Intelligent compatibility method for hazardous waste treatment

Abstract

The invention discloses an intelligent compatibility method for hazardous waste disposal, and the method comprises the steps: obtaining a hazardous waste disposal object inventory table, and taking the inventory table as the input data of a linear programming model; constructing a linear programming model, taking the disposal benefit maximization of the hazardous waste disposal objects as an objective function, and taking the requirements of heat value, pollutant discharge and classification proportion as constraint conditions; solving the model to obtain an optimal solution of the model, and taking the optimal solution as a preliminary result of compatibility; performing incompatibility rule check on the preliminary result; if incompatible disposal substances exist, preferentially retaining the incompatible disposal substances, namely, carrying out compatibility on the premise of locking the treatment capacity of part of the hazardous waste disposal substances, and carrying out iterative operation through a part locking algorithm; if the incompatible treatment substances do not exist, the compatibility result is rounded automatically, and the compatibility result with operability is obtained. According to the method, hazardous waste treatment objects which are not easy to store and high in danger can be treated preferentially; the condition of incompatibility of hazardous waste disposal substances can be avoided; and an unreasonable compatibility value can be avoided.

Description

Technical Field

[0001] The invention belongs to the field of hazardous waste treatment, and specifically relates to an intelligent matching method for hazardous waste disposal. Background Art

[0002] Compatibility is an important part of hazardous waste treatment, and its purpose is to improve the stability and treatment efficiency of hazardous waste through reasonable ratios and combinations. However, there are many problems in hazardous waste compatibility, which restrict the effect and efficiency of hazardous waste treatment.

[0003] (1) Complex types: There are many types of solid wastes with different properties. The physical and chemical properties of different wastes vary greatly. This brings great difficulties to the hazardous waste compatibility, because specific compatibility schemes need to be designed for wastes of different properties. How to effectively classify various wastes and select appropriate compatibility schemes is the main problem currently faced.

[0004] (2) Emission control: Solid waste may contain toxic and hazardous substances, which may be released during the treatment process and cause harm to the environment and human health. How to reduce the emission of toxic and hazardous substances through reasonable mixing and incineration is an important issue.

[0005] (3) Safety: The compatibility assessment of hazardous wastes is an integral part of the compounding process. If incompatible hazardous wastes are compounded, dangerous situations such as toxic gas leakage, violent combustion, or even explosion may occur.

[0006] At present, the theoretical research on the compatibility principle is relatively consistent, focusing on three aspects: the calorific value of hazardous waste combustion, the control of pollutant components and chemical compatibility. Hazardous waste compatibility mainly relies on manual operation. Although this model can complete the compatibility task to a certain extent, its limitations are becoming more and more obvious with the increase in the amount of hazardous waste treatment and the improvement of environmental protection requirements. The main problems of manual compatibility include the following:

[0007] (1) Mainly dependent on manual labor: Hazardous waste preparation involves complex chemical and physical property analysis, as well as the evaluation of the safety of the prepared materials. These tasks are highly dependent on the experience and knowledge of professionals, while manual operations are often limited by individual ability, energy and experience.

[0008] (2) Efficiency and precision issues: Manual operation is not only inefficient, but also difficult to ensure the accuracy of the mixing. When dealing with large amounts of hazardous waste, manual operation often finds it difficult to complete the mixing task quickly and accurately, thus affecting the overall efficiency of hazardous waste treatment.

[0009] (3) Professional training requirements for personnel: Hazardous waste preparation requires professional knowledge and skills, and the training requirements for operators are relatively high. However, the talent pool in the hazardous waste treatment industry is currently insufficient, and the lack or insufficiency of professional training further exacerbates the difficulty of manual operation.

[0010] (4) Safety risks and supervision: Manual operation may increase safety risks, such as misoperation and misjudgment, leading to improper compatibility and thus safety accidents. In addition, supervision of manual operation is relatively difficult, and it is difficult to ensure that every link meets safety standards.

[0011] The research on the compatibility of specific hazardous wastes has certain limitations in practical application. At present, scholars are focusing on studying the compatibility models with high efficiency and accuracy. The following briefly lists some known progress:

[0012] (1) Yu Shufen et al. developed an automatic matching system based on the DELPHI language SOLServer2000 database. It performs single-line screening based on the input hazardous waste information and simple matching principles, and finally gives three matching schemes. Relying on cloud computing, successful matching cases of various hazardous waste incineration enterprises can be uploaded to improve the system. The system's operation logic is relatively simple and the operation time is long.

[0013] (2) Zhang Hongliang studied the use of high calorific value hazardous wastes as fuels and low calorific value as raw materials for cement kiln disposal, established a mathematical model for incineration compatibility and applied it for verification. Based on the known compatibility between hazardous wastes, the model established a material compatibility selection matrix for optimizing the compatibility model, but did not consider the specific identification method of hazardous waste compatibility.

