METHOD, APPARATUS, COMPUTER DEVICE AND STORAGE MEDIUM FOR DETERMINING ALTERNATIVE FUELS

Abstract

METHOD, APPARATUS, COMPUTER DEVICE AND STORAGE MEDIUM FOR DETERMINING ALTERNATIVE FUELS The present invention relates to a method, device, computer device and storage medium for determining an alternative fuel, the method comprising: obtaining a target fuel corresponding to a target cement kiln and a plurality of alternative component categories, property parameters, a maximum carrying capacity of an alternative fuel combination to be selected, as well as a fuel boundary condition, constructing an objective function and a constraint condition; Based on the objective function and the constraint conditions, calculating the initial alternative fuel combination ratio solution for each alternative fuel combination to be selected;using a non-dominated sequential genetic algorithm to optimize the initial alternative fuel combination ratio solution, and calculating the theoretical substitution ratio of each optimized alternative fuel combination; based on the theoretical substitution ratio, selecting a fuel combination from a plurality of alternative fuel combinations to be selected. Based on the theoretical substitution ratio, determining the alternative fuel component scheme corresponding to the target fuel from among the alternative fuel combinations to be selected. The invention solves the problem of fluctuation of working conditions in cement kilns due to the complexity of the composition of alternative fuels, and improves the accuracy and reliability of determining alternative fuels. Figure for abstract: none;

Description

Title of the invention: METHOD, APPARATUS, COMPUTER DEVICE AND STORAGE MEDIUM FOR DETERMINING ALTERNATIVE FUELS FIELD OF THE INVENTION

[0001] The present invention relates to the field of cleaner production technologies and more particularly to methods, devices, computer equipment and storage media for determining alternative fuels. CONTEXT OF THE INVENTION

[0002] The current energy structure is mainly powered by coal, which accounts for about 80% of the energy consumed in cement production. In recent years, the cement industry has accelerated technological innovation and implemented energy-saving and emission-reducing technologies to achieve green development of the cement industry. Among them, the development of technologies such as the joint disposal of industrial waste, municipal waste, and sludge, and the improvement of the utilization rate of alternative fuels can effectively reduce the carbon emissions per unit of cement product, but the difference in the quality of different alternative fuels may have an impact on the operation of the cement kiln system, and their quality control is necessary.Depending on the dosing point of the substitute fuels in the cement kiln, the requirements for their composition and properties are different. The kiln head, with its high ambient temperature, is the key element in clinker firing and must meet strict requirements for fuel calorific value, flame position and shape. It is mainly used to dose gaseous (landfill gas, decomposition gas, etc.), liquid, semi-solid and solid granular substitute fuels with high calorific value and sufficiently small and homogeneous particle size. The requirements for the quality of substitute fuels at the kiln outlet are not as strict, and larger solid substitute fuels can be added.

[0003] Currently, substitute fuels commonly used by cement plants include solid wastes such as plastics, used tires, wood, and rice husks, as well as semi-solid or liquid wastes such as sludge, waste oils, and solvents. Due to their complex composition, substitute fuels are likely to cause fluctuations in kiln operating conditions during batching, which affects the process clinker calcination process and the final quality of the clinker. In addition, organic components that may be contained in substitute fuels can lead to an increase in the amount of flue gas in the kiln and fluctuations in the composition of the flue gases, and therefore, how to determine the combination and ratio of substitute fuels is an issue that urgently needs to be addressed by field technicians. CONTENT OF THE INVENTION

[0004] In view of the above, the present invention provides a method, an apparatus, a computer device and a storage medium for determining a substitute fuel, in order to solve the problem of difficulty in determining the combination and ratio of the substitute fuel due to the complexity of the composition of the substitute fuel and the possible inclusion of organic components in the substitute fuel, which may cause an increase in the amount of flue gas in the furnace and fluctuations in the composition of the flue gas.

[0005] In a first aspect, the present invention provides a method for determining an alternative fuel, the method comprising: obtaining a target fuel corresponding to a target cement kiln and a plurality of alternative component categories, property parameters, maximum delivery capacity and fuel boundary conditions of a plurality of alternative fuel combinations to be selected, the alternative fuel combinations to be selected comprising at least two alternative component categories; constructing an objective function based on the alternative component categories, property parameters and maximum delivery capacity of the multiple alternative fuel combinations to be selected, and constructing constraints based on the fuel boundary conditions;calculating an initial alternative fuel combination ratio solution based on the objective function and the constraints to obtain the initial alternative fuel combination ratio solution for each of the alternative fuel combinations to be selected; and optimizing each of the initial alternative fuel combination ratio solutions using a non-dominated sequential genetic algorithm to obtain the initial alternative fuel combination ratio solution for the furnace, respectively, the optimized alternative fuel combination ratio solution for each alternative fuel combination to be selected is obtained;the theoretical replacement rate of each optimized combination of alternative fuels to be selected is calculated on the basis of the category of alternative components, the property parameter, the maximum delivery capacity and the; optimized solution of substitution fuel combination ratio for each substitution fuel combination to be selected; and, based on the theoretical substitution ratio, the theoretical substitution ratio of each substitution fuel combination to be selected is calculated based on the theoretical substitution ratio, based on the theoretical substitution ratio, the composition of the substitution fuels corresponding to the target cement kiln is determined from the multiple substitution fuel combinations to be selected.

[0006] The method for determining alternative fuels provided in this embodiment firstly obtains the alternative component categories, property parameters, maximum delivery capacity and fuel boundary conditions for the target fuel corresponding to the target cement kiln and a plurality of alternative fuel combinations to be selected, thereby improving the completeness and accuracy of determining alternative fuels and providing the necessary basic data for the following steps. Secondly, by constructing an objective function based on the alternative component categories, property parameters and maximum delivery capacity of the alternative fuel combinations to be selected, and constructing constraints based on the fuel boundary conditions,the reasonableness and validity of the evaluation of alternative fuel options are improved, the objective function can reflect the performance requirements of different alternative fuel combinations, and the constraints ensure the feasibility of alternative options, calculation of the initial solution of the ratio of the alternative fuel combination to be selected: the initial solution of the ratio of the alternative fuel combination to be selected for each alternative fuel combination to be selected is obtained by calculation based on the objective function and constraints, which improves the accuracy and reliability of the initial ratio solution and provides a good starting point for the subsequent optimization process. Then,The efficiency and accuracy of the optimization process are improved by using the non-dominant sorting genetic algorithm to optimize the ratio solution for each initial substitute fuel combination to be selected. The non-dominated sequential genetic algorithm is capable of performing crossover and mutation selection operations on the population according to the fitness function to gradually approach the optimal solution and obtain the theoretical substitution ratio of each optimized substitute fuel combination based on the substitute component category, property parameter, maximum delivery capacity and proportioning solution, optimized alternative fuel combinations to be selected, this improves the objectivity and accuracy of the comparison and selection of alternative fuel combinations. The theoretical substitution rate can reflect the degree of substitutability of different alternative fuel combinations with respect to the target fuel and provide a basis for the final determination. Finally, by determining the component scheme of the alternative fuel corresponding to the target fuel from a number of alternative fuel combinations to be selected based on the theoretical substitution rate, the practicability and feasibility of the finalized component scheme are improved, and the optimal alternative fuel combination is determined as the substitution scheme for practical application, which provides a reliable basis for subsequent industrial application.It solves the problem of difficulty in determining the combination and proportion of substitute fuels due to the complex composition of substitute fuels, which may contain organic components that may cause fluctuations in kiln operating conditions during dosing, which affects the clinker calcination process and the final quality of the clinker.

[0007] In summary, the method for determining substitute fuels provided by the present invention can effectively solve the problem of fluctuation of working conditions of cement kiln due to the complexity of composition of substitute fuels through the above-mentioned steps and technical effects, improve the accuracy and reliability of determining substitute fuels, and provide strong support for its practical application in cement kiln.

[0008] In an optional embodiment, before obtaining the alternative component category, property parameters, maximum delivery capacity and fuel boundary conditions for the target fuel and the plurality of alternative fuel combinations to be selected, the method further comprises: obtaining the alternative component category, property parameters, maximum delivery capacity and fuel boundary conditions for each alternative component category corresponding to the target cement kiln; determining a grouping rule for the alternative fuels based on the fuel boundary conditions;grouping the alternative components of the category based on the alternative component category, property parameters, maximum delivery capacity and grouping rule to obtain a plurality of alternative fuel combinations to be selected. ;

[0009] The method for determining alternative fuels provided in this embodiment improves the accuracy and completeness of a comprehensive understanding of alternative fuels by obtaining the alternative component categories, property parameters, maximum delivery capacity, and fuel boundary conditions for each alternative component category corresponding to the target cement kiln. This information forms the basis for subsequent grouping and combination. The rationality and efficiency of alternative fuel combinations are improved by determining grouping rules for the alternative fuels based on the fuel boundary conditions.Grouping rules can be established based on fuel type, delivery capacity, and other parameters to ensure the compatibility and complementarity of the components in the alternative fuel mix. The diversity and flexibility of alternative fuel combinations are improved by grouping alternative components based on alternative component categories, type parameters, maximum delivery capacity, and grouping rules. The grouping process can be adjusted according to actual needs and conditions to meet the specific requirements of different target cement kilns, enabling multiple alternative fuel combinations to be selected, thereby improving the diversity and feasibility of alternative fuel selection.These alternative fuel combinations to be selected can provide rich alternatives for the subsequent optimization process. In summary, the accuracy and reliability of determining alternative fuels can be further improved by the above-mentioned technical steps and effects before obtaining the alternative component categories, property parameters, maximum delivery capacity, and fuel boundary conditions for the target fuel and the plurality of alternative fuel combinations to be selected. By obtaining detailed information on the alternative components of each category, determining the grouping rules based on the fuel boundary conditions, and grouping the alternative components of the categories, it is possible to provide more comprehensive and reasonable alternatives for the subsequent optimization process.

[0010] In an optional embodiment, the objective function comprises a calorific value objective function and a deliverability objective function, and the objective function is constructed based on the alternative component categories, property parameters, and maximum deliverability of the plurality of alternative fuel combinations to be selected, comprising: defining the mass fraction corresponding to each alternative component category in the plurality of alternative fuel combinations to be selected as an objective independent variable; constructing the calorific value objective function based on the objective independent variable, the calorific value objective function is constructed based on the objective independent variable, the calorific value parameter in the alternative component categories; and the property parameters of the alternative fuel combinations to be selected, and the transport capacity objective function is constructed based on the objective independent variable and the maximum transport capacity of the alternative fuel combinations to be selected.

[0011] This embodiment provides a method for determining an alternative fuel by constructing a calorific value objective function, based on the calorific value parameter in the target independent variable, the alternative component category and the property parameter of the alternative fuel combination to be selected, which improves the ability of the objective function to evaluate the calorific value performance of the alternative fuel combination. The calorific value objective function can reflect the calorific value requirements of different alternative fuel combinations, and provide important performance indicators for the optimization process.By constructing the delivery capacity objective function based on the target independent variable, the maximum delivery capacity of the alternative fuel combination to be selected, the ability of the objective function to evaluate the delivery capacity of the alternative fuel combination is improved. The delivery capacity objective function reflects the delivery requirements of different alternative fuel combinations and ensures the feasibility of optimized alternative fuel combinations in practical applications. The accuracy and reliability of determining alternative fuels can be further improved by defining target independent variables, and constructing objective functions of calorific value and delivery capacity.These objective functions can be evaluated for different performance requirements, and provide effective guidance for the subsequent optimization process. At the same time, comprehensively considering various factors, such as calorific value and distribution capacity, can more comprehensively meet the needs of practical applications and improve the applicability and feasibility of alternative fuels.

[0012] In an optional embodiment, the initial alternative fuel combination ratio solutions to be selected are separately optimized using the non-dominated sorting genetic algorithm to obtain the optimized alternative fuel combination ratio solutions to be selected for each alternative fuel combination to be selected, comprising: setting the crossover operator in the non-dominated sorting genetic algorithm to be a simulated binary crossover operator, the variation operator to be an adaptive polynomial variation, and the selection operator to be a binary tournament selection; performing crossover and mutation operations on each initial alternative fuel combination ratio solution to be selected based on the non-dominated sorting genetic algorithm, respectively, to obtain an optimized alternative fuel combination ratio solution to be selected for each alternative fuel combination to be selected.

[0013] This embodiment provides a method for determining alternative fuels that improves the reliability and efficiency of crossover operations by setting a crossover operator in a non-dominated sorting genetic algorithm to a simulated binary crossover operator. The simulated binary crossover operator is capable of performing crossover operations on individuals based on a fitness function to generate new individuals, thereby increasing the diversity of the population. The flexibility and relevance of the mutation operation are improved by setting the mutation operator of the non-dominated sorting genetic algorithm to the adaptive polynomial mutation.Adaptive polynomial variation can adaptively adjust the variation probability according to the distribution and the evolution of the population's fitness, which ensures the diversity of the population and promotes the overall search ability of the algorithm. By defining the selection operator in the non-dominated sorting genetic algorithm as binary tournament selection, the competitiveness and accuracy of the selection operation are improved. Binary tournament selection can competitively select individuals based on the fitness function, which ensures the proportion of excellent individuals in the population and accelerates the convergence speed of the algorithm.The diversity and overall search capability of the optimization process are enhanced by performing crossover and mutation operations on each initial alternative fuel combination ratio solution to be selected based on the non-dominated sorting genetic algorithm. These operations can generate new and superior alternative fuel combination ratio solutions to be selected, which improves the reliability and validity of the finalized alternative fuel combinations. The resulting optimized alternative fuel combination ratio solutions for each alternative fuel combination to be selected improve the accuracy and reliability of determining alternative fuels. These optimized fuel combinations of . substitution provide a reliable basis for the subsequent determination of substitute fuel component solutions corresponding to the target fuels. The accuracy and reliability of determining substitute fuels can be further improved by defining appropriate mutation crossover and selection operators and optimizing the initial ratio solutions of substitute fuel combinations to be selected using a non-dominated sequential genetic algorithm. The selection and tuning of these operators can improve the overall search capability and convergence speed of the algorithm, and produce better dosage solutions of the substitute fuel combinations to be selected.This provides a reliable basis for the subsequent determination of component solutions of substitute fuels corresponding to the target fuels, and helps to solve problems in practical production.

[0014] In an optional embodiment, separately performing crossover and mutation operations on each initial alternative fuel combination ratio solution to be selected based on the non-dominated sorting genetic algorithm to obtain the optimized alternative fuel combination ratio solution to be selected for each alternative fuel combination to be selected, comprising: setting the crossover operator in the non-dominated sorting genetic algorithm to a simulated binary crossover operator, the mutation operator to an adaptive polynomial mutation, and the selection operator to a binary tournament selection performing crossover operations;and mutation on each initial alternative fuel combination ratio solution to be selected based on the non-dominated sorting genetic algorithm, respectively, to obtain a new alternative fuel combination ratio solution to be selected for each alternative fuel combination to be selected; using a penalty function to process the new alternative fuel combination ratio solution to be selected that violates the fuel boundary conditions, and until the stopping condition is satisfied, each optimized alternative fuel combination ratio solution is obtained. ;

[0015] This embodiment provides a method for determining alternative fuels that improves the constraints and limitations of alternative fuel combination rationing solutions to be selected by using a penalty function to process new alternative fuel combination rationing solutions that violate the fuel boundary conditions. The penalty function is capable of penalizing individuals appropriately based on the degree of violation of the boundary conditions, thereby ensuring that the optimized fuel mix solution alternative fuel combinations to be selected meets the constraints of practical applications. By combining the non-dominated sorting genetic algorithm and the penalty function processing method, it is possible to effectively process the dosage solution of the alternative fuel combination to be selected that violates the fuel boundary conditions, and obtain the optimized dosage solution of the alternative fuel combination to be selected that meets the requirements of practical applications. This method can achieve the goals of energy saving, emission reduction and sustainable development of cement kilns.

[0016] In an optional embodiment, the method further comprises: if the substitute component of the substitute fuel combination to be selected comprises a solid and a liquid, the fuel boundary condition further comprises: a solid-liquid ratio within a first predetermined range.

[0017] The method for determining a substitute fuel provided in this embodiment can improve production efficiency, product quality, and environmental performance, and reduce production costs by setting reasonable parameters for the solid-liquid ratio.

[0018] In an optional embodiment, the maximum conveying capacity is obtained based on the target cement kiln performing a feed volume test.

[0019] The present embodiment provides a method for determining a substitute fuel, in which the maximum conveying capacity is obtained by performing a feed volume test based on a target cement kiln, thereby solving a problem in actual production. In actual production, conveying capacity is one of the main constraints, and an accurate maximum conveying capacity can ensure that the substitute fuel can be conveyed stably and efficiently during the production process, and improve production efficiency and product quality.

[0020] In a second aspect, the present invention provides a device for determining a substitute fuel, the device comprising: an acquisition module for acquiring a target fuel corresponding to a target cement kiln and a plurality of alternative component categories, property parameters, maximum delivery capacities of a plurality of alternative fuel combinations to be selected, and a fuel boundary condition, the alternative fuel combinations to be selected comprising at least two alternative component categories; a construction module, for constructing an objective function based on the alternative component categories, the property parameters, and the maximum delivery capacity of the plurality of alternative fuel combinations to be selected, and to construct constraints based on the boundary conditions of the fuel; a first calculation module for obtaining an initial alternative fuel combination ratio solution to be selected for each of the alternative fuel combinations to be selected by calculation based on the objective function and the constraints, respectively; an optimization module which is used to optimize the ratio between the alternative fuel combinations to be selected and the alternative fuel combinations to be selected;according to the fuel boundary conditions, the optimization module is used to optimize the initial alternative fuel combination ratio solution using a non-dominated sequential genetic algorithm to obtain the optimized alternative fuel combination ratio solution for each alternative fuel combination to be selected;the second calculation module is used for calculating, on the basis of the alternative component category, the property parameter of each alternative fuel combination to be selected, the second calculation module is used for calculating a theoretical substitution rate for each optimized alternative fuel combination to be selected on the basis of the alternative component category, the property parameter, the maximum carrying capacity and the optimized alternative fuel combination ratio solution of each alternative fuel combination to be selected; and the determination module is used for determining, on the basis of the theoretical substitution rate, a component scheme of the alternative fuel corresponding to the target fuel among the plurality of alternative fuel combinations to be selected. ;

[0021] In a third aspect, the present invention provides a computing device comprising: a memory and a processor, the memory and the processor being communicatively coupled to each other, the memory storing computer instructions, the processor executing the computer instructions so as to perform the method of determining a substitute fuel of the first aspect described above, or any corresponding embodiment thereof.

[0022] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to cause the computer to execute the method of determining a substitute fuel of the first aspect described above or any corresponding embodiment thereof. DESCRIPTION OF FIGURES

[0023] In order to illustrate more clearly the technical solutions of the specific embodiments or prior art of the present invention, the following will briefly introduce the attached figures which are to be used in the description of the specific embodiments or prior art, and it will be obvious that the attached figures in the following description are some of the embodiments of the present invention, and that for the person having ordinary skill in the art, without creative work, other attachments can be obtained based on these figures, other figures can be obtained from these figures.

[0024] [Fig. 1] [Fig. 1] is a flowchart of a method for determining a substitute fuel according to one embodiment of the present invention;

[0025] [Fig.2] [Fig.2] is a flowchart of a method of determining another substitute fuel according to one embodiment of the present invention;

[0026] [Fig.3] [Fig.3] is a functional diagram of the structure of a device of determining a substitute fuel according to an embodiment of the present invention;

[0027] [Fig.4] [Fig.4] is a diagram of the hardware structure of a computing device according to one embodiment of the present invention.

[0028] DETAILED DESCRIPTION OF THE INVENTION

[0029] In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be described clearly and completely in the following, in conjunction with the drawings accompanying the embodiments of the present invention, and it is obvious that the described embodiments are part of the embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by a person skilled in the art without doing any creative work fall within the scope of protection of the present invention.

[0030] The current energy structure is mainly powered by coal, which accounts for about 80% of the energy consumed for cement production. In recent years, the cement industry has accelerated technological innovation, implemented energy-saving technologies, and emission reduction technologies to achieve green development of the cement industry. Among them, the development of technologies such as the joint disposal of industrial waste, municipal waste, and sludge, and the improvement of the utilization rate of alternative fuels can effectively reduce the carbon emissions per unit of cement product, but the difference in the quality of different alternative fuels may have an impact on the operation of the cement kiln system, and their quality control is necessary. According to the point When dosing alternative fuels in the cement kiln, the requirements for their composition and properties are different. The kiln head, with its high ambient temperature, is the key element in clinker firing and must meet strict requirements for fuel calorific value, flame position and shape. It is mainly used to dose gaseous (landfill gas, decomposition gas, etc.), liquid, semi-solid and solid granular alternative fuels with high calorific value and sufficiently small and homogeneous particle size. The requirements for the quality of alternative fuels at the kiln outlet are not as strict, and larger solid alternative fuels can be added.

[0031] Currently, substitute fuels commonly used by cement plants include solid wastes such as plastics, used tires, wood, and rice husks, as well as semi-solid or liquid wastes such as sludge, waste oils, and solvents. Due to their complex composition, substitute fuels are likely to cause fluctuations in kiln operating conditions during batching, which affects the clinker calcination process and the final quality of the clinker.In addition, the organic components that may be contained in the substitute fuels may cause an increase in the amount of flue gas in the furnace and fluctuations in the composition of the flue gases, and therefore, how to determine the combination and ratio of substitute fuels is a problem that urgently needs to be solved by field technicians.

[0032] The method for determining substitute fuels described in the present embodiment firstly comprises obtaining the categories of substitute components, property parameters, maximum delivery capacity and fuel boundary conditions for the target fuel corresponding to the target cement kiln and a plurality of combinations of substitute fuels to be selected, thereby improving the completeness and accuracy of the determination of substitute fuels and providing the basic data necessary for subsequent steps.Second, by constructing an objective function based on the alternative component categories, property parameters and maximum delivery capacity of the alternative fuel combinations to be selected, and constructing constraints based on the boundary conditions of the fuels, the reasonableness and validity of the evaluation of alternative fuel solutions are improved, the objective function reflecting the performance requirements of different alternative fuel combinations and the constraints ensuring the feasibility of the alternative solutions, calculating the initial alternative fuel combination ratio solution. to be selected: The initial ratio solution of the alternative fuel combination to be selected for each alternative fuel combination to be selected is obtained by calculation based on the objective function and constraints, which improves the accuracy and reliability of the initial ratio solution and provides a good starting point for the subsequent optimization process. Then, the efficiency and accuracy of the optimization process are improved by using the non-dominance sorting genetic algorithm to optimize the ratio solution for each initial alternative fuel combination to be selected.The non-dominated sequential genetic algorithm is capable of performing selection, crossover, and mutation operations on the population according to the fitness function to gradually approach the optimal solution and obtain the theoretical substitution rate of each optimized alternative fuel combination based on the category of substitution components, property parameter, maximum delivery capacity, and optimized dosage solution of the alternative fuel combinations to be selected, thereby improving the efficiency and accuracy of the comparison and selection of alternative fuels and reducing costs. The theoretical substitution rate can reflect the degree of substitutability of different alternative fuel combinations with respect to the target fuel and serves as the basis for the final determination.Finally, through the theoretical substitution rate based on a number of substitution fuel combinations to be selected from the target fuel corresponding to the substitution fuel component program, to improve the practicality and feasibility of the final determination of the component program, the optimal substitution fuel combination will be identified as a practical application of the substitution program for subsequent industrial applications, to provide a reliable basis. The problem of difficulty in determining the combination and proportion of the substitution fuel is solved due to the complex composition of the substitution fuel, which may contain organic components that may cause fluctuations in the kiln working conditions during the feeding process, thus affecting the clinker calcination process and the final quality of the clinker.In summary, the method for determining substitute fuels provided by the present invention can, through the above-mentioned steps and technical effects, effectively solve the problems caused by the complexity of the composition of substitute fuels, improve the accuracy and reliability of determining substitute fuels, and provide strong support for the practical application of the cement kiln.

[0033] In accordance with embodiments of the present invention, an embodiment of a method for determining a substitute fuel is provided, with the understanding that the steps illustrated in the flowchart of the accompanying drawings may be performed in a computer system such as a set of computer-executable instructions, and that, although a logical sequence is illustrated in the flowchart, the steps illustrated or described may, in some instances, be performed in a different order than that shown herein.

[0034] [Fig.l] is a flowchart of a method for determining a substitute fuel according to one embodiment of the present invention, which, as shown in [Fig.l], comprises the following steps:

[0035] Step S101, obtaining alternative component categories, property parameters, maximum delivery capacity and fuel boundary conditions for a target fuel corresponding to a target cement kiln, and a plurality of alternative fuel combinations to be selected, which include at least two alternative component categories.

[0036] More specifically, substitute fuels have different requirements for composition and properties depending on when they are introduced into the cement kiln. The high ambient temperature around the kiln head is a key element in the clinker firing process, which imposes strict requirements on the fuel calorific value, flame position and shape. It is mainly used for metering gaseous (landfill gas, decomposition gas, etc.), liquid, semi-solid and solid substitute fuels in pellet form having high calorific value, small particle size and sufficient homogenization. The kiln end has less stringent requirements for the quality of the substitute fuel to be fed, and solid substitute fuels with larger particle size can be fed.The target kiln is the kiln that currently requires the alternative fuel, and the target fuel is the fuel currently burned in the target kiln, usually coal. The alternative fuel combination to be selected is obtained by combining the various alternative components, such as rice and coffee husks, waste oil, and MB waste organic solvents. The alternative component category refers to the state of the alternative component, which can be solid or liquid. The property parameters are the physical properties of the target fuel and alternative components, such as calorific value, kinematic viscosity, chlorine content, ash, moisture, and total sulfur. The calorific value is measured and calculated according to the constant temperature calorimeter method in GB / T 213-2008 for . obtain the lower calorific value of pulverized coal and substitute fuels, and unit conversion is performed; moisture is measured according to GB / T 211-2017; particle size is measured according to GB / T 189-1997; and ash and volatile matter are measured according to GB / T 212-2008; whole sulfur is measured according to GB / T 214-2007; kinematic viscosity is measured according to the capillary method in GB / T 10247-2008; chlorine content is measured according to GB / T 3558-2014. The maximum conveying capacity of each fuel component is different for each kiln and depends on the kiln parameters, fuel parameters, and the efficiency of the machine that grinds the solid fuel. Fuel boundary conditions are related to the type of reciprocating components and differ for solid-solid, solid-liquid and liquid-liquid combinations.

[0037] For example, the boundary conditions of the solid substitute fuel may be specified as follows: particle size d < 30mm, ash AC < 40wt% by weight, volatile matter VC > 24wt% by weight, moisture < 40wt% by weight and full sulfur < 2.0wt% by weight. The boundary conditions for liquid substitute fuels are as follows: kinematic viscosity (20°C) between 3.0mm2 / s~8.0mm2 / s, Chlorine content < 1.5wt%, ash AC < 40wt%, moisture < 40wt%, and full sulfur < 2.0wt%.

[0038] In step S102, an objective function is developed based on the alternative component categories, property parameters, and maximum delivery capacity of the plurality of alternative fuel combinations to be selected, and constraints are developed based on the boundary conditions of the fuels.

[0039] More specifically, the objective function should have as its main targets the calorific value and the substitution rate of the alternative fuel mixture. The calorific value is a measure of the amount of heat released during the combustion of a fuel and is an important parameter for evaluating the energy efficiency. The substitution rate, on the other hand, indicates the relative utilization of the alternative fuels, i.e., the proportion of alternative fuels. The independent variable of the objective function is the proportion of the mass fraction of the different alternative components, i.e., the relative content of each alternative component in the fuel mixture. Specific steps of constructing the objective function: first, determine the form of the objective function. The weighted sum, the weighted product and other forms can be selected to construct the objective function.Then, depending on the natural parameters and the maximum delivery capacity of the combination of substitute fuels to be selected, they are substituted. in the objective function. For the calorific value objective, the total calorific value of the alternative fuel combination to be selected can be used as a term in the objective function. The total calorific value can be calculated by summing the products of the calorific values ​​and the mass fraction ratios of the individual substitution components. For the substitution rate objective, a target value can be set for the substitution rate and a deviation term from the actual substitution rate can be constructed as a term in the objective function. Set appropriate weighting coefficients for the calorific value objective and the substitution rate objective based on the actual demand. Construct constraints: Construct constraints based on the fuel boundary conditions.For example, for solid alternative fuels, constraints such as particle size, ash, volatile matter, moisture, and total sulfur can be defined. For liquid alternative fuels, constraints such as kinematic viscosity, chlorine content, ash, moisture, and total sulfur can be defined. Ensure that the selected alternative fuel combination meets all constraints.

[0040] Step S103, an initial solution of the ratio of the combination of alternative fuels to be selected for each of the combinations of alternative fuels to be selected is calculated based on the objective function and the constraints, respectively.

[0041] More specifically, a suitable optimization algorithm, such as a linear programming algorithm, a nonlinear programming algorithm, or a genetic algorithm, is used to solve the constructed objective function. By means of an iterative or search method, the mass fraction ratio of the alternative components that optimizes the objective function is found as a solution for the initial combination of alternative fuels to be selected.

[0042] Step S104, each initial alternative fuel combination ratio solution to be selected is separately optimized using a non-dominated sorting genetic algorithm to obtain an optimized alternative fuel combination ratio solution to be selected for each alternative fuel combination to be selected.

[0043] More specifically, the initial alternative fuel combination ratio solution to be selected is optimized using a non-dominated sequential genetic algorithm as follows: based on the initial alternative fuel combination ratio solution to be selected, an initial population is created, and each individual in the population represents an alternative fuel combination ratio solution, i.e., a mass fraction ratio of each substitution component. The fitness of each individual in the population is assessed and the value of its objective function is calculated. The smaller the objective function value, the more adaptable the substitution fuel combination. The individuals in the population are ranked in a non-dominant order based on the objective function value. The population is divided into levels, each containing non-dominant individuals. Non-dominant sorting ensures that the individuals in each stratum are optimal in terms of the objective function value. Based on the results of non-dominant sorting, individuals are selected for genetic manipulation. Individuals from higher levels are usually selected for crossover and mutation operations to generate new dosage solutions for substitution fuel combinations.Crossover and mutation operations are performed based on the selection operation. The crossover operation generates new individuals by exchanging parts of the genes of two individuals. The mutation operation, on the other hand, generates diversity by randomly changing some of the genes of an individual. Termination conditions are set, such as the maximum number of iterations or the degree of convergence of the objective function values ​​of the individuals in the population. When the termination condition is met, the algorithm stops the iteration. Depending on the stopping condition, the final population, i.e., the optimized solutions for the alternative fuel combination ratios to be selected, is produced. These solutions are the best alternative fuel combination ratios obtained after optimization by the genetic algorithm.The initial alternative fuel combination ratio solutions to be selected can be further optimized by the non-dominated sorting genetic algorithm to obtain alternative fuel combinations that better meet the target requirements. This can better meet the energy demand and production quality requirements of the cement kiln, and achieve the goals of energy saving, emission reduction and sustainable development.

[0044] Step S105, a theoretical substitution rate for each optimized substitution fuel combination to be selected is calculated based on the substitution component category, the property parameter, the maximum delivery capacity and the optimized substitution fuel combination ratio solution for each substitution fuel combination to be selected.

[0045] More specifically, the maximum delivery capacity and the calorific value of the alternative fuel combination to be selected are calculated on the basis of the categories of substitution components, the property parameters, the maximum delivery capacity and the optimized ratio solution of the alternative fuel combination to be selected, and the amount of The heat generated per hour by the alternative fuel combination to be selected is calculated based on the maximum distribution capacity and calorific value of the alternative fuel combination to be selected, and the target fuel quantity that can be replaced per hour can be calculated based on the maximum distribution capacity and calorific value of the alternative fuel combination to be selected, then it is possible to calculate the target fuel quantity that can be replaced per hour by the alternative fuel combination to be selected. For example: if coal powder is used as the target fuel and rice husk and coffee husk are the alternative fuel combinations to be selected, the maximum calorific value of the alternative fuel combinations is 3658.02 kcal / kg when the mass fractions of rice husk and coffee husk are 58wt% by weight and 42wt% by weight, respectively, and the maximum conveying capacity at this time is 9.52t / h. Compared with the test results on coal dust, according to the calorific value of conversion, in the case of 100% thermal conversion efficiency, 1.76t of this substitute fuel combination can theoretically replace It of coal dust, and according to the calculated maximum conveying capacity, this substitute fuel combination can theoretically achieve a substitution rate of 29.96%.

[0046] Step S106, based on the theoretical substitution rate, a component scheme of the substitution fuel corresponding to the target fuel is determined from among the plurality of combinations of substitution fuels to be selected.

[0047] More specifically, the substitution potential of each of the alternative fuel combinations to be selected is evaluated with respect to the target fuel based on the previously calculated theoretical substitution rate. A higher theoretical substitution rate indicates a higher substitution potential of the alternative fuel combination. Based on the evaluation of the theoretical substitution rate, the combinations having a higher substitution potential are selected from the multiple alternative fuel combinations to be selected. These selected alternative fuel combinations constitute the possible component solutions. In addition to the theoretical substitution rate, other factors such as fuel nature parameters (e.g., calorific value, humidity, ash, etc.), maximum delivery capacity, economic cost and availability may also be considered. Maximum delivery capacity, economic cost and availability may also be considered. These factors may influence the selection of final component options. Taking into account the theoretical substitution rate and other relevant factors, the component options of fuels of . Substitution solutions corresponding to the final target fuel are determined. These solutions must meet the energy demand and production quality requirements of the target cement kiln, while achieving the objectives of energy saving, emission reduction and sustainable development. The identified solutions are applied to real cement kilns for implementation and validation. The feasibility and effectiveness of the solutions are assessed by collecting and analyzing real operating data, and adjustments and optimizations are made if necessary.

[0048] Through the above steps, the alternative fuel component programs corresponding to the target fuels can be determined from a plurality of alternative fuel combinations to be selected. These solutions can meet the energy demand and performance requirements of cement kilns and contribute to achieving the goals of energy saving, emission reduction and sustainable development.

[0049] The method for determining substitute fuels provided in this embodiment firstly obtains substitute component categories, property parameters, maximum delivery capacity and fuel boundary conditions for the target fuel corresponding to the target cement kiln and a plurality of substitute fuel combinations to be selected, thereby improving the completeness and accuracy of the determination of substitute fuels and providing the necessary basic data for subsequent steps. Secondly, by constructing an objective function based on the alternative component categories, property parameters and maximum delivery capacity of the substitute fuel combinations to be selected, and constructing constraints based on the fuel boundary conditions,the reasonableness and validity of the evaluation of alternative fuel options are improved, the objective function can reflect the performance requirements of different alternative fuel combinations, and the constraints ensure the feasibility of alternative options, calculation of the initial solution of the ratio of the alternative fuel combination to be selected: the initial solution of the ratio of the alternative fuel combination to be selected for each alternative fuel combination to be selected is obtained by calculation based on the objective function and constraints, which improves the accuracy and reliability of the initial solution of the ratio and provides a good starting point for the subsequent optimization process. Then,The efficiency and accuracy of the optimization process are improved by using a non-dominated sequential genetic algorithm to optimize the ratio solution for each initial alternative fuel combination to be selected. The non-dominated sequential genetic algorithm is capable of performing selection, crossover and mutation operations on the population according to the fitness function, gradually approaching the optimal solution and obtaining the theoretical substitution rate of each optimized alternative fuel combination to be selected by calculating the theoretical substitution rate of each optimized alternative fuel combination based on the category of the alternative component of the alternative fuel combination to be selected, the nature parameter, the maximum delivery capacity and the optimized dosage solution of the alternative fuel combination to be selected, which improves the objectivity and accuracy of the comparison and selection of alternative fuel combinations,this improves the objectivity and accuracy of the comparison and selection of substitute fuel combinations. The theoretical substitution rate can reflect the degree of substitutability of different substitute fuel combinations with respect to the target fuel and provide a basis for the final determination. Finally, by determining the component scheme of the substitute fuel corresponding to the target fuel from a plurality of substitute fuel combinations to be selected on the basis of the theoretical substitution rate, the practicability and feasibility of the finalized component scheme are improved, and the optimal substitute fuel combination is determined as a substitution scheme for practical application, which provides a reliable basis for subsequent industrial application,It also solves the problem of difficulty in determining the combination and proportion of substitute fuels due to the complex composition of substitute fuels, which may contain organic components that may cause fluctuations in kiln conditions during the dosing process, which affects the clinker calcination process and the final quality of the clinker.

[0050] In summary, the method for determining substitute fuels provided by the present invention can effectively solve the problems caused by the complexity of the composition of substitute fuels by the above-mentioned steps and technical effects, improve the accuracy and reliability of determining substitute fuels, and provide strong support for the practical application of cement kilns.

[0051] [Fig. 2] is a flowchart of a method for determining a substitute fuel according to one embodiment of the present invention, which, as shown in [Fig. 2], comprises the following steps:

[0052] Step al, obtain the alternative component categories, property parameters, maximum delivery capacity and fuel boundary conditions for each alternative component category corresponding to the target cement kiln.

[0053] More specifically, the substitute component categories, property parameters, maximum transport capacity and fuel boundary conditions of the substitute components of each category corresponding to the target cement kiln are obtained in the manner described in step S101.

[0054] In step a2, a grouping rule for the substitute fuel is determined based on the fuel boundary conditions.

[0055] More specifically, the grouping rule here means that at least one of the property parameters of the alternative components must satisfy a boundary condition, and it is not possible to make the property parameters of the alternative fuel combination to be selected satisfy this boundary condition by individually adjusting the mass fractions of the alternative components, if the property parameters of the individual alternative components within the combination are outside a certain boundary condition.

[0056] Step a3, the alternative components of the category are grouped based on the alternative component category, property parameters, maximum delivery capacity and grouping rules to obtain a plurality of alternative fuel combinations to be selected.

[0057] More specifically, the alternative component categories determine whether the alternative components can be grouped together, for example, by eliminating alternative fuel combinations that will be chemically reactive. The property parameters as well as the grouping rules can filter out alternative fuel combinations whose property parameters do not satisfy the grouping rules. Alternative fuel combinations that have a lower maximum delivery capacity than coal are also eliminated.

[0058] The method for determining substitute fuels provided in this embodiment improves the accuracy and completeness of an overall understanding of substitute fuels by obtaining the substitute component categories, property parameters, maximum delivery capacity, and fuel boundary conditions for each substitute component category corresponding to the target cement kiln. This information forms the basis for subsequent grouping and combination. The rationality and efficiency of substitute fuel combinations are improved by determining grouping rules for the substitute fuels based on the fuel boundary conditions. The grouping rules can be established based on of fuel nature, delivery capacity and other parameters, to ensure the compatibility and complementarity of the components of the alternative fuel combination. The diversity and flexibility of alternative fuel combinations are improved by grouping the alternative components based on the categories of alternative components, nature parameters, maximum delivery capacity and grouping rules. The grouping process can be adjusted according to actual needs and conditions to meet the specific requirements of different target cement kilns, allowing multiple alternative fuel combinations to be selected, thereby improving the diversity and feasibility of alternative fuel selection.These alternative fuel combinations to be selected can provide a large number of options for the subsequent optimization process. In summary, the accuracy and reliability of determining alternative fuels can be further improved by the above-mentioned technical steps and effects before obtaining the alternative component categories, nature parameters, maximum delivery capacity and fuel boundary conditions for the target fuel and the plurality of alternative fuel combinations to be selected. By obtaining detailed information on the alternative components of each category, determining the grouping rules based on the fuel boundary conditions and grouping the alternative components of the categories, it is possible to provide more comprehensive and reasonable alternatives for the subsequent optimization process.

[0059] Step S201, the alternative component categories, property parameters, maximum delivery capacity and boundary conditions of the fuel are obtained for a target fuel corresponding to the target cement kiln and a plurality of alternative fuel combinations to be selected, the alternative fuel combinations to be selected comprising at least two alternative component categories.

[0060] More specifically, the alternative component categories, property parameters, maximum delivery capacity and fuel boundary conditions for each alternative component category corresponding to the target cement kiln are obtained as shown in step S101.

[0061] In step S202, an objective function is constructed based on the alternative component categories, property parameters, and maximum transport capacity of the plurality of alternative fuel combinations to be selected, and constraints are constructed based on the boundary conditions of the fuels.

[0062] More specifically, the objective function comprises a calorific value objective function and a delivery capacity objective function, and step S202 comprises:

[0063] Step S2021 consists of defining a mass fraction corresponding to each category of alternative component in the plurality of combinations of alternative fuels to be selected as a target independent variable.

[0064] Step S2022: constructing a calorific value objective function based on the target independent variable, the alternative component categories of the substitute fuel combinations to be selected and a calorific value parameter in the property parameter.

[0065] More specifically, an objective calorific value function is constructed based on the target independent variables and the calorific value parameters, for example, using the calorific value parameters as weights. The objective of the function is to maximize the total calorific value of the fuel mixture to meet the energy demand of the cement kiln.

[0066] Step S2023: construction of an objective delivery capacity function based on the target independent variable, the maximum delivery capacity of the combination of substitute fuels to be selected.

[0067] More specifically, an objective function of transport capacity is constructed based on the target independent variable and the maximum transport capacity. The objective of the function is to optimize the maximum transport capacity of the fuel combination to meet the requirements of the practical application.

[0068] Step S2024, construct constraints based on fuel boundary conditions.

[0069] More specifically, corresponding mathematical expressions are created for each fuel boundary condition. These mathematical expressions are used to describe the limits and relationships of alternative fuel combinations under different constraints.

[0070] This embodiment provides a method for determining a substitute fuel by constructing a calorific value objective function based on the calorific value parameter in the target independent variable, the substitute component category, and the property parameter of the substitute fuel combination to be selected, which improves the ability of the objective function to evaluate the calorific value performance of the substitute fuel combination. The calorific value objective function can reflect the calorific value requirements of different substitute fuel combinations and provide important performance indicators for the optimization process. By constructing the calorific value objective function, distribution based on the target independent variable, the maximum delivery capacity of the alternative fuel combination to be selected, the ability of the objective function to evaluate the delivery capacity of the alternative fuel combination is improved. The delivery capacity objective function can reflect the delivery requirements of different alternative fuel combinations, which ensures the feasibility of the optimized alternative fuel combinations in practical applications.

