Method and device for optimizing a waste pyrolysis system based on three-stream synergy

Abstract

This invention relates to the field of waste pyrolysis technology, and particularly to an optimization method and apparatus for a waste pyrolysis system based on three-flow synergy. The method includes: determining the information flow orderliness of the pyrolysis system based on information flow level indicators; determining the material flow orderliness of the pyrolysis system based on the information flow orderliness and the material flow level indicators; determining the energy flow orderliness of the pyrolysis system based on the material flow orderliness and the energy flow level indicators; determining the three-flow synergy degree based on the information flow orderliness, the material flow orderliness, and the energy flow orderliness; constructing an objective function for the economic benefits of the pyrolysis system, and solving the objective function using the three-flow synergy degree as a constraint to optimize the economic benefits of the pyrolysis system.

Description

Technical Field

[0001] This invention relates to the field of waste pyrolysis technology, and in particular to an optimization method and apparatus for a waste pyrolysis system based on three-stream synergy. Background Technology

[0002] like Figure 3 As shown, material flow, energy flow, and information flow are the three major components of a system, and they coordinate and cooperate with each other, forming an inseparable whole. Information flow, as a bridge between the system and the outside world, can regulate the distribution of material and energy flows; simultaneously, the results of material and energy flows can also serve as information indicators for the system, feeding back to society, nature, and the environment. Pyrolysis is one method of waste recycling and treatment, but due to its high energy consumption, large carbon emissions, and poor synergy among material, energy, and information flows, the economic benefits of pyrolysis systems are significantly affected by electricity prices.

[0003] Current research on pyrolysis systems largely focuses on the effects of material and energy flow, neglecting the role of information flow. Therefore, optimizing the economic efficiency of waste pyrolysis systems is a pressing issue that needs to be addressed. Summary of the Invention

[0004] This invention describes an optimization method and apparatus for a waste pyrolysis system based on three-stream 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] Based on information flow level indicators of the waste pyrolysis system, the orderliness of the information flow of the pyrolysis system is determined.

[0007] The material flow order of the pyrolysis system is determined based on the information flow order and the material flow level index of the pyrolysis system.

[0008] The energy flow order of the pyrolysis system is determined based on the material flow order and the energy flow level index of the pyrolysis system.

[0009] Based on the orderliness of the information flow, the orderliness of the material flow, and the orderliness of the energy flow, the degree of synergy among the three flows is determined;

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

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

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

[0013] The 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] The 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] The fourth determining unit is configured to determine the degree of coordination among the three flows based on the orderliness of the information flow, the orderliness of the material flow, and the orderliness of the energy flow.

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

[0017] Thirdly, embodiments of this specification also provide an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the method described in any embodiment of this specification.

[0018] Fourthly, embodiments of this specification also provide a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the methods described in any embodiment of this specification.

[0019] The optimization method and apparatus for a waste pyrolysis system based on the synergy of three flows provided by the present invention introduces a new index, the degree of synergy of the three flows, by linking the material flow, energy flow and information flow in the pyrolysis system. From the perspective of system synergy theory, it proposes a system optimization method with the highest comprehensive benefits of material flow, energy flow and information flow. That is, based on the guidance of information flow on material flow and energy flow, and with the synergistic relationship between material flow, energy flow and information flow as a constraint, it is used to solve the economic benefits of the pyrolysis system under different conditions. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1A flowchart illustrating an optimization method for a waste pyrolysis system based on three-flow synergy according to one embodiment is shown.

[0022] Figure 2 A schematic block diagram of an optimized apparatus for a waste pyrolysis system based on a three-flow synergy, according to one embodiment, is shown.

[0023] Figure 3 A schematic diagram illustrating the three-flow internal processes and external information exchange of a system according to one embodiment is shown;

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

[0025] Figure 5 A schematic diagram of the spatial field structure of matter flow, energy flow, and information flow in a system according to one embodiment is shown.

[0026] Figure 6 A schematic diagram illustrating the relationship between information flow, material flow, and energy flow according to one embodiment is shown. Detailed Implementation

[0027] The solution provided by the present invention will now be described with reference to the accompanying drawings.

