Method, device and equipment for determining carbon compliance scheme and storage medium

Abstract

The application provides a carbon compliance scheme determination method, device, equipment and storage medium. By obtaining historical carbon emissions, historical carbon quota data, historical voluntary emission reduction data, historical energy consumption data, planned production data and carbon quota estimates of the control and emission enterprise, and further determining the carbon quota price sequence, the voluntary emission reduction price sequence and the carbon emissions corresponding to each compliance stage, the carbon quota purchase amount, the first purchase time, the voluntary emission reduction purchase amount and the second purchase time of each compliance stage can be determined in combination with the carbon emissions, the carbon quota estimates, the price changes and the historical compliance resource conditions. The method reduces the deviation between static calculation and actual compliance execution, and improves the dynamic adaptability of the carbon compliance scheme and the compliance cost control precision under different compliance stages.

Description

Technical Field

[0001] This application relates to the field of carbon emission management technology, and in particular to a method, apparatus, equipment and storage medium for determining a carbon compliance scheme. Background Technology

[0002] In the current carbon compliance management of emission-controlled enterprises, compliance decisions are usually made by combining carbon emission accounting, quota gap calculation, quota and emission reduction procurement, and emission reduction measure evaluation.

[0003] However, existing solutions are mostly based on static gap calculations or empirical judgments, which are difficult to adapt to the decision-making needs of different compliance stages. At the same time, when facing carbon compliance decision-making needs at different compliance stages, existing technologies do not comprehensively consider the company's historical compliance status, emission change trends, energy consumption characteristics, planned production status, and carbon market-related factors. They lack the ability to coordinate and analyze the compliance needs and compliance resources at each compliance stage, resulting in limited accuracy of compliance cost control and adaptability of solutions.

[0004] Therefore, how to improve the dynamic adaptability and cost optimization of carbon compliance decisions at different stages of compliance has become a technical problem that needs to be solved. Summary of the Invention

[0005] This application provides a method, apparatus, equipment, and storage medium for determining carbon compliance schemes, in order to address the shortcomings of existing technologies that lack the ability to collaboratively analyze compliance requirements and resources at each compliance stage, resulting in limited accuracy in compliance cost control and scheme adaptability.

[0006] In a first aspect, this application provides a method for determining a carbon compliance scheme, the method comprising:

[0007] Obtain carbon compliance data for enterprises subject to emission control. The carbon compliance data includes: historical carbon emissions, historical carbon quota data, historical voluntary emission reduction data, historical energy consumption data, