CN112151123B - Method for predicting pyrolysis coke yield of torrefied biomass - Google Patents
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Abstract
The invention discloses a method for predicting pyrolysis coke yield of baked biomass, which comprises the steps of performing aerobic baking and anaerobic baking on biomass respectively to obtain a first solid product and a second solid product, calculating to obtain a first baking quality yield and a second baking quality yield, putting the first solid product and the second solid product into a slow pyrolysis device for slow pyrolysis to obtain fixed carbon content, putting the first solid product and the second solid product into a fast pyrolysis device for fast pyrolysis to obtain fast pyrolysis Jiao Yangpin, weighing to obtain fast pyrolysis coke quality, and further obtaining relative coke yield and absolute coke yield; the method comprises the steps of obtaining a prediction model under slow pyrolysis by taking a first baking quality yield and a second baking quality yield as independent variables and taking a fixed carbon content as a dependent variable, and obtaining a prediction model under fast pyrolysis by taking the first baking quality yield and the second baking quality yield as independent variables and taking a relative coke yield and an absolute coke yield as dependent variables.
Description
Technical Field
The invention relates to a method for predicting pyrolysis coke yield of torrefied biomass.
Background
The traditional baking (anaerobic baking) is a mild pyrolysis technology under the condition of normal pressure inert atmosphere at 200-300 ℃, and can remove moisture and light volatile matters in biomass raw materials to obtain the fuel with low water content, high energy density and better grindability. Compared with an anaerobic environment, the boiler flue gas is used as a baking atmosphere, so that the economical efficiency of the baking process can be improved, the fuel quality (grindability, hydrophobicity and heat value are not greatly changed compared with those of anaerobic baking) of biomass can not be remarkably reduced, and the method has potential of large-scale application in industry. The oxygen concentration in boiler flue gas, which is affected by the excess air factor, typically varies between 1-13%, and is therefore also known as aerobic roasting. The existing researches show that the oxygen-free baking can obviously promote crosslinking coking among chemical bonds of biomass, so that the yield of the subsequent pyrolytic coke is improved, and a very small amount of documents show that the existence of oxygen in the baking can also obviously improve the coke yield of the subsequent pyrolytic coke. Whether anaerobic or aerobic baking can obviously improve the quality of biomass fuel, so the biomass fuel is gradually popularized and applied to the pretreatment process of biomass combustion and gasification. However, the baking prolongs the biomass conversion time and reduces the conversion efficiency while improving the pyrolysis coke yield, so how to predict the pyrolysis coke yield of the baked biomass by adopting a simple method is very important in industrial application as an index for optimizing the baking treatment process and as a reference for adjusting the working conditions of the boiler and the gasification reactor. In addition, the activated carbon with large specific surface area can be obtained after the activated treatment of the pyrolytic coke obtained after baking, and the activated carbon can be used for soil improvement, sewage treatment and other occasions. The prediction of the coke yield is beneficial to preparing a proper amount of coke, and can even directly predict the yield of the activated carbon under a specific process as a raw material for preparing the activated carbon. In the research at home and abroad so far, only a method suitable for predicting the pyrolysis coke yield of coal exists, the method has many required parameters and a complex model; but lacks a method for predicting biomass char yield.
Disclosure of Invention
In order to solve the problems in the prior art, it is an object of embodiments of the present application to provide a method of predicting the pyrolysis char yield of torrefied biomass.
