Method and device for optimizing waste pyrolysis system based on three-flow collaboration

Abstract

The invention relates to the technical field of waste pyrolysis, in particular to an optimization method and device of a waste pyrolysis system based on three-flow collaboration. The method comprises the following steps: determining an information flow order degree of a pyrolysis system based on an information flow level index of the waste pyrolysis system; determining the material flow order degree of the pyrolysis system based on the information flow order degree and the material flow level index of the pyrolysis system; based on the material flow order degree and an energy flow level index of the pyrolysis system, determining the energy flow order degree of the pyrolysis system; based on the information flow order degree, the material flow order degree and the energy flow order degree, determining a three-flow cooperation degree; and constructing an objective function aiming at the economic benefits of the pyrolysis system, and solving the objective function by taking the three-flow collaboration degree as a constraint condition to optimize the economic benefits of the pyrolysis system.

Description

Technical Field

[0001] The present invention relates to the technical field of waste pyrolysis, and in particular to an optimization method and device for a waste pyrolysis system based on three-flow synergy. Background Art

[0002] like Figure 3 As shown in the figure, material flow, energy flow and information flow are the three major factors of the system, and they coordinate and cooperate with each other in the system and are inseparable. As a bridge for the system to communicate with the outside world, information flow can regulate the distribution of material flow and energy flow; at the same time, the results of material flow and energy flow can also be used as information indicators of the system to feedback to society, nature and the environment. Pyrolysis is one of the methods for recycling waste, but due to the high energy consumption and large carbon emissions of the pyrolysis process, the synergistic effect between material flow, energy flow and information flow is poor, and the economic benefits of the pyrolysis system are significantly affected by electricity prices.

[0003] At present, most of the research on pyrolysis systems only focuses on the influence of material flow and energy flow, while ignoring the role of information flow in pyrolysis systems. Therefore, how to optimize the economic benefits of waste pyrolysis systems is an urgent problem to be solved. Summary of the invention

[0004] The present invention describes an optimization method and device for a waste pyrolysis system based on three-flow synergy, which can optimize the economic benefits of the waste pyrolysis system.

[0005] According to a first aspect, the present invention provides an optimization method for a waste pyrolysis system based on three-stream synergy, comprising:

[0006] Determining the orderliness of information flow of the waste pyrolysis system based on information flow level indicators of the waste pyrolysis system;

[0007] Determining the material flow order of the pyrolysis system based on the information flow order and the material flow level index of the pyrolysis system;

[0008] Determining the energy flow order of the pyrolysis system based on the material flow order and the energy flow level index of the pyrolysis system;

[0009] Determining the three-flow coordination degree based on the information flow order degree, the material flow order degree and the energy flow order degree;

[0010] An objective function for the economic benefit of the pyrolysis system is constructed, and the three-flow synergy is used as a constraint condition to solve the objective function to optimize the economic benefit of the pyrolysis system.

[0011] According to a second aspect, the present invention provides an optimization device for a waste pyrolysis system based on three-flow synergy, comprising:

[0012] A first determining unit is configured to determine the orderliness of information flow of the waste pyrolysis system based on information flow level indicators of the waste pyrolysis system;

[0013] A second determining unit is configured to determine the material flow order of the pyrolysis system based on the information flow order and the material flow level index of the pyrolysis system;

[0014] A third determining unit is configured to determine the energy flow order of the pyrolysis system based on the material flow order and the energy flow level index of the pyrolysis system;

[0015] a fourth determining unit, configured to determine a three-flow coordination degree based on the information flow order degree, the material flow order degree and the energy flow order degree;

[0016] A solution unit is constructed, which is configured to construct an objective function for the economic benefits of the pyrolysis system, and solve the objective function with the three-flow synergy as a constraint condition to optimize the economic benefits of the pyrolysis system.

[0017] In a third aspect, an embodiment of this specification further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method described in any embodiment of this specification is implemented.