[0014] (3) Li et al. used a mathematical model to establish an industrial hazardous waste matching software system to improve the accuracy and efficiency of matching work, and verified the model. However, the mathematical model has certain limitations, and the calculation rate needs to be improved.

[0015] (4) Liang et al. used the grey relational analysis (GRA) method to construct a compatibility model and established an index system in terms of calorific value, water content, corrosiveness and toxicity that affect the incineration effect.

[0016] (5) Hao Liangjun et al. studied a compatibility process model that can obtain the optimal solution. This model can take into account both the processing capacity of the incineration equipment and the economic benefits of the enterprise, but did not discuss compatibility.

[0017] Invention patent application CN110688741A discloses an intelligent matching algorithm for hazardous waste incineration disposal, which greatly reduces the workload of technical personnel. Even personnel who do not understand matching can use the proposed intelligent matching algorithm to make an executable matching list, which reduces the operating pressure of hazardous waste disposal units, reduces the repetitive workload of technical personnel, improves matching accuracy, and realizes accurate and rapid generation of matching plans. The intelligent matching algorithm for hazardous waste incineration disposal lists a set of equations according to the constraints, and uses the Newton iteration method of iteratively solving the equations to find the optimal solution of the objective function, that is, the matching amount for each type of waste.

[0018] Invention patent application CN110175350A provides a compatibility method for hazardous waste incineration disposal, the method comprising: obtaining known parameters about materials; obtaining known parameters about the hazardous waste incineration system; determining compatibility quantity constraints, calorific value constraints, pollution emission constraints and compatibility constraints based on the known parameters about the materials and the known parameters about the hazardous waste incineration system, and calculating the compatibility quantity of each material with daily processing volume as the objective function; and performing matching according to the compatibility quantities.

[0019] The existing intelligent matching algorithms are generally based on the three matching principles of combustion calorific value, pollution composition, and material compatibility. According to the various test indicators and properties of the hazardous waste disposal materials in stock, the optimal matching scheme that meets the requirements is calculated through computer programs. However, there are generally the following limitations:

[0020] (1) Storage time is not considered: Different hazardous wastes have different storage risk factors. For hazardous wastes with high risk factors, long-term storage will increase the additional risk factor and increase the operational management pressure of the enterprise. Therefore, the algorithm model should include the risk factor and storage time of each hazardous waste as the basis for calculation.

[0021] (2) Operability of the compatibility value: The compatibility algorithm should be combined with the packaging form of the waste to give an operable compatibility result. For example, if a hazardous waste is stored in barrels, then the compatibility value should be given in integer multiples of the unit ton barrel to be operable. Otherwise, it will involve many links such as the disassembly, subpackaging, and weighing of hazardous waste, which will increase the company's operating risks and costs.

[0022] (3) Model prediction capability: From an operational perspective, hazardous waste disposal companies need to maintain stable operating conditions in their incinerators. This requires using the same set of calorific value and pollutant indicators for iterative calculations under current inventory conditions, and planning multiple matching values ​​in the near term in advance, so as to make a scientific assessment of inventory conditions. Currently, research on matching algorithms still focuses on single calculations of matching models. Summary of the invention

[0023] Purpose of the invention: In view of the above problems, the present invention proposes an intelligent matching method for hazardous waste disposal. In a set of optimization algorithm models based on linear programming, many factors such as the calorific value, pollutant content, compatibility, storage time, operability, etc. of the disposal material are comprehensively considered to provide a scientific and reasonable optimal matching plan for hazardous waste disposal plants, thereby improving the production and operation efficiency, environmental emissions and safety of hazardous waste disposal enterprises; and it can provide matching predictions over a period of time to assist them in making scientific business decisions.

[0024] Technical solution: To achieve the purpose of the present invention, the technical solution adopted by the present invention is: an intelligent compatibility method for hazardous waste disposal, comprising the following steps:

[0025] (1) obtaining an inventory table of hazardous waste disposal materials and using the inventory table as input data for a linear programming model, wherein the inventory table includes various types of laboratory data of the hazardous waste disposal materials;

[0026] (2) constructing a linear programming model, taking maximizing the disposal efficiency of hazardous waste as the objective function of the model, and taking the requirements of calorific value, pollutant emission and classification ratio as the constraints of the model;

[0027] (3) Solve the linear programming model and obtain the optimal solution of the model as the preliminary result of compatibility;

[0028] (4) Check the preliminary results for incompatible rules;

[0029] (5) If there are incompatible disposals, the best ones will be retained, that is, under the premise of locking the treatment volume of some hazardous waste disposals, they will be matched and iterated through the partial locking algorithm;

[0030] (6) If there are no incompatible disposal materials, the compatibility results are automatically rounded to obtain an operational compatibility result.