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

[0029] Step 100: Determine the orderliness of the information flow in the waste pyrolysis system based on the information flow level indicators.

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

[0031] Step 104: 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;

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

[0033] Step 107: Construct an objective function for the economic benefits of the pyrolysis system, and solve the objective function with the three-flow synergy degree as a constraint 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 index of three-flow synergy is introduced. 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 between material flow, energy flow, and information flow as a constraint, it is used to solve the economic benefits of the pyrolysis system under different conditions.

[0035] The degree of matching among the material flow, energy flow, and information flow affects the dynamics and development of the pyrolysis system. This degree of matching can be represented by the synergy among the three flows, i.e., the three-flow synergy. As a comprehensive indicator, the three-flow synergy can provide a reference for the optimal design of the system.

[0036] In some implementations, photovoltaic (PV) modules are considered waste with high recycling value. To address the large-scale "retirement wave" of PV modules, their high-value recycling has become a research hotspot. Pyrolysis is one method of recycling, but due to its high energy consumption, large carbon emissions, and poor synergy between material flow, energy flow, and information flow, the economic benefits of pyrolysis systems are significantly affected by electricity prices. Coupled with a molten salt photothermal system, solar energy can replace some electrical energy, making the structure of material flow, energy flow, and information flow within the system more stable and reducing the impact of information flow (such as electricity prices) fluctuations on the system's economics, thereby achieving cost reduction and improved energy utilization. The following study will focus on an integrated pyrolysis system for EVA components in waste PV modules, as shown in the system diagram below. Figure 4 As shown, the changes in system economic benefits under the constraint of three-stream synergy are calculated when electricity prices fluctuate. Then, using economic indicators as feedback, the substitution ratio of the molten salt solar thermal system to achieve good economic benefits under high electricity prices is determined.

[0037] First, the evaluation indicators for material flow, energy flow, and information flow are determined (see Table 1). Specifically, the information flow 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 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; and the energy flow indicators include at least one of the following: unit product energy consumption, process energy efficiency, waste heat and energy utilization rate, etc. Efficiency and by-product energy recovery rate.

[0038] Table 1 Evaluation Indicators for Material Flow, Energy Flow, and Information Flow

[0039]

[0040] In one embodiment of the present invention, the orderliness of information flow, the orderliness of material flow, and the orderliness of energy flow are calculated using the following formulas:

[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 represents the orderliness of information flow, a represents the orderliness of material flow, b represents the orderliness of energy flow, and E represents the orderliness of energy flow. ca E is the influence coefficient of information flow on material flow. ab Let w be the coefficient of influence of material flow on energy flow, N be the total number of indices, and w be the coefficient of influence of material flow on energy flow. c,n w a,n and w b,n The weights for the information flow level indicators, material flow level indicators, and energy flow level indicators are listed in order (these weights can be obtained using traditional expert scoring methods, analytic hierarchy process, or entropy methods). m,n Indicators are categorized into information flow level indicators, material flow level indicators, and energy flow level indicators. These represent the maximum values ​​of the information flow level indicators, the maximum values ​​of the material flow level indicators, and the maximum values ​​of the energy flow level indicators. This refers to 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] Following the above embodiments, the calculation results of information flow orderliness, material flow orderliness, and energy flow orderliness can be found in Table 2.

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

[0048]

[0049] In one embodiment of the present invention, the degree of three-flow synergy is calculated using the following formula:

[0050]

[0051]

[0052] In the formula, S is the degree of synergy among the three flows, and I1, I2 and I3 are the direction cosines of the normal vector of the synergy plane ABC; where the degree of orderliness of information flow, material flow and energy flow are the intercepts of the synergy plane ABC on the xyz axis, respectively.

