CN113887021A - Optimization and adjustment method for anaerobic digestion process parameters - Google Patents
Optimization and adjustment method for anaerobic digestion process parameters Download PDFInfo
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Abstract
The invention discloses an optimization and adjustment method for anaerobic digestion process parameters. The method comprises the following steps of (1) establishing a fitting function by using a K nearest neighbor method, wherein the temperature T of an anaerobic tank, the pH of the anaerobic tank, the slurry quantity L of the anaerobic tank, the slurry solid content G of the anaerobic tank and the accumulated stirring time J of the anaerobic tank are independent variables, and the anaerobic digestion gas production Q is a dependent variable; and (3) performing optimization analysis on the gas production function Q, solving the values of all key process parameters when the energy consumption is the lowest and the anaerobic digestion gas production is the largest, and for the problem of optimizing the anaerobic digestion gas production, constructing an evaluation function and 3 constraint conditions, wherein 3 objective functions are Q, T and J, thereby completing the establishment of a mathematical model of the anaerobic digestion gas production multi-objective planning. The invention realizes the automatic optimization and adjustment of the process parameters, which not only reduces the working intensity of operators, but also greatly improves the working efficiency and the working quality.
Description
Technical Field
The invention relates to the technical field of environmental treatment, in particular to an optimization and adjustment method for anaerobic digestion process parameters.
Background
Anaerobic digestion is a very important solid waste treatment method, and is a process of placing organic matters (kitchen waste, kitchen garbage, livestock and poultry manure, organic sludge, agricultural wastes and the like) into a closed container (anaerobic tank) for anaerobic fermentation, so that organic matters of organic macromolecules are decomposed and converted into methane mainly comprising methane. Compared with disposal methods such as landfill, incineration, compost and the like, anaerobic digestion is the most widely applied resource disposal method internationally at present due to efficient resource recovery and lower environmental impact.
The anaerobic digestion and biogas purification system mainly comprises a mechanical pretreatment system, an anaerobic digestion system (consisting of one or a plurality of anaerobic tanks) and a biogas purification system. Generally, the control of the three systems can be integrated and displayed in the same operation interface, and an operator only needs to operate on one operation interface to complete the manual control of the three systems.
What the operator needs to do is mainly to pay attention to and adjust the following key process parameters in real time: the method comprises the following steps of controlling the liquid level height of a feeding pool, opening and closing a stirrer of the feeding pool, opening and closing a feeding pump, setting feeding amount, controlling the liquid level height of each anaerobic tank, controlling the temperature of each anaerobic tank, controlling the pressure of each anaerobic tank, opening and closing the number of stirrers of each anaerobic tank, opening and closing a material delivery pump between each anaerobic tank and each anaerobic tank, setting the gas production channel occupancy of each anaerobic tank, setting the ignition pressure of a torch of each anaerobic tank, and setting the gas production flow of a biogas purification product gas. The aim is to ensure that the daily gas production of the biogas purification product is as large as possible under the condition of low energy consumption as possible.
An operator needs to pay attention to tens of key process parameters in real time, make correct and reasonable judgment in a short time and make corresponding adjustment. This is not a small stress for the operator. After all, the operator has limited energy and is not able to take the problem into account, and the operator is inevitably left. It is unrealistic to ensure that the daily gas production of the product gas is as large as possible only by manpower. The daily gas production achieved by different operators will necessarily vary from operator to operator, depending on experience and competence.
Therefore, there is an urgent need for an accurate automatic adjustment method, wherein the control system can perform automatic coordinated control on the mechanical pretreatment system, the anaerobic digestion system and the biogas purification system on the premise of sufficient supply of anaerobic digestion raw materials and stable components, so as to ensure the maximum daily gas production of biogas purification product gas under the condition of low energy consumption.
Disclosure of Invention
The invention aims to provide an optimized adjustment method for anaerobic digestion process parameters, which reduces the working strength of operators and greatly improves the working efficiency and the working quality aiming at the defects in the prior art.