[0031] As a further technical solution of the present invention, the linear programming model construction method is as follows:

[0032] (2-1) The measured calorific values ​​of m types of hazardous waste disposal and the inspection indicators of n types of pollutant content are regularized into the indicator parameter matrix A:

[0033]

[0034] The first column is the measured calorific value of m types of hazardous waste disposal, a i,j is the j-th pollutant content of the i-th hazardous waste disposal, i∈{0,1,...,m-1},j∈{1,2,...,n};

[0035] (2-2) Let the final compatibility of m types of hazardous waste be the vector X = [x0, x1, x2..., x i ...,x m-1 ] T , where x i is the compatibility amount of the i-th hazardous waste disposal;

[0036] (2-3) Assume that the total amount of the predetermined compatibility is Sum, and the upper and lower limits of the calorific value are Q max and Q min , the emission limit of the jth pollutant is Max j , the inventory of the i-th hazardous waste disposal is Stock i ;

[0037] (2-4) Set the weight coefficients to be a vector F = [f0, f1, f2..., f i ...,f m-1 ] T , where f i is the weighting coefficient of the i-th hazardous waste disposal;

[0038] (2-5) The objective function of the linear programming model is The constraints include:

[0039] Constraints on the total amount of compatibility:

[0040] Upper limit of calorific value:

[0041] Calorific value lower limit constraint:

[0042] The jth pollutant emission limit constraint:

[0043] Inventory Constraint: x i ≤Stock i ,

[0044] Reasonable constraint: x i ≥0.

[0045] As a further technical solution of the present invention, in step (2), the objective function of the linear programming model is set by adopting a tendency model;

[0046] The tendency modes include standard mode, calorific value priority mode, emission priority mode, efficiency priority mode and comprehensive mode;

[0047] The standard model described, i.e., no preference for any hazardous waste disposal;

[0048] The calorific value priority mode, that is, the higher the calorific value of the hazardous waste disposal, the heavier its authority, then when solving the maximization linear programming model, the solution with the maximum calorific value is obtained under the premise of satisfying all constraints;

[0049] In the emission priority mode, the weighting coefficient is set to the negative sum of the emission content, and the maximum linear programming model is uniformly used; when solving the maximum linear programming model, the solution with the minimum emission content is obtained under the premise of satisfying all constraints;

[0050] The efficiency priority mode mentioned above, that is, the more hazardous waste disposal materials are in stock, the heavier the authority is, so when solving the maximum linear programming model, the solution with the least material types is obtained under the premise of satisfying all constraints;

[0051] The comprehensive model comprehensively considers calorific value, emission and efficiency, and obtains a matching result that takes various indicators into consideration by adjusting the tendency coefficients of calorific value, emission and efficiency.

[0052] As a further technical solution of the present invention, in step (2), the weighting coefficients in the model objective function corresponding to each tendency pattern are set as follows:

[0053] Standard mode: f i =1;

[0054] Thermal value priority mode: f i =a 0,i ;

[0055] Emissions priority mode:

[0056] Efficiency priority mode: f i =Stock i ;

[0057] Comprehensive mode:

[0058] Among them, Fact0, Fact1 and Fact2 represent the tendency coefficients for calorific value, emission and efficiency respectively.

[0059] As a further technical solution of the present invention, in step (2), the objective function of the linear programming model is set by taking into account the time factor, and the implementation is as follows:

[0060] The treatment priority of hazardous waste disposal is set to be proportional to the hazard factor and exponentially proportional to the storage time; the storage time of hazardous waste disposal must be greater than the reserved disposal time;

[0061] Then the weight coefficient in the model objective function of the comprehensive time factor is set as:

[0062] Among them, di is the hazard factor of the i-th hazardous waste disposal, t i and t i0 are the inventory time and reserved disposal time of the i-th hazardous waste disposal material, and e is a natural constant.

[0063] As a further technical solution of the present invention, in step (2), the classification ratio constraint is implemented as follows:

[0064] Assume that the inventory of hazardous waste disposal is divided into K categories, represented by type1, type2, ..., type k ...,type K , according to the incinerator type and operating characteristics corresponding to each category, determine the best matching ratio;

[0065] Then, in the optimization model of the linear programming algorithm, add the following constraints:

[0066] type k Upper limit constraint:

[0067] type k Lower limit constraint:

[0068] Among them, type k represents the kth classification inventory, b k,i is a Boolean value, indicating whether the i-th hazardous waste disposal belongs to the k-th classification inventory. If the i-th hazardous waste disposal belongs to the k-th classification inventory, b k,i =1, otherwise b k,i =0.

