CN117114262A - Method for selecting and distributing carbon utilization point supply sources - Google Patents
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- 229910002092 carbon dioxide Inorganic materials 0.000 claims abstract description 63
- 239000001569 carbon dioxide Substances 0.000 claims abstract description 63
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims abstract description 32
- 229910052799 carbon Inorganic materials 0.000 claims abstract description 32
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 8
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 claims description 7
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- FEBLZLNTKCEFIT-VSXGLTOVSA-N fluocinolone acetonide Chemical compound C1([C@@H](F)C2)=CC(=O)C=C[C@]1(C)[C@]1(F)[C@@H]2[C@@H]2C[C@H]3OC(C)(C)O[C@@]3(C(=O)CO)[C@@]2(C)C[C@@H]1O FEBLZLNTKCEFIT-VSXGLTOVSA-N 0.000 claims description 6
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06313—Resource planning in a project environment
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
Abstract
The invention discloses a method for selecting and distributing a carbon utilization point supply source, which comprises the following steps: step 1, acquiring the space position and the planned utilization amount of a carbon utilization point; step 2, determining the number i, the spatial position, the industrial type and the carbon emission C of the alternative supply sources i The method comprises the steps of carrying out a first treatment on the surface of the Step 3, constructing a captured carbon dioxide economic cost function f (R i )，R i Carbon emission rate for the i-th candidate supply; step 4, determining the unit carbon dioxide transportation cost T of the alternative supply source i The method comprises the steps of carrying out a first treatment on the surface of the And 5, selecting and distributing the supply sources. The invention can reduce the technical cost of the CCUS, thereby improving the technical efficiency of the CCUS system and realizing the optimal configuration of resources.
Description
Technical Field
The invention relates to the field of CCUS technical deployment, in particular to a method for selecting and distributing carbon utilization point supply sources.
Background
Carbon capture, utilization and sequestration (CCUS) quiltIs considered as one of the important technical paths for reducing the emission of greenhouse gases. However, CCUS is systematic and costly, and planning and deployment thereof requires overall consideration of CO in the CCUS system 2 The technical matching and economic feasibility of the emission source (abbreviated as "source") and the utilization and storage place (abbreviated as "sink") and the transportation link between the emission source and the storage place (abbreviated as "sink") have more difficulties in practical application.
The existing CCUS deployment technology has the following problems:
1. considering a specific technical link of the CCUS system, attention of the whole CCUS system is not enough. The research of single technologies such as carbon capture, carbon transportation, carbon sequestration or carbon utilization is carried out in specific links in multi-focus CCUS technology chains at home and abroad, and the economic and technical benefits of the specific links are improved. But lack of consideration for the full chain of the CCUS system, it is difficult to guide the deployment application of the CCUS overall system.
The economic considerations of ccus deployment are inadequate. The institutions and scholars at home and abroad have developed a batch of systems and methods for source-sink matching decision support with various characteristics, such as a GeoCapacity DSS, a SimCCS model, an InfraCCS tool and the like. However, the technical matching between the source and the sink is mostly considered, and the factors such as infrastructure and capacity are mainly considered, so that the economic consideration is insufficient or the calculation is too rough. However, the economy of the CCUS deployment scheme directly relates to whether the deployment technology can be implemented, and the existing research has a shortage of cost consideration for the deployment of the CCUS technology, is mainly used for scientific research, and cannot introduce research results into specific application links.
3. Most of the CCUS deployment studies involving carbon sequestration sites, and none of the CCUS deployment studies involving carbon utilization sites. The institutions and scholars at home and abroad pay attention to strategic research, develop macroscopic CCUS technical deployment, pay attention to large-capacity source-sink matching and transportation pipe network arrangement of the sealing points and the collecting points, but the arrangement consideration is rough, and often the implementation and the application are difficult due to huge economic cost and real space conditions. From the feasibility and economy of application, small-capacity and small-scale CCUS technology deployment is developed aiming at carbon utilization points with cyclic utilization value.
Disclosure of Invention
The invention aims at overcoming the technical defects in the prior art and provides a method for selecting and distributing a carbon utilization point supply source.
The technical scheme adopted for realizing the purpose of the invention is as follows:
a method for selecting and distributing carbon utilization point supply sources, comprising the steps of:
step 1, acquiring the space position and the planned utilization amount of a carbon utilization point;
step 2, determining the number i, the space position and the carbon emission C of the supply sources to be selected i ；
Step 3, constructing a captured carbon dioxide economic cost function f (R i )，R i Carbon emission rate for the i-th candidate supply;
step 4, determining the unit carbon dioxide transportation cost T of the alternative supply source i ；
Step 5, selecting and distributing the supply sources:
and taking the comprehensive total economic cost after the carbon utilization point is matched with the point source to be selected as an optimization evaluation index.
In the above technical solution, in the step 3, the carbon dioxide capturing economic cost function f (R i ) And constructing by using chemical process simulation software PROII according to an MEA absorption method.
In the above technical solution, the assumptions and parameter settings performed by the simulation process are as follows: (1) the flow and the concentration of inlet flue gas take the industrial production data of specific point to be selected emission sources as basic basis; (2) in the process of the equipment unit, the heat exchanger is a convection exchange model, and the minimum heat exchange temperature difference is set to be 10 ℃; (3) isentropic efficiency of the process pump is assumed to be 70-85%; (4) the carbon capture rate in the absorption process is controlled to be between 70 and 90 percent; (5) the carbon dioxide trapped by the absorption method is finally pressurized at low temperature to obtain a liquid carbon dioxide product with the concentration of 99 percent; (6) the carbon trapping process based on the MEA absorption method integrates and optimally designs the heat energy.
In the above technical solution, in the step 3, the total carbon dioxide capturing cost includes operation and investment costs, operation costs and operation and maintenance costs.
In the above technical solution, total carbon dioxide capture cost toc=cpaex+opex+o & M, wherein:
C total sum of purchase costs for each device, M c For annual carbon dioxide capture of the alternative supply source, the purchase cost per plant is +.>Cy represents the purchase cost in y years, iy represents CEPCI in y years, I 2018 603.1, cy=c a ，C a By->Calculating, wherein A is equipment cost attribute, namely unit equipment volume capacity parameter, C is equipment purchasing cost, n is cost index, and subscripts a and b represent equipment attribute of the engineering calculation a and the reference engineering case b;
OPEX＝N n ×4+W e ×0.06+M MEA ×0.97+N w ×0.01
wherein N is n The volume of natural gas consumed by heating each ton of carbon dioxide is captured in the process; w (W) e Capturing the consumed electric energy of each ton of carbon dioxide in the process; m is M MEA An absorbent MEA that is lost during the process; n (N) w Capturing the volume of condensed water consumed by heating each ton of carbon dioxide in the process;
O&M＝0.03×CAPEX；
obtaining cost TOC along with carbon capture rate R according to output of chemical process simulation software PROII and economic cost calculation method i Is subjected to nonlinear fitting to obtain corresponding functionsRelation f (R) i )。
In the above technical solution, in the step 4, T i Calculated by the following steps:
step s1, taking a carbon utilization point as an end point, taking the to-be-selected supply source as a starting point, and establishing an internal road network of a target area in an Arc GIS;
step s2, screening a transportable road network in the area, and guaranteeing the technical feasibility of carbon transportation;
step s3, determining a transportable shortest path between each candidate supply source and the carbon utilization point based on Dijkstra algorithm by taking the carbon utilization point as an origin point and the candidate industrial supply source as a destination point;
step s4, outputting the length of the shortest path of each candidate industrial supply source identified by Dijkstra algorithm, and determining that the shortest transport length from each candidate supply source to a carbon utilization point is L i ；
And step s5, calculating the optimal unit carbon dioxide transportation cost of the to-be-selected trapping point.
In the above technical solution, in step s2, the screening conditions are as follows: road width > 11M, where road width >7M.
In the above-described aspect, in the step s3, the temporary set NB is formed from the carbon utilization starting point s s Selecting a neighbor intersection node k with the smallest distance as a transfer point, and classifying the neighbor intersection node k to a shortest path identification set S; then updating the value of the node in the difference set of the temporary set of the intersection node k and the identification set, and updating the value of the node in the difference set of the temporary set of all nodes in the identification set S and the difference set U-shaped NB of the identification set k-s And selecting a node with the smallest path distance value as the next transfer point, classifying the node into the shortest path identification set S, repeating the process until all intersection nodes in the path from the carbon utilization starting point to the industrial supply source end point to be selected are identified, and ending the algorithm.
