CN116700163A - Energy dynamic optimization control method for ultra-clean emission of organic pollutants - Google Patents

Abstract

The invention provides an energy dynamic optimization control method for ultra-clean discharge of organic pollutants, comprising: constructing a self-heating balance rate; establishing an energy dynamic self-heating balance model; constructing an energy dynamic optimization problem for ultra-clean discharge of organic pollutants; adopting an improved control method The trajectory parameterization method expresses the control input variable as a discrete form, transforms the energy dynamic optimization problem into a nonlinear programming problem; uses the ODE solver to solve the equality constraints; uses the penalty function method that constructs an obstacle function in the objective function to construct a dual optimization The problem is to solve the inequality constraints, and obtain the optimal control sequence and terminal time by iteratively reducing the weight in the barrier function; the rolling optimization strategy of model predictive control is used for iterative optimization to realize the energy self-sufficiency of the system. The invention realizes the target of ultra-clean discharge operation by rationally utilizing the self-energy of high-concentration organic pollutants, and at the same time solves the problems of large energy consumption and high cost of the traditional pollutant treatment process.

Description

An energy dynamic optimization control method for ultra-clean emission of organic pollutants

technical field

The invention relates to the technical fields of chemical engineering, ultra-clean discharge of organic pollutants and optimization control of complex industrial processes, specifically but not limited to an energy dynamic optimization control method for ultra-clean discharge of organic pollutants.

Background technique

The treatment of organic pollutants has become one of the hot research topics of environmental treatment technology. At present, the mainstream methods of organic pollutant treatment mainly include the following three methods: biological method, incineration method and catalytic oxidation method. The traditional biological method is to metabolize organic matter as a carbon source and energy source, and convert the organic matter into renewable energy and biosolids through anaerobic microorganisms. The biological method not only requires a large investment and occupies a large area, but also requires the treatment of high-concentration organic wastewater. Dilution pretreatment increases process complexity and cost. The incineration method directly burns organic matter at a high temperature, and the required temperature is as high as 1000°C and above, which is dangerous and requires high investment and operating costs. The catalytic oxidation method uses cheap air oxidants and advanced catalytic materials to catalyze and oxidize harmful organic macromolecules in multi-phase state (gas, liquid, solid), multi-structure (element, compound, polymer) through "gas-solid" two-phase catalytic oxidation. Reaction, transform into harmless CO ₂ , H ₂ O, N ₂ and easy-to-handle SO ₂ , HCl and other small molecules.

High-concentration organic pollutants contain a lot of energy. How to efficiently use the energy of pollutants is very critical to reduce the energy consumption of pollutant treatment. The energy contained in organic matter in wastewater is about 9-10 times that required for wastewater treatment, and the rectification raffinate is rich in a large amount of energy. Traditional energy recycling methods mainly use pyrolysis, gasification and other means to convert pollutants into secondary energy sources such as biogas, steam, and electricity. There are few reports on the efficient use of the energy contained in organic pollutants and the realization of system energy self-sufficiency through internal energy optimization control. Carrying out research on energy dynamic optimization control of ultra-clean emissions of organic pollutants is of great significance for effectively reducing the energy consumption of treatment devices and solving the problems of difficult operation and maintenance and high costs of enterprise treatment devices.

In view of this, it is necessary to provide a new control method in order to solve at least part of the above problems.

Contents of the invention

Aiming at one or more problems in the prior art, the present invention proposes an energy dynamic optimization control method for ultra-clean emission of organic pollutants, which uses the energy released by the catalytic oxidation reaction for the temperature rise and vaporization of non-gaseous pollutants. Energy, build an energy self-heating balance system, realize the ultra-clean discharge of organic pollutants, and reduce the energy consumption of the treatment device.

The technical solution that realizes the object of the present invention is:

An energy dynamic optimization control method for ultra-clean emission of organic pollutants, comprising:

S1. Constructing the self-heat balance rate of organic pollutant treatment, the self-heat balance rate is defined as the ratio of the total energy absorbed to the total energy released during the treatment of organic pollutants;

S2. Based on the oxygen cracking catalytic oxidation treatment process adopted by organic pollutants, according to the concentration of each component of organic pollutants and the change of oxygen consumption, the energy conversion equation and energy transfer equation of the organic pollutant treatment process are established, and the energy dynamics are constructed Self-heating balance model;

S3. Based on the energy dynamic self-heat balance model, construct the energy dynamic optimization problem of ultra-clean emission of organic pollutants, and determine the optimization objective function;

S4. Using the improved control trajectory parameterization method to express the control input variables of the pollutant control system in a discrete form, so that the energy dynamic optimization problem is transformed into a nonlinear programming problem;

S5, using the ODE solver to solve the equality constraints in the above-mentioned nonlinear programming problem; using the penalty function method of constructing an obstacle function in the objective function, constructing a dual optimization problem, and solving the inequality constraints in the above-mentioned nonlinear programming problem, And through continuous iteration to reduce the weight of the barrier function, the optimal control sequence and terminal time are obtained; the rolling optimization strategy of model predictive control is used for iterative optimization to realize the energy self-sufficiency of the system.

Further, in the energy dynamic optimization control method for ultra-clean emission of organic pollutants of the present invention, the self-heating balance rate of organic pollutant treatment in S1 is constructed including:

S1-1. Based on thermodynamic analysis, establish an energy conversion equation for the catalytic oxidation process of organic pollutants, and calculate the total energy ∑Q _r released by organic pollutants during the catalytic oxidation process based on this equation. The total energy ∑Q _r released is Including: heat Q _rwg released by catalytic oxidation of gaseous organic matter, heat Q _rww released by catalytic oxidation of wastewater, heat Q _rds released by catalytic oxidation of raffinate;

S1-2. Establish the energy transfer equation of the organic pollutant treatment process, and based on this equation, calculate the total energy ∑Q _a absorbed by the organic pollutant during the temperature rise and phase transition process. The total absorbed energy ∑Q _a includes: Sensible heat Q _aH2O-SH-w and latent heat of vaporization Q _aH2O-LH required to raise the temperature of wastewater and raffinate, and the total sensible heat Q _gas required to raise the temperature of water vapor and air to the optimum reaction temperature;

S1-3. Construct the self-heating balance rate of organic pollutant treatment:

Further, in the energy dynamic optimization control method for ultra-clean emission of organic pollutants of the present invention, the total energy ΣQ _r released by organic pollutants in the catalytic oxidation process in S1-1 is:

Among them, H _wg represents the heat release corresponding to the oxygen consumption of the exhaust gas, V _wg represents the volume corresponding to the oxygen consumption of the exhaust gas, C _wg represents the concentration of organic pollutants in the waste gas, _NO2 represents the mole fraction of oxygen, and V _m represents the exhaust gas Molar volume, H _ww represents the heat release corresponding to the oxygen consumption of wastewater, V _ww represents the volume corresponding to the oxygen consumption of wastewater, ρ _ds represents the density of the raffinate, V _ds represents the volume corresponding to the oxygen consumption of the raffinate, H _ds represents the heat release corresponding to the oxygen consumption of the raffinate, Indicates the heat absorbed by the residual liquid in the process of purification, /> Indicates the heat absorbed by the carbon dioxide produced by the raffinate during the purification process.

Further, in the energy dynamic optimization control method for ultra-clean emission of organic pollutants of the present invention, the total energy ΣQ _a absorbed by organic pollutants in the process of temperature rise and phase change in S1-2 is:

in, Indicates the molar flow rate of water, /> Represents the molar mass of water, T ₀ represents the initial temperature of the waste water raffinate, /> Represents the latent heat of vaporization of water, VM _gas represents the molar flow rate of the gas, and T _flu represents the operating temperature of the fluidized bed.

Further, in the energy dynamic optimization control method for ultra-clean discharge of organic pollutants of the present invention, the energy conversion equation, energy transfer equation and energy dynamic self-heat balance model established in S2 are:

Among them, V _i , T _i , and C _i respectively represent the volume, temperature, and concentration of the i-th reactant, Indicates the total energy released by organic pollutants during the reaction at different times, /> Indicates the total energy absorbed by organic pollutants during temperature rise and phase transition at different times.

Further, in the energy dynamic optimization control method for ultra-clean emission of organic pollutants of the present invention, the energy dynamic optimization problem and objective function in S3 are:

Among them, J is the objective function, x ^* represents the initial state of the pollutant control system at the initial time t ^* , T _f represents the terminal time of the batch process, and is also the prediction time domain in the optimal control problem, V ₁ and V ₂ is the economic item parameter in the objective function, where V ₁ is the process economic item parameter of the system, V ₂ is the terminal economic item parameter, U is the optimal control sequence, x() is the desired state, and u(t) is the control input Variable, d(t) represents the disturbance variable, F(x(t),u(t),d(t)) represents the nonlinear mapping relationship of the process, COD(x ^* ) represents the chemical oxygen demand, VOCs(x ^* ) represents volatile organic compounds, x(t) represents the state of the pollutant control system, x ^min represents the lower limit of the feasible region of the state variable, x ^max represents the upper limit of the feasible region of the state variable, u ^min represents the minimum value of the control input, and u ^max represents The maximum value of the control input, Indicates the minimum value of the batch process terminal time, Indicates the maximum value of the batch process terminal time.

Further, in the energy dynamic optimization control method for ultra-clean emission of organic pollutants of the present invention, in S4, the improved control trajectory parameterization method is used to express the control input variables of the system as discrete forms, including:

For the i-th control input, its input sequence is discretized into several discrete continuous segments within a finite time interval, where, Represents the length of each control interval, /> Represents the number of control intervals, and its product /> Indicates the length of the entire control time domain;

When the control time domain exceeds the previously set terminal time, the width of the control unit remains unchanged, and the number of control units becomes:

Among them, the symbol Represents rounding down, t* represents the starting time;

When the control time domain is shorter than the optimal control time domain, the control interval calculation formula is as follows:

Among them, ω ₀ represents the ratio of the expected control time domain to the current moment control time domain.

Further, in the energy dynamic optimization control method for ultra-clean emission of organic pollutants of the present invention, the iterative optimization using the rolling optimization strategy of model predictive control in S5 includes:

In each sampling interval, the optimal control sequence and the optimized terminal time T _f in the next cycle are calculated by the objective function, and the first number of the optimal control sequence and the optimized terminal time T _f are applied to In the energy dynamic self-heat balance model, the optimal trajectory and terminal time of the next control time domain are solved.

Further, the energy dynamic optimization control method of ultra-clean discharge of organic pollutants of the present invention checks the state variable N _Bound times of the system from the initial moment of the system to the terminal time domain (t*, T _f ), if there is Boundary constraints, calculate the integral value beyond the constraint range and multiply it by a coefficient to punish φ, and add it to the original objective function to obtain a new objective function:

Among them, φ _k represents the penalty coefficient at time k, Represents the dimension of the state variable, x ^bound represents the boundary value of the state variable, t ₁ represents the start time of exceeding the boundary constraint, and t ₂ represents the end time of exceeding the boundary constraint.

Compared with the prior art, the present invention adopts the above technical scheme and has the following technical effects:

1. The energy dynamic optimization control method for ultra-clean discharge of organic pollutants of the present invention, through rational use of the energy of high-concentration organic pollutants, establishes an internal energy self-heating balance control system for pollutant treatment, and realizes the operation target of ultra-clean emissions.

2. The energy dynamic optimization control method for ultra-clean discharge of organic pollutants of the present invention solves the problems of high energy consumption and high cost of traditional pollutant treatment processes while purifying and controlling organic pollutants.

Description of drawings

The accompanying drawings are used to provide a further understanding of the present invention, and are used together with the description to explain the embodiments of the present invention, and do not constitute a limitation to the present invention. In the attached picture:

Fig. 1 shows the process diagram of the catalytic oxidation treatment of organic pollutants in the present invention.

Fig. 2 shows a schematic diagram of the energy dynamic optimization control method of the present invention.

Fig. 3 shows a schematic diagram of the energy internal self-heat balance system of the present invention.

Fig. 4 shows a schematic diagram of the non-stationary terminal optimization method in the prediction time domain and the control time domain.

Figure 5 shows the effect diagram of organic pollutant treatment.

Detailed ways

In order to further understand the present invention, the preferred embodiments of the present invention are described below in conjunction with examples, but it should be understood that these descriptions are only to further illustrate the features and advantages of the present invention, rather than to limit the claims of the present invention.

The description in this part is only for typical embodiments, and the present invention is not limited to the scope of the description of the embodiments. Combinations of different embodiments, mutual replacement of some technical features in different embodiments, mutual replacement of the same or similar prior art means and some technical features in the embodiments are also within the scope of description and protection of the present invention.

According to one aspect of the present invention, an energy dynamic optimization control method for ultra-clean emission of organic pollutants, comprising:

S1. Constructing the self-heating balance rate of organic pollutant treatment, the self-heating balance rate is defined as the ratio of the total energy absorbed to the total energy released in the process of organic pollutant treatment.

S1-1. Based on thermodynamic analysis, establish an energy conversion equation for the catalytic oxidation process of organic pollutants, and calculate the total energy ∑Q _r released by organic pollutants during the catalytic oxidation process based on this equation. The total energy ∑Q _r released is Including: the heat released by catalytic oxidation of gaseous organic matter Q _rwg , the heat released by catalytic oxidation of wastewater Q _rww , the heat released by catalytic oxidation of raffinate Q _rds ; the total energy ∑Q _r released by organic pollutants in the process of catalytic oxidation is:

Among them, H _wg represents the heat release corresponding to the oxygen consumption of the exhaust gas, V _wg represents the volume corresponding to the oxygen consumption of the exhaust gas, and C _wg represents the concentration of organic pollutants in the exhaust gas, Represents the mole fraction of oxygen, V _m represents the molar volume of exhaust gas, H _ww represents the heat release corresponding to the oxygen consumption of wastewater, V _ww represents the volume corresponding to the oxygen consumption of wastewater, ρ _ds represents the density of raffinate, V _ds represents The volume corresponding to the oxygen consumption of the raffinate, H _ds represents the heat release corresponding to the oxygen consumption of the raffinate, /> Indicates the heat absorbed by the residual liquid in the process of purification, /> Indicates the heat absorbed by the carbon dioxide produced by the raffinate during the purification process.

S1-2. Establish the energy transfer equation of the organic pollutant treatment process, and based on this equation, calculate the total energy ∑Q _a absorbed by the organic pollutant during the temperature rise and phase transition process. The total absorbed energy ∑Q _a includes: Sensible heat required to raise the temperature of waste water and raffinate and latent heat of vaporization /> And the total sensible heat Q _gas required by water vapor and air to heat up to the optimum reaction temperature; the total energy ΣQ _a absorbed by organic pollutants in the process of temperature rise and phase change is:

in, Indicates the molar flow rate of water, /> Represents the molar mass of water, T ₀ represents the initial temperature of the waste water raffinate, /> Represents the latent heat of vaporization of water, VM _gas represents the molar flow rate of the gas, and T _flu represents the operating temperature of the fluidized bed.

S1-3. Construct the self-heating balance rate of organic pollutant treatment:

S2. Based on the oxygen cracking catalytic oxidation treatment process adopted by organic pollutants, according to the concentration of each component of organic pollutants and the change of oxygen consumption, the energy conversion equation and energy transfer equation of the organic pollutant treatment process are established, and the energy dynamics are constructed Self-heating equilibrium model. The established energy conversion equation, energy transfer equation and energy dynamic self-heat balance model are:

Among them, V _i , T _i , and C _i respectively represent the volume, temperature, and concentration of the i-th reactant, Indicates the total energy released by organic pollutants during the reaction at different times, /> Indicates the total energy absorbed by organic pollutants during temperature rise and phase transition at different times.

S3. Based on the energy dynamic self-heat balance model, construct the energy dynamic optimization problem of ultra-clean emission of organic pollutants, and determine the optimization objective function. The energy dynamic optimization problem and objective function are:

Among them, J is the objective function, x ^* represents the initial state of the pollutant control system at the initial time t ^* , T _f represents the terminal time of the batch process, and is also the prediction time domain in the optimal control problem, V ₁ and V ₂ is the economic item parameter in the objective function, where V ₁ is the process economic item parameter of the system, V ₂ is the terminal economic item parameter, U is the optimal control sequence, x() is the desired state, and u(t) is the control input Variable, d(t) represents the disturbance variable, F(x(t),u(t),d(t)) represents the nonlinear mapping relationship of the process, COD(x ^* ) represents the chemical oxygen demand, VOCs(x ^* ) represents volatile organic compounds, x(t) represents the state of the pollutant control system, x ^min represents the lower limit of the feasible region of the state variable, x ^max represents the upper limit of the feasible region of the state variable, u ^min represents the minimum value of the control input, and u ^max represents The maximum value of the control input, Indicates the minimum value of the batch process terminal time, Indicates the maximum value of the batch process terminal time.