[0053] To better illustrate the degree of synergy among the flow of matter, energy, and information, the concept of a spatial geometric field is introduced, thus introducing a new indicator: the degree of synergy among the three flows. Figure 5 As shown, the intercepts of the cooperative plane on the x, y, and z axes are the orderliness of matter flow (a), energy flow (b), and information flow (c), respectively. The orderliness of information flow (c) can be expressed as... That is, the product of the information flow metric and its weight. For example... Figure 6 As shown, since information flow acts as a communication bridge between the outside world and the system, it can directly affect the distribution and effect of material flow. Therefore, the orderliness 'a' of material flow is jointly determined by the elements in the material flow subsystem and the information flow, i.e. Where E ca Let be the influence coefficient of information flow on material flow. Similarly, as energy is the carrier of matter, the degree of order 'b' of energy flow is determined jointly by the elements in the energy flow subsystem and the material flow, i.e. Where Eab is the influence coefficient of material flow on energy flow.

[0054] Regarding the determination of the influence coefficient E, the following uses the influence coefficient E of information flow on material flow as an example. ca Taking this as an example, we will provide a detailed explanation of the influence coefficient E of material flow on energy flow. ab And so on.

[0055] When the information flow has a good degree of order (c > 0.6), the information flow promotes the material flow, and the influence coefficient E ca >1; When the information flow has poor orderliness (c < 0.6), the information flow inhibits the material flow, and the influence coefficient E ca <1; When the orderliness of information flow is at the average level (c = 0.6), the effect of information flow on material flow is not significant, and the influence coefficient E ca =1. Similarly, when the information flow orderliness score is 0 (c=0), it indicates a severe lack of information guidance in the system, and the influence coefficient E ca =0. Secondly, the influence coefficient E ca The rate of change reflects the degree of influence of information flow on material flow. The closer the orderliness of information flow is to the average level (c is around 0.6), the less significant the influence of information flow, i.e., dE. ca / dc→0; The further the orderliness of the information flow deviates from the average level (c deviates from 0.6), the greater the impact of the information flow, i.e., dE. ca / dc increases with the distance between c and 0.6. The influence coefficient E of matter 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] Once the values ​​of the orderliness 'a' of the matter flow, the orderliness 'b' of the energy flow, and the orderliness 'c' of the information flow are determined, the equation of the cooperative plane ABC can be expressed as follows:

[0060]

[0061] Let n be the normal vector of the coplanar plane ABC, then the direction cosine of n is...

[0062]

[0063] We define cosα as the material flow responsivity I1. The larger cosα is, the smaller the space angle α is, and the more the plane is tilted towards the x-axis, indicating that the material flow component has a more significant impact on the system. Similarly, we define cosβ as the energy flow responsivity I2 and cosγ as the information flow responsivity I3.

[0064] When cosα, cosβ, and cosγ are equal, the synergistic plane tilts equally towards the x, y, and z axes, indicating that the influence of material flow, energy flow, and information flow on the system is balanced, and their synergy is at its best. The greater the dispersion of cosα, cosβ, and cosγ, the more unbalanced the influence of these three flows on the system, and the worse their synergy. Therefore, the reciprocal of the standard deviations of cosα, cosβ, and cosγ is defined as the synergy degree S of the system. As shown in the above formula, S is a variable related to the orderliness of the information flow, reflecting the guidance and control of the information flow on the pyrolysis system.

[0065] To find the optimal solution for a specific indicator in a pyrolysis system, a linear programming model can be used for system optimization. The formula for calculating the three-flow synergy degree S, as explained above, allows for the determination of a suitable range of values ​​for the synergy degree based on the specific requirements of the system, serving as a constraint on the linear programming model. Furthermore, the value ranges of various indicators within the system can also be used as constraints. The objective function, such as the pyrolysis system recovery rate or recovery cost, is the object of study. Once the expression for the objective function regarding each indicator is determined, the values ​​(ranges) of each indicator when the objective function reaches its maximum (minimum) value can be calculated.