In the above technical solution, in step s5, the optimal unit carbon dioxide transportation cost of the to-be-selected capture point is: t (T) i ＝L i ×t
Wherein T is i For the ith candidate industrial supplyThe most economical cost per unit of transportation of carbon dioxide to the carbon utilization point; l (L) i The shortest transport length from the ith candidate industrial supply source to the point of use; t is the cost of carbon dioxide road transportation per unit distance.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention considers the economic-technical benefits of the CCUS overall system, and performs planning and deployment of the supply source aiming at specific carbon utilization points. Under the condition of ensuring that the carbon utilization point obtains the same carbon dioxide capturing amount, the scheme with the lowest economic cost of the whole CCUS system is selected.
2. The invention can realize the technical optimization of the CCUS whole-flow system from the utilization end to the source end, and reduce the technical cost of the CCUS under the condition of ensuring the technical feasibility and the technical output, thereby improving the technical efficiency of the CCUS and realizing the optimal configuration of resources.
3. The invention evaluates and optimally designs the whole process of CCUS technology production aiming at the carbon utilization point, and has more representative and practical values for CCUS economic-technical evaluation related to the carbon utilization point.
Drawings
Fig. 1 is a schematic diagram of a technical flow of the present invention.
FIG. 2 shows a flow chart for carbon dioxide capture by MEA absorption.
Fig. 3 shows the input and output of the chemical simulation software proci 10.0.
Detailed Description
The present invention will be described in further detail with reference to specific examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Example 1
A method for selecting and distributing carbon utilization point supply sources, comprising the steps of:
and 1, collecting basic information of carbon utilization points. And acquiring the space information and the data information of the carbon utilization points, and determining the positions and the planned utilization amount of the carbon utilization points.
And 2, determining basic information of the supply source to be selected. And acquiring the number i of industrial carbon capture points within the range of 50KM around the carbon utilization point, collecting spatial information and data information of the industrial carbon capture points, and determining the number, spatial position and flue gas carbon dioxide concentration and emission of the to-be-selected supply sources.
And 3, constructing an economic cost function of capturing carbon dioxide of the alternative supply source.
This example is based on the technology-developed and widely used ethanolamine (MEA) absorption method for capturing carbon dioxide after combustion, and the specific technological process of the ethanolamine (MEA) absorption method is shown in fig. 2: the absorption method carbon dioxide trapping device mainly comprises an absorption tower and a regeneration tower, wherein flue gas enters the absorption tower from the bottom and flows reversely with an absorption liquid at the top of the tower to fully contact and react, carbon dioxide in the flue gas is absorbed, a rich liquid rich in carbon dioxide is further decompressed through a decompression valve and separated into partial water vapor by a flash tank, the partial water vapor is further conveyed into the regeneration tower after the temperature is further raised, the rich liquid is desorbed at high temperature and separated into high-concentration carbon dioxide, the condensed and compressed carbon dioxide is formed into liquid carbon dioxide for further transportation, the output low-concentration carbon dioxide lean liquid flows back to the absorption tower for recycling, the temperature of the absorption liquid is lowered through a heat exchanger in the process, the pressure of the absorption liquid is raised through a process pump, and meanwhile, the water lost in the process and the MEA absorption liquid are supplemented.
And designing the absorption and desorption process of carbon dioxide based on the MEA absorption liquid by using chemical simulation software PROII 10.0 according to the gas components and flow information in the flue gas of the corresponding to-be-supplied source, and completing mass and energy balance in the carbon capturing process. The energy consumption and volumetric capacity parameters of each plant unit process were based on different recovery rates using simulation software output for the economic cost calculations described below, with software input and output as shown in fig. 3. The assumptions and parameter settings for the simulation process were as follows:
(1) the flow and the concentration of inlet flue gas take the industrial production data of a specific supply source to be selected as basic basis; (2) in the process of the equipment unit, the heat exchanger is a convection exchange model, and the minimum heat exchange temperature difference is set to be 10 ℃; (3) isentropic efficiency of the process pump is assumed to be 70-85%; (4) the carbon capture rate in the absorption process is controlled to be between 70 and 90 percent; (5) the carbon dioxide trapped by the absorption method is finally pressurized at low temperature to obtain a liquid carbon dioxide product with the concentration of 99 percent; (6) the carbon trapping process based on the absorption method integrates and optimally designs the heat energy.
