Optimization method of coal-fired power generation carbon emission reduction path based on multi-objective constraints

Abstract

The present invention relates to a method for optimizing the path of coal-fired power generation carbon emission reduction based on multi-objective constraints, and belongs to the field of power system transformation. The method comprises: using a unit decommissioning algorithm module to calculate the life parameters of the active units, and eliminating the units whose life parameters are lower than the life parameters; using a carbon emission reduction technology optimization algorithm module to generate a carbon emission reduction technology transformation plan based on the remaining units, and continuously iterating to find the optimal carbon emission reduction technology transformation plan through a simulated annealing algorithm. The present invention determines the scale of retired units through the unit decommissioning algorithm module, and obtains the changes in installed capacity such as the total installed capacity / newly installed capacity / retired capacity of various types of coal-fired power units; and obtains the layout of the coal-fired power generation low-carbon transformation path, the carbon emission reduction amount of the coal-fired power generation low-carbon transformation path, and the investment cost, operation and maintenance cost, and carbon reduction cost of the carbon emission reduction technology during the planning period through the carbon emission reduction technology optimization algorithm module, taking into account a series of external constraints such as energy security, economic development, and policy carbon reduction targets.

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 further reduce the power system's rotational inertia, but will also lead to a massive waste of resources and stranded coal-fired power assets. A rapid transition to clean energy could ultimately have catastrophic consequences. New power systems require proactive guidance to ensure sufficient system inertia. This demonstrates the practical significance of research on the functional transformation of coal-fired power units for the safe and stable operation of power systems.

[0003] Extensive research and calculations have demonstrated that the adoption of carbon reduction technologies can, to a certain extent, achieve the carbon reduction goals of my country's coal-fired power generation industry. For example, the invention patent application with application publication number CN117172021A discloses a method for optimizing the functional transformation of coal-fired power units that takes into account the inertia support of the power system. This invention first selects alternative units within the power system that meet the retirement capacity requirements based on the proposed retirement plan of the coal-fired power units. Then, based on the system's minimum inertia demand value constrained by frequency security, the capacity of the alternative units that need to undergo functional transformation to support the system's inertia level, i.e., the inertia target value, is determined. The functional transformation coal-fired power units, i.e., the modified units, are then identified. Finally, flexibility modifications are performed on the modified units to further reduce their minimum technical output, thereby encouraging them to provide inertia support for the system under the incentive of inertia auxiliary services.

[0004] However, the low-carbon transition of the coal-fired power industry is a long-term process involving complex decision-making issues, including the construction of new units, unit shutdowns, the expansion of large-scale power generation and the reduction of small-scale power generation (a policy measure in the power industry aimed at achieving energy conservation, emission reduction, and improved energy efficiency by building new large-capacity, high-performance, low-consumption, and low-emission power generation units while simultaneously shutting down some small thermal power units), and the application of carbon emission reduction technologies to units. At the same time, a series of external constraints, such as energy security, economic development, and relevant carbon emission reduction policy targets, must also be taken into account. Therefore, how to effectively integrate these issues into the development plan of a low-carbon power system and develop a decision-making model that conforms to the development process of the coal-fired power system and an optimization algorithm for coal-fired power carbon emission reduction paths based on multi-objective constraints are key steps in exploring the low-carbon development of coal-fired power. Summary of the Invention

[0005] The purpose of this 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.

[0006] To solve the above technical problems, the present invention provides a method for optimizing coal-fired power generation carbon emission reduction paths based on multi-objective constraints, which includes the following steps:

[0007] 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 by policy;

[0008] S2. Use the carbon emission reduction technology optimization algorithm module to generate carbon emission reduction technology transformation plans based on the retained and newly added units, and use the simulated annealing algorithm to continuously iterate and find the most economical carbon emission reduction technology transformation plan.

[0009] Preferably, the calculation formula for calculating the life parameters of the active units in the unit decommissioning algorithm module in S1 is:

[0010]

[0011] 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.

[0012] Preferably, the objective function of the carbon emission reduction technology optimization algorithm module in S2 is:

[0013]

[0014] in, is the minimum carbon emission 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 T i In the crew class U j The applicable installed capacity, P k Period Technology T i In the unit U j The carbon reduction potential can be obtained For technology T i In the unit U j The unit capacity investment cost on the basis of r is the discount rate, For technology T i technical life, For technology T i Applicable to unit type U jThe change in unit operation and maintenance cost when For technology T i Applicable to unit type U j variable costs at the time of

[0015] 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 adopted on a single unit j during this period.

[0016] Preferably, the calculation formula for the variable cost includes:

[0017]

[0018]

[0019] in, For technology T 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 Applied 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 supply is For unit type U j Auxiliary power consumption rate, For unit type U j Applied 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 operating time of the energy storage device, η ES For the storage and discharge efficiency of energy storage technology, For technology T i In the crew class U j The change in coal consumption of the power generation unit after the above application, P coal is the price of standard coal ton, η pun is the efficiency penalty for applying biomass co-firing technology to coal-fired power units, 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 biomass co-firing technology in coal-fired power plants, EMPP is the annual carbon emissions 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 by CCS technology;

[0020] 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.

[0021] 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:

[0022] The algorithm expression of carbon emission reduction target constraint is:

[0023]

[0024] Among them, EM new is the annual carbon emission of the newly added units, EM old To preserve the unit’s annual carbon emissions, The maximum permissible emissions from the coal-fired power industry at the end of the planning period. The maximum carbon emissions that all units participating in the technical transformation can achieve through technical transformation during the planning period are CAP 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 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;

[0025] The algorithm expression of technology weight constraint is:

[0026]

[0027] Among them, P k is the discrimination value of the application 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;

[0028] The algorithm expression of energy efficiency constraint is:

[0029]

[0030] in, is the coal consumption of power supply of 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 plan; is the benchmark coal consumption level for power supply of single unit j at the end of the planning period.

[0031] 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:

[0032] Step 1. Read the units retained and newly added after the elimination operation of the unit decommissioning module;

[0033] Step 2. Read the total carbon reduction and total cost;

[0034] Step 3. Carry out technical transformation of the retained units and / or additional units to formulate a carbon emission reduction technical transformation plan;

[0035] Step 4. Calculate the total technological transformation potential of the resulting carbon emission reduction technological transformation plan Total cost And the power supply coal consumption of each unit after transformation

[0036] 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.

[0037] Step 6. Calculate the unit carbon emission reduction cost of the carbon emission reduction technology transformation plan, and determine whether technical transformation is necessary based on 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 based on 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 search for the optimal solution, reset the number of iterations, and return 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.

[0038] Preferably, the calculation method of the total potential of technical transformation in step 4 is to first calculate the application of each technology in the unit type U j The carbon reduction potential is obtained, and then the technologies are applied to the unit type Uj The carbon emission reduction potentials obtained above are added together to form the total technological transformation potential of the technological transformation combination plan;

[0039] The above technologies are applied in the unit type U j The algorithm formula for the carbon emission reduction potential obtained includes:

[0040]

[0041] 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

[0042] in, For technology T i Applicable to unit type U j the carbon reduction potential achieved on For technology T i In the crew class U j The applicable installed capacity, For unit type U j installed capacity, For technology T i In the crew class U j Scale has been applied to it. is the average annual utilization hours of unit type j, For technology T 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 T i In the crew class U j After the above application, the change in the plant power rate of the unit is: For unit type U j The average annual coal consumption for power supply is For unit type U j Auxiliary power consumption rate, For technology T i After applying to 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 applying biomass co-firing technology to coal-fired power units, 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;

[0043] The algorithm formula for the total carbon emission reduction potential of the technological transformation is:

[0044]

[0045] in, For unit type U j The total carbon emission reduction potential of technological transformation.

[0046] Preferably, the algorithm formula for the total cost in step 4 is:

[0047]

[0048] in, For unit type U j The total carbon emission reduction cost after applying the adopted carbon emission reduction technology solutions, For technology T i In the crew class U j Applicable installed capacity, For technology T i The unit capacity investment cost on unit type j, r is the discount rate, For technology T i technical life, For technology T i Applicable to unit type U j The change in unit operation and maintenance cost on For technology T i Applicable to unit type U j Variable costs at For technology T i Application in unit type U j The carbon reduction potential achieved.

[0049] Preferably, the algorithm formula for the power supply coal consumption after the technical transformation of the unit in step 4 is:

[0050]

[0051] in, is the coal consumption of power supply of 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 =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.

[0052] Preferably, the algorithm formula for the unit carbon emission reduction cost in step 6 is:

[0053]

[0054] in, For technology T i Applicable to unit type U j The unit carbon reduction cost after For technology T i In the crew class Uj Applicable installed capacity, For technology T i The unit capacity investment cost on unit type j, r is the discount rate, For technology T i technical life, For technology T i In the crew class U j The change in unit operation and maintenance cost on For technology T i In the crew class U j variable costs, Corresponding technology T i Application in unit type U j The carbon emission reductions achieved.

[0055] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:

[0056] The present invention determines the scale of retired units during 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 economic and environmental goals, that is, it seeks to minimize the carbon emission reduction cost of the coal-fired power industry during the planning period; the optimization results obtained by solving the algorithm model include changes in installed capacity such as total installed capacity / newly 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 carbon emission reduction of various coal-fired power low-carbon transformation paths, the total carbon emission reduction cost 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 goals. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is the operational flow chart of the coal-fired power carbon emission reduction path optimization method based on multi-objective constraints;

[0058] Figure 2 Workflow diagram of the carbon emission reduction technology optimization algorithm module. DETAILED DESCRIPTION

[0059] The present invention is described in detail below, clearly and completely describing the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0060] Refer to the attached Figure 1As shown, the present embodiment involves a method for optimizing coal-fired power generation carbon emission reduction paths based on multi-objective constraints. The method is implemented based on a unit decommissioning algorithm module and a carbon emission reduction technology optimization algorithm module, and specifically includes the following steps:

[0061] 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 life parameters and policy requirements. In this embodiment, the upper limit of the life parameter is 0.8. The calculation formula for calculating the life parameters of the active units is:

[0062]

[0063] 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.

[0064] S2. Use the carbon emission reduction technology optimization algorithm module to generate carbon emission reduction technology transformation plans based on the remaining units, and use the simulated annealing algorithm to continuously iterate and find the optimal carbon emission reduction technology transformation plan.

[0065] The objective function of the carbon emission reduction technology optimization algorithm module is:

[0066]

[0067] in, is the minimum carbon emission 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 T i In the crew class U j The applicable installed capacity, P k Period Technology T i In the unit U j The carbon reduction potential available on For technology T i In the unit U j The unit capacity investment cost on the basis of r is the discount rate, For technology T i technical life, For technology T i Applicable to unit type U j The change in unit operation and maintenance cost when For technology Ti Applicable to unit type U j variable costs at the time of

[0068] Among them, variable costs The algorithm formula includes:

[0069]

[0070] in, For technology T 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 Applied 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 supply is For unit type U j Auxiliary power consumption rate, For unit type U j Applied 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 operating time of the energy storage device, η ES For the storage and discharge efficiency of energy storage technology, For technology T i In the crew class U j The change in coal consumption of the power generation unit after the above application, P coal is the price of standard coal ton, η pun is the efficiency penalty for applying biomass co-firing technology to coal-fired power units, 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 biomass co-firing technology in coal-fired power plants, EM PP is the annual carbon emissions 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 of .

[0071] The above carbon emission reduction technology optimization algorithm module generates carbon emission reduction technology transformation plans in accordance with the above objective function, which shows that in P k When this carbon emission reduction technology transformation plan is adopted during the period, the carbon reduction cost of single unit j is the lowest.