Embodiments of the present application provide a method of predicting torrefied biomass pyrolysis char yield, comprising: performing aerobic baking on biomass to obtain a first solid product, performing anaerobic baking on biomass to obtain a second solid product, defining a baking quality yield = solid product quality/raw material quality after baking, and respectively obtaining a first baking quality yield during aerobic baking and a second baking quality yield during anaerobic baking according to a calculation formula of the baking quality yield;
putting the first solid product and the second solid product into a slow pyrolysis device for slow pyrolysisTesting to obtain fixed carbon content FC under anhydrous ashless base condition daf ；
Placing the first solid product and the second solid product into a fast pyrolysis device for fast pyrolysis experiments to obtain fast pyrolysis Jiao Yangpin, weighing the fast pyrolysis Jiao Yangpin to obtain fast pyrolysis coke quality, defining phase focus yield = coke quality/baked solid product quality, and absolute coke yield = relative coke yield x baked quality yield x 100%, wherein the relative coke yield and the absolute coke yield in the fast pyrolysis device can be obtained;
respectively taking the first baking quality yield and the second baking quality yield as independent variables, taking the fixed carbon content as a dependent variable, respectively establishing a prediction model of the coke yield of biomass under slow pyrolysis after aerobic baking and anaerobic baking, and establishing a prediction model of the coke yield of biomass under slow pyrolysis after baking under normal pressure and low oxygen atmosphere by combining the first baking quality yield and the second baking quality yield;
respectively taking the first baking quality yield and the second baking quality yield as independent variables, taking the relative coke yield and the absolute coke yield as dependent variables, respectively establishing a prediction model of the coke yield of the biomass under the fast pyrolysis after the aerobic baking and the anaerobic baking, and establishing a prediction model of the coke yield of the fast pyrolysis biomass after the baking in the normal pressure and low oxygen atmosphere by combining the first baking quality yield and the second baking quality yield.
Further improved, the slow pyrolysis device is a thermogravimetric analyzer.
Further improved, the fast pyrolysis device is a suspension burner.
Further improved, the biomass is hardwood.
Further improves, the first solid product has 9 types, correspondingly can obtain the first baking quality yield of 9 types of solids, the first solid product can obtain nine types of coke after the fast pyrolysis experiment or the slow pyrolysis experiment, and correspondingly can obtain 9 types of fixed carbon content FC daf、 9 relative focal yields and 9 absolute focal yields;
said firstThe second solid product has 5 kinds, and can correspondingly obtain the second baking quality yield of 5 kinds of solids, the first solid product can obtain five kinds of coke after fast pyrolysis experiment or slow pyrolysis experiment, and correspondingly obtain 5 kinds of fixed carbon content FC daf、 5 relative focal yields and 5 absolute focal yields.
Further improving, the fixed carbon content under the anhydrous ashless base condition is obtained by the following specific steps:
according to the data change relation of the mass of the first solid product and the second solid product with time in the slow heat decomposition experiment, the water (M) ad ) Volatile (VM) ad ) And Ash content (Ash) ad ) I.e. slow pyrolysis char yield FC ad ％＝100(％)-M ad (％)-VM ad (％)-Ash ad (％)；
And further the fixed carbon content FC can be obtained daf I.e. FC daf ＝FC ad /(100-M ad -Ash ad )×100。
Further improved, the prediction model under the condition of slow pyrolysis comprises:
fitting nine first baking quality yields of nine first solid products obtained during aerobic baking and corresponding nine fixed carbon contents to obtain a prediction model of the aerobic baked coke yield, wherein the prediction model is as follows
Slow pyrolysis char yield (daf,%) = -0.61 x first torrefaction mass yield +68; r is R 2 ＝0.91 (9)
Fitting five second baking quality yields of five first solid products obtained during anaerobic baking and corresponding five fixed carbon contents to obtain a prediction model of anaerobic baked coke yield, wherein the prediction model is that
Slow pyrolysis char yield (daf,%) = -0.31 x second torrefaction mass yield +47.2; r is R 2 ＝0.89 (8)
And the prediction model of the coke yield of the biomass after baking in the normal-pressure low-oxygen atmosphere is that
Slow pyrolysis char yield (daf,%) = -0.48 x torrefaction mass yield +59.6; r is R 2 ＝0.8 (7)
Further improved, the prediction model of coke yield under fast pyrolysis conditions is as follows:
fitting nine first baking quality yields of nine first solid products obtained during aerobic baking and corresponding nine relative coke yields to obtain a prediction model of the relative coke yields after aerobic baking, wherein the prediction model is as follows
The relative yield of fast pyrolysis coke = -0.33 x first torrefaction mass yield +41.6; r is R 2 ＝0.78 (5)
Fitting nine first baking quality yields of nine first solid products obtained during aerobic baking and corresponding nine absolute coke yields to obtain a prediction model of the absolute coke yields after aerobic baking, wherein the prediction model is as follows
