A regional carbon management strategy optimization method and terminal

Abstract

The application provides a regional carbon management strategy optimization method and a terminal, and comprises the following steps: S1, a target region is preset, and a current carbon management statistical period is divided into a plurality of time periods, and a power generation plan of the region in a current time period is configured, the power generation plan comprising power generation amounts of a set of energy facilities in the region in each time period; S2, in the current time period, real-time power generation amounts of the set of energy facilities monitored in the region are counted, a difference between the real-time power generation amounts and the power generation amounts in the current time period in the power generation plan is calculated to obtain a power generation amount difference, and a power supply side structure in the region is optimized according to the power generation amount difference and carbon emission conditions; and S3, whether the current carbon management statistical period is ended is judged, if not, the step S1 is returned, and execution of a next time period is continued. The application can solve the defect that carbon emission is managed after being emitted in the prior art, and reasonably manages a whole carbon emission period.

Description

Technical Field

[0001] This invention relates to the field of carbon footprint analysis and management technology, and in particular to a method and terminal for optimizing regional carbon management strategies. Background Technology

[0002] Due to policy requirements in various countries and regions around the world, an increasing number of industries and enterprises are required to provide information on the carbon dioxide emissions of their products and investments. Calculating carbon footprints is perhaps the most basic technology currently available. The commonly used method for calculating carbon footprints is Life Cycle Assessment (LCA). However, existing big data analysis methods for carbon footprints lack sensitivity analysis, making it impossible to identify key influencing factors. Numerous uncertainties lead to significant errors in the final quantitative calculation and analysis of carbon footprints.

[0003] Meanwhile, carbon assets typically refer to carbon quota assets and carbon emission reduction (CCER) assets. Since the power grid industry is not a key emission control industry in the national carbon trading market, the carbon assets of the power system industry are mainly CCER carbon emission reduction assets, as well as carbon quota assets obtained by some enterprises included in the local carbon trading market.

[0004] Current technologies for carbon footprint tracking and carbon management focus more on detection and quota management, typically concentrating on carbon trading order at the end of the management cycle. However, they often neglect the actual carbon cycle management process, i.e., the so-called "emissions first, then treatment." Overemphasizing carbon emission trading to achieve carbon emission management is not only detrimental to the sustainable development of the green economy, but also hinders enterprises from improving energy efficiency and optimizing their own technological management level.

[0005] Therefore, how to ensure power generation efficiency and meet users' electricity demand, and how to optimize and adjust the power supply structure in real time, so as to ensure the economic efficiency and greenness of power generation, improve power generation efficiency and meet users' electricity demand, while keeping the regional carbon emission level within the quota control range as much as possible, is a technical problem that industrial enterprises urgently need to face and solve in the face of the carbon neutrality and management wave. Summary of the Invention

[0006] The technical problem to be solved by this invention is to provide a regional carbon management strategy optimization method and terminal, which solves the defects of the prior art of emission first and management later, and enables reasonable management of carbon emission throughout the entire life cycle.

[0007] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0008] A method for optimizing regional carbon management strategies includes the following steps:

[0009] S1. Preset target area D, and divide the current carbon management statistical period T into several time periods T1, T2...Tn Configure the region D in the current time period T i The power generation plan within (1≤i≤n) includes the power generation F of the energy facility set G in region D within each time period. i ;

[0010] S2, in the current time period T i Within the region D, the real-time power generation F of the energy facility set G monitored is statistically analyzed. s Calculate the real-time power generation F s Compared with the current time period T in the power generation plan i Electricity generation F within i The difference is used to obtain the power generation difference. Based on the power generation difference and carbon emission situation, the power supply side structure in the region D is optimized.

[0011] S3. Determine whether the current carbon management statistical period T has ended. If it has not ended, i.e., i < n, return to step S1 and continue the execution of the next time period until i = n, then end the carbon management operation within the current carbon management statistical period T.

[0012] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is as follows:

[0013] A regional carbon management strategy optimization terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in a regional carbon management strategy optimization method as described above.

[0014] The beneficial effects of this invention are as follows: This invention provides a regional carbon management strategy optimization method and terminal. By optimizing the energy utilization structure of the target region, carbon management within the target region can quickly achieve the predetermined goals. Compared with the existing technology, which usually only focuses on carbon emission quotas at the end of the carbon management statistical cycle, the management strategy of this application has the advantage of continuously monitoring and predicting the carbon emission trend within the region during the carbon management statistical cycle, optimizing the power generation structure or conducting carbon emission quota trading in advance, avoiding the traditional practice of sudden carbon emission trading. In particular, it introduces a differentiated management strategy that focuses on carbon emission amounts between different time periods, and calculates based on the corresponding transitional situations of carbon emissions in different time periods, making the carbon emission prediction process more accurate. This not only helps reduce the carbon emission quota compliance requirements within the region, but also quickly optimizes the power supply structure system for different power generation and consumption situations, achieving the goal of energy conservation and emission reduction. Furthermore, it helps reduce the carbon emission compliance and carbon quota trading costs for enterprises, promoting the development of a green circular economy. Attached Figure Description

[0015] Figure 1This is an overall flowchart of a regional carbon management strategy optimization method according to an embodiment of the present invention;

[0016] Figure 2 This is a schematic diagram of the structure of a regional carbon management strategy optimization terminal according to an embodiment of the present invention.

[0017] Label Explanation:

[0018] 1. A regional carbon management strategy optimization terminal; 2. Memory; 3. Processor. Detailed Implementation

[0019] To explain in detail the technical content, objectives, and effects of the present invention, the following description is provided in conjunction with the embodiments and accompanying drawings.

[0020] Please refer to Figure 1 A method for optimizing regional carbon management strategies, comprising the following steps:

[0021] S1. Preset target area D, and divide the current carbon management statistical period T into several time periods T1, T2...T n Configure the region D in the current time period T i The power generation plan within (1≤i≤n) includes the power generation F of the energy facility set G in region D within each time period. i ;

[0022] S2, in the current time period T i Within the region D, the real-time power generation F of the energy facility set G monitored is statistically analyzed. s Calculate the real-time power generation F s Compared with the current time period T in the power generation plan i Electricity generation F within i The difference is used to obtain the power generation difference. Based on the power generation difference and carbon emission situation, the power supply side structure in the region D is optimized.

[0023] S3. Determine whether the current carbon management statistical period T has ended. If it has not ended, i.e., i < n, return to step S1 and continue the execution of the next time period until i = n, then end the carbon management operation within the current carbon management statistical period T.

[0024] As described above, the beneficial effects of this invention are as follows: by optimizing the energy utilization structure of the target area, carbon management within the target area can quickly achieve the predetermined goals. Compared with the existing technology, which typically only focuses on carbon emission allowances at the end of the carbon management statistical cycle, the management strategy of this application has the advantage of continuously monitoring and predicting carbon emission trends within the region during the carbon management statistical cycle, optimizing the power generation structure in advance, or conducting carbon emission allowance trading in advance, avoiding the traditional practice of sudden carbon emission trading. In particular, it introduces a differentiated management strategy that focuses on carbon emission amounts between different time periods, and calculates based on the corresponding transitional situations of carbon emissions in different time periods, making the carbon emission prediction process more accurate. This not only helps reduce the carbon emission allowance compliance requirements within the region, but also quickly optimizes the power supply structure system for different power generation and consumption situations, achieving the goal of energy conservation and emission reduction. Furthermore, it helps reduce the carbon emission compliance and carbon allowance trading costs for enterprises, promoting the development of a green circular economy.

[0025] Furthermore, the acquisition of carbon emission information in step S2 specifically involves:

[0026] Based on the current time period T i The actual carbon emissions C within region D are described above. ti The calculated periodic carbon emissions C ave ;

[0027] Among them, the statement based on the current time period T i The actual carbon emissions C within region D are described above. ti The calculated periodic carbon emissions C ave This refers to the current monitored actual carbon emissions (C). ti The periodic carbon emissions C are calculated using the following formula (1). ave :

[0028]

[0029] Among them, C r1 C r2 ...refers to the current time period T within the current carbon management statistical period T. i The actual carbon emissions of region D in the previous time periods, μ1, μ2...μ n This refers to the various time periods T1, T2...T n The carbon emission proportion weighting coefficient is the ratio of the actual emissions in each time period of the historical carbon management statistical period to the average emissions in each time period of the historical carbon management statistical period.

[0030] Furthermore, obtaining the carbon emission information also includes the following steps:

[0031] Based on the Markov chain, the carbon emission proportion weighting coefficients μ1, μ2...μ n Adjusted to P1, P2...P n Formula (2) is as follows:

[0032]

[0033] Where P 11 ...P nn These are the transition probability values ​​in the transition probability matrix, used to calculate the periodic carbon emissions C. ave The following formula (3):

[0034]

[0035] As described above, the advantage of using Markov chains to calculate cyclical carbon emissions is that the carbon emissions of each controlled emission enterprise in the region have a certain degree of continuity between different time periods, and will not experience a sharp increase or decrease. Considering the continuity of emissions between different time periods, Markov chains can fully take into account the continuity between the carbon emissions of the previous time period and the current time period, and thus more accurately predict cyclical carbon emissions based on this continuity.

