Coal power carbon emission reduction path optimization method based on multi-objective constraint

Abstract

The invention relates to a coal power carbon emission reduction path optimization method based on multi-objective constraint, which belongs to the field of power system transformation, and comprises the following steps: calculating the service life parameter of an active service unit by adopting a unit decommissioning algorithm module, and eliminating units with the service life parameter lower than the service life parameter; and a carbon emission reduction technology optimization algorithm module is adopted to generate a carbon emission reduction technology transformation scheme on the basis of the remaining units, and an optimal carbon emission reduction technology transformation scheme is searched through continuous iteration of a simulated annealing algorithm. According to the invention, the scale of a decommissioning unit is determined through a unit decommissioning algorithm module, and installed capacity change conditions such as total installed capacity / newly-added installed capacity / decommissioning installed capacity of various coal power units are obtained; and solving through a carbon emission reduction technology optimization algorithm module to obtain a coal-electricity low-carbon transformation path layout, a carbon emission reduction amount of a coal-electricity low-carbon transformation path, and investment cost, operation and maintenance cost, carbon reduction cost and the like of a carbon emission reduction technology in a planning period, and a series of external constraint conditions such as energy safety, economic development, policy carbon reduction target and the like are considered.

Description

Technical Field

[0001] The present invention belongs to the field of power system transformation, and in particular relates to a method for optimizing coal-fired power carbon emission reduction paths based on multi-objective constraints. Background Art

[0002] The large-scale retirement of coal-fired power units will not only cause the power system's rotational inertia to further decrease, but will also lead to a large-scale waste of resources and stranded coal-fired power assets. The transition to clean energy is too fast, which may eventually have catastrophic consequences. The new power system needs to be guided in advance to ensure the system's inertia adequacy. This shows that the research on the functional transformation of coal-fired power units has practical significance for the safe and stable operation of the power system.

[0003] A large number of studies and calculations have demonstrated that the use of carbon reduction technology can achieve the carbon reduction goals of my country's coal-fired power generation industry to a certain extent. For example, the invention patent application with application publication number CN117172021A discloses a method for optimizing the functional transformation of coal-fired power units considering the inertia support of the power system. The invention first selects the candidate units that meet the retirement capacity in the power system according to the proposed retirement plan of the coal-fired power units; then, based on the minimum inertia demand value of the system constrained by frequency safety, determines the unit capacity that needs to be functionally transformed to support the system inertia level among the candidate units, that is, the inertia target value; then determines the functional transformation coal-fired power units, that is, the transformed units, and finally performs flexibility transformation on the transformed units to further reduce their minimum technical output, and encourages them to provide inertia support for the system under the incentive of inertia auxiliary services.

[0004] However, the low-carbon transformation of the coal-fired power industry is a long process, which involves complex decision-making issues, including the construction of new units, unit shutdowns, large-scale and small-scale (large-scale and small-scale is a policy measure in the power industry, which aims to achieve energy conservation and emission reduction and improve energy efficiency by building new large-capacity, high-parameter, low-consumption and low-emission power generation units and shutting down some small thermal power units at the same time) and the application of carbon emission reduction technology transformation of units. At the same time, a series of external constraints such as energy security, economic development and relevant carbon emission reduction policy goals must also be taken into account. Therefore, how to effectively integrate these issues into the development plan of the low-carbon power system, and formulate a decision-making model that conforms to the development process of the coal-fired power system and a coal-fired power carbon emission reduction path optimization algorithm based on multi-objective constraints is a key step in exploring the low-carbon development of coal-fired power. Summary of the invention

[0006] The purpose of the present invention is to provide a coal-fired power carbon emission reduction path optimization method based on multi-objective constraints to solve the problems that existing low-carbon transformation plans are unable to adapt to complex decision-making problems and are unable to take into account a series of external constraints such as energy security, economic development and carbon emission reduction policy goals.

[0007] In order to solve the above technical problems, the present invention provides a method for optimizing the coal-fired power carbon emission reduction path based on multi-objective constraints, which comprises the following steps:

[0008] S1. Use the unit retirement algorithm module to calculate the life parameters of the active units, and eliminate the units whose life parameters are lower than the set life parameter upper limit and the units required to be eliminated by the policy;

[0009] S2. The carbon emission reduction technology optimization algorithm module is used to generate carbon emission reduction technology transformation plans based on the retained and newly added units, and the most economical carbon emission reduction technology transformation plan is continuously iterated through the simulated annealing algorithm.

[0010] Preferably, the calculation formula for calculating the life parameters of the active units in the unit retirement algorithm module in S1 is:

[0011]

[0012] Among them, S age,j is the life parameter of unit j; Plan Re is the planned retirement year of the unit, P k Start year for planning j is the commissioning time of unit j.

[0013] Preferably, the objective function of the carbon emission reduction technology optimization algorithm module in S2 is:

[0014]

[0015] in, is the minimum carbon reduction cost, which means that k The carbon emission reduction cost after the most economical combination of carbon emission reduction technologies is adopted for the unit during the period; T i is the carbon emission reduction technology numbered i; U j For the unit of unit type j, Un j is a single unit in unit class j, It is technology i In the crew class U j The applicable installed capacity, P k Period Technology i In the unit U j The carbon reduction potential can be obtained For technology i In the unit U j The unit capacity investment cost on the basis of For technology i Technical lifespan, For technology i Applicable to unit type U jThe change in unit operation and maintenance cost when For technology i Applicable to unit type U j variable costs at the time of

[0016] The carbon emission reduction technology optimization algorithm module generates a carbon emission reduction technology transformation plan by following the above objective function, indicating that P k The carbon reduction cost is lowest when the corresponding carbon reduction technology combination is used on a single unit j during the period.

[0017] Preferably, the calculation formula of the variable cost includes:

[0018]

[0019]

[0020] in, For technology i In the crew class U j The applicable installed capacity, is the average annual utilization hours of unit type j, For unit type U j Application Technology i The change value of the power consumption rate of the rear unit, For unit type U j The average annual coal consumption for power generation is For unit type U j The auxiliary power consumption rate, For unit type U j Application Technology i Auxiliary power saving rate of the rear unit, P ES is the energy storage cost, E ES is the annual storage and discharge capacity of energy storage, CAP ES Installed capacity for energy storage technology, UUH ES is the annual operation time of the energy storage device, η ES For the storage and discharge efficiency of energy storage technology, For technology i In the crew class U j The change in coal consumption of the unit after the above application, P coal is the standard coal price, η pun is the efficiency penalty for coal-fired power units using biomass co-firing technology, η bio is the biomass blending rate of coal-fired power units, H coal is the calorific value of standard coal, H bio is the calorific value of biomass, P bio is the biomass price, η bio is the biomass blending rate of coal-fired power units, η pun Efficiency penalty for applying biomass co-firing technology to coal-fired power plants, EMPP is the annual carbon emission of the unit, η ccs is the capture efficiency of coal-fired power units coupled with CCS technology, σ ab The consumption of absorbent for capturing 1 ton of carbon dioxide by CCS technology, P ab is the price of CCS absorbent, P tran&stor is the price of transport and storage of unit carbon dioxide, σ energy The coal consumption for capturing energy of CCS technology;

[0021] According to the optimization technology T i , select formula (3)-formula (7) and optimization technology T i Corresponding calculation formula Calculation technology T i In the crew class U j variable costs.

[0022] Preferably, the carbon emission reduction technology optimization algorithm module in S2 needs to meet the following constraints when generating the carbon emission reduction technology transformation plan:

[0023] The algorithm expression of carbon emission reduction target constraint is:

[0024]

[0025] Among them, EM new is the annual carbon emission of the newly added units, EM old To preserve the annual carbon emissions of the unit, The maximum permissible emissions from the coal-fired power industry at the end of the planning period. The CAP is the maximum carbon emission that all units participating in the technical transformation can achieve through technical transformation during the planning period. new For the installed capacity of the newly added units, UUH system is the industry average utilization hours, Spcr new is the average power consumption rate of the newly added units, β new is the coal consumption of the newly added units, CAP old In order to retain the installed capacity of the unit, Spcr old To retain the average power consumption rate of the unit, β old To retain the average coal consumption for power generation of the unit, k is the IPCC recommended calculated value of carbon dioxide emissions per ton of standard coal;

[0026] The algorithm expression of technology weight constraint is:

[0027]

[0028] Among them, P k is the application discrimination value of technology i on a single unit j, “1” represents that the unit has been modified, and “0” represents that the unit has not been modified;

[0029] The algorithm expression of energy efficiency constraint is:

[0030]

[0031] in, is the coal consumption of power supply of a single unit j after the end of the planning period; For a single unit j, the maximum power supply coal consumption can be reduced by technical transformation within the planning period; It is the benchmark level of coal consumption for power supply of single unit j at the end of the planning period.

[0032] Preferably, the carbon emission reduction technology optimization algorithm module in S2 continuously iterates to find the optimal carbon emission reduction technology transformation plan through the simulated annealing algorithm in the following specific steps:

[0033] Step 1. Read the units retained and newly added after the elimination operation of the unit decommissioning module;

[0034] Step 2. Read the total carbon reduction and total cost;

[0035] Step 3. Carry out technical transformation of the retained units and / or additional units to form a carbon emission reduction technical transformation plan;

[0036] Step 4. Calculate the total technical transformation potential of the resulting carbon emission reduction technical transformation plan Total Cost And the coal consumption of each unit after transformation

[0037] Step 5. Determine whether the power supply coal consumption exceeds the set threshold. If so, iterate and update the carbon emission reduction technology transformation plan and return to step 2; if not, proceed to step 6;

[0038] Step 6. Calculate the unit carbon emission reduction cost of the carbon emission reduction technology transformation plan, and determine whether technical transformation is needed in combination with the total potential of technical transformation. If compared with the initial plan, the unit carbon emission reduction cost and the total potential of technical transformation of the carbon emission reduction technology transformation plan are not reduced at the same time, determine whether the carbon emission reduction technology transformation plan is acceptable according to the Metropolis acceptance criteria. If acceptable, update the carbon emission reduction technology transformation plan and return to step 2. If unacceptable, reduce the randomness in the process of searching for the optimal solution and reset the number of iterations before returning to step 2. If compared with the initial plan, the unit carbon emission reduction cost and the total potential of technical transformation of the carbon emission reduction technology transformation plan are reduced at the same time, determine that the carbon emission reduction technology transformation plan is the optimal plan, and output the carbon emission reduction technology transformation plan.

[0039] Preferably, the total potential of technical transformation in step 4 is calculated by first calculating the application of each technology in unit type U j The carbon reduction potential is then applied to the unit type Uj The carbon emission reduction potential obtained above is added to form the total technical transformation potential of the technical transformation combination plan;

[0040] The above technologies are applied in the unit type U j The algorithm formula for the carbon reduction potential obtained includes:

[0041]

[0042] Select the corresponding algorithm formula according to the technology type and calculate the application of each technology in the unit type U j the carbon reduction potential achieved on

[0043] in, For technology i Applicable to unit type U j the carbon reduction potential achieved on For technology i In the crew class U j The applicable installed capacity, For unit type U j Installed capacity, For technology i In the crew class U j The scale has been applied to is the average annual utilization hours of unit type j, For technology i In the crew class U j The change in coal consumption for power generation after the above application, k is the IPCC recommended calculated value for carbon dioxide emissions per ton of standard coal, For technology i In the crew class U j After the above application, the change in the plant power consumption rate of the unit is: For unit type U j The average annual coal consumption for power generation is For unit type U j The auxiliary power consumption rate, For technology i After application on unit type j, the auxiliary power saving rate of the unit is η bio is the biomass blending rate of coal-fired power units, η pun is the efficiency penalty for coal-fired power units using biomass co-firing technology, η ccs is the capture efficiency of coal-fired power units coupled with CCS technology, η EN is the net capture efficiency of the CCS technology;

[0044] The algorithm formula for the total carbon emission reduction potential of the technical transformation is:

[0045]

[0046] in, For unit type U j The total carbon emission reduction potential of technological transformation.

[0047] Preferably, the algorithm formula of the total cost in step 4 is:

[0048]

[0049] in, For unit type U j The total carbon reduction cost after applying the adopted carbon reduction technology solutions, For technology i In the crew class U j Applicable installed capacity, For technology i The unit capacity investment cost on unit type j, r is the discount rate, For technology i Technical lifespan, For technology i Applicable to unit type U j The change in unit operation and maintenance cost on For technology i Applicable to unit type U j The variable cost at For technology i Application in unit type U j The carbon reduction potential achieved.

[0050] Preferably, the algorithm formula for the power supply coal consumption after the technical transformation of the unit in step 4 is:

[0051]

[0052] in, is the coal consumption of power supply of a single unit j after the end of the planning period; is the coal consumption of unit j before the planning period (when k = 1, it is the coal consumption of unit U nj is the coal consumption for power supply before technical transformation); For a single unit j, the maximum power supply coal consumption can be reduced through technical transformation within the plan.

[0053] Preferably, the algorithm formula for the unit carbon emission reduction cost in step 6 is:

[0054]

[0055] in, For technology i Applicable to unit type U j The unit carbon reduction cost after For technology i In the crew class Uj Applicable installed capacity, For technology i The unit capacity investment cost on unit type j, r is the discount rate, For technology i Technical lifespan, For technology i In the crew class U j The change in unit operation and maintenance cost on For technology i In the crew class U j The variable cost, Corresponding technology i Application in unit type U j Carbon emissions reductions achieved.

[0056] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:

[0057] The present invention determines the scale of retired units within the planning period through the unit decommissioning algorithm module, and the remaining unit data will be input into the carbon emission reduction technology optimization algorithm module. The carbon emission reduction technology optimization algorithm module is guided by the economic and environmental goals, that is, it seeks to minimize the carbon emission reduction cost of the coal-fired power industry within the planning period; the optimization results solved by the algorithm model include changes in installed capacity such as total installed capacity / newly added installed capacity / retired installed capacity of various types of coal-fired power units, the layout of various coal-fired power low-carbon transformation paths, the total amount of carbon emission reduction of various coal-fired power low-carbon transformation paths, the total cost of carbon emission reduction of various coal-fired power low-carbon transformation paths during the planning period, and the application of various carbon emission reduction technologies in various types of coal-fired power units. It can adapt to complex decision-making problems while taking into account a series of external constraints such as energy security, economic development and relevant carbon emission reduction policy objectives. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 This is the operation flow chart of the coal-fired power carbon emission reduction path optimization method based on multi-objective constraints;

[0059] Figure 2 Workflow diagram of the algorithm module for optimizing carbon emission reduction technology. DETAILED DESCRIPTION

[0060] The present invention is described in detail below, and the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only 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.

