A method for optimizing process parameters of a biomass thermal conversion power generation

Abstract

The present application belongs to the technical field of biomass thermal conversion power generation, and discloses a biomass thermal conversion power generation process parameter optimization method. The optimization method is: a process model is established by using a process simulation software; process parameter data of the disclosed biomass thermal conversion power generation is obtained to establish a data set; a biomass and its corresponding process parameter set are selected, and a thermal conversion power generation process is simulated by using the process model; the process parameter set is screened with the constraint conditions that the syngas components meet the target content of each component, the low heat value meets the first threshold value, and the gasification efficiency of the biomass meets the second threshold value, to obtain an optimized process parameter set. The biomass thermal conversion power generation process parameter optimization method has high reliability, can guide the determination of the biomass thermal conversion power generation process parameters, is conducive to improving the utilization efficiency of biomass resources, and promotes the large-scale application of biomass power generation technology.

Description

Technical Field

[0001] This invention relates to the field of biomass thermal conversion power generation technology, and in particular to a method for optimizing process parameters of biomass thermal conversion power generation. Background Technology

[0002] With the continuous growth of global energy demand and the increasing severity of environmental problems, finding sustainable energy solutions has become particularly important. Among many potential alternative energy sources, biomass resources, with their zero-carbon properties, have significant advantages. As a renewable energy source, biomass has gradually attracted widespread attention due to its abundant resources, wide distribution, and low carbon emissions.

[0003] Biomass power generation technology converts biomass resources, such as agricultural and forestry waste, into electricity, achieving not only the utilization of waste resources but also effectively reducing dependence on fossil fuels. Therefore, biomass power generation is considered a clean and green energy technology with significant carbon emission reduction potential. However, compared to fossil fuels such as coal, oil, and natural gas, biomass has a lower energy density, producing relatively less heat per volume or mass. Furthermore, biomass resources are widely and dispersed, resulting in high costs for collection, storage, processing, and transportation, hindering the formation of a complete industrial chain and limiting large-scale development.

[0004] Current biomass thermal conversion technologies suffer from immature processing techniques, resulting in issues such as low effective components in gaseous pyrolysis products and high oxygen content and poor stability in liquid products. Furthermore, existing technologies primarily focus on the impact of syngas quality on biomass thermal conversion power generation efficiency, conducting experiments and explorations based on syngas composition to determine optimal process parameters. However, the determined process parameters often fail to effectively reduce carbon emissions while improving energy utilization efficiency. This leads to a lengthy, complex, and inefficient optimization process for determining green power generation process parameters, resulting in high trial-and-error costs and hindering the promotion of renewable energy utilization and environmental protection. Summary of the Invention

[0005] This invention aims to overcome the shortcomings of existing technologies by improving the process parameters of biomass thermal conversion power generation, thereby increasing the utilization efficiency of biomass resources, reducing costs, and promoting the large-scale application and sustainable development of biomass power generation technology. Therefore, this invention provides a method for optimizing biomass thermal conversion power generation process parameters. This invention utilizes process control software to simulate the biomass gasification power generation process. By optimizing the target values ​​of gasification efficiency, syngas composition, and its lower heating value, the invention guides the determination of the preparation process parameters for biomass gasification power generation. This ensures that the biomass thermal conversion power generation process using the selected process parameters can improve energy utilization efficiency, effectively reduce carbon emissions, achieve green power generation, and promote the utilization of renewable energy and environmental protection.

[0006] The method for optimizing biomass thermal conversion power generation process parameters according to the present invention is achieved through the following technical solution:

[0007] The method for optimizing biomass thermal conversion power generation process parameters provided by this invention specifically includes the following steps:

[0008] Step 1: Based on the process flow and material balance relationship of biomass thermal conversion power generation, a process model for biomass thermal conversion power generation is established using the process simulation software Aspen Plus.

[0009] It should be noted that this invention takes into account existing technologies, such as... Figure 1 As shown, the biomass thermal conversion power generation process includes the following steps: First, agricultural, forestry, and urban biomass waste is collected and pre-treated, and combustion efficiency is improved through pre-treatment methods such as crushing and drying. Next, during pyrolysis or gasification, biomass is decomposed at high temperatures to generate combustible gas, liquid bio-oil, and solid char, or reacts with a gasifying agent to generate syngas. Subsequently, the syngas is cooled, filtered, and desulfurized and denitrified to remove impurities and pollutants. The purified syngas enters a gas turbine for combustion and power generation, with some heat used to heat water to generate steam, which drives a steam turbine to generate electricity. Waste heat is recovered through a heat exchanger and can be used as a drying heat source in the biomass pre-treatment stage. Finally, the flue gas generated during power generation is treated to ensure emissions meet standards, while the char and ash generated during pyrolysis or gasification are treated and utilized as soil conditioners or industrial raw materials.

[0010] Therefore, based on the aforementioned traditional biomass thermal conversion power generation process flow, this invention uses Aspen Plus to simulate the main processes of drying and pyrolysis gasification combustion, resulting in the process model for biomass thermal conversion power generation. It is important to emphasize that the process control software model used in this invention is Aspen Plus. Aspen Plus is a commonly used software for designing, optimizing, and simulating complex systems in the fields of chemical, food, and environmental processes. Furthermore, Aspen Plus has already been used in the prior art to accurately simulate complex chemical reactions and thermodynamic processes, providing important support for the study of biomass thermal conversion. Therefore, Aspen Plus is a commonly used software in the field of biomass thermal conversion, and will not be elaborated upon further here; those skilled in the art should be aware of it. For ease of description, this invention will directly refer to the process control software model used in this invention as Aspen Plus.

[0011] It should also be noted that, during the exploration process, this invention found that focusing primarily on the impact of syngas quality on biomass thermal conversion power generation efficiency, due to the overly simplistic consideration of factors, makes it difficult to accurately guide the determination of optimized process parameters for biomass thermal conversion power generation that effectively reduce carbon emissions while improving energy utilization efficiency, thus hindering the determination of optimal process parameters for green power generation. Therefore, this invention utilizes AspenPlus to simulate the biomass gasification power generation process. By optimizing the target values ​​for gasification efficiency, syngas composition, and its lower heating value, the invention guides the determination of preparation process parameters for biomass gasification power generation. This ensures that the biomass thermal conversion power generation process using the selected process parameters can improve energy utilization efficiency, effectively reduce carbon emissions, achieve green power generation, and promote the utilization of renewable energy and environmental protection.

[0012] In some preferred embodiments of the present invention, the process model includes a drying unit, a pyrolysis gasification unit, and a calculator unit, and the process flow diagram of the obtained process model is shown below. Figure 2 As shown.

[0013] The drying unit of the present invention includes a dryer module and a first separator module; wherein, the dryer module is used to simulate the drying process of wet biomass, and the first separator module is used to simulate the process of water evaporation and discharge during the drying process. The dryer module is also referred to as the DRYER module, and the first separator module is also referred to as the SEP1 module.

[0014] In some preferred embodiments of the present invention, the DRYER module used is the RStoic reactor module in the AspenPlus software, where RStoic stands for Stoichiometric Reactor.

[0015] In some preferred embodiments of the present invention, the SEP1 module used is the SSplit module in the Aspen Plus software, where SSplit stands for Stream Splitter.

[0016] The drying unit of this invention mainly realizes the process of removing moisture from biomass raw materials to obtain dry biomass and water. The expression of this process is shown in Equation 1:

[0017] Biomass wet →Biomass dry +H2O Formula 1;

[0018] In Equation 1, Biomass wet Biomass is a biomass feedstock containing water. dryThe substance is dried biomass, and H2O is the removed water.

[0019] The pyrolysis gasification unit of this invention includes a separator module, a pyrolyzer module, and a second separator module. The separator module, also known as the DECMP module, is used to simulate the pyrolysis gasification process of dried biomass. The pyrolyzer module, also known as the PYROL module, is used to simulate the combustion process. The second separator module, also known as the SEP2 module, is used to simulate the solid-gas separation of combustion products.

[0020] In some preferred embodiments of the present invention, the DECMP module used is the RYield module in the AspenPlus software, where RYield stands for Yield Reactor.

[0021] In some preferred embodiments of the present invention, the PYROL module used is the RGibbs module in the AspenPlus software, where RGibbs stands for Gibbs Reactor.

[0022] In some preferred embodiments of the present invention, the SEP2 module used is the Flash module in the Aspen Plus software, where Flash stands for Flash Drum.

[0023] The calculator unit of the present invention includes multiple calculator modules with nested formula translation statements, wherein the formula translation statements are also called FORTRAN statements. The multiple calculator modules are respectively used to accept input instructions and send them to the drying unit and the pyrolysis gasification unit to realize drying, pyrolysis gasification and combustion operations.

[0024] In some preferred embodiments of the present invention, the calculator module used is the Calculator module in the AspenPlus software.

[0025] The pyrolysis gasification unit of this invention mainly realizes the thermal decomposition reaction of some organic matter in biomass under anaerobic conditions, and the expression of this process is shown in Equation 2:

[0026] Biomass dry →CO+H2O+CO2+CH4+H2+ASH Equation 2;

[0027] In Equation 2, Biomass dry The biomass is dry, and CO, H2O, CO2, CH4, H2O and ASH are all pyrolysis products of the thermal decomposition reaction of some organic matter in the biomass; among them, ASH is ash.

[0028] As can be seen from Equation 2, the yield and quality of combustible gases in the products of the pyrolysis gasification combustion stage have a significant impact on improving the efficiency of subsequent biomass thermal conversion power generation. That is, the gasification efficiency of biomass is an important indicator for evaluating the performance of biomass thermal conversion power generation. Therefore, the gasification efficiency of biomass is used as a screening constraint condition in this invention.

[0029] Equation 2 also shows that the products of the pyrolysis gasification combustion stage include fuel gases such as carbon monoxide and hydrogen. Increased carbon monoxide and hydrogen content is beneficial for improving the power generation efficiency of the gas turbine. However, the products of the pyrolysis gasification combustion stage also include greenhouse gases such as carbon dioxide and methane. If the carbon dioxide content is too high, it will lead to increased greenhouse gas emissions, which is detrimental to low-carbon development goals. Therefore, the syngas composition of biomass is not only an important indicator for evaluating the performance of biomass thermal conversion power generation, but also an important indicator for evaluating carbon emissions. Gasification efficiency directly affects the proportion of biomass converted into combustible gas. Furthermore, lower heating value (LHV) is an important indicator for measuring fuel energy density. For ease of description, this invention will use LHV to represent lower heating value below.

[0030] In some preferred embodiments of the present invention, the property method of the process model is selected as the Peng-Robinson equation property method, wherein the Peng-Robinson equation is a commonly used gas equation of state in the art, also known as the Peng-Robinson cubic equation of state, or simply the PR equation.

[0031] In some preferred embodiments of the present invention, the DCOALIGT model is selected as the method for calculating the density of materials in the process model. For example, the density of raw materials and the density of ash in the process model are both calculated using the DCOALIGT model. The DCOALIGT model is a commonly used method for calculating the density of materials in the art, and those skilled in the art should be aware of it.

[0032] In some preferred embodiments of the present invention, the HCOALLGEN model is selected as the method for calculating the enthalpy of materials in the process model. For example, the enthalpy of the density and ash content of the raw materials in the process model are both calculated using the HCOALLGEN model. The HCOALLGEN model is a commonly used method for calculating the enthalpy of materials in the art, and those skilled in the art should be aware of it.

[0033] Based on the above, the present invention preferably obtains the syngas components, lower heating value, and gasification efficiency generated during the simulated biomass thermal conversion power generation process. By considering multiple factors, including the impact of the products of the pyrolysis gasification combustion stage on the subsequent biomass thermal conversion power generation efficiency and the impact of carbon emissions from the pyrolysis gasification combustion stage, the present invention ultimately optimizes the process parameters to ensure that, under the optimized process parameters, the biomass thermal conversion power generation process can effectively reduce carbon emissions while improving energy utilization efficiency, thereby promoting the utilization of renewable energy and environmental protection.

[0034] Step 2: Obtain publicly available data on biomass used in biomass thermal conversion power generation and corresponding process parameters. Use biomass as input and the corresponding process parameter data as output to establish a dataset.

[0035] It should be noted that when obtaining process parameter data for biomass thermal conversion power generation, this invention obtains the corresponding process parameters based on the actual process parameters to be optimized. For example, in some preferred embodiments of this invention, considering that the composition of syngas plays an important role in the analysis of subsequent power generation and carbon emissions, and that the composition of biomass gasification products changes significantly under different gasification temperatures, the gasification temperature has a significant impact on the biomass thermal conversion power generation process. Therefore, the determined process parameter data includes, but is not limited to, the gasification temperature.

[0036] Step 3: Using the biomass in the actual biomass thermal conversion power generation process to be optimized as input, obtain the corresponding process parameter data from the dataset as the process parameter set; use the required biomass and its corresponding process parameter set as the simulation reaction raw materials and simulation reaction process parameters, and use the process model to simulate the thermal conversion power generation process.

[0037] Step 4: Using the constraints of syngas components meeting target content, lower heating value meeting the first threshold, and biomass gasification efficiency meeting the second threshold, the process parameter set is screened to obtain an optimized process parameter set.

[0038] It should be noted that, in some preferred embodiments of the present invention, the target volume fraction of CO in the synthesis gas is 25% to 30%; the target volume fraction of H2 is 30% to 35%; the target volume fraction of CH4 is 5% to 10%; and the target volume fraction of CO2 is 30% to 35%.

[0039] In some preferred embodiments of the present invention, the optimized set of process parameters is obtained by screening through the following steps:

[0040] 1) Obtain the volume fraction of each component in the syngas produced during the simulated thermal conversion power generation process. Use the data corresponding to the volume fraction of each component in the syngas as input and the corresponding process parameters as output to construct a syngas prediction dataset. Then, using the constraint that the syngas components meet the target content of each component, filter the syngas prediction dataset to obtain a first set of process parameters.

[0041] 2) Obtain the lower heating value of syngas during the simulated thermal conversion power generation process. Use the data corresponding to the lower heating value of syngas as input and the corresponding process parameters as output to construct a lower heating value prediction dataset. Use the lower heating value meeting the first threshold as a constraint condition to filter the lower heating value prediction dataset to obtain a second set of process parameters.

[0042] 3) Using the data corresponding to the gasification efficiency of biomass as input and the corresponding process parameters as output, construct a gasification efficiency prediction dataset; using the gasification efficiency of biomass satisfying the second threshold as a constraint, filter the gasification efficiency prediction dataset to obtain a third set of process parameters.

[0043] 4) Take the intersection of the first process parameter set, the second process parameter set, and the third process parameter set as the optimized process parameter set.

[0044] It should be noted that, in some preferred embodiments of the present invention, the first threshold is ≥12MJ / m 3 .

[0045] In some preferred embodiments of the present invention, the second threshold is ≥80%.

[0046] In some preferred embodiments of the present invention, the volume fraction of each component in the synthesis gas is obtained through literature review and / or analytical testing.

[0047] In some preferred embodiments of the present invention, the analytical method used to obtain the volume fraction of each component in the synthesis gas is gas chromatography.

[0048] It should be noted that, in some preferred embodiments of the present invention, the lower heating value of the synthesis gas is calculated using the formula described in Equation 3:

[0049]

[0050] In Equation 3, LHV Gas This indicates the lower heating value of the syngas; Y represents the volume fraction of hydrogen in the synthesis gas. CO This indicates the volume fraction of carbon monoxide in the synthesis gas. This represents the volume fraction of methane in the synthesis gas. In Equation 3, the units for 10.79, 12.62, and 35.81 are all MJ / m³. 3 .

[0051] It should also be noted that Equation 3 in this invention is obtained according to the formula for LHV in Reference 1, and Reference 1 is:

[0052] Kaewluan S. Potential of synthesis gas production from rubber woodchip gasification in a bubbling fluidised bed gasifier. Energy Conversion and Management. 2011; 52:75-84. DOI: 10.1016 / j.enconman.2010.06.044.

[0053] In some more preferred embodiments of the present invention, It was obtained by gas chromatography combined with a thermal conductivity detector.

[0054] In some more preferred embodiments of the present invention, Y CO It was obtained by gas chromatography combined with flame ionization detector testing.

[0055] In some more preferred embodiments of the present invention, It was obtained by gas chromatography combined with flame ionization detector testing.

[0056] It should also be noted that, in some preferred embodiments of the present invention, the gasification efficiency of the biomass is obtained through literature review and / or analytical testing.

[0057] In some preferred embodiments of the present invention, the analytical testing method used to obtain the gasification efficiency of the biomass is a method combining thermogravimetric analysis and mass balance calculation of gasification products.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] This invention utilizes Aspen Plus to simulate the biomass gasification power generation process, establishing a process model for biomass thermal conversion power generation. Based on the biomass in the actual biomass thermal conversion power generation process to be optimized, and its corresponding process parameter set, the model is used to simulate the thermal conversion power generation process. This invention analyzes the factors affecting the biomass thermal conversion power generation process. To improve the power generation efficiency of biomass thermal conversion power generation while reducing carbon emissions, the process parameter set is screened using the composition of syngas produced during thermal conversion power generation, the lower heating value of syngas, and the gasification efficiency of biomass as screening criteria. The resulting set of process parameters is the optimized set. This invention, through the use of the Aspen Plus model and dataset construction method, makes the process parameter optimization process more scientific and systematic, reduces trial-and-error costs, and improves optimization efficiency. It provides important technical reference and data support for the practical application of biomass gasification power generation, contributing to the promotion of renewable energy utilization and environmental protection.

[0060] Compared to existing technologies that use a single screening condition for optimization, this invention improves gasification efficiency and optimizes the composition and lower heating value of syngas. This not only provides more accurate guidance for determining the optimal process parameters for biomass gasification power generation, but also, when the process parameters optimized by this invention are used, can effectively improve energy utilization efficiency, reduce costs, and further reduce carbon emissions and harmful gas emissions, thus achieving green power generation and promoting the utilization of renewable energy and environmental protection. Attached Figure Description

[0061] Figure 1 This is a process flow diagram for biomass thermal conversion power generation.

[0062] Figure 2 This is a schematic diagram of the process model of the present invention.

