An exhaust gas treatment system and method using an oxidation furnace for oxidation treatment

Abstract

The application provides a waste gas treatment system and method using an oxidation furnace for oxidation treatment, and relates to the technical field of waste gas treatment. The system comprises a waste gas treatment and data collection module for pretreating different types of waste gas and collecting data. A waste heat strategy development module is used for obtaining production load data by processing the influence degree of different types of waste gas on the overall equipment, and developing a waste heat utilization strategy according to waste heat parameter change data. A waste heat strategy optimization module is used for obtaining waste heat prediction data by predicting waste heat changes, developing an adjustment strategy according to the production load data and the waste heat prediction data, and adjusting the waste heat utilization strategy according to user demand and waste heat quality data to obtain an optimized waste heat scheme. The application significantly improves the comprehensive utilization rate of energy, and realizes fine management of waste gas treatment and dynamic adjustment of the waste heat utilization strategy, thereby improving the scientificity and effectiveness of energy management.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of waste gas treatment, and in particular to a waste gas treatment system and method using an oxidation furnace for oxidation treatment. BACKGROUND

[0002] With the acceleration of industrialization, waste gas treatment has become a key link for environmental protection and sustainable development of enterprises. The traditional waste gas treatment system generally has the problem of low waste heat utilization efficiency, and a large amount of waste heat resources is wasted, which not only increases the energy consumption and production cost of enterprises, but also causes unnecessary heat pollution to the environment.

[0003] However, the existing waste gas treatment system has many problems. On the one hand, waste gas usually contains particulate matter, oily substances and the like. In the waste heat recovery process, these substances are easy to adhere to the wall of the heat exchange tube, forming a dust layer, which reduces the waste heat conduction conversion rate and the waste heat utilization efficiency. Moreover, when the amount of waste gas generated is large and the flow rate is fast, the treated waste gas may still have some heat, which further affects the waste heat recovery effect. On the other hand, due to the complexity and variability of the composition of waste gas, the existing system often cannot dynamically adjust the waste heat distribution strategy according to the real-time changes of waste gas and production requirements, making it difficult to achieve optimal utilization of waste heat, and cannot well meet the energy saving and emission reduction and production process of enterprises. The demand for heat energy. In addition, different types of waste gas have different effects on the treatment equipment, and if not considered, it may affect the normal operation and service life of the equipment and increase the maintenance cost.

[0004] In view of the above defects, the present application aims to provide a waste gas treatment system and method using an oxidation furnace for oxidation treatment. SUMMARY

[0005] The present application provides a waste gas treatment system and method using an oxidation furnace for oxidation treatment, to solve the defects of low waste heat utilization efficiency and inability to dynamically adjust the waste heat distribution strategy in the existing waste gas treatment system.

[0006] In one aspect, the present application provides a waste gas treatment system using an oxidation furnace for oxidation treatment, comprising:

[0007] A waste gas treatment and data collection module is used to pretreat different types of waste gas, perform oxidation reaction through an oxidation furnace, collect waste heat data after oxidation reaction, and monitor waste gas changes in real time to obtain waste gas fluctuation data.

[0008] A waste heat strategy development module is used to obtain production load data according to the influence of different types of waste gas on the overall equipment by waste gas-equipment load method, extract waste heat parameter change data and waste heat quality data from waste heat data, and develop a waste heat utilization strategy according to the waste heat parameter change data.

[0009] The waste heat strategy optimization module is used to predict waste heat changes based on waste heat parameter change data using waste heat prediction methods. It then formulates adjustment strategies based on production load data and waste heat prediction data, and further adjusts the waste heat utilization strategy by combining user needs and waste heat quality data to obtain an optimized waste heat solution.

[0010] According to the present invention, a waste gas treatment system employing an oxidation furnace for oxidation treatment includes a pretreatment step for different types of waste gas, comprising:

[0011] Based on different types, waste gas is classified into organic waste gas, acid and alkali waste gas, dust-containing waste gas, malodorous waste gas, and high-temperature and high-humidity waste gas.

[0012] Organic waste gas is treated by filtration and dust removal, condensation and cooling, adsorption and concentration, and gas washing and purification; acid and alkaline waste gas is treated by neutralization and dust removal.

[0013] Dust-laden exhaust gas is treated mechanically, by filtration and wet dust removal; odorous exhaust gas is treated by water washing, dust removal and humidification, acid and alkali washing and adsorption; and high-temperature and high-humidity exhaust gas is treated by cooling and dehumidification.

[0014] According to the present invention, a waste gas treatment system employing an oxidation furnace for oxidation treatment includes the following steps for obtaining production load data:

[0015] Based on the physical and chemical properties of different waste gases, the characteristics of the corresponding waste gas types are determined. Parameters during the operation of the affected equipment are collected, and the generation and characteristic changes of waste gases at different treatment stages are analyzed to obtain the equipment characteristics.

[0016] A factor analysis model is established based on the characteristics of exhaust gas and equipment to analyze the quantitative relationship between exhaust gas parameters and equipment performance, determine the influence weight of each parameter in the exhaust gas parameters on equipment operation, and calculate the actual impact of different types of exhaust gas on the equipment.