[0069] As a further technical solution of the present invention, under the premise of locking the treatment capacity of part of the hazardous waste disposal, the matching is carried out, and the implementation process of partial locking is as follows:

[0070] (5-1) Emergency disposal of some hazardous wastes, while keeping the total amount constraint and calorific value constraint unchanged, that is, dynamically adjusting the total amount of compatibility, upper and lower limits of calorific value, and upper limit of emissions to achieve locked treatment of some hazardous wastes;

[0071] Assume that among the m types of disposal items in stock, there are r types of disposal items that need emergency treatment, 2≤r≤m, and the index parameter matrix of the r types of disposal items is set to B. Matrix B is a submatrix of matrix A, and matrix B is expressed as:

[0072]

[0073] The first column is the measured calorific value of the r types of disposal materials that require emergency treatment, b s,jis the jth pollutant content of the sth emergency treatment disposal, s∈{1,...,r},j∈{1,2,...,n}; the emergency treatment volume of the sth emergency treatment disposal is Lock s ,but:

[0074]

[0075] (5-2) Iterative calculation to evaluate whether the current inventory can ensure the stability of the incinerator operating conditions under the set indicators;

[0076] Assuming that the formulation is done once a day, under the same total formulation amount, upper and lower limits of calorific value, and upper limit of emissions, the formulation plan for each day within w days is made, and the iterative formula is:

[0077] Stock i,w =Stock i,w-1 -x i,w-1 ,

[0078] Among them, Stock i,w and Stock i,w-1 are the inventory of the i-th disposal on day w and day w-1, respectively, i,w-1 is the compatibility value of the i-th treatment on the w-1th day, i∈{0,1,...,m-1};

[0079] That is, at each iteration, the last calculated compatibility value is deducted from the inventory of each disposal object, and the result of each calculation is the compatibility value of the wth day;

[0080] If the last iteration of the matching result cannot meet the constraint conditions, a warning is issued, and it is determined that the set of indicators is not sufficient to support the matching plan for w days under the current inventory conditions.

[0081] As a further technical solution of the present invention, if there is no incompatible disposal material, the compatibility result is rounded up or down according to the principle of rounding off based on the packaging form of the disposal material, specifically:

[0082] The compatibility of m types of hazardous wastes obtained by solving the model is a vector X = [x0, x1, x2..., x m-1 ] T , x i is the amount of the i-th hazardous waste disposal, i∈{0,1,...,m-1}, and x is updated according to the following formula i :

[0083]

[0084] Among them, unit iis the packaging unit of the i-th type of hazardous waste disposal; through automatic rounding, the final operational matching result is obtained.

[0085] Beneficial effects: Compared with the prior art, the technical solution of the present invention has the following beneficial technical effects:

[0086] The intelligent matching method for hazardous waste disposal proposed in the present invention can provide a variety of algorithm tendencies such as calorific value priority, emission priority, efficiency priority, etc. for daily business decision-making selection; the present invention can give priority to the disposal of some hazardous wastes that must be treated first due to special reasons by partially locking the matching values ​​and automatically replenishing the inventory; the present invention can achieve a reasonable allocation of material classification ratios to adapt to the specific working conditions of the incinerator.

[0087] The present invention can comprehensively consider the storage time and storage risk coefficient, and give priority to hazardous waste disposal materials that are difficult to preserve and highly dangerous; the present invention can avoid incompatibility of hazardous waste disposal materials, thereby avoiding risks such as reactions leading to explosions; the present invention can automatically round up according to the storage and packaging forms of hazardous waste disposal materials, avoiding unreasonable compatibility values. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] Figure 1 It is the overall logic flow chart of the method of the present invention.

[0089] Figure 2 It is a flowchart of the algorithm implementation of incompatible rules.

[0090] Figure 3 This is an example diagram of the combination parameter setting. DETAILED DESCRIPTION

[0091] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0092] The intelligent compatibility method for hazardous waste disposal described in the present invention has a process as follows: Figure 1 As shown, the specific implementation steps are as follows:

[0093] (1) Obtain a hazardous waste inventory table and use it as input data for the linear programming model.

[0094] The hazardous waste inventory table contains various test data of hazardous waste. The data of the hazardous waste inventory table obtained in this embodiment, as shown in Table 1, include hazardous waste code, hazardous waste name, material type, calorific value, PH, fluorine, chlorine, bromine, sulfur, Na, potassium, salt content and inventory.

[0095] (2) Construct a linear programming model, set the objective function and constraints of the linear programming model, take maximizing the disposal efficiency of hazardous waste as the objective function, and take the requirements of calorific value, pollutants and classification ratio as the constraints of the linear programming model.