[0063] Figure 2 The accompanying figure labels are explained as follows:

[0064] 1-Wet biomass input module; 2-Dryer module; 3-First separator module; 31-First gas output terminal; 32-First solid output terminal; 4-Separator module; 5-Pyrolysis unit module; 6-Second separator module; 61-Second gas output terminal; 62-Second solid output terminal; 7-First calculator module; 8-Second calculator module; 9-Third calculator module; 10-Air input module; 11-Heater module; 12-Power module.

[0065] Figure 3 This is a graph showing the variation of syngas composition at different gasification temperatures in the process model of this invention.

[0066] Figure 4 This is a graph showing the variation of biomass gasification efficiency at different gasification temperatures for the process model of this invention.

[0067] Figure 5 This is a graph showing the variation of the lower heating value of the process model of the present invention at different gasification temperatures. Detailed Implementation

[0068] The technical solutions in the embodiments of the present invention will be clearly and completely described below.

[0069] Example 1

[0070] This embodiment provides a method for optimizing process parameters of biomass thermal conversion power generation.

[0071] This embodiment uses wood chips as biomass and takes the optimization of the gasification temperature in the wood chip thermal conversion power generation process as an example. By optimizing the gasification temperature in the pyrolysis gasification process, the gasification efficiency and the lower heating value of the syngas can be improved.

[0072] Furthermore, the biomass thermal conversion power generation process parameter optimization method in this embodiment specifically includes the following steps:

[0073] 1) Based on the process flow and material balance relationship of biomass thermal conversion power generation, a process model of biomass thermal conversion power generation was established using the process simulation software Aspen Plus.

[0074] 2) Obtain publicly available data on biomass used in biomass thermal conversion power generation and corresponding process parameters. Use biomass as input and the corresponding process parameter data as output to establish a dataset.

[0075] 3) Based on actual needs, obtain the corresponding set of process parameters using the required biomass as input; use the required biomass and its corresponding set of process parameters as the raw materials and process parameters for the simulated reaction, and use the process model to simulate the thermal conversion power generation process.

[0076] 4) Obtain the volume fraction of each component in the syngas produced during the simulated thermal conversion power generation process. Use the data corresponding to the volume fraction of each component in the syngas as input and the corresponding process parameters as output to construct a syngas prediction dataset.

[0077] 5) Obtain the volume fraction of each component in the syngas produced during the simulated thermal conversion power generation process. Use the data corresponding to the volume fraction of each component in the syngas as input and the corresponding process parameters as output to construct a syngas prediction dataset.

[0078] 6) Using the constraints that the syngas components satisfy the following conditions: CO volume fraction of 25%–30%, H2 volume fraction of 30%–35%, CH4 volume fraction of 5%–10%, and CO2 volume fraction of 30%–35%, the syngas prediction dataset is filtered, and the filtered process parameters are sorted in descending order to obtain the first set of process parameters.

[0079] 7) Obtain the lower heating value of syngas during the simulated thermal conversion power generation process. Use the data corresponding to the lower heating value of syngas as input and the corresponding process parameters as output to construct a lower heating value prediction dataset.

[0080] 8) With a lower heating value ≥12MJ / m 3 As a constraint, the low-calorific-value prediction dataset is filtered, and the filtered process parameters are sorted in descending order to obtain the second set of process parameters.

[0081] 9) Using the data corresponding to the gasification efficiency of biomass as input and the corresponding process parameters as output, construct a gasification efficiency prediction dataset.

[0082] 10) With the constraint that the biomass gasification efficiency is ≥80%, the gasification efficiency prediction dataset is filtered, and the process parameters obtained from the filtering are sorted in descending order to obtain the third process parameter set.

[0083] 11) Take the intersection of the first process parameter set, the second process parameter set, and the third process parameter set as the optimized process parameter set.

[0084] Please see Figure 2 The process model established in this embodiment includes a drying unit, a pyrolysis gasification unit, and a calculator unit.

[0085] The drying unit includes a dryer module 2 and a first separator module 3 connected in series. Figure 2 As can be seen, in this embodiment, the dryer module 2 is connected to the output end of the wet biomass input module 1 to simulate the process of drying wet biomass.

[0086] The input end of the first separator module 3 is connected to the output end of the drying unit 2, and the first separator module 3 is provided with a first gas output end 31 and a first solid output end 32 to simulate the process of water evaporation and discharge during the drying process to obtain dry biomass.

[0087] The pyrolysis gasification unit in this embodiment includes a separator module 4, a pyrolyzer module 5, and a second separator module 6 connected in series.

[0088] The input end of the separator module 4 is connected to the first solid output end 32, and is used to simulate the process of receiving the dried biomass and pyrolyzing and gasifying it.