S4. Using the improved control trajectory parameterization method to express the control input variables of the pollutant control system in a discrete form, so that the energy dynamic optimization problem is transformed into a nonlinear programming problem. Specifically:

For the i-th control input, its input sequence is discretized into several discrete continuous segments within a finite time interval, where, Represents the length of each control interval, /> Represents the number of control intervals, and its product /> Indicates the length of the entire control time domain;

When the control time domain exceeds the previously set terminal time, the width of the control unit remains unchanged, and the number of control units becomes:

Among them, the symbol Represents rounding down, t* represents the starting time;

When the control time domain is shorter than the optimal control time domain, the control interval calculation formula is as follows:

Among them, ω ₀ represents the ratio of the expected control time domain to the current moment control time domain.

S5, using the ODE solver to solve the equality constraints in the above-mentioned nonlinear programming problem; using the penalty function method of constructing an obstacle function in the objective function, constructing a dual optimization problem, and solving the inequality constraints in the above-mentioned nonlinear programming problem, And through continuous iteration to reduce the weight of the barrier function, the optimal control sequence and terminal time are obtained; the rolling optimization strategy of model predictive control is used for iterative optimization to realize the energy self-sufficiency of the system. Among them, the iterative optimization using the rolling optimization strategy of model predictive control includes:

In each sampling interval, the optimal control sequence and the optimized terminal time T _f in the next cycle are calculated by the objective function, and the first number of the optimal control sequence and the optimized terminal time T _f are applied to In the energy dynamic self-heat balance model, the optimal trajectory and terminal time of the next control time domain are solved.

From the initial moment of the system to the terminal time domain (t*, T _f ), check the state variable of the system N _Bound times, if there is a boundary constraint, calculate the integral value beyond the constraint range and multiply it by a coefficient to punish φ , and add it to the original objective function, the new objective function is:

Among them, φ _k represents the penalty coefficient at time k, Represents the dimension of the state variable, x ^bound represents the boundary value of the state variable, t ₁ represents the start time of exceeding the boundary constraint, and t ₂ represents the end time of exceeding the boundary constraint.

Example 1

Taking part of the organic pollutant treatment process in the production process of acrylic acid as an example, the organic pollutants produced in the production of acrylic acid are treated with two-stage two-phase catalytic oxidation technology in a fluidized bed reactor and a fixed bed reactor for oxygen cracking and catalytic oxidation to remove pollutants removed, as shown in Figure 1. Construct the energy dynamic self-heat balance system, as shown in Figure 2. A large amount of energy released by the catalytic reaction can be directly used for the heat required for temperature rise and vaporization of non-gaseous pollutants, as shown in Figure 3. The technical solution of the present invention is based on the in-depth analysis of the oxygen cracking catalytic oxidation treatment process, and based on the thermodynamic analysis, a simplified calculation method of "oxygen consumption" is proposed to calculate the energy conversion in the process of catalytic oxidation of organic pollutants under different components and different phase states. Equation (that is, release energy), and the energy transfer equation (that is, energy absorption) of organic pollutants in different phases in the process of temperature rise and phase change.

Using the energy dynamic optimization control method under the constraints of ultra-clean discharge of organic pollutants in this technical solution, a dynamic energy self-heating balance model is constructed for the organic pollutants produced in the production process of acrylic acid. The specific steps include:

S1. Construct the self-heat balance rate of organic pollutant treatment, and define the self-heat balance rate as the ratio of the total energy absorbed to the total energy released during the treatment of organic pollutants.

S1-1. Establish the energy conversion equation for the catalytic oxidation process of organic pollutants, calculate the total energy ∑Q _r released by organic pollutants during the reaction process, including the heat Q _rwg released by catalytic oxidation of gaseous organic substances such as propylene, propane, and carbon monoxide, The heat Q _rww released by catalytic oxidation of wastewater, and the heat Q _rds released by catalytic oxidation of raffinate.