Absolute yield of fast pyrolysis coke = -0.14 x first torrefaction mass yield +23.0; r is R 2 ＝0.83 (6)
Fitting the five second baking quality yields of the five first solid products obtained during the anaerobic baking and the corresponding five relative focal yields to obtain a prediction model of the focal yields after the anaerobic baking, wherein the prediction model is as follows
The relative yield of fast pyrolysis coke = -0.37 x second torrefaction mass yield +45.3; r is R 2 ＝0.95 (3)
Fitting the five second baking quality yields of the five first solid products obtained during the anaerobic baking and the corresponding five absolute coke yields to obtain a prediction model of the absolute coke yields after the anaerobic baking, wherein the prediction model is as follows
Absolute yield of fast pyrolysis coke = -0.14 x second torrefaction mass yield +22.7; r is R 2 ＝0.96 (4)
And a relative coke yield prediction model and an absolute coke yield prediction model after baking under normal pressure and low oxygen atmosphere can be obtained respectively:
relative yield of fast pyrolysis coke = -0.34 x baking quality yield +41.9; r is R 2 ＝0.81 (1)
Absolute yield of fast pyrolysis coke = -0.14 x torrefaction mass yield +22.7; r is R 2 ＝0.85 (2)
Compared with the prior art, the invention has the following beneficial effects:
according to the obtained baking quality yield, the fast pyrolysis coke yield in the biomass boiler can be predicted, so that a basis is provided for selecting the combustion condition of the biomass boiler, and the biomass burnout rate is improved. At the same time, the torrefaction quality yield is also used to predict the slow pyrolysis coke yield in a fixed bed, thereby facilitating the preparation of a sufficient amount of biomass coke for the preparation of activated carbon or providing a reference for directly predicting the activated carbon yield.
Drawings
Fig. 1 is a flow chart of a prediction method according to an embodiment of the present invention.
Fig. 2 is a predictive model of the fast pyrolysis coke yield (simulating the combustion conditions of a biomass boiler) provided by an embodiment of the invention.
FIG. 3 is a model of the prediction of slow pyrolysis char yield (fixed carbon content) provided by an embodiment of the present invention.
Detailed Description
For a better understanding of the present invention, the following examples are further illustrated, but are not limited to the following examples.
In the embodiment, a hard wood (lotus wood) in the south of China is used as a raw material, a certain number of lotus balls are placed in a ceramic crucible in each baking experiment, and after the temperature and atmosphere in the furnace reach set values, the raw material and the crucible are sent into a three-temperature-zone tube furnace for baking. The baking temperature of the experiment ranges from 200 ℃ to 300 ℃, the residence time ranges from 30min to 240min, and the oxygen concentration ranges from 0% to 10% by volume. And weighing the mass of the solid product before and after baking by an analytical balance, and calculating to obtain the baking mass yield. Definition of torrefaction quality yield is defined as the quality of the solid product/the quality of the feedstock after torrefaction. The biomass is subjected to aerobic baking and anaerobic baking, a product obtained after the aerobic baking is a first solid product, a product obtained after the anaerobic baking is a second solid product, and the first baking quality yield and the second baking quality yield can be correspondingly obtained according to a calculation formula of the baking quality yield. In this embodiment, the biomass used is lotus wood, 9 first solid products and 5 second solid products are produced, and the first baking quality yields of the 9 first solid products and the second baking quality yields of the 5 second solid products can be obtained respectively by the above formula. And carrying out pyrolysis experiments on the first solid product and the second solid product as experimental samples, wherein the pyrolysis experiments comprise a fast pyrolysis experiment and a slow pyrolysis experiment, and the pyrolysis experiments are respectively carried out on a suspension burner and a thermogravimetric analyzer.
The suspension burner simulates the actual combustion process of biomass fuel in a boiler, the measured temperature value in the boiler is 1226 ℃ under the wet base condition, and the measured oxygen concentration value is 3vol%. Since the suspension burner is equipped with a high-speed camera, the entire combustion process of the char particles can be observed, so that at the moment when the fuel particle volatile flame is extinguished, the experimenter immediately withdraws the residual solid char particles to the water cooling chamber, and after it has cooled to room temperature, the mass is then weighed with an analytical balance, whereby the char yield under high-temperature fast pyrolysis conditions can be obtained. Definition phase yield = coke mass/mass of solid product after baking, absolute coke yield = relative coke yield x baked mass yield x 100%, i.e. relative coke yield = coke particle mass/baked wood particle mass x 100% in this example. By the relative and absolute coke yield formulas, 9 relative and 9 absolute coke yields of 9 first solid products corresponding to 9 first baking quality yields, respectively, can be calculated, and 5 relative and 5 absolute coke yields of 5 second solid products corresponding to second baking quality, respectively, can be calculated, respectively.