[0017] An energy balance model was established to calculate the total energy balance value, and production load data for treating different types of waste gas was calculated by combining the equipment's design load and actual impact.

[0018] According to the present invention, a waste gas treatment system employing an oxidation furnace for oxidation treatment includes the following steps for calculating the total energy balance value:

[0019] The energy input items are determined based on the fuel combustion heat and electricity input required to treat different waste gases, combined with the energy of the waste gas itself.

[0020] The energy output item is determined based on the energy emitted after waste gas treatment and the energy carried away by products and by-products.

[0021] The total energy balance value is calculated according to the energy input and the energy output, in combination with the energy loss in the reaction process and the internal energy generated by the reaction.

[0022] According to the waste gas treatment system for oxidation treatment by using an oxidation furnace provided by the application, the steps of extracting the waste heat parameter change data and the waste heat quality data include:

[0023] The temperature change data is obtained by calculating the difference between the initial temperature of the waste gas after the oxidation reaction and the medium temperature after the waste heat recovery through analyzing the temperature data at different positions, and the flow parameter change data is obtained by calculating the flow change of the waste gas through counting the flow data at the inlet and outlet of the waste heat recovery.

[0024] The pressure parameter change data is obtained by calculating the loss and the change range of the pressure through the pressure change at the outlet of the oxidation furnace and the waste heat recovery equipment, and the waste heat parameter change data is composed of the temperature change data and the flow parameter change data.

[0025] The heat quality of the waste heat is obtained by calculating the total heat and the heat power of the waste heat according to the temperature change data, the waste gas parameters and the specific heat capacity, and the temperature quality is determined.

[0026] The stability of the waste heat is evaluated by analyzing the change trend of the waste heat parameters with time, and the waste heat quality data is composed of the heat quality and the temperature quality.

[0027] According to the waste gas treatment system for oxidation treatment by using an oxidation furnace provided by the application, the steps of formulating the waste heat utilization strategy include:

[0028] The energy recovery target is obtained by determining the scale and the degree of the waste heat recovery utilization according to the energy demand and the energy saving and emission reduction target of the enterprise, and the production demand is obtained by analyzing the demand for heat energy of the production process and the equipment in the enterprise.

[0029] The type and the amplitude of the parameter change are identified through the temperature change data and the flow change data, and the time characteristics of the waste heat parameter change data are extracted.

[0030] The matching strategy is formulated through the energy recovery target and the production demand, the waste heat parameter fluctuation scene is generated according to the type and the amplitude of the parameter change and the time characteristics, and the key factors of different scenes are determined from the waste heat parameter fluctuation scene.

[0031] The waste heat utilization strategy is obtained by selecting the corresponding waste heat utilization mode according to the waste heat parameter fluctuation scene and adjusting the influence degree of the key factors on the matching strategy.

[0032] According to the waste gas treatment system for oxidation treatment by using an oxidation furnace provided by the application, the steps of obtaining the waste heat prediction data include:

[0033] A waste heat prediction model based on random forest is established, and the waste heat temperature, waste heat heat and waste heat pressure are obtained by analyzing the change rule and characteristics of the waste heat parameter change data in each working period.

[0034] The waste heat prediction model is trained by taking the waste gas characteristics, environmental characteristics and time characteristics as inputs and the waste heat temperature, waste heat heat and waste heat pressure as outputs, and the model parameters meeting the test accuracy are reserved.

[0035] According to the current waste gas characteristics, current environmental characteristics and current time characteristics, the corresponding current waste heat temperature, current waste heat heat and current waste heat pressure are extracted, and the waste heat parameter prediction value is obtained by inputting the trained waste heat prediction model.

[0036] According to the heat loss rate calculated by heat transfer, and combined with the environmental temperature, the related waste heat steam evaporation rate is calculated, and the formula is expressed as:

[0037]

[0038]

[0039] In the formula, is the heat loss rate, is the thermal conductivity of the material, is the heat transfer area, is the waste heat temperature, is the environmental temperature, is the material thickness, is the total heat of waste heat, is the time, is the initial hot water quality, is the evaporation coefficient, is the saturated steam pressure of hot water at temperature is the water vapor partial pressure in the environment, is the waste heat steam evaporation rate. The waste heat prediction data is calculated by combining the waste heat parameter prediction value, the heat loss rate and the waste heat steam evaporation rate.

[0040] According to the waste gas treatment system for oxidation treatment provided by the application, the steps of formulating the adjustment strategy include:

[0041] The waste heat prediction data and the production load data are converted to the same time granularity by an interpolation algorithm, and the abnormal value is processed.

[0042] A two-dimensional matrix is established by describing the matching relationship between different time periods and waste heat grades.

[0043]

[0044] ​Calculate the heat gap of each period, and grade it according to the gap degree, into multiple levels of gaps.

[0045] Establish an optimization model targeting energy efficiency, economic cost and carbon emissions.

[0046] Use the dynamic programming algorithm to transfer the state of the optimization model to obtain the waste heat utilization value, and combine different levels of gaps to develop a graded response mechanism to obtain the adjustment strategy.

[0047] According to the waste gas treatment system for oxidation treatment provided by the application, the steps of adjusting the optimized waste heat scheme include:

[0048] According to the urgency and importance of user demand, classify and combine enterprise production plan to estimate the size and duration of different types of user demand in different periods to obtain priority ranking.

[0049] Combine waste heat quality data and waste heat prediction data to evaluate the total amount and space-time distribution characteristics of waste heat resources, and combine the matching degree with user demand to obtain the evaluation result.

[0050] According to the priority ranking and evaluation result, adjust the waste heat utilization strategy, reallocate the waste heat resources, and determine the waste heat utilization mode according to different waste heat quality and user demand to obtain the optimized waste heat scheme.

[0051] In another aspect, the application also provides a waste gas treatment method using an oxidation furnace for oxidation treatment, comprising:

[0052] Pretreat different types of waste gas, perform oxidation reaction through the oxidation furnace, collect waste heat data after oxidation reaction, and obtain waste gas fluctuation data by real-time monitoring of waste gas changes.

[0053] According to the influence degree of different types of waste gas on the overall equipment by the waste gas-equipment load method, obtain production load data, extract waste heat parameter change data and waste heat quality data from waste heat data, and develop waste heat utilization strategy according to waste heat parameter change data.

[0054] Use waste heat prediction method to predict waste heat change according to waste heat parameter change data to obtain waste heat prediction data, develop adjustment strategy according to production load data and waste heat prediction data, and adjust waste heat utilization strategy according to user demand and waste heat quality data to obtain optimized waste heat scheme.

[0055] This invention provides a waste gas treatment system and method using an oxidation furnace. By employing the waste gas-equipment load method, it analyzes the quantitative relationship between the physicochemical properties of waste gas and equipment operating parameters, establishing factor analysis and energy balance models. This solves the problems of lack of quantitative analysis of the impact of different types of waste gas on equipment performance and difficulty in accurately assessing production load. Using a waste heat prediction method, combined with random forest algorithms and heat transfer formulas, it constructs a waste heat parameter prediction model, solving the problems of large fluctuations in waste heat parameters and lagging utilization strategies. Through a multi-objective optimization model and dynamic programming algorithm, a "prediction-adjustment-verification" closed loop is formed, solving the problem of balancing and real-time controlling multiple objectives such as energy efficiency, economic cost, and carbon emissions. Ultimately, it reduces production load calculation errors, significantly improves waste gas treatment efficiency, equipment reliability, and waste heat resource utilization, and enhances energy efficiency, system adaptability, and intelligent decision-making capabilities. Attached Figure Description

[0056] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0057] Fig. 1 This is a schematic diagram of a waste gas treatment system using an oxidation furnace for oxidation treatment provided in an embodiment of the present invention;

[0058] Fig. 2 This is a schematic flowchart of a waste gas treatment method using an oxidation furnace, provided by an embodiment of the present invention. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0060] The following is combined Figs. 1-2 This invention describes a waste gas treatment system and method that employs an oxidation furnace for oxidation treatment.

[0061] like Fig. 1 As shown in the embodiment of the present invention, a waste gas treatment system and method using an oxidation furnace for oxidation treatment is provided. The executing entity can be a waste gas treatment system using an oxidation furnace for oxidation treatment, including:

[0062] The waste gas treatment and data collection module is used for pre-treating different types of waste gas, carrying out oxidation reaction through the oxidation furnace, collecting waste heat data after the oxidation reaction, and obtaining waste gas fluctuation data by monitoring the change of waste gas in real time. The collection of waste heat data can be realized by installing temperature sensors, pressure sensors, flow meters, heat meters and other monitoring devices at the outlet of the oxidation furnace and the relevant positions of the waste heat recovery system to monitor the temperature, pressure and flow of waste gas after the oxidation reaction and the temperature and flow of the inlet and outlet of the waste heat recovery system in real time.

[0063] The steps of pre-treating different types of waste gas include:

[0064] According to different types, the waste gas is divided into organic waste gas, acid-base waste gas, dust-containing waste gas, malodorous waste gas and high-temperature and high-humidity waste gas.

[0065] The organic waste gas is treated by filtration, dust removal, condensation, adsorption concentration and gas washing purification, and the acid-base waste gas is treated by neutralization and dust removal.

[0066] The dust-containing waste gas is treated by mechanical filtration and wet dust removal, the malodorous waste gas is treated by water washing, dust removal and humidification, acid-base washing and adsorption, and the high-temperature and high-humidity waste gas is treated by cooling and dehumidification.

[0067] Organic waste gas: filter dust removal: if the waste gas carries particulate matter, a dry filter such as a bag filter, activated carbon filter, etc. should be used first to remove dust, particles and other impurities to prevent them from clogging subsequent treatment equipment such as adsorbents, catalysts, etc. and ensure normal operation of the waste gas treatment system.

[0068] Condensation cooling: for high-temperature organic waste gas, a condenser can be used for cooling treatment to condense organic vapor in the waste gas into liquid, facilitating subsequent separation and recovery, while reducing the temperature of the waste gas and reducing the impact on subsequent treatment equipment.

[0069] Adsorption concentration: for low-concentration and large-volume organic waste gas, activated carbon adsorption, zeolite rotary adsorption and other adsorption concentration technologies can be used to adsorb organic matter in the waste gas on the surface of the adsorbent, increase the concentration of organic matter, reduce the difficulty and cost of subsequent treatment, and then perform desorption and purification treatment.

[0070] Gas washing and purification: using a gas washing tower, water or chemical absorption liquid is used to wash the waste gas to remove acidic gases, part of the organic matter and oil mist and other impurities. Common absorption liquids include lye, acid, oxidizing agent solution, etc. The appropriate absorption liquid is selected according to the composition and properties of the waste gas.

[0071] Acid and alkali waste gas: neutralization treatment: acidic waste gas can be absorbed by alkali solution, such as sodium hydroxide solution, lime milk, etc. Alkaline waste gas is absorbed by acid solution, such as sulfuric acid, hydrochloric acid, etc. The waste gas is fully contacted with the absorption liquid through the equipment such as spray tower and packed tower, and the neutralization reaction occurs, generating corresponding salt and water, so as to achieve the purpose of removing acid and alkali waste gas.

[0072] Dust removal and impurity removal: if the waste gas also contains particulate matter or other impurities, dust removal treatment can be carried out before neutralization treatment. Cyclone dust collector, bag type dust collector and other equipment are used to remove dust in waste gas, improve the effect of neutralization treatment and the service life of absorption liquid.

[0073] Dusty waste gas: mechanical dust removal: the particulate matter in the waste gas is separated out by mechanical force. Common mechanical dust removal equipment includes gravity settling chamber and cyclone dust collector. Gravity settling chamber relies on the natural sedimentation of particulate matter itself, and is suitable for treating large particles and high concentration dust. Cyclone dust collector uses centrifugal force to separate particulate matter from gas flow, and has relatively high dust removal efficiency, which is good for removing dust particles above 5 μm.

[0074] Filter dust removal: the particulate matter in the waste gas is intercepted by filter medium such as filter cloth and filter bag. Common equipment includes bag type dust collector and filter cartridge dust collector. Bag type dust collector has high dust removal efficiency and can effectively remove dust particles above 1 μm, but it has poor adaptability to high temperature and high humidity waste gas. Filter cartridge dust collector has compact structure, small floor area and large filtration area, and is suitable for treating medium concentration dust waste gas.

[0075] Wet dust removal: water or other liquid is fully contacted with dusty waste gas to make dust particles wet and heavy, so as to be settled down or captured by liquid. Common wet dust removal equipment includes spray tower and Venturi scrubber. Wet dust removal has high requirement for dust wettability, and has good removal effect for hydrophilic dust, and can also remove part of gaseous pollutants in waste gas, but will produce waste water which needs subsequent treatment.

[0076] Malodorous waste gas: water washing, dust removal and humidification: malodorous gas often contains dust and impurities. Water washing is used to remove particulate matter, and the humidity of waste gas is increased to facilitate subsequent biological treatment or chemical oxidation treatment. Spray tower can be used for water washing operation.

[0077] Acid and alkali washing: for malodorous waste gas containing acidic or alkaline substances, acid and alkali washing can be carried out to neutralize the acidic or alkaline components and adjust the pH value of waste gas to create suitable conditions for subsequent treatment. For example, acid liquid washing can be used for malodorous waste gas containing ammonia. Alkali liquid washing can be used for waste gas containing hydrogen sulfide.

[0078] Adsorption treatment: using activated carbon, molecular sieve, zeolite and other adsorbents to adsorb odor molecules in the odor gas, remove organic components and part of inorganic components, achieve the purpose of purifying waste gas, common adsorption equipment includes fixed bed adsorber, adsorption tower, etc. Activated carbon has good adsorption effect, but it needs to be replaced or regenerated in time after adsorption saturation.

[0079] High temperature and high humidity waste gas: cooling treatment: through heat exchanger, spray cooling and other ways to reduce the temperature of waste gas to the range suitable for subsequent treatment, generally requires the temperature to be lower than 40℃, to prevent high temperature from causing damage to subsequent treatment equipment or affecting the treatment effect. Heat exchanger can recover the heat in waste gas, realizing energy reuse. Spray cooling uses the latent heat of water evaporation to take away the heat in waste gas, which is simple in operation and obvious in effect.

[0080] Dehumidification treatment: using condensation dehumidification, adsorption dehumidification and other methods to remove moisture in waste gas, reducing the humidity of waste gas. Condensation dehumidification is to cool the waste gas to below the dew point temperature, so that the water vapor condenses into water droplets, which are separated out through a gas-liquid separation device. Adsorption dehumidification uses silica gel, molecular sieve and other adsorbents to adsorb moisture in waste gas to achieve the purpose of dehumidification.

