Biomass thermal conversion power generation process parameter optimization method

Abstract

The invention 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 comprises the following steps: establishing a process model by utilizing process simulation software; the method comprises the following steps: acquiring process parameter data of disclosed biomass thermal conversion power generation, and establishing a data set; selecting biomass and a process parameter set corresponding to the biomass, and simulating a thermal conversion power generation process by utilizing the process model; and screening the process parameter set under the constraint conditions that the synthesis gas component meets the target content of each component, the lower calorific value meets a first threshold value and the gasification efficiency of the biomass meets a second threshold value to obtain an optimized process parameter set. The biomass thermal conversion power generation process parameter optimization method is high in reliability, can guide and determine the biomass thermal conversion power generation process parameters, is beneficial to improving the utilization efficiency of biomass resources, and promotes large-scale application of a biomass power generation technology.

Description

Technical Field

[0001] The present invention relates to the technical field of biomass thermal conversion power generation, and in particular to a method for optimizing process parameters of biomass thermal conversion power generation. Background Art

[0002] With the continuous growth of global energy demand and the increasing severity of environmental problems, it is particularly important to find sustainable energy solutions. Among many potential alternative energy sources, biomass resources with zero carbon properties have great 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, which not only realizes the resource utilization of waste, but also effectively reduces dependence on fossil fuels. Therefore, biomass power generation is considered to be a clean green energy technology with significant carbon emission reduction potential. However, compared with fossil energy such as coal, oil and natural gas, biomass has a lower energy density and can generate relatively less heat with the same volume or mass. In addition, biomass resources are widely distributed and dispersed, and the cost of collection, storage, processing and transportation is high, which hinders the formation of a complete industrial chain and limits large-scale development.

[0004] The current biomass thermal conversion technology has problems such as low effective components in the pyrolysis gaseous products, high oxygen content in the liquid products and poor stability due to the immature processing technology. In addition, the existing technology currently focuses on the impact of the quality of syngas on the efficiency of biomass thermal conversion power generation. Experiments and explorations are conducted based on the components of syngas to determine the optimal process parameters. However, the determined process parameters are difficult to effectively reduce carbon emissions on the basis of improving energy utilization efficiency, resulting in a long optimization process cycle for determining the process parameters for green power generation, complex and cumbersome operations, low optimization efficiency, high trial and error costs, and difficulty in promoting the use of renewable energy and environmental protection. Summary of the invention

[0005] The present invention aims to overcome the deficiencies in the above-mentioned prior art by improving the process parameters of biomass thermal conversion power generation, improve the utilization efficiency of biomass resources, reduce costs, and promote the large-scale application and sustainable development of biomass power generation technology. Therefore, the present invention provides a method for optimizing process parameters of biomass thermal conversion power generation. The present invention uses process control software to simulate the biomass gasification power generation process, and optimizes the target values ​​of gasification efficiency, synthesis gas composition and its low calorific value to guide the determination of the preparation process parameters of the biomass gasification power generation process, 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.

[0006] A method for optimizing process parameters of biomass thermal conversion power generation of the present invention is achieved through the following technical solutions:

[0007] The present invention provides a method for optimizing process parameters of biomass thermal conversion power generation, which specifically comprises the following steps:

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

[0009] It should be noted that the present invention takes into account the prior art, such as Figure 1 As shown in the figure, the biomass thermal conversion power generation process includes the following steps: First, collect and pre-treat agricultural, forestry and urban biomass waste, and improve the combustion efficiency through pre-treatment methods such as crushing and drying. Then, in the process of pyrolysis or gasification, the biomass is decomposed at high temperature to generate combustible gas, liquid bio-oil and solid charcoal, or reacted with a gasifying agent to generate synthesis gas. Subsequently, the synthesis gas is cooled, filtered, desulfurized and denitrified to remove impurities and pollutants. The purified synthesis gas enters the gas turbine for combustion and power generation, and part of the heat is used to heat water to generate steam to drive the steam turbine to generate electricity. The waste heat is recovered through the heat exchanger and can be used as a drying heat source in the biomass pretreatment stage. Finally, the flue gas generated in the power generation process is treated to ensure that the emission meets the standards, and the charcoal and ash generated in the pyrolysis or gasification process are treated and utilized as soil conditioners or industrial raw materials.

[0010] Therefore, based on the process flow of the above-mentioned traditional biomass thermal conversion power generation process, the main processes simulated by the present invention based on Aspen Plus are the drying process and the pyrolysis gasification combustion process, and the process model of the biomass thermal conversion power generation of the present invention is obtained. It should be emphasized that the process control software model adopted by the present invention is Aspen Plus. AspenPlus is a design, optimization and simulation of complex systems commonly used in the fields of chemical industry, food and environmental processes. And AspenPlus has been used in the prior art to accurately simulate complex chemical reactions and thermodynamic processes, which provides important support for the study of biomass thermal conversion. Therefore, AspenPlus belongs to the commonly used software in the field of biomass thermal conversion. Therefore, the present invention will not be repeated here, and those skilled in the art should know. For the convenience of expression, the present invention will directly use Aspen Plus to represent the process control software model adopted by the present invention.

[0011] It should also be noted that the present invention has found in the process of exploration that when focusing on the impact of synthesis gas quality on biomass thermal conversion power generation efficiency, due to the overly single factors considered, it is difficult to accurately guide the determination of the process parameters of the optimized biomass thermal conversion power generation process that can effectively reduce carbon emissions on the basis of improving energy utilization efficiency, thereby determining green power generation. Therefore, the present invention uses Aspen Plus to simulate the biomass gasification power generation process, and optimizes the target values ​​of gasification efficiency, synthesis gas composition and its low calorific value to guide the determination of the preparation process parameters of the biomass gasification power generation process, so as to ensure that the biomass thermal conversion power generation process performed by 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 as follows: Figure 2 shown.

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

[0014] In some more preferred embodiments of the present invention, the DRYER module used is the RStoic reactor module in the AspenPlus software, wherein the full English name of RStoic is Stoichiometric Reactor, and its Chinese name is Stoichiometric Reactor.

[0015] In some more preferred embodiments of the present invention, the adopted SEP1 module is the SSplit module in the Aspen Plus software, wherein the full name of SSplit in English is Stream Splitter, and its Chinese name is stream separator.

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

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

[0018] In formula 1, Biomass wet Biomass is a water-containing biomass raw material. dryis the dried biomass, and H2O is the removed water.

[0019] The pyrolysis and gasification unit of the present invention comprises a mass separator module, a pyrolyzer module and a second separator module. The mass separator module is also called a DECMP module, which is used to simulate the pyrolysis and gasification process of the dry biomass obtained after drying. The pyrolyzer module is also called a PYROL module, which is used to simulate the combustion process. The second separator module is also called a SEP2 module, which is used to simulate the solid-gas separation of the combustion products.

[0020] In some more preferred embodiments of the present invention, the DECMP module used is the RYield module in the AspenPlus software, wherein the full name of RYield in English is Yield Reactor, and its Chinese name is Yield Reactor.

[0021] In some more preferred embodiments of the present invention, the PYROL module used is the RBibbs module in the AspenPlus software, wherein the full name of RBibbs in English is Gibbs Reactor, and its Chinese name is Gibbs Reactor.

[0022] In some more preferred embodiments of the present invention, the adopted SEP2 module is the Flash module in the Aspen Plus software, wherein the full name of Flash in English is Flash Drum, and its Chinese name is 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, and the multiple calculator modules are respectively used to receive input instructions and transmit them to the drying unit and pyrolysis gasification unit to realize drying, pyrolysis gasification and combustion operations.

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

[0025] The pyrolysis gasification unit of the present invention mainly realizes the thermal cracking reaction of part of the organic matter in the biomass under anaerobic conditions. The expression of the process is shown in Formula 2:

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

[0027] In formula 2, Biomass dry It is dry biomass. CO, H2O, CO2, CH4, H2O and ASH are all cracking products of thermal cracking reaction of some organic matter in biomass; among them, ASH is ash.

[0028] It can be seen from Formula 2 that the yield and quality of combustible gas in the products of the pyrolysis gasification combustion stage have a great influence on improving the subsequent biomass thermal conversion power generation efficiency, that is, the gasification efficiency of biomass is an important indicator for evaluating the performance of biomass thermal conversion power generation. Therefore, the present invention uses the gasification efficiency of biomass as a screening constraint condition of the present invention.

[0029] It can also be seen from Formula 2 that the products of the pyrolysis, gasification and combustion stage include fuel gases such as carbon monoxide and hydrogen. When the content of carbon monoxide and hydrogen increases, it is beneficial to improve the power generation efficiency of the gas turbine. However, the products of the pyrolysis, gasification and combustion stage also include greenhouse gases such as carbon dioxide and methane. If the content of carbon dioxide is too high, it will lead to an increase in greenhouse gas emissions, which is not conducive to the goal of low-carbon development. Therefore, the syngas component 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. The gasification efficiency directly affects the proportion of biomass converted into combustible gas, and the lower heating value is an important indicator for measuring the energy density of fuel. The full name of the lower heating value in English is Lower Heating Value, abbreviated as LHV. For the convenience of expression, the present invention will use LHV to represent the lower heating value below.

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

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

[0032] In some preferred embodiments of the present invention, in the process model, the HCOALGEN model is selected as the calculation method of the enthalpy of the material. For example, the density of the raw material and the enthalpy of the ash in the process model are both selected from the HCOALGEN model. Among them, the HCOALGEN model is a commonly used method for calculating the enthalpy of a material in the art, and those skilled in the art should know it.

[0033] Based on the above, the present invention preferably obtains the synthesis gas components and its low calorific value and gasification efficiency generated in the simulated thermal conversion power generation process, so as to coordinately consider 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 in the pyrolysis gasification combustion stage, and finally achieves the optimization of process parameters to ensure that by carrying out the biomass thermal conversion power generation process under the optimized process parameters, it can achieve effective reduction of carbon emissions on the basis of improving energy utilization efficiency, thereby promoting the utilization of renewable energy and environmental protection.

[0034] Step 2: Obtain the biomass used in the publicly available biomass thermal conversion power generation and the corresponding process parameter data, and establish a data set with the biomass as input and the corresponding process parameter data as output.

[0035] It should be noted that when obtaining the process parameter data of biomass thermal conversion power generation, the present invention can obtain the corresponding process parameters according to the actual process parameters to be optimized. For example, in some preferred embodiments of the present invention, considering that the composition of syngas plays an important role in the subsequent analysis of power generation and carbon emissions, and under different gasification temperature conditions, the composition of biomass gasification products will change significantly, so the gasification temperature has a greater impact on the biomass thermal conversion power generation process, so the determined process parameter data include but are not limited to the gasification temperature.

[0036] Step 3, taking the biomass in the actual biomass thermal conversion power generation process to be optimized as input, obtaining the corresponding process parameter data from the data set as a process parameter set; taking the required biomass and its corresponding process parameter set as simulated reaction raw materials and simulated reaction process parameters, and using the process model to simulate the thermal conversion power generation process.

[0037] Step 4: With the constraints that the synthesis gas components meet the target content of each component, the lower heating value meets the first threshold, and the gasification efficiency of the biomass meets 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, 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%.

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

[0040] 1) Obtain the volume fraction content of each component in the synthesis gas generated in the simulated thermal conversion power generation process, take the data corresponding to the volume fraction content of each component in the synthesis gas as input, take the corresponding process parameters as output, and construct a synthesis gas prediction data set. Obtain the volume fraction content of each component in the synthesis gas generated in the simulated thermal conversion power generation process, take the data corresponding to the volume fraction content of each component in the synthesis gas as input, take the corresponding process parameters as output, and construct a synthesis gas prediction data set; take the synthesis gas components satisfying the target content of each component as a constraint condition, screen the synthesis gas prediction data set to obtain a first process parameter set.

[0041] 2) Obtain the low calorific value of the synthesis gas in the simulated thermal conversion power generation process, use the data corresponding to the low calorific value of the synthesis gas as input, and use the corresponding process parameters as output to construct a low calorific value prediction data set; use the low calorific value satisfying the first threshold as a constraint condition, screen the low calorific value prediction data set to obtain a second process parameter set.

[0042] 3) Taking data corresponding to the gasification efficiency of biomass as input and corresponding process parameters as output, a gasification efficiency prediction data set is constructed; taking the gasification efficiency of biomass satisfying the second threshold as a constraint condition, the gasification efficiency prediction data set is screened to obtain a third process parameter set.

[0043] 4) Taking 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 value is ≥ 12 MJ / 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 content of each component in the synthesis gas is obtained by literature research and / or analytical testing.

[0047] In some more preferred embodiments of the present invention, when obtaining the volume fraction content of each component in the synthesis gas, the analytical test method adopted is gas chromatography analytical test.

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

[0049]

[0050] In formula 3, LHV Gas Indicates the lower heating value of the synthesis gas; represents the volume fraction of hydrogen in the synthesis gas, Y CO represents the volume fraction of carbon monoxide in the synthesis gas, represents the volume fraction of methane in the synthesis gas. In Formula 3, the units of 10.79, 12.62 and 35.81 are all MJ / m 3 .

[0051] It should also be noted that Formula 3 in the present invention is obtained according to the formula of LHV in Document 1, and Document 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 is obtained by gas chromatography combined with thermal conductivity detector testing.

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

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

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

[0057] In some more preferred embodiments of the present invention, when obtaining the gasification efficiency of the biomass, the analytical test method adopted is a method of thermogravimetric analysis combined with mass balance calculation of the gasification product.

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

[0059] The present invention uses Aspen Plus to simulate the biomass gasification power generation process, establishes a process model for biomass thermal conversion power generation, and uses the biomass in the actual biomass thermal conversion power generation process to be optimized and its corresponding process parameter set as simulated reaction raw materials and simulated reaction process parameters, and uses the process model to simulate the thermal conversion power generation process. The present invention analyzes the factors affecting the biomass thermal conversion power generation process, and in order to reduce carbon emissions while improving the power generation efficiency of the biomass thermal conversion power generation process, the synthesis gas components generated in the thermal conversion power generation process, the low calorific value of the synthesis gas and the gasification efficiency of the biomass are used as screening conditions to screen the process parameter set, and the process parameter set obtained by screening is the optimized process parameter set. The present invention makes the process parameter optimization process more scientific and systematic by using the method constructed by the Aspen Plus model and data set, reduces the trial and error cost, improves the optimization efficiency, and provides important technical references and data support for the practical application of biomass gasification power generation, which helps to promote the utilization of renewable energy and environmental protection.

[0060] Compared with the method of using a single screening condition for optimization in the prior art, the present invention can not only more accurately guide the determination of the optimized process parameters of the biomass gasification power generation process by improving the gasification efficiency and optimizing the synthesis gas composition and its low calorific value, but also when working with the process parameters optimized by the present invention, it can further effectively reduce carbon emissions and harmful gas emissions on the basis of effectively improving energy utilization efficiency and reducing costs, thereby achieving green power generation and promoting the utilization of renewable energy and environmental protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 This is the process flow chart of biomass thermal conversion power generation.

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

[0063] Figure 2 The description of the reference numerals in the figures is 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-qualifier module; 5-pyrolyzer 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 It is a graph showing the changes in the content of synthesis gas components at different gasification temperatures of the process model of the present invention.

[0066] Figure 4 This is a graph showing the change in gasification efficiency of biomass at different gasification temperatures according to the process model of the present invention.

[0067] Figure 5 It is a diagram showing the change of low calorific value of the process model of the present invention at different gasification temperatures. DETAILED DESCRIPTION

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

[0069] Example 1

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

[0071] This embodiment uses sawdust as biomass and optimizes the gasification temperature of the sawdust thermal conversion power generation process as an example. By optimizing the gasification temperature in the pyrolysis gasification process, the gasification efficiency and the low calorific value of the synthesis gas are improved.

[0072] The method for optimizing the process parameters of biomass thermal conversion power generation in this embodiment specifically includes the following steps:

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

[0074] 2) Obtain the biomass used in the publicly available biomass thermal conversion power generation and the corresponding process parameter data, and establish a data set with the biomass as input and the corresponding process parameter data as output.

[0075] 3) According to actual needs, the required biomass is used as input to obtain a corresponding set of process parameters; the required biomass and its corresponding set of process parameters are used as simulated reaction raw materials and simulated reaction process parameters, and the process model is used to simulate the thermal conversion power generation process.

[0076] 4) Obtain the volume fraction content of each component in the synthesis gas generated in the simulated thermal conversion power generation process, use the data corresponding to the volume fraction content of each component in the synthesis gas as input, and use the corresponding process parameters as output to construct a synthesis gas prediction data set.

[0077] 5) Obtain the volume fraction content of each component in the synthesis gas generated in the simulated thermal conversion power generation process, use the data corresponding to the volume fraction content of each component in the synthesis gas as input, and use the corresponding process parameters as output to construct a synthesis gas prediction data set.

[0078] 6) Taking the synthesis gas components satisfying the constraints of CO volume fraction content of 25% to 30%, H2 volume fraction content of 30% to 35%, CH4 volume fraction content of 5% to 10% and CO2 volume fraction content of 30% to 35%, the synthesis gas prediction data set is screened, and the screened process parameters are sorted in descending order to obtain a first process parameter set.

[0079] 7) Obtain the low calorific value of the synthesis gas in the simulated thermal conversion power generation process, use the data corresponding to the low calorific value of the synthesis gas as input, and use the corresponding process parameters as output to construct a low calorific value prediction data set.

[0080] 8) Low calorific value ≥ 12MJ / m 3 As a constraint condition, the low calorific value prediction data set is screened, and the screened process parameters are sorted in descending order to obtain a second process parameter set.

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

[0082] 10) Taking the biomass gasification efficiency ≥ 80% as a constraint condition, the gasification efficiency prediction data set is screened, and the screened process parameters are sorted in descending order to obtain a third process parameter set.

[0083] 11) Taking 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] See also 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 comprises a dryer module 2 and a first separator module 3 connected in series. Figure 2 It can be seen that 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 the 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, so as to simulate the process of evaporation and discharge of water during the drying process to obtain dry biomass.

[0087] The pyrolysis and gasification unit of this embodiment comprises a mass separator module 4, a pyrolyzer module 5 and a second separator module 6 which are connected in series in sequence.

[0088] The input end of the mass separator module 4 is connected to the first solid output end 32, so as to simulate the process of receiving the dry biomass obtained after drying and pyrolyzing and gasifying it.

[0089] The input end of the pyrolyzer module 5 is connected to the output end of the mass separator module 4 for simulating a combustion process.

[0090] The input end of the second separator module 6 is communicated with the output end of the pyrolyzer 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 of this embodiment includes three calculator modules with nested FORTRAN statements, namely, the first calculator module 7, the second calculator module 8 and the third calculator module 9. Among them, the first calculator module has a FORTRAN statement corresponding to the nested formula 1, which is set between the dryer module 2 and the first separator module 3, and is used to receive input instructions and transmit them to the drying unit to realize the drying operation and corresponding calculation work. Among them, formula 1 is shown as follows:

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

[0093] In formula 1, Biomass wet Biomass is a water-containing biomass raw material. dry is the dried biomass, and H2O is the removed water.

[0094] The second calculator module 8 has a FORTRAN statement corresponding to the nested formula 2, and is arranged between the mass separator module 4 and the pyrolyzer module 5, and is used to receive input instructions and transmit them to the pyrolyzer module to perform the corresponding calculation work of the operation of the corresponding function. Among them, formula 2 is shown as follows:

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

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

[0097] The third calculator module 9 has a FORTRAN statement corresponding to the nested formula 3 and is arranged between the pyrolyzer module 5 and the second separator module 6 to receive input instructions and transmit them to the second separator module 6 to implement operations of executing corresponding functions and corresponding calculation work.

[0098] Wherein, formula 3 is as follows:

[0099]

[0100] In formula 3, LHV Gas Indicates the lower heating value of the synthesis gas; represents the volume fraction of hydrogen in the synthesis gas, Y CO represents the volume fraction of carbon monoxide in the synthesis gas, represents the volume fraction of methane in the synthesis gas. In Formula 3, the units of 10.79, 12.62 and 35.81 are all MJ / m 3 .

[0101] It should also be noted that the pyrolyzer module 5 of the present invention is also connected to an air input module 10 for simulating the oxygen content required in the combustion process.

[0102] In this embodiment, the second gas output end 61 is also provided with a heater module 11 and a power module 12 in series, so that the heater module 11 is used to heat the finally separated gas and then transmit it to the power module 12 to realize biomass thermal conversion and power generation.