[0018] In a fourth aspect, an embodiment of the present specification further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed in a computer, the computer is caused to execute the method described in any embodiment of the present specification.

[0019] According to the optimization method and device of the waste pyrolysis system based on three-flow synergy provided by the present invention, by linking the material flow, energy flow and information flow in the pyrolysis system, a new indicator of three-flow synergy is introduced, and from the perspective of system synergy theory, a system optimization method with the highest comprehensive benefits of material flow, energy flow and information flow is proposed, that is, based on the guidance of information flow on material flow and energy flow, with the synergistic relationship among material flow, energy flow and information flow as a constraint condition, it is used to solve the economic benefits of the pyrolysis system under different conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1A schematic flow chart of an optimization method for a waste pyrolysis system based on three-stream synergy according to an embodiment is shown;

[0022] Figure 2 A schematic block diagram of an optimization device for a waste pyrolysis system based on three-stream synergy according to an embodiment is shown;

[0023] Figure 3 A schematic diagram showing three-flow flow inside a system and external information exchange according to an embodiment;

[0024] Figure 4 A schematic diagram of a waste photovoltaic assembly pyrolysis system coupled with molten salt photothermal heat according to an embodiment is shown;

[0025] Figure 5 A schematic diagram showing the spatial field structure of material flow, energy flow, and information flow in a system according to an embodiment;

[0026] Figure 6 A schematic diagram showing the relationship among information flow, material flow and energy flow according to an embodiment is shown. DETAILED DESCRIPTION

[0027] The solution provided by the present invention is described below in conjunction with the accompanying drawings.

[0028] Figure 1 A schematic diagram of a process flow of an optimization method for a waste pyrolysis system based on three-stream synergy according to an embodiment is shown. It can be understood that the method can be executed by any device, equipment, platform, or equipment cluster with computing and processing capabilities. Figure 1 As shown, the method includes:

[0029] Step 100: determining the orderliness of information flow of the pyrolysis system based on information flow level indicators of the waste pyrolysis system;

[0030] Step 102: determining the material flow order of the pyrolysis system based on the information flow order and the material flow level index of the pyrolysis system;

[0031] Step 104: determining the energy flow order of the pyrolysis system based on the material flow order and the energy flow level index of the pyrolysis system;

[0032] Step 106: Determine the coordination degree of the three flows based on the order degree of the information flow, the order degree of the material flow and the order degree of the energy flow;

[0033] Step 107: construct an objective function for the economic benefits of the pyrolysis system, and use the three-flow synergy as a constraint to solve the objective function to optimize the economic benefits of the pyrolysis system.

[0034] In this embodiment, by linking the material flow, energy flow and information flow in the pyrolysis system, a new indicator of three-flow synergy is introduced, and from the perspective of system synergy theory, a system optimization method with the highest comprehensive benefits of material flow, energy flow and information flow is proposed. That is, based on the guidance of information flow on material flow and energy flow, and with the synergistic relationship among material flow, energy flow and information flow as a constraint condition, it is used to solve the economic benefits of the pyrolysis system under different conditions.

[0035] Among them, the matching degree among material flow, energy flow and information flow affects the dynamics and development of the pyrolysis system. This matching degree can be expressed by the coordination degree among material flow, energy flow and information flow, namely the three-flow coordination degree. As a comprehensive indicator, the three-flow coordination degree can provide a reference for the optimal design of the system.

[0036] In some embodiments, photovoltaic modules are a type of waste with a high recycling value. In response to the large-scale "retirement wave" of photovoltaic modules, the high-value recycling of photovoltaic modules has become a research hotspot. Among them, pyrolysis is one of the recycling methods, but due to the high energy consumption and large carbon emissions of the pyrolysis process, the synergy between material flow, energy flow, and information flow is poor, and the economic benefits of the pyrolysis system are significantly affected by electricity prices. If the photovoltaic module pyrolysis treatment system is coupled with a molten salt thermal system, solar energy can be used to replace part of the electrical energy, which can not only make the material flow, energy flow, and information flow structure in the system more stable, but also reduce the impact of information flow (such as electricity prices) fluctuations on the system economy, thereby achieving the effect of reducing costs and improving energy utilization. The following will take the pyrolysis integrated system of EVA components in discarded photovoltaic modules as the research object. The system diagram is shown in the figure below. Figure 4 As shown in the figure. Under the constraints of the three-flow synergy, the changes in the economic benefits of the system when the electricity price fluctuates are calculated. Then, the economic indicators are used as feedback to solve the replacement ratio of the molten salt solar thermal system to achieve good economic benefits when the electricity price is high.

[0037] First, determine the evaluation indicators of material flow, energy flow, and information flow (see Table 1), that is, the information flow level indicators include at least one of the following: environmental policy responsiveness, staff professionalism, equipment effectiveness, plant design rationality, and resource price rationality; the material flow level indicators include at least one of the following: silver recovery rate, silicon recovery rate, glass recovery rate, waste recycling rate, and by-product output rate; the energy flow level indicators include at least one of the following: unit product energy consumption, process energy efficiency, waste heat and waste energy utilization rate, Efficiency, by-product energy recovery.

[0038] Table 1 Evaluation indicators of material flow, energy flow and information flow

[0039]

[0040] In one embodiment of the present invention, the information flow order, material flow order and energy flow order are calculated by the following formula:

[0041]

[0042] E ca =4.6296(c-0.6) 3 +1

[0043] E ab =4.6296(a-0.6) 3 +1

[0044]

[0045] In the formula, c is the order of information flow, a is the order of material flow, b is the order of energy flow, E ca is the influence coefficient of information flow on material flow, E ab is the influence coefficient of material flow on energy flow, N is the total number of indicators, w c,n 、w a,n and w b,n The weights of the indicators at the information flow level, material flow level, and energy flow level are respectively (which can be obtained by using the traditional expert scoring method, hierarchical analysis method, or entropy value method), e m,n These are indicators at the information flow level, material flow level, and energy flow level. is the maximum value among the indicators at the information flow level, the maximum value among the indicators at the material flow level, and the maximum value among the indicators at the energy flow level. It is the minimum value among the indicators at the information flow level, the minimum value among the indicators at the material flow level, and the minimum value among the indicators at the energy flow level.

[0046] Continuing with the above embodiment, the calculation results of the information flow order, material flow order and energy flow order can be found in Table 2.

[0047] Table 2 Indicators, weights and order of material flow, energy flow and information flow

[0048]

[0049] In one embodiment of the present invention, the three-stream coordination degree is calculated by the following formula:

[0050]

[0051]

[0052] Where S is the three-flow coordination degree, I1, I2 and I3 are the direction cosines of the normal vector of the coordination plane ABC; among them, the order of information flow, the order of material flow and the order of energy flow are the intercepts of the coordination plane ABC on the xyz axis respectively.

[0053] In order to better demonstrate the degree of coordination among the three flows of material flow, energy flow and information flow, the concept of spatial geometric field is introduced, that is, a new indicator of the three-flow coordination degree is introduced, such as Figure 5 As shown, the intercepts of the synergy plane on the x, y, and z axes are the material flow order a, energy flow order b, and information flow order c, respectively. The information flow order c can be expressed as That is, the product of the information flow index and the weight. Figure 6 As shown in the figure, since information flow, as a bridge between the outside world and the system, can directly affect the distribution and effect of material flow, the order degree a of material flow is determined by the elements in the material flow subsystem and the information flow, that is, Where E ca is the influence coefficient of information flow on material flow. Similarly, energy is the carrier of matter, and the order of energy flow b is determined by the elements in the energy flow subsystem and the material flow, that is, Where Eab is the influence coefficient of material flow on energy flow.