[0036] Furthermore, in step S2, based on the difference in power generation and the carbon emission situation, the power supply side structure within region D is optimized, specifically as follows:

[0037] S2a, if the current time period T i The difference in power generation within the range is greater than the first threshold, and C ave It did not exceed the total carbon emission quota C. U If so, proceed directly to step S3.

[0038] As described above, a first threshold is preset for the difference between the actual power generation and the planned power generation. If the difference is greater than the first threshold and the calculated periodic carbon emissions do not exceed the total carbon emission quota, it means that the power generation can meet the demand, that is, there is no need to adjust the current energy supply strategy, and we can directly proceed to the next step.

[0039] Furthermore, in step S2, based on the difference in power generation and the carbon emission situation, the power supply side structure within region D is optimized, specifically as follows:

[0040] S2b, if the current time period T i The difference in power generation within the period is greater than the first threshold, and the periodic carbon emissions C ave Exceeding the total carbon emission quota C U Then, the power plant is structurally optimized according to the following formula (4) until the current time period T. iEnd, then continue to step S3:

[0041]

[0042] Among them, P n Let P0 be the total optimized power generation of the collection of new energy power plants in region D during the current carbon management statistical period T, and let F be the total optimized power generation of the collection of traditional power plants in region D during the current carbon management statistical period T. s,ti For the Tth i The actual power generation of the energy facility set G within a time period, P n,ti For the new energy stations within the region D in the current time period T i Optimized power generation within the system, M j θ represents the actual amount of raw materials used in the j-th traditional power plant after optimization of traditional energy. j ρ is the average energy density of traditional energy sources in the j-th traditional power plant. j M is the average energy conversion efficiency of traditional energy sources in the j-th traditional power plant. j0 C is the planned quota of traditional energy in the j-th traditional power plant. t1i It is the optimized current time period T i The total carbon emissions within region D, where M0 is the carbon emissions in the current time period T. i The projected raw material usage, E, for the j-th conventional power plant in the power generation plan before conventional energy optimization. j It is the carbon emission factor of the j-th traditional energy source.

[0043] As described above, if the difference in power generation is greater than the first threshold and the calculated periodic carbon emissions exceed the total carbon emission quota, it indicates that the current carbon emissions are too high, which may lead to insufficient carbon emission quotas in the current period T. If the power generation has already met the supply, then it is necessary to perform structural optimization of the energy facility geometry, that is, to perform structural optimization of the power plant while ensuring that the power generation meets the requirements.

[0044] Furthermore, step S2b also includes:

[0045] If the increased purchase / use cost of traditional energy after optimization is higher than the cost of directly purchasing carbon emission allowances in the carbon emission trading market within region D, then carbon emission trading allowances can be purchased directly in the carbon emission trading market within region D.

[0046] If the purchase limit C is mentioned M If the problem is insufficient, the power plant should be structurally optimized according to formula (4).

[0047] As described above, cost factors can be considered. For example, if the increased purchase / use cost of traditional energy after optimization is higher than the cost of directly purchasing carbon emission allowances in the target region's carbon emission trading market, then carbon emission allowances in the target region's carbon emission trading market can be purchased directly without performing the optimization in step S2b, further saving time and cost to achieve the goal of energy conservation and emission reduction. When considering purchasing carbon emission allowances in the target region's carbon emission trading market instead of using the formula in step S2b for structural optimization, the available purchase quota C in the target region's carbon emission trading market should also be considered. M If the quantity is insufficient to purchase, then the structural optimization scheme in step S2b still needs to be adopted.

[0048] Furthermore, in step S2, based on the difference in power generation and the carbon emission situation, the power supply side structure within region D is optimized, specifically as follows:

[0049] S2c, if the current time period T i The difference in power generation within the period is less than a first threshold, and the periodic carbon emissions C ave Not exceeding the total carbon emission allowance of C U Then, according to the following formula (5), the power supply side of the traditional power station in the region D will be structurally adjusted:

[0050]

[0051] Where △P0 represents the total additional power generation of the traditional power station within region D, and M... j It is the additional raw material consumption of traditional energy in the j-th traditional power plant, △C avej The increase in carbon emissions in region D after adding additional power generation to a conventional power plant in region D, if ΔC avej ≤(C U -C ave If the carbon emission requirement is met, proceed to step S3; otherwise, purchase the corresponding difference from the carbon emission trading market within region D to meet the carbon emission requirements until the current time period T. i End of step S3.

[0052] As described above, if the difference in power generation is less than the first threshold, and the calculated periodic carbon emissions exceed the total carbon emission allowance, it indicates that the current time period T... i The power generation of new energy power plants in the power generation plan did not reach the expected power generation in the power generation plan within this cycle T. Since it is usually difficult to quickly adjust the power generation of new energy power plants, a strategy can be adopted to further increase the power generation of traditional energy by increasing the power generation of traditional power plants, and to carry out structural optimization and adjustment of the energy facility set.

