4), the actual production data is set to use the calculator module in Aspen plus to embed Fortran statements in the RStoic reactor (DRYER) to identify different substances and their actual water conversion rate, so as to realize the simulation of the whole drying process, and the input reaction equation and calculator module statement are as follows:

[0063] Biomass (wet)→ Biomass (dry) + ΦH2O

[0064] CONV = (H2OIN-H2OOUT) / (100-H2OOUT)

[0065] A Fortran statement is embedded in the RYield reactor (DECOMP) using the calculator module to calculate the specific decomposition yield of biomass, and the Fortran statement is as follows:

[0066] FACT = (100-WATER) / 100

[0067] ASH = ULT(1) / 100*FACT

[0068] CARB = ULT(2) / 100*FACT

[0069] H2 = ULT(3) / 100*FACT

[0070] N2 = ULT(4) / 100*FACT

[0071] SULF = ULT(6) / 100*FACT

[0072] O2 = ULT(7) / 100*FACT

[0073] Wherein, FACT represents the dry basis content of the raw material, and ULT(1) to ULT(7) represent the content of the corresponding raw material element analysis.

[0074] Further, in the step (5), the model verification is calculated according to the following formula: wherein Y CHAR , Y OIL , Y GAS are the yields of the three-phase pyrolysis products (%), W CHAR , W OIL , W GAS are the mass flow rates of the three-phase pyrolysis products (kg / h), W0 is the mass flow rate of the pyrolysis feed (the mass flow rate of the dried feed) (kg / h), and A is the proportion of ash in the feed in the dry basis; the calculation results are compared with the actual yield for verification.

[0075]

[0076]

[0077]

[0078] Further, the built model can be used as a simulation of the co-pyrolysis of biomass waste pine and traditional Chinese medicine residues and municipal source sludge with different treatment processes, and the effects of the co-proportion, pyrolysis temperature, moisture content of the dried raw materials and other factors on the biomass char yield, CO2 yield and pollution gas (CO, nitrogen oxides and sulfur oxides) yield can be analyzed.

[0079] Further, the effects of the co-proportion on the pyrolysis results are analyzed, and the condition parameters of the simulation are set as the pyrolysis temperature of 550 DEG C and the moisture content of the dried raw materials of 10% as the basic parameter conditions, the traditional Chinese medicine residues and municipal source sludge with different treatment processes are mixed into the agricultural and forestry source waste pine for pyrolysis, the proportion is increased by a certain step from 0% to 100%, and the effects of the co-proportion on the pyrolysis results can be studied.

[0080] Further, the effects of the pyrolysis temperature on the pyrolysis results are analyzed, and the condition parameters of the simulation are set as the pyrolysis temperature of 400 DEG C to 600 DEG C according to the actual production situation, and the pyrolysis temperature is increased by a certain step, and the effects of the pyrolysis temperature on the pyrolysis results can be studied.

[0081] Further, the effects of the moisture content of the dried raw materials on the pyrolysis results are analyzed, and the condition parameters of the simulation are set as the moisture content of the dried raw materials in the range of 2% to 20% according to the actual production situation, and the moisture content of the dried raw materials is increased by a certain step, and the effects of the moisture content of the dried raw materials on the pyrolysis results can be studied.

[0082] Figure 1 The module schematic diagram used in the multi-source typical organic solid waste co-pyrolysis resource simulation method provided by the embodiment one of the present application. Figure 2 The pyrolysis carbonization process flowchart simulated by the embodiment one of the present application, wherein DRYER is the RStoic reactor, DECOMP is the RYield reactor, PYRO is the RGibbs reactor, SPLIT is the SSplit splitter, and HOTWIND is the RGibbs reactor. Figures 3a-3c The influence curve schematic diagram of the two-source co-proportion on the pyrolysis results provided by the embodiment one of the present application. Figures 4a-4bThis is a schematic diagram illustrating the influence of the synergistic ratio of the three sources on the pyrolysis results provided in Embodiment 1 of the present invention. This embodiment simulates the synergistic pyrolysis process of agricultural and forestry biomass (waste pine wood), industrial medicinal herb residue, and urban sludge from different treatment processes. It analyzes the influence of the synergistic ratio on biochar yield, CO2 production, and the production of pollutant gases (CO, nitrogen oxides, and sulfur oxides). The process consists of four steps: establishing the system simulation flowchart, setting components and selecting physical property methods, parameter input and simulation operation, and result analysis.