[0054] Regarding the determination of the influence coefficient E, the following is the influence coefficient E of information flow on material flow ca Take the example to introduce in detail the influence coefficient E of material flow on energy flow. ab And so on.

[0055] When the order of information flow is good (c>0.6), information flow promotes material flow, and the influence coefficient E ca >1; when the order of information flow is poor (c < 0.6), information flow has an inhibitory effect on material flow, and the influence coefficient E ca <1; when the order of information flow is at the average level (c = 0.6), the effect of information flow on material flow is not obvious, and the influence coefficient E ca =1. Similarly, when the information flow order score is 0 (c=0), it means that there is a serious lack of information guidance in the system, and the impact coefficient E ca = 0. Secondly, the influence coefficient E ca The rate of change of can reflect the influence of information flow on material flow. The closer the order of information flow is to the average level (c is around 0.6), the less obvious the influence of information flow is. ca / dc→0; the further the order of information flow is from the average level (c is further from 0.6), the greater the impact of information flow, that is, dE ca / dc increases with the distance between c and 0.6. The influence coefficient E of material flow on energy flow abThe derivation process is similar and will not be elaborated here.

[0056] In summary, the following function is selected to represent the influence coefficient E of information flow on material flow: ca , the influence coefficient E of material flow on energy flow ab .

[0057] E ca =4.6296(c-0.6) 3 +1

[0058] E ab =4.6296(a-0.6) 3 +1

[0059] After determining the values ​​of the material flow order a, energy flow order b, and information flow order c, the equation of the synergy plane ABC can be expressed as

[0060]

[0061] is the normal vector of the coplanar ABC, then the direction cosine of n is

[0062]

[0063] Define cosα as the material flow responsiveness I1. The larger the cosα, the smaller the spatial angle α and the more the plane is inclined toward the x-axis, which means that the material flow component has a more significant impact on the system. Similarly, define cosβ as the energy flow responsiveness I2 and cosγ as the information flow responsiveness I3.

[0064] When cosα, cosβ, and cosγ are equal, the inclination of the synergy plane to the x, y, and z axes is the same, indicating that the influence of material flow, energy flow, and information flow on the system is balanced, and the synergy of the three is the best; when the degree of dispersion of cosα, cosβ, and cosγ is greater, it means that the influence of material flow, energy flow, and information flow on the system is more unbalanced, and the synergy of the three is worse. Therefore, the reciprocal of the standard deviation of cosα, cosβ, and cosγ is defined as the synergy S of the system. From the above calculation formula, it can be seen that S is a variable related to the order of information flow, which reflects the guidance and regulation of information flow on the pyrolysis system.

[0065] In order to solve the optimal solution of a certain indicator in the pyrolysis system in a targeted manner, a linear programming model can be selected to optimize the design of the pyrolysis system. The above description clarifies the calculation formula of the three-flow synergy degree S, which can be used to determine the optimal value range of the synergy degree according to the specific requirements of the system, and use this as a constraint condition for the linear programming model. In addition, the value range of each indicator in the system can also be used as a constraint condition. The objective function is the research object, such as the recovery rate and recovery cost of the pyrolysis system. After determining the expression of the objective function for each indicator, the value (range) of each indicator can be solved when the objective function takes the maximum (minimum) value.

[0066] In one embodiment of the present invention, the objective function is:

[0067] Z=p1e 1,1 -p2e 1,2 -p3e 1,3 -p4e 1,5 -e 2,1 ·e 3,5

[0068] Where Z is the objective function, p1 is the price of silver, p2 is the price of silicon, p3 is the price of glass, p4 is the price of by-products, and e 1,1 is the silver recovery rate, e 1,2 is the silicon recovery rate, e 1,3 is the glass recycling rate, e 1,5 is the by-product yield, e 2,1 is the energy consumption per unit product, e 3,5 Reasonable resource prices;

[0069] The constraints include:

[0070] 0.9≤e 1,1 <1.0

[0071] 0.8≤e 1,2 <1.0

[0072] 0.9≤e 1,3 <1.0

[0073] S≥10.

