Garbage power generation optimization method, storage medium and computer equipment

Abstract

The invention provides a garbage power generation optimization method, a storage medium and computer equipment. The garbage power generation optimization method comprises the steps of S1, garbage classification and preliminary data processing; s2, a boxing algorithm is applied, and the garbage is combined and optimized; and S3, the garbage incineration process is monitored, regulated and controlled. According to the invention, heat energy release in each incineration process can be ensured to be maximized; by introducing a heuristic method and combining a boxing algorithm, not only can garbage grouping and combustion strategies be optimized, but also dynamic adjustment can be made according to real-time monitoring data, the incineration efficiency and stability are improved, the stability of heat energy release is ensured, and then the heat energy recovery efficiency is improved; a systematic and global optimization scheme is formed, all links of garbage treatment can be considered, and the overall efficiency is improved; the method can be widely applied to waste incineration power plants, can greatly improve the heat energy utilization rate and the power generation efficiency of the incineration power plants, reduces emission of harmful substances, and improves environmental protection benefits.

Description

Technical Field

[0001] The present invention belongs to the technical field of waste power generation, and in particular relates to a waste power generation optimization method, a storage medium and a computer device. Background Art

[0002] At present, garbage classification and collection are important prerequisites for achieving efficient incineration. Existing waste-to-energy plants usually rely on manual or semi-automatic methods to classify garbage. The basis for classification is mainly the physical properties of garbage (such as plastics, paper, metals, etc.) and some basic chemical properties (such as calorific value, humidity, etc.). However, the existing classification methods often fail to fully consider the diversity and complexity of garbage combustion characteristics, resulting in insufficient classification and affecting subsequent combustion efficiency.

[0003] In the process of garbage incineration, traditional incinerators generally adopt a fixed combustion process and cannot dynamically adjust the incineration strategy according to the combustion characteristics of the garbage. Existing technologies usually control the incineration process through pre-set parameters such as incineration temperature and air supply. However, due to the complexity of garbage composition, a single combustion strategy is difficult to adapt to the combustion needs of all garbage, which often leads to incomplete combustion of some garbage or insufficient heat release, thus affecting power generation efficiency.

[0004] In order to improve the efficiency of waste incineration, existing technical solutions have adopted strategies such as layered combustion and staged combustion. These methods have improved the combustion effect to a certain extent, but due to the lack of accurate understanding of the characteristics of waste, there are still problems such as waste of calorific value and uneven incineration.

[0005] In summary, the existing waste incineration power generation technology has the following deficiencies in classification, incineration, and heat recovery:

[0006] 1. Garbage classification is not detailed enough: the existing classification method cannot fully consider the combustion characteristics of garbage, resulting in low calorific value utilization during the combustion process.

[0007] 2. Lack of dynamic adjustment in the incineration process: Existing incineration technologies usually adopt fixed combustion strategies and are unable to adjust incineration parameters based on real-time monitoring data, resulting in incomplete combustion of some garbage or waste of heat energy.

[0008] 3. The heat recovery efficiency is low: Due to the volatility of the incineration process, the existing heat recovery system is difficult to maximize the utilization of the heat energy generated by incineration, affecting the power generation efficiency.

[0009] In addition, some existing technologies have introduced intelligent control systems, but these systems are often limited to local optimization and lack overall systematic optimization capabilities, making it difficult to achieve efficient, stable and sustainable development of waste incineration.

[0010] In the industry, some waste incineration power plants have begun to try to optimize the waste sorting and incineration process through advanced computing technologies (such as artificial intelligence and big data analysis). For example:

[0011] Big data analysis: Use big data technology to analyze the composition and combustion characteristics of garbage, thereby providing more detailed guidance on garbage classification.

[0012] Artificial intelligence algorithms: Some power plants have introduced artificial intelligence algorithms to predict changes in calorific value during the incineration process and dynamically adjust incineration strategies to improve heat recovery rates.

[0013] Distributed control system: The distributed control system monitors and adjusts various parameters of the incineration process in real time to reduce heat energy waste.

[0014] However, these technical solutions still have certain limitations, mainly reflected in the complexity of data processing, the high cost of system implementation and the feasibility of technical application. Although most existing methods have improved the efficiency of waste incineration power generation to a certain extent, they have not yet formed a mature and widely applicable optimization system.

[0015] Through the above analysis, it can be seen that although the existing technology has made certain progress in the field of waste incineration power generation, it still needs further improvement in refined classification, incineration process optimization and heat recovery. Summary of the invention

[0016] In view of the above problems, the present invention provides a garbage power generation optimization method, storage medium and computer equipment.

[0017] The garbage power generation optimization method provided by the present invention comprises the following steps:

[0018] S1. Waste classification and preliminary data processing;

[0019] S2, applying a binning algorithm to combine and optimize the garbage;

[0020] S3. Monitoring and control of the incineration process of the garbage.

[0021] further,

[0022] The step S1 comprises the steps of:

[0023] S11, data collection: obtaining basic information of the garbage from the garbage collection system;

[0024] S12, preliminarily classifying the garbage based on the physical and chemical properties of the garbage;

[0025] S13, feature extraction: extracting combustion characteristic parameters of each type of garbage through detection equipment, and using the combustion characteristic parameters as input parameters in the packing algorithm.

[0026] further,

[0027] The step S2 comprises the steps of:

[0028] S21, parameter setting or constraint setting, that is, setting the constraint conditions of the packing algorithm;

[0029] S22, using the bin packing algorithm to optimize the combination of the garbage with different characteristics, and generating an optimal garbage grouping solution through three steps of combination, iteration and optimization;

[0030] S23, garbage grouping: according to the result of the optimization combination, the garbage is packaged and prepared to be put into the incinerator for incineration.

[0031] further,

[0032] In step S21, the constraint conditions include:

[0033] S211. Capacity limits of incinerators:

[0034] The total volume of the garbage combination incinerated each time shall not exceed the maximum capacity of the incinerator.

[0035] The incinerator has a maximum load mass that it can bear; the total mass of the garbage combination incinerated each time does not exceed the bearing capacity of the incinerator chamber and the supporting structure;

[0036] S212, calorific value requirements:

[0037] The total calorific value of the garbage combination in each incineration must reach or exceed the minimum calorific value requirement of the incineration furnace.

[0038] The total calorific value of the garbage combination incinerated each time shall not exceed the maximum design calorific value of the incinerator;

[0039] S213, Combustion temperature requirements:

[0040] The combustion characteristics of the garbage combination in each incineration are combined to maintain the temperature in the furnace higher than the minimum combustion temperature,

[0041] The calorific value obtained from the combustion of the garbage combination each time is incinerated does not exceed the expected calorific value threshold;

[0042] S214, Humidity Control:

[0043] The average humidity of the garbage combination in each incineration is not higher than the expected humidity high threshold,

[0044] The humidity of the garbage combination incinerated each time is not lower than the expected humidity low threshold;

[0045] S215, Volatile matter and ash control:

[0046] The volatile matter content of each waste combination incinerated does not exceed the expected volatile matter content threshold,

[0047] The ash content of each waste combination incinerated does not exceed the expected ash content threshold;

[0048] S216. Pollutant emission limits:

[0049] The nitrogen content of each waste combination incinerated does not exceed the expected nitrogen content threshold,

[0050] The sulfur content of each waste combination incinerated does not exceed the expected sulfur content threshold,

[0051] The chlorine content of each waste combination incinerated does not exceed the expected chlorine content threshold;

[0052] S217, Burning time and speed limit:

[0053] The burning time of the garbage combination in each incineration is kept within the optimal burning rate range of the incinerator design;

[0054] S218, Safety operation restrictions:

[0055] Identify and limit the contents of combustible gas and flammable and explosive waste of each waste combination incinerated to below the expected combustible gas content threshold and the expected flammable and explosive waste content threshold;

[0056] The auto-ignition temperature of the garbage combination incinerated each time does not exceed the startup safety temperature of the incinerator;

[0057] S219, Preprocessing requirements:

[0058] The humidity of each waste combination incinerated is lower than the expected humidity threshold.