[0061] See attached Figure 1As shown, the present embodiment involves a method for optimizing the coal-fired power carbon emission reduction path based on multi-objective constraints. The method is implemented based on a unit retirement algorithm module and a carbon emission reduction technology optimization algorithm module, and specifically includes the following steps:

[0062] S1. The unit retirement algorithm module is used to calculate the life parameters of the active units, and the units whose life parameters are lower than the life parameters and policy requirements are eliminated. In this embodiment, the upper limit of the life parameter is 0.8, and the calculation formula for calculating the life parameters of the active units is:

[0063]

[0064] Among them, S age,j is the life parameter of unit j; Plan Re is the planned retirement year of the unit, P k Start year for planning j is the commissioning time of unit j.

[0065] S2. The carbon emission reduction technology optimization algorithm module is used to generate carbon emission reduction technology transformation plans based on the remaining units, and the optimal carbon emission reduction technology transformation plan is continuously iterated through the simulated annealing algorithm.

[0066] The objective function of the carbon emission reduction technology optimization algorithm module is:

[0067]

[0068] in, is the minimum carbon reduction cost, which means that k The carbon emission reduction cost after the most economical combination of carbon emission reduction technologies is adopted for the unit during the period; T i is the technology numbered i; U j For the unit of unit type j, Un j is a single unit in unit class j, It is technology i In the crew class U j The applicable installed capacity, P k Period Technology i In the unit U j The carbon reduction potential available For technology i In the unit U j The unit capacity investment cost on the basis of For technology i Technical lifespan, For technology i Applicable to unit type U j The change in unit operation and maintenance cost when For technologyi Applicable to unit type U j variable costs at the time of

[0069] Among them, variable costs The algorithm formula includes:

[0070]

[0071] in, For technology i In the crew class U j The applicable installed capacity, is the average annual utilization hours of unit type j, For unit type U j Application Technology i The change value of the power consumption rate of the rear unit, For unit type U j The average annual coal consumption for power generation is For unit type U j The auxiliary power consumption rate, For unit type U j Application Technology i Auxiliary power saving rate of the rear unit, P ES is the energy storage cost, E ES is the annual storage and discharge capacity of energy storage, CAP ES Installed capacity for energy storage technology, UUH ES is the annual operation time of the energy storage device, η ES For the storage and discharge efficiency of energy storage technology, For technology i In the crew class U j The change in coal consumption of the unit after the above application, P coal is the standard coal price, η pun is the efficiency penalty for coal-fired power units using biomass co-firing technology, η bio is the biomass blending rate of coal-fired power units, H coal is the calorific value of standard coal, H bio is the calorific value of biomass, P bio is the biomass price, η bio is the biomass blending rate of coal-fired power units, η pun Efficiency penalty for applying biomass co-firing technology to coal-fired power plants, EM PP is the annual carbon emission of the unit, η ccs is the capture efficiency of coal-fired power units coupled with CCS technology, σ ab The consumption of absorbent for capturing 1 ton of carbon dioxide by CCS technology, P ab is the price of CCS absorbent, P tran&stor is the price of transport and storage of unit carbon dioxide, σ energyis the coal consumption of the capture energy consumption of CCS technology; according to the selected optimization technology T i , select formula (3)-formula (7) and optimization technology T i Corresponding calculation formula Calculation technology T i Applicable to unit type U j variable costs at the time.

[0072] The above carbon emission reduction technology optimization algorithm module follows the above objective function when generating carbon emission reduction technology transformation plans, indicating that in P k When this carbon emission reduction technology transformation plan is adopted during this period, the carbon reduction cost of single unit j is the lowest.

[0073] The carbon reduction technology optimization algorithm module also meets the following constraints when generating carbon reduction technology transformation plans:

[0074] 1) The algorithm expression of carbon emission reduction target constraint is:

[0075]

[0076] Among them, EM new is the annual carbon emission of the newly added units, EM old To preserve the annual carbon emissions of the unit, The maximum permissible emissions from the coal-fired power industry at the end of the planning period. The CAP is the maximum carbon emission that all units participating in the technical transformation can achieve through technical transformation during the planning period. new For the installed capacity of the new units, UUH system is the industry average utilization hours, Spcr new is the average power consumption rate of the newly added units, γ new is the coal consumption of the newly added units, CAP old In order to retain the installed capacity of the unit, Spcr old To retain the average power consumption rate of the unit, γ old To retain the average coal consumption for power generation of the unit, k is the IPCC recommended calculated value of carbon dioxide emissions per ton of standard coal;

[0077] 2) The algorithm expression of technology weight constraint is:

[0078]

[0079] Among them, P k is the application discrimination value of technology i on a single unit j, “1” represents that the unit has been modified, and “0” represents that the unit has not been modified;

[0080] 3) The algorithm expression of energy efficiency constraint is:

[0081]

[0082] in, is the coal consumption of power supply of a single unit j after the end of the planning period; For a single unit j, the maximum power supply coal consumption can be reduced by technical transformation within the planning period; It is the benchmark level of coal consumption for power supply of single unit j at the end of the planning period.

