A decision-making method for site selection of photovoltaic waste recycling facilities based on actual road network

Abstract

The present invention relates to a decision-making method for the site selection of photovoltaic waste recycling facilities based on an actual road network, and belongs to the field of management science and technology. The method first uses a dynamic Weibull probability distribution function to model and evaluate the photovoltaic scrap volume, obtains the spatiotemporal distribution of the photovoltaic scrap volume, and obtains the location and scale of the photovoltaic scrap point; then, considering environmental constraints such as farmland, woodland, Gobi desert, water area, and ecological protection area, the grid points suitable for the construction of a recycling plant are screened out in the obtained scrap volume distribution layer, that is, as potential processing center site selection points. The present invention reasonably considers multiple influencing factors, which is more conducive to determining the optimal site selection of the target facility.

Description

Technical Field

[0001] The invention relates to a decision-making method for site selection of photovoltaic waste recycling facilities based on an actual road network, and belongs to the field of management science and technology. Background Art

[0002] The development of photovoltaics is to promote energy transformation.

[0003] As an emerging solid waste, promoting the green disposal and recycling of retired photovoltaic modules is a key task in the future. However, the recycling of retired photovoltaic modules is currently in its early stages, with disposal mainly taking the form of open-air stacking and landfill, and most of them flow to small workshops for informal recycling. The industry's enthusiasm is not high, resulting in a low level of module recycling. The management level of module recycling needs to be improved urgently.

[0004] The site selection problem of the photovoltaic waste reverse logistics network is one of the key issues in photovoltaic waste management. The recycling of photovoltaic modules involves multi-dimensional factors such as resource recovery potential, geographical conditions, road network, social development level, recycling technology, etc., and has strong regional heterogeneity. Compared with the straight-line distance, the complexity and connectivity of the actual road network can affect the logistics transportation cost and environmental costs such as carbon emissions during the recycling process. Considering the actual road network can more accurately evaluate the feasibility and efficiency of photovoltaic module recycling. How to comprehensively consider the above multi-dimensional factors to achieve efficient recycling of retired photovoltaic modules still lacks practical methods and applications. It is not clear when, where, and what technology to recycle retired modules. Therefore, it is necessary to solve the site selection problem of photovoltaic waste recycling facilities. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a decision-making method for the site selection of photovoltaic waste recycling facilities based on the actual road network. First, the dynamic Weibull probability distribution function is used to model and evaluate the photovoltaic scrap volume, and the spatiotemporal distribution of the photovoltaic scrap volume at the grid scale (1km*1km) is obtained to obtain the location and scale of the photovoltaic scrap points; then, considering environmental constraints such as farmland, woodland, Gobi desert, water area, and ecological protection area, the grid points suitable for the construction of recycling plants are screened out in the obtained scrap volume distribution layer, that is, as potential site selection points for processing centers.

[0006] According to the extended producer responsibility system, photovoltaic module manufacturers are selected as alternative collection center points, and a photovoltaic waste reverse logistics network structure including scrapped photovoltaic power stations-collection centers-processing centers is constructed. On this basis, the construction cost, transportation cost, and carbon emission cost of each proposed facility in the photovoltaic waste reverse logistics network structure are considered. When calculating the transportation cost, the actual road network is considered to construct a scrap point-collection center, collection center-processing center distance matrix (OD cost distance matrix), and the distances of scrap point-collection center, collection center-processing center are obtained, which ensures the authenticity of the transportation distance. Finally, the minimum total cost of the reverse logistics network system is used as the objective function, and a mixed integer linear programming equation is constructed to solve and determine the number, site selection points, and recycling technology of target facilities in the network. The present invention reasonably considers multiple influencing factors, which is more conducive to determining the optimal site selection of target facilities.

[0007] The technical solution of the present invention is as follows:

[0008] A decision-making method for site selection of photovoltaic waste recycling facilities based on actual road networks, the steps are as follows:

[0009] (1) Using the Weibull probability distribution function f1 for modeling and evaluation, we can obtain the photovoltaic scrapping amount W in various regions at a 1km*1km grid scale. i Distribution layers;

[0010] (2) In the obtained PV scrap distribution map, exclude environmental constraints such as farmland, forest land, Gobi desert, water area, and ecological protection area to obtain potential site selection points for the treatment center;

[0011] (3) Organize the locations of PV module manufacturers and determine alternative collection center locations;

[0012] (4) Construct a reverse logistics network structure of photovoltaic waste, including scrapped photovoltaic power plants, collection centers, and processing centers;

[0013] (5) In order to obtain accurate transportation distance, the actual road network is considered, a distance matrix is ​​constructed, and the total transportation cost f2 is calculated;

[0014] (6) Calculate environmental costs such as carbon emission costs during transportation f3;

[0015] (7) Construct a mixed integer linear programming equation z, with the minimum total cost of the reverse logistics network system as the objective function. The optimal solution is the minimum z value, which is the location of the target facility in the photovoltaic waste reverse logistics network structure.

[0016] According to the preferred embodiment of the present invention, in step (1),

[0017]

[0018] Where β is the shape parameter of the function, which has a significant influence on the curve shape of the probability density function, indicating how the scrap volume per unit time changes with time t; T is the characteristic life parameter of the photovoltaic panel, and the Weibull distribution function is mainly controlled by the parameters T and β.

[0019] Integrating formula f1, we get the probability P of installed PV failing in the time interval between 0 and t:

[0020]

[0021] In the formula, W(σ) represents the probability of failure at the longest age, and σ represents the maximum age of the photovoltaic panel, which is generally 40 years;

[0022] Therefore, for the photovoltaic installed in the kth year, the probability of scrapping between the mth year and the m+1th year is as follows:

[0023] P k (k≤t≤m+1)=W k (m+1)-W k (k) (3)

[0024] The calculation formula for photovoltaic scrapping is as follows:

[0025] annual PV waste k (m) = new PV capacity (k) * (W k (m+1)-W k (k)). (4)

[0026] W i =∑annual PV waste(m) (5)

[0027] Where annual PV waste k represents the amount of scrap generated each year, and ew PV capacity(k) represents the amount of new PV installed each year.

[0028] According to the preferred embodiment of the present invention, in step (5),

[0029]

[0030] In the formula, i is the scrapped photovoltaic power station, assuming that there are I scrapped photovoltaic power stations; k is the collection center, assuming that there are K collection centers; τ is the unit transportation cost; j is the processing center, assuming that there are J processing centers; δ k is whether the collection center is opened, if it is opened, k The value is 1, if it is not set, the value is 0; W ik is the weight of PV waste transported from scrapping point i to collection center k; Dik is the distance from scrap point i to collection center k; σ j is whether photovoltaic recycling and processing center j is open, if it is open, it is 1, if not, it is 0; W kj is the weight of photovoltaic waste transported from collection center k to photovoltaic recycling and processing center j; D kj is the distance from the collection center k to the photovoltaic recycling and processing center j.

[0031] According to the preferred embodiment of the present invention, in step (6),

[0032]

[0033] Where EP represents the cost of carbon emissions generated by transporting unit weight of discarded components per unit distance, and its value is 0.142 yuan / km / ton.

[0034] According to the preferred embodiment of the present invention, in step (7),

[0035]

[0036]

[0037] In the formula, x j is the fixed investment cost of photovoltaic recycling facilities; t To recover the technology cost; k is the fixed investment cost of the collection center; t is the photovoltaic module recycling technology, including mechanical technology, chemical technology, and pyrolysis technology. T refers to the collection of photovoltaic recycling technologies; W i is the scrap quantity generated by scrap point i; Q k is the processing capacity of the collection center; U j is the processing capacity of photovoltaic recycling facilities; jt Whether photovoltaic recycling and processing center j chooses t recycling technology, if it chooses, the value is 1, if not, the value is 0;

[0038] Constraints (9) and (10) represent material balance constraints, that is, the amount of scrap transported to each collection center and processing center is equal to the sum of the scrap generated at the scrapping point.

[0039] Constraints (11)(12) represent the maximum disposal capacity limit of the photovoltaic recycling and processing center.

[0040] Constraints (13) and (14) indicate that the amount of scrap transported from the scrap point to the processing center is at least zero.

[0041] Constraint (15) indicates whether the collection center and processing center are opened and what technology is selected for the processing center.

[0042] Constraint (16) indicates that the choice of technology cannot exceed the number of PV recycling facilities opened.

[0043] Decision variable: δ k : Whether the collection center is open; σ j : Whether photovoltaic recycling facilities are opened; σ jt :Which recycling technology should be selected by photovoltaic recycling facility j? ik , W kj : Weight for transportation to collection centers and photovoltaic recycling facilities.

[0044] The beneficial effects of the present invention are:

[0045] The photovoltaic recycling facility site selection decision method proposed in the present invention constructs a photovoltaic waste reverse logistics network structure including scrapped photovoltaic power stations, collection centers, and processing centers. The construction cost, transportation cost, and carbon emission cost of the transportation stage of each proposed facility in the photovoltaic waste reverse logistics network structure are considered. The total cost of the reverse logistics network system is minimized as the objective function, and a mixed integer linear programming equation is constructed to solve and determine the number and site selection of target facilities in the network. This method reasonably considers multiple influencing factors and is more conducive to determining the optimal site selection of the target facility. DETAILED DESCRIPTION

[0046] The present invention will be further described below by way of examples, but is not limited thereto.