[0089] The input end of the pyrolysis module 5 is connected to the output end of the separator module 4 to simulate the combustion process.

[0090] The input end of the second separator module 6 is connected to the output end of the pyrolysis module 5, and the second separator module 6 is also provided with a second gas output end 61 and a second solid output end 62 for simulating solid-gas separation of combustion products.

[0091] like Figure 2 As shown, the calculator unit in this embodiment includes three calculator modules with nested FORTRAN statements: a first calculator module 7, a second calculator module 8, and a third calculator module 9. The first calculator module, containing the FORTRAN statement corresponding to nested Equation 1, is located between the dryer module 2 and the first separator module 3. It receives input instructions and transmits them to the drying unit to perform drying operations and corresponding calculations. Equation 1 is shown below:

[0092] Bimass wet →Biomass dry +H2O Formula 1;

[0093] In Equation 1, Biomass wet Biomass is a biomass feedstock containing water. dry The substance is dried biomass, and H2O is the removed water.

[0094] The second calculator module 8, containing the FORTRAN statement corresponding to nested Equation 2, is located between the separator module 4 and the pyrolyzer module 5. It receives input instructions and transmits them to the pyrolyzer module to perform the corresponding calculations. Equation 2 is shown below:

[0095] Biomass dry →CO+H2O+CO2+CH4+H2+ASH Equation 2;

[0096] In Equation 2, Biomass dry The dried biomass CO, H2O, CO2, CH4, H2O and ASH are all pyrolysis products of the thermal decomposition reaction of some organic matter in the biomass; among them, ASH is ash.

[0097] The third calculator module 9, equipped with a nested FORTRAN statement corresponding to the 3, is located between the pyrolyzer module 5 and the second separator module 6. It is used to receive input instructions and send them to the second separator module 6 to perform corresponding functions and calculations.

[0098] Equation 3 is shown below:

[0099]

[0100] In Equation 3, LHV Gas This indicates the lower heating value of the syngas; Y represents the volume fraction of hydrogen in the synthesis gas. CO This indicates the volume fraction of carbon monoxide in the synthesis gas. This represents the volume fraction of methane in the synthesis gas. In Equation 3, the units for 10.79, 12.62, and 35.81 are all MJ / m³. 3 .

[0101] It should also be noted that the pyrolysis module 5 of the present invention is also connected to an air input module 10 to simulate the oxygen content required during combustion.

[0102] In this embodiment, the second gas output terminal 61 is also connected in series with a heater module 11 and a power module 12, so that the gas separated by the heater module 11 is heated and then delivered to the power module 12 for use in biomass thermal conversion power generation.

[0103] In this embodiment, the property method of the process model is the Peng Robinson cubic equation of state property method, and the density of the raw materials and the density of the ash in the process model are both selected from the DCOALIGT model.

[0104] In this embodiment, the density of the raw materials and the enthalpy of ash in the process model are both based on the HCOALGEN model.

[0105] In this embodiment, the dryer module 2 used is the RStoic reactor module in the Aspen Plus software.

[0106] In this embodiment, the first separator module 3 is the SSplit module in the Aspen Plus software.

[0107] In this embodiment, the separator module 4 used is the RYield module in the Aspen Plus software.

[0108] In this embodiment, the pyrolyzer module 5 used is the RGibbs module in the Aspen Plus software.

[0109] In this embodiment, the second separator module 6 used is the Flash module in the AspenPlus software.

[0110] In this embodiment, wood chips were selected as biomass and were defined as unconventional materials in the simulation. The above steps were carried out sequentially, and the optimized gasification temperature was finally obtained to be 1000℃.

[0111] The industrial and elemental analyses of the biomass wood chips used in this invention are shown in Table 1. The data in Table 1 are derived from Reference 2.

[0112] Salaudeen SA, Acharya B, Heidari M, Al-Salem SM, Dutta A. Hydrogen-RichGas Stream from Steam Gasification of Biomass: Eggshell as a CO2Sorbent. Energy & Fuels. 2020; 34:4828-36. DOI: 10.1021 / acs.energyfuels.9b03719.

[0113] Table 1. Industrial and elemental analysis results of biomass wood chips.

[0114]

[0115] To verify the reliability of the process model of this invention, it is necessary to determine whether the created Aspenplus model can be used to simulate the biomass pyrolysis gasification process and whether the nested FORTRAN statements are reasonable by comparing the error between the real experimental data and the simulation data.

[0116] This invention utilizes experimental data from relevant literature for comparative analysis and verification with simulation results. The relevant operating parameters of this model were set to be the same as the experimental parameters in the literature, and simulation data and relative errors were obtained, as shown in Table 2.