[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] In the formula, 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 For silver recovery rate, e 1,2 For silicon recovery rate, e 1,3 For glass recycling rate, e 1,5 e represents the by-product yield. 2,1 e represents the energy consumption per unit of product. 3,5 To ensure the reasonableness of 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] In addition, taking into account the fluctuations and distribution of electricity prices in Hubei Province and the range of values ​​for each indicator, Tables 3 and 4 below calculate the energy consumption, product, three-stream synergy, and economic efficiency 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. Coordination of the three flows in the EVA pyrolysis system at different electricity prices

[0076]

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

[0078]

[0079]

[0080] The calculation results above show that: 1) the revenue of the EVA pyrolysis integrated system is directly proportional to the synergy of the three flows in the system; 2) the direction to improve the synergy of the three flows in the system is to improve the orderliness of the material flow and the orderliness of the energy flow; 3) as the electricity price decreases, 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's power consumption decreases and the system revenue decreases significantly.

[0081] Since the system revenue is negative under high electricity prices, the substitution ratio of the molten salt solar thermal system is calculated by substituting the positive revenue value into the objective function, as shown in Table 6 below.

[0082] Table 6. Substitution ratio of molten salt solar thermal systems under high electricity prices.

[0083]

[0084] In summary, when the electricity price is ≤0.45 kWh / yuan, the electricity cost is low, and the pyrolysis system can guarantee its profitability without the need for a molten salt solar thermal system. To further improve the system's profitability at this point, efforts should be made from the material flow perspective, such as improving product quality and upgrading technologies to increase the yield of pyrolysis oil and precious metals, and optimizing combustion conditions to increase the yield of recycled flue gas. This will increase the synergy among the three flows (material flow, liquid flow, and gas flow) and thus achieve higher profitability.

[0085] When the electricity price exceeds 0.45 kWh / yuan, due to cost constraints, a pyrolysis system alone cannot achieve high returns. Therefore, it is necessary to fully leverage the advantages of molten salt solar thermal systems and utilize solar energy to compensate for the lack of energy flow. The specific substitution ratio can be calculated based on the relationship between expected returns and energy flow, material flow, and information flow. Simultaneously, the efficiency of molten salt solar thermal systems should be improved by selecting high-performance storage tank materials to optimize the energy storage system design and exploring suitable heat storage media.

[0086] As demonstrated by the above calculation examples, the optimization method for pyrolysis systems based on the synergy of material flow, energy flow, and information flow can analyze the system's energy consumption and economic efficiency while fully considering the synergy and matching of these three flows. Furthermore, it can quantitatively represent the specific values ​​of each indicator, highlighting the regulatory role of information flow on the system and achieving targeted optimization. Compared to traditional optimization methods, this method proposes an optimization approach from the perspective of the synergistic theory of the three flows, making it more suitable for the operation and development of the system.

[0087] The foregoing has described specific embodiments of the invention. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

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

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

[0090] The 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] The 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] The fourth determining unit is configured to determine the degree of coordination among the three flows based on the orderliness of the information flow, the orderliness of the material flow, and the orderliness of the energy flow.

[0093] A solution unit is constructed and configured to construct an objective function for the economic benefits of the pyrolysis system, and solve the objective function with the three-flow synergy degree as a constraint 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 embodiment, 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 embodiment, 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 and by-product energy recovery rate.

[0097] In a preferred embodiment, the orderliness of the information flow, the orderliness of the material flow, and the orderliness of the energy flow are calculated using the following formulas:

[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 represents the orderliness of the information flow, a represents the orderliness of the material flow, b represents the orderliness of the energy flow, and E ca E is the influence coefficient of information flow on material flow. ab Let W be the coefficient of influence of material flow on energy flow, where N is the total number of indices. c,n w a,n and w b,n The weights corresponding to the information flow level indicators, the material flow level indicators, and the energy flow level indicators are, in order, e. m,n These are the information flow level indicators, the material flow level indicators, and the energy flow level indicators. These are the maximum values ​​of the information flow level indicators, the maximum values ​​of the material flow level indicators, and the maximum values ​​of 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] In a preferred embodiment, the three-flow synergy degree is calculated using the following formula:

[0104]

[0105]

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

[0107] In a preferred embodiment, 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] In the formula, 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 For silver recovery rate, e 1,2 For silicon recovery rate, e 1,3 For glass recycling rate, e 1,5 e represents the by-product yield. 2,1 e represents the energy consumption per unit of product. 3,5 To ensure the reasonableness of 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, a computer-readable storage medium is also provided, on which a computer program is stored, which, when executed in a computer, causes the computer to perform a combination Figure 1 The method described.

