A multi-period deployment optimization method for CCUS system considering carbon tax incentives

Abstract

The present invention provides a multi-period deployment optimization method for a CCUS system considering carbon tax incentives, the method comprising: collecting carbon emission data, node data and production data of the CCUS system, constructing constraint conditions of a multi-period deployment optimization model for the CCUS system based on a carbon tax incentive policy, constructing a multi-period deployment optimization model for the CCUS system based on a carbon tax incentive policy according to an objective function of minimizing the annualized total investment operating cost, and solving the model to obtain a multi-period deployment optimization scheme for the CCUS system with the minimum annualized total investment operating cost. Based on the consideration of the carbon tax incentive policy, the method optimizes the deployment for the multi-period operation of the CCUS system, effectively realizes the best match between carbon sources and carbon sinks, and significantly reduces the operating cost of the CCUS system.

Description

Technical Field

[0001] The present invention relates to the field of multi-period pipeline network optimization, and in particular to a multi-period deployment optimization method for a CCUS system considering carbon tax incentives. Background Art

[0002] In recent years, energy and environmental issues have attracted widespread attention from the international community, and carbon peak and carbon neutrality (dual carbon goals) have become a global trend. The dual carbon goal issue is a systemic issue that involves economic structure, industrial structure, energy structure, energy conservation, carbon technology and carbon market, etc. The focus is on energy structure adjustment and energy conservation and consumption reduction. Although the development and application of non-fossil energy is increasing, the main energy supply still comes from fossil fuels at this stage. Therefore, there is an urgent need for a method to use fossil fuels reasonably and sustainably to reduce the environmental pollution caused. Carbon dioxide produced by the combustion of fossil fuels, as one of the most important greenhouse gases, plays an important role in climate change.

[0003] CCUS technology has an irreplaceable position as a carbon emission reduction response measure. It is one of the key ways to achieve the goal of controlling warming and near-zero emissions in this century, and it is also a good way to curb global climate change. However, the deployment process of CCUS technology in enterprises is not smooth. Most enterprises are not very enthusiastic about deployment and need to use relevant policies to incentivize it. Carbon tax incentive policy is currently the main means to increase the enthusiasm of enterprises to deploy. Carbon tax is an environmental tax levied on enterprises' carbon dioxide emissions. Its tax rate directly affects the investment and operating costs of carbon reduction projects, and it will also affect the achievement of carbon reduction targets. Therefore, studying the appropriate carbon tax rate is crucial for optimizing the operating costs and carbon capture volume of carbon capture, utilization and storage pipelines.

[0004] The optimization of multi-cycle carbon capture, utilization and storage pipeline networks is carried out in the context of balancing economic development and greenhouse effect control. By formulating phased carbon emission reduction targets, the implementation of the dual carbon target strategy is gradually promoted. Therefore, it is of great significance to study the construction of multi-cycle source-sink matching pipeline networks in carbon capture, utilization and storage pipeline networks, which can effectively reduce the overall economic benefits and is a practical and feasible application.

[0005] In summary, the present invention provides a multi-period deployment optimization method for CCUS systems considering carbon tax incentives. Taking into account different investment and operating costs, technical material combinations, carbon tax collection rates, emission reduction targets under different periods, and influencing factors of different scenarios, a multi-period carbon capture, utilization and storage pipeline optimization study is carried out. It can, to a certain extent, steadily promote the achievement of dual carbon goals in stages, and has important guiding significance for guiding the multi-period implementation of large-scale CCUS demonstration projects. It is also conducive to regulating the balanced development of the overall regional economy and environment. Summary of the invention

[0006] In response to the problem of multi-period carbon capture, utilization and storage pipeline network optimization research, the present invention proposes a multi-period deployment optimization method for CCUS system considering carbon tax incentives. This method can optimize the pipeline network layout with the minimum total annualized investment and operating cost as the objective function, which has certain guiding significance for the optimal layout of CCUS pipeline network.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] The present invention provides a multi-period deployment optimization method for a CCUS system considering carbon tax incentives, comprising:

[0009] S1: Collect CCUS system carbon emission data, node data and basic data;

[0010] S2: Construct the constraints of the multi-period deployment optimization model of CCUS system based on carbon tax incentive policy;

[0011] S3: Construct a multi-period deployment optimization model for CCUS system based on carbon tax incentive policy according to the constraint conditions and the objective function of minimizing the annualized total investment operating cost;

[0012] S4: Solve the model to obtain the multi-period deployment optimization plan of the CCUS system with the minimum annualized total investment and operating cost.

[0013] Preferably, the CCUS system multi-period deployment optimization method considering carbon tax incentives is characterized in that the CCUS system described in step S1 is composed of a carbon emission source node and a storage sink node, the carbon emission data is carbon dioxide emissions, and the calculation formula is:

[0014] An=Cap*Capf*Hr*Emf*9.2427×10 -12

[0015] Where An is the annual carbon dioxide emissions of coal-fired units, 10 6 t; Cap is the capacity of the coal-fired unit, MW; Capf is the capacity factor; Hr is the heat rate of the coal-fired power plant, Btu / kWh; Emf is the emission factor;

[0016] The node data are the longitude and latitude coordinates of the carbon emission source nodes and the storage sink nodes;

[0017] The basic data include carbon capture compression technical parameters, pipeline construction cost parameters, storage unit cost, annual compound interest coefficient and system planning period.

[0018] Preferably, the multi-period deployment optimization method of CCUS system considering carbon tax incentives is characterized in that the constraints described in step S2 include flow constraints, emission source capture constraints, cycle-year carbon emission reduction target constraints, capture compression technology material combination and quantity constraints, storage sink storage constraints, pipeline cycle reuse constraints and decision variable value range constraints;

[0019] The flow constraints include maximum flow constraints, minimum flow constraints, and node flow balance constraints;

[0020] The maximum flow constraint means that the pipeline flow of any candidate pipeline path p with a period diameter of d should not be greater than its maximum pipeline flow. The constraint formula is:

[0021]

[0022] In the formula, is the maximum flow rate of a pipe with a diameter of d, t / a; Q p,d,u is the pipeline flow rate of the candidate pipeline path p with a diameter of d in the uth period, t / a;

[0023] The pipeline minimum flow constraint means that since the candidate pipeline path is bidirectional, the pipeline flow may be negative, and the pipeline flow with a negative flow direction should not be greater than its maximum pipeline flow. The constraint formula is:

[0024]

[0025] The node flow balance constraint means that the capture or storage volume of any emission source and storage sink node should be equal to the sum of its node inflow and outflow. The constraint formula is:

[0026] Emission sources:

[0027] Seal Exchange:

[0028] The emission source capture constraint means that the emission source capture in any period should be less than the maximum annual carbon dioxide emissions of the emission source. At the same time, in order to ensure the continuous supply of the emission source, the capture in the current period should not be less than the capture in the previous period. The constraint formula is:

[0029]

[0030] x i,u+1 ≥x i,u

[0031] The cycle annual carbon emission reduction target constraint refers to the annual carbon capture amount in each cycle within the region meeting the cycle annual carbon emission reduction target. The constraint formula is:

[0032]

[0033] In the formula, Capt u Indicates the carbon emission reduction target for each period, t / a;

[0034] The aforementioned capture and compression technology material combination quantity constraint means that the carbon dioxide emission source in any period during the planning period can only use one technology material combination process to capture and compress carbon dioxide. The constraint formula is:

[0035]

[0036] The capture compression technology material combination constraint refers to the different carbon dioxide contents in flue gas from different types of emission sources. Different technology material combinations are suitable for different flue gas carbon dioxide contents. The constraint formula is:

[0037]

[0038] In the formula, Indicates the upper limit of flue gas carbon dioxide concentration applicable to each technical material combination k, %; Indicates the lower limit of flue gas carbon dioxide concentration applicable to each technical material combination k, %;

[0039] The storage capacity constraint of the storage sink refers to the need for the annual storage capacity of carbon dioxide in the storage sink to meet the continuous use of the reservoir during the project planning period. The constraint formula is:

[0040]

[0041] r j,u+1 -r j,u ≥0

[0042] In the formula, represents the maximum storage capacity of reservoir j, t; r j,u represents the binary decision variable for activation of the storage sink j reservoir in period u, which is 1 when activated and 0 when not activated;

[0043] The pipeline cycle reuse constraint refers to the model requirement that only one pipeline of a specific diameter be built on the candidate pipeline path during the project planning period, and the built pipeline can be reused in subsequent cycles. The constraint formula is:

[0044]

[0045] Where η p,d A binary variable representing pipeline reuse with a candidate pipeline path of diameter d and p, which is 0 when the pipeline is built or reused and 1 when it is not built; A represents the number of optional pipe diameter options;

[0046] The decision variable value range constraint formula is:

[0047] a i,u ∈{0,1}i∈I,u∈U

[0048] r j,u ∈{0,1}j∈J,u∈U

[0049] b p,d,u ∈{0,1}p∈P,d∈D,u∈U

[0050] z i,k,u ∈{0,1}i∈I,k∈K,u=U

[0051] η p,d ∈{0,1}p∈P,d∈D.

[0052] Preferably, the CCUS system multi-period deployment optimization method considering carbon tax incentives is characterized in that the objective function described in step S3 is composed of flue gas dehydration cost, carbon dioxide capture and compression investment cost, carbon dioxide capture and compression operating cost, annual capital recovery amount of pipeline construction, annual pipeline operating cost, carbon dioxide storage cost, and carbon tax payment cost, and the objective function formula is:

[0053] min F=F W +F IC +F OC +F IPC +F OPC +F SC +F tax

[0054] Where, F is the total annualized investment and operating cost, RMB / a; F W is the annual flue gas dehydration cost of the emission source, RMB / a; F IC Compress the annual investment cost of carbon dioxide capture from emission sources, RMB / a; F OC The CO2 compression operating cost of the emission source, RMB / a; F IPC is the annualized investment cost of pipeline construction, RMB / a; F OPC is the annual operation cost of the pipeline, RMB / a; F SC is the annual storage cost of the storage exchange, RMB / a; F tax The annual carbon tax payment cost for emission sources, RMB / a;

[0055] The annual flue gas dehydration cost for the carbon tax incentive emission source is calculated based on the amount of carbon dioxide captured by the coal-fired power plant as follows:

[0056]

[0057] Where v is the number of cycles u in the project planning period; s is the number of carbon dioxide emission sources; ε is the unit carbon dioxide dehydration cost of flue gas, yuan / t; x i,u is the annual carbon dioxide capture of emission source i in the uth cycle, t / a; int is the discount rate; λ is the capital recovery coefficient during the project planning period; δ is the period annuity present value coefficient during the project planning period; T is the project planning period; is the cycle number of the uth cycle; T0 is the cycle duration;

[0058] The annualized investment cost of carbon dioxide capture and compression for emission sources under the carbon tax incentive policy is the annualized investment cost of new capture facilities and compression facilities, and the formula is as follows:

[0059]

[0060] In the formula, e is the number of technical material combinations; Calculate the parameters for the capture compression investment cost of the technology material combination k; i,k,u represents the capture binary decision variable for emission source i to adopt technology material combination k in period u, with a value of 1 when adopted and a value of 0 when not adopted; w i is the carbon dioxide content in the flue gas from emission source i, %; E i is the flue gas capture flow rate of emission source i, mol / s;

[0061] The annual operating cost of carbon dioxide capture compression for the carbon tax incentive emission source is the operating cost formula of capture device materials and boosting:

[0062]

[0063] In the formula, Calculate the parameters for the capture compression operating cost of the technical material combination k;

[0064] The annualized investment cost of the carbon tax incentive policy pipeline construction is the annuity present value formula of the pipeline construction investment within the period:

[0065]

[0066] Where g is the number of candidate pipelines; q is the number of pipeline diameters; b p,d,u Indicates the binary decision variable for pipeline construction in the uth cycle, where the candidate path is p and the diameter is d. It is 1 when the pipeline is constructed and 0 when it is not constructed. p is the length of the candidate pipeline path p, km; CB d is the construction cost per unit length of a pipeline with a diameter of d, RMB / km;

[0067] The formula for the annual operating cost of the carbon tax incentive policy pipeline is:

[0068]

[0069] The annual storage cost of the carbon tax incentive policy storage sink is the storage cost or production increase benefit formula generated by the storage sink node by storing carbon dioxide in the reservoir:

[0070]

[0071] Where r is the amount of carbon dioxide storage sink; y j,u is the annual carbon dioxide storage capacity of sink node j in the uth cycle, t / a; CR j represents the unit carbon dioxide storage / utilization cost of sink node j, RMB / t;

[0072] The annual carbon tax payment cost of the emission source under the carbon tax incentive policy is the tax cost formula for the emission source node directly emitting carbon dioxide into the atmosphere:

[0073]

[0074] In the formula, tax u is the carbon tax rate in cycle u, yuan / t; is the maximum annual carbon dioxide emission of emission source i, t / a.

[0075] Preferably, the CCUS system multi-period deployment optimization method considering carbon tax incentives is characterized in that the model solving steps in step S4 are as follows:

[0076] S401: Delaunay triangulation algorithm is used to determine the matching scheme of each carbon emission source node and storage sink node in the CCUS system;

[0077] S402: Determine the pipe diameter between the carbon emission source node and the storage sink node in combination with the node flow data, and calculate the CCUS system construction cost;

[0078] S403: Based on the objective function and constraint conditions of the CCUS system multi-cycle deployment optimization model, a branch and bound algorithm is used to solve the optimization model to obtain a CCUS system multi-cycle deployment optimization solution.

[0079] Preferably, the multi-period deployment optimization method of the CCUS system considering carbon tax incentives is characterized in that the optimization result of the carbon capture, utilization and storage system described in step S4 includes: annualized investment and operating costs, matching schemes of carbon emission source nodes and storage sink nodes, and the carbon capture amount of the carbon emission source nodes and the storage amount of the storage sink nodes.

[0080] The present invention optimizes the layout of a multi-period CCUS network from the perspective of a carbon tax incentive policy, taking into account different carbon tax prices and multi-period influencing factors, and constructs an optimization model for a multi-period carbon capture, utilization and storage network based on a carbon tax incentive policy with the objective function of minimizing the total annualized investment and operating cost. The optimization results of the CCUS network layout, carbon capture, carbon storage and various costs are obtained, ensuring the practicability of the optimization scheme. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 It is a flow chart of the present invention;

[0082] Figure 2 Comparison of various costs in various scenario cycles in a specific application embodiment of the present invention: (a) ERTm scenario, (b) TAXm scenario;

[0083] Figure 3 It is the optimization comparison of CCUS pipe network in each cycle in the specific application embodiment of the present invention;

[0084] Figure 4 The optimization result of carbon capture amount of each cycle of the emission source in the specific application embodiment of the present invention;

[0085] Figure 5 The optimization result of carbon sequestration amount of each cycle of the emission source in the specific application embodiment of the present invention; DETAILED DESCRIPTION

[0086] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0087] like Figure 1 As shown, the present invention provides a CCUS system multi-period deployment optimization method considering carbon tax incentives, comprising the following steps:

[0088] S1: Calculate the annual CO2 emissions of the carbon source according to the carbon dioxide emissions calculation formula, and use the basic data of the CCUS system to obtain the node data of the carbon source sink;

[0089] S2: According to the CCUS network structure parameters, network flow parameters, carbon source capture parameters, annual carbon emission reduction total, and CO2 capture compression technical parameters, the constraints of the multi-period deployment optimization model of the CCUS system based on the carbon tax incentive policy are constructed;

[0090] S3: Construct a multi-period deployment optimization model for CCUS system based on carbon tax incentive policy according to the constraint conditions and the objective function of minimizing the annualized total investment operating cost;

[0091] S4: Solve the multi-period deployment optimization plan of the CCUS system with the minimum annualized total investment and operating cost that meets the constraints.