[0117] Furthermore, the experimental data used in this invention are derived from reference 3:

[0118] Loha C, Chattopadhyay H, Chatterjee PK. Thermodynamic analysis of hydrogen rich synthetic gas generation from fluidized bed gasification of ricehusk. Energy. 2011; 36: 4063-71. DOI: https: / / doi.org / 10.1016 / j.energy.2011.04.042.

[0119] Table 2 Comparison of pyrolysis and gasification simulation results with experimental data

[0120]

[0121] As shown in Table 2, the relative errors between the experimental and simulated values ​​of syngas components H2, CO, CO2, and CH4 are generally around 10%. However, the experimental and simulated values ​​for CH4 show a larger error, although similar findings have been reported in other studies. The verification results indicate that the Aspenplus model of this invention has a certain degree of reliability and can be used for further simulation research.

[0122] To further verify the reliability of the optimization method of the present invention, the present invention also uses the process model of the present invention and adjusts the gasification temperature, that is, simulates thermal conversion power generation under different gasification temperature conditions of 600℃, 700℃, 800℃, 900℃ and 1000℃ respectively.

[0123] This invention simulates thermal conversion power generation using the process model of this invention under different gasification temperatures of 600℃, 700℃, 800℃, 900℃, and 1000℃. The composition of the resulting syngas is summarized as follows: Figure 3 As shown.

[0124] Depend on Figure 3It can be seen that, under different gasification temperature conditions, the volume fractions of CO and CO2 gradually increase with increasing gasification temperature, while the volume fractions of H2 and CH4 gradually decrease. This trend indicates that higher gasification temperatures help increase the CO content in the syngas, but also increase the amount of CO2 generated. Under gasification conditions of 800℃, the syngas contains higher levels of CO and H2, which is beneficial for improving the power generation efficiency of the gas turbine, while the CH4 content is lower, reducing emissions of methane, a potent greenhouse gas. The results show that by rationally selecting the gasification temperature and optimizing process parameters, biomass gasification power generation can not only achieve efficient energy conversion but also significantly reduce greenhouse gas emissions, contributing to the achievement of low-carbon development goals. In terms of carbon emission reduction analysis, biomass gasification power generation has significant advantages over traditional fossil fuel power generation. First, biomass absorbs a large amount of carbon dioxide through photosynthesis during its growth process, so the carbon emissions during its combustion process can be considered carbon neutralized. Second, by optimizing the gasification temperature and process conditions, the quality of the syngas and the power generation efficiency can be maximized, thereby reducing the carbon emissions per unit of electricity.

[0125] This invention simulates biomass gasification efficiency by conducting thermal conversion power generation under different gasification temperatures of 600℃, 700℃, 800℃, 900℃, and 1000℃ using the process model of this invention. Figure 4 As shown.

[0126] Depend on Figure 4 It can be seen that the biomass gasification efficiency significantly improves with increasing gasification temperature. This is because higher temperatures help accelerate the gasification reaction, promoting the pyrolysis and gasification process of biomass, thereby increasing the yield and quality of combustible gases. At 600℃, the gasification efficiency is 65.2%, while at 1000℃, it increases to 86.7%. This trend indicates that appropriately increasing the gasification temperature can significantly improve gasification efficiency, allowing more biomass to be converted into combustible gases. However, excessively high gasification temperatures may also bring some challenges, such as increased requirements for the high-temperature resistance of equipment materials and increased energy consumption. Therefore, in practical applications, it is necessary to comprehensively consider gasification efficiency and economics to select the optimal gasification temperature. By optimizing the gasification temperature, not only can the efficiency of biomass gasification power generation be improved, but carbon emissions can also be effectively reduced, contributing to the achievement of low-carbon development goals.

[0127] This invention simulates thermal conversion power generation using the process model of this invention under different gasification temperatures of 600℃, 700℃, 800℃, 900℃, and 1000℃. The lower heating value of the syngas is then analyzed as follows: Figure 5 As shown.

[0128] Depend on Figure 5It can be seen that the lower heating value (LHV) of biomass gasification products gradually increases with increasing gasification temperature. This is because higher gasification temperatures help promote the pyrolysis and gasification reactions of biomass, generating more combustible gases such as CO and H2, thereby increasing the calorific value of the syngas. At 600℃, the lower heating value is 10.5 MJ / m³. 3 At 1000℃, the lower heating value increases to 13.5 MJ / m³. 3 This trend indicates that appropriately increasing the gasification temperature can significantly improve the energy density of the gasification products.

[0129] Through comprehensive Figures 3-5 The test results show that at a gasification temperature of 1000℃, the gasification efficiency and the lower heating value of the syngas can be effectively improved, thereby helping to improve power generation efficiency and fuel utilization.