[0083] (1) System simulation flow chart establishment: Based on the simplified process of biomass pyrolysis, models were built by selecting RStoic reactor (DRYER), RYield reactor (DECOMP), RGibbs reactor (PYRO), SSplit splitter (SPLIT), and RGibbs reactor (HOTWIND).

[0084] (2) Component setting and property method selection: The components set are mainly various elemental substances and different gas-liquid-solid product components, such as C, H2, CH4, CO2, C6H6O, etc.; RK-SOAVE is selected as the basic property method of the model; due to the presence of unconventional solid raw materials and inert ash components, the global flow type needs to be selected as MCINCPSD. When performing energy calculations on the system, it is necessary to involve the heat calculation of the materials. The HCOALGEN and DCOALIGT methods in the software are selected as the enthalpy and density calculation methods of the raw materials; biomass, Chinese medicine residue, and sludge of the co-pyrolysis substances are defined according to Table 1 and Table 2.

[0085] Table 1 Industrial Analysis of Synergistic Pyrolysis Substances

[0086]

[0087] Table 2 Elemental analysis of substances involved in synergistic pyrolysis

[0088]

[0089] (3) Parameter input and simulation operation: The raw material feed rate is 1000 kg / h, the air temperature is set to 20 to 30℃, the drying reactor temperature is set to 120 to 140℃, the pyrolysis temperature is set to 400 to 600℃, and the pressure in the process is set to 1.01 to 1.02 bar; Chinese medicine residue and urban sludge from different treatment processes are added to agricultural and forestry pine wood for pyrolysis, with the proportion increasing from 0% to 100% in a certain step size, and the simulation operation is carried out.

[0090] (4) Results Analysis: Through the output of the simulation results, the changes in the proportions of *Sargentodoxa cuneata*, *Alisma plantago-aquatica*, S sludge, P sludge, and F sludge, as well as the biochar yield, CO2 emissions, and pollutant gas emissions in the pyrolysis products, are shown below. Figures 3a-3c、 Figures 4a-4b As shown in the pyrolysis of three-source organic solid waste, the results are optimal when the ratio of pine wood, sargentia and PAM sludge is 5:3:2. It can effectively reduce 20.0% CO2 emissions, but will reduce 1.5% of the pyrolysis carbon yield, and increase 5.6% of the pollution gas emissions. The results can be used to predict the actual pyrolysis, and can play a certain guiding role for the actual operation.

[0091] In this embodiment, the chemical process simulation software Aspen plus is used for modeling. By comparing and optimizing, the RStoic reactor (DRYER) is used to simulate the drying process of raw materials, the RYield reactor (DECOMP) and the RGibbs reactor (PYRO) are used to simulate the pyrolysis volatiles and biomass char, the SSplit splitter (SPLIT) is used to simulate the two-phase separation of the generated pyrolysis volatiles and biomass char, the RGibbs reactor (HOTWIND) is used to simulate the combustion reaction of the separated pyrolysis volatiles under the combustion of air, the heat exchanger is used to simulate the heat transfer process of the high-temperature flue gas (FLUE-GAS) generated after combustion to other two modules, and the advantages of various existing models are combined to realize the prediction and simulation of the multi-source typical organic solid waste co-pyrolysis resource process.

[0092] The embodiment provides a multi-source organic solid waste co-pyrolysis simulation method which can analyze influencing factors such as co-pyrolysis ratio, pyrolysis temperature and water content of raw materials after drying. The method can simulate the co-pyrolysis process of various complex source typical organic solid waste such as agricultural and forestry source biomass (waste pine wood), industrial source traditional Chinese medicine residue and municipal source sludge treated by different processes, solves the problems of modeling and simulation of co-pyrolysis process of multi-source organic solid waste under unique conditions, product generation control, multi-scene setting material flow analysis, co-pyrolysis system energy efficiency sensitivity analysis and other problems in the prior art, and has good guiding significance for optimizing multi-source organic solid waste pyrolysis process, reducing resource investment, improving resource utilization efficiency, improving solid waste resource utilization and increasing system economic benefits.