The invention discloses an optimization and adjustment method of anaerobic digestion process parameters, which comprises the following steps:
s1: establishing a database: recording the temperature T of the anaerobic tank, the pH value of the anaerobic tank, the slurry amount L of the anaerobic tank, the solid content G of the slurry of the anaerobic tank, the accumulated stirring time J of the anaerobic tank and the anaerobic digestion gas production Q, and establishing a database of the 6 key data;
s2, establishing a mathematical model of anaerobic digestion gas production: selecting the temperature T of an anaerobic tank, the pH value of the anaerobic tank, the slurry quantity L of the anaerobic tank, the slurry solid content G of the anaerobic tank and the accumulative stirring time J of the anaerobic tank in a database, taking the 5 key parameters as independent variables, taking the anaerobic digestion gas production Q as dependent variables, and establishing a fitting function by using a K nearest method to obtain the fitting function: q ═ F (T, pH, L, G, J);
s3: establishing a mathematical model of anaerobic digestion gas production multi-objective planning: for each anaerobic tank, in order to ensure that the anaerobic digestion gas production is maximum under the condition of lowest energy consumption, the gas production function Q must be optimized and analyzed to obtain key values when the energy consumption is minimum and the anaerobic digestion gas production is maximumThe value of the process parameter is that for the problem of optimizing the anaerobic digestion gas production, the target value is 3, namely the anaerobic digestion gas production Q, the anaerobic tank temperature T and the anaerobic tank accumulated stirring time J, and the following evaluation function is constructed, namely minQ [ [ omega ] ]1f(T)+ω2f(J)+ω3f(L)+ω4f(pH)+ω5f(G)]One of the constraint conditions is the value range of 3 key process parameters, namely the temperature T of the anaerobic tank must be between the minimum temperature and the maximum temperature T necessary for anaerobic digestion reactionmin≤T≤TmaxThe amount of anaerobic tank slurry L must be between the lowest and highest capacity L that the anaerobic tank can carrymin≤L≤LmaxThe cumulative stirring time J of the anaerobic jar must be between the lowest cumulative time and the highest cumulative time Jmin≤J≤Jmax(ii) a The second constraint condition is that the pH value of the anaerobic tank is equal to a given pH value, and the solid content G of the slurry in the anaerobic tank is equal to a given solid content; omega1、ω2And ω3Is the weight of 3 objective functions, omega4、ω5Assigning the weight of the non-key parameter to a specific value according to the actual situation;
the establishment of a mathematical model of the anaerobic digestion gas production multi-target planning is completed with an objective function and constraint conditions, and the values of all key process parameters can be obtained when the energy consumption is as low as possible and the anaerobic digestion gas production is as large as possible by optimizing the multi-target planning problem.
Further, the temperature regulation of the anaerobic tank is realized by opening or closing the boiler; the increase of the slurry quantity L of the anaerobic tank is realized by feeding the slurry into the anaerobic tank through a feeding tank or conveying the slurry to the anaerobic tank through other anaerobic tanks, and the decrease of the slurry quantity L of the anaerobic tank is realized by outputting the slurry to other anaerobic tanks or directly discharging the slurry to a biogas slurry tank from outside; the method is characterized in that the cumulative stirring time J of the anaerobic tank is increased by opening the stirrers of the anaerobic tank, increasing the number and the time of opening the stirrers of the anaerobic tank, and the cumulative stirring time J of the anaerobic tank is reduced by completely closing the stirrers of the anaerobic tank or partially closing the stirrers of the anaerobic tank.
Further, automatic adjustment is carried out according to a mathematical model, so that 3 key process parameters, namely the temperature T of the anaerobic tank, the slurry quantity L of the anaerobic tank and the accumulated stirring time J of the anaerobic tank reach an optimized value, the pressure of the anaerobic tank changes at the moment, the pressure of the anaerobic tank must be within a certain range, the pressure range of the anaerobic tank is divided into 3 areas, namely a high-pressure early warning area, a normal working area and a low-pressure early warning area, and when the pressure of the anaerobic tank fluctuates in the normal working area, the process parameters do not need to be adjusted; when the pressure of the anaerobic tank is in a high-pressure early warning area or a low-pressure early warning area, the corresponding pressure reduction method or the corresponding pressure increase method is started immediately, namely, the process parameters are required to be adjusted.
Further, the pressure of the anaerobic tank is reduced by completely or partially closing the agitator of the anaerobic tank, or increasing the gas production flow of a biogas purification product, or opening a boiler until the pressure of the anaerobic tank is restored to a normal working area; the method for improving the pressure of the anaerobic tank is to completely open or partially open the agitator of the anaerobic tank, or reduce the gas production flow of the biogas purification product, or close the boiler.
Further, when the pressure of the anaerobic tank is in a high-pressure early warning area or a low-pressure early warning area, the pressure of the anaerobic tank is adjusted, the pressure of the anaerobic tank is restored to a normal working area, but the temperature T of the anaerobic tank, the slurry quantity L of the anaerobic tank and the cumulative stirring duration J of the anaerobic tank may deviate from the current optimized value, when the current optimized value is deviated, multi-objective planning is performed according to the current 5 process parameter values, namely the temperature T of the anaerobic tank, the pH value of the anaerobic tank, the slurry quantity L of the anaerobic tank, the solid content G of the slurry of the anaerobic tank and the cumulative stirring duration J of the anaerobic tank according to the current 5 process parameter values, so that the optimized values of the temperature T of the anaerobic tank, the slurry quantity L of the anaerobic tank and the cumulative stirring duration J of the anaerobic tank in a given time period can be obtained, then the temperature T of the anaerobic tank, the slurry quantity L of the anaerobic tank and the cumulative stirring duration J of the anaerobic tank are adjusted according to the optimized values, and the change of the pressure of the anaerobic tank can be caused, if the pressure of the anaerobic tank fluctuates in a normal working area, the technological parameters do not need to be adjusted; if the pressure of the anaerobic tank is in a high-pressure early warning area or a low-pressure early warning area, the corresponding pressure reduction method or the corresponding pressure increase method is started immediately, namely, the process parameters need to be adjusted, and the process is repeated in such a circulating way, so that the whole process parameter system is maintained in a dynamic balance.
According to the invention, through establishment of the mathematical model of anaerobic digestion gas production and multi-objective planning of key process parameters, automatic optimization and adjustment of the process parameters are realized, so that not only is the working intensity of an operator reduced, but also the working efficiency and the working quality are greatly improved.
Detailed Description
The following are specific examples of the present invention and further describe the technical solutions of the present invention, but the present invention is not limited to these examples.
Anaerobic digestion process parameters are not independent, but are correlated, and some parameters are even buckled in a ring.
For the liquid level height of the feeding pool, the liquid level height must be within a certain range, and if the liquid level height is too high, raw materials overflow the feeding pool, so that environmental pollution and raw material waste are caused; too low, the feed tank agitator may hang in the air, which is detrimental to the agitator. For the feeding pool stirrer, the stirrer does not need to work for 24 hours continuously, and only when the material dragging vehicle discharges materials or the feeding pump is started, the stirrer needs to work. For the feed pump, it is only switched on, typically off, when the anaerobic tank needs to be fed or when the feed tank level is too high. For the feeding quantity, the size of the feeding quantity is determined according to the liquid level height of the feeding pool and the pressure condition of the anaerobic tank, if the pressure of the anaerobic tank is too low, the feeding pump is started, and the proper feeding quantity is set, so that the pressure of the anaerobic tank can be increased; however, if the feeding amount is set to be too large, the liquid level height of the feeding pool and the liquid level height of the anaerobic tank are seriously influenced, and the pressure of the anaerobic tank is also too high.
For the liquid level height of the anaerobic tank, the liquid level height must be within a certain range, and if the liquid level height is too high, no gas storage space exists at all, and the pressure of the anaerobic tank is forced to be too high; if the liquid level is too low, most of stirrers of the anaerobic tank are empty, so that the stirrers are not favorable, and in addition, the pressure of the anaerobic tank is unstable due to too low liquid level, so that the pressure is difficult to maintain. For the temperature of the anaerobic tank, the temperature of the anaerobic tank must be within a certain range, and methanogens in the tank can only survive within a certain temperature range. In addition, the anaerobic tank is generally heated by a boiler, energy of the boiler is derived from methane generated by the anaerobic tank, and once the tank body needs to be heated, the methane in the anaerobic tank is consumed inevitably, so that the pressure of the anaerobic tank is reduced. For the pressure of the anaerobic tank, the pressure must be within a certain range, if the pressure is too high, the top membrane of the anaerobic tank is in a high-pressure tight state, the top membrane is unfavorable, the anaerobic tank is provided with a safety relief valve, once the pressure exceeds a critical value, the safety relief valve can be immediately and automatically opened, gas in the tank is forcibly discharged, and therefore the pressure of the anaerobic tank is forced to be reduced, generally, the step cannot be achieved, because the pressure reaches the critical value, the torch ignition pressure of the anaerobic tank is also set, the setting of the torch ignition pressure is also ingenious, and if the setting is too low, frequent overpressure ignition of the anaerobic tank can be caused; setting too high is detrimental to the top film. If the anaerobic tank pressure is too low, it will cause the anaerobic tank to suck back, which is absolutely not allowed. For the anaerobic tank stirrer, the anaerobic tank stirrer does not need to work for 24 hours continuously, and only needs to work when the pressure of the anaerobic tank is reduced. When the stirrer works, on one hand, the slurry in the tank is uniform, and on the other hand, the anaerobic biochemical reaction is accelerated, so that the gas in the slurry is quickly overflowed, and the pressure of the anaerobic tank is increased. In addition, the effect of more than one stirrer in an anaerobic tank, all the stirrers working simultaneously and a single stirrer working alone is different.
In order to keep the material balance among different anaerobic tanks, a slurry conveying pump between the anaerobic tanks needs to be opened at intervals, the anaerobic tank with a high liquid level conveys slurry to the anaerobic tank with a low liquid level, the pressure of the anaerobic tank with the high liquid level can be reduced along with the discharge of the slurry, and the pressure of the anaerobic tank with the low liquid level can be increased along with the input of the slurry. But it is not necessary to ensure that the slurry among different anaerobic tanks is absolutely equal, and the slurry balance among different anaerobic tanks is delicate balance which not only properly reduces the liquid level difference, but also ensures that the influence of the pressure of the anaerobic tanks is minimized.
The gas production channels of all the anaerobic tanks are finally gathered into a main pipe, and the main pipe is finally led to biogas purification equipment. In order to balance the exhaust flow of each anaerobic tank, the tail end of the gas production channel of each anaerobic tank is provided with a regulating valve, and the regulating valve can regulate the opening degree of the branch pipe, so that the gas production channel occupancy of each anaerobic tank is changed. When the opening of one anaerobic tank adjusting valve is adjusted to be small, the pressure of the anaerobic tank is increased, otherwise, the pressure of the anaerobic tank is decreased. Through the adjustment, the purpose of adjusting the pressure of the anaerobic tank is achieved.
The gas production flow of the biogas purification product must be within a certain range, and the higher the flow is, the better the flow is, but the higher the flow is, the pressure of the anaerobic tank is greatly reduced; too low, this can cause a significant increase in the pressure in the anaerobic tank. This necessitates a dynamic balance.
Since anaerobic digestion includes various complex reactions such as biology, chemistry, physics and the like, the anaerobic digestion is difficult to describe by using an accurate mathematical model, but in order to quantify how the change of various parameters brings about the influence of the anaerobic digestion gas production, a function which takes certain process parameters as independent variables and the anaerobic digestion gas production as dependent variables must be constructed. The function can only be fitted by approximation, so that the error between the fitted function and the actual function is as small as possible. Factors influencing an anaerobic digestion system are many, such as the change of conditions of anaerobic tank temperature, anaerobic environment, anaerobic tank pH value, fatty acid, anaerobic tank slurry quantity, anaerobic tank slurry solid content, anaerobic tank stirring effect and the like, all influence the anaerobic digestion methane production effect, wherein many parameters are necessary for establishing a mathematical model, but a large amount of data cannot be available in actual engineering. By means of modern mathematical numerical simulation technology and data mining technology, all parameters are not required to be mastered, a fitting function can be constructed by only utilizing the existing parameters, and the error precision of the fitting function can be controlled.
For this purpose, the temperature (. degree. C.) of the anaerobic tank, the pH value of the anaerobic tank, and the amount (m) of the slurry in the anaerobic tank were selected3The 5 key parameters of the solid content of the anaerobic tank slurry and the cumulative stirring time (min) of the anaerobic tank are independent variables, and the anaerobic digestion gas production (m)3Min) is a dependent variable, and a fitting function is established by using a K nearest neighbor method.
The KNN (K-Nearest Neighbor) method, the K Nearest Neighbor method, originally proposed by Cover and Hart in 1968, is a theoretically mature method and one of the simplest machine learning algorithms. The method has the following advantages that the idea is very simple and intuitive: if a sample belongs to a certain class in the K most similar samples in the feature space (i.e., the nearest neighbors in the feature space), then the sample also belongs to this class. The method only determines the category of the sample to be classified according to the category of the nearest sample or a plurality of samples in the classification decision. The KNN method is only related to a very small number of adjacent samples when the classification is decided. Because the KNN method mainly determines the class by the limited adjacent samples around, rather than by the method of distinguishing the class domain, the KNN method is more suitable than other methods for the sample sets to be classified with more class domain intersections or overlaps.
The KNN classification algorithm comprises the following 4 steps:
firstly, preparing data and preprocessing the data.
Calculating the distance from the test sample point (namely the point to be classified) to each other sample point.
And thirdly, sequencing each distance, and then selecting K points with the minimum distance.
And fourthly, comparing the categories of the K points, and classifying the test sample points into the category with the highest ratio among the K points according to the principle that a minority obeys majority.
The data here are the previously recorded parameter data, i.e., the anaerobic tank temperature T (. degree. C.), the anaerobic tank pH, the anaerobic tank slurry amount L (m)3Min), anaerobic tank slurry solid content G, anaerobic tank cumulative stirring time J (min) and anaerobic digestion gas production Q (m)3Min), the smaller and more accurate the error of the finally obtained fitting function is as long as the samples are enough and the proper K value is set.
Finally, a fitting function can be obtained:
Q＝F(T、pH、L、G、J)。
the fitting function Q is established for a single anaerobic tank on the premise that the components of the slurry are fixed and invariable, and obviously, the parameter data of different types of slurry, such as kitchen waste, livestock and poultry manure and organic sludge, are different, so the gas production function fitted according to the parameter data is necessarily different. In addition, the formula is considered in time unit of "minute", and if it is considered in time unit of "hour" or "day", the time interval is too long to be beneficial for the next optimization, so it is considered in time unit of "minute". And when parameter data acquisition is carried out in the early stage, measurement is carried out by taking minutes as time units correspondingly.
For each anaerobic tank, in order to ensure that the anaerobic digestion gas production is maximum under the condition of lowest energy consumption, the gas production function Q must be optimized and analyzed, and the values of all key process parameters when the energy consumption is lowest and the anaerobic digestion gas production is maximum are solved.
This is a problem of multi-objective planning, which is a branch of mathematical planning. The optimization of more than one objective function over a given area is studied, also known as multiobjective optimization. In many practical problems, such as the fields of economy, management, military, science and engineering design, the quality of a scheme is difficult to judge by using one index, and needs to be compared by using a plurality of targets, and the targets are sometimes not very coordinated or even contradictory. Any multi-objective planning problem consists of two basic components: (1) more than two objective functions; (2) several constraints.
Since the largest problem can be translated into the smallest problem, the general form of the multi-objective planning problem is:
min[f1(x),f2(x),…,fp(x)]T,p＞1
s.t.gi(x)≥0,i＝1,2,…,m
hi(x)＝0,i＝1,2,…,n
the most basic method for solving the multi-target planning problem is an evaluation function method, and the basic method is as follows: and constructing an evaluation function by means of a visual background in geometry or application, converting the multi-objective optimization problem into a single-objective optimization problem, then solving the optimal solution by using a solving method of the single-objective optimization problem, and taking the optimal solution as the optimal solution of the multi-objective optimization problem.
In optimization problems with multiple indices, it is always desirable to give larger weight coefficients to those indices that are relatively important, thereby converting the multi-objective vector problem into a weighted sum scalar problem for all objectives. Based on this reality, the following evaluation functions are constructed, namely
minF(x)＝ω1f1(x)+ω2f2(x)+…+ωifi(x),i＝1,2,…,p
In the formula of omegaiFor the weighting factor, there are many methods to choose, such as expert scoring, tolerance method, etc.
For the problem of optimizing anaerobic digestion gas production, 3 target values are provided, namely anaerobic digestion gas production Q, anaerobic tank temperature T and anaerobic tank accumulated stirring time J, the anaerobic digestion gas production Q is expected to be as large as possible, the anaerobic tank temperature T and the anaerobic tank accumulated stirring time J are expected to be as small as possible, but the weights of the 3 target values are different, and obviously, the anaerobic digestion gas production Q is maximum, and the weight of the anaerobic tank temperature T is minimum. As for how large the weights of the 3 objective functions are respectively, comprehensive judgment needs to be carried out according to actual conditions.
For the anaerobic digestion gas production optimization problem, the evaluation function is as follows:
minQ＝-[ω1f(T)+ω2f(J)+ω3f(L)+ω4f(pH)+ω5f(G)]
one of the constraint conditions of the anaerobic digestion gas production optimization problem is the value range of 3 key process parameters, namely the temperature T of the anaerobic tank must be between the minimum temperature and the maximum temperature necessary for anaerobic digestion reaction, the slurry quantity L of the anaerobic tank must be between the minimum capacity and the maximum capacity which can be borne by the anaerobic tank, and the accumulative stirring time J of the anaerobic tank must be between the minimum accumulative time and the maximum accumulative time.
The second constraint condition is that the pH value of the anaerobic tank is equal to a given pH value, and the solid content G of the slurry in the anaerobic tank is equal to a given solid content.
Thus, the establishment of the mathematical model of the anaerobic digestion gas production multi-target planning is completed with the target values and the constraint conditions.
ω1、ω2And ω3Is the weight of 3 objective functions, omega4、ω5Assigning the weight of the non-key parameter to a specific value according to the actual situation; the weight value is an empirical value obtained in the prior period during data accumulation, and the practical condition refers to the condition of system operation in the prior period.
By solving the multi-objective planning problem, the values of each key process parameter can be obtained when the energy consumption is as low as possible and the anaerobic digestion gas production is as large as possible.
By means of anaerobic digestion gas production optimization calculation, optimized values of 3 key process parameters (the temperature T of the anaerobic tank, the slurry quantity L of the anaerobic tank and the accumulative stirring time J of the anaerobic tank) in a given time period can be obtained, and according to comparison of the optimized values and the current actual values, a conclusion can be obtained: in order to optimize the anaerobic digestion gas production, it is necessary to increase or decrease the anaerobic tank temperature T, increase or decrease the anaerobic tank slurry amount L, increase or decrease the anaerobic tank cumulative stirring period J during the current period (1 minute).
The temperature T of the anaerobic tank is increased by opening a boiler; the reduction of the anaerobic tank temperature T is achieved by shutting down the boiler. This causes a change in the anaerobic tank pressure. When the temperature T of the anaerobic tank is increased, the pressure of the anaerobic tank is reduced; when the anaerobic tank temperature T is decreased, the anaerobic tank pressure increases.
The increase of the slurry quantity L of the anaerobic tank is realized by feeding the slurry into the anaerobic tank through a feeding tank or conveying the slurry to the anaerobic tank through other anaerobic tanks; the reduction of the slurry amount L of the anaerobic tank is realized by outputting slurry to other anaerobic tanks or directly discharging the slurry to a biogas slurry tank from outside.
Increasing the cumulative stirring time J of the anaerobic tank by opening the stirrers of the anaerobic tank and increasing the number and the time of opening; the reduction of the cumulative anaerobic tank stirring time J is realized by completely closing the anaerobic tank stirrer or partially closing the anaerobic tank stirrer. This causes a change in the anaerobic tank pressure. When the cumulative stirring time J of the anaerobic tank is increased, the pressure of the anaerobic tank is increased; when the cumulative agitation time period J of the anaerobic tank is reduced, the anaerobic tank pressure is reduced.
The system enables 3 key process parameters (the temperature T of the anaerobic tank, the slurry quantity L of the anaerobic tank and the accumulated stirring time J of the anaerobic tank) to reach optimal values through automatic adjustment, and the pressure of the anaerobic tank changes accordingly. As described above, the pressure of the anaerobic tank must be within a certain range, and for this purpose, the anaerobic tank pressure range is divided into 3 regions, i.e., a high pressure early warning region, a normal operation region, and a low pressure early warning region. When the pressure of the anaerobic tank fluctuates in a normal working area, the technological parameters do not need to be adjusted; when the pressure of the anaerobic tank is in a high-pressure early warning area or a low-pressure early warning area, the corresponding pressure reduction method or the corresponding pressure increase method is started immediately, namely, the process parameters are required to be adjusted.
The pressure of the anaerobic tank is reduced by completely or partially closing an anaerobic tank stirrer, or increasing the gas production flow of a biogas purification product, or opening a boiler. Until the pressure of the anaerobic tank is restored to the normal working area.
The method for improving the pressure of the anaerobic tank is to completely open or partially open the agitator of the anaerobic tank, or reduce the gas production flow of the biogas purification product, or close the boiler, or feed the anaerobic tank through a feed tank, or other anaerobic tanks deliver slurry to the anaerobic tank. Until the pressure of the anaerobic tank is restored to the normal working area.
After the system automatically adjusts the pressure of the anaerobic tank, the pressure of the anaerobic tank is restored to a normal working area, but at the moment, 3 key process parameters (the temperature T of the anaerobic tank, the slurry amount L of the anaerobic tank and the accumulative stirring time J of the anaerobic tank) may be separated from the current optimized value, so the system aims at the anaerobic digestion gas production function Q according to the current 5 process parameter values (the temperature T of the anaerobic tank, the pH value of the anaerobic tank, the slurry amount L of the anaerobic tank, the slurry solid content G of the anaerobic tank and the accumulative stirring time J of the anaerobic tank)Gas productionPerforming multi-objective planning to obtain optimized values of 3 key process parameters (the temperature T of the anaerobic tank, the slurry amount L of the anaerobic tank and the cumulative stirring time J of the anaerobic tank) in a given time period, and automatically selecting a method to adjust the 3 key process parameters (the temperature T of the anaerobic tank, the slurry amount L of the anaerobic tank and the cumulative stirring time J of the anaerobic tank) according to the optimized valuesThe stirring time J) is measured, so that the pressure of the anaerobic tank can be changed, and if the pressure of the anaerobic tank fluctuates in a normal working area, the technological parameters do not need to be adjusted; if the pressure of the anaerobic tank is in a high-pressure early warning area or a low-pressure early warning area, the corresponding pressure reduction method or the corresponding pressure increase method is started immediately, namely, the process parameters need to be adjusted. Then the pressure of the anaerobic tank is restored to a normal working area, 3 key process parameters (the temperature T of the anaerobic tank, the slurry quantity L of the anaerobic tank and the accumulated stirring time J of the anaerobic tank) can be separated from the current optimized value, a new round of anaerobic digestion gas production function Q multi-objective planning is carried out, and the steps are repeated in such a circulating way, and the whole process parameter system is maintained in a dynamic balance.
The automatic optimization technology is realized by relying on a modern control system, wherein the establishment and the correction of an anaerobic digestion gas production quantity mathematical model, the multi-objective planning of key process parameters and the establishment and the expansion of a database are all independent of a computer.
The above is not relevant and is applicable to the prior art.
While certain specific embodiments of the present invention have been described in detail by way of illustration, it will be understood by those skilled in the art that the foregoing is illustrative only and is not limiting of the scope of the invention, as various modifications or additions may be made to the specific embodiments described and substituted in a similar manner by those skilled in the art without departing from the scope of the invention as defined in the appending claims. It should be understood by those skilled in the art that any modifications, equivalents, improvements and the like made to the above embodiments in accordance with the technical spirit of the present invention are included in the scope of the present invention.
Claims (5)
1. An optimization and adjustment method for anaerobic digestion process parameters is characterized by comprising the following steps: the method comprises the following steps:
s1: establishing a database: recording the temperature T of the anaerobic tank, the pH value of the anaerobic tank, the slurry amount L of the anaerobic tank, the solid content G of the slurry of the anaerobic tank, the accumulated stirring time J of the anaerobic tank and the anaerobic digestion gas production Q, and establishing a database of the 6 key data;
s2, establishing a mathematical model of anaerobic digestion gas production: selecting the temperature T of an anaerobic tank, the pH value of the anaerobic tank, the slurry quantity L of the anaerobic tank, the slurry solid content G of the anaerobic tank and the accumulative stirring time J of the anaerobic tank in a database, taking the 5 key parameters as independent variables, taking the anaerobic digestion gas production Q as dependent variables, and establishing a fitting function by using a K nearest method to obtain the fitting function: q ═ F (T, pH, L, G, J);
s3: establishing a mathematical model of anaerobic digestion gas production multi-objective planning: for each anaerobic tank, in order to ensure that the anaerobic digestion gas production is maximum under the condition of lowest energy consumption, optimization analysis must be carried out on a gas production function Q, the value of each key process parameter is obtained when the energy consumption is lowest and the anaerobic digestion gas production is maximum, for the anaerobic digestion gas production optimization problem, the target value is 3, namely the anaerobic digestion gas production Q, the anaerobic tank temperature T and the anaerobic tank accumulated stirring time J, and the following evaluation function is constructed, namely minQ [ omega ] is formed1f(T)+ω2f(J)+ω3f(L)+ω4f(pH)+ω5f(G)]One of the constraint conditions is the value range of 3 key process parameters, namely the temperature T of the anaerobic tank must be between the minimum temperature and the maximum temperature T necessary for anaerobic digestion reactionmin≤T≤TmaxThe amount of anaerobic tank slurry L must be between the lowest and highest capacity L that the anaerobic tank can carrymin≤L≤LmaxThe cumulative stirring time J of the anaerobic jar must be between the lowest cumulative time and the highest cumulative time Jmin≤J≤Jmax(ii) a The second constraint condition is that the pH value of the anaerobic tank is equal to a given pH value, and the solid content G of the slurry in the anaerobic tank is equal to a given solid content; omega1、ω2And ω3Is the weight of 3 objective functions, omega4、ω5Assigning the weight of the non-key parameter to a specific value according to the actual situation;
the establishment of a mathematical model of the anaerobic digestion gas production multi-target planning is completed with an objective function and constraint conditions, and the values of all key process parameters can be obtained when the energy consumption is as low as possible and the anaerobic digestion gas production is as large as possible by optimizing the multi-target planning problem.
2. A method of optimizing anaerobic digestion process parameters according to claim 1, wherein: the temperature regulation of the anaerobic tank is realized by opening or closing a boiler; the increase of the slurry quantity L of the anaerobic tank is realized by feeding the slurry into the anaerobic tank through a feeding tank or conveying the slurry to the anaerobic tank through other anaerobic tanks, and the decrease of the slurry quantity L of the anaerobic tank is realized by outputting the slurry to other anaerobic tanks or directly discharging the slurry to a biogas slurry tank from outside; the method is characterized in that the cumulative stirring time J of the anaerobic tank is increased by opening the stirrers of the anaerobic tank, increasing the number and the time of opening the stirrers of the anaerobic tank, and the cumulative stirring time J of the anaerobic tank is reduced by completely closing the stirrers of the anaerobic tank or partially closing the stirrers of the anaerobic tank.
3. A method of optimizing anaerobic digestion process parameters according to claim 1, wherein: the method comprises the following steps of automatically adjusting according to a mathematical model, enabling 3 key process parameters, namely the temperature T of an anaerobic tank, the slurry quantity L of the anaerobic tank and the accumulated stirring time J of the anaerobic tank to reach an optimized value, changing the pressure of the anaerobic tank at the moment, dividing the pressure range of the anaerobic tank into 3 areas, namely a high-pressure early warning area, a normal working area and a low-pressure early warning area, wherein when the pressure of the anaerobic tank fluctuates in the normal working area, the process parameters do not need to be adjusted; when the pressure of the anaerobic tank is in a high-pressure early warning area or a low-pressure early warning area, the corresponding pressure reduction method or the corresponding pressure increase method is started immediately, namely, the process parameters are required to be adjusted.
4. A method of optimizing anaerobic digestion process parameters according to claim 3, wherein: the method for reducing the pressure of the anaerobic tank is that the stirrer of the anaerobic tank is completely closed or partially closed, or the gas production flow of the biogas purification product is increased, or a boiler is started until the pressure of the anaerobic tank is recovered to a normal working area; the method for improving the pressure of the anaerobic tank is to completely open or partially open the agitator of the anaerobic tank, or reduce the gas production flow of the biogas purification product, or close the boiler.
5. A method of optimizing anaerobic digestion process parameters according to claim 3, wherein: when the pressure of the anaerobic tank is in a high-pressure early warning area or a low-pressure early warning area, the pressure of the anaerobic tank is restored to a normal working area after being adjusted, but the temperature T of the anaerobic tank, the slurry quantity L of the anaerobic tank and the cumulative stirring time J of the anaerobic tank can possibly deviate from the current optimized value, when the current optimized value is deviated, multi-objective planning is carried out according to the current 5 process parameter values, namely the temperature T of the anaerobic tank, the pH value of the anaerobic tank, the slurry quantity L of the anaerobic tank, the solid content G of the slurry of the anaerobic tank and the cumulative stirring time J of the anaerobic tank according to the current 5 process parameter values, so that the optimized values of the temperature T of the anaerobic tank, the slurry quantity L of the anaerobic tank and the cumulative stirring time J of the anaerobic tank in a given time period can be obtained, then the temperature T of the anaerobic tank, the slurry quantity L of the anaerobic tank and the cumulative stirring time J of the anaerobic tank are adjusted according to the optimized values, thus the pressure of the anaerobic tank is changed, if the pressure of the anaerobic tank fluctuates in a normal working area, the technological parameters do not need to be adjusted; if the pressure of the anaerobic tank is in a high-pressure early warning area or a low-pressure early warning area, the corresponding pressure reduction method or the corresponding pressure increase method is started immediately, namely, the process parameters need to be adjusted, and the process is repeated in such a circulating way, so that the whole process parameter system is maintained in a dynamic balance.
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