[0081] The waste heat strategy making module is used for obtaining production load data according to the influence degree of different types of waste gas on the overall equipment, extracting waste heat parameter change data and waste heat quality data from waste heat data, and making waste heat utilization strategy according to the waste heat parameter change data.

[0082] The step of obtaining production load data includes:

[0083] The waste gas characteristics of the corresponding waste gas type are determined according to the physical and chemical properties of different waste gases, the parameters in the running process of the affected equipment are collected, and the production amount and characteristic change of waste gas in different treatment stages are analyzed to obtain the equipment characteristics.

[0084] A factor analysis model is established according to the waste gas characteristics and equipment characteristics, the quantitative relationship between the waste gas parameters and the equipment performance is analyzed, the influence weight of each parameter in the waste gas parameters on the equipment operation is determined, and the actual influence degree of different types of waste gas on the equipment is calculated. The waste gas parameters can include waste gas composition, concentration and flow, etc.

[0085] An energy balance model is established to calculate the total energy balance value, and the production load data when treating different types of waste gas is calculated combined with the design load of the equipment and the actual influence degree, which is expressed as:

[0086]

[0087] In the formula, is the production load data, is the actual influence degree, is the design load.

[0088] The step of calculating the total energy balance value includes:

[0089] The energy input item is determined according to the fuel combustion heat and electricity input required for treating different waste gas, combined with the energy of the waste gas itself.

[0090] The energy output item is determined according to the energy discharged after waste gas treatment and the energy taken away by products and by-products.

[0091] The total energy balance value is calculated according to the energy input item and the energy output item, combined with the energy loss in the reaction process and the internal energy generated by the reaction, and the formula is expressed as:

[0092]

[0093] In the formula, is the total energy balance value, is the energy input item, is the internal energy, is the energy output item, is the energy loss.

[0094] The step of extracting waste heat parameter change data and waste heat quality data includes:

[0095] By analyzing the temperature data at different positions, the temperature change data is calculated by calculating the difference between the initial temperature of the waste gas after oxidation reaction and the medium temperature after waste heat recovery, and the flow data of the waste heat recovery inlet and outlet are counted to calculate the flow change of the waste gas, analyze the stability of the flow, record the fluctuation amplitude and frequency of the flow, and the correlation between the flow and the temperature change. The flow parameter change data is obtained.

[0096] The pressure parameter change data is obtained by calculating the loss and change range of the pressure through the pressure change at the outlet of the oxidation furnace and in the waste heat recovery equipment, and together with the temperature change data and the flow parameter change data, the waste heat parameter change data is obtained.

[0097] The heat quality is obtained by calculating the total heat and thermal power of the waste heat according to the temperature change data, the waste gas parameters and the specific heat capacity, and the temperature quality is determined.

[0098] The stability of the waste heat is evaluated by analyzing the change trend of the waste heat parameters over time, and the waste heat quality data is composed of the heat quality and the temperature quality.

[0099] The step of formulating a waste heat utilization strategy includes:

[0100] According to the energy demand of the enterprise and the energy saving and emission reduction target, the scale and degree of waste heat recovery and utilization are determined to obtain the energy recovery target, and the demand for heat energy of the production process and equipment within the enterprise is analyzed to obtain the production demand.

[0101] Identify the type and magnitude of parameter changes through temperature change data and flow change data, and extract the time characteristics of residual heat parameter change data.

[0102] Develop matching strategies through energy recovery targets and production needs, generate residual heat parameter fluctuation scenarios according to the type and magnitude of parameter changes and time characteristics, and determine the key factors of different scenarios. The method of determining the key factors of different scenarios can include: from the sharp change of temperature, the large fluctuation of flow, etc., analyze how these factors affect the previously developed matching strategies, such as possible mismatch between residual heat supply and production demand, unstable operation of equipment, etc.

[0103] According to the residual heat parameter fluctuation scenario, select the corresponding residual heat utilization mode, and adjust the matching strategy according to the influence degree of the key factors to obtain the residual heat utilization strategy.

[0104] The residual heat strategy optimization module is used to predict the residual heat change using the residual heat prediction method according to the residual heat parameter change data to obtain residual heat prediction data, develop adjustment strategies according to production load data and residual heat prediction data, and adjust the residual heat utilization strategy according to user demand and residual heat quality data to obtain an optimized residual heat scheme.

[0105] The step of obtaining residual heat prediction data includes:

[0106] Establish a residual heat prediction model based on random forest, analyze the change rule and characteristics of residual heat parameter change data in each working period to obtain residual heat temperature, residual heat quantity and residual heat pressure, and extract waste gas features, environmental features and time features from residual heat parameter change data.

[0107] Take the waste gas features, environmental features and time features as input, and take the residual heat temperature, residual heat quantity and residual heat pressure as output, train the residual heat prediction model, and retain the model parameters that meet the test accuracy.