S1-2. Establish the energy transfer equation of the organic pollutant treatment process, and calculate the total energy ∑Q _a absorbed by the organic pollutant in the process of temperature rise and phase change, including the sensible heat required for the temperature rise of waste water and raffinate and latent heat of vaporization /> And the total sensible heat Q _gas required to warm up the water vapor and air to the optimum reaction temperature.

S1-3. The self-heating balance rate of organic pollutant treatment is the ratio of the total energy absorbed to the total energy released:

S2. Establish the energy conversion equation and energy transfer equation of the organic pollutant treatment process according to the change of the concentration of each component of the organic pollutant and the oxygen consumption, and construct the energy dynamic self-heating balance model:

Where V _i , T _i , and C _i represent the volume, temperature, and concentration of the i-th reactant, respectively, Indicates the total energy released by organic pollutants during the reaction at different times, /> Indicates the total energy absorbed by organic pollutants during temperature rise and phase transition at different times.

When HBR(t)=1, the internal energy of the organic pollutant treatment system is self-sufficient and does not require external heat supply; when HBR(t)≠1, it is necessary to calculate and control the flow of waste water and rectification raffinate until it satisfies HBR(t)=1; if HBR(t)>1 after adjustment, it means that the heat released by the organic pollutants is not enough to maintain the self-heating balance, and an external heat supply is needed to maintain the optimal reaction temperature of the catalytic reaction.

S3. Construct an energy dynamic optimization problem under multiple constraints of ultra-clean emission of organic pollutants, and determine an optimization objective function. Its dynamic optimization problem is described as:

Where x ^* represents the initial state of the system at the initial time t ^* , and T _f represents the terminal time of the batch process, which is also the prediction time domain in the optimal control problem. V ₁ and V ₂ are the economic item parameters in the objective function, where V ₁ indicates the process economic item parameters of the system, and V ₂ indicates the terminal economic item parameters.

S4. Use the control trajectory parameterization method to discretize the control input variables of the system, so that the dynamic optimization problem is transformed into a nonlinear programming constraint problem, and solve the nonlinear programming problem, specifically:

As shown in Figure 4, for the i-th control input, its input sequence is discretized into several discrete continuous segments within a finite time interval, where Represents the length of each control interval, /> Represents the number of control intervals, the product of which Indicates the length of the entire control domain. In the process of initial selection of the length and size of the control interval, it is determined by the dynamic characteristics of the controlled object, and the discrete control sequence is more conducive to the calculation of the objective function.

When the control time domain exceeds the previously set terminal time, the width of the control unit will remain unchanged, while the number of control units will change:

symbol Represents rounding down, and t* represents the starting time.

When the control time domain is shorter than the optimal control time domain, the control interval calculation formula is as follows:

Where ω ₀ represents the ratio of the expected control time domain to the current moment control time domain.

The equality constraints in the boundary constraints, that is, the energy dynamic model, can be directly calculated by the ODE solver. When solving inequality constraints, since it is impossible to directly calculate, the penalty function method is used to solve the inequality constraints. The penalty function method solves the inequality constraints in the nonlinear programming problem by constructing an obstacle function in the objective function and constructing a dual optimization problem. Through continuous iteration To reduce the weight in the barrier function, get the best control sequence and optimal time.

In each cycle of optimal control, the objective function needs to be recalculated and estimated. The process model calculates the optimal control sequence in the next cycle and the optimized terminal time T _f through the objective function, and optimizes the control sequence The first number of and the optimized terminal time T _f are applied to the dynamic model to solve the optimal trajectory and terminal time of the next control time domain, from the initial moment of the system to the terminal time domain (t*,T _f ) Within, the state variable of the system will be checked N _Bound times, if there is a boundary constraint, the integral value beyond the constraint range will be calculated and multiplied by a coefficient to punish φ, and added to the original objective function:

In each sampling interval, the process model calculates the optimal control sequence and the optimized terminal time T _f in the next cycle through the objective function, and applies the first number of the optimized control sequence and the optimized terminal time T _f to Into the dynamic model, to solve the optimal trajectory and terminal time of the next control time domain, iterative optimization realizes real-time automatic control of organic waste gas, wastewater, raffinate and oxygen excess multiples, and realizes self-sufficiency of system energy.

The description and application of the invention herein is illustrative and is not intended to limit the scope of the invention to the above-described embodiments. Relevant descriptions such as effects or advantages involved in the description may not be reflected in actual experimental examples due to uncertainties in specific conditions and parameters or other factors. Relevant descriptions such as effects or advantages are not used to limit the scope of the invention. Variations and changes to the embodiments disclosed herein are possible, and substitutions and equivalents for various components of the embodiments are known to those of ordinary skill in the art. It should be clear to those skilled in the art that the present invention can be realized in other forms, structures, arrangements, proportions, and with other components, materials and parts without departing from the spirit or essential characteristics of the present invention. Other modifications and changes may be made to the embodiments disclosed herein without departing from the scope and spirit of the invention.

Claims (9)

1. The energy dynamic optimization control method for the ultra-clean emission of the organic pollutants is characterized by comprising the following steps of:

s1, constructing an self-heating balance rate for organic pollutant treatment, wherein the self-heating balance rate is defined as the ratio of total energy absorbed to total energy released in the organic pollutant treatment process;

s2, based on an oxygen-induced cracking catalytic oxidation treatment process adopted by the organic pollutants, an energy conversion equation and an energy transfer equation of the organic pollutant treatment process are established according to the concentration of each component of the organic pollutants and the change of oxygen consumption, and an energy dynamic self-heating balance model is established;

s3, constructing an energy dynamic optimization problem of ultra-clean emission of organic pollutants based on an energy dynamic self-heating balance model, and determining an optimization objective function;

s4, using an improved control track parameterization method to represent a control input variable of the pollutant treatment system in a discrete form, so that the energy dynamic optimization problem is converted into a nonlinear programming problem;

s5, solving the equation constraint in the nonlinear programming problem by adopting an ODE solver; constructing a dual optimization problem by adopting a penalty function method for constructing an obstacle function in an objective function, solving the inequality constraint in the nonlinear programming problem, and reducing the weight in the obstacle function through continuous iteration to obtain an optimal control sequence and terminal time; and (3) performing iterative optimization by adopting a rolling optimization strategy of model predictive control to realize self-sufficiency of system energy.

2. The energy dynamic optimization control method for ultra-clean emission of organic pollutants according to claim 1, wherein constructing the self-heating balance rate for organic pollutant treatment in S1 comprises:

s1-1, based on thermodynamic analysis, establishing an energy conversion equation of the catalytic oxidation process of the organic pollutants, and calculating the release of the organic pollutants in the catalytic oxidation process based on the equationTotal energy sigma Q _r The total energy of the release Σq _r Comprising the following steps: heat Q released by catalytic oxidation of gaseous organic matter _rwg Heat Q released by catalytic oxidation of waste water _rww Heat released by catalytic oxidation of residual liquid Q _rds ；

S1-2, establishing an energy transfer equation of the organic pollutant treatment process, and calculating total energy sigma Q absorbed by the organic pollutant in the temperature rise and phase change processes based on the equation _a The total energy of the absorption sigma Q _a Comprising the following steps: sensible heat required by heating up waste water and residual liquidAnd latent heat of vaporization->Total sensible heat Q required for water vapor and air to warm up to optimal reaction temperature _gas ；

S1-3, constructing self-heating balance rate of organic pollutant treatment:

3. the energy dynamic optimization control method for ultra-clean emission of organic pollutants according to claim 2, wherein the total energy Sigma Q released by the organic pollutants in S1-1 in the catalytic oxidation process _r The method comprises the following steps:

wherein ,H_wg Represents the amount of heat release corresponding to the oxygen consumption of the exhaust gas, V _wg Representing the volume corresponding to the oxygen consumption of the exhaust gas, C _wg Indicating the concentration of organic pollutants in the exhaust gas,represents the mole fraction of oxygen, V _m Represents the molar volume of the exhaust gas, H _ww Represents the heat release amount corresponding to the oxygen consumption of the wastewater, V _ww Represents the volume corresponding to the oxygen consumption of the wastewater, ρ _ds Representing the density of the residual liquid, V _ds Represents the volume corresponding to the oxygen consumption of the residual liquid, H _ds Indicates the heat release amount corresponding to the oxygen consumption of the residual liquid, < + >>Indicating that the residual liquid generates heat absorbed by water during purification>Indicating the amount of heat absorbed by the carbon dioxide generated by the raffinate during the purification process.

4. The energy dynamic optimization control method for ultra-clean emission of organic pollutants according to claim 2, wherein the total energy sigma Q absorbed by the organic pollutants in S1-2 in the temperature rise and phase change processes _a The method comprises the following steps:

wherein ,represents the molar flow of water, +.>Represents the molar mass of water, T ₀ Indicating the initial temperature of the residual liquid of the wastewater,representing the latent heat of vaporization of water, VM _gas Represents the molar flow rate of the gas, T _flu Indicating the fluidized bed operating temperature.

5. The energy dynamic optimization control method for ultra-clean emission of organic pollutants according to claim 1, wherein the energy conversion equation, the energy transfer equation and the energy dynamic self-heating balance model established in S2 are as follows:

wherein ,V_i 、T _i 、C _i Respectively representing the volume, temperature and concentration of the ith reactant,represents the total energy released by the organic pollutants during the reaction at different times, +.>Indicating the total energy absorbed by the organic contaminants during the temperature rise and phase change at different times.

6. The energy dynamic optimization control method for ultra-clean emission of organic pollutants according to claim 1, wherein the energy dynamic optimization problem and objective function in S3 are:

wherein J is an objective function, x ^* Indicating that the pollutant treating system is at the initial time t ^* Initial state of time system, T _f Representing the end time of a batch process, and also being the predicted time domain in the optimization control problem, V ₁ and V₂ Is an economic term parameter in the objective function, where V ₁ Representing process economic parameters of the system, V ₂ Indicating terminal economyThe term parameters, U, represents the optimal control sequence, x () represents the desired state, U (t) represents the control input variable, d (t) represents the disturbance variable, F (x (t), U (t), d (t)) represents the nonlinear mapping of the process, COD (x) ^* ) Represents chemical oxygen demand, VOCs (x ^* ) Representing volatile organic compounds, x (t) representing the state of the pollutant abatement system, x ^min Representing the lower bound, x, of the feasible domain of state variables ^max Representing the upper limit, u, of the feasible region of the state variable ^min Representing the minimum value of the control input, u ^max Represents the maximum value of the control input,Representing the minimum value of the end time of the batch process,Representing the maximum value of the end time of the batch process.

7. The energy dynamic optimization control method of ultra-clean emission of organic pollutants according to claim 1, wherein the representation of the control input variables of the system in a discrete form using the modified control trajectory parameterization method in S4 comprises:

for the ith control input, its input sequence is discretized into a number of discrete, consecutive segments within a finite time interval, wherein,representing the length of each control interval, +.>Represents the number of control intervals, the product +.>Representing the length of the entire control time domain;

when the control time domain exceeds the previously set terminal time, the width of the control units remains unchanged, and the number of the control units becomes:

wherein the symbols areRepresents a downward rounding, t represents a starting time;

when the control time domain is shorter than the optimal control time domain, the control interval calculation formula is as follows:

wherein ,ω₀ Representing the ratio of the desired control time domain to the current time control time domain.

8. The method for dynamic energy optimization control of ultra-clean emission of organic pollutants according to claim 1, wherein the iterative optimization in S5 using a rolling optimization strategy controlled by model prediction comprises:

in each sampling interval, calculating the optimal control sequence and the optimized terminal time T in the next period through an objective function _f And the first number of the optimal control sequences and the optimized terminal time T _f The method is applied to an energy dynamic self-heating balance model, and solves the optimal track and the terminal time of the next control time domain.

9. The method for dynamically optimizing and controlling the energy of ultra-clean emission of organic pollutants according to claim 8, wherein the time-domain (T, T _f ) In, the state variable N of the inspection system _Bound If the boundary constraint is exceeded, calculating an integral value exceeding the constraint range, multiplying the integral value by a coefficient penalty phi, and adding the coefficient penalty phi to the original objective function to obtain a new objective function as follows:

wherein ,φ_k The penalty factor at time k is indicated,representing the dimension, x of a state variable ^bound Representing the boundary value, t, of a state variable ₁ Represents the start time, t, beyond the boundary constraint ₂ Indicating a termination time beyond the boundary constraint.