The carbon capture costs mainly include three parts, namely investment costs (Capital expenditure, CAPEX), operating costs (Operational expenditure, OPEX) and operation and maintenance costs (Operation and Maintenance cost O & M), calculated as follows:
(1) Investment costs (Capital expenditure, CAPEX)
And calculating the direct investment cost of the equipment by adopting the following formula according to the volume capacity parameters of the unit equipment obtained in the simulation process.
Wherein A is equipment cost attribute (namely unit equipment volume capacity parameter), C is equipment purchase cost, and n is cost index. The subscripts a, b represent the engineering calculation (a) and the reference engineering case (b) equipment attributes. The cost index n is taken to be 0.6. The purchase costs of the individual device components of the project are calculated from the device capacity parameters using the device purchase costs of the related industrial cases.
Meanwhile, the chemical engineering device cost index (CEPCI) is used for adjusting the time value of equipment and reflecting the current economic condition, and the formula is as follows.
Where Cy represents the purchase cost of y years (i.e., the equipment purchase cost of engineering technique a obtained above, y is the project year of b in the above reference case engineering case), and Iy represents the CEPCI of y years. The CEPCI value in 2018 was 603.1. The price of the purchase cost of each device is converted into 2018 purchase cost through the conversion.
According to the direct investment cost of the equipment, the carbon dioxide capturing cost of the alternative supply source is calculated, and the following formula is adopted:
wherein the average investment cost, C, of the CAPEX ($/ton) carbon dioxide capture total The sum of the purchase costs for the various devices of the above technology (columns, pumps, condensers, etc.) during the project. The annual average investment cost is calculated by multiplying the direct investment cost obtained above by the project installation coefficient and the equipment depreciation coefficient of the project (the project period is assumed to be 25 years), and divided by the annual captured carbon dioxide yield. M is M c (ton) annual carbon dioxide capture amount of the alternative supply source.
(2) Running cost (Operational expenditure, OPEX)
The main operating costs in the process are from the public works such as heat energy, electric energy and condensate water which need to be consumed in the process, and the heat energy in the process is supposed to be provided by natural gas. According to the quantity of public works consumed by each unit in the carbon dioxide capturing process, the running cost is calculated according to the following formula:
OPEX＝N n ×4+W e ×0.06+M MEA ×0.97+N w ×0.01
wherein N is n (m 3 Ton) is the volume of natural gas consumed by heating of captured carbon dioxide per ton in the process, and the price of the natural gas is set to be 4$/m 3 ；W e (KWh/ton) is to capture the electric energy consumed by each ton of carbon dioxide in the process, and the electric power price is set to be 0.06$/KWh; m is M MEA (kg/ton) of the absorbent MEA to be consumed in the process, the price of which is set to be 0.97$/kg; n (N) w (m 3 Ton) is the volume of condensed water consumed by heating each ton of carbon dioxide captured in the process, and the price of the condensed water is set to be 0.01$/m 3 ，N n 、W e 、M MEA And N w The numerical values of (2) are output by chemical simulation software PROII 10.0.
(3) Operation and maintenance costs (Operation and Maintenance cost O & M)
Repair and other small-scale operating costs are estimated to be 2% (repair) and 1% (other operating costs) of the total cost of the equipment.
O&M＝0.03×CAPEX
(4) Total cost of carbon dioxide capture (Total cost, TOC)
TOC＝CPAEX+OPEX+O&M
The total carbon trapping cost TOC is influenced by the carbon dioxide component concentration of different supply point sources and the carbon trapping rate of the process, and the cost TOC along with the carbon trapping rate R is obtained based on the simulation software design and the economic cost calculation method under the condition of determining the components and the flow rate of a certain supply point source i And non-linear fitting is performed to obtain a corresponding functional relationship f (R i ). Meanwhile, fitting functions of different corresponding point sources can be obtained by different point sources.
Step 4, determining the unit carbon dioxide transportation cost of the supply source to be selected, which specifically comprises the following steps:
(1) And taking the carbon utilization point as an end point, taking the industrial supply source to be selected as a starting point, and establishing a road network in a target area in the Arc GIS. The entire network map will consist of intersection points and road segments.
(2) And screening the transportable road network in the area, so as to ensure the technical feasibility of carbon transportation. The specific screening conditions are as follows: road width > 11M, where road width >7M.