[0092] In one embodiment, the carbon dioxide emission calculation formula in step S1 is calculated according to the carbon dioxide emission calculation formula of the Intergovernmental Panel on Climate Change for coal-fired power plants:

[0093] An=Cap*Capf*Hr*Emf*9.2427×10 -12 (1)

[0094] Where An is the annual carbon dioxide emissions of coal-fired units, 10 6 t; Cap is the capacity of the coal-fired unit, MW; Capf is the capacity factor; Hr is the heat rate of the coal-fired power plant, Btu / kWh; Emf is the emission factor;

[0095] In one embodiment, the basic data of the CCUS system described in step S1 includes the name of the power plant, longitude and latitude information, unit capacity, heat rate, emission coefficient, etc. After merging, screening and calculating the data, the node data of the carbon source sink is finally obtained;

[0096] In one embodiment, the constraints described in step S2 include flow constraints, emission source capture constraints, cycle annual carbon emission reduction target constraints, capture compression technology material combination and quantity constraints, storage sink storage constraints, pipeline cycle reuse constraints and decision variable value range constraints;

[0097] The flow constraints include a maximum flow constraint for a positive pipeline flow, a minimum flow constraint for a negative pipeline flow, and a node flow balance constraint;

[0098] The maximum flow constraint for the positive pipeline flow direction means that the pipeline flow of any candidate pipeline path p with a period diameter of d should not be greater than its maximum pipeline flow. The constraint formula is:

[0099]

[0100] In the formula, is the maximum flow rate of a pipe with a diameter of d, t / a; Q p,d,u is the pipeline flow rate of the candidate pipeline path p with a diameter of d in the uth period, t / a;

[0101] The minimum flow constraint for a pipeline with a negative flow direction means that since the candidate pipeline path is bidirectional, the pipeline flow may be negative, so the pipeline flow with a negative flow direction should not be greater than its maximum pipeline flow. The constraint formula is:

[0102]

[0103] The node flow balance constraint means that for any emission source and storage sink, the capture or storage volume of the node should be equal to the sum of its node inflow and outflow. The constraint formula is:

[0104] Emission sources:

[0105] Seal Exchange:

[0106] The emission source capture constraint means that the capture amount of the emission source in any period should be less than the maximum annual carbon dioxide emissions of the emission source. At the same time, in order to ensure the continuous and stable supply of the emission source, the capture amount of the current period should not be lower than the capture amount of the previous period. The constraint formula is:

[0107]

[0108] x i,u+1 ≥x i,u (7)

[0109] The cycle annual carbon emission reduction target constraint refers to the requirement that the total annual carbon emission reduction in each cycle within the region must meet the cycle annual carbon emission reduction target constraint. The constraint formula is:

[0110]

[0111] In the formula, Capt u Indicates the carbon emission reduction target for each period, t / a;

[0112] The aforementioned capture and compression technology material combination quantity constraint means that for any period of carbon dioxide emission source within the planning period, only one technology material combination process can be used to capture and compress carbon dioxide. The constraint formula is:

[0113]

[0114] The capture compression technology material combination constraint refers to the different carbon dioxide contents in flue gas from different types of emission sources. Different technology material combinations are suitable for different flue gas carbon dioxide contents. The constraint formula is:

[0115]

[0116] In the formula, Indicates the upper limit of flue gas carbon dioxide concentration applicable to each technical material combination k, %; Indicates the lower limit of flue gas carbon dioxide concentration applicable to each technical material combination k, %;

[0117] The storage capacity constraint of the storage sink refers to the need for the annual storage capacity of carbon dioxide in the storage sink to meet the continuous use of the reservoir during the project planning period. The constraint formula is:

[0118]

[0119] r j,u+1 -r j,u ≥0(12)

[0120] In the formula, represents the maximum storage capacity of reservoir j, t; r j,u represents the binary decision variable for activation of the storage sink j reservoir in period u, which is 1 when activated and 0 when not activated;

[0121] The pipeline cycle reuse constraint refers to the model requirement that only one pipeline of a specific diameter be built on the candidate pipeline path during the project planning period, and the built pipeline can be reused in subsequent cycles. The constraint formula is:

[0122]

[0123] Where η p,d A binary variable representing pipeline reuse with a candidate pipeline path of diameter d and p, which is 0 when the pipeline is built or reused and 1 when it is not built; A represents the number of optional pipe diameter options;

[0124] The other variable value range constraints include a i,u 、r j,u , b p,d,u 、z i,k,u , η p,d,u , the constraint formula is:

[0125] a i,u ∈{0,1}i∈I,u∈U(17)

[0126] r j,u ∈{0,1}j∈J,u∈U(18)