[0053] Furthermore, in step S2, based on the difference in power generation and the carbon emission situation, the power supply side structure within region D is optimized, specifically as follows:

[0054] S2d, if the current time period T i The difference in power generation within the period is less than a first threshold, and the periodic carbon emissions C ave The total carbon emission allowance exceeds C U At this point, an early warning is issued to the regional dispatch personnel, prompting them and maintenance personnel to inspect the power plants within the energy facility set G, confirm whether there are any faults in the facilities, and whether the instructions of the power generation plan are being executed correctly. After the inspection and confirmation are completed, the process returns to step S1 to deploy and execute the current time period T. i The power generation plan will be implemented, and power generation and carbon emissions will be monitored up to the current time period T. i End of step S3.

[0055] As described above, if the difference in power generation is less than the first threshold and the calculated periodic carbon emissions do not exceed the total carbon emission quota, it indicates that the energy facility set G may have a corresponding fault, resulting in not only the power generation falling short of expectations but also the carbon emissions exceeding the quota. Therefore, it is necessary to issue an early warning to the regional dispatch personnel in a timely manner so that the regional dispatch personnel and maintenance personnel can repair the faulty equipment in a timely manner.

[0056] Furthermore, the step between S1 and S2 also includes:

[0057] S12, Statistical analysis of the current time period T i Purchaseable quotas C in the carbon emissions trading market within region D. M And it is updated in real time;

[0058] Between steps S2 and S3, the following is also included:

[0059] S23. Verify the actual carbon emissions C within the current carbon management statistical period T. act Does it exceed the total carbon emission allowance of C? U If the emission limit is not exceeded, proceed to step S3; if the limit is exceeded, purchase the corresponding difference from the carbon emission trading market in region D to meet the carbon emission requirements, and then proceed to step S3.

[0060] Please refer to Figure 2 A regional carbon management strategy optimization terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the regional carbon management strategy optimization method described above.

[0061] As described above, the beneficial effects of this invention are as follows: Based on the same technical concept, and in conjunction with the aforementioned regional carbon management strategy optimization method, a regional carbon management strategy optimization terminal is provided. By optimizing the energy utilization structure of the target region itself, carbon management within the target region can quickly achieve the predetermined goals. Compared to the existing practice of only focusing on carbon emission allowances at the end of the carbon management statistical cycle, the management strategy of this application has the advantage of continuously monitoring and predicting the carbon emission trend within the region during the carbon management statistical cycle, optimizing the power generation structure in advance, or conducting carbon emission allowance trading in advance, avoiding the traditional practice of sudden carbon emission trading. In particular, it introduces a differentiated management strategy that focuses on carbon emission amounts between different time periods, and calculates based on the corresponding transitional situations of carbon emissions in different time periods, making the carbon emission prediction process more accurate. This not only helps reduce the carbon emission allowance compliance requirements within the region, but also quickly optimizes the power supply structure system for different power generation and consumption situations, achieving the goal of energy conservation and emission reduction. Furthermore, it helps reduce the carbon emission compliance and carbon allowance trading costs for enterprises, promoting the development of a green circular economy.

[0062] This invention provides a regional carbon management strategy optimization method and terminal, applicable to both new energy power plants and traditional power plants, for carbon emission quota management strategies, power supply side structure optimization, and early warning while meeting their electricity demand. The following detailed description is provided in conjunction with specific embodiments.

[0063] Please refer to Figure 1 Embodiment 1 of the present invention is as follows:

[0064] A method for optimizing regional carbon management strategies, in this embodiment, first defines the target region D for which regional carbon management strategy optimization and early warning are required. Within region D, there are several user sets U, representing all energy-consuming users in region D, including emission-controlled enterprises U1, non-emission-controlled enterprises U2, and ordinary users U3. The total carbon emission allowances of region D are C. U One of the users has a carbon allowance of C. Ui The energy facility set G in region D includes all energy-providing facilities like the user set U, such as thermal power plants, photovoltaic power plants, and hydropower plants. The annual emission reduction of energy facility set G is C. CCER .

[0065] like Figure 1 As shown, the steps include:

[0066] S1. Preset target area D, and divide the current carbon management statistical period T into several time periods T1, T2...T n Configure region D in the current time period T iThe power generation plan within (1≤i≤n) includes the power generation F of the energy facility set G in region D within each time period. i ;

[0067] S2, in the current time period T i Within the statistical region D, the real-time power generation F of the energy facility set G monitored is recorded. s Calculate the real-time power generation F s Compared with the current time period T in the power generation plan i Electricity generation F within i The difference is used to obtain the power generation difference. Based on the power generation difference and carbon emission, the power supply side structure in region D is optimized.

[0068] S3. Determine whether the current carbon management statistical period T has ended. If it has not ended, i.e., i < n, return to step S1 and continue the execution of the next time period until i = n, then end the carbon management operation within the current carbon management statistical period T.

[0069] In this embodiment, by optimizing the energy utilization structure of the target area, carbon management within the target area can quickly achieve the predetermined goals. Compared to the existing practice of only focusing on carbon emission allowances at the end of the carbon management statistical cycle, the management strategy of this application has the advantage of continuously monitoring and predicting carbon emission trends within the region during the carbon management statistical cycle, optimizing the power generation structure in advance, or conducting carbon emission allowance trading in advance, avoiding the sudden carbon emission trading in the traditional approach. In particular, it introduces a differentiated management strategy that focuses on carbon emission amounts between different time periods, and calculates based on the corresponding transitional situations of carbon emissions in different time periods, making the carbon emission prediction process more accurate. This not only helps reduce the carbon emission allowance compliance requirements within the region, but also quickly optimizes the power supply structure system for different power generation and consumption situations, achieving the goal of energy conservation and emission reduction. Furthermore, it helps reduce the carbon emission compliance and carbon allowance trading costs for enterprises, promoting the development of a green circular economy.

[0070] In this embodiment, the step between S1 and S2 further includes:

[0071] S12, Statistical analysis of the current time period T i Available carbon emission trading quotas C in the inner region D M And it is updated in real time.

[0072] The steps between S2 and S3 also include:

[0073] S23. Verify the actual carbon emissions C within the current carbon management statistical period T. act Does it exceed the total carbon emission allowance of C? UIf the emission limit is not exceeded, proceed to step S3. If the limit is exceeded, purchase the corresponding difference from the carbon emission trading market in region D to meet the carbon emission requirements, and then proceed to step S3.

[0074] In addition, in this embodiment, step S3 further includes:

[0075] If the process ends (i=n), then the carbon emission data record for the current carbon management statistical period T in region D is generated, and the carbon emission trading record is uploaded to the carbon management server cloud as the historical carbon emission record of the controlled emission enterprise set U1, thus ending the carbon management operation within the current carbon management statistical period T.

[0076] Embodiment 2 of the present invention is as follows:

[0077] A method for optimizing regional carbon management strategies, based on the above-described embodiment one, in this embodiment, uses the current time period T... i For example, the acquisition of carbon emissions in step S2 is specifically as follows:

[0078] Based on the current time period T i Actual carbon emissions C within inner region D ti The calculated periodic carbon emissions C ave .

[0079] Among them, according to the current time period T i Actual carbon emissions C within inner region D ti The calculated periodic carbon emissions C ave This refers to the current monitored actual carbon emissions (C). ti The periodic carbon emissions C are calculated using the following formula (1). ave :

[0080]

[0081] Among them, C r1 C r2 ...refers to the current time period T within the current carbon management statistical period T. i The actual carbon emissions of region D in previous time periods, μ1, μ2...μ n This refers to the various time periods T1, T2...T n The carbon emission proportion weighting coefficient is the ratio of the actual emissions in each time period of the historical carbon management statistical period to the average emissions in each time period of the historical carbon management statistical period.

[0082] In this embodiment, since the carbon emissions of each controlled emission enterprise in the region exhibit a certain degree of continuity across different time periods, without sudden spikes or drops, a Markov chain is introduced to calculate cyclical carbon emissions, taking into account the continuity of emissions between different time periods. The Markov chain can fully consider the continuity between carbon emissions in the previous time period and those in the current time period, and thus, based on this continuity, cyclical carbon emissions can be predicted more accurately. That is, in this embodiment:

[0083] Further, based on the Markov chain, the carbon emission proportion weighting coefficients μ1, μ2...μ n Adjusted to P1, P2...P n Formula (2) is as follows:

[0084]

[0085] Where P 11 ...P nn P is the transition probability value in the transition probability matrix. 11 ...P nn The calculation can be performed by statistically analyzing the carbon emissions of various time periods in the past k historical cycles, selecting the carbon emission data of each time period in a certain historical cycle as a benchmark, and then calculating the probability of change of the carbon emission proportion weighting coefficients of other historical cycles relative to each time period in the previous cycle. Finally, the results of each cycle are normalized by linear mean to obtain P. 11 ...P nn Then, the periodic carbon emissions C are calculated based on this. ave Then the following formula (3) is given:

[0086]

[0087] In this embodiment, a first threshold is set. The relationship between the power generation difference and the first threshold, combined with the relationship between periodic carbon emissions and total carbon emission quotas, yields four scenarios for structural optimization of the target area. Specifically, in step S2, the power supply side structure optimization within area D is performed based on the power generation difference and carbon emission situation.

[0088] Scenario 1:

[0089] S2a, if the current time period T i The difference in power generation within the range is greater than the first threshold, and C ave It did not exceed the total carbon emission quota C U If so, proceed directly to step S3.

[0090] In this embodiment, if the difference in power generation is greater than the first threshold and the calculated periodic carbon emissions do not exceed the total carbon emission quota, it means that the power generation can meet the demand, that is, there is no need to adjust the current energy supply strategy, and we can directly proceed to the next step S3.

[0091] Scenario 2:

[0092] S2b, if the current time period T i The difference in electricity generation within the period exceeds the first threshold, and the periodic carbon emissions C ave Exceeding the total carbon emission quota C U Then, the power plant is structurally optimized according to the following formula (4) until the current time period T. i End, then continue to step S3:

[0093]

[0094] Among them, P n Let P0 be the total optimized power generation of the collection of new energy power plants in region D during the current carbon management statistical period T, and let F be the total optimized power generation of the collection of traditional power plants (such as thermal power plants) in region D during the current carbon management statistical period T. s,ti For the Tth i The actual power generation of energy facility set G within a time period, P n,ti For the new energy stations within region D in the current time period T i Optimized power generation within the system, M j θ represents the actual amount of raw materials used in the j-th traditional power plant after optimization of traditional energy. j ρ is the average energy density of traditional energy sources in the j-th traditional power plant. j M is the average energy conversion efficiency of traditional energy sources in the j-th traditional power plant. j0 C is the planned quota of traditional energy in the j-th traditional power plant. t1i It is the optimized current time period T i The total carbon emissions within region D, M0 is the carbon emissions in the current time period T. i The projected raw material usage, E, for the j-th conventional power plant in the internal power generation plan before conventional energy optimization. j It is the carbon emission factor of the j-th traditional energy source. If we take time period T1 as an example, then i = 1 in the above formula (4).

[0095] In this embodiment, when the difference in power generation is greater than the first threshold and the calculated periodic carbon emissions exceed the total carbon emission quota, it indicates that the current carbon emissions are too high, which may lead to insufficient carbon emission quota in the current period T. When the power generation has already met the supply, it is necessary to perform structural optimization of the energy facility geometry, that is, to perform structural optimization of the power plant while ensuring that the power generation meets the requirements.

[0096] In another embodiment, step S2b further includes:

[0097] If the increased purchase / use cost of conventional energy after optimization is higher than the cost of directly purchasing carbon emission allowances in the carbon emission trading market within region D, then purchasing carbon emission trading allowances in the carbon emission trading market within region D can be considered directly. In other words, cost factors can be taken into account. For example, if the increased purchase / use cost of conventional energy after optimization is higher than the cost of directly purchasing carbon emission allowances in the carbon emission trading market within the target region, then purchasing carbon emission trading allowances in the carbon emission trading market within the target region can be done directly without performing the optimization step S2b, further saving time and costs to achieve the goal of energy conservation and emission reduction.

[0098] At the same time, it should be considered that if the purchase quota C is available... M If insufficient, structural optimization of the power plant should still be considered according to formula (4). That is, when considering purchasing carbon emission trading allowances in the carbon emission trading market within the target area instead of using the formula in step S2b for structural optimization, the available quota C in the carbon emission trading market within the target area should also be considered. M If the quantity is insufficient to purchase, then the structural optimization scheme in step S2b still needs to be adopted.

[0099] Scenario 3:

[0100] S2c, if the current time period T i The difference in electricity generation within the period is less than the first threshold, and the periodic carbon emissions C ave Not exceeding the total carbon emission allowance of C U Then, according to the following formula (5), the power supply side of the traditional power station in region D will be structurally adjusted:

[0101]

[0102] Where △P0 represents the total additional power generation from traditional power plants within region D, and M... j It is the additional raw material consumption of traditional energy in the j-th traditional power plant, △C avej The increase in carbon emissions in region D after adding extra power generation to traditional power plants in region D, if ΔC avej ≤(CU -C ave If the carbon emission requirement is met, proceed to step S3; otherwise, purchase the corresponding difference from the carbon emission trading market within region D to meet the carbon emission requirements until the current time period T. i End of step S3.

[0103] In this embodiment, when the difference in power generation is less than the first threshold and the calculated periodic carbon emissions exceed the total carbon emission allowance, it indicates that the current time period T... i The power generation of new energy power plants in the power generation plan did not reach the expected power generation in the power generation plan within this cycle T. Since it is usually difficult to quickly adjust the power generation of new energy power plants, a strategy can be adopted to further increase the power generation of traditional energy by increasing the power generation of traditional power plants, and to carry out structural optimization and adjustment of the energy facility set.