[0108] According to the current waste gas features, current environmental features and current time features, extract the corresponding current residual heat temperature, current residual heat quantity and current residual heat pressure, and input the trained residual heat prediction model to obtain the residual heat parameter prediction value.

[0109] According to the heat loss rate calculated by heat transfer, and combined with the environmental temperature to calculate the relevant residual heat steam evaporation rate, the formula is expressed as:

[0110]

[0111]

[0112] In the formula, is the heat loss rate, is the thermal conductivity of the material, It is the heat transfer area. It is the residual heat temperature. It is the ambient temperature. It refers to the thickness of the material. It is the total heat of waste heat. It is time. It is the initial hot water quality. It is the evaporation coefficient. It is hot water at the temperature The saturated vapor pressure below It is the partial pressure of water vapor in the environment. It is the waste heat steam evaporation rate.

[0113] Waste heat prediction data is calculated by combining predicted waste heat parameters, heat loss rate, and waste heat steam evaporation rate. Waste heat prediction data may include total waste heat discharge, average temperature, etc.

[0114] The steps to develop an adjustment strategy include:

[0115] Waste heat prediction data and production load data are converted to the same time granularity using an interpolation algorithm, and outlier handling is performed.

[0116] A two-dimensional matrix is ​​established by describing the matching relationship between different time periods and waste heat quality, and the formula is expressed as:

[0117]

[0118] In the formula, It is a time period Recoverable waste heat It is a time period Requires calories It is the waste heat-load quality matching efficiency. It is a two-dimensional matrix.

[0119]

[0120] In the formula, It is the temperature difference between the waste heat inlet and the load demand. It is the maximum theoretical thermal efficiency. This is a reference temperature.

[0121] The heat gap for each time period is calculated and classified into multiple levels according to the degree of the gap. These multiple levels of gap can be represented as follows:

[0122] Level 1 deficit: It is necessary to activate backup heat sources (such as gas boilers) or reduce non-critical loads.

[0123] Secondary gap: Balance supply and demand by adjusting production process parameters (such as reducing the heating rate of the reactor).

[0124] Third-level gap: Utilize waste heat cascade utilization optimization (such as using high-grade waste heat and waste pressure to drive refrigeration unit).

[0125] An optimization model targeting energy efficiency, economic cost and carbon emissions is established, which is expressed as:

[0126]

[0127] In the formula, , , is the target weight coefficient, is the total energy consumption, is the operating cost, is the carbon emissions, is the optimization model.

[0128] The dynamic programming algorithm is used to obtain the waste heat utilization value by state transition of the optimization model, which is expressed as:

[0129]

[0130] In the formula, is the waste heat inventory at time , is the load gap at time , is the available waste heat at time , is the used waste heat at time , is the waste heat storage efficiency coefficient, is the waste heat inventory at time

[0131] And combined with different levels of gap to develop a hierarchical response mechanism to obtain the adjustment strategy.

[0132] The steps of adjusting the optimized waste heat scheme include:

[0133] According to the urgency and importance of user demand, classify and combine with enterprise production plan to estimate the size and duration of various user demands in different periods to obtain priority ranking.

[0134] Combined with waste heat quality data and waste heat prediction data, evaluate the total amount and space-time distribution characteristics of waste heat resources, and combined with the matching degree with user demand to obtain the evaluation results.

[0135] According to the priority ranking and evaluation results, adjust the waste heat utilization strategy, reallocate waste heat resources, and determine the waste heat utilization mode according to different waste heat quality and user demand to obtain the optimized waste heat scheme.

[0136] For example Fig. 2As shown, based on the same overall inventive concept, the present application also protects a waste gas treatment method using an oxidation furnace for oxidation treatment, the waste gas treatment method comprising:

[0137] The different types of waste gas are pretreated, the oxidation reaction is carried out through the oxidation furnace, the waste heat data after the oxidation reaction is collected, and the waste gas fluctuation data is obtained by real-time monitoring of the change of the waste gas.

[0138] The production load data is obtained according to the influence degree of different types of waste gas on the overall equipment by using the waste gas-equipment load method, the waste heat parameter change data and the waste heat quality data are extracted from the waste heat data, and the waste heat utilization strategy is formulated according to the waste heat parameter change data.

[0139] The waste heat prediction method is used to predict the waste heat change according to the waste heat parameter change data to obtain the waste heat prediction data, the adjustment strategy is formulated according to the production load data and the waste heat prediction data, and the waste heat utilization strategy is adjusted according to the user demand and the waste heat quality data to obtain the optimized waste heat scheme.