[0127] b p,d,u ∈{0,1}p∈P,d∈D,u∈U(19)

[0128] z i,k,u ∈{0,1}i∈I,k∈K,u=U(20)

[0129] η p,d ∈{0,1}p∈P,d∈D(21)

[0130] In one embodiment, the objective function described in step S3 is composed of flue gas dehydration cost, carbon dioxide capture and compression investment cost, carbon dioxide capture and compression operating cost, annual capital recovery of pipeline construction, annual pipeline operating cost, carbon dioxide storage cost, and carbon tax payment cost. The objective function formula is as follows:

[0131] min F=F W +F IC +F OC +F IPC +F OPC +F SC +F tax (twenty two)

[0132] Where, F is the total annualized investment and operating cost, RMB / a; F W is the annual flue gas dehydration cost of the emission source, RMB / a; F IC Compress the annual investment cost of carbon dioxide capture from emission sources, RMB / a; F OC The CO2 compression operating cost of the emission source, RMB / a; F IPC is the annualized investment cost of pipeline construction, RMB / a; F OPC is the annual operation cost of the pipeline, RMB / a; F SC is the annual storage cost of the storage exchange, RMB / a; F tax The annual carbon tax payment cost for emission sources, RMB / a;

[0133] The annual flue gas dehydration cost for the carbon tax incentive emission source is calculated based on the amount of carbon dioxide captured by the coal-fired power plant, as follows:

[0134]

[0135] Where v is the number of cycles u in the project planning period; s is the number of carbon dioxide emission sources; ε is the unit carbon dioxide dehydration cost of flue gas, yuan / t; x i,u is the annual carbon dioxide capture of emission source i in the uth cycle, t / a; int is the discount rate, which is 8% in the model; λ is the capital recovery coefficient during the project planning period; δ is the period annuity present value coefficient during the project planning period; T is the project planning period; is the cycle number of the uth cycle; T0 is the cycle duration;

[0136] The annualized investment cost of carbon dioxide capture and compression for emission sources under the carbon tax incentive policy is the annualized investment cost of new capture facilities and compression facilities, and the formula is as follows:

[0137]

[0138] In the formula, e is the number of technical material combinations; Calculate the parameters for the capture compression investment cost of the technology material combination k; i,k,u represents the capture binary decision variable for emission source i to adopt technology material combination k in period u, with a value of 1 when adopted and a value of 0 when not adopted; w i is the carbon dioxide content in the flue gas from emission source i, %; E i is the flue gas capture flow rate of emission source i, mol / s;

[0139] The annual operating cost of carbon dioxide capture and compression for the carbon tax incentive emission source is the operating cost of the capture device materials and the booster, and the formula is as follows:

[0140]

[0141] In the formula, Calculate the parameters for the capture compression operating cost of the technical material combination k;

[0142] The annualized investment cost of the carbon tax incentive policy pipeline construction is the annuity present value of the pipeline construction investment within the period, and the formula is as follows:

[0143]

[0144] Where g is the number of candidate pipelines; q is the number of pipeline diameters; b p,d,u Indicates the binary decision variable for pipeline construction in the uth cycle, where the candidate path is p and the diameter is d. It is 1 when the pipeline is constructed and 0 when it is not constructed. p is the length of the candidate pipeline path p, km; CB d is the construction cost per unit length of a pipeline with a diameter of d, RMB / km;

[0145] The annual operating cost of the carbon tax incentive policy pipeline is as follows:

[0146]

[0147] The annual storage cost of the carbon tax incentive policy storage sink is the storage cost or increased production income generated by the storage sink node by storing carbon dioxide in the reservoir, and the formula is as follows:

[0148]

[0149] Where r is the amount of carbon dioxide storage sink; y j,u is the annual carbon dioxide storage capacity of sink node j in the uth cycle, t / a; CR j represents the unit carbon dioxide storage / utilization cost of sink node j, RMB / t;

[0150] The annual carbon tax payment cost of the emission source under the carbon tax incentive policy is the tax cost levied on the emission source node directly emitting carbon dioxide into the atmosphere. The formula is as follows:

[0151]

[0152] In the formula, tax u is the carbon tax rate in cycle u, yuan / t; is the maximum annual carbon dioxide emission of emission source i, t / a;

[0153] The symbols of formulas (1) to (31) are shown in Tables 1 and 2.

[0154] Table 1 Index and set of CCUS pipeline network multi-period optimization models based on carbon tax incentive policy

[0155] i∈I Carbon source collection j∈J Carbon sink n∈N Node collection of carbon sources and sinks k∈K Carbon dioxide capture technology materials portfolio p∈P A collection of candidate pipeline paths d∈D Pipe diameter collection u∈U Period collection within the project planning period

[0156] Table 2 Parameters of CCUS pipeline network multi-period optimization model based on carbon tax incentive policy

[0157]

[0158]

[0159] In one embodiment, the optimization model in step S4 is solved by using a branch and bound method. A periodic carbon emission reduction target constraint is set, and the same carbon emission reduction target is achieved by adjusting the periodic carbon tax rate.

[0160] In one embodiment, the multi-gas source network operation scheduling optimization results described in step S4 include: annualized investment and operating costs, carbon capture, utilization and storage pipelines, and carbon capture and storage volumes under two different model scenarios (ERTm and TAXm).