[0104] Scenario 4:

[0105] S2d, if the current time period T i The difference in electricity generation within the period is less than the first threshold, and the periodic carbon emissions C ave Exceeding the total carbon emission allowance by C U At this point, an early warning is issued to the regional dispatchers, prompting them and maintenance personnel to inspect the power plants within the energy facility cluster G to confirm whether there are any faults in the facilities and whether the instructions for the power generation plan have been correctly executed. After the inspection and confirmation are completed, the process returns to step S1 to deploy and execute the current time period T. i The power generation plan will be implemented, and power generation and carbon emissions will be monitored up to the current time period T. i End of step S3.

[0106] In this embodiment, when the difference in power generation is less than the first threshold and the calculated periodic carbon emissions do not exceed the total carbon emission quota, it indicates that the energy facility set G may have a corresponding malfunction, resulting in not only lower-than-expected power generation but also carbon emissions exceeding the quota. This is because, according to the original power generation plan, if power generation does not meet expectations, the periodic carbon emissions C will be higher. ave It will inevitably be less than the total carbon emission allowance of C. U Therefore, it is necessary to issue timely warnings to regional dispatchers so that they and maintenance personnel can promptly repair the faulty equipment and confirm whether the original power generation plan instructions have been correctly executed.

[0107] Please refer to Figure 2 Embodiment 3 of the present invention is as follows:

[0108] A regional carbon management strategy optimization terminal 1 includes a memory 2, a processor 3, and a computer program stored in the memory 2 and executable on the processor 3. In this embodiment, when the processor 3 executes the computer program, it implements the steps of any one of the embodiments in Embodiments 1 to 3 described above.

[0109] In summary, the regional carbon management strategy optimization method and terminal provided by this invention optimizes the energy utilization structure of the target region, enabling the carbon management within the target region to quickly achieve predetermined goals. Compared to the existing practice of only focusing on carbon emission allowances at the end of the carbon management statistical cycle, the management strategy of this application has the advantage of continuously monitoring and predicting the carbon emission trend within the region during the carbon management statistical cycle, optimizing the power generation structure or conducting carbon emission allowance trading in advance, avoiding the traditional practice of sudden carbon emission trading. In particular, it introduces a differentiated management strategy focusing on carbon emissions at different time periods, and uses Markov chain algorithms for calculation based on the corresponding transitional situations of carbon emissions at different time periods, making the carbon emission prediction process more accurate. This not only helps reduce the carbon emission allowance compliance requirements within the region, but also rapidly optimizes the power supply structure system for different power generation and consumption situations, achieving the goal of energy conservation and emission reduction. Furthermore, it helps reduce the carbon emission compliance and carbon allowance trading costs for enterprises, promoting the development of a green circular economy.

[0110] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for optimizing regional carbon management strategies, characterized in that, Including the following steps: S1. Preset target area D, and divide the current carbon management statistical period T into several time periods. T 1. T 2…… T n Configure the region D in the current time period T i (1≤ i ≤ n The power generation plan within the region D includes the power generation of the energy facility set G in the region D within each time period. F i ; The step between S1 and S2 also includes: S12, Statistical analysis of the current time period T i Purchaseable credits in the carbon emissions trading market within region D. C M And it is updated in real time; S2, in the current time period T i Within the region D, the real-time power generation of the energy facility set G monitored is statistically analyzed. F s Calculate real-time power generation F s Compared with the current time period in the power generation plan T i Electricity generation within F i The difference is used to obtain the power generation difference. Based on the power generation difference and carbon emission situation, the power supply side structure in the region D is optimized. The carbon emission information was obtained specifically as follows: Based on the current time period T i Actual carbon emissions within region D C ti Calculated periodic carbon emissions C ave ; Among them, the one based on the current time period T i Actual carbon emissions within region D C ti Calculated periodic carbon emissions C ave This refers to the actual carbon emissions currently monitored. C ti The periodic carbon emissions are calculated using the following formula (1). C ave : (1)； in, C r1 , C r2 ...refers to the current time period within the current carbon management statistical period T. T i The actual carbon emissions of region D in the previous time periods. μ 1. μ 2…… μ n Refers to each time period T 1. T 2…… T n The carbon emission proportion weighting coefficient is the ratio of the actual emissions in each time period of the historical carbon management statistical period to the average emissions in each time period of the historical carbon management statistical period. The acquisition of the carbon emissions information also includes the following steps: The carbon emission proportion weighting coefficients are based on Markov chains. μ 1. μ 2…… μ n Adjusted to P 1. P 2…… P n Formula (2) is as follows: （2）； in P 11 ... P nn These are the transition probability values ​​in the transition probability matrix, used to calculate periodic carbon emissions. C ave The following formula (3): （3）； Between steps S2 and S3, the following is also included: S23. Verify the carbon emissions within the current carbon management statistical period T. C ave Does it exceed the total carbon emission quota? C U If the carbon emission requirement is not exceeded, proceed to step S3; if it is exceeded, purchase the corresponding difference from the carbon emission trading market in region D to meet the carbon emission requirement, and then proceed to step S3. S3. Determine whether the current carbon management statistical period T has ended. If not, i < n If the condition is met, return to step S1 and continue execution for the next time period until... i=n If the carbon management operation within the current carbon management statistical period T is terminated, then the carbon management operation within that period will end.