Respectively taking the first baking quality yield and the second baking quality yield as independent variables, taking the relative coke yield and the absolute coke yield as dependent variables, respectively establishing a prediction model of the coke yield of the biomass under the fast pyrolysis after the aerobic baking and the anaerobic baking, and establishing a prediction model of the coke yield of the biomass under the fast pyrolysis after the normal-pressure low-oxygen atmosphere baking by combining the first baking quality yield and the second baking quality yield, wherein the prediction model comprises a relative coke yield prediction model and an absolute coke yield prediction model under the aerobic baking, a relative coke yield prediction model and an absolute coke yield prediction model under the anaerobic baking and a coke yield prediction model obtained by comprehensively considering the oxygen and the oxygen.
Specifically, the prediction model of coke yield under fast pyrolysis conditions is as follows:
fitting nine first baking quality yields of nine first solid products obtained during aerobic baking and corresponding nine relative coke yields to obtain a prediction model of the relative coke yields after aerobic baking, wherein the prediction model is as follows
The relative yield of fast pyrolysis coke = -0.33 x first torrefaction mass yield +41.6; r is R 2 ＝0.78 (5)
Fitting nine first baking quality yields of nine first solid products obtained during aerobic baking and corresponding nine absolute coke yields to obtain a prediction model of the absolute coke yields after aerobic baking, wherein the prediction model is as follows
Absolute yield of fast pyrolysis coke = -0.14 x first torrefaction mass yield +23.0; r is R 2 ＝0.83 (6)
Fitting the five second baking quality yields of the five first solid products obtained during the anaerobic baking and the corresponding five relative focal yields to obtain a prediction model of the focal yields after the anaerobic baking, wherein the prediction model is as follows
The relative yield of fast pyrolysis coke = -0.37 x second torrefaction mass yield +45.3; r is R 2 ＝0.95 (3)
Fitting the five second baking quality yields of the five first solid products obtained during the anaerobic baking and the corresponding five absolute coke yields to obtain a prediction model of the absolute coke yields after the anaerobic baking, wherein the prediction model is as follows
Absolute yield of fast pyrolysis coke = -0.14 x second torrefaction mass yield +22.7; r is R 2 ＝0.96 (4)
As shown in fig. 2, the first baking quality yield obtained by aerobic baking and the second baking quality yield obtained by anaerobic baking are simultaneously used as data points to be fitted, and collectively referred to as baking quality yield, and the relative coke yield and the absolute coke yield in fast pyrolysis are respectively subjected to least square fitting to obtain a relative coke yield prediction model and an absolute coke yield prediction model after baking under normal pressure and low oxygen atmosphere:
relative yield of fast pyrolysis coke = -0.34 x baking quality yield +41.9; r is R 2 ＝0.81 (1)
Absolute yield of fast pyrolysis coke = -0.14 x torrefaction mass yield +22.7; r is R 2 ＝0.85 (2)
Wherein R is 2 Representing the ratio of the sum of squares of the regression to the sum of squares of the total dispersion, representing the proportion of the total sum of squares of the dispersion that can be interpreted by the sum of squares of the regression. R is R 2 The closer to 1 between 0 and 1, the better the regression fit effect.