[0130] In summary, the biomass thermal conversion power generation process parameter optimization method of the present invention helps to obtain optimized process parameters in a reasonable manner, so as to ensure that the biomass thermal conversion power generation process carried out by the selected process parameters can improve energy utilization efficiency, effectively reduce carbon emissions, realize green power generation, and promote the utilization of renewable energy and environmental protection.

[0131] Obviously, the above embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

Claims

1. A method for optimizing process parameters for a biomass thermal conversion power generation process, characterized by, The method comprises the following steps: According to the process flow and material balance relationship of the biomass thermal conversion power generation process, a process model of the biomass thermal conversion power generation is established by using a process simulation software; The biomass used in the biomass thermal conversion power generation and the corresponding process parameter data are obtained, the biomass is taken as the input, the corresponding process parameter data are taken as the output, and a data set is established; The biomass used in the actual biomass thermal conversion power generation process to be optimized is taken as the input, and the corresponding process parameter data are obtained from the data set as a process parameter set; The biomass and the corresponding process parameter set are taken as the simulation reaction raw materials and simulation reaction process parameters, and the process model is used to simulate the thermal conversion power generation process; The process parameter set is screened with the constraint conditions that the component content of the synthesis gas meets the target content, the low heat value meets the first threshold value, and the gasification efficiency of the biomass meets the second threshold value, to obtain an optimized process parameter set; in the synthesis gas, the target volume fraction content of CO is 25% to 30%, the target volume fraction content of H2 is 30% to 35%, the target volume fraction content of CH4 is 5% to 10%, and the target volume fraction content of CO2 is 30% to 35%; The process model comprises a drying unit, a pyrolysis and gasification unit, and a calculator unit; the drying unit comprises a dryer module and a first separator module; the dryer module is used to simulate the drying process of wet biomass, and the first separator module is used to simulate the process of water evaporation and discharge; The pyrolysis and gasification unit comprises a quality separator module, a pyrolyzer module, and a second separator module; the quality separator module is used to simulate the pyrolysis and gasification process of dry biomass obtained after drying; the pyrolyzer module is used to simulate the combustion process; and the second separator module is used to simulate the solid-gas separation of the combustion product; The calculator unit comprises a plurality of calculator modules with nested formula translation statements, which are used to accept input instructions and deliver them to the drying unit and the pyrolysis and gasification unit; The method for screening the process parameter set comprises the following steps: The volume fraction content of each component in the synthesis gas generated in the simulation of the thermal conversion power generation process is obtained, the data corresponding to the volume fraction content of each component in the synthesis gas is taken as the input, the corresponding process parameters are taken as the output, a synthesis gas prediction data set is constructed, and the first process parameter set is obtained by screening the synthesis gas prediction data set with the constraint condition that the component content of the synthesis gas meets the target content; The low heat value of the synthesis gas in the simulation of the thermal conversion power generation process is obtained, the data corresponding to the low heat value of the synthesis gas is taken as the input, the corresponding process parameters are taken as the output, a low heat value prediction data set is constructed, and the second process parameter set is obtained by screening the low heat value prediction data set with the constraint condition that the low heat value meets the first threshold value; Analog thermal conversion power generation process is acquired, and the gasification efficiency of the biomass is obtained. The data corresponding to the gasification efficiency of the biomass is taken as input, and the corresponding process parameters are taken as output to construct a gasification efficiency prediction data set. The gasification efficiency prediction data set is filtered under the constraint condition that the gasification efficiency of the biomass meets a second threshold value, and a third process parameter set is obtained. The intersection of the first process parameter set, the second process parameter set, and the third process parameter set is taken as an optimized process parameter set. the first threshold value is ≥ 12 MJ / m 3 ; The second threshold value is greater than or equal to 80%.

2. The method of optimizing process parameters for a biomass thermal conversion power generation process according to claim 1, wherein, The property method of the process model is selected as the Peng-Robinson equation property method.

3. The method of optimizing process parameters for a biomass power generation process of claim 1, wherein, In the process model, the DCOALIGT model is selected as the calculation method of the density of the material. The HCOALGEN model is selected as the calculation method of the enthalpy of the material.

4. The method of optimizing process parameters for a biomass power generation process of claim 1, wherein, The low heat value of the synthesis gas is calculated by formula 3. Formula 3; in formula 3, represents the lower heating value of the synthesis gas; represents the volume fraction of hydrogen in the synthesis gas, represents the volume fraction of carbon monoxide in the synthesis gas, represents the volume fraction of methane in the synthesis gas; and 10.79, 12.62 and 35.81 have units of MJ / m 3 .

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