[0096] The core algorithm of the present invention is the compatibility optimization based on linear programming. The compatibility algorithm is essentially a multi-objective optimization problem, that is, in the case of m kinds of hazardous waste disposal materials and n kinds of pollutant emission indicators, how to select i kinds (i < n) of disposal materials so that after incineration in the furnace, it can meet the requirements of calorific value content and various pollutant emissions up to standard at the same time. The present invention uses the linear programming algorithm to realize the core operation, and the specific model implementation is as follows:

[0097] (2-1) Regularize the measured calorific values of m kinds of hazardous waste disposal materials and the inspection indicators of n kinds of pollutant contents into the index parameter matrix A:

[0098]

[0099] Among them, the first column is the measured calorific values of m kinds of hazardous waste disposal materials, and a i,j is the content of the jth pollutant in the ith hazardous waste disposal material, i ∈ {0, 1,..., m - 1}, j ∈ {1, 2,..., n}.

[0100] (2-2) Let the final compatibility amounts of m kinds of hazardous waste disposal materials be the vector X = [x0, x1, x2..., x i ..., x m-1 T , where x i is the compatibility amount of the ith hazardous waste disposal material.

[0101] (2-3) Let the predetermined total compatibility amount be Sum, the upper and lower limits of calorific value be Q max and Q min , the upper limit of the jth pollutant emission be Max j , and the inventory of the ith hazardous waste disposal material be Stock i .

[0102] (2-4) Set the weighting coefficient as the vector F = [f0, f1, f2..., f i ..., f m-1 T , where f i is the weighting coefficient of the ith hazardous waste disposal material.

[0103] Generally speaking, the weighting coefficient in the linear programming algorithm is the economic benefit coefficient; for hazardous waste disposal materials, it is the "disposal benefit" of the hazardous waste disposal materials. The "disposal benefit" comprehensively considers various factors such as the calorific value, pollutant content, storage time, inventory form, and hazard coefficient of each hazardous waste, and is dynamically adjusted under different algorithm modes.

[0104] (2-5) Set FX as the objective function of the linear programming model, then the linear programming standard model of the compatibility algorithm is:​​

[0105] Objective function:

[0106] The constraints include:

[0107] Constraints on the total amount of compatibility:

[0108] Upper limit of calorific value:

[0109] Calorific value lower limit constraint:

[0110] The jth pollutant emission limit constraint:

[0111] Inventory Constraint: x i ≤Stock i ,

[0112] Reasonable constraint: x i ≥0.

[0113] (2-6) By finding the optimal solution of the linear programming model, the final compatibility value X can be obtained. There are many solutions to the linear programming model. This embodiment uses the standard solution of the python library pulp model.

[0114] In step (2), the objective function of the linear programming model is set by integrating the time factor through the algorithm's tendency mode, wherein the tendency mode includes calorific value priority, emission priority and efficiency priority.

[0115] In the actual application of hazardous waste disposal, there is usually a certain tendency to prioritize one of the indicators, such as calorific value or emissions, based on the needs of daily operations. When the constraints remain unchanged, the objective function can be changed by adjusting the weighting coefficient F, thereby realizing various tendency modes of the algorithm.

[0116] The implementation process of each tendency mode is as follows:

[0117] (a) Standard model, i.e. no preference for any hazardous waste disposal; setting:

[0118] f i =1;

[0119] (b) Calorific value priority mode, that is, the higher the calorific value of the hazardous waste disposal, the heavier its authority. When solving the maximization linear programming model, the solution with the maximum calorific value is obtained under the premise of satisfying all constraints; set:

[0120] f i =a 0,i ;

[0121] (c) Emission priority mode, set the weighting coefficient to the negative of the sum of emission content, and uniformly use the maximum linear programming model; when solving the maximum linear programming model, the solution with the minimum emission is obtained under the premise of satisfying all constraints; set:

[0122]

[0123] (d) Efficiency priority mode, that is, the more hazardous waste disposal materials are in stock, the heavier the authority is. When solving the maximum linear programming model, the solution with the least types of materials (hazardous waste disposal materials) is obtained under the premise of satisfying all constraints; setting:

[0124] f i =Stock i ;

[0125] (e) Comprehensive mode, setting:

[0126]

[0127] Among them, Fact0, Fact1 and Fact2 represent the tendency coefficients for calorific value, emission and efficiency respectively. According to the actual production and operation needs, by adjusting the above coefficients, the matching results that take into account various indicators can be obtained.

[0128] In step (2), the algorithm implementation process of the comprehensive time factor is as follows:

[0129] Different hazardous waste disposal materials have different optimal treatment times. Some hazardous waste disposal materials are highly dangerous and difficult to store, and need to be handled in a timely manner according to inventory conditions to improve economic efficiency.