[0071] The accuracy and reliability of alternative fuel determinations can be further improved by defining objective independent variables and constructing objective functions of calorific value and delivery capacity. These objective functions can evaluate different performance requirements, and provide effective guidance for the subsequent optimization process. At the same time, by comprehensively considering various factors, such as calorific value and delivery capacity, it is possible to more comprehensively meet the needs of practical applications and improve the applicability and feasibility of alternative fuels.

[0072] In step S203, an initial solution of the ratio of the combination of alternative fuels to be selected for each of the combinations of alternative fuels to be selected is calculated based on the objective function and the constraints, respectively.

[0073] More specifically, the constructed mathematical model is solved using an appropriate optimization algorithm and calculation method, including an iterative method, linear programming, nonlinear programming, etc. The objective of the solution is to find the optimal rationing solution that satisfies the constraints and maximizes the objective function.

[0074] Step S204: Optimizing each of the initial substitute fuel combination ratio solutions to be selected using a non-dominated sorting genetic algorithm, and obtaining an optimized substitute fuel combination ratio solution for each of the substitute fuel combinations to be selected.

[0075] More specifically, step S204 comprises:

[0076] Step S2041 is to define the crossover operator in the non-dominated sorting genetic algorithm as a simulated binary crossover operator, the variation operator as an adaptive polynomial variation and the selection operator as a binary tournament selection.

[0077] More specifically, the simulated binary crossover operator is chosen as the crossover operator. The simulated binary crossover operator is a crossover operator commonly used in genetic algorithms for coding real numbers, which achieves the genetic recombination of two parent individuals by simulating the binary crossover process. The crossover probability determines the degree of utility of the crossover operator and must be adjusted on a case-by-case basis. Generally, high crossover probabilities increase population diversity but may also result in the loss of good genes, while lower crossover probabilities maintain the stability of good genes, but the population is not sufficiently diverse. Adaptive polynomial variation is chosen as the variation operator. Adaptive polynomial variation can adaptively adjust the variation probability according to the fitness values ​​of individuals, so that the variation operation has different degrees of influence in different fitness ranges. Binary tournament selection is chosen as the selection operator.Binary tournament selection is a selection operator based on the tournament selection strategy, which selects the individual with the best fitness for the genetic operation by randomly selecting two individuals for comparison. The tournament size determines the number of individuals involved in the comparison at each selection and should be adjusted accordingly. A larger tournament will increase the selection accuracy but may also decrease the selection efficiency; smaller tournaments may decrease the selection accuracy but are more efficient.

[0078] Step S2042, crossover and mutation operations are performed on each of the initial to-be-selected alternative fuel combination ratio solutions based on the non-dominated sorting genetic algorithm, respectively, to obtain an optimized to-be-selected alternative fuel combination ratio solution for each of the to-be-selected alternative fuel combinations.

[0079] More specifically, in the non-dominated sorting genetic algorithm, it is first necessary to create an initial population. This population consists of a plurality of individuals, each representing a dosage solution for a combination of alternative fuels to be selected. Crossover operations are performed on the individuals of the population according to a defined crossover operator (simulated binary crossover operator). The main objective of the crossover operation is to generate new gene combinations in order to increase the diversity of the population and find better solutions. Through the crossover operation, the genes of two parent individuals are recombined to generate two new offspring individuals. The mutation operation is performed on the individuals of the population according to the defined mutation operator (adaptive polynomial mutation).The main objective of the mutation operation is to increase the diversity of the population and to prevent the algorithm from falling into optimal solutions. local. Through the mutation operation, a part of an individual's genes is randomly modified to produce a new combination of genes. Selection operations are performed on the individuals in the population according to the ensemble selection operator (binary tournament selection). The main objective of the selection operation is to retain the most fit individuals and eliminate the least fit ones. Through the selection operation, the most fit individuals are selected for genetic manipulation to gradually approach the optimal solution. In each generation of the population, individuals are sorted according to their dominance relationships. Non-dominance sorting is a hierarchical sorting method in which the individuals in the population are divided into different levels according to their dominance relationships, and the individuals at each level do not dominate each other.Non-dominated sorting is used to find the optimal solution in the current population. The crossover, mutation, selection, and non-dominant sorting operations are repeated until the termination conditions (e.g., reaching a predefined maximum number of iterations or a satisfactory solution) are met. At each iteration, the individuals in the population evolve through the genetic operations and gradually approach the optimal solution. After the iterative optimization, the algorithm produces the final optimization results, i.e., the optimized proportional solutions of the alternative fuel combinations to be selected for each alternative fuel combination to be selected. These ratio solutions will be used in subsequent practical applications as the best alternative fuel combination solutions that satisfy the constraints and maximize the objective function.

[0080] In this case, a solid-solid substitute fuel combination to be selected, a solid-liquid substitute fuel combination to be selected, and a liquid-liquid substitute fuel combination to be selected, respectively, are given as an example, and the process of calculating the theoretical replacement rate is as follows:

[0081] Example 1:

[0082] Approach to improve fuel substitution rates through theoretical modeling using rice husk and coffee husk as substitute fuels for pulverized coal in a cement kiln, with the relevant properties shown in Table 1:

[0083] [Tables 1] Form Calori fic value kcal / kg Moisture wt% Particle size mm Ash wt% Volatile matter wt% Full sulfur wt% Coal dust 6458 2.3 1.6 9.38 34.07 0.68 Rice husk 3488 12 2.54 23.03 64.14 0.17 Coffee shell 3894 12.33 25 7 56.29 4.45

[0084] The calorific value is calculated according to the constant temperature calorimeter method of GB / T 213-2008 to obtain the low-level calorific value of pulverized coal and substitute fuels, and unit conversion is performed; the moisture is determined according to GB / T 211-2017; and the particle size is determined according to GB / T 189-1997; the ash and volatile matter were determined according to GB / T 212-2008; the total sulfur was determined according to GB / T 214-2007. Tests conducted in the production process revealed that the maximum conveying capacity of rice husk and coffee husk was 10 t / h and 4 t / h respectively, and the average conveying capacity of coal dust was 18 t / h.

[0085] Define the optimization problem: the mass fractions of rice husk and coffee husk are xl and x2 respectively, and the objective function is defined as follows:

[0086] f1 = 3488% + 3894% / \ f2 = 4% / X| + 4# \7

[0087] Define the constraints as follows:

[0088] g^ 12%+ 12.33% <40 / \ g2 = 2.54% + 25% < 30 g3 = 23.03% + 7% < 40 g4 - - 64.14% - 56.29% < - 24 4- g5 = 0.17% + 4.45% < 40 # (

[0089] The NSGA-II algorithm was used to optimize the mass fractions of rice husk and coffee husk using real number coding, setting the crossover operator to simulate the binary crossover SBX, the operator variation on adaptive polynomial variation and the selection operator on binary tournament selection.

[0090] The boundary conditions relating to moisture, particle size, ash and volatile matter of the above substitute fuels having been satisfied, only the boundary condition relating to total sulfur <2.0 wt% needs to be considered, so that the constraint function is set to g(xl,x2)=0.17xl+4.45x2<2.0, if the constraint condition is satisfied, the constraint violation value is 0, if the constraint is not respected, the constraint violation value is -100* g(xl,x2).

[0091] The maximum calorific value of the combined substitute fuel was calculated to be 3658.02 kcal / kg for a mass fraction of 58wt% by weight and 42 wt% by weight of rice husk and coffee husk, respectively, while the maximum delivery capacity was 9.52t / h.

[0092] Comparing the results of the coal dust test, converting according to the calorific value, in the case of 100% thermal conversion efficiency, 1.76 t of this substitute fuel combination can theoretically replace 1 t of coal dust, and according to the calculated maximum transport capacity, the replacement rate of this substitute fuel combination can theoretically reach 29.96%.

[0093] Example 2:

[0094] A method for improving fuel substitution rate by theoretical modeling using waste oils and waste organic solvents MB as substitute fuels for pulverized coal in cement kilns, with the relevant properties shown in Table 2:

[0095] [Tables2] Form Calori fic value kcal / kg Kinematic viscosity mm 2 / s Chlorine content wt% Ash wt% Moisture wt% Full sulphur wt% Coal dust 6495 / / 1.8 9.80 33.71 Used oil 9002 5.3 0.01 0.2 5 3 Used organic solvent MB 5256 4.4 0.4 1.6 21 0.2

[0096] The calorific value was measured and calculated according to the thermostatic calorimeter method described in GB / T 213-2008 to obtain the low-level calorific value of pulverized coal and substitute fuels, and the unit conversion was carried out; the kinematic viscosity was measured according to the capillary method described in GB / T 10247-2008; the chlorine content was measured in accordance with GB / T 3558-2014; the ash content was measured in accordance with GB / T 212-2008; the moisture was measured in accordance with GB / T 211-2017; and the total sulfur was measured in accordance with GB / T 214-2007. Tests conducted in the production process revealed that the maximum conveying capacity of waste oil and waste organic solvent MB was 0.7t / h and 1.5t / h, respectively, and the average conveying capacity of coal powder was 15.4t / h.

[0097] Define the optimization problem: the mass fractions of used oil and used organic solvent MB are xl and x2 respectively, and the objective function is defined as follows:

[0098] £^9002^5 + 5256¾ \ f2 = 0.7*x1 / x2+0.7 V /

[0099] Define the constraints as follows:

[0100] -53%-4.4*X2< -3M g? = 5.3¾ + 4.4 *x2 < 8 g3 = 0.01%+ 0.4*x2 <1.5 g, 0.2% +16% < 40 4 g5 = 5% + 21% < 40 g6 = 3% + 0.2%<2 (

[0101] The NSGA-II algorithm was used to optimize the mass fractions of used oil and used organic solvent MB using real number coding, setting the crossover operator to the simulation of the binary crossover SBX, the variation operator to the adaptive polynomial variation and the selection operator to the binary tournament selection.

[0102] Thus, the combined substitute fuel has a maximum calorific value of 7664.68 kcal / kg at a mass fraction of 64.3wt% and 35.7wt% of waste oil and waste organic solvent MB, respectively, at a time when the maximum delivery capacity is 1.09t / h.

[0103] Comparing the results of the coal dust test and converting them according to the calorific value, in the case of 100% thermal conversion efficiency, 0.85t of this substitute fuel combination can theoretically replace It of coal dust, and according to the calculated maximum transport capacity, the replacement rate of this substitute fuel combination can theoretically reach 8.35%.