[0140] The waste gas treatment system and method provided by the embodiment use an oxidation furnace for oxidation treatment, real-time collection of waste heat data after oxidation reaction, including temperature, flow, pressure and other key parameters, and monitoring of the change of waste gas, providing data support for the formulation of waste heat utilization strategy. The influence of different types of waste gas on the equipment is analyzed by using the waste gas-equipment load method, the factor analysis model and the energy balance calculation model are established, the production load data is calculated, and the equipment running state in the waste gas treatment process is quantitatively evaluated. From the waste heat data, the waste heat parameter change data and the waste heat quality data are extracted, the waste heat utilization strategy is formulated in combination with the energy demand and the energy saving and emission reduction target of the enterprise, so as to realize the effective recovery and utilization of waste heat. A waste heat prediction model based on random forest is constructed to predict the waste heat parameter change data, generate waste heat prediction data, and formulate an adjustment strategy accordingly to cope with the fluctuation and uncertainty of waste heat supply. In combination with the priority ranking of user demand and the evaluation result of waste heat quality data, the waste heat utilization strategy is adjusted, the waste heat resources are redistributed, and the appropriate waste heat utilization mode is determined to obtain a more optimized waste heat scheme. The comprehensive utilization rate of energy is significantly improved, and the fine management of waste gas treatment and waste heat utilization process is realized, improving the scientificity and effectiveness of energy management.

[0141] The device embodiments described above are only schematic, wherein the units shown as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, i.e., can be located in one place, or can be distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment scheme. Those skilled in the art can understand and implement without creative labor.

[0142] Those skilled in the art can clearly understand the implementation of the embodiments by means of software and necessary general hardware platforms through the description of the above embodiments, and of course, the embodiments can also be implemented by hardware. Based on such understanding, the above technical solutions can be embodied in the form of a software product, and the computer software product can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the method described in each embodiment or some parts of the embodiment.

[0143] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing examples, or make equivalent replacement for some technical features; and these modifications or replacements 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 application.

Claims

1. A waste gas treatment system employing an oxidation furnace for oxidation treatment, characterized in that, include: The waste gas treatment and data collection module is used to pretreat different types of waste gas, perform oxidation reactions in an oxidation furnace, collect waste heat data after the oxidation reaction, and monitor waste gas changes in real time to obtain waste gas fluctuation data. The waste heat strategy formulation module is used to obtain production load data based on the impact of different types of waste gas on the overall equipment using the waste gas-equipment load method, extract waste heat parameter change data and waste heat quality data from the waste heat data, and formulate waste heat utilization strategies based on the waste heat parameter change data. The steps for obtaining the production load data include: Based on the physical and chemical properties of different waste gases, the characteristics of the corresponding waste gas types are determined. Parameters during the operation of the affected equipment are collected, and the generation and characteristic changes of waste gases at different treatment stages are analyzed to obtain the equipment characteristics. A factor analysis model is established based on the characteristics of the exhaust gas and the characteristics of the equipment to analyze the quantitative relationship between exhaust gas parameters and equipment performance, determine the influence weight of each parameter in the exhaust gas parameters on the equipment operation, and calculate the actual influence of different types of exhaust gas on the equipment. An energy balance model is established to calculate the total energy balance value, and the production load data for treating different types of waste gas is calculated by combining the equipment's design load and the actual impact. The steps for calculating the total energy balance value include: The energy input items are determined based on the fuel combustion heat and electricity input required to treat different waste gases, combined with the energy of the waste gases themselves. The energy output item is determined based on the energy emitted after waste gas treatment and the energy carried away by products and by-products. The total energy balance value is calculated based on the energy input and energy output items, combined with the energy loss during the reaction process and the internal energy generated by the reaction. The waste heat strategy optimization module is used to predict waste heat changes based on the waste heat parameter change data using the waste heat prediction method to obtain waste heat prediction data, formulate adjustment strategies based on the production load data and the waste heat prediction data, and adjust the waste heat utilization strategy in combination with user needs and waste heat quality data to obtain an optimized waste heat solution. The steps for obtaining the waste heat prediction data include: A waste heat prediction model based on random forest is established. The change patterns and characteristics of the waste heat parameters in each working cycle are analyzed to obtain waste heat temperature, waste heat heat and waste heat pressure. Waste gas characteristics, environmental characteristics and time characteristics are extracted from the waste heat parameter change data. The waste gas characteristics, environmental characteristics, and time characteristics are used as inputs, and the waste heat temperature, waste heat heat, and waste heat pressure are used as outputs to train the waste heat prediction model, retaining model parameters that meet the test accuracy. Based on the current characteristics of the exhaust gas, the current environmental characteristics, and the current time characteristics, extract the corresponding current waste heat temperature, current waste heat heat, and current waste heat pressure, and input them into the trained waste heat prediction model to obtain the predicted values ​​of waste heat parameters. The heat loss rate is calculated based on heat transfer principles, and the waste heat steam evaporation rate is calculated in conjunction with the ambient temperature. The formula is as follows: ； ； In the formula, It is the heat loss rate. It is the thermal conductivity of the material. It is the heat transfer area. It is the residual heat temperature. It is the ambient temperature. It refers to the thickness of the material. It is the total heat of waste heat. It is time. It is the initial hot water quality. It is the evaporation coefficient. It is hot water at the temperature The saturated vapor pressure below, It is the partial pressure of water vapor in the environment. It is the waste heat steam evaporation rate; The waste heat prediction data is calculated by combining the predicted waste heat parameters, the heat loss rate, and the waste heat steam evaporation rate. The steps for developing the adjustment strategy include: The waste heat prediction data and the production load data are converted to the same time granularity using an interpolation algorithm, and outlier handling is performed. A two-dimensional matrix is ​​established by describing the matching relationship between different time periods and waste heat quality; Calculate the heat gap for each time period and classify it into multiple levels according to the degree of the gap; Establish an optimization model with energy efficiency, economic cost, and carbon emissions as objectives; The optimization model is used to perform state transitions to obtain waste heat utilization values, and a graded response mechanism is formulated based on different levels of gaps to obtain the adjustment strategy.