[0059] further,

[0060] The step S22 comprises the steps of:

[0061] S221, combination, specifically comprising the steps of:

[0062] S221a, initialize input parameters: let the garbage set be L = {L1, L2, ..., L n}, L i is the i-th type of garbage in the garbage collection, 1≤i≤n, n is an integer greater than 1, L i The properties include: volume V i, quality M i , calorific value H i , humidity W i , ash content A i , chlorine content C i , sulfur content S i ;

[0063] S221b, initializing the constraints of the incinerator: maximum volume V max , minimum calorific value H min , maximum calorific value H max , maximum humidity W max , ash content upper limit A max 、Upper limit of chlorine content C max and sulfur content limit S max ;

[0064] S221c, combination strategy: using the packing algorithm to combine different types of garbage to obtain multiple garbage combinations, i.e., garbage groups, each of which is an incineration batch;

[0065] S221d, objective function: maximize the total calorific value H of a single incineration total ,Right now

[0066]

[0067] In the above formula, G represents the set of garbage in the current garbage group;

[0068] S221e, combined constraints, including:

[0069] Volume Constraints

[0070] Calorific value constraint

[0071] Humidity constraints

[0072] Ash and contaminant constraints and

[0073] S222, iteration, specifically including the steps:

[0074] S222a, initial grouping: using a greedy algorithm to generate a preliminary combination to fill the incinerator and meet its volume limit;

[0075] S222b, local adjustment:

[0076] Adjustment strategy: If the initial garbage combination does not meet the constraints, the excessive garbage will be gradually eliminated or replaced, and the qualified garbage will be retained;

[0077] Local optimality check: After adjustment, check whether the new garbage combination meets all constraints, compare with the previous combination, and select the optimal solution;

[0078] S222c, repeated iteration: using a global optimization technology based on simulated annealing or genetic algorithm, performing multiple iterations, adjusting the existing garbage combination on the basis of each iteration, and finding a better solution: in each iteration, generating a new garbage combination and comparing the total calorific value utilization rate and the total volume utilization rate of the incinerator with the previous garbage combination, if the new garbage combination is better than the previous garbage combination, retaining the new garbage combination as a new solution;

[0079] S223, optimal selection: selecting the optimal solution from all the iteratively generated garbage combinations, specifically including the steps of:

[0080] S223a, optimizing the comprehensive objective function: Under the premise of satisfying all the combination constraints, select a combination that maximizes the comprehensive objective function value, and the comprehensive objective function value is expressed by the following formula:

[0081]

[0082] In the above formula, Z is the comprehensive objective function value; αα, β, γ are weight coefficients; Indicates the total calorific value utilization rate; Indicates the volume utilization rate of the incinerator; Indicates the degree of humidity control;

[0083] S223b, optimal solution selection: after the iteration is completed, the garbage combination with the highest comprehensive objective function value is selected as the final optimal solution;

[0084] S223c, outputting an optimal solution: the optimal solution includes a detailed list of garbage combinations that are the optimal solutions.

[0085] further,

[0086] In step S23, the garbage is packaged according to the optimal solution.

[0087] further,

[0088] The step S3 comprises:

[0089] S31. Real-time monitoring: During the incineration process, the following parameters in the incinerator are monitored in real time through sensors and monitoring systems:

[0090] Temperature related parameters, including: furnace temperature, flue gas temperature, hearth temperature, wall temperature;

[0091] Pressure related parameters, including: furnace pressure, chimney pressure, blower pressure;

[0092] Combustion rate related parameters, including: fuel delivery rate, air supply, combustion rate;

[0093] Gas composition parameters, including: oxygen concentration, carbon dioxide concentration, carbon monoxide concentration, nitrogen oxide concentration, sulfur dioxide concentration, hydrogen chloride concentration, ammonia concentration, hydrogen sulfide concentration, volatile organic compound concentration;

[0094] Particulate matter parameters, including: particle concentration, fly ash content;

[0095] Heat recovery parameters, including: steam pressure, steam temperature, steam flow, cooling water temperature;

[0096] Other parameters include: slag emission rate, exhaust gas flow rate, humidity, fuel moisture content, and furnace visibility.

[0097] further,

[0098] The step S3 further comprises:

[0099] S32, dynamic adjustment, including: when one of the parameters monitored in step S31 exceeds a set range, the following adjustment is performed:

[0100] S321, adjust the feed rate, based on the formula:

[0101] F neu =F current +K T ·(T set -T measured ),

[0102] In the above formula, F new is the adjusted feed rate, F current is the current feed rate, K T is the temperature control coefficient, T set is the target temperature, T measured is the actual monitored furnace temperature;

[0103] S322. Adjust the air supply according to the formula:

[0104] A new =A current +K O ·(O set -O measured ),

[0105] In the above formula, A new is the adjusted air supply, A current is the current air supply, KO is the oxygen regulation factor, O set is the target oxygen concentration, O measured is the actual monitored oxygen concentration;

[0106] S323. Adjust the combustion chamber pressure based on the formula:

[0107] P new =P current +K P ·(P set -P measured ),

[0108] In the above formula, P new is the adjusted combustion chamber pressure, P current is the current combustion chamber pressure, K P is the pressure regulation coefficient, P set is the target pressure value, P measured is the actual monitored combustion chamber pressure;

[0109] S324. Adjust the combustion rate based on the formula:

[0110] R comb =f(F new , A new ),

[0111] In the above formula, R comb is the burning rate, F new is the new feed rate, A new is the new air supply amount, and the specific form of the formula f is obtained through experimental simulation;

[0112] S325. Control of pollutant emissions, including:

[0113] When it is detected that the CO concentration is too high, that is, the CO concentration exceeds the preset CO concentration threshold, the air supply is increased or the fuel supply is reduced;

[0114] When NO is detected x Too high a concentration of NO x Concentration checked by preset NO x When the concentration threshold is reached, the combustion temperature is lowered or oxygen is supplied in stages;

[0115] When it is detected that the SO2 concentration is too high, that is, the SO2 concentration exceeds the preset SO2 concentration threshold, the desulfurization agent is added.

[0116] The present invention also provides a computer device, which includes a memory, a first processor, and a first computer program stored in the memory and executable on the first processor, wherein the first computer program implements the above-mentioned waste-to-energy optimization method when executed by the first processor.

[0117] The present invention also provides a computer-readable storage medium, which is used to store a second computer program. The second computer program can be executed by at least one second processor to enable the at least one second processor to execute the above-mentioned waste-to-energy optimization method.

[0118] The garbage power generation optimization method provided by the present invention can further carry out fine combination after garbage classification to ensure the maximization of heat energy release during each incineration process; by introducing heuristic methods and combining with the packing algorithm, it can not only optimize the garbage grouping and combustion strategy, but also make dynamic adjustments according to real-time monitoring data to improve the incineration efficiency and stability, ensure the stability of heat energy release, and then improve the heat energy recovery efficiency; form a systematic and global optimization plan that can take into account all aspects of garbage treatment and improve overall efficiency; can be widely used in garbage incineration power plants, can greatly improve the heat energy utilization rate and power generation efficiency of incineration power plants, reduce the emission of harmful substances, and improve environmental protection benefits.

[0119] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0120] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0121] Figure 1 A flow chart of a waste-to-energy optimization method according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0122] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0123] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions. The terms "first", "second", "third", etc. in the specification and claims of this application or the above-mentioned figures are used to distinguish different objects, not to describe a specific order or a primary and secondary relationship. "Multiple" appearing in this application refers to more than two (including two).

[0124] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0125] Figure 1 This is a flow chart of the waste-to-energy optimization method provided by the present invention. Figure 1 , the waste power generation optimization method comprises the following steps.

[0126] S1. Garbage classification and preliminary data processing. Including the following steps:

[0127] S11. Data collection: Obtain basic information about the garbage from the garbage collection system, such as the type, volume, calorific value, humidity, and ash content of the garbage. This basic information is the basis for the subsequent application of the packing algorithm and heuristic method. The basic information includes:

[0128] D1. Types of garbage: Specific types of garbage, including: combustible garbage (including plastic, paper, wood, etc.), non-combustible garbage (including glass, metal, etc.), organic garbage (including food residues, plant waste, etc.), hazardous waste (including chemical waste, electronic waste, etc.).

[0129] D2. Volume: The total volume of the garbage (m 3 , cubic meters), which can be used to assess the space required and efficiency of its incineration treatment.

[0130] D3. Calorific value: including:

[0131] Lower Heating Value (LHV): The net energy released when a unit mass of waste is burned, after removing the heat of condensation of water vapor;

[0132] Higher Heating Value (HHV): The net energy released when a unit mass of garbage is burned, including the heat released when water vapor condenses, reflecting the total calorific value potential of the garbage.