[0047] Embodiment 1:

[0048] This embodiment provides a decision-making method for site selection of photovoltaic waste recycling facilities based on an actual road network, and the steps are as follows:

[0049] (1) Using the Weibull probability distribution function f1 for modeling and evaluation, we can obtain the photovoltaic scrapping amount W in various regions at a 1km*1km grid scale. i Distribution layers;

[0050] Specific

[0051]

[0052] Where β is the shape parameter of the function, which has a significant influence on the curve shape of the probability density function, indicating how the scrap volume per unit time changes with time t; T is the characteristic life parameter of the photovoltaic panel, and the Weibull distribution function is mainly controlled by the parameters T and β.

[0053] Integrating formula f1, we get the probability P of installed PV failing in the time interval between 0 and t:

[0054]

[0055] In the formula, W(σ) represents the probability of failure at the longest age, and σ represents the maximum age of the photovoltaic panel, which is generally 40 years;

[0056] Therefore, for the photovoltaic installed in the kth year, the probability of scrapping between the mth year and the m+1th year is as follows:

[0057] P k (k≤t≤m+1)=W k (m+1)-W k (k) (3)

[0058] The calculation formula for photovoltaic scrapping is as follows:

[0059] annual PV waste k (m) = new PV capacity (k) * (W k (m+1)-W k (k))· (4)

[0060] W i =∑annual PV waste(m) (5)

[0061] Where annual PV waste k represents the amount of scrap generated each year, and ew PV capacity(k) represents the amount of new PV installed each year.

[0062] (2) In the obtained PV scrap distribution map, exclude environmental constraints such as farmland, forest land, Gobi desert, water area, and ecological protection area to obtain potential site selection points for the treatment center;

[0063] (3) Organize the locations of PV module manufacturers and determine alternative collection center locations;

[0064] (4) Construct a reverse logistics network structure of photovoltaic waste, including scrapped photovoltaic power plants, collection centers, and processing centers;

[0065] (5) In order to obtain accurate transportation distance, the actual road network is considered, a distance matrix is ​​constructed, and the total transportation cost f2 is calculated;

[0066]

[0067] In the formula, i is the scrapped photovoltaic power station, assuming that there are I scrapped photovoltaic power stations; k is the collection center, assuming that there are K collection centers; τ is the unit transportation cost; j is the processing center, assuming that there are J processing centers; δ k is whether the collection center is open, if it is open, k The value is 1, if it is not set, the value is 0; W ikis the weight of PV waste transported from scrapping point i to collection center k; D ik is the distance from scrap point i to collection center k; σ j is whether photovoltaic recycling and processing center j is open, if it is open, it is 1, if not, it is 0; W kj is the weight of photovoltaic waste transported from collection center k to photovoltaic recycling and processing center j; D kj is the distance from the collection center k to the photovoltaic recycling and processing center j.

[0068] (6) Calculate environmental costs such as carbon emission costs during transportation f3;

[0069]

[0070] Where EP represents the cost of carbon emissions generated by transporting unit weight of discarded components per unit distance, and its value is 0.142 yuan / km / ton.

[0071] (7) Construct a mixed integer linear programming equation z, with the minimum total cost of the reverse logistics network system as the objective function. The optimal solution is the minimum z value, which is the location of the target facility in the photovoltaic waste reverse logistics network structure.

[0072]

[0073] In the formula, x j is the fixed investment cost of photovoltaic recycling facilities; t To recover the technology cost; k is the fixed investment cost of the collection center; t is the photovoltaic module recycling technology, including mechanical technology, chemical technology, and pyrolysis technology. T refers to the collection of photovoltaic recycling technologies; W i is the scrap quantity generated by scrap point i; Q k is the processing capacity of the collection center; U j is the processing capacity of photovoltaic recycling facilities; jt Whether photovoltaic recycling and processing center j chooses t recycling technology, if it chooses, the value is 1, if not, the value is 0;

[0074] Constraints (9) and (10) represent material balance constraints, that is, the amount of scrap transported to each collection center and processing center is equal to the sum of the scrap generated at the scrapping point.

[0075] Constraints (11)(12) represent the maximum disposal capacity limit of the photovoltaic recycling and processing center.

[0076] Constraints (13) and (14) indicate that the amount of scrap transported from the scrap point to the processing center is at least zero.

[0077] Constraint (15) indicates whether the collection center and processing center are opened and what technology is selected for the processing center.

[0078] Constraint (16) indicates that the choice of technology cannot exceed the number of PV recycling facilities opened.