[0104] Example 3:

[0105] A method for improving the fuel substitution rate through theoretical modeling using dry treated sludge and CA waste solvents as substitute fuels for pulverized coal, with the relevant properties shown in Table 3:

[0106] [Tables3] Form Calorific value kc al / kg Moisture wt% Particle size mm Ash wt% Volatile matter wt% Full sulfur wt% Kinematic viscosity mm2 / s Chlorine content wt% Coal dust 6482 2.57 1.4 8.97 35.24 0.64 / / Dry sludge 4061 24.99 30 46.29 35.96 0.59 / 0.28 Solvent used CA 3801 28 / 1.6 / 0.2 6.4 0.4

[0107] The calorific value is measured and calculated according to the constant temperature calorimeter method in GB / T 213-2008 to obtain the low-level heat of pulverized coal and substitute fuels, and unit conversion; moisture is measured according to GB / T 211-2017; particle size is measured according to GB / T 189-1997; ash, volatile fraction is measured according to GB / T 212-2008; complete sulfur is measured according to GB / T 214-2007; kinematic viscosity is measured according to the capillary method in GB / T 10247-2008; and chlorine content is measured according to GB / T 3558-2014. Tests conducted in the production process revealed that the maximum conveying capacity of drying sludge and CA waste solvents was 4.17t / h and 6.35t / h respectively, and the average conveying capacity of coal dust was 16t / h.

[0108] Define the optimization problem: the mass fractions of dried sludge and used solvent CA are xl and x2 respectively, and the objective function is defined as follows:

[0109] = 4061*Xj+ 3801^X2 / \ f2 = 4.17% / x2+4.17\ /

[0110] The constraints are defined as follows: [YES] g1 = 24.99*Xj + 28%<40 g? = 46.29% + 1.6% 40 g3 = 0.59*Xj + 02% 2 g4 = 0.28% +0.4% < 15 g =X] / x2^0.8 g6= -xjx2< -0.2

[0112] The mass fractions of dried sludge and CA waste solvent were optimized using the NSGA-II algorithm with real-number coding, setting the crossover operator to SBX binary crossover simulation, the variation operator to adaptive polynomial variation, and the selection operator to binary tournament selection.

[0113] Thus, the combined substitute fuel has a maximum calorific value of 4024.41 kcal / kg at a mass fraction of 85.9 wt% and 14.1 wt% of dried sludge and CA waste solvent, respectively, while the maximum delivery capacity is 4.85t / h.

[0114] Comparing the results of the coal dust test and converting them according to the calorific value, in the case of 100% thermal conversion efficiency, 1.6It of this substitute fuel combination can theoretically replace 1 ton of coal dust, and according to the calculated maximum transport capacity, the replacement rate of this substitute fuel combination can theoretically reach 18.82%.

[0115] The method for determining alternative fuels provided in this embodiment improves the reliability and efficiency of the crossover operation by setting the crossover operator in the non-dominated sorting genetic algorithm to a simulated binary crossover operator. The simulated binary crossover operator is capable of performing crossover operations on the individuals based on a fitness function to generate new individuals, thereby increasing the diversity of the population. The flexibility and relevance of the mutation operation are improved by setting the mutation operator of the non-dominated sorting genetic algorithm to the adaptive polynomial mutation.Adaptive polynomial variation can adaptively adjust the variation probability according to the fitness distribution and population evolution, which ensures the diversity of the population and promotes the global search ability of the algorithm. By defining the selection operator in the non-dominated sorting genetic algorithm as binary tournament selection, the competitiveness and accuracy of the selection operation are improved. Binary tournament selection. enables competitive selection of individuals based on the fitness function, which ensures the proportion of excellent individuals in the population and accelerates the convergence of the algorithm. The diversity and overall search capability of the optimization process are improved by performing crossover and mutation operations on each initial alternative fuel combination ratio solution to be selected based on the non-dominated sorting genetic algorithm. These operations generate new and superior alternative fuel combination ratio solutions to be selected, which improves the reliability and validity of the finalized alternative fuel combinations.The final optimized alternative fuel combination ratio solutions for each alternative fuel combination to be selected improve the accuracy and reliability of alternative fuel determination. These optimized alternative fuel combinations provide a reliable basis for the subsequent determination of alternative fuel component solutions corresponding to the target fuels. The accuracy and reliability of alternative fuel determination can be further improved by defining appropriate crossover, mutation, and selection operators and optimizing the initial alternative fuel combination ratio solutions using a non-dominated sequential genetic algorithm.The selection and tuning of these operators can improve the overall search capability and convergence speed of the algorithm, and produce a better dosage solution of the alternative fuel combination to be selected. This provides a reliable basis for the subsequent determination of the solutions of the alternative fuel components corresponding to the target fuels and helps to solve problems in practical production.

[0116] Step S205, a theoretical substitution rate of each optimized substitution fuel combination to be selected is obtained by calculating the theoretical substitution rate of each optimized substitution fuel combination to be selected on the basis of the substitution component category, the property parameter, the maximum carrying capacity and the optimized substitution fuel combination dosage solution of each substitution fuel combination to be selected. For details, see step S105 of the embodiment of [Fig.l], which will not be repeated here.

[0117] Step S206, based on the theoretical substitution rate, a component scheme of the substitution fuel corresponding to the target fuel is determined from among the plurality of combinations of substitution fuels to be selected. See step S106 of the embodiment of [Fig.l] for details, which will not be repeated here.

[0118] In some embodiments, step S204 above may be continued using a penalty function to process new substitute fuel combination dosing solutions that violate the fuel boundary conditions until a termination condition is satisfied, to obtain an optimized substitute fuel combination dosing solution for the substitute fuels to be selected.

[0119] More specifically, to address new alternative fuel combination rationing solutions to be selected that violate fuel boundary conditions, a penalty function approach can be used. A penalty function is a way to address constraints in an optimization algorithm, whereby a solution violating a constraint is penalized by adding a constraint-related term to the objective function to steer the algorithm toward a solution that satisfies the constraint, and a penalty function can be introduced into a non-dominated sequential genetic algorithm to address the new alternative fuel combination rationing solution to be selected that violates fuel boundary conditions.At each iteration, the corresponding penalty value is calculated for individuals that violate the fuel boundary conditions based on their degree of constraint violation and is added to the fitness function. In this way, the value of the constraint-violating solution in the fitness function is modified, allowing it to be eliminated or given lower priority in the selection operation. Through the penalty function processing, the non-dominated sorting genetic algorithm is able to gradually evolve towards solutions that satisfy the fuel boundary conditions. During the iteration process, the gene combinations of individuals are continuously adjusted to gradually approach the solution that satisfies all constraints through crossover, mutation, and selection operations.Finally, when the termination condition is met, the algorithm produces the optimized alternative fuel combination ratio solutions for each alternative fuel combination to be selected, which will satisfy the fuel boundary conditions.

[0120] This embodiment provides a method for determining substitute fuels that improves the constraints and limitations of the rationing solutions of the substitute fuel combinations to be selected by using a penalty function to process new rationing solutions of the substitute fuel combinations that violate the boundary conditions of the fuels. The penalty function is capable of penalizing individuals appropriately based on the degree of violation of the boundary conditions, which which ensures that the optimized solution for dosing the alternative fuel combinations to be selected meets the constraints of practical applications. By combining the non-dominated sorting genetic algorithm and the penalty function processing method, it is possible to effectively process the solution for dosing the alternative fuel combination to be selected that violates the fuel boundary conditions and obtain the optimized solution for dosing the alternative fuel combination to be selected that meets the requirements of practical applications. This method can achieve the goals of energy saving, emission reduction and sustainable development of cement kilns.

[0121] In some optional embodiments, the method for determining the substitute fuel further comprises: if the alternative component of the substitute fuel combination to be selected comprises solids and liquids, the fuel boundary condition further comprises: a solid-liquid ratio within a first predetermined range.

[0122] Specifically, to feed the combination of solid and liquid substitute fuels, it is necessary to add the following boundary condition: the solid-liquid ratio is between 20% ~ 80% based on the above-mentioned boundary condition. When setting the solid-liquid ratio parameter, it is necessary to comprehensively consider factors such as process conditions, product properties, raw material characteristics, operational stability, economic factors, and environmental protection requirements.

[0123] The method for determining a substitute fuel provided in this embodiment can improve production efficiency, product quality and environmental performance, and reduce production costs by setting reasonable parameters for the solid-liquid ratio.

[0124] In some optional embodiments, in the method for determining the substitute fuel, the maximum carrying capacity is obtained based on a target cement kiln performing a feed volume test.

[0125] In particular, cement kiln parameters are important determinants of the maximum fuel component delivery capacity; different types and sizes of cement kilns have different combustion requirements and capacities, and therefore require different amounts of fuel to maintain their proper operation. For example, larger kilns need more fuel to provide sufficient heat and energy, and therefore their fuel delivery capacity is generally higher than that of smaller kilns. Different types of fuel (coal, oil, gas, etc.) have different physical and chemical properties, such as density, viscosity and calorific value. These properties affect the mode (e.g., piping, pumping, etc.) and flow rate of the fuel, which in turn affects its maximum conveying capacity. For example, highly viscous fuels may require more powerful pumps to overcome their viscosity and ensure smooth conveying. Finally, the efficiency of the grinding unit can also impact the ability to convey fuel components. In some cement kilns, solid fuels such as coal must be ground for better combustion. The efficiency of the grinding unit determines the size and distribution of fuel particles, which affects their conveying and combustion characteristics.If the inefficiency of the grinding unit results in fuel particles that are too large or too small, this can affect the fuel conveying capacity, as particles that are too large can cause clogging or uneven flow, while particles that are too small can cause uneven conveying due to too good a flow. Therefore, the maximum conveying capacity of the target fuel and each alternative component is based on the target furnace feed test, during which the maximum hourly conveying capacity is measured.

[0126] The present embodiment provides a method for determining a substitute fuel, in which the maximum conveying capacity is obtained by performing a feed volume test based on a target cement kiln, thereby solving a problem in actual production. In actual production, conveying capacity is one of the main constraints, and an accurate maximum conveying capacity can ensure that the substitute fuel can be conveyed stably and efficiently during the production process, and improve production efficiency and product quality.

[0127] In this embodiment, there is also provided an alternative fuel determination device for carrying out the above embodiments and the preferred embodiments, which have already been described without further elaboration. As used hereinafter, the term "module" may be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software form, an implementation in hardware form, or a combination of software and hardware, is also possible and contemplated.

[0128] This embodiment provides a device for determining substitute fuels, as illustrated in [Fig.3], which comprises:

[0129] Acquisition module 301, for acquiring alternative component categories, property parameters, maximum delivery capacity and fuel boundary conditions for a target fuel and a plurality of combinations of alternative fuels to be selected depending on the target cement kiln, the combinations of alternative fuels to be selected comprising at least two categories of alternative components;

[0130] A construction module 302, which allows to construct an objective function based on the alternative component categories, the property parameters and the maximum delivery capacity of a plurality of alternative fuel combinations to be selected, and to construct constraints based on the boundary conditions of the fuels;

[0131] The first calculation module 303 makes it possible to obtain an initial solution of the ratio of the combination of substitute fuels to be selected for each combination of substitute fuels to be selected, on the basis of the objective function and the constraint conditions, respectively;

[0132] The optimization module 304 is used to optimize each initial alternative fuel combination ratio solution to be selected using a non-dominated sorting genetic algorithm, and to obtain an optimized alternative fuel combination ratio solution for each alternative fuel combination to be selected;

[0133] A second calculation module 305 for calculating a theoretical substitution rate for each optimized substitution fuel combination to be selected based on the substitution component category, the property parameter, the maximum delivery capacity and the optimized substitution fuel combination ratio solution for each substitution fuel combination to be selected;

[0134] Determination module 306, making it possible to determine, on the basis of a theoretical substitution rate, a scheme of components of a substitution fuel corresponding to a target fuel among a plurality of combinations of substitution fuels to be selected.