[0133] D4. Moisture Content: including:

[0134] Total moisture: All moisture in the garbage, including adsorbed water and free water, affects combustion efficiency.

[0135] Free moisture: easily evaporated moisture, which directly affects the pretreatment requirements of garbage before incineration.

[0136] Adsorbed moisture: The moisture absorbed by the garbage material itself is difficult to evaporate directly.

[0137] D5. Ash Content: The proportion of inorganic matter remaining after combustion (%, percentage), which affects the treatment requirements of slag after incineration.

[0138] D6. Volatile Matter Content: The proportion of combustible gas that can be released when heated, which affects the combustion rate and smoke emission characteristics of the combustion process.

[0139] D7. Fixed Carbon Content: The proportion of carbon elements remaining after combustion, used to evaluate the sustainability of the calorific value of garbage combustion.

[0140] D8. Density: The mass of garbage per unit volume, which affects the loading method of garbage in the incinerator and the combustion air requirement.

[0141] D9. Particle Size Distribution: The particle size distribution of garbage affects the air flow and heat energy release efficiency during combustion.

[0142] D10, Chemical composition: including:

[0143] Nitrogen: Nitrogen oxides (NO x , X=1,2), affecting environmental emission requirements.

[0144] Sulfur: May produce sulfur dioxide (SO2), affecting the exhaust gas treatment system.

[0145] Chlorine: May generate hydrogen chloride (HCl), which is corrosive to incineration equipment.

[0146] Heavy metals: lead (Pb), mercury (Hg), cadmium (Cd), etc., may produce toxic smoke and affect the exhaust gas purification system.

[0147] D11. Pyrolysis Temperature: The temperature at which garbage begins to decompose thermally under anaerobic or low-oxygen conditions, which affects the pyrolysis and gasification process.

[0148] D12. Ignition Temperature: The temperature at which garbage spontaneously combusts without an external fire source, which determines the difficulty of starting and controlling incineration.

[0149] D13. Emissions Potential: including:

[0150] The amount of carbon dioxide produced by garbage burning affects the carbon emission assessment.

[0151] Carbon monoxide content represents a pollutant from incomplete combustion.

[0152] The contents of nitrogen oxides, sulfur oxides, hydrogen chloride, and volatile organic compounds (VOCs) represent the pollutant potential estimated based on the chemical composition of the garbage.

[0153] D14. Composition of thermal decomposition gas: The gas components released after pyrolysis of garbage include methane (CH4), ethane, hydrogen, etc., which affect heat recovery and waste gas treatment.

[0154] D15. Ash Fusion Temperature: The temperature at which ash begins to melt at high temperatures, which determines whether slag will be produced in the combustion furnace.

[0155] D16. Biodegradability: The biodegradability characteristics of organic components in garbage, used to assess the possibility of organic residues in the ash after incineration.

[0156] D17. Heterogeneity of Composition: The material heterogeneity of garbage, such as material mixing degree and hierarchical structure, affects the heat conduction and reactivity during combustion.

[0157] D18. Release Rate of Volatiles During Combustion: The release rate of volatiles during combustion affects the heat conduction of the combustion process and the stability of the combustion flame.

[0158] D19, Combustion Residue: including:

[0159] Slag volume: the volume and composition of slag remaining after incineration.

[0160] Fly ash quantity: Fly ash produced during the combustion process and its particle size and chemical composition.

[0161] D20. Energy Utilization Efficiency: The efficiency data of converting garbage into heat energy and electrical energy through the incineration process.

[0162] S12. Preliminary classification: Preliminary classification of garbage based on its physical and chemical properties. The present invention proposes a systematic preliminary classification method to ensure efficient combustion and heat recovery of garbage during incineration. The classification of garbage covers multiple key dimensions, including the source, combustibility, chemical composition and physical state of the garbage. The preliminary classification includes the following steps:

[0163] S121, Combustibility classification: Classify garbage into highly combustible garbage, low combustible garbage and non-combustible garbage.

[0164] in,

[0165] Highly combustible waste refers to waste with a low calorific value (LHV) greater than 15MJ / kg (megajoule / kilogram) and a volatile matter content greater than 40%, including paper, wood, cloth, rubber, plastic, etc. This type of waste has a high combustion calorific value, is suitable for direct incineration, and is easy to ignite.

[0166] Low-combustible waste refers to waste with a low calorific value (LHV) between 8-15MJ / kg and a humidity greater than 30%, including organic waste (such as kitchen waste, plant residues), agricultural waste with high humidity, etc. This type of waste has certain combustion potential, but due to its high water content or complex chemical properties, it needs to be mixed with high-combustible waste for incineration or pre-treated before incineration.

[0167] Non-combustible waste is waste with a low calorific value (LHV) of less than 5MJ / kg and an ash content greater than 50%, including inorganic waste such as metal, glass, and concrete. This type of waste is not suitable for incineration and may contain metal or inorganic matter. It will not generate sufficient calorific value during incineration and may affect combustion equipment.

[0168] S122, Humidity classification: Classify garbage into high humidity garbage, medium humidity garbage and low humidity garbage.

[0169] in,

[0170] High-humidity garbage refers to garbage with a humidity greater than 40%, including kitchen waste, fruit peels, vegetable residues, sludge, etc. This type of garbage has a high humidity and contains a large amount of water. Direct incineration will consume a lot of energy and needs to be pre-treated (such as dehydration) before incineration.

[0171] Medium-humidity garbage refers to garbage with a humidity between 20-40%, including food packaging waste, wet cardboard, wet wood, etc. This type of garbage contains a certain amount of moisture, but it does not affect the incineration efficiency and can be incinerated directly or mixed with highly combustible garbage for incineration.

[0172] Low-moisture garbage refers to garbage with a humidity of less than 20%, including plastics, dry paper, fiber materials, etc. This type of garbage contains almost no moisture and is suitable for direct incineration. It can also be used to improve the overall combustion efficiency of high-moisture garbage.

[0173] S123. Physical classification: Classify garbage into solid garbage, semi-solid garbage and liquid garbage.

[0174] in,

[0175] Solid waste refers to waste with a density greater than 0.8g (gram) / cm (centimeter)3 and a particle size greater than 10cm, including metals, hard plastics, wood blocks, etc. This type of waste has a high density and a stable volume, and is suitable for long-term high-temperature treatment in an incinerator.

[0176] Semi-solid waste has a density of 0.3-0.8g / cm 3 Garbage with particle size less than 10cm but larger than 1cm, including grease, soft plastics, rubber products, etc., the volume of this type of garbage is unstable and may change its shape after heating, so it needs special treatment or mixed incineration with other garbage.

[0177] Liquid waste has a density less than 0.3g / cm 3 , garbage in the form of liquid or viscous liquid, including industrial waste liquid, aqueous oil pollution, waste oil, etc. This type of garbage needs to be treated by adsorption or other pre-treatment methods to prevent it from flowing directly into the incinerator.

[0178] S124, Chemical composition classification: Classify garbage into high-chlorine garbage, high-sulfur garbage and garbage with high heavy metal content.

[0179] in,

[0180] High-chlorine garbage refers to garbage with a chlorine content greater than 0.5%, including PVC plastics, chlorine-containing polymers, etc. This type of garbage has a high chlorine content and will produce corrosive fumes (such as hydrogen chloride) when incinerated, requiring special treatment (such as dechlorination).

[0181] High-sulfur garbage refers to garbage with a sulfur content greater than 0.2%, including rubber, certain industrial waste, etc. This type of garbage has a high sulfur content and may produce sulfur dioxide (SO2) when burned, so it needs to be desulfurized.

[0182] Garbage with high heavy metal content refers to garbage with a heavy metal content (such as lead, cadmium, and mercury) greater than 0.01%, including electronic waste, batteries, and industrial chemical waste. This type of garbage contains toxic heavy metals and may produce heavy metal oxides during incineration, requiring strict gas purification and solid residue treatment.

[0183] S124. Hazard classification: Classify garbage into inflammable and explosive garbage, toxic garbage and biohazardous garbage.

[0184] in,

[0185] Flammable and explosive garbage refers to garbage that contains flammable and explosive chemicals with a flash point below 23°C or a vapor pressure greater than 300kPa, including discarded paint, spray cans, gas cylinders, chemical waste, etc. This type of garbage may produce dangerous chemical reactions or explosions when incinerated and must be handled with caution.

[0186] Toxic waste refers to waste whose toxic substance concentration is higher than the statutory safety concentration threshold, including cyanide-containing waste, benzene-containing waste, etc. This type of waste contains toxic substances and will produce toxic fumes when incinerated, requiring a strict waste gas purification system.

[0187] Biohazardous waste is waste that is infectious or has biological hazard risks, including medical waste, remains of dead animals, etc. This type of waste contains pathogens or other biological hazards and needs to be disinfected at high temperature before incineration.

[0188] S13, feature extraction: extract the combustion characteristic parameters of various types of garbage through detection equipment, and use these characteristic parameters as input parameters in the packing algorithm. The combustion characteristics include:

[0189] S131, Calorific Value:

[0190] Lower Heating Value (LHV): does not take into account the heat released by the condensation of water vapor in the combustion products. LHV is usually used to measure the actual available heat energy.

[0191] Higher Heating Value (HHV): includes the heat released by the condensation of water vapor in the combustion products. HHV is usually higher than LHV and is suitable for theoretical analysis.

[0192] S132, Moisture Content:

[0193] Total Moisture: All moisture contained in the garbage, including free water and adsorbed water.

[0194] Equilibrium Moisture: The moisture content of garbage when it reaches humidity equilibrium with the air under specific conditions.

[0195] Free Moisture: Water that can be removed by simple evaporation or mechanical dehydration.

[0196] S133, ash content (Moisture Content), that is, the content of inorganic substances remaining after the garbage is burned, the inorganic substances include:

[0197] S133a, Metal Oxides: Calcium oxide (CaO), magnesium oxide (MgO), aluminum oxide (Al2O3), iron oxide (Fe2O3, Fe3O4), sodium oxide (Na2O), potassium oxide (K2O), zinc oxide (ZnO), copper oxide (CuO): derived from copper products or copper-containing waste, chromium oxide (Cr2O3).

[0198] S133b, Silicon-containing compounds (Silicates): silicon dioxide (SiO2), aluminum silicate (Al2SiO5), calcium silicate (CaSiO3).

[0199] S133c, Sulfides and Sulfates: calcium sulfate (CaSO4), iron sulfide (FeS), sodium sulfate (Na2SO4).

[0200] S133d, Carbonates: calcium carbonate (CaCO3), magnesium carbonate (MgCO3).

[0201] S133e, Chlorides and Fluorides: Calcium chloride (CaCl2); Sodium chloride (NaCl); Calcium fluoride (CaF2): Commonly found as residues after the combustion of fluorine-containing substances.

[0202] S133f, Phosphates: calcium phosphate (Ca3(PO4)2).

[0203] S133g, other metal compounds: nickel oxide (NiO); lead oxide (PbO); cadmium oxide (CdO); mercury oxide (HgO).

[0204] S133h, other minerals: borates; manganese oxide (MnO2).

[0205] S133i, trace elements: germanium (Ge), vanadium (V), cobalt (Co), etc.

[0206] S134, Volatile Matter Content, i.e. the content of gases and liquids released during the decomposition of garbage during heating, including:

[0207] S134a, Combustible gases (Gases): Hydrogen (H2), methane (CH4), ethylene (C2H4), propylene (C3H6), acetylene (C2H2), carbon monoxide (CO), carbon dioxide (CO2), ammonia (NH3), hydrogen sulfide (H2S), hydrogen cyanide (HCN), nitrous oxide (N2O), styrene (C8H8). Among them, although carbon dioxide is not a combustible gas, it is the main gas produced when volatiles are burned.

[0208] S134b, flammable liquids: methanol (CH3OH), ethanol (C2H5OH), acetaldehyde (CH3CHO), acetone (C3H6O), benzene (C6H6), toluene (C7H8), phenols, acetic acid (CH3COOH), dioxane (C6H 12 O2), styrene (C6H5CH=CH2), cyclohexane (C6H 12 ), formic acid (HCOOH).

[0209] S134c, other gaseous and liquid components: water vapor (H2O), alcohols other than methanol and ethanol (Alcohols), esters, polycyclic aromatic hydrocarbons (PAHs), and amines.

[0210] S135, Fixed Carbon: Carbonaceous matter left after the combustion of garbage, excluding volatile matter and ash.

[0211] S136. Combustion Temperature: Ignition Temperature: The lowest temperature at which garbage spontaneously combusts without an external fire source; Maximum Combustion Temperature: The highest temperature that may be reached during the combustion process.

[0212] S137. Burning Rate: The rate at which garbage burns per unit time, usually expressed as the rate of mass reduction.

[0213] S138. Combustion Efficiency: The efficiency of converting fuel into heat energy during the garbage combustion process, usually expressed as the ratio of actual heat released to theoretical heat.

[0214] S139. Ash Fusion Temperature: The temperature at which ash begins to melt and form a molten material at high temperature.

[0215] S1310, Flue Gas Composition: Flue gas composition produced during the combustion process. Flue gas composition produced during waste incineration includes multiple (more than 1) gases and particulate matter, and these components have different impacts on the environment. They mainly include combustion products such as carbon dioxide, carbon monoxide, and water vapor; acidic gases such as nitrogen oxides, sulfur dioxide, and hydrogen chloride; volatile organic compounds such as benzene, aldehydes, and dioxins; and fly ash, heavy metal particles, etc.

[0216] S1311, Chlorine Content: The chlorine content in the garbage.

[0217] S1312, Sulfur Content: The sulfur content in the garbage.

[0218] S1313. Metal Content: Heavy metals (such as lead, cadmium, and mercury) contained in garbage. There are many kinds of heavy metals in garbage, mainly including common toxic metals such as lead, cadmium, mercury, chromium, nickel, copper, zinc, and arsenic. In addition, it may also contain small amounts of other heavy metal elements such as cobalt, antimony, vanadium, and thallium that are potentially harmful to the environment and human body.

[0219] S1314. Properties of combustion products, including:

[0220] S1314a. Slag properties, including:

[0221] Particle size: Slag particles include coarse slag, fine slag and powder slag. The particle size of coarse slag is usually greater than 10mm (millimeter), the particle size of fine slag is between 1mm-10mm, and the particle size of powder slag is less than 1mm.

[0222] Density: Apparent density: 0.8-1.6g / cm 3 (Under loose state); real density: 2.0-3.0g / cm 3 (Density after removing voids).

[0223] Chemical composition, including:

[0224] Silicates: silicon dioxide (SiO2), calcium silicate (CaSiO3).

[0225] Metal oxides: aluminum oxide (Al2O3), iron oxide (Fe2O3), calcium oxide (CaO), magnesium oxide (MgO).

[0226] Sulfate: Calcium sulfate (CaSO4).

[0227] Heavy metals: lead (Pb), cadmium (Cd), mercury (Hg), chromium (Cr), nickel (Ni), etc.

[0228] Melting point: initial melting temperature: 900℃-1200℃; complete melting temperature: 1300℃-1500℃.

[0229] S1314b. Properties of smoke, including:

[0230] Particle size: Smoke particles are divided into ultrafine particles, fine particles and coarse particles. The particle size of ultrafine particles is <0.1μm (micrometer), the particle size of fine particles is 0.1-2.5μm, and the particle size of coarse particles is 2.5-10μm.

[0231] Dust concentration: Untreated concentrations can reach hundreds to thousands of mg / m 3 , after treatment should be less than 30mg / m 3 .

[0232] The components of smoke include: carbonaceous matter, i.e. unburned carbon particles and organic residues; metal oxides: iron oxide (Fe2O3), aluminum oxide (Al2O3), calcium oxide (CaO), magnesium oxide (MgO); sulfates: calcium sulfate (CaSO4), sodium sulfate (Na2SO4); heavy metal particles: lead (Pb), cadmium (Cd), mercury (Hg), chromium (Cr); halogen compounds: chlorides (such as NaCl), fluorides (such as CaF2).

[0233] S1315, Chemical Reactivity: The chemical reaction rate of garbage at high temperature.

[0234] S1316. Pyrolysis Characteristics: The characteristics of garbage decomposition under anaerobic or low-oxygen conditions. The pyrolysis products include:

[0235] S1316a, flammable gases, including: hydrogen (H2), methane (CH4), carbon monoxide (CO), carbon dioxide (CO2), ethylene (C2H4), propylene (C3H6), acetylene (C2H2), other lower alkanes and alkenes (such as ethane, butane), ammonia (NH3), hydrogen sulfide (H2S), hydrogen cyanide (HCN).