[0103] In this embodiment, the physical property method of the process model selects the Peng Robinson cubic state equation physical property method, and the density of the raw material and the density of the ash of the process model both select the DCOALIGT model.

[0104] In this embodiment, the density of the raw material and the enthalpy of the 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 used is the SSplit module in the Aspen Plus software.

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

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

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

[0110] In this embodiment, wood chips are selected as biomass, which is defined as unconventional material in the simulation. The above steps are performed sequentially, and the optimized gasification temperature is finally optimized to be 1000°C.

[0111] The industrial analysis and elemental analysis of the biomass sawdust used in the present invention are shown in Table 1. The data in Table 1 are from Document 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 analysis and elemental analysis results of biomass sawdust

[0114]

[0115] In order to verify the reliability of the process model of the present invention, it is necessary to determine whether the created Aspenplus model can be used to simulate the biomass pyrolysis and gasification process and whether the nested FORTRAN statements are reasonable based on the size of the error between the real experimental data and the simulation data.

[0116] The present invention searches for experimental data in appropriate related literature for comparison and analysis with the simulation results. The relevant operating parameters of the model are set to be the same as the experimental parameters in the literature, and the simulation data and relative errors are obtained. The results are shown in Table 2.

[0117] The experimental data used in this invention are from document 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] It can be seen from the results in Table 2 that the relative errors between the experimental values ​​and the simulated values ​​of the synthesis gas components H2, CO, CO2 and CH4 are basically around 10%. However, the experimental value and the simulated value of CH4 have a large error, but similar reports have been made in related studies. The verification results show that the Aspenplus model of the present invention has certain reliability and can be used for the next simulation study.

[0122] In order to further verify the reliability of the optimization method of the present invention, the present invention also adopts the process model of the present invention, by adjusting the gasification temperature, that is, the process model of the present invention is respectively used to simulate thermal conversion power generation under different gasification temperature conditions of 600°C, 700°C, 800°C, 900°C and 1000°C.

[0123] The present invention simulates thermal conversion power generation under different gasification temperature conditions of 600°C, 700°C, 800°C, 900°C and 1000°C, and the composition of the synthesis gas obtained is summarized as follows: Figure 3 shown.

[0124] Depend on Figure 3It can be seen that under different gasification temperature conditions, the process model of the present invention gradually increases the volume fraction of CO and CO2, while the volume fraction of H2 and CH4 gradually decreases as the gasification temperature increases. This trend shows that higher gasification temperature helps to increase the content of CO in the syngas, but it also increases the amount of CO2 generated. Under the gasification condition of 800 ° C, the content of CO and H2 in the syngas is high, which is conducive to improving the power generation efficiency of the gas turbine. At the same time, the content of CH4 is low, which reduces the emission of methane, a potent greenhouse gas. The results show that by reasonably selecting the gasification temperature and optimizing the process parameters, biomass gasification power generation can not only achieve efficient energy conversion, but also significantly reduce greenhouse gas emissions, helping to achieve the goal of low-carbon development. 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, so the carbon emissions during its combustion process can be regarded as carbon neutral. Secondly, by optimizing the gasification temperature and process conditions, the quality and power generation efficiency of the syngas can be maximized, thereby reducing the carbon emissions per unit of electricity.

[0125] The process model of the present invention is subjected to simulated thermal conversion power generation under different gasification temperature conditions of 600°C, 700°C, 800°C, 900°C and 1000°C, and the gasification efficiency of biomass is summarized as follows: Figure 4 shown.

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

[0127] The present invention simulates thermal conversion power generation under different gasification temperature conditions of 600°C, 700°C, 800°C, 900°C and 1000°C, and the low calorific value of the synthesis gas is sorted as follows: Figure 5 shown.

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

[0129] Through comprehensive Figure 3 to Figure 5 The test results show that at a gasification temperature of 1000°C, the gasification efficiency and the low calorific value of the syngas can be effectively improved, which helps 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 reasonably obtain optimized process parameters to ensure that the biomass thermal conversion power generation process carried out through 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.