[0072] The carbon emission reduction technology optimization algorithm module also meets the following constraints when generating carbon emission reduction technology transformation plans:

[0073] 1) The algorithm expression of carbon emission reduction target constraint is:

[0074]

[0075] Among them, EM new is the annual carbon emission of the newly added units, EM old To preserve the unit’s annual carbon emissions, The maximum permissible emissions from the coal-fired power industry at the end of the planning period. The maximum carbon emissions that all units participating in the technical transformation can achieve through technical transformation during the planning period are CAP 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 The coal consumption of the newly added units, CAP old In order to retain the installed capacity of the unit, Spcr old In order 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;

[0076] 2) The algorithm expression of technology weight constraint is:

[0077]

[0078] Among them, P k is the discrimination value of the application 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;

[0079] 3) The algorithm expression of energy efficiency constraint is:

[0080]

[0081] in, is the coal consumption of power supply of 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 plan; is the benchmark coal consumption level for power supply of single unit j at the end of the planning period.

[0082] 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 , the application process of the coal-fired power low-carbon transformation planning optimization system is further explained.

[0083] Refer to the attached Figure 1 As shown in FIG, the application process of the coal-fired power low-carbon transformation planning optimization system is as follows:

[0084] Scenario setting: including basic scenario, low-carbon scenario and enhanced scenario.

[0085] The basic scenario means that coal-fired power installed capacity will continue to grow during the planning period, with the growth rate referring to the growth rate of coal-fired power installed 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 the application of new carbon emission reduction technologies such as CCS, energy storage, and biomass co-firing will not be considered.

[0086] The low-carbon scenario means that coal-fired power generation capacity will refer to the existing dual-carbon strategic plan to explore the impact of carbon emission reduction technologies 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 capacity will slowly decline. At the same time, starting from 2025, the industry will vigorously promote carbon emission reduction technologies and the number of utilization hours will begin to decline year by year. After 2035, energy storage, biomass co-firing, and CCS technologies will begin to be applied on a large scale, and carbon emissions per kilowatt-hour of coal-fired power will be greatly reduced.

[0087] The enhanced scenario assumes that a stricter 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 have been retrofitted with energy storage, biomass co-firing, and CCS technologies.

[0088] The unit decommissioning module calculates the life parameter 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:

[0089]

[0090] 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.

[0091] S2. The carbon reduction technology optimization algorithm module generates carbon reduction technology transformation plans based on the retained and newly added units, and continuously iterates through the simulated annealing algorithm to find the most economical carbon reduction technology transformation plan. The specific steps are as follows:

[0092] Step 1. Read the units retained and newly added after the elimination operation of the unit decommissioning module;

[0093] Step 2. Read the total carbon reduction and total cost;

[0094] Step 3. Carry out technical renovations on the remaining units and / or add new units to formulate a carbon emission reduction technical renovation plan;

[0095] Step 4. Calculate the total technological transformation potential of carbon emission reduction technology transformation options Total cost And the power supply coal consumption of each unit after transformation

[0096] 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;

[0097] The algorithm formula for the carbon emission reduction potential achieved by applying each technology to the unit type includes:

[0098]

[0099] 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; For technology T i Applicable to unit type U j the carbon reduction potential achieved on For technology T i In the crew class U j The applicable installed capacity, For unit type U j installed capacity, For technology T i In the crew class U j Scale has been applied to it. is the average annual utilization hours of unit type j, For technology T 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 T i In the crew class U j After the above application, the change in the plant power rate of the unit is: γ Uj For unit type U j The average annual coal consumption for power supply is For unit type U j Auxiliary power consumption rate, For technology T i After applying to 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 applying biomass co-firing technology to coal-fired power units, 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.

[0100] The algorithm formula for the total carbon emission reduction potential of technological transformation is:

[0101]

[0102] in, For unit type U j The total carbon emission reduction potential of technological transformation.