[0236] S1316b, tar.

[0237] S1316c, charcoal (or carbon), and its carbon (carbon) compounds, inorganic residues (such as metal oxides, silicates), metal residues (such as aluminum, iron, copper)

[0238] S1316d, other by-products, including: water vapor (H2O), sulfur oxides (SO2, SO3), nitrogen oxides (NO x , N2O), volatile inorganic substances (such as hydrogen chloride, hydrogen fluoride).

[0239] S2. Application of the bin packing algorithm. Specifically includes the following steps:

[0240] S21, parameter setting or constraint setting: according to the capacity, design calorific value, combustion temperature and other requirements of the waste incinerator, set the constraints of the packing algorithm. In the waste incineration power generation optimization system of the present invention, parameter setting is a key step to ensure that the packing algorithm can effectively optimize the waste combination, maximize the incineration efficiency, and meet the operating requirements of the incinerator. It should be noted that each batch of waste has different components, although the types of waste are the same, they can constitute multiple waste combinations. The set constraints mainly include the following aspects:

[0241] S211. The capacity limit of the incinerator should take into account:

[0242] Furnace capacity (Volume Capacity), the corresponding constraint condition: the garbage combination incinerated each time must not exceed the maximum capacity of the incinerator, ensuring that there is enough combustion space for garbage in the furnace to prevent excessive accumulation and uneven combustion. If the maximum capacity of the incinerator is 20 cubic meters, the packing algorithm should ensure that the total volume of the garbage combination incinerated each time does not exceed 20 cubic meters.

[0243] Mass capacity, corresponding constraints: the incinerator has a maximum load mass that it can bear; the total mass of the garbage combination incinerated each time cannot exceed the bearing capacity of the furnace and the supporting structure. Example: If the maximum load mass of the incinerator is 10 tons, the algorithm needs to ensure that the total mass of the garbage combination incinerated each time is less than 10 tons.

[0244] S212, calorific value requirements, need to consider:

[0245] Minimum Calorific Value, corresponding constraint: the total calorific value of each combination of garbage incinerated must meet or exceed the minimum calorific value requirement to ensure that the necessary combustion temperature can be maintained during the combustion process to avoid incomplete or inefficient combustion. Example: If the minimum combustion calorific value requirement of the furnace is 15MJ (megajoules) / kg (kilograms), the packing algorithm should ensure that the total calorific value of each combination of garbage incinerated is not less than this value.

[0246] Maximum Calorific Value, corresponding constraint: the total calorific value of each combination of garbage incinerated must not exceed the maximum design calorific value of the incinerator to prevent excessive temperature, resulting in equipment damage or safety issues. Example: If the upper limit of the incinerator design calorific value is 30MJ / kg, the algorithm needs to ensure that the total calorific value of each combination of garbage incinerated does not exceed this value.

[0247] S213, combustion temperature requirements, need to consider:

[0248] Minimum Combustion Temperature, corresponding constraint: The combustion characteristics of each combination of garbage incinerated must be able to maintain the furnace temperature above the minimum combustion temperature to ensure complete combustion and reduce pollutant emissions. Example: If the minimum combustion temperature of the garbage incinerator is 850℃ (degrees Celsius), the packing algorithm should ensure that the combustion characteristics of each combination of garbage incinerated can produce and maintain this temperature.

[0249] Maximum Combustion Temperature, corresponding constraint: The calorific value of each combination of garbage incinerated cannot be too high (exceeding the expected calorific value threshold) to prevent the furnace temperature from exceeding the safe operating range. Excessive temperature may cause equipment damage or reduced thermal efficiency. Example: If the upper limit of the safe operating temperature of the incinerator is 1200°C, the packing algorithm should ensure that the total calorific value of each combination of garbage incinerated is within the allowable range.

[0250] S214, humidity control, need to consider:

[0251] Maximum Moisture Content, corresponding constraint: Too high humidity of garbage will affect combustion efficiency, because too much water requires a lot of heat energy to evaporate. The average humidity of each garbage combination incinerated should not be higher than the expected humidity high threshold. Example: If the maximum humidity that the garbage incinerator can handle, that is, the expected humidity high threshold, is 30%, the packing algorithm should ensure that the humidity of each garbage combination incinerated does not exceed this threshold during incineration.

[0252] Minimum Moisture Content, corresponding constraint: Too low humidity of garbage will cause too fast combustion or overheating, affecting combustion control. Each combination of garbage incinerated should have an appropriate humidity that is higher than the expected low humidity threshold to help control the combustion speed and balance heat release. Example: If the minimum humidity, i.e. the expected low humidity threshold, is 10%, the algorithm should ensure that the humidity of each combination of garbage incinerated is not lower than this value during incineration to avoid excessive combustion.

[0253] S215, Volatile matter and ash control, need to consider:

[0254] Volatile Matter Content Limit, corresponding constraint: garbage with too high volatile content will cause too intense combustion and produce an unstable combustion environment. Therefore, the volatile content of each garbage combination incinerated needs to be controlled within a reasonable range, that is, not exceeding the expected volatile content threshold, to prevent sudden fluctuations in temperature and pressure in the furnace. Example: If the expected volatile content threshold is 60%, the packing algorithm should ensure that the volatile content of each garbage combination incinerated meets this limit.

[0255] Ash Content Limit, corresponding constraint: the ash content in the garbage affects the handling capacity of the slag after incineration. Too much ash will reduce the calorific value utilization rate and increase the slag handling burden. The algorithm needs to control the ash content of each garbage combination incinerated within a reasonable range, that is, not exceeding the expected ash content threshold. Example: If the design of the slag handling system allows a maximum ash content, that is, an expected ash content threshold of 20%, the algorithm should ensure that the ash content in each garbage combination incinerated does not exceed this value.

[0256] S216, Pollutant emission limits, need to consider:

[0257] Nitrogen oxides (NO x ) generation limit, the corresponding constraint condition is: according to the nitrogen content of the garbage, the potential generation of nitrogen oxides of each garbage combination incinerated is controlled, that is, the nitrogen content in each garbage combination does not exceed the expected nitrogen content threshold, so as to avoid NO x Emissions exceed the limit. Example: If NO x Emissions shall not exceed 150mg (milligrams) / Nm 3 (Unit: cubic meter at 0 degrees Celsius and 1 standard atmosphere). The algorithm needs to ensure that the nitrogen content in each garbage combination incinerated is controlled within the corresponding range, that is, within the expected nitrogen content threshold.

[0258] Sulfur dioxide (SO2) generation limit, corresponding constraint: Based on the sulfur content in the garbage, control the SO2 emission potential, that is, the sulfur content in each garbage combination incinerated does not exceed the expected sulfur content threshold to avoid excessive sulfur emissions. Example: If the SO2 emission limit is 100mg / Nm 3 , the algorithm should ensure that the sulfur content in each combination of waste incinerated is lower than the allowed value, namely the expected sulfur content threshold.

[0259] Hydrogen chloride (HCl) emission control, corresponding constraints: According to the chlorine content in the garbage, control the generation of HCl, that is, the chlorine content in each garbage combination incinerated does not exceed the expected chlorine content threshold to prevent the generation of a large amount of corrosive gas during the incineration process. Example: If the upper limit of HCl emission allowed by the incinerator is 50mg / Nm 3 , the binning algorithm needs to ensure that the chlorine content in each waste combination incinerated is below the expected sulfur content threshold to reduce HCl emissions.

[0260] S217, burning time and speed limit, need to consider:

[0261] Combustion Rate Limitation, corresponding constraint: Ensure that the combustion rate of each combination of garbage incinerated matches the operating process of the incinerator to avoid burning too fast or too slow. Too fast combustion will make the temperature difficult to control, while too slow combustion will affect the processing efficiency. Example: The algorithm should ensure that the combustion time of each combination of garbage incinerated remains within the optimal combustion rate range of the incinerator design, such as 20-30 minutes.

[0262] S218, safe operation restrictions, need to consider:

[0263] Explosion Risk Control (Explosion Risk Contro1), corresponding constraints: According to the physical and chemical characteristics of the garbage, identify and limit the content of combustible gas and flammable and explosive garbage in each incineration of the garbage combination to be lower than the expected combustible gas content threshold and the expected flammable and explosive garbage content threshold to prevent the risk of explosion during the incineration process. Example: If the garbage contains a high concentration of volatile organic compounds (VOCs), the algorithm should control the content of volatile substances to be lower than the expected volatile substance content threshold to avoid accumulation and explosion.