2. The waste gas treatment system using an oxidation furnace for oxidation treatment according to claim 1, characterized in that, The steps for pretreatment of different types of waste gas include: According to different types, waste gas is classified into organic waste gas, acid and alkali waste gas, dust-containing waste gas, malodorous waste gas, and high temperature and high humidity waste gas; The organic waste gas is subjected to filtration and dust removal, condensation and cooling, adsorption and concentration and gas washing purification treatment, and the acid and alkaline waste gas is subjected to neutralization and dust removal and impurity removal treatment. The dust-laden exhaust gas is subjected to mechanical, filtration, and wet dust removal treatment; the odorous exhaust gas is subjected to water washing, dust removal, humidification, acid and alkali washing, and adsorption treatment; and the high-temperature and high-humidity exhaust gas is subjected to cooling and dehumidification treatment.

3. The waste gas treatment system using an oxidation furnace for oxidation treatment according to claim 1, characterized in that, The steps for extracting the waste heat parameter change data and the waste heat quality data include: By analyzing temperature data at different locations, the temperature change data is obtained by calculating the difference between the initial temperature of the waste gas after the oxidation reaction and the temperature of the medium after waste heat recovery. The flow rate data of the inlet and outlet of the waste heat recovery are also statistically analyzed to calculate the flow rate change data of the waste gas. By calculating the pressure loss and range of change through the pressure changes at the outlet of the oxidizer and in the waste heat recovery equipment, pressure parameter change data is obtained, and together with the temperature change data and the flow rate parameter change data, the waste heat parameter change data is formed. The total heat and heat power of the waste heat are calculated based on the temperature change data, the waste gas parameters and specific heat capacity to obtain the heat quality, and the temperature quality is determined. By analyzing the changing trends of the waste heat parameters over time, the stability of the waste heat is assessed, and the waste heat quality data is formed together with the heat quality and the temperature quality.

4. The waste gas treatment system using an oxidation furnace for oxidation treatment according to claim 3, characterized in that, The steps for formulating the waste heat utilization strategy include: Based on the company's energy demand and energy conservation and emission reduction goals, the scale and extent of waste heat recovery and utilization are determined to obtain the energy recovery target, and the company's internal production processes and equipment demand for heat energy are analyzed to obtain the production demand. The type and magnitude of parameter changes are identified by the temperature change data and the flow rate change data, and the temporal characteristics of the waste heat parameter change data are extracted. A matching strategy is formulated based on the energy recovery target and the production demand. Waste heat parameter fluctuation scenarios are generated according to the type and magnitude of parameter changes and the time characteristics, and the key factors of different scenarios are determined from them. The waste heat utilization strategy is obtained by selecting the corresponding waste heat utilization method based on the waste heat parameter fluctuation scenario and adjusting the degree of influence of the matching strategy on the key factors.

5. A waste gas treatment system using an oxidation furnace for oxidation treatment according to claim 1, characterized in that, The steps for adjusting and obtaining the optimized waste heat scheme include: The user needs are categorized according to their urgency and importance, and then prioritized based on the enterprise's production plan to estimate the scale and duration of each type of user need at different times. By combining the waste heat quality data and the waste heat prediction data, the total amount and spatiotemporal distribution characteristics of waste heat resources are evaluated, and the evaluation result is obtained by combining the matching degree with the user's needs. The waste heat utilization strategy is adjusted based on the priority ranking and the evaluation results, waste heat resources are reallocated, and the waste heat utilization method is determined according to different waste heat qualities and user needs to obtain the optimized waste heat solution.

6. A method for treating waste gas using an oxidation furnace, comprising a waste gas treatment system using an oxidation furnace as described in any one of claims 1 to 5, characterized in that, The waste gas treatment method includes: Different types of waste gas are pretreated, and then oxidized in an oxidation furnace. Waste heat data after the oxidation reaction is collected, and waste gas fluctuation data is obtained by real-time monitoring of waste gas changes. Based on the waste gas-equipment load method, production load data is obtained to assess the impact of different types of waste gas on the overall equipment. Waste heat parameter change data and waste heat quality data are extracted from the waste heat data. Waste heat utilization strategies are then formulated based on the waste heat parameter change data. The waste heat prediction method is used to predict waste heat changes based on the waste heat parameter change data to obtain waste heat prediction data. An adjustment strategy is formulated based on the production load data and the waste heat prediction data. The waste heat utilization strategy is then adjusted in conjunction with user needs and waste heat quality data to obtain an optimized waste heat solution.

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