[0079] Decision variable: δ k : Whether the collection center is open; σ j : Whether photovoltaic recycling facilities are opened; σ jt :Which recycling technology should be selected by photovoltaic recycling facility j? ik , W kj : Weight for transportation to collection centers and photovoltaic recycling facilities.

[0080] The above descriptions are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A decision-making method for site selection of photovoltaic waste recycling facilities based on actual road network, characterized in that: Here are the steps: (1) Use the Weibull probability distribution function f1 to model and evaluate the amount of photovoltaic scrapped in various regions W i Distribution layers, specifically: Where β is the shape parameter of the function, which has a significant impact on the shape of the probability density function curve, indicating how the scrap volume per unit time changes with time t; T is the characteristic life parameter of the photovoltaic panel; Integrating formula f1, we get the probability P of installed PV failing in the time interval between 0 and t: In the formula, W(σ) represents the probability of failure at the longest age, and σ represents the maximum age of the photovoltaic panel, which is generally 40 years; Therefore, for the photovoltaic installed in the kth year, the probability of scrapping between the mth year and the m+1th year is as follows: P k (k≤t≤m+1)=W k (m+1)-W k (k)(3) The calculation formula for photovoltaic scrapping is as follows: annual PV waste k (m)=new PV capacity(k)*(W k (m+1)-W k (k)) (4) W i =Σannual PV waste(m) (5) Where annual PV waste k represents the scrapped amount generated each year, ew PV capacity(k) represents the newly installed PV capacity each year; (2) In the obtained PV scrapping distribution map, exclude the environmental constraints of farmland, forest land, Gobi desert, water area, and ecological protection area to obtain potential site selection points for the treatment center; (3) Organize the locations of PV module manufacturers and determine alternative collection center locations; (4) Construct a reverse logistics network structure of photovoltaic waste, including scrapped photovoltaic power plants, collection centers, and processing centers; (5) Considering the actual road network, construct the distance matrix and calculate the total transportation cost f2; (6) Calculate the environmental cost f3 during transportation; (7) Construct a mixed integer linear programming equation z, with the minimum total cost of the reverse logistics network system as the objective function. The optimal solution is the minimum z value, which is the location of the target facility in the photovoltaic waste reverse logistics network structure.

2. The decision-making method for site selection of photovoltaic waste recycling facilities based on actual road network according to claim 1, characterized in that: In step (5), In the formula, i is the scrapped photovoltaic power station, assuming that there are I scrapped photovoltaic power stations; k is the collection center, assuming that there are K collection centers; τ is the unit transportation cost; j is the processing center, assuming that there are J processing centers; δ k is whether the collection center is opened, if it is opened, k The value is 1, if it is not set, the value is 0; W ik is the weight of PV waste transported from scrapping point i to collection center k; D ik is the distance from scrap point i to collection center k; σ j is whether photovoltaic recycling and processing center j is open, if it is open, it is 1, if not, it is 0; W kj is the weight of photovoltaic waste transported from collection center k to photovoltaic recycling center j; D kj is the distance from the collection center k to the photovoltaic recycling and processing center j.

3. The decision-making method for site selection of photovoltaic waste recycling facilities based on actual road network according to claim 2, characterized in that: In step (6), Where EP represents the cost of carbon emissions generated by transporting unit weight of discarded components per unit distance, and its value is 0.142 yuan / km / ton.

4. The decision method for site selection of photovoltaic waste recycling facilities based on actual road network according to claim 3, characterized in that: In step (7), In the formula, x j is the fixed investment cost of photovoltaic recycling facilities; t To recover the technology cost; k is the fixed investment cost of the collection center; t is the photovoltaic module recycling technology, including mechanical technology, chemical technology, and pyrolysis technology. T refers to the collection of photovoltaic recycling technologies; W i is the scrap quantity generated by scrap point i; Q k is the processing capacity of the collection center; U j is the processing capacity of photovoltaic recycling facilities; jt Whether photovoltaic recycling and processing center j chooses t recycling technology, if it chooses, the value is 1, if not, the value is 0; Constraints (9) and (10) represent material balance constraints, that is, the amount of scrap transported to each collection center and processing center is equal to the sum of the scrap generated at the scrapping point; Constraints (11) and (12) represent the maximum disposal capacity limit of the photovoltaic recycling and processing center; Constraints (13) and (14) indicate that the amount of scrap transported from the scrap point to the processing center is at least zero; Constraint (15) indicates whether the collection center and processing center are opened and what technology is selected for the processing center; Constraint (16) indicates that the choice of technology cannot exceed the number of PV recycling facilities opened; Decision variable: δ k : Whether the collection center is open; σ j : Whether photovoltaic recycling facilities are opened; σ jt :Which recycling technology should be selected by photovoltaic recycling facility j? ik , W kj : Weight for transportation to collection centers and photovoltaic recycling facilities.

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