[0161] To further illustrate this method, a CCUS system in Northwest China was used as a research example to conduct a multi-cycle CCUS system deployment optimization study. The system includes 36 carbon emission source nodes and 33 storage sink nodes, where the storage sink node reservoir types include ECBM coal seams, deep saline aquifers, depleted gas fields, and EOR reservoirs. The carbon emission source node parameters are shown in Table 3, and the storage sink node parameters are shown in Table 4.

[0162] Table 3 Carbon emission source node parameters of a CCUS system in Northwest China

[0163]

[0164]

[0165] Table 4 Storage sink node parameters of a CCUS system in Northwest China

[0166]

[0167]

[0168] The planning period of the CCUS system is 40 years, which is divided into 8 cycles. The annual carbon emission reduction targets for different cycles are shown in Table 5.

[0169] Table 5 Carbon emission reduction targets for different periods

[0170]

[0171] The carbon tax rates in different periods are shown in Table 6.

[0172] Table 6 Carbon tax rates at different periods

[0173]

[0174] The unit storage cost and annual compound interest coefficient of different reservoir types are shown in Table 7.

[0175] Table 7 Cost related parameters

[0176]

[0177] The annualized investment and operating cost optimization results obtained by solving this specific application example are as follows Figure 2 The annual flue gas dehydration cost, annualized investment cost of capture compression, annualized operating cost of capture compression, annualized investment cost of pipeline construction, and annual operating cost of pipelines under the ERTm scenario are summarized as follows: Figure 2 As shown in (a): In the u2 period, due to the need to consider the need for pipeline reuse in the subsequent cycles, and under the condition of ensuring the continuous and stable supply of carbon emission sources, the dehydration and compression costs are similar to those of u1 and u2. Since the pipeline construction in u1-u4 can basically meet the carbon emission reduction target in the u5 period, the capture cost is significantly higher than the annual flue gas dehydration cost and capture and compression cost in the same period. In the ERTm scenario, the flue gas dehydration cost, the annual operating cost of capture and compression, and the annualized investment cost are the main parts of the total system cycle cost, accounting for 73.4-91% of the total system cycle cost. As the cycle carbon capture target increases, the cost also gradually increases accordingly. The annualized investment and operating cost of the u1 cycle is 9.51×10 9 Yuan; the annualized investment and operating cost of the u2 cycle is 1.18×10 10 Yuan; the annualized investment and operating cost of the u3 cycle is 1.04×10 10 Yuan; the annualized investment and operating cost of the u4 cycle is 1.28×10 10 Yuan; the annualized investment and operating cost of the u5 cycle is 2.06×10 10Yuan; the annualized investment and operating cost of the u6 cycle is 3.34×10 10 Yuan; the annualized investment and operating cost of the u7 cycle is 4.02×10 10 Yuan; the annualized investment and operating cost of the u8 cycle is 5.31×10 10 Yuan; Annual flue gas dehydration cost, annualized investment cost of capture compression, annualized operating cost of capture compression, annualized investment cost of pipeline construction, annual operating cost of pipeline, etc. in each cycle under TAXm scenario Figure 2 (b) As shown. Similar to the ERTm scenario, in period u2, due to the need to consider the need for pipeline reuse in subsequent cycles, and under the condition of ensuring the continuous and stable supply of carbon emission sources, the dehydration and compression costs are similar to u1 and u2. Since the pipeline construction in u1-u4 can basically meet the carbon emission reduction target in period u5, the capture cost is significantly higher than the annual flue gas dehydration cost and capture and compression cost in the same period. In the TAXm scenario, the annual carbon tax payment cost of the system accounts for the main part of the annual capital cost, accounting for 47.81-81.48% of the total system cycle cost, of which only a small part of the total system cycle cost in periods u7 and u8, 31.62 and 6.67% respectively, mainly because most of the carbon dioxide emission sources have been carbon captured and stored. Due to the addition of the carbon tax collection policy, the annual investment and operating cost of the system is relatively stable, but in the early stage of carbon emission reduction, the emission reduction cost will be higher than the project investment in the ERTm scenario.

[0178] Carbon capture, utilization and storage networks in different cycles Figure 3 As shown in the figure, it can be seen that the carbon capture, utilization and storage pipelines in the three cycles u1-u3 are almost the same, which also confirms the change in related costs. The main reason for this phenomenon is that the system needs to maintain a continuous and stable supply of carbon dioxide from carbon emission sources, even if the carbon emission reduction target of the u2 cycle is slightly lower, it can maintain a stable supply of carbon dioxide. As the carbon emission reduction target increases year by year in the later period, the complexity of the pipeline network gradually increases, and the pipeline network layout is carried out based on the carbon emission source cluster. The model decision tends to store carbon dioxide in the EOR reservoirs and ECBM coal seams that are stored and utilized, to obtain the benefits of increased oil and coalbed methane production, and balance the system cost.

[0179] The number and diameter of pipelines constructed and applied in each period are summarized as shown in Table 8. It can be seen from the table that as the carbon emission reduction target gradually increases, the proportion of pipelines with larger diameters gradually increases. In the period with smaller carbon emission reduction targets, the model also tends to build pipelines with larger diameters to prepare for the capture and storage of large amounts of carbon dioxide in the later period.