(3) And determining the transportable shortest path between each industrial supply source to be selected and the carbon utilization point based on Dijkstra algorithm by taking the carbon utilization point as a starting point and the industrial supply source to be selected as an ending point. The specific operation is as follows:
temporary set NB from carbon utilization origin s s Selecting a neighbor intersection node k with the smallest distance as a transfer point (a node set directly connected with the origin point S), and simultaneously classifying the neighbor intersection node k into a shortest path identification set S; then updating the value of the node in the difference set of the temporary set of the intersection node k and the identification set, and updating the value of the node in the difference set of the temporary set of all nodes in the identification set S and the difference set U-shaped NB of the identification set k-s And selecting a node with the smallest path distance value as the next transfer point, and classifying the node into the shortest path identifier set S. Repeating the above process until all intersection nodes in the path from the carbon utilization start point to the destination of the industrial supply source to be selected are identifiedThe algorithm ends.
In the shortest path calculation process, the specific execution algorithm is as follows:
let n be the shortest transport path from the start point of carbon utilization to the end point of the industrial supply source to be selected, NB r For the temporary set of the r-th intersection node in the shortest transport path, S is the shortest transport path identification set, omega j For the shortest path length from carbon utilization origin s to node j, P j Is the previous node of point j in the shortest path from s to j, d rj Is the distance from node r to node j.
(1) Initializing an identification set S= { S }, omega r ＝d sr (r∈NB s ) OtherwiseP r ＝s；
(2) If the distance from the k temporary set node to the carbon utilization starting point is minimum d sk ＝mind sj ，j∈NB s S=s & { k };
(3) modifying k temporary aggregation node NB k Omega in S j Value: omega j ＝min{ω j ；ω k +d kj }，j∈NB k -S; if omega j Value changes, P j ＝k；
(4) Selecting a marked temporary node set NB r Omega in S (r.epsilon.S) j Minimum value, ω, and assign it to S k ＝minω j ，j∈∪NB r -S; s=s { k }; if |s|=n, the node has been identified, the algorithm terminates, otherwise go to (2).
(4) Outputting the length of the shortest path n of each industrial supply source to be selected, which is identified by Dijkstra algorithm, and determining that the shortest transport length from each industrial supply source to the utilization point to be selected is L i ；
(5) The optimal unit carbon dioxide transportation cost of the trapping point to be selected is calculated, and the algorithm of the optimal economic cost of the carbon dioxide transportation from the ith trapping point to the carbon utilization point is as follows:
T i ＝L i ×t
wherein T is i Is the ithThe most suitable economic cost of carbon dioxide transportation per unit from the industrial supply source to the carbon utilization point is selected; l (L) i The shortest transport length from the ith candidate industrial supply source to the point of use; t is the transportation cost of the carbon dioxide road per unit distance, and is 1 yuan/ton.km.
And 5, selecting and distributing the supply sources. And determining an objective function to optimally design the transportation and carbon capture rate based on the environmental-direction capture points and the economic cost of the transportation end. The specific algorithm is as follows:
wherein C is i Carbon emission for the ith candidate industrial supply, R i Carbon capture rate for the ith candidate industrial supply, f (R i ) An economic cost function of captured carbon dioxide for the ith candidate industrial supply, T i The optimal economic cost for transporting carbon dioxide per unit of supply source from the ith candidate to the carbon utilization point,and taking the comprehensive total economic cost after the carbon utilization point is matched with the point source to be selected as an optimization evaluation index.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (9)
1. A method for selecting and distributing a carbon utilization point supply source, comprising the steps of:
step 1, acquiring the space position and the planned utilization amount of a carbon utilization point;
step 2, determining the number i, the space position and the carbon emission C of the supply sources to be selected i ；
Step 3, constructing the trapping dioxide of the alternative supply sourceCarbon economic cost function f (R i )，R i Carbon emission rate for the i-th candidate supply;
step 4, determining the unit carbon dioxide transportation cost T of the alternative supply source i ；
Step 5, selecting and distributing the supply sources:
and taking the comprehensive total economic cost after the carbon utilization point is matched with the point source to be selected as an optimization evaluation index.
2. The method for selecting and distributing carbon utilization point sources according to claim 1, wherein in said step 3, a carbon dioxide capturing economic cost function f (R i ) And constructing by using chemical process simulation software PROII according to an MEA absorption method.