[0083] This embodiment adopts three types of improved technologies: energy-saving and efficiency-enhancing technology, CCS technology and biomass blending technology. i Taking the example of coal-fired power low-carbon transformation planning optimization system as an example, the application process is further explained.

[0084] See attached Figure 1 As shown, the application process of the coal-fired power low-carbon transformation planning optimization system is as follows:

[0085] Scenario setting: including basic scenario, low-carbon scenario and enhanced scenario.

[0086] The basic scenario means that coal-fired power generation capacity will continue to grow during the planning period, with the growth rate referring to the growth rate of coal-fired power generation capacity during the 14th Five-Year Plan period. There will be no annual carbon emission cap constraint, no participation in carbon emission reduction technology transformation, the utilization hours will remain unchanged at 3,800, and new carbon emission reduction technologies such as CCS, energy storage, and biomass blending will not be considered.

[0087] The low-carbon scenario means that coal-fired power generation capacity will refer to the existing dual-carbon strategic planning to explore the impact of carbon emission reduction technology on carbon emission reduction in my country's coal-fired power industry. Under this scenario, coal-fired power generation capacity will grow slowly before 2030 and eventually reach 1.3 billion kilowatts. After 2030, no new coal-fired power units will be added, and the scale of coal-fired power generation will slowly decline. At the same time, starting from 2025, the industry will vigorously promote carbon emission reduction technology and the number of utilization hours will begin to decline year by year. After 2035, energy storage, biomass blending, and CCS technologies will begin to be widely used, and carbon emissions per kilowatt-hour of coal-fired power will be greatly reduced.

[0088] The enhanced scenario assumes that a more stringent coal-fired power control policy will be implemented on a low-carbon basis, that is, no new coal-fired power generation capacity will be added after 2025. At the same time, carbon emission reduction technologies will be vigorously promoted from 2025, and the utilization hours will begin to decline year by year. After 2030, ultra-supercritical units will be retrofitted with energy storage, biomass co-firing, and CCS technologies. By 2040, all ultra-supercritical units will be retrofitted with energy storage, biomass co-firing, and CCS technologies.

[0089] The unit decommissioning module calculates the life parameters S of the active units age,j , and eliminate the coal consumption of power supply that does not reach the average value and the life parameter is lower than the life parameter threshold, that is, S age,j For units with a life span of less than 0.8, the calculation formula for the life span parameters is:

[0090]

[0091] Among them, S age,j is the life parameter of unit j; Plan Re is the design life of the unit, P k Start year for planning j is the commissioning time of unit j.

[0092] S2. The carbon emission reduction technology optimization algorithm module generates a carbon emission reduction technology transformation plan based on the retained and newly added units, and continuously iterates through the simulated annealing algorithm to find the most economical carbon emission reduction technology transformation plan. The specific steps are as follows:

[0093] Step 1. Read the units retained and newly added after the elimination operation of the unit decommissioning module;

[0094] Step 2. Read the total carbon reduction and total cost;

[0095] Step 3. Carry out technical transformation of the retained units and / or add units to form a carbon emission reduction technical transformation plan;

[0096] Step 4. Calculate the total technical transformation potential of carbon emission reduction technical transformation options Total Cost And the coal consumption of each unit after transformation

[0097] The total potential of technological transformation is calculated by first calculating the carbon emission reduction potential achieved by applying each technology to the unit type, and then summing up the carbon emission reduction potential achieved by applying each technology to the unit type to form the total potential of technological transformation;

[0098] The algorithm formulas for the carbon emission reduction potential achieved by the application of each technology in the unit category include:

[0099]

[0100] Select the corresponding algorithm formula according to the technology type to calculate the carbon emission reduction potential achieved by applying each technology to the unit type; among them, For technology i Applicable to unit type U j the carbon reduction potential achieved on For technology i In the crew class U j The applicable installed capacity, For unit type U j Installed capacity, For technology i In the crew class U j The scale has been applied to is the average annual utilization hours of unit type j, For technology iIn the crew class U j The change in coal consumption for power generation after the above application, k is the IPCC recommended calculated value for carbon dioxide emissions per ton of standard coal, For technology i In the crew class U j After the above application, the change in the plant power consumption rate of the unit is, γ Uj For unit type U j The average annual coal consumption for power generation is For unit type U j The auxiliary power consumption rate, For technology i After application on unit type j, the auxiliary power saving rate of the unit is η bio is the biomass blending rate of coal-fired power units, η pun is the efficiency penalty for coal-fired power units using biomass co-firing technology, η ccs is the capture efficiency of coal-fired power units coupled with CCS technology, η EN is the net capture efficiency of CCS technology.

[0101] The algorithm formula for the total carbon emission reduction potential of technological transformation is:

[0102]

[0103] in, For unit type U j The total carbon emission reduction potential of technological transformation.