[0264] Autoignition Temperature Control (Autoignition Temperature Contro1), the corresponding constraint condition: ensure that the autoignition temperature of each garbage combination incinerated does not exceed the startup safety temperature of the incinerator to prevent the garbage from spontaneously igniting during the loading process. Example: If the autoignition temperature of the garbage is lower than 200℃, the packing algorithm should prioritize the removal of garbage with high autoignition properties to ensure safe operation.

[0265] S219, Pre-processing requirements, need to consider:

[0266] Dehydration pretreatment requirements, corresponding constraints: For garbage with high humidity, the packing algorithm should prioritize marking and arranging dehydration pretreatment to ensure that each garbage combination for incineration has reached a reasonable humidity requirement before entering the incinerator, that is, the humidity is lower than the expected humidity threshold. Example: If the humidity exceeds 35%, the garbage cannot be incinerated directly and needs to be processed by dehydration equipment before packing.

[0267] S22, Optimization combination: Use the bin packing algorithm to combine garbage with different characteristics and select the optimal garbage grouping scheme. That is, this step uses the bin packing algorithm to optimize the garbage combination, and generates the optimal garbage grouping scheme through the three processes of combination, iteration and selection, so that the garbage combination in each incineration process reaches the best balance under the constraints of volume, calorific value, etc. It includes the following steps:

[0268] S221. Combination: Under the premise of satisfying the aforementioned constraints such as incinerator capacity, calorific value, humidity, etc., garbage with different characteristics is grouped to maximize the utilization of incineration calorific value and optimize resource allocation. The specific steps include:

[0269] S221a, initialize input parameters: let the garbage set, i.e. the current batch of garbage, be L = {L1, L2, ..., L n}, L i is the i-th type of garbage in the garbage collection, 1≤i≤n, n is an integer greater than 1, and each type of garbage in the garbage collection has specific physical and chemical properties. i The properties include: volume V i , quality M i , calorific value H i , humidity W i , ash content A i , chlorine content C i , sulfur content S i .

[0270] S221b, Initialize the constraints of the incinerator: Maximum volume V max , is the total volume of the incinerator, used to limit the volume of garbage incinerated at a time; the minimum calorific value H min , is the minimum calorific value required to be achieved in a single incineration process to ensure combustion efficiency; the maximum calorific value H max , to prevent the combustion from being too fast or the temperature in the furnace from being too high; the maximum humidity W max , the humidity in the garbage combination cannot exceed this value, so as not to affect the efficiency of the combustion process; ash and pollutant limits, including the ash upper limit A max 、Upper limit of chlorine content C max and sulfur content limit S max .

[0271] S221c, combination strategy: Use the standard bin packing algorithm to combine different types of garbage to obtain multiple garbage combinations, i.e., garbage groups. Each of the obtained garbage groups is an incineration batch. The goal of garbage combination is to meet the constraints on volume and calorific value, and to maximize the calorific value utilization of incineration.

[0272] S221d, objective function (preliminary objective): maximize the total calorific value H of a single incineration total ,Right now

[0273]

[0274] In the above formula, G represents the set of garbage in the current garbage group.

[0275] S221e, combined constraints, including:

[0276] Volume Constraints

[0277] Calorific value constraint

[0278] Humidity constraints

[0279] Ash and contaminant constraints and

[0280] S222, Iteration: Optimize the garbage grouping through multiple iterations to find the global optimal solution. Each iteration adjusts the garbage combination to gradually meet all combination constraints. The specific steps include:

[0281] S222a, initial grouping: Use a greedy algorithm to generate a preliminary combination, give priority to garbage with high calorific value and low humidity (i.e., calorific value higher than the expected initial grouping calorific value threshold and humidity lower than the expected initial grouping humidity threshold), fill the incinerator and meet its volume limit.

[0282] S222b, local adjustment:

[0283] Adjustment strategy: If the initial combination does not meet the combination constraints, such as excessive calorific value or humidity, the excessive garbage will be gradually removed or replaced, and the qualified garbage will be kept first. For example, when the calorific value is too high, the high calorific value garbage will be removed and the low calorific value garbage will be added;

[0284] Local optimality check: After adjustment, check whether the new combination meets all combination constraints, compare it with the previous combination, and select the optimal solution.

[0285] S222c, repeated iteration: Use global optimization technology based on simulated annealing or genetic algorithm to perform multiple (more than 1) iterations. Each iteration adjusts the existing garbage combination to find a better solution. In each iteration, a new garbage combination is generated and compared with the total calorific value utilization rate, total volume utilization rate of the incinerator, etc. of the previous garbage combination. If the new combination is better than the previous combination, the new combination is retained as the new solution.

[0286] S223, Optimal Selection: Select the best solution from all iteratively generated garbage combinations. The solution should satisfy all combination constraints and perform best in terms of calorific value utilization and volume allocation. The specific steps include:

[0287] S223a, optimize the comprehensive objective function: Under the premise of satisfying all combination constraints, select the combination that maximizes the comprehensive objective function value. The comprehensive objective function value is expressed by the following formula:

[0288]

[0289] In the above formula, Z is the comprehensive objective function value; α, β, γ are weight coefficients, which are set by technicians according to working conditions and are used to balance the optimization of calorific value, volume and humidity; Indicates total calorific value utilization; Indicates the total volume utilization of the incinerator; Indicates the degree of humidity control.

[0290] S223b, optimal solution selection: After the iteration is completed, the garbage combination with the highest comprehensive objective function value is selected as the final optimal solution. This combination can maximize the calorific value utilization and volume efficiency of incineration under all combination constraints.

[0291] S223c, output the optimal solution: the optimal solution includes a detailed list of garbage combinations that are the optimal solution, including information such as the type, quantity, calorific value, volume, etc. of the garbage. The solution can be directly used for the operation of the incinerator and the scheduling of garbage treatment.

[0292] S23. Garbage grouping: Based on the results of the optimization combination, the garbage is packaged according to the optimal solution and prepared to be put into the incinerator for incineration.

[0293] S3. Monitoring and control of the waste incineration process. The specific steps include:

[0294] S31. Real-time monitoring: During the incineration process, the following parameters in the incinerator are monitored in real time through sensors and monitoring systems:

[0295] Temperature-related parameters include: Furnace Temperature: the temperature distribution in different areas inside the incinerator; Flue Gas Temperature: the temperature of the exhaust flue gas, usually measured at the chimney or the inlet of the heat exchanger; Grate Temperature: the temperature of the garbage when it burns on the grate, which affects the completeness of combustion; Wall Surface Temperature: the temperature of the inner wall of the furnace, used to monitor whether the furnace wall is overheated.

[0296] Pressure-related parameters include: Furnace Pressure: the gas pressure inside the furnace, which is monitored to prevent gas leakage or incomplete combustion; Chimney Pressure: the pressure in the flue gas emission channel, which affects the emission flow rate and control; Blower Pressure: the pressure of the air supply system, which affects the air supply.

[0297] It is related to the combustion rate, including: Fuel Feed Rate: the amount of garbage put into the furnace per unit time; Air Supply Rate: the amount of oxygen or air supplied during the combustion process; Combustion Rate: the garbage combustion rate, which reflects the completeness and speed of garbage combustion.

[0298] Gas composition parameters, including: Oxygen concentration (O2Concentration): the remaining oxygen content during the combustion process, affecting the combustion efficiency; Carbon dioxide concentration (CO2Concentration): the main gas component produced when the combustion is complete; Carbon monoxide concentration (CO Concentration): the concentration of toxic gases produced when the combustion is incomplete; Nitrogen oxide concentration (NO x Concentration): Nitrogen oxides include nitric oxide (NO) and nitrogen dioxide (NO2), which are important sources of air pollution; Sulfur dioxide concentration (SO2 Concentration): The concentration of acidic gases produced when sulfur-containing garbage is burned; Hydrogen chloride concentration (HCl Concentration): The concentration of corrosive gases produced when chlorine-containing garbage (such as PVC plastic) is burned; Ammonia concentration (NH3 Concentration): The concentration of gases produced when garbage with high nitrogen content is burned; Hydrogen sulfide concentration (H2S Concentration): The concentration of toxic gases produced when sulfur-containing substances are burned; Volatile organic compound concentration (VOCs Concentration): The concentration of volatile organic compounds such as methane and benzene, which comes from the concentration of unburned organic garbage.