[0180] Table 8 Number and diameter of pipes used in each cycle

[0181]

[0182] The carbon capture amount in each cycle is as follows: Figure 4 As shown in the figure, the locations of carbon capture in the u1-u3 cycles are almost the same. After the u3 cycle, due to the increase in the carbon reduction target, other carbon emission sources also reduced carbon emissions accordingly. The total carbon capture in the u1, u2, and u3 cycles is 4.59×10 7 tons; the total carbon capture in the u4 cycle is 6.23×10 7 tons; the total carbon capture in the u5 cycle is 8.96×10 7 tons; the total carbon capture in the u6 cycle is 1.28×10 8 tons; the total carbon capture in the u7 cycle is 1.77×10 8 tons; the total carbon capture in the u8 cycle is 2.37×10 8 ton.

[0183] The carbon storage amount in each cycle is as follows: Figure 5 As shown in the figure, the carbon storage sites in cycles u1-u3 are almost the same. After cycle u3, due to the increase in carbon emission reduction targets, the existing carbon storage sites are not enough to support the carbon storage volume within the project planning period. Therefore, cycle u4 uses the c5 storage sink for carbon dioxide geological storage, and the annual carbon dioxide storage volume is 6.23×10 7 In the period when the capture target is small, CO2 geological storage tends to be stored in EOR oil reservoirs and ECBM coal seam utilization sites. When the carbon emission reduction target increases, due to the capacity limitation of the utilization site, CO2 geological storage tends to be stored in deep saline aquifers with larger capacity.

[0184] The above is only an example of the embodiment of the present specification and is not intended to limit the embodiment of the present specification. For those skilled in the art, the embodiment of the present specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiment of the present specification shall be included in the scope of the claims of the embodiment of the present specification.

Claims

1. A multi-period deployment optimization method for CCUS system considering carbon tax incentives, characterized in that: The following steps are involved: S1: Collect CCUS system carbon emission data, node data and basic data; S2: Construct the constraints of the multi-period deployment optimization model of CCUS system based on carbon tax incentives; The constraints include flow constraints, emission source capture constraints, cycle annual carbon emission reduction target constraints, capture compression technology material combination and quantity constraints, storage sink storage constraints, pipeline cycle reuse constraints and decision variable value range constraints; The flow constraints include maximum flow constraints, minimum flow constraints, and node flow balance constraints; The maximum flow constraint states that any pipeline flow is less than the maximum flow required by the pipeline design. The constraint formula is: In the formula, is the maximum flow rate of a pipe with a diameter of d; Q p,d,u is the pipeline flow rate of the candidate pipeline path p with a diameter of d in the uth period; The pipeline minimum flow constraint stipulates that the pipeline flow is greater than the minimum flow required by the pipeline design. The constraint formula is: The node flow balance constraint stipulates that the capture and storage capacity of any emission source and storage sink node should be equal to the sum of its node inflow and outflow. The constraint formula is: Emission sources: Seal Exchange: The emission source capture constraint stipulates that the emission source capture should be less than the maximum annual carbon dioxide emissions of the emission source, and the capture in the current cycle is greater than the capture in the previous cycle. The constraint formula is: x i,u+1 ≥x i,u The cycle annual carbon emission reduction target constraint stipulates that the total annual carbon capture amount in each cycle in the region meets the cycle annual carbon emission reduction target. The constraint formula is: In the formula, Capt u Indicates the carbon emission reduction target for each period, t / a; The aforementioned capture and compression technology material combination quantity constraint stipulates that a carbon dioxide emission source can only use one technology material to capture and compress carbon dioxide. The constraint formula is: The capture compression technology material combination constraint formula is: In the formula, Indicates the upper limit of flue gas carbon dioxide concentration applicable to each technical material combination k, %; Indicates the lower limit of flue gas carbon dioxide concentration applicable to each technical material combination k, %; The storage capacity constraint of the storage sink stipulates that the annual storage capacity of carbon dioxide in the storage sink must meet the reservoir use demand. The constraint formula is: r j,u+1 -r j,u ≥0 In the formula, represents the maximum storage capacity of reservoir j, t; r j,u represents the binary decision variable for activation of the storage sink j reservoir in period u, which is 1 when activated and 0 when not activated; The pipeline cycle reuse constraint regulation model requires that only one pipeline with a specific diameter be built on the candidate pipeline path during the project planning period, and the built pipeline can be reused in subsequent cycles. The constraint formula is: Where η p,d A binary variable representing pipeline reuse with a candidate pipeline path of diameter d and p, which is 0 when the pipeline is built or reused and 1 when it is not built; A represents the number of optional pipe diameter options; The decision variable value range constraint formula is: a i,u ∈{0,1}i∈I,u∈U r j,u ∈{0,1}j∈J,u∈U b p,d,u ∈{0,1}p∈P,d∈D,u∈U z i,k,u ∈{0,1}i∈I,k∈K,u=U or p,d ∈{0,1}p∈P,d∈D S3: Construct a multi-period deployment optimization model of CCUS system based on carbon tax incentives according to the constraint conditions and the objective function of minimizing the annualized total investment and operating cost; S4: Solve the model to obtain the multi-period deployment optimization plan of the CCUS system with the minimum annualized total investment and operating cost.