3. The method for selecting and distributing carbon utilization point sources according to claim 2, wherein assumptions and parameter settings of the simulation process are as follows: (1) the flow and the concentration of inlet flue gas take the industrial production data of specific point to be selected emission sources as basic basis; (2) in the process of the equipment unit, the heat exchanger is a convection exchange model, and the minimum heat exchange temperature difference is set to be 10 ℃; (3) isentropic efficiency of the process pump is assumed to be 70-85%; (4) the carbon capture rate in the absorption process is controlled to be between 70 and 90 percent; (5) the carbon dioxide trapped by the absorption method is finally pressurized at low temperature to obtain a liquid carbon dioxide product with the concentration of 99 percent; (6) the carbon trapping process based on the MEA absorption method integrates and optimally designs the heat energy.
4. The method for selecting and distributing carbon utilization point sources according to claim 1, wherein in said step 3, the total carbon dioxide capturing cost includes operation and investment costs, operation costs and operation and maintenance costs.
5. The method for selecting and distributing a carbon utilization point supply source according to claim 4, wherein total carbon dioxide capture cost TOC = cpaex+opex+o & M, wherein:
C total sum of purchase costs for each device, M c For annual carbon dioxide capture of the alternative supply source, the purchase cost per plant is +.>Cy represents the purchase cost in y years, iy represents CEPCI in y years, I 2018 603.1, cy=c a ，C a By->Calculating, wherein A is equipment cost attribute, namely unit equipment volume capacity parameter, C is equipment purchasing cost, n is cost index, and subscripts a and b represent equipment attribute of the engineering calculation a and the reference engineering case b;
OPEX＝N n ×4+W e ×0.06+M MEA ×0.97+N w ×0.01
wherein N is n The volume of natural gas consumed by heating each ton of carbon dioxide is captured in the process; w (W) e Capturing the consumed electric energy of each ton of carbon dioxide in the process; m is M MEA An absorbent MEA that is lost during the process; n (N) w Capturing the volume of condensed water consumed by heating each ton of carbon dioxide in the process;
O&M＝0.03×CAPEX；
obtaining cost TOC along with carbon capture rate R according to output of chemical process simulation software PROII and economic cost calculation method i And non-linear fitting is performed to obtain a corresponding functional relationship f (R i )。
6. The method for selecting and distributing carbon utilization point sources according to claim 1, wherein in said step 4, T i Calculated by the following steps:
step s1, taking a carbon utilization point as an end point, taking the to-be-selected supply source as a starting point, and establishing an internal road network of a target area in an Arc GIS;
step s2, screening a transportable road network in the area, and guaranteeing the technical feasibility of carbon transportation;
step s3, determining a transportable shortest path between each candidate supply source and the carbon utilization point based on Dijkstra algorithm by taking the carbon utilization point as an origin point and the candidate industrial supply source as a destination point;
step s4, outputting the length of the shortest path of each candidate industrial supply source identified by Dijkstra algorithm, and determining that the shortest transport length from each candidate supply source to a carbon utilization point is L i ；
And step s5, calculating the optimal unit carbon dioxide transportation cost of the to-be-selected trapping point.
7. The method for selecting and distributing a carbon utilization point supply source according to claim 6, wherein in the step s2, the screening conditions are as follows: road width > 11M, where road width >7M.
8. The method for selecting and distributing carbon utilization point sources as defined in claim 6, wherein in said step s3, from a temporary set NB of carbon utilization points s s Selecting a neighbor intersection node k with the smallest distance as a transfer point, and classifying the neighbor intersection node k to a shortest path identification set S; then updating the value of the node in the difference set of the temporary set of the intersection node k and the identification set, and updating the value of the node in the difference set of the temporary set of all nodes in the identification set S and the difference set U-shaped NB of the identification set k-s Selecting a node with the smallest path distance value as the next transfer point, classifying the node into a shortest path identification set S, repeating the process until all intersection nodes in the path from the carbon utilization starting point to the industrial supply source end point to be selected are markedAfter recognition, the algorithm ends.
9. The method for selecting and distributing carbon utilization point sources according to claim 6, wherein in step s5, the optimum carbon dioxide transportation cost per unit of the trapping point to be selected is: t (T) i ＝ i ×t
Wherein T is i The optimal economic cost of carbon dioxide per unit of transportation from the ith candidate industrial supply source to the carbon utilization point; l (L) i The shortest transport length from the ith candidate industrial supply source to the point of use; t is the cost of carbon dioxide road transportation per unit distance.
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