[0299] Particulate matter parameters include: Particulate Matter Concentration (PM): the concentration of tiny solid particles produced after incineration, usually including PM10 and PM2.5; Fly Ash Content: the amount of fly ash carried in the flue gas, which needs to be treated by filtering equipment.

[0300] Heat recovery parameters include: Steam Pressure: the steam pressure used for power generation; Steam Temperature: the steam temperature used for power generation, which determines the heat recovery efficiency; Steam Flow Rate: the steam flow rate generated from the incinerator; Cooling Water Temperature: the inlet and outlet temperatures of the cooling water in the cooling system, which is used to control the heat exchange efficiency.

[0301] Other parameters include: Slag Discharge Rate: the amount of slag discharged per unit time, reflecting the residue after combustion; Flue Gas Velocity: the flow rate of flue gas emissions, which affects the emission of pollutants; Humidity: the air humidity and flue gas humidity during the incineration process, which affect the combustion conditions; Fuel Moisture Cntent: the moisture content of the garbage, which affects the combustion efficiency and flue gas composition; Furnace Visibility: the visibility in the furnace is monitored by cameras or optical equipment to determine the combustion conditions.

[0302] S32, dynamic adjustment: using heuristic methods to analyze the real-time monitoring data, and dynamically adjusting the combustion strategy according to the analysis results, including: when one of the parameters monitored in step S31 exceeds the set range (such as temperature is too high, oxygen concentration is too low, CO concentration is too high), analyzing and calculating the adjustment of feed rate, air supply and combustion chamber pressure, etc., to ensure the stability of the combustion process, including the following adjustments:

[0303] S321, adjust the feed rate, based on the formula:

[0304] F new =F currcnt +K T ·(T set -T measurcd ),

[0305] In the above formula, F new is the adjusted feed rate (tons / hour), F current is the current feed rate, K T is the temperature control coefficient, which depends on the system response speed and is generally 0.1 to 0.5. set is the target temperature (set value), T mcasurcd The above two temperature units are degrees Celsius (°C) or degrees Fahrenheit (°F).

[0306] S322. Adjust the air supply according to the formula:

[0307] A new =A currcnt +K O ·(O set -O measured ),

[0308] In the above formula, A new is the adjusted air supply (m3 / h), A current is the current air supply, K O is the oxygen regulation coefficient, which is generally between 0.05 and 0.2. The specific value depends on the system response speed and the sensitivity of the air flow control equipment. set is the target oxygen concentration (%), which is generally set at 6% to 12%. measured is the actual monitored oxygen concentration.

[0309] S323. Adjust the combustion chamber pressure based on the formula:

[0310] P new =P current +K P ·(P set -P measuted ),

[0311] In the above formula, P new is the adjusted combustion chamber pressure, P current is the current combustion chamber pressure, K P is the pressure adjustment coefficient, usually ranging from 0.1 to 0.3, P set is the target pressure value, which is usually maintained in the slightly negative pressure range (-5 Pa to -20 Pa). measured is the actual monitored combustion chamber pressure.

[0312] S324. Adjust the combustion rate based on the formula:

[0313] R comb =f(F new , A new ),

[0314] In the above formula, R comb is the burning rate (kg / s), F new is the new feed rate, A new is the new air supply amount, and the specific form of the formula f is obtained through experimental simulation.

[0315] When the combustion rate is too fast (i.e., exceeds the preset first combustion rate threshold), the air supply and feed rate are appropriately reduced to avoid excessive temperature and pressure in the furnace; when the combustion rate is too slow (i.e., lower than the preset second combustion rate threshold), the air supply and feed rate are increased to improve combustion efficiency.

[0316] S325. Control of pollutant emissions, including:

[0317] When it is detected that the CO concentration is too high (i.e. the CO concentration exceeds the preset CO concentration threshold), the air supply is increased or the fuel supply is reduced to ensure complete combustion of the garbage and reduce CO.

[0318] When NO is detected x Too high a concentration (i.e. NO x Concentration checked by preset NO x When the concentration threshold is reached, the NO concentration can be reduced by lowering the combustion temperature or supplying oxygen in stages. x Generation of.

[0319] When it is detected that the SO2 concentration is too high (ie, the SO2 concentration exceeds a preset SO2 concentration threshold), the amount of desulfurization agent such as limestone or lime is increased to neutralize the generated SO2.

[0320] The present invention also provides a computer device, which includes a memory, a first processor, and a first computer program stored in the memory and executable on the first processor, wherein the first computer program implements the above-mentioned waste-to-energy optimization method when executed by the first processor.

[0321] The present invention also provides a computer-readable storage medium, which is used to store a second computer program. The second computer program can be executed by at least one second processor to enable the at least one second processor to execute the above-mentioned waste-to-energy optimization method.

[0322] The present invention optimizes the grouping of garbage by applying a packing algorithm, so that the calorific value release in each incineration process is more balanced and efficient. Compared with the traditional garbage classification and combustion method, the present invention can release higher heat under the same incineration conditions, thereby improving the efficiency of converting heat energy into electrical energy. The present invention uses a packing algorithm to finely combine garbage, maximize the release and utilization of calorific value, and solve the problem that the existing technology is difficult to fully consider the diversity and complex combustion characteristics of garbage, resulting in insufficient utilization of calorific value. Under the same garbage input conditions, the present invention achieves an average 15% increase in power generation efficiency, while the power generation efficiency of the traditional method is only 5-10%. At the same time, the present invention increases the calorific value utilization rate from 85% of the traditional method to more than 92%. The present invention uses a heuristic method to use real-time monitoring and feedback mechanisms to continuously optimize the combustion process, reduce temperature and pressure fluctuations, and solve the problem that the existing technology usually adopts a fixed combustion strategy and lacks a dynamic adjustment mechanism, resulting in large temperature fluctuations during the combustion process, affecting the overall efficiency. The present invention reduces the fluctuation range of the combustion temperature from ±50°C of the traditional method to ±15°C, and reduces the proportion of incomplete combustion from the traditional 10% to less than 3%. Compared with the existing technology, the present invention effectively controls the generation of pollutants in the combustion process through refined garbage grouping and combustion strategy optimization, and reduces the negative impact on the environment through efficient heat recovery, reducing CO emissions from 50ppm in traditional methods to below 20ppm, and reducing NOx emissions from 150mg / Nm 3 Reduced to 80mg / Nm 3 , reducing SO2 emissions from the traditional method of 200mg / Nm 3 Reduced to 100mg / Nm 3 .

[0323] The present invention applies the packing algorithm to the field of waste-to-energy for the first time, and is used to group and combine waste with different characteristics. Through the packing algorithm, waste with different combustion characteristics can be optimally combined so that the calorific value and volume of each group of waste can reach the best balance, thereby improving the efficiency and balance of the incineration process. The present invention introduces a heuristic method for real-time optimization of the combustion strategy and heat recovery strategy during the waste incineration process. The heuristic method can dynamically adjust the incineration parameters and heat recovery parameters according to real-time monitoring data such as temperature, combustion rate, flue gas composition, etc., to ensure the efficient operation and stability of the system. The present invention realizes refined control of the waste combustion process by combining the packing algorithm and the heuristic method. This control is not only reflected in the initial grouping of the waste, but also includes dynamic adjustments based on real-time data during the incineration process to ensure stable and efficient heat release during the combustion process.

[0324] Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent substitutions for some of the technical features therein; and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing waste-to-energy generation, characterized in that: Includes steps: S1. Waste classification and preliminary data processing; S2, applying a binning algorithm to combine and optimize the garbage; S3. Monitoring and control of the incineration process of the garbage.

2. The waste-to-energy optimization method according to claim 1, characterized in that: The step S1 comprises the steps of: S11, data collection: obtaining basic information of the garbage from the garbage collection system; S12, preliminarily classifying the garbage based on the physical and chemical properties of the garbage; S13, feature extraction: extracting combustion characteristic parameters of each type of garbage through detection equipment, and using the combustion characteristic parameters as input parameters in the packing algorithm.