[0104] The algorithm formula for the total cost is:

[0105]

[0106] in, For unit type U j The total carbon reduction cost after applying the adopted carbon reduction technology solutions, For technology i In the crew class U j Applicable installed capacity, For technology i The unit capacity investment cost on unit type j, r is the discount rate, For technology i Technical lifespan, For technology i Applicable to unit type U j The change in unit operation and maintenance cost on For technology i Applicable to unit type U j The variable cost at For technology i Application in unit type U j The carbon reduction potential achieved.

[0107] The calculation formula of coal consumption for power supply after technical transformation of the unit is:

[0108]

[0109] in, is the coal consumption of power supply of a single unit j after the end of the planning period; is the coal consumption of unit j before the planning period (when k = 1, it is the coal consumption of unit U nj is the coal consumption for power supply before technical transformation); For a single unit j, the maximum power supply coal consumption can be reduced through technical transformation within the plan.

[0110] Step 5. Determine whether the power supply coal consumption exceeds the set threshold. If so, iterate and update the carbon emission reduction technology transformation plan and return to step 2; if not, proceed to step 6;

[0111] Step 6. Calculate the unit carbon reduction cost and total technical transformation potential of the carbon reduction technology transformation plan.

[0112] The algorithm formula for the unit carbon emission reduction cost in step 6 is:

[0113]

[0114] in, For technology i Applicable to unit type U j The unit carbon reduction cost after For technology i In the crew class U j Applicable installed capacity, For technology i The unit capacity investment cost on unit type j, r is the discount rate, t Ti For technology i Technical lifespan, For technology i In the crew class U j The change in unit operation and maintenance cost on For technology i In the crew class U j The variable cost, Corresponding technology i Application in unit type U j Carbon emissions reductions achieved.

[0115] If compared with the initial plan, the unit carbon emission reduction cost and the total technical transformation potential of the carbon emission reduction technical transformation plan are not reduced at the same time, judge whether the carbon emission reduction technical transformation plan is acceptable according to the Metropolis acceptance criteria. If it is acceptable, update the carbon emission reduction technical transformation plan and return to step 2. If it is not acceptable, reduce the randomness in the process of searching for the optimal solution and reset the number of iterations before returning to step 2; if compared with the initial plan, the unit carbon emission reduction cost and the total technical transformation potential of the carbon emission reduction technical transformation plan are reduced at the same time, determine that the carbon emission reduction technical transformation plan is the optimal plan, and output the carbon emission reduction technical transformation plan.

[0116] Through the above methods, we can propose the new construction, technological transformation and elimination of coal-fired power plants in stages and units in the near and medium term, and provide the optimal development path for coal-fired power carbon emission reduction strategies, retirement and transformation of coal-fired power units. We also conduct an in-depth analysis of the transformation cost and carbon reduction situation of the coal-fired power system during the planning period.

[0117] According to the "dual carbon" goals, relevant planning and research, considering the construction of new coal-fired power units and carbon emission reduction technology transformation, three coal-fired power low-carbon transformation scenarios are set up, namely the baseline scenario, the low-carbon scenario and the enhanced scenario. The specific plans for the low-carbon transformation path of coal-fired power under the three scenarios from 2025 to 2040 are analyzed in detail, including the capacity of retired and newly built units, the scale and application technology of units participating in technical transformation, and the total cost and composition of carbon emission reduction technology transformation of coal-fired power units. Under the low-carbon scenario, during the planning period, the cumulative carbon emission reduction is 5.00 billion tons through the elimination of backward coal-fired power, the cumulative carbon emission reduction is 2.50 billion tons through the reduction of utilization hours, the cumulative carbon emission reduction is 1.402 billion tons through capacity replacement, the cumulative carbon emission reduction is 7.952 billion tons through the replacement of new units with renewable power sources, and the cumulative carbon emission reduction is 5.11 billion tons through carbon emission reduction technology transformation. In the carbon emission reduction technology transformation, energy-saving and efficiency-enhancing technologies contribute 4.175 billion tons of carbon emission reduction. Energy storage, CCS and biomass co-combustion technologies will not be put into operation until 2035, so the cumulative carbon reduction is relatively small, 0.6, 7.5 and 2.1 billion tons respectively. At the same time, under this scenario, the total cost of carbon reduction technology transformation during the planning period is 1.33 trillion yuan, of which the transformation costs of energy storage, CCS and biomass co-combustion account for 1.02%, 45.09% and 30.19% of the total cost respectively.

[0118] The present invention is described in detail above in conjunction with the embodiments, but the contents described are only preferred embodiments of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of application of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A coal-fired power carbon emission reduction path optimization method based on multi-objective constraints, characterized in that: It includes the following steps: S1. Use the unit retirement algorithm module to calculate the life parameters of the active units, and eliminate the units whose life parameters are lower than the set life parameter upper limit and the units required to be eliminated by the policy; S2. The carbon emission reduction technology optimization algorithm module is used to generate carbon emission reduction technology transformation plans based on the retained and newly added units, and the most economical carbon emission reduction technology transformation plan is continuously iterated through the simulated annealing algorithm.