2. A CCUS system multi-period deployment optimization method considering carbon tax incentives as claimed in claim 1, characterized in that: The CCUS system described in step S1 is composed of a carbon emission source node and a storage sink node. The carbon emission data is carbon dioxide emissions, and the calculation formula is: An=Cap*Capf*Hr*Emf*9.2427×10 -12 Where An is the annual carbon dioxide emissions of coal-fired units, 10 6 t; Cap is the capacity of the coal-fired unit, MW; Capf is the capacity factor; Hr is the heat rate of the coal-fired power plant, Btu / kWh; Emf is the emission factor; The node data are the longitude and latitude coordinates of the carbon emission source nodes and the storage sink nodes; The basic data include carbon capture compression technical parameters, pipeline construction cost parameters, storage unit cost, annual compound interest coefficient and system planning period.

3. A CCUS system multi-period deployment optimization method considering carbon tax incentives as claimed in claim 1, characterized in that: The objective function described in step S3 is composed of flue gas dehydration cost, carbon dioxide capture and compression investment cost, carbon dioxide capture and compression operating cost, annual capital recovery of pipeline construction, annual pipeline operating cost, carbon dioxide storage cost, and carbon tax payment cost. The objective function formula is: min F=F W +F IC +F OC +F IPC +F OPC +F SC +F tax Where, F is the total annualized investment and operating cost, RMB / a; F W is the annual flue gas dehydration cost of the emission source, RMB / a; F IC Compress the annual investment cost of carbon dioxide capture from emission sources, RMB / a; F OC The CO2 compression operating cost of the emission source, RMB / a; F IPC is the annualized investment cost of pipeline construction, RMB / a; F OPC is the annual operation cost of the pipeline, RMB / a; F SC is the annual storage cost of the storage exchange, RMB / a; F tax The annual carbon tax payment cost for emission sources, RMB / a; The annual flue gas dehydration cost calculation formula for the carbon tax incentive policy emission source is: Where v is the number of cycles u in the project planning period; s is the number of carbon dioxide emission sources; ε is the unit carbon dioxide dehydration cost of flue gas; x i,u is the annual carbon dioxide capture of emission source i in the uth cycle; int is the discount rate; λ is the capital recovery coefficient during the project planning period; δ is the period annuity present value coefficient during the project planning period; T is the project planning period; is the cycle number of the uth cycle; T0 is the cycle duration; The annualized investment cost calculation formula for carbon dioxide capture compression of emission sources under the carbon tax incentive policy is: In the formula, e is the number of technical material combinations; Calculate the parameters for the capture compression investment cost of the technology material combination k; i,k,u represents the capture binary decision variable for emission source i to adopt technology material combination k in period u, with a value of 1 when adopted and a value of 0 when not adopted; w i is the carbon dioxide content in the flue gas from emission source i; E i is the flue gas capture flow rate of emission source i; The formula for calculating the annual operating cost of carbon dioxide capture compression for emission sources under the carbon tax incentive policy is: In the formula, Calculate the parameters of the captured compressed operating costs for the technical material combination k; The formula for calculating the annualized investment cost of the carbon tax incentive policy pipeline construction is: Where g is the number of candidate pipelines; q is the number of pipeline diameters; b p,d,u Indicates the binary decision variable for pipeline construction in the uth cycle, where the candidate path is p and the diameter is d. It is 1 when the pipeline is constructed and 0 when it is not constructed. p is the length of the candidate pipeline path p; CB d is the construction cost per unit length of a pipeline with a diameter of d; The formula for calculating the annual operating cost of the carbon tax incentive policy pipeline is: The annual storage cost of the carbon tax incentive policy storage sink is the storage cost or production increase income generated by the storage sink node by storing carbon dioxide in the reservoir: Where r is the amount of carbon dioxide storage sink; y j,u is the annual carbon dioxide storage capacity of sink node j in the uth cycle; CR j represents the unit CO2 storage / utilization cost of sink node j; The calculation formula for the annual carbon tax payment cost of the emission sources under the carbon tax incentive policy is: In the formula, tax u is the carbon tax rate for period u; is the maximum annual carbon dioxide emission of emission source i.

4. A CCUS system multi-period deployment optimization method considering carbon tax incentives as claimed in claim 1, characterized in that: The model solving steps in step S4 are as follows: S401: Delaunay triangulation algorithm is used to determine the matching scheme of each carbon emission source node and storage sink node in the CCUS system; S402: Determine the pipe diameter between the carbon emission source node and the storage sink node in combination with the node flow data, and calculate the CCUS system construction cost; S403: Based on the objective function and constraint conditions of the CCUS system multi-cycle deployment optimization model, a branch and bound algorithm is used to solve the optimization model to obtain a CCUS system multi-cycle deployment optimization solution.

5. A CCUS system multi-period deployment optimization method considering carbon tax incentives as claimed in claim 1, characterized in that: The optimization results of the carbon capture, utilization and storage system described in step S4 include: annualized investment and operating costs, matching schemes of carbon emission source nodes and storage sink nodes, and the carbon capture amount of carbon emission source nodes and the storage amount of storage sink nodes.

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