The preparation of slow pyrolysis coke is carried out on a standard fixed bed (thermogravimetric analyzer) according to the national standard for biomass industry analysis (GBT 28731-2012). Under nitrogen atmosphere, as the temperature in the furnace increases, the sample gradually removes moisture and volatiles, and the atmosphere is then switched to 5% o 2 And 95% N 2 The fixed carbon is gradually burned until only ash remains. According to the data change relation of the sample mass along with time, the moisture (M) in the sample can be obtained under the Air dry basis (ad) ad ) Volatile (VM) ad ) And Ash content (Ash) ad ) While the corresponding fixed carbon content (FC ad I.e. slow pyrolysis coke yield%) =100 (%) -M ad (％)-VM ad (％)-Ash ad (%) and the following. The fixed carbon content of the sample under the condition of Dry ash free (daf), namely FC, can be obtained by referring to a coal standard conversion formula daf ＝FC ad /(100-M ad -Ash ad ) X 100. By FC daf The fixed carbon content of 5 second solid products corresponding to 5 second baking quality yields in anaerobic baking and the fixed carbon content of 9 first solid products corresponding to 9 first baking quality yields in aerobic baking can be obtained respectively. Respectively taking the first baking quality yield and the second baking quality yield as independent variables, taking the fixed carbon content as dependent variables, respectively establishing a prediction model of the coke yield of the biomass under the slow pyrolysis after the aerobic baking and the anaerobic baking, and establishing a prediction model of the coke yield of the biomass under the slow pyrolysis after the baking under the normal pressure and low oxygen atmosphere by combining the first baking quality yield and the second baking quality yield.
Specifically, the prediction model under the condition of slow pyrolysis comprises:
fitting nine first baking quality yields of nine first solid products obtained during aerobic baking and corresponding nine fixed carbon contents to obtain a prediction model of the aerobic baked coke yield, wherein the prediction model is as follows
Slow pyrolysis char yield (daf,%) = -0.61 x first torrefaction mass yield +68; r is R 2 ＝0.91 (9)
Fitting five second baking quality yields of five first solid products obtained during anaerobic baking and corresponding five fixed carbon contents to obtain a prediction model of anaerobic baked coke yield, wherein the prediction model is that
Slow pyrolysis char yield (daf,%) = -0.31 x second torrefaction mass yield +47.2; r is R 2 ＝0.89 (8)
Combining mass yield and char yield in oxygen-free and oxygen-free torrefaction, a predictive model including mass yield after oxygen-free and oxygen-free torrefaction and slow pyrolysis char yield can be obtained
Slow pyrolysis char yield (daf,%) = -0.48 x torrefaction mass yield +59.6; r is R 2 ＝0.8 (7)
As can be seen from the above prediction model, the quality yield of the baked products has a good linear relationship with the fast pyrolysis coke yield (R is more than or equal to 0.78) after either anaerobic baking or aerobic baking 2 Not more than 0.96), and has good linear relation (R is not less than 0.8) with the relative yield of slow pyrolysis coke 2 Less than or equal to 0.91). Therefore, the relative/absolute coke yield of the fast pyrolysis coke and the slow pyrolysis coke yield can be obtained according to the simple and easily obtained baking quality yield and substituted into the fitted prediction model.
The difference between the relative and absolute coke yields is that the latter reacts to crosslink-char the chemical bonds between the biomass by torrefaction, promoting the secondary reaction in the pyrolysis process, leading to a true increase in pyrolysis coke. Whereas the relative coke yield can only represent an increase in the content of inert substances, the two meaning are different. Knowing the torrefaction quality yields, the end objective of both is to predict the char yield of fast pyrolysis (simulating biomass boiler combustion conditions).
The relative focus yield is increasedConcentration effects due to bake weight loss (i.e. water, CO 2 The precipitation of the iso-light volatiles, other inert components such as ash and fixed carbon relative concentrations increase), while absolute coke yield increases because torrefaction promotes cross-coking reactions between biomass functionalities, representing a true increase in coke yield. The relative/absolute coke yield is used as two ubiquitous evaluation indexes in published domestic and foreign documents, and has predicted value. The relative/absolute coke yield model of the fast pyrolysis can be used for predicting the coke yield in the biomass boiler and predicting the coke burn-out time, so that a basis is provided for adjusting the combustion working condition of the biomass boiler. The prediction model of the first torrefaction quality yield and the relative/absolute coke yield is suitable for predicting the biomass coke yield after aerobic torrefaction; the second baking quality yield and relative/absolute coke yield prediction model is suitable for predicting biomass coke yield after anaerobic baking; the data points of the first torrefaction mass yield and the second torrefaction mass yield are collectively referred to as torrefaction mass yield, which is least squares fitted with relative/absolute coke yield to yield a universal model for use in predicting relative/absolute coke yield of biomass after torrefaction in an atmospheric, low oxygen atmosphere. The slow pyrolysis coke (fixed carbon) is an index in biomass industrial analysis, can be used for evaluating the quality of biomass fuel properties, and the prediction model of the first baking quality yield and the slow pyrolysis coke yield is suitable for predicting the fixed carbon content of the biomass after aerobic baking; the prediction model of the second baking quality yield and the slow pyrolysis coke yield is suitable for predicting the fixed carbon content of the biomass after anaerobic baking; and performing least square fitting on the data points of the first baking quality yield and the second baking quality yield, which are collectively called the baking quality yield and the slow pyrolysis coke yield, so as to obtain a general model applied to the prediction of the fixed carbon content of the biomass after baking in the normal pressure and low oxygen atmosphere.