2. The method for optimizing coal-fired power generation carbon emission reduction paths based on multi-objective constraints according to claim 1 is characterized by: The algorithm formula for calculating the life parameters of the active units in the unit retirement algorithm module in S1 is: Among them, S age,j is the life parameter of unit j; Plan Re is the planned retirement year of the unit, P k Start year for planning j is the commissioning time of unit j.

3. The method for optimizing coal-fired power generation carbon emission reduction paths based on multi-objective constraints according to claim 1 is characterized by: The objective function of the carbon emission reduction technology optimization algorithm module in S2 is: in, is the minimum carbon reduction cost, which means that k The carbon emission reduction cost after the most economical combination of carbon emission reduction technologies is adopted for the unit during the period; T i is the carbon emission reduction technology numbered i; U j For the unit of unit type j, Un j is a single unit in unit class j, It is technology i In the crew class U j The applicable installed capacity, P k Period Technology i In the unit U j The carbon reduction potential can be obtained For technology i In the unit U j The unit capacity investment cost on the basis of For technology i Technical lifespan, For technology i Applicable to unit type U j The change in unit operation and maintenance cost when For technology i Applicable to unit type U j variable costs at the time of The carbon emission reduction technology optimization algorithm module generates a carbon emission reduction technology transformation plan in accordance with the above objective function, indicating that P k The carbon reduction cost is lowest when the corresponding carbon reduction technology combination is used on a single unit j during the period.

4. The method for optimizing coal-fired power generation carbon emission reduction paths based on multi-objective constraints according to claim 3 is characterized by: The algorithm formula of the variable cost includes: in, For technology i In the crew class U j The applicable installed capacity, is the average annual utilization hours of unit type j, For unit type U j Application Technology i The change value of the power consumption rate of the rear unit, For unit type U j The annual average coal consumption for power generation is For unit type U j The auxiliary power consumption rate, For unit type U j Application Technology i Auxiliary power saving rate of the rear unit, P ES is the energy storage cost, E ES is the annual storage and discharge capacity of energy storage, CAP ES Installed capacity for energy storage technology, UUH ES is the annual operation time of the energy storage device, η ES For the storage and discharge efficiency of energy storage technology, For technology i In the crew class U j The change in coal consumption of the power supply unit after the above application, P coal is the standard coal price, η pun is the efficiency penalty for coal-fired power units using biomass co-firing technology, η bio is the biomass blending rate of coal-fired power units, H coal is the calorific value of standard coal, H bio is the calorific value of biomass, P bio is the biomass price, η bio is the biomass blending rate of coal-fired power units, η pun Efficiency penalty for applying biomass co-firing technology to coal-fired power plants, EM PP is the annual carbon emission of the unit, η ccs is the capture efficiency of coal-fired power units coupled with CCS technology, σ ab The consumption of absorbent for capturing 1 ton of carbon dioxide by CCS technology, P ab is the price of CCS absorbent, P tran&stor is the price of transport and storage of unit carbon dioxide, σ energy The coal consumption for capturing energy of CCS technology; According to the optimization technology T i , select formula (3)-formula (7) and optimization technology T i Corresponding calculation formula Calculation technology T i In the crew class U j of variable costs.

5. The method for optimizing coal-fired power generation carbon emission reduction paths based on multi-objective constraints according to claim 1 is characterized by: The carbon emission reduction technology optimization algorithm module in S2 must also meet the following constraints when generating a carbon emission reduction technology transformation plan: The algorithm expression of carbon emission reduction target constraint is: Among them, EM new is the annual carbon emission of the newly added units, EM old To preserve the annual carbon emissions of the unit, The maximum permissible emissions from the coal-fired power industry at the end of the planning period. The CAP is the maximum carbon emission that all units participating in the technical transformation can achieve through technical transformation during the planning period. new For the installed capacity of the newly added units, UUH system is the industry average utilization hours, Spcr new is the average power consumption rate of the newly added units, γ new is the coal consumption of the newly added units, CAP old In order to retain the installed capacity of the unit, Spcr old To retain the average power consumption rate of the unit, γ old To retain the average coal consumption for power generation of the unit, k is the IPCC recommended calculated value of carbon dioxide emissions per ton of standard coal; The algorithm expression of technology weight constraint is: Among them, P k is the application discrimination value of technology i on a single unit j, "1" represents that the unit has been modified, and "0" represents that the unit has not been modified; The algorithm expression of energy efficiency constraint is: in, is the coal consumption of power supply of a single unit j after the end of the planning period; For a single unit j, the maximum power supply coal consumption can be reduced by technical transformation within the planning period; It is the benchmark level of coal consumption for power supply of single unit j at the end of the planning period.