[0103] The algorithm formula for the total cost is:

[0104]

[0105] in, For unit type U j The total carbon emission reduction cost after applying the adopted carbon emission reduction technology solutions, For technology T i In the crew class U j Applicable installed capacity, For technology T i The unit capacity investment cost on unit type j, r is the discount rate, For technology T i technical life, For technology T i Applicable to unit type U j The change in unit operation and maintenance cost on For technology T i Applicable to unit type U j Variable costs at For technology T i Application in unit type U j The carbon reduction potential achieved.

[0106] The calculation formula for power supply coal consumption after the unit technical transformation is:

[0107]

[0108] in, is the coal consumption of power supply of 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 =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.

[0109] 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.

[0110] Step 6. Calculate the unit carbon reduction cost and total potential of the carbon reduction technology transformation plan.

[0111] The algorithm formula for the unit carbon emission reduction cost in step 6 is:

[0112]

[0113] in, For technology T i Applicable to unit type U j The unit carbon reduction cost after For technology T i In the crew class U j Applicable installed capacity, For technology T i The unit capacity investment cost on unit type j, r is the discount rate, t Ti For technology T i technical life, For technology T i In the crew class U j The change in unit operation and maintenance cost on For technology T i In the crew class U j variable costs, Corresponding technology T i Application in unit type U j The carbon emission reductions achieved.

[0114] If the unit carbon emission reduction cost and the total potential of the carbon emission reduction technology transformation plan are not reduced at the same time compared with the initial plan, the acceptance of the carbon emission reduction technology transformation plan is judged according to the Metropolis acceptance criteria. If it is acceptable, the carbon emission reduction technology transformation plan is updated and the process returns to step 2. If it is not acceptable, the randomness in the search for the optimal solution is reduced and the number of iterations is reset before returning to step 2. If the unit carbon emission reduction cost and the total potential of the carbon emission reduction technology transformation plan are reduced at the same time compared with the initial plan, the carbon emission reduction technology transformation plan is determined to be the optimal plan and the carbon emission reduction technology transformation plan is output.

[0115] 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, decommissioning and transformation of coal-fired power units. We also conduct an in-depth analysis of the transformation costs and carbon reduction status of the coal-fired power system during the planning period.

[0116] Based on the "dual carbon" goals, relevant planning, and research, three scenarios for the low-carbon transition of coal-fired power generation were developed, taking into account new coal-fired power generation units and carbon emission reduction technology retrofits: a baseline scenario, a low-carbon scenario, and an enhanced scenario. The report detailed the specific pathways for the low-carbon transition of coal-fired power generation from 2025 to 2040 under each of these scenarios, including the capacity of retired and newly built units, the scale and applied technologies of units participating in the technical retrofit, and the total cost and composition of carbon emission reduction technology retrofits for coal-fired power generation units. Under the low-carbon scenario, cumulative carbon emissions reductions of 5.00 billion tons will be achieved during the planning period through the retirement of outdated coal-fired power generation units, 2.50 billion tons through reduced utilization hours, 1.402 billion tons through capacity substitution, 7.952 billion tons through the replacement of newly built units with renewable power sources, and 5.110 billion tons through carbon emission reduction technology retrofits. Energy-saving and efficiency-enhancing technologies contributed 4.175 billion tons of carbon reductions to these carbon emission reduction technology retrofits. Energy storage, CCS, and biomass co-firing technologies, due to their operational launch in 2035, will contribute relatively small cumulative carbon reductions of 0.6 million, 0.75 million, and 0.21 million tons, respectively. Furthermore, under this scenario, the total cost of carbon reduction technology upgrades over the planning period is 1.33 trillion yuan, of which energy storage, CCS, and biomass co-firing account for 1.02%, 45.09%, and 30.19%, respectively.