[0116] According to another embodiment, an electronic device is also provided, including a memory and a processor, wherein the memory stores executable code, and when the processor executes the executable code, it implements a combination... Figure 1 The method described.

[0117] The various embodiments in this invention are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

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

[0119] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment 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 within 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: Based on information flow level indicators of the waste pyrolysis system, the orderliness of the information flow of the pyrolysis system is determined. The material flow order of the pyrolysis system is determined based on the information flow order and the material flow level index of the pyrolysis system. The energy flow order of the pyrolysis system is determined based on the material flow order and the energy flow level index of the pyrolysis system. Based on the orderliness of the information flow, the orderliness of the material flow, and the orderliness of the energy flow, the degree of synergy among the three flows is determined; Construct an objective function for the economic benefits of the pyrolysis system, and solve the objective function using the three-flow synergy degree as a constraint. When the waste is photovoltaic modules, the pyrolysis system of the photovoltaic modules is coupled with the molten salt photothermal system. By calculating the changes in the economic benefits of the system when the electricity price fluctuates under the constraint of the three-flow synergy, the economic indicators are used as feedback to solve the substitution ratio of the molten salt photothermal system when the electricity price is >0.45 kWh / yuan. The substitution ratio is converted according to the expected benefits and the relationship between energy flow, material flow and information flow. 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 rate; The orderliness of the information flow, the orderliness of the material flow, and the orderliness of the energy flow are calculated using the following formulas: AND ca =4.6296(c-0.6) 3 +1 AND ab =4.6296(a-0.6) 3 +1 In the formula, c represents the orderliness of the information flow, a represents the orderliness of the material flow, b represents the orderliness of the energy flow, and E ca E is the influence coefficient of information flow on material flow. ab Let w be the coefficient of influence of material flow on energy flow, N be the total number of indices, and w be the coefficient of influence of material flow on energy flow. c,n w a,n and w b,n The weights corresponding to the information flow level indicators, the material flow level indicators, and the energy flow level indicators are, in order, e. m,n These are the information flow level indicators, the material flow level indicators, and the energy flow level indicators. These are the maximum values ​​of the information flow level indicators, the maximum values ​​of the material flow level indicators, and the maximum values ​​of the energy flow level indicators. These are the minimum values ​​of the information flow level indicators, the minimum values ​​of the material flow level indicators, and the minimum values ​​of the energy flow level indicators. The degree of synergy among the three flows is calculated using the following formula: In the formula, S is the degree of synergy among the three flows, and I1, I2 and I3 are the direction cosines of the normal vectors of the synergy plane ABC; wherein, the degree of orderliness of the information flow, the degree of orderliness of the material flow and the degree of orderliness of the energy flow are the intercepts of the synergy plane ABC on the xyz axis, respectively. The objective function is: Z=p1e 1,1 -p2e 1,2 -p3e 1,3 -p4e 1,5 -And 2,1 ·And 3,5 In the formula, 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 For silver recovery rate, e 1,2 For silicon recovery rate, e 1,3 For glass recycling rate, e 1,5 e represents the by-product yield. 2,1 e represents the energy consumption per unit of product. 3,5 To ensure the rationality of 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。 2. An optimized device for a waste pyrolysis system based on three-stream synergy, characterized in that, The method applied to claim 1 includes: The first determining unit is configured to determine the orderliness of the information flow of the waste pyrolysis system based on information flow level indicators of the waste pyrolysis system. The 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. The 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. The fourth determining unit is configured to determine the degree of coordination among the three flows based on the orderliness of the information flow, the orderliness of the material flow, and the orderliness of the energy flow. A solution unit is constructed and configured to construct an objective function for the economic benefits of the pyrolysis system, and solve the objective function using the three-flow synergy degree as a constraint.

3. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method as described in claim 1.

4. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed in a computer, causes the computer to perform the method of claim 1.

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