6. The method for optimizing coal-fired power generation carbon emission reduction paths based on multi-objective constraints according to claim 1 is characterized by: The specific steps of the carbon emission reduction technology optimization algorithm module in S2 to continuously iterate and find the optimal carbon emission reduction technology transformation plan through the simulated annealing algorithm are as follows: Step 1. Read the units retained and newly added after the elimination operation of the unit decommissioning module; Step 2. Read the total carbon reduction and total cost; Step 3. Carry out technical transformation of the retained units and / or additional units to form a carbon emission reduction technical transformation plan; Step 4. Calculate the total technical transformation potential of the resulting carbon emission reduction technical transformation plan Total Cost And the coal consumption of each unit after transformation Step 5. Determine whether the power supply coal consumption exceeds the set threshold. If so, iterate and update the carbon emission reduction technology transformation plan and return to step 2; If not, proceed to step 6; Step 6. Calculate the unit carbon emission reduction cost of the carbon emission reduction technology transformation plan, and determine whether technical transformation is needed in combination with the total potential of technical transformation. If compared with the initial plan, the unit carbon emission reduction cost and the total potential of technical transformation of the carbon emission reduction technology transformation plan are not reduced at the same time, determine whether the carbon emission reduction technology transformation plan is acceptable according to the Metropolis acceptance criteria. If acceptable, update the carbon emission reduction technology transformation plan and return to step 2. If unacceptable, reduce the randomness in the process of searching for the optimal solution and reset the number of iterations before returning to step 2. If compared with the initial plan, the unit carbon emission reduction cost and the total potential of technical transformation of the carbon emission reduction technology transformation plan are reduced at the same time, determine that the carbon emission reduction technology transformation plan is the optimal plan, and output the carbon emission reduction technology transformation plan.

7. The method for optimizing coal-fired power generation carbon emission reduction paths based on multi-objective constraints according to claim 6 is characterized by: The calculation method of the total potential of technical transformation in step 4 is to first calculate the application of each technology in unit type U j The carbon reduction potential is then applied to the unit type U j The carbon emission reduction potential obtained above is added to form the total technical transformation potential of the technical transformation combination plan; The above technologies are applied in the unit type U j The carbon reduction potential algorithm formula obtained above includes: According to the technology type, select the corresponding algorithm formula to calculate the application of each technology in the unit type U j The carbon reduction potential achieved on For technology i Applicable to unit type U j the carbon reduction potential achieved on For technology i In the crew class U j The applicable installed capacity, For unit type U j Installed capacity, For technology i In the crew class U j The scale has been applied to is the average annual utilization hours of unit type j, For technology i In the crew class U j The change in coal consumption for power generation after the above application, k is the IPCC recommended calculated value for carbon dioxide emissions per ton of standard coal, For technology i In the crew class U j After the above application, the change in the plant power consumption rate of the unit is: For unit type U j The annual average coal consumption for power generation is For unit type U j The auxiliary power consumption rate, For technology i After application on unit type j, the auxiliary power saving rate of the unit is η bio is the biomass blending rate of coal-fired power units, η pun is the efficiency penalty for coal-fired power units using biomass co-firing technology, η ccs is the capture efficiency of coal-fired power units coupled with CCS technology, η EN is the net capture efficiency of the CCS technology; The algorithm formula for the total carbon emission reduction potential of the technical transformation is: in, For unit type U j The total carbon emission reduction potential of technological transformation.

8. The method for optimizing coal-fired power generation carbon emission reduction paths based on multi-objective constraints according to claim 6 is characterized by: The algorithm formula of the total cost in step 4 is: in, For unit type U j The total carbon reduction cost after applying the adopted carbon reduction technology solutions, For technology i In the crew class U j Applicable installed capacity, For technology i The unit capacity investment cost on unit type j, r is the discount rate, For technology i Technical lifespan, For technology i Applicable to unit type U j The change in unit operation and maintenance cost on For technology i Applicable to unit type U j The variable cost at For technology i Application in unit type U j The carbon reduction potential achieved.

9. The method for optimizing coal-fired power generation carbon emission reduction paths based on multi-objective constraints according to claim 6 is characterized by: The algorithm formula for the power supply coal consumption after the technical transformation of the unit in step 4 is: in, is the coal consumption of power supply of a single unit j after the end of the planning period; is the coal consumption of power supply of unit j before the planning period; For a single unit j, the maximum coal consumption for power supply can be reduced through technical transformation within the plan.

10. The method for optimizing coal-fired power generation carbon emission reduction paths based on multi-objective constraints according to claim 6, characterized in that: The algorithm formula for the unit carbon emission reduction cost in step 6 is: in, For technology i Applicable to unit type U j The unit carbon reduction cost after For technology i In the crew class U j Applicable installed capacity, For technology i The unit capacity investment cost on unit type j, r is the discount rate, For technology i Technical lifespan, For technology i In the crew class U j The change in unit operation and maintenance cost on For technology i In the crew class U j The variable cost, Corresponding technology i Application in unit type U j Carbon emissions reductions achieved.

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