[0130] Generally, the treatment priority of hazardous waste disposal follows the following rule: the treatment priority is proportional to the hazard factor and the storage time. In particular, in order to strengthen the hazardous waste disposal characteristic that the longer the storage time, the higher the operating cost, the algorithm of the present invention designs the treatment priority to be exponentially proportional to the storage time.

[0131] In addition, some types of hazardous waste require a certain amount of disposal time after entering the factory, so the inventory time must be greater than this disposal time.

[0132] In summary, the algorithm of the time factor on the weighted coefficient is as follows:

[0133]

[0134] Among them, d i is the hazard factor of the i-th type of hazardous waste disposal, which is determined by laboratory indicators or comprehensive experience, and different disposal plants need to set it according to actual conditions; i and t i0are the inventory time and reserved disposal time of the i-th hazardous waste disposal material, and e is a natural constant.

[0135] In step (2), the algorithm implementation process of the classification ratio is as follows:

[0136] In this embodiment, it is assumed that the hazardous waste disposal enterprise classifies its inventory into: waste liquid, sludge, distillation residue, activated carbon / resin, discarded goods and others; and according to its incinerator type and business characteristics, the optimal matching ratio is stipulated as: distillation residue less than 30%, sludge 15% to 25%, and waste liquid 15% to 45%. Then the classification ratio algorithm is implemented as follows:

[0137] Let type = [waste liquid, sludge, distillation residue, activated carbon / resin, dumping, other]; in the optimization model of the core linear programming algorithm, add the following constraints:

[0138] type[k] upper limit constraint:

[0139] type[k] ratio lower limit constraint:

[0140] Among them, type[k] represents the kth classification inventory, b i It is a Boolean value, indicating whether the i-th material (hazardous waste disposal) belongs to the k-th classification inventory. When the i-th material type belongs to the k-th classification inventory, b k,i =1, otherwise b k,i = 0. For example, when type[k] is distillation residue, when the i-th material type is distillation residue, b k,i =1, otherwise b k,i =0.

[0141] (3) Maximize the linear programming model to obtain preliminary results of the combination.

[0142] (4) Check the preliminary results for incompatible rules. The algorithm implementation process of incompatible rules is as follows:

[0143] In the hazardous waste compatibility process, compatibility between hazardous wastes means that after two or more hazardous wastes come into contact or mix with each other, no heat, high pressure, toxic or harmful substances will be generated, no polymerization reaction will occur, no dangerous phenomena such as combustion or explosion will occur, and no reactions or changes that have an adverse effect on incineration will occur. At present, there is no unified standard for the identification of compatibility in the industry. In actual compatibility, most companies use a combination of component analysis and small-scale experiments to determine the compatibility of hazardous wastes. The present invention uses a comprehensive method of component analysis and empirical elimination to determine incompatibility rules. The process is as follows: Figure 2 .

[0144] (5) If there are incompatible materials, they will be retained on a preferential basis and iterated through the partial locking algorithm. There are at least two situations where it is necessary to lock the treatment volume of certain hazardous waste disposal materials and then perform matching. The partial locking algorithm implementation process is as follows:

[0145] (5-1) Certain hazardous wastes need to be disposed of urgently, but other constraints such as the total amount of compatibility and calorific value remain unchanged; that is, the total amount of compatibility, the upper and lower limits of calorific value, and the upper limit of emissions are dynamically adjusted internally to achieve locked-in treatment of some hazardous wastes.

[0146] In this embodiment, suppose that there are two materials in the inventory with an emergency handling capacity of Lock i , i = 1, 2, the algorithm for partial locking of the compatibility is implemented as:

[0147]

[0148] (5-2) Iterative calculations are required to evaluate whether the current inventory can ensure the stability of the incinerator operating conditions under the set indicators.

[0149] Assuming that the formulation is done once a day, under the same total formulation amount, upper and lower limits of calorific value, and upper limit of emissions, the formulation plan for each day within w days is made, and the iterative formula is:

[0150] Stock i,w =Stock i,w-1 -x i,w-1 ,

[0151] Among them, Stock i,w and Stock i,w-1 are the inventory of the i-th type of hazardous waste on day w and day w-1, respectively, i,w-1 is the compatibility value of the i-th hazardous waste disposal on the w-1th day, i∈{0,1,...,m-1}, and w represents the number of iterations.

[0152] That is, in each iteration, the last calculated compatibility value is deducted from the inventory of each material, and the result of each calculation is the compatibility value of the wth day.

[0153] If the last iteration of the matching result cannot meet the constraint conditions, a warning is issued, and it is determined that the set of indicators is not sufficient to support the matching plan for w days under the current inventory conditions.