[0093] This embodiment models the actual pyrolysis process of an enterprise, selecting waste pine wood from agricultural and forestry sources as raw material for pyrolysis simulation. The input feed properties and reactor operating parameters for different modules (feed rate of 1000 kg / h, air temperature of 20 to 30°C, drying reactor temperature of 120 to 140°C, pyrolysis temperature of 500 to 700°C, and pressure in the process of 1.01 to 1.02 bar) are set to be consistent with the parameters of the pine wood pyrolysis experiment. After the model runs and the results are compared with the experimental results, it is found that the simulation results are not much different from the experimental results between 500 and 700°C, and the overlap is better at around 600°C. Therefore, the model established in this embodiment is relatively close to the actual pyrolysis process and can be used for subsequent simulation of the actual production process of the enterprise's pyrolysis system, and provide a certain reference for its system optimization.

[0094] Example 2

[0095] Figures 5a-5c This is a schematic diagram of the effect curves of different pyrolysis temperatures on the pyrolysis results provided in Embodiment 2 of the present invention. This embodiment repeats Embodiment 1 with the same steps, except that in step (3) of this embodiment, the proportion of *Sargentodoxa cuneata* is selected as 0-5%, 15-20%, 25-30%, 35-40%, 45-50%, and 55-60%, and the temperature range is selected as 400-600℃ with a step size of 20℃ based on actual research to study the effect of pyrolysis temperature on the process. The results are as follows: Figures 5a-5c As shown, under different co-production ratios, the biochar yield decreases slightly with the increase of pyrolysis temperature, CO2 emissions increase slightly, but pollutant gases decrease accordingly; when the co-production ratio of *Sargentodoxa cuneata* is high, the biochar yield decreases significantly with the increase of pyrolysis temperature, and there may be a phenomenon of incomplete combustion leading to a significant increase in pollutant gases.

[0096] Currently, there is no established model for the pyrolysis of organic solid waste. Research mainly relies on existing pyrolysis principles and generalizes actual processes to construct models. Existing Aspen Plus simulations of organic solid waste pyrolysis primarily focus on the rapid pyrolysis of bio-oil and the biomass gasification process, rarely conducting comprehensive simulations and analyses of the entire process of biochar production and flue gas flow. This embodiment utilizes the chemical process simulation software Aspen Plus for modeling. Through comparison and selection, the RStoic reactor (DRYER) is preferred to simulate the raw material drying process. The RYield reactor (DECOMP) and RGibbs reactor (PYRO) are used to simulate the generation of pyrolysis volatiles and biochar. The SSplit splitter (SPLIT) is used to simulate the two-phase separation of the generated pyrolysis volatiles and biochar. The RGibbs reactor (HOTWIND) is used to simulate the combustion reaction of the separated pyrolysis volatiles under air-assisted combustion. The heat exchanger is used to simulate the heat exchange process of the high-temperature flue gas (FLUE-GAS) generated after combustion being transported to the other two modules. Through engineering data verification, the prediction of the biochar generation process behavior and the entire process of flue gas generation, combustion, heating, and emission is realized.

[0097] This embodiment provides a typical organic solid waste co-pyrolysis simulation method that can analyze the influencing factors such as the co-proportion of multi-source organic solid waste, pyrolysis temperature, and moisture content of raw materials after drying. By changing process parameters, the method analyzes the impact on results, solving problems in existing technologies such as process flow modeling and simulation of multi-source organic solid waste co-pyrolysis under unique conditions, product generation control, multi-scenario material flow analysis, and energy efficiency sensitivity analysis of co-pyrolysis systems. The research results have significant guiding value for optimizing multi-source organic solid waste pyrolysis processes, reducing resource input, improving resource utilization efficiency, enhancing solid waste resource recovery, and increasing system economic benefits.