3. The waste-to-energy optimization method according to claim 2, characterized in that: The step S2 comprises the steps of: S21, parameter setting or constraint setting, that is, setting the constraint conditions of the packing algorithm; S22, using the bin packing algorithm to optimize the combination of the garbage with different characteristics, and generating an optimal garbage grouping solution through three steps of combination, iteration and optimization; S23, garbage grouping: according to the result of the optimization combination, the garbage is packaged and prepared to be put into the incinerator for incineration.

4. The waste-to-energy optimization method according to claim 3, characterized in that: In step S21, the constraint conditions include: S211. Capacity limits of incinerators: The total volume of the garbage combination incinerated each time shall not exceed the maximum capacity of the incinerator. The incinerator has a maximum load mass that it can bear; the total mass of the garbage combination incinerated each time does not exceed the bearing capacity of the incinerator chamber and the supporting structure; S212, calorific value requirements: The total calorific value of the garbage combination in each incineration must reach or exceed the minimum calorific value requirement of the incineration furnace. The total calorific value of the garbage combination incinerated each time shall not exceed the maximum design calorific value of the incinerator; S213, Combustion temperature requirements: The combustion characteristics of the garbage combination in each incineration are combined to maintain the temperature in the furnace higher than the minimum combustion temperature, The calorific value obtained from the combustion of the garbage combination each time is incinerated does not exceed the expected calorific value threshold; S214, Humidity Control: The average humidity of the garbage combination in each incineration is not higher than the expected humidity high threshold, The humidity of the garbage combination incinerated each time is not lower than the expected humidity low threshold; S215, Volatile matter and ash control: The volatile matter content of each waste combination incinerated does not exceed the expected volatile matter content threshold, The ash content of each waste combination incinerated does not exceed the expected ash content threshold; S216. Pollutant emission limits: The nitrogen content of each waste combination incinerated does not exceed the expected nitrogen content threshold, The sulfur content of each waste combination incinerated does not exceed the expected sulfur content threshold, The chlorine content of each waste combination incinerated does not exceed the expected chlorine content threshold; S217, Burning time and speed limit: The burning time of the garbage combination in each incineration is kept within the optimal burning rate range of the incinerator design; S218, Safety operation restrictions: Identify and limit the contents of combustible gas and flammable and explosive waste of each waste combination incinerated to below the expected combustible gas content threshold and the expected flammable and explosive waste content threshold; The auto-ignition temperature of the garbage combination incinerated each time does not exceed the startup safety temperature of the incinerator; S219, Preprocessing requirements: The humidity of each waste combination incinerated is lower than the expected humidity threshold.

5. The waste-to-energy optimization method according to claim 4, characterized in that: The step S22 comprises the steps of: S221, combination, specifically comprising the steps of: S221a, initialize input parameters: let the garbage set be L = {L1, L2, ..., L n }, L i is the i-th type of garbage in the garbage collection, 1≤i≤n, n is an integer greater than 1, L i The properties include: volume V i , quality M i , calorific value H i , humidity W i , ash content A i , chlorine content C i , sulfur content S i ; S221b, initializing the constraints of the incinerator: maximum volume V max , minimum calorific value H min , maximum calorific value H max , maximum humidity W max , ash content upper limit A max 、Upper limit of chlorine content C max and sulfur content limit S max ; S221c, combination strategy: using the packing algorithm to combine different types of garbage to obtain multiple garbage combinations, i.e., garbage groups, each of which is an incineration batch; S221d, objective function: maximize the total calorific value H of a single incineration total ,Right now In the above formula, G represents the set of garbage in the current garbage group; S221e, combined constraints, including: Volume Constraints Calorific value constraint Humidity constraints Ash and contaminant constraints and S222, iteration, specifically including the steps: S222a, initial grouping: using a greedy algorithm to generate a preliminary combination to fill the incinerator and meet its volume limit; S222b, local adjustment: Adjustment strategy: If the initial garbage combination does not meet the constraints, the excessive garbage will be gradually eliminated or replaced, and the qualified garbage will be retained; Local optimality check: After adjustment, check whether the new garbage combination meets all constraints, compare with the previous combination, and select the optimal solution; S222c, repeated iteration: using a global optimization technology based on simulated annealing or genetic algorithm, performing multiple iterations, adjusting the existing garbage combination on the basis of each iteration, and finding a better solution: in each iteration, generating a new garbage combination and comparing the total calorific value utilization rate and the total volume utilization rate of the incinerator with the previous garbage combination, if the new garbage combination is better than the previous garbage combination, retaining the new garbage combination as a new solution; S223, optimal selection: selecting the optimal solution from all the iteratively generated garbage combinations, specifically including the steps of: S223a, optimizing the comprehensive objective function: Under the premise of satisfying all the combination constraints, select a combination that maximizes the comprehensive objective function value, and the comprehensive objective function value is expressed by the following formula: In the above formula, Z is the comprehensive objective function value; α, β, γ are weight coefficients; Indicates the total calorific value utilization rate; Indicates the volume utilization rate of the incinerator; Indicates the degree of humidity control; S223b, optimal solution selection: after the iteration is completed, the garbage combination with the highest comprehensive objective function value is selected as the final optimal solution; S223c, outputting an optimal solution: the optimal solution includes a detailed list of garbage combinations that are the optimal solutions.

6. The waste-to-energy optimization method according to claim 5, characterized in that: In step S23, the garbage is packaged according to the optimal solution.

7. The waste-to-energy optimization method according to claim 6, characterized in that: The step S3 comprises: S31. Real-time monitoring: During the incineration process, the following parameters in the incinerator are monitored in real time through sensors and monitoring systems: Temperature related parameters, including: furnace temperature, flue gas temperature, hearth temperature, wall temperature; Pressure related parameters, including: furnace pressure, chimney pressure, blower pressure; Combustion rate related parameters, including: fuel delivery rate, air supply, combustion rate; Gas composition parameters, including: oxygen concentration, carbon dioxide concentration, carbon monoxide concentration, nitrogen oxide concentration, sulfur dioxide concentration, hydrogen chloride concentration, ammonia concentration, hydrogen sulfide concentration, volatile organic compound concentration; Particulate matter parameters, including: particle concentration, fly ash content; Heat recovery parameters, including: steam pressure, steam temperature, steam flow, cooling water temperature; Other parameters include: slag emission rate, exhaust gas flow rate, humidity, fuel moisture content, and furnace visibility.

8. The waste-to-energy optimization method according to claim 7, characterized in that: The step S3 further comprises: S32, dynamic adjustment, including: when one of the parameters monitored in step S31 exceeds a set range, the following adjustment is performed: S321, adjust the feed rate, based on the formula: F new =P currcnt +K T ·(T set -T measured ), In the above formula, r new is the adjusted feed rate, F′ current is the current feed rate, K T is the temperature control coefficient, T sct is the target temperature, T measured is the actual monitored furnace temperature; S322. Adjust the air supply according to the formula: THE new =A current +K O ·(THE set -THE measured ), In the above formula, A new is the adjusted air supply, A current is the current air supply, K O is the oxygen regulation factor, O sct is the target oxygen concentration, O measured is the actual monitored oxygen concentration; S323. Adjust the combustion chamber pressure based on the formula: P new =P current +K P ·(P set -P measured ), In the above formula, P new is the adjusted combustion chamber pressure, P current is the current combustion chamber pressure, K P is the pressure regulation coefficient, P set is the target pressure value, P measured is the actual monitored combustion chamber pressure; S324. Adjust the combustion rate based on the formula: R comb =f(F new ,A new ), In the above formula, R comb is the burning rate, F new is the new feed rate, A new is the new air supply amount, and the specific form of the formula f is obtained through experimental simulation; S325. Control of pollutant emissions, including: When it is detected that the CO concentration is too high, that is, the CO concentration exceeds the preset CO concentration threshold, the air supply is increased or the fuel supply is reduced; When NO is detected x Too high a concentration of NO x Concentration checked by preset NO x When the concentration threshold is reached, the combustion temperature is lowered or oxygen is supplied in stages; When it is detected that the SO2 concentration is too high, that is, the SO2 concentration exceeds the preset SO2 concentration threshold, the desulfurization agent is added.

9. Computer device, characterized in that The invention comprises a memory, a first processor and a first computer program stored in the memory and executable on the first processor, wherein the first computer program, when executed by the first processor, implements the waste-to-energy optimization method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium is used to store a second computer program, and the second computer program can be executed by at least one second processor, so that the at least one second processor executes the waste-to-energy optimization method according to any one of claims 1-8.

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