[0131] Obviously, the above embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

Claims

1. A method for optimizing process parameters of biomass thermal conversion power generation, characterized in that: The following steps are involved: According to the process flow and material balance relationship of biomass thermal conversion power generation, a process model of biomass thermal conversion power generation is established using process simulation software; Obtain the biomass used in the publicly disclosed biomass thermal conversion power generation and the corresponding process parameter data, and establish a data set with the biomass as input and the corresponding process parameter data as output; Taking biomass in the actual biomass thermal conversion power generation process to be optimized as input, corresponding process parameter data is obtained from the data set as a process parameter set; The biomass and its corresponding process parameter set are used as simulated reaction raw materials and simulated reaction process parameters, and the process model is used to simulate the thermal conversion power generation process; With the constraints that the syngas components meet the target content of each component, the lower calorific value meets the first threshold and the gasification efficiency of the biomass meets the second threshold, the process parameter set is screened to obtain an optimized process parameter set.

2. The method for optimizing process parameters of biomass thermal conversion power generation according to claim 1, characterized in that: The process model includes a drying unit, a pyrolysis and gasification unit and a calculator unit; The drying unit includes a dryer module and a first separator module; wherein the dryer module is used to simulate the process of drying wet biomass, and the first separator module is used to simulate the process of evaporation and discharge of water during the process; The pyrolysis and gasification unit includes a mass separator module, a pyrolyzer module and a second separator module; wherein the mass separator module is used to simulate the pyrolysis and gasification process of the 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 products; The calculator unit includes a plurality of calculator modules with nested formula translation statements, which are respectively used to receive input instructions and transmit them to the drying unit and the pyrolysis gasification unit.

3. The method for optimizing process parameters of biomass thermal conversion power generation according to claim 1, characterized in that: The physical property method of the process model selects the physical property method of the Peng-Robinson equation.

4. The method for optimizing process parameters of biomass thermal conversion power generation according to claim 1, characterized in that: 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 for the enthalpy of the material.

5. The method for optimizing process parameters of biomass thermal conversion power generation according to claim 1, characterized in that: The target volume fraction of CO in the synthesis gas is 25% to 30%; The target volume fraction content of H2 is 30% to 35%; The target volume fraction of CH4 is 5% to 10%; The target volume fraction content of CO2 is 30% to 35%.

6. The method for optimizing process parameters of biomass thermal conversion power generation according to claim 1, characterized in that: The optimized process parameter set is obtained by screening through the following steps: Obtain the volume fraction content of each component in the synthesis gas generated in the simulated thermal conversion power generation process, use the data corresponding to the volume fraction content of each component in the synthesis gas as input, and use the corresponding process parameters as output to construct a synthesis gas prediction data set; Taking the synthesis gas components satisfying the target content of each component as a constraint condition, the synthesis gas prediction data set is screened to obtain a first process parameter set; Obtain the lower calorific value of the syngas in the simulated thermal conversion power generation process, use the data corresponding to the lower calorific value of the syngas as input, and use the corresponding process parameters as output to construct a lower calorific value prediction data set; Taking the low heating value satisfying the first threshold as a constraint condition, screening the low heating value prediction data set to obtain a second process parameter set; Obtain the gasification efficiency of biomass in the simulated thermal conversion power generation process, use the data corresponding to the gasification efficiency of biomass as input, and use the corresponding process parameters as output to construct a gasification efficiency prediction data set; Taking the biomass gasification efficiency satisfying the second threshold as a constraint condition, the gasification efficiency prediction data set is screened to obtain a third process parameter set; The intersection of the first process parameter set, the second process parameter set and the third process parameter set is taken as the optimized process parameter set.

7. The method for optimizing process parameters of biomass thermal conversion power generation according to claim 6, characterized in that: The first threshold is ≥12MJ / m 3 .

8. The method for optimizing process parameters of biomass thermal conversion power generation according to claim 6, characterized in that: The second threshold value is ≥80%.

9. The method for optimizing process parameters of biomass thermal conversion power generation according to claim 1, characterized in that: The lower heating value of the synthesis gas is calculated by the formula described in Formula 3: In formula 3, LHV Gas Indicates the lower heating value of the synthesis gas; represents the volume fraction of hydrogen in the synthesis gas, Y CO represents the volume fraction of carbon monoxide in the synthesis gas, represents the volume fraction of methane in the synthesis gas; and the units of 10.79, 12.62 and 35.81 are all MJ / m 3 .

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