2. The method for optimizing a regional carbon management strategy according to claim 1, characterized in that, In step S2, the power supply side structure within region D is optimized based on the power generation difference and carbon emission data, specifically as follows: S2a, if the current time period T i The difference in power generation within the range is greater than the first threshold, and C ave It did not exceed the total carbon emission quota. C U If so, proceed directly to step S3.

3. The method for optimizing a regional carbon management strategy according to claim 1, characterized in that, In step S2, the power supply side structure within region D is optimized based on the power generation difference and carbon emission data, specifically as follows: S2b, if the current time period T i The difference in power generation within the period is greater than the first threshold, and the periodic carbon emissions are... C ave Exceeding the total carbon emission quota C U Then, the power plant is structurally optimized according to the following formula (4) until the current time period. T i End, then continue to step S3: （4）； in, P n The total power generation of the new energy power plants within region D, after optimization, during the current carbon management statistical period T. P 0 represents the optimized total power generation of the traditional power plant cluster within region D during the current carbon management statistical period T. F s,ti For the first T i The actual power generation of the energy facility set G within a given time period. P n,ti For the new energy stations within the area D in the current time period T i Optimized power generation within the system M j It is the first j The actual amount of raw materials used in a traditional power plant after optimizing traditional energy sources. θ j It is the first j The average energy density of traditional energy sources in a traditional power plant ρ j It is the first j Average energy conversion efficiency of traditional energy sources in a traditional power plant M j0 It is the first j The planned quota of traditional energy in each traditional power plant C t1i This is the optimized current time period. T i The total carbon emissions within region D. M 0 represents the current time period. T i The power generation plan described in the article j The estimated raw material usage of a traditional power plant before traditional energy optimization E j It is the first j Carbon emission factors of traditional energy sources.

4. The method for optimizing a regional carbon management strategy according to claim 3, characterized in that, Step S2b further includes: If the increased purchase / use cost of traditional energy after optimization is higher than the cost of directly purchasing carbon emission allowances in the carbon emission trading market within region D, then carbon emission trading allowances can be purchased directly in the carbon emission trading market within region D. If the purchase limit is as stated C M If the problem is insufficient, the power plant should be structurally optimized according to formula (4).

5. The method for optimizing a regional carbon management strategy according to claim 1, characterized in that, In step S2, the power supply side structure within region D is optimized based on the power generation difference and carbon emission data, specifically as follows: S2c, if the current time period T i The difference in power generation within the period is less than a first threshold, and the periodic carbon emissions are... C ave Not exceeding the total carbon emission quota of C U Then, according to the following formula (5), the power supply side of the traditional power station in the region D will be structurally adjusted: （5）； in, △P 0 represents the additional total power generation generated by traditional power plants within region D, while △M j It is the first j The additional raw material consumption of traditional energy in a conventional power plant. △C avej The increase in carbon emissions in region D after adding additional power generation to conventional power plants in region D, if ≤( C U - C ave If the carbon emission requirement is met, proceed to step S3; otherwise, purchase the corresponding difference from the carbon emission trading market within region D to meet the carbon emission requirements until the current time period. T i End of step S3.

6. The method for optimizing a regional carbon management strategy according to claim 1, characterized in that, In step S2, the power supply side structure within region D is optimized based on the power generation difference and carbon emission data, specifically as follows: S2d, if the current time period T i The difference in power generation within the period is less than a first threshold, and the periodic carbon emissions are... C ave Exceeding the total carbon emission quota C U At this point, an early warning is issued to the regional dispatch personnel, prompting them and maintenance personnel to inspect the power plants within the energy facility set G to confirm whether there are any faults in the facilities and whether the instructions of the power generation plan are being executed correctly. After the inspection and confirmation are completed, the process returns to step S1 to deploy and execute the current time period. T i The power generation plan will be implemented, and power generation and carbon emissions will be monitored up to the current time period. T i End of step S3.

7. A regional carbon management strategy optimization terminal, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the steps of the regional carbon management strategy optimization method according to any one of claims 1 to 6.

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