[0154] (6) If there are no incompatible materials, the final operational compatibility result is obtained by automatic rounding.

[0155] Since the optimal result value calculated by the intelligent matching algorithm is a floating point number, such as:

[0156] X=[1.56,0,0.2,...,0.97] T ,

[0157] If x0=1.56, the corresponding hazardous waste disposal material is waste liquid, and its packaging form is ton barrels. However, the compatibility value of 1.56 tons is not operational and must be rounded up or down according to its packaging form and the principle of rounding off.

[0158]

[0159] Among them, unit i It is the packaging unit of the i-th type of hazardous waste disposal.

[0160] The present invention provides an intelligent matching method for hazardous waste incineration disposal. In a set of optimization algorithm models based on linear programming, many factors such as the calorific value, pollutant content, compatibility, storage time, operability, etc. of the disposal material are comprehensively considered. The algorithm implementation of the tendency mode, partial locking, time factor, and classification ratio in the intelligent matching of the present invention provides a scientific and reasonable optimal matching scheme for hazardous waste disposal plants, thereby improving the production and operation efficiency, environmental emissions, and safety of hazardous waste disposal enterprises. This embodiment lists the experimental data and matching results of the algorithm, among which Table 1 is the inventory of hazardous waste disposal materials of a certain enterprise, and Table 2 is the generation result of the intelligent matching (the calculation time is less than 1 second). The matching parameters are set as follows: Figure 3 shown.

[0161] Table 1

[0162]

[0163]

[0164]

[0165]

[0166]

[0167]

[0168]

[0169]

[0170]

[0171] Table 2

[0172]

[0173]

[0174] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An intelligent compatibility method for hazardous waste disposal, characterized in that: The method comprises the following steps: (1) obtaining an inventory table of hazardous waste disposal materials and using the inventory table as input data for a linear programming model, wherein the inventory table includes various types of laboratory data of the hazardous waste disposal materials; (2) constructing a linear programming model, taking maximizing the disposal efficiency of hazardous waste as the objective function of the model, and taking the requirements of calorific value, pollutant emission and classification ratio as the constraints of the model; (3) Solve the linear programming model and obtain the optimal solution of the model as the preliminary result of compatibility; (4) Check the preliminary results for incompatible rules; (5) If there are incompatible disposals, the best ones will be retained, that is, under the premise of locking the treatment volume of some hazardous waste disposals, they will be matched and iterated through the partial locking algorithm; (6) If there are no incompatible disposal materials, the compatibility results are automatically rounded to obtain an operational compatibility result.

2. The intelligent compatibility method for hazardous waste disposal according to claim 1 is characterized in that: The linear programming model construction method is as follows: (2-1) The measured calorific values ​​of m types of hazardous waste disposal and the inspection indicators of n types of pollutant content are regularized into the indicator parameter matrix A: The first column is the measured calorific value of m types of hazardous waste disposal, a i,j is the j-th pollutant content of the i-th hazardous waste disposal, i∈{0,1,...,m-1},j∈{1,2,...,n}; (2-2) Let the final compatibility of m types of hazardous waste be the vector X = [x0, x1, x2..., x i ...,x m-1 ] T , where x i is the compatibility amount of the i-th hazardous waste disposal; (2-3) Assume that the total amount of the predetermined compatibility is Sum, and the upper and lower limits of the calorific value are Q max and Q min , the emission limit of the jth pollutant is Max j , the inventory of the i-th hazardous waste disposal is Stock i ; (2-4) Set the weight coefficients to be a vector F = [f0, f1, f2..., f i ...,f m-1 ] T , where f i is the weighting coefficient of the i-th hazardous waste disposal; (2-5) The objective function of the linear programming model is The constraints include: Constraints on the total amount of compatibility: Upper limit of calorific value: Calorific value lower limit constraint: The jth pollutant emission limit constraint: Inventory Constraint: x i ≤Stock i , Reasonable constraint: x i ≥0.

3. The intelligent compatibility method for hazardous waste disposal according to claim 2 is characterized in that: In step (2), the objective function of the linear programming model is set by adopting the tendency model; The tendency modes include standard mode, calorific value priority mode, emission priority mode, efficiency priority mode and comprehensive mode; The standard model described, i.e., no preference for any hazardous waste disposal; The calorific value priority mode, that is, the higher the calorific value of the hazardous waste disposal, the heavier its authority, then when solving the maximization linear programming model, the solution with the maximum calorific value is obtained under the premise of satisfying all constraints; In the emission priority mode, the weighting coefficient is set to the negative sum of the emission content, and the maximum linear programming model is uniformly used; when solving the maximum linear programming model, the solution with the minimum emission content is obtained under the premise of satisfying all constraints; The efficiency priority mode mentioned above, that is, the more hazardous waste disposal materials are in stock, the heavier the authority is, so when solving the maximum linear programming model, the solution with the least material types is obtained under the premise of satisfying all constraints; The comprehensive model comprehensively considers calorific value, emission and efficiency, and obtains a matching result that takes various indicators into consideration by adjusting the tendency coefficients of calorific value, emission and efficiency.