[0135] This embodiment provides a device for determining a substitute fuel. Firstly, by obtaining the alternative component categories, property parameters, maximum delivery capacity and boundary conditions of the target fuel corresponding to the target cement kiln and the plurality of alternative fuel combinations to be selected, the completeness and accuracy of the determination of the substitute fuel are improved, and the necessary basic data are provided for the subsequent steps. Secondly, the rationality and efficiency of the evaluation of the substitute fuel system are improved by constructing the objective function based on the alternative component categories, property parameters and maximum delivery capacity of the fuel combinations. of substitution to be selected, and by constructing constraints based on the fuel boundary conditions, where the objective function reflects the performance requirements of different substitution fuel combinations, and the constraints ensure the feasibility of the substitution system, and the calculation of the initial substitution fuel combinations to be selected for the ratio solution is carried out. Ratio solution: The initial ratio solution for each substitution fuel combination to be selected is obtained by calculation based on the objective function and constraints, which improves the accuracy and reliability of the initial ratio solution and provides a good starting point for the subsequent optimization process.Then, the efficiency and accuracy of the optimization process are improved by using the dominance-free sorting genetic algorithm to optimize the ratio solution for each initial alternative fuel combination to be selected.The non-dominated sorting genetic algorithm can gradually approach the optimal solution by selecting, crossing and mutating the population according to the fitness function, and the theoretical substitution rate of each optimized substitution fuel combination can be obtained by calculating the theoretical substitution rate of each optimized substitution fuel combination based on the substitution component category, nature parameter, maximum delivery capacity and optimized dosage solution of each substitution fuel combination, which improves the objectivity and accuracy of the comparison and selection of substitution fuel combinations. This improves the objectivity and accuracy of the comparison and selection of substitution fuel combinations.The theoretical substitution rate can reflect the degree of substitutability of different alternative fuel combinations with respect to the target fuel and provide a basis for the final determination. Finally, by determining the alternative fuel component scheme corresponding to the target fuel from a number of alternative fuel combinations to be selected based on the theoretical substitution rate, the practicality and feasibility of the finalized component scheme are improved, and the optimal alternative fuel combination is determined as the substitution scheme for practical application, which provides a reliable basis for subsequent industrial application.It solves the problem of difficulty in determining the combination and proportion of substitute fuels due to the complex composition of substitute fuels, which may contain organic components that may cause fluctuations in kiln operating conditions during dosing, which affects the clinker calcination process and the final quality of the clinker.

[0136] In some optional embodiments, the substitute fuel determination device comprises:

[0137] A pre-acquisition module for acquiring the alternative component categories, property parameters, maximum delivery capacity and fuel boundary conditions for each alternative component category corresponding to the target cement kiln;

[0138] A rule determination module for determining a grouping rule for the substitute fuel based on the boundary conditions of the fuel;

[0139] A grouping module for grouping alternative component categories based on the alternative component categories, property parameters, maximum delivery capacity, and grouping rules to obtain a plurality of alternative fuel combinations to select from.

[0140] This embodiment provides a substitute fuel determination device that improves the accuracy and completeness of an overall understanding of substitute fuels by obtaining the substitute component categories, property parameters, maximum delivery capacity, and fuel boundary conditions for each substitute component category corresponding to the target cement kiln. This information forms the basis for subsequent grouping and combination. The rationality and efficiency of substitute fuel combinations are improved by determining grouping rules for the substitute fuels based on the fuel boundary conditions.Grouping rules can be established based on fuel type, delivery capacity, and other parameters to ensure the compatibility and complementarity of the components in the alternative fuel mix. The diversity and flexibility of alternative fuel combinations are improved by grouping categories of alternative components based on their category, natural parameters, maximum delivery capacity, and grouping rules. The grouping process can be adjusted to meet the specific requirements of different target cement kilns according to actual needs and conditions, allowing multiple alternative fuel combinations to be selected, thereby improving the diversity and feasibility of alternative fuel choices.These alternative fuel combinations to be selected can provide many options for the subsequent optimization process. In summary, the accuracy and reliability of alternative fuel determination can be further improved by the above-mentioned technical steps and effects before obtaining the alternative component categories, property parameters, maximum delivery capacity and fuel boundary conditions for the . target fuel and the plurality of alternative fuel combinations to be selected. By obtaining detailed information on the alternative components of each category, determining the grouping rules based on the fuel boundary conditions, and grouping the alternative components of the categories, it is possible to provide more comprehensive and reasonable alternatives for the subsequent optimization process.

[0141] In some optional implementations, the build module 302 includes:

[0142] Definition unit for defining a mass fraction corresponding to each class of alternative components in the plurality of combinations of substitute fuels to be selected as a target independent variable;

[0143] Calorific value objective function construction unit for constructing a calorific value objective function based on a calorific value parameter in the target independent variable, the alternative component category of the alternative fuel combination to be selected and the property parameter;

[0144] Delivery capacity objective function construction unit for constructing a delivery capacity objective function based on a target independent variable, a maximum delivery capacity of a combination of alternative fuels to be selected.

[0145] This embodiment provides a substitute fuel determination device that improves the capability of the objective function to evaluate the calorific value performance of substitute fuel combinations by constructing a calorific value objective function based on the calorific value parameter in the target independent variable, the category of substitute components of the substitute fuel combination to be selected, and the property parameter. The calorific value objective function can reflect the calorific value requirements of different substitute fuel combinations and provide important performance indicators for the optimization process.By constructing the distribution capacity objective function based on the target independent variable, the maximum distribution capacity of the alternative fuel combination to be selected, the ability of the objective function to evaluate the distribution capacity of the alternative fuel combination is improved. The distribution capacity objective function can reflect the distribution requirements of different alternative fuel combinations, which ensures the feasibility of the optimized alternative fuel combinations in practical applications. The accuracy and reliability of alternative fuel determinations can be further improved. improved by defining target independent variables and constructing objective functions of calorific value and distribution capacity. These objective functions can be evaluated for different performance requirements and provide effective guidance for the subsequent optimization process. At the same time, comprehensively considering various factors, such as calorific value and distribution capacity, can more comprehensively meet the needs of practical applications and improve the applicability and feasibility of alternative fuels.

[0146] In some optional implementations, the optimization module 304 comprises:

[0147] A first setting unit for setting the crossover operator in the non-dominated sorting genetic algorithm to an analog binary crossover operator, the mutation operator to an adaptive polynomial mutation, and the selection operator to a binary tournament selection;

[0148] A first iterative unit for performing crossover and mutation operations on each initial alternative fuel combination ratio solution to be selected based on the non-dominated sorting genetic algorithm, respectively, to obtain an optimized alternative fuel combination ratio solution to be selected for each alternative fuel combination to be selected.

[0149] This embodiment provides a device for determining a substitute fuel that improves the reliability and efficiency of a crossover operation by setting a crossover operator in a non-dominated sorting genetic algorithm to an analog binary crossover operator. The analog binary crossover operator is capable of performing crossover operations on individuals based on a fitness function, generating new individuals, and increasing the diversity of a population. The flexibility and relevance of the mutation operation are improved by setting the mutation operator in the non-dominated sorting genetic algorithm to the adaptive polynomial mutation.Adaptive polynomial variation can adaptively adjust the variation probability according to the fitness distribution and population evolution, which ensures the diversity of the population and promotes the global search ability of the algorithm. By defining the selection operator in the non-dominated sorting genetic algorithm as binary tournament selection, the competitiveness and accuracy of the selection operation are improved. Binary tournament selection can competitively select individuals based on the fitness function, which ensures the proportion of excellent individuals in the population and accelerates the convergence speed of the algorithm. Diversity and global search ability. of the optimization process are improved by performing crossover and mutation operations on each initial alternative fuel combination ratio solution to be selected based on the non-dominated sorting genetic algorithm. These operations can generate new and superior alternative fuel combination ratio solutions to be selected, which improves the reliability and validity of the finalized alternative fuel combinations. The resulting optimized alternative fuel combination ratio solutions for each alternative fuel combination to be selected improve the accuracy and reliability of the determination of alternative fuels. These optimized alternative fuel combinations provide a reliable basis for the subsequent determination of alternative fuel component solutions corresponding to the target fuels.The accuracy and reliability of surrogate fuel determination can be further improved by defining appropriate crossover, mutation, and selection operators and optimizing the initial ratio solutions of surrogate fuel combinations to be selected using a non-dominated sequential genetic algorithm. The selection and tuning of these operators can improve the overall search capability and convergence speed of the algorithm, and produce better dosage solutions of the surrogate fuel combinations to be selected. This provides a reliable basis for the subsequent determination of the component solutions of the surrogate fuels corresponding to the target fuels and helps to solve problems in practical production.

[0150] In some optional embodiments, the optimization module 304 comprises:

[0151] A second setting unit for setting the crossover operator in the non-dominated sorting genetic algorithm to an analog binary crossover operator, the mutation operator to an adaptive polynomial mutation, and the selection operator to a binary tournament selection;

[0152] A second iteration unit for separately performing crossover and mutation operations on each initial alternative fuel combination ratio solution to be selected based on the non-dominated sorting genetic algorithm to obtain a new alternative fuel combination ratio solution to be selected for each alternative fuel combination to be selected;

[0153] A penalty function processing unit for using the penalty function to process the new alternative fuel combination dosing solution to be selected that violates the fuel boundary conditions until the termination condition is satisfied, in order to obtain each optimized solution of the dosage of the alternative fuel combination to be selected.

[0154] This embodiment provides an apparatus for determining alternative fuels, which improves the constraints and limitations of the alternative fuel combination dosing solutions to be selected by using a penalty function to process new alternative fuel combination dosing solutions that violate the boundary conditions of the fuels. The penalty function is capable of penalizing individuals appropriately according to the degree of violation of the boundary conditions, ensuring that the optimized alternative fuel combination dosing solution to be selected satisfies the constraints of the practical application.By combining the non-dominated sorting genetic algorithm and the penalty function processing method, it is possible to effectively process the dosage solution of the alternative fuel combination to be selected that violates the fuel boundary conditions and obtain the optimized dosage solution of the alternative fuel combination to be selected that meets the requirements of practical applications. This method can achieve the goals of energy saving, emission reduction and sustainable development of cement kilns.