[0098] Example 3

[0099] Figures 6a-6c This is a schematic diagram illustrating the effect of the moisture content of the raw material after drying with different proportions in the dual-source synergistic process on the pyrolysis results, provided in Embodiment 3 of the present invention. This embodiment repeats Embodiment 1 with the same steps, except that in the parameters input in step (3) of this embodiment, the proportion of *Sargentodoxa cuneata* is selected as 0 to 5%, 15 to 20%, 25 to 30%, 35 to 40%, 45 to 50%, and 55 to 60%, respectively. The moisture content of the dried raw material varies between 2% and 20%, with a step size of 2%, to study the effect of moisture content on the process. The results are as follows... Figures 6a-6cAs shown, when the raw materials have low moisture content and high dryness before entering the pyrolysis module, the yield of pyrolyzed biochar will increase, and the impact on pollutant gas emissions will be small while reducing CO2 emissions. When the dryness is insufficient and the moisture content is high, adding *Sargentodoxa cuneata* for synergistic pyrolysis can effectively reduce the rate of biochar loss. However, under synergistic conditions, incomplete combustion is more likely to occur, leading to a significant increase in pollutant gases. Therefore, attention should be paid to increasing the supply of combustion air.

[0100] Currently, organic solid waste pyrolysis faces challenges such as a single source, a relatively fixed operating mode, and an inability to adapt to changes in the source. This embodiment, based on actual engineering pyrolysis processes, utilizes the chemical process simulation software Aspen Plus for modeling. It can simulate typical organic solid waste pyrolysis processes from complex sources (agricultural and forestry, industrial, and urban sources) in multiple scenarios, accurately predict the three-state pyrolysis yields, and simultaneously achieve the simulation, analysis, and controllability of products (biochar and pollutant gases). By combining the advantages of existing models, it realizes the prediction of multi-source typical organic solid waste synergistic pyrolysis resource utilization processes, enriches existing research on single-source organic solid waste pyrolysis carbonization, and has good engineering guidance significance for improving the resource utilization of organic solid waste.

[0101] The multi-source typical organic solid waste co-pyrolysis resource utilization simulation method provided in this embodiment includes five steps: system simulation flowchart establishment, component setting and property method selection, parameter input and simulation operation, analysis tool application, and model verification. It is used to analyze the effects of the co-proportion, pyrolysis temperature, and moisture content of raw materials after drying on biochar yield, carbon dioxide production, and pollutant gas production of typical organic solid waste from multiple complex sources such as agricultural and forestry, industrial, and urban sources. It optimizes the multi-source organic solid waste co-pyrolysis process, reduces resource input, improves resource utilization efficiency, improves solid waste resource utilization efficiency, and increases the system's economic benefits.

[0102] It is understood that the above embodiments are merely exemplary implementations used to illustrate the principles of the present invention, and the present invention is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A multi-source typical organic solid waste co-pyrolysis resource simulation method, characterized in that, The method comprises the following steps: Step S1, selecting corresponding unit operation modules according to the actual pyrolysis process, device and operation mechanism of organic solid waste, connecting the modules by means of material and heat flow, establishing a complete system simulation flowchart by means of module connection representing the relationship between material and heat or work in the process; Step S2, inputting corresponding chemical component names according to the input and output substances of the process, and automatically retrieving the physical property data of the substances from the database by the simulation system, wherein the physical property method is selected as a method for calculating the pyrolysis process and the equilibrium reaction; Step S3, setting parameters in the corresponding unit operation modules according to the reaction conditions and equipment operation requirements of the actual process, wherein the parameters include reactor temperature, pressure, material and energy flow of different streams, and after the input of the parameters is completed, simulation is performed; Step S4, adding corresponding model analysis tools to the model established in the foregoing step according to different simulation requirements, wherein the model analysis tools include calculator tools, sensitivity analysis tools and working condition analysis tools, and the model analysis tools are used for optimization research on the simulated process; Step S5, setting the input feed property data of the model and the reactor operation parameters of different modules to be consistent with the actual production parameters, comparing the simulation results with the actual production results, and verifying the accuracy of the model; The simulation method uses modules including a drying module, a pyrolysis module and a combustion module; The drying module is used for simulating the physical change process of the raw material in the drying process in the dryer; The pyrolysis module is used for simulating the process of pyrolyzing the dried raw material into biomass charcoal and pyrolysis volatile matter under specific conditions in the pyrolysis furnace; The combustion module is used for simulating the process of burning the pyrolysis volatile matter in the hot blast furnace to generate high-temperature flue gas for heating the pyrolysis furnace; The step S5 comprises: Calculating the pyrolysis product yield, and the calculation formula of the pyrolysis product yield is as follows: ， ， ， wherein Y CHAR , Y OIL、 Y GAS are the yields of the pyrolysis three-phase products, respectively, W CHAR , W OIL、 W GAS are the mass flow rates of the pyrolysis three-phase products, respectively, W0 is the mass flow rate of the pyrolysis feed, which is the mass flow rate of the feed after drying, and A is the proportion of ash in the feed in the dry state.