The shaded portions in fig. 2 and 3 are 95% confidence intervals for the overall fitting (i.e., fitting combining experimental data from anaerobic and aerobic baking) results, with measured data points falling within the intervals indicating greater reliability. When the torrefaction mass yield is at a low value (< 50%), the measured value of relative/absolute coke yield deviates from the 95% confidence interval, meaning that the present model has lower reliability of coke yield of biomass under conditions of predicting low torrefaction mass yield. However, under actual industrial application conditions, in order to reduce the energy consumption required by the torrefaction process and reduce the mass loss of biomass in the torrefaction process, the mass yield of the torrefied biomass is generally between 70% and 90%, and at this time, most of actually measured relative and absolute focal yield values are located in 95% confidence intervals of the prediction model, which indicates that the model can accurately predict the relative/absolute focal yield of the torrefied biomass under the industrial application conditions.
The invention is not related in part to the same or implemented in part by the prior art.
The foregoing is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Various equivalent changes and modifications can be made by those skilled in the art based on the above embodiments, and all equivalent changes and modifications made within the scope of the claims shall fall within the scope of the present invention.
Claims (8)
1. A method of predicting the pyrolysis char yield of torrefied biomass, comprising:
performing aerobic baking on biomass to obtain a first solid product, performing anaerobic baking on biomass to obtain a second solid product, defining a baking quality yield = solid product quality/raw material quality after baking, and respectively obtaining a first baking quality yield during aerobic baking and a second baking quality yield during anaerobic baking according to a calculation formula of the baking quality yield;
putting the first solid product and the second solid product into a slow pyrolysis device for a slow pyrolysis experiment to obtain a fixed carbon content FC under the condition of no water and no ash base daf The method comprises the steps of carrying out a first treatment on the surface of the Placing the first solid product and the second solid product into a fast pyrolysis device for fast pyrolysis experiments to obtain fast pyrolysis Jiao Yangpin, weighing the fast pyrolysis Jiao Yangpin to obtain fast pyrolysis coke quality, defining phase coke yield = coke quality/baked solid product quality, absolute coke yield = relative coke yield x baked quality yield x 100%,the relative and absolute coke yields in the fast pyrolysis unit can be obtained;
respectively taking the first baking quality yield and the second baking quality yield as independent variables, taking the fixed carbon content as a dependent variable, respectively establishing a prediction model of the coke yield of biomass under slow pyrolysis after aerobic baking and anaerobic baking, and establishing a prediction model of the coke yield of biomass under slow pyrolysis after baking under normal pressure and low oxygen atmosphere by combining the first baking quality yield and the second baking quality yield;
respectively taking the first baking quality yield and the second baking quality yield as independent variables, taking the relative coke yield and the absolute coke yield as dependent variables, respectively establishing a prediction model of the coke yield of the biomass under the fast pyrolysis after the aerobic baking and the anaerobic baking, and establishing a prediction model of the coke yield of the fast pyrolysis biomass after the baking in the normal pressure and low oxygen atmosphere by combining the first baking quality yield and the second baking quality yield.
2. A method of predicting the char yield of torrefied biomass as claimed in claim 1, wherein the slow pyrolysis device is a thermogravimetric analyzer.
3. A method of predicting the char yield of torrefied biomass as claimed in claim 1, wherein the fast pyrolysis device is a suspension burner.