[0074] Among them, combined with the fluctuation and distribution of electricity prices in Hubei Province, the value range of various indicators, etc., the following Tables 3 and 4 calculate the energy consumption, products, three-flow coordination and economy of the EVA (i.e. photovoltaic module) pyrolysis system when the electricity price is 0.3, 0.45, 0.65 and 0.98 yuan / kWh.

[0075] Table 4 Three-flow coordination degree of EVA pyrolysis system at different electricity prices

[0076]

[0077] Table 5 Total revenue of EVA pyrolysis system at different electricity prices

[0078]

[0079]

[0080] From the above calculation results, we can see that 1) the income of the EVA pyrolysis integrated system is proportional to the coordination degree of the three flows of the system; 2) the direction of improving the coordination degree of the three flows of the system is to improve the order of material flow and energy flow; 3) with the decrease of electricity price, the energy consumption and products of the EVA pyrolysis integrated system gradually increase, and then tend to stabilize; 4) when the electricity price is high, the system power consumption decreases, and the system income decreases significantly.

[0081] Since the system revenue is negative when the electricity price is high, the positive revenue value is brought into the objective function to calculate the replacement ratio of the molten salt solar thermal system as shown in Table 6 below:

[0082] Table 6 Replacement ratio of molten salt solar thermal system under high electricity price

[0083]

[0084] In summary, when the electricity price is ≤0.45 kWh / yuan, the electricity cost is low, and the pyrolysis system can guarantee the system's profit without the use of the molten salt solar thermal system. If the system's profit is to be further improved at this time, it should be based on the material flow, such as improving product quality and quality improvement technology to increase the pyrolysis oil yield and precious metal yield, optimizing combustion conditions to increase the yield of recycled hot flue gas, so that the three-flow synergy is increased, thereby achieving higher profits.

[0085] When the electricity price is greater than 0.45 kWh / yuan, due to cost constraints, the pyrolysis system alone cannot achieve the goal of high returns. It is necessary to give full play to the advantages of the molten salt thermal system and use solar energy to make up for the lack of energy flow. The specific replacement ratio can be converted according to the relationship between the expected benefits and the energy flow, material flow, and information flow. At the same time, the efficiency of the molten salt thermal system should be improved by selecting storage tank materials with better performance to optimize the design of the energy storage system and explore suitable heat storage media.

[0086] From the above calculation cases, we can know that the optimization method of pyrolysis system based on the coordination of material flow, energy flow and information flow can analyze the energy consumption, economy and other factors of the system while fully considering the coordination and matching of material flow, energy flow and information flow; and can quantitatively express the specific values ​​of various indicators, highlighting the regulatory role of information flow on the system, and achieving the purpose of directional optimization. Compared with traditional optimization methods, this method proposes an optimization method from the perspective of the three-flow coordination theory of the system, which is more suitable for the operation and development of the system.

[0087] The above describes specific embodiments of the present invention. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0088] According to an embodiment of another aspect, the present invention provides an optimization device for a waste pyrolysis system based on three-stream synergy. Figure 2 A schematic block diagram of an optimization device for a waste pyrolysis system based on three-stream synergy according to an embodiment is shown. It can be understood that the device can be implemented by any device, equipment, platform and equipment cluster with computing and processing capabilities. Figure 2 As shown, the device includes: a first determination unit 200, a second determination unit 202, a third determination unit 204, a fourth determination unit 206 and a construction and solution unit 208. The main functions of each component unit are as follows:

[0089] A first determining unit is configured to determine the orderliness of information flow of the waste pyrolysis system based on information flow level indicators of the waste pyrolysis system;

[0090] A second determining unit is configured to determine the material flow order of the pyrolysis system based on the information flow order and the material flow level index of the pyrolysis system;

[0091] A third determining unit is configured to determine the energy flow order of the pyrolysis system based on the material flow order and the energy flow level index of the pyrolysis system;

[0092] a fourth determining unit, configured to determine a three-flow coordination degree based on the information flow order degree, the material flow order degree and the energy flow order degree;

[0093] A solution unit is constructed, which is configured to construct an objective function for the economic benefits of the pyrolysis system, and solve the objective function with the three-flow synergy as a constraint condition to optimize the economic benefits of the pyrolysis system.