[0155] In some optional embodiments, the substitute fuel determination device comprises: if the alternative component of the substitute fuel combination to be selected comprises solids and liquids, the fuel boundary condition further comprises: a solid-liquid ratio within a first predetermined range.

[0156] The substitute fuel determination device provided in the present embodiment can improve production efficiency, product quality and environmental performance, and reduce production costs by setting reasonable parameters for the solid-liquid ratio.

[0157] In some optional embodiments, the substitute fuel determination device comprises: a maximum conveying capacity is obtained based on a target cement kiln performing a feed volume test.

[0158] The present embodiment provides a substitute fuel determination device that can solve an actual production problem by obtaining a maximum conveying capacity based on a feed quantity test conducted in a target cement kiln. In actual production, conveying capacity is one of the main constraints, and an accurate maximum conveying capacity can ensure that the substitute fuel can be conveyed stably and efficiently during the production process, and improve production efficiency and product quality.

[0159] Other functional descriptions of the various modules and units described above are the same as those of the corresponding embodiments described above and will not be repeated herein.

[0160] In this embodiment, the hardware encryption device is in the form of a functional unit, the unit referring to an ASIC (Application Specified Integrated Circuit), a processor and a memory that executes one or more software or fixed programs, a memory, and / or other devices capable of performing the aforementioned functions.

[0161] Embodiments of the present invention also provide a computing device having the hardware encryption device illustrated in [Fig.3] above.

[0162] Referring to [Fig. 4], [Fig. 4] is a schematic diagram of the structure of a computing device provided by an optional embodiment of the present invention, which, as shown in [Fig. 4], comprises: one or more processors 10, a memory 20, and interfaces for connecting the various components, including a high-speed interface and a low-speed interface. The various components are connected together by different buses and may be mounted on a common motherboard or in any other desired manner. The processor may process instructions executed in the computing device, including instructions stored in or on the memory to display graphical information from the GUI on an external input / output device (e.g., a display device coupled to the interface).In some optional implementations, multiple processors and / or multiple buses may be used with multiple memories and multiple memories, if desired. Similarly, a plurality of computing devices may be connected, with the individual devices providing some of the necessary operations (e.g., as a server network, a group of blade servers, or a multiprocessor system). A processor 10 is used as an example in [Fig. 4].

[0163] The processor 10 may be a central processor, a network processor, or a combination thereof. The processor 10 may also include a hardware chip. This hardware chip may be a special integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device described above may be a complex programmable logic device, a programmable logic gate array, a general-purpose logic array, or any combination thereof.

[0164] In which, the memory 20 stores instructions executable by the at least one processor 10 so that the latter executes the method of implementing the embodiments illustrated above.

[0165] The memory 20 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the storage data area may store data created based on use of the computing device, among other things. Further, the memory 20 may include high-speed random access memory, as well as non-transitory memory, such as at least one disk memory, flash memory, or other non-transitory solid-state memory. In some optional implementations, the memory 20 may optionally include memories located remotely from the processor 10, and these remote memories may be connected to this computing device via a network. Examples of networks include, but are not limited to, the Internet, a corporate intranet, a local area network, a mobile communications network, and combinations of these networks.

[0166] The memory 20 may comprise volatile memory, for example, random access memory; the memory may also comprise non-volatile memory, for example, flash memory, a hard disk drive, or a solid state hard disk drive; and the memory 20 may also comprise a combination of the aforementioned memory types.

[0167] The computing device also includes a communication interface 30 allowing the computing device to communicate with other communication devices or networks.

[0168] Embodiments of the present invention also provide a computer-readable storage medium, wherein the method described above according to embodiments of the present invention may be implemented in hardware, firmware, or implemented as computer code recordable on a storage medium, or implemented as computer code originally stored on a remote storage medium or a non-transitory machine-readable storage medium downloaded over a network and to be stored on a local storage medium. Thus, the methods described herein may be processed by software stored on a storage medium using a general computer, a specialized processor, or programmable or specialized hardware.The storage medium may be a magnetic disk, a compact disk, a read-only storage memory, a random storage memory, a flash memory, a hard disk drive or a solid state disk, etc. It will be appreciated that the computer, processor, microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code, and when the software or computer code is accessed by the computer, processor or hardware and is executed, the methods illustrated in the above embodiments are implemented.

[0169] Although the embodiments of the present invention are described in conjunction with the accompanying drawings, the skilled person may provide various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations fall within the scope limited by the appended claims.

Claims

1. Claims Method for determining a substitute fuel, characterized in that this method comprises: - obtaining alternative component categories, property parameters, maximum delivery capacity and fuel boundary conditions for a target fuel corresponding to a target cement kiln and a plurality of alternative fuel combinations to be selected, these alternative fuel combinations to be selected comprising at least two alternative component categories; - constructing an objective function based on the alternative component categories, property parameters and maximum delivery capacity of said plurality of alternative fuel combinations to be selected, and constructing constraint conditions based on the boundary conditions of the fuels; - calculating an initial solution of the ratio of the combination of alternative fuels to be selected for each of said combinations of alternative fuels to be selected on the basis of said objective function and the constraint conditions, respectively; - optimizing each of these initial alternative fuel combination ratio solutions using a non-dominated sequential genetic algorithm to obtain an optimized alternative fuel combination ratio solution for each of the alternative fuel combinations to be selected; - calculating a theoretical replacement rate for each of said optimized combinations of substitute fuels based on the class of substitution components, the property parameter, the maximum delivery capacity and said optimized solution of substitution fuel combination ratio for each of said combinations of substitute fuels to be selected; - determine, on the basis of the theoretical substitution rate, from the plurality of combinations of substitute fuels to select a scheme of substitute fuel components corresponding to the targeted fuels.

2. Method according to claim 1, characterized in that before obtaining the alternative component categories, property parameters, maximum delivery capacity and fuel boundary conditions for a combination of a target fuel and a plurality of substitute fuels to be selected, said method further comprises: - obtaining the alternative component categories, property parameters, maximum delivery capacity and fuel boundary conditions for each alternative component category corresponding to the target cement kiln; - determining a grouping rule for the substitute fuels based on the fuel boundary conditions;- grouping these alternative component categories based on these alternative component categories, property parameters, maximum delivery capacity and grouping rules to obtain the plurality of alternative fuel combinations to be selected.;

3. The method according to claim 1, characterized in that said objective function comprises a calorific value objective function and a delivery capacity objective function, - constructing an objective function based on the alternative component categories, the property parameters and the maximum delivery capacity of said plurality of alternative fuel combinations to be selected, comprising: - defining a mass fraction corresponding to each alternative component category in said plurality of alternative fuel combinations to be selected as a target independent variable; - constructing said calorific value objective function based on said target independent variable, said alternative component category of said alternative fuel combination to be selected, and a calorific value parameter in the property parameter;- construct said objective delivery capacity function on the basis of said target independent variable, the delivery capacity; maximum of said combination of substitute fuels to be selected.

4. The method according to claim 1, characterized in that said optimization of the initial solutions for dosing the combinations of alternative fuels to be selected separately using a non-dominated sorting genetic algorithm to obtain an optimized solution for dosing the combinations of alternative fuels to be selected for each of said combinations of alternative fuels to be selected, comprises: - defining the crossover operator in the non-dominated sorting genetic algorithm as an analog binary crossover operator, the variation operator as an adaptive polynomial variation, and the selection operator as a binary tournament type selection;- performing crossover and mutation operations on each of said initial solutions of ratio of combination of substitute fuels to be selected on the basis of the implemented non-dominated sorting genetic algorithm, respectively, in order to obtain an optimized solution of ratio of combination of substitute fuels to be selected for each of said combinations of substitute fuels to be selected.;

5. The method according to claim 1, characterized in that the crossover and mutation operations based on said non-dominated sorting genetic algorithm are performed separately on each of said initial solutions for dosing the combinations of alternative fuels to be selected in order to obtain an optimized solution for dosing the combinations of alternative fuels to be selected for each of said combinations of alternative fuels to be selected, comprising: - defining the crossover operator in the non-dominated sorting genetic algorithm as an analog binary crossover operator, the mutation operator as an adaptive polynomial mutation, and the selection operator as a binary tournament selection;- performing crossover and mutation operations on each of the initial solutions for dosing the alternative fuel combinations to be selected on the basis of the developed non-dominated sorting genetic algorithm, respectively, to obtain a; new alternative fuel combination dosage solution to be selected for each of said alternative fuel combinations to be selected; - processing these new alternative fuel combination dosage solutions to be selected which violate said constraints using a penalty function until a termination condition is satisfied, in order to obtain each optimized alternative fuel combination dosage solution to be selected.

6. A method according to claim 1, characterized in that said method further comprises: - if the alternative components of said combination of substitute fuels to be selected comprise solids and liquids, said fuel boundary condition further comprises: a solid-liquid ratio within a first predetermined range.

7. A method according to claim 1 or 2, characterized in that said maximum conveying capacity is obtained on the basis of a feed test of the target cement kiln.

8. A device for determining an alternative fuel, characterized in that said device comprises: - an acquisition module for acquiring a target fuel corresponding to a target cement kiln and a plurality of alternative component categories, property parameters, maximum delivery capacity of a plurality of alternative fuel combinations to be selected, and fuel boundary conditions, said alternative fuel combinations to be selected comprising at least two alternative component categories; - a construction module for constructing an objective function based on the alternative component categories, property parameters and maximum delivery capacity of said plurality of alternative fuel combinations to be selected, and for constructing constraints based on the fuel boundary conditions;- a first calculation module for calculating, on the basis of said objective function and the constraints, an initial solution of the ratio of the combination of alternative fuels for; each of said combinations of substitute fuels to be selected; - an optimization module for optimizing each of these initial alternative fuel combination ratio solutions using a non-dominated sequential genetic algorithm to obtain an optimized fuel combination ratio solution for each of said alternative fuel combinations to be selected; - a second calculation module for calculating a theoretical substitution rate for each of the optimized combinations of substitute fuels to be selected, based on the type of alternative component, the property parameter, the maximum delivery capacity of each of the combinations of substitute fuels to be selected and said optimized substitute fuel combination ratio solution; - a determination module for determining, on the basis of this theoretical substitution rate, a component solution for a substitute fuel corresponding to this target fuel from among this plurality of combinations of substitute fuels to be selected.

9. Computer device characterized in that it comprises: - a memory and a processor, said memory and said processor being communicatively connected to each other, said memory containing computer instructions, said processor executing said computer instructions, thereby performing the fuel substitution described in any one of claims 1 to 7.

10. A computer-readable storage medium characterized in that said computer-readable storage medium contains computer instructions, said computer instructions being used to cause a computer to perform a fuel substitution as claimed in one of claims 1 to 7.

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