4. The intelligent compatibility method for hazardous waste disposal according to claim 3 is characterized in that: In step (2), the weight coefficients in the model objective function corresponding to each tendency pattern are set as follows: Standard mode: f i =1; Thermal value priority mode: f i =a 0,i ; Emissions priority mode: Efficiency priority mode: f i =Stock i ; Comprehensive mode: Among them, Fact0, Fact1 and Fact2 represent the tendency coefficients for calorific value, emission and efficiency respectively.

5. The intelligent compatibility method for hazardous waste disposal according to claim 3 is characterized in that: In step (2), the objective function of the linear programming model is set by taking into account the time factor and implemented as follows: The treatment priority of hazardous waste disposal is set to be proportional to the hazard factor and exponentially proportional to the storage time; the storage time of hazardous waste disposal must be greater than the reserved disposal time; Then the weight coefficient in the model objective function of the comprehensive time factor is set as: Among them, d i is the hazard factor of the i-th hazardous waste disposal, t i and t i0 are the inventory time and reserved disposal time of the i-th hazardous waste disposal material, and e is a natural constant.

6. The intelligent compatibility method for hazardous waste disposal according to claim 2 is characterized in that: In step (2), the classification ratio constraint is implemented as follows: Assume that the inventory of hazardous waste disposal is divided into K categories, represented by type1, type2, ..., type k ...,type K , according to the incinerator type and operating characteristics corresponding to each category, determine the best matching ratio; Then, in the optimization model of the linear programming algorithm, add the following constraints: type k Upper limit constraint: type k Lower limit constraint: Among them, type k represents the kth classification inventory, b k,i is a Boolean value, indicating whether the i-th hazardous waste disposal belongs to the k-th classification inventory. If the i-th hazardous waste disposal belongs to the k-th classification inventory, b k,i =1, otherwise b k,i =0.

7. The intelligent compatibility method for hazardous waste disposal according to claim 2 is characterized in that: Under the premise of locking the treatment volume of some hazardous waste disposal, the matching is carried out, and the implementation process of partial locking is as follows: (5-1) Emergency disposal of some hazardous wastes, while keeping the total amount constraint and calorific value constraint unchanged, that is, dynamically adjusting the total amount of compatibility, upper and lower limits of calorific value, and upper limit of emissions to achieve locked treatment of some hazardous wastes; Assume that among the m types of disposal items in stock, there are r types of disposal items that need emergency treatment, 2≤r≤m, and the index parameter matrix of the r types of disposal items is set to B. Matrix B is a submatrix of matrix A, and matrix B is expressed as: The first column is the measured calorific value of the r types of disposal materials that require emergency treatment, b s,j is the jth pollutant content of the sth emergency treatment disposal, s∈{1,...,r},j∈{1,2,...,n}; the emergency treatment volume of the sth emergency treatment disposal is Lock s ,but: (5-2) Iterative calculation to evaluate whether the current inventory can ensure the stability of the incinerator operating conditions under the set indicators; Assuming that the formulation is done once a day, under the same total formulation amount, upper and lower limits of calorific value, and upper limit of emissions, the formulation plan for each day within w days is made, and the iterative formula is: Stock i,w =Stock i,w-1 -x i,w-1 , Among them, Stock i,w and Stock i,w-1 are the inventory of the i-th disposal on day w and day w-1, respectively, i,w-1 is the compatibility value of the i-th treatment on the w-1th day, i∈{0,1,...,m-1}; That is, at each iteration, the last calculated compatibility value is deducted from the inventory of each disposal object, and the result of each calculation is the compatibility value of the wth day; If the last iteration of the matching result cannot meet the constraint conditions, a warning is issued, and it is determined that the set of indicators is not sufficient to support the matching plan for w days under the current inventory conditions.

8. The intelligent compatibility method for hazardous waste disposal according to any one of claims 1 to 7, characterized in that: If there are no incompatible disposal materials, the compatibility results shall be rounded up or down according to the packaging form of the disposal materials and the principle of rounding off, specifically: The compatibility of m types of hazardous wastes obtained by solving the model is a vector X = [x0, x1, x2..., x m-1 ] T , x i is the amount of the i-th hazardous waste disposal, i∈{0,1,...,m-1}, and x is updated according to the following formula i : Among them, unit i is the packaging unit of the i-th type of hazardous waste disposal; through automatic rounding, the final operational matching result is obtained.

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