2. The multi-source typical organic solid waste synergistic pyrolysis resource simulation method according to claim 1, characterized in that, The step S1 comprises: According to the simplified process of biomass charcoal production by pyrolysis, the drying process is simulated by using an RStoic reactor; Elemental analysis data is used to decompose the material into elements and inert components by using an RYield reactor; The decomposed elements are input into an RGibbs reactor for pyrolysis recombination, and pyrolysis volatile matter and biomass charcoal are obtained after recombination; The generated pyrolysis volatile matter is sent to the combustion module as fuel of the hot blast furnace of the combustion device after two-phase separation by an SSplit splitter, and air is input for combustion support, the combustion module selects the RGibbs reactor for simulation of the combustion reaction, and the high-temperature flue gas generated after combustion is sent to the drying module and the pyrolysis module through a heat exchanger.

3. The multi-source typical organic solid waste synergistic pyrolysis resource simulation method according to claim 2, characterized in that, The step S2 comprises: According to the industrial and elemental analysis of pine, traditional Chinese medicine residues and municipal sludge treated by different processes, input components are set; RK-SOAVE state equation is selected as the basic physical property method of the model. According to the solid raw material and the ash of the inert component, the global flow type is selected as MCINCPSD, and according to the energy calculation of the system, the enthalpy and density calculation methods of the raw material are selected as HCOALGEN and DCOALIGT methods.

4. The multi-source typical organic solid waste synergistic pyrolysis resource simulation method according to claim 3, characterized in that, In the step S3, the parameters include: the raw material feeding speed is 1000 kg / h, the air temperature is 20-30 ℃, the drying reactor temperature is 120-140 ℃, the pyrolysis temperature is 400-600 ℃, and the pressure in the process is 1.01-1.02 bar.

5. The multi-source typical organic solid waste synergistic pyrolysis resource simulation method according to claim 4, characterized in that, The step S4 includes: Different substances and their actual water conversion rates are identified by using a calculator module and a RStoic reactor to simulate the entire drying process; The specific decomposition yield of biomass is calculated by using the calculator module and the RYield reactor.

6. The multi-source typical organic solid waste synergistic pyrolysis resource simulation method according to claim 5, characterized in that, The simulation method forms a co-pyrolysis model for co-pyrolysis of the pine wood, the traditional Chinese medicine residue and the municipal source sludge treated by different processes, and is also used for analyzing the influence of the co-proportion, pyrolysis temperature and water content of the raw material after drying on the pyrolysis results. The pyrolysis results include biomass char yield, CO2 yield and pollution gas yield, and the pollution gas includes carbon monoxide, nitrogen oxide and sulfur oxide.

7. The multi-source typical organic solid waste synergistic pyrolysis resource simulation method according to claim 6, characterized in that, The condition parameters of the simulation method include: selecting 550 ℃ as the pyrolysis temperature and 10% as the water content of the raw material after drying as the basic parameter conditions, mixing the traditional Chinese medicine residue and the municipal source sludge treated by different processes into the pine wood for pyrolysis, and increasing the proportion of the traditional Chinese medicine residue and the municipal source sludge treated by different processes from 0% to 100% at a preset step to study the influence of the co-proportion on the pyrolysis results.

8. The multi-source typical organic solid waste synergistic pyrolysis resource simulation method according to claim 7, characterized in that, The condition parameters of the simulation method also include: selecting 400-600 ℃ as the pyrolysis temperature according to the actual production situation and increasing it at a preset step to study the influence of the pyrolysis temperature on the pyrolysis results.

9. The multi-source typical organic solid waste synergistic pyrolysis resource simulation method according to claim 8, characterized in that, The condition parameters of the simulation method also include: selecting 2-20% as the water content of the raw material after drying according to the actual production situation and increasing it at a preset step to study the influence of the water content of the raw material after drying on the pyrolysis results.

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