[0117] The present invention has been described in detail above with reference to the embodiments. However, the contents described are only preferred embodiments of the present invention and should not be considered as limiting the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A multi-objective constraint-based coal-fired power generation carbon emission reduction path optimization method, characterized by: 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 by policy; S2. The carbon emission reduction technology optimization algorithm module generates carbon emission reduction technology transformation plans 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 objective function of the carbon emission reduction technology optimization algorithm module in S2 is: in, is the minimum carbon emission 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 T i In the crew class U j The applicable installed capacity, P k Period Technology T i In the unit U j The carbon reduction potential can be obtained For technology T i In the unit U j The unit capacity investment cost on the basis of r is the discount rate, For technology T i technical life, For technology T i Applicable to unit type U j The change in unit operation and maintenance cost when For technology T i Applicable to unit type U j The variable cost at the time of the calculation is as follows: in, For technology T 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 Applied 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 supply is For unit type U j Auxiliary power consumption rate, For unit type U j Applied 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 operating time of the energy storage device, η ES For the storage and discharge efficiency of energy storage technology, For technology T i In the crew class U j The change in coal consumption of the power generation unit after the above application, P coal is the price of standard coal ton, η pun is the efficiency penalty for applying biomass co-firing technology to coal-fired power units, 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 biomass co-firing technology in coal-fired power plants, EM PP is the annual carbon emissions 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 by 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 variable costs; 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; The carbon emission reduction technology optimization algorithm module must also meet the following constraints when generating carbon emission reduction technology transformation plans: 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 unit’s annual carbon emissions, The maximum permissible emissions from the coal-fired power industry at the end of the planning period. The maximum carbon emissions that all units participating in the technical transformation can achieve through technical transformation during the planning period are CAP 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 The coal consumption of the newly added units, CAP old In order to retain the installed capacity of the unit, Spcr old In order 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 discrimination value of the application 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 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 plan; is the benchmark coal consumption level for power supply of single unit j at the end of the planning period.

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 specific steps of the carbon emission reduction technology optimization algorithm module in S2 for continuously iterating to 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 formulate a carbon emission reduction technical transformation plan; Step 4. Calculate the total technological transformation potential of the resulting carbon emission reduction technological transformation plan Total cost And the power supply 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, go 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 necessary based on 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 based on 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 search for the optimal solution, reset the number of iterations, and return 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.

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 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 obtained, and then the technologies are applied to the unit type U j The carbon emission reduction potentials obtained above are added together to form the total technical transformation potential of the carbon emission reduction technical transformation plan; The above technologies are applied in the unit type U j The carbon reduction potential algorithm formulas obtained above include: 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 emission reduction potential achieved on For technology T i Applicable to unit type U j the carbon reduction potential achieved on For technology T i In the crew class U j The applicable installed capacity, For unit type U j installed capacity, For technology T i In the crew class U j Scale has been applied to it. is the average annual utilization hours of unit type j, For technology T 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 T i In the crew class U j After the above application, the change in the plant power rate of the unit is: For unit type U j The average annual coal consumption for power supply is For unit type U j Auxiliary power consumption rate, For technology T i After applying to 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 applying biomass co-firing technology to coal-fired power units, 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 potential of technological transformation is: in, For unit type U j The total potential for technological transformation.

5. 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 for the total cost in step 4 is: in, For unit type U j The total carbon emission reduction cost after applying the adopted carbon emission reduction technology solutions, For technology T i In the crew class U j Applicable installed capacity, For technology T i The unit capacity investment cost on unit type j, r is the discount rate, For technology T i technical life, For technology T i Applicable to unit type U j The change in unit operation and maintenance cost on For technology T i Applicable to unit type U j Variable costs at For technology T i Application in unit type U j The carbon reduction potential achieved.

6. 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 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 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 power supply coal consumption can be reduced through technical transformation within the plan.

7. 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 for the unit carbon emission reduction cost in step 6 is: in, For technology T i Applicable to unit type U j The unit carbon reduction cost after For technology T i In the crew class U j Applicable installed capacity, For technology T i The unit capacity investment cost on unit type j, r is the discount rate, For technology T i technical life, For technology T i In the crew class U j The change in unit operation and maintenance cost on For technology T i In the crew class U j variable costs, Corresponding technology T i Application in unit type U j The carbon emission reductions achieved.

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