4. The method of predicting the pyrolysis char yield of torrefied biomass of claim 1, wherein the biomass is hardwood.
5. A method of predicting the char yield of torrefied biomass of any one of claims 1-4,
the number of the first solid products is 9, the first baking quality yield of 9 solids can be correspondingly obtained, nine types of coke can be obtained after the first solid products are subjected to a fast pyrolysis experiment or a slow pyrolysis experiment, and 9 solids can be correspondingly obtainedCarbon content FC daf、 9 relative focal yields and 9 absolute focal yields;
the second solid products have 5 types, correspondingly can obtain the second baking quality yield of 5 solids, the first solid product can obtain five types of coke after the fast pyrolysis experiment or the slow pyrolysis experiment, and correspondingly can obtain 5 fixed carbon content FC daf、 5 relative focal yields and 5 absolute focal yields.
6. A method of predicting the char yield of torrefied biomass of claim 5,
the method for obtaining the fixed carbon content under the anhydrous ashless base condition comprises the following specific steps:
according to the data change relation of the mass of the first solid product and the second solid product with time in the slow heat decomposition experiment, the moisture M in the first solid product and the second solid product under the base condition can be obtained ad Volatile VM ad And Ash content Ash ad Slow pyrolysis coke yield FC ad ＝1-M ad -VM ad -Ash ad ；
And further the fixed carbon content FC can be obtained daf I.e. FC daf ＝FC ad /(1-M ad -Ash ad )。
7. The method of claim 5, wherein the predictive model under slow pyrolysis conditions comprises:
fitting nine first baking quality yields of nine first solid products obtained during aerobic baking and corresponding nine fixed carbon contents to obtain a prediction model of the aerobic baked coke yield, wherein the prediction model is as follows
Slow pyrolysis char yield (daf,%) = -0.61 x first torrefaction mass yield +68%; r is R 2 ＝0.91(9)
Fitting five second baking quality yields of five first solid products obtained during anaerobic baking and corresponding five fixed carbon contents to obtain a prediction model of anaerobic baked coke yield, wherein the prediction model is that
Slow pyrolysis char yield (daf,%) = -0.31 x second torrefaction mass yield +47.2%; r is R 2 ＝0.89(8)
And the prediction model of the coke yield of the biomass after baking in the normal-pressure low-oxygen atmosphere is that
Slow pyrolysis char yield (daf,%) = -0.48 x torrefaction mass yield +59.6%; r is R 2 ＝0.8(7)。
8. A method of predicting the char yield of torrefied biomass as claimed in claim 5, wherein the prediction model of the char yield under fast pyrolysis conditions is as follows:
fitting nine first baking quality yields of nine first solid products obtained during aerobic baking and corresponding nine relative coke yields to obtain a prediction model of the relative coke yields after aerobic baking, wherein the prediction model is as follows
The relative yield of fast pyrolysis coke = -0.33 x first torrefaction mass yield +41.6%; r is R 2 ＝0.78(5)
Fitting nine first baking quality yields of nine first solid products obtained during aerobic baking and corresponding nine absolute coke yields to obtain a prediction model of the absolute coke yields after aerobic baking, wherein the prediction model is as follows
Absolute yield of fast pyrolysis coke = -0.14 x first torrefaction mass yield +23.0%; r is R 2 ＝0.83(6)
Fitting the five second baking quality yields of the five first solid products obtained during the anaerobic baking and the corresponding five relative focal yields to obtain a prediction model of the focal yields after the anaerobic baking, wherein the prediction model is as follows
The relative yield of fast pyrolysis coke = -0.37 x second torrefaction mass yield +45.3%; r is R 2 ＝0.95(3)
Fitting the five second baking quality yields of the five first solid products obtained during the anaerobic baking and the corresponding five absolute coke yields to obtain a prediction model of the absolute coke yields after the anaerobic baking, wherein the prediction model is as follows
Absolute yield of fast pyrolysis coke = -0.14 x second torrefaction mass yield +22.7%; r is R 2 ＝0.96(4)
And a relative coke yield prediction model and an absolute coke yield prediction model after baking under normal pressure and low oxygen atmosphere can be obtained respectively:
relative yield of fast pyrolysis coke = -0.34 x baked quality yield +41.9%; r is R 2 Absolute yield = -0.14 x baked mass yield +22.7% of fast pyrolysis coke = 0.81 (1); r is R 2 ＝0.85(2)。
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