[0094] As a preferred implementation, the information flow level indicators include at least one of the following: environmental policy responsiveness, staff professionalism, equipment effectiveness, plant design rationality and resource price rationality.

[0095] As a preferred implementation, the material flow level indicators include at least one of the following: silver recovery rate, silicon recovery rate, glass recovery rate, waste recycling rate and by-product output rate.

[0096] As a preferred implementation, the energy flow level indicators include at least one of the following: unit product energy consumption, process energy efficiency, waste heat and waste energy utilization rate, Efficiency, by-product energy recovery.

[0097] As a preferred implementation, the information flow order, the material flow order and the energy flow order are calculated by the following formula:

[0098]

[0099] E ca =4.6296(c-0.6) 3 +1

[0100] E ab =4.6296(a-0.6) 3 +1

[0101]

[0102] In the formula, c is the order of the information flow, a is the order of the material flow, b is the order of the energy flow, E ca is the influence coefficient of information flow on material flow, E ab is the influence coefficient of material flow on energy flow, N is the total number of indicators, W c,n 、w a,n and w b,n are the weights corresponding to the information flow level indicator, the material flow level indicator and the energy flow level indicator, respectively, e m,n are the information flow level indicators, the material flow level indicators and the energy flow level indicators, is the maximum value among the information flow level indicators, the maximum value among the material flow level indicators, and the maximum value among the energy flow level indicators, It is the minimum value among the information flow level indicators, the minimum value among the material flow level indicators, and the minimum value among the energy flow level indicators.

[0103] As a preferred implementation, the three-stream coordination degree is calculated by the following formula:

[0104]

[0105]

[0106] In the formula, S is the three-flow coordination degree, I1, I2 and I3 are the direction cosines of the normal vector of the coordination plane ABC; wherein the information flow order, the material flow order and the energy flow order are the intercepts of the coordination plane ABC on the xyz axis respectively.

[0107] As a preferred implementation, the objective function is:

[0108] Z=p1e 1,1 -p2e 1,2 -p3e 1,3 -p4e 1,5 -e 2,1 ·e 3,5

[0109] Where Z is the objective function, p1 is the price of silver, p2 is the price of silicon, p3 is the price of glass, p4 is the price of by-products, and e 1,1 is the silver recovery rate, e 1,2 is the silicon recovery rate, e 1,3 is the glass recycling rate, e 1,5 is the by-product yield, e 2,1 is the energy consumption per unit product, e 3,5 Reasonable resource prices;

[0110] The constraints include:

[0111] 0.9≤e 1,1 <1.0

[0112] 0.8≤e 1,2 <1.0

[0113] 0.9≤e 1,3 <1.0

[0114] S≥10.

[0115] According to another embodiment, there is also provided a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to execute a combination of Figure 1 The method described.

[0116] According to another embodiment of the present invention, there is also provided an electronic device, comprising a memory and a processor, wherein the memory stores an executable code, and when the processor executes the executable code, the Figure 1 The method described.

[0117] The various embodiments of the present invention are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0118] Those skilled in the art should be aware that in one or more of the above examples, the functions described in the present invention can be implemented by hardware, software, firmware or any combination thereof. When implemented by software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium.

[0119] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solution of the present invention should be included in the scope of protection of the present invention.

Claims

1. An optimization method for a waste pyrolysis system based on three-stream synergy, characterized in that: include: Determining the orderliness of information flow of the waste pyrolysis system based on information flow level indicators of the waste pyrolysis system; Determining the material flow order of the pyrolysis system based on the information flow order and the material flow level index of the pyrolysis system; Determining the energy flow order of the pyrolysis system based on the material flow order and the energy flow level index of the pyrolysis system; Determining the three-flow coordination degree based on the information flow order degree, the material flow order degree and the energy flow order degree; An objective function for the economic benefit of the pyrolysis system is constructed, and the three-flow synergy is used as a constraint condition to solve the objective function to optimize the economic benefit of the pyrolysis system.

2. The method according to claim 1, characterized in that The information flow level indicators include at least one of the following: environmental policy responsiveness, staff professionalism, equipment effectiveness, plant design rationality and resource price rationality.

3. The method according to claim 1, characterized in that: The material flow level indicators include at least one of the following: silver recovery rate, silicon recovery rate, glass recovery rate, waste recycling rate and by-product output rate.

4. The method according to claim 1, characterized in that The energy flow level indicators include at least one of the following: unit product energy consumption, process energy efficiency, waste heat and waste energy utilization rate, Efficiency, by-product energy recovery.

5. The method according to any one of claims 1 to 4, characterized in that The information flow order, the material flow order and the energy flow order are calculated by the following formula: AND ca =4.6296(c-0.6) 3 +1 AND ab =4.6296(a-0.6) 3 +1 m takes a,b,c In the formula, c is the order of the information flow, a is the order of the material flow, b is the order of the energy flow, E ca is the influence coefficient of information flow on material flow, E ab is the influence coefficient of material flow on energy flow, N is the total number of indicators, w c,n 、w a,n and w b,n are the weights corresponding to the information flow level indicator, the material flow level indicator and the energy flow level indicator, respectively, e m,n are the information flow level indicators, the material flow level indicators and the energy flow level indicators, is the maximum value among the information flow level indicators, the maximum value among the material flow level indicators, and the maximum value among the energy flow level indicators, It is the minimum value among the information flow level indicators, the minimum value among the material flow level indicators, and the minimum value among the energy flow level indicators.

6. The method according to claim 5, characterized in that The three-stream coordination degree is calculated by the following formula: In the formula, S is the three-flow coordination degree, I1, I2 and I3 are the direction cosines of the normal vector of the coordination plane ABC; wherein the information flow order, the material flow order and the energy flow order are the intercepts of the coordination plane ABC on the xyz axis respectively.

7. The method according to claim 6, characterized in that The objective function is: Z=p1e 1,1 -p2e 1,2 -p3e 1,3 -p4e 1,5 -And 2,1 ·And 3,5 Where Z is the objective function, p1 is the price of silver, p2 is the price of silicon, p3 is the price of glass, p4 is the price of by-products, and e 1,1 is the silver recovery rate, e 1,2 is the silicon recovery rate, e 1,3 is the glass recycling rate, e 1,5 is the by-product yield, e 2,1 is the energy consumption per unit product, e 3,5 Reasonable resource prices; The constraints include: 0.9≤e 1,1 <1.0 0.8≤e 1,2 <1.0 0.9≤e 1,3 <1.0 S≥10。 8. An optimization device for a waste pyrolysis system based on three-stream synergy, characterized in that: include: A first determining unit is configured to determine the orderliness of information flow of the waste pyrolysis system based on information flow level indicators of the waste pyrolysis system; A second determining unit is configured to determine the material flow order of the pyrolysis system based on the information flow order and the material flow level index of the pyrolysis system; A third determining unit is configured to determine the energy flow order of the pyrolysis system based on the material flow order and the energy flow level index of the pyrolysis system; a fourth determining unit, configured to determine a three-flow coordination degree based on the information flow order degree, the material flow order degree and the energy flow order degree; A solution unit is constructed, which is configured to construct an objective function for the economic benefits of the pyrolysis system, and solve the objective function with the three-flow synergy as a constraint condition to optimize the economic benefits of the pyrolysis system.

9. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed in a computer, the computer is caused to execute the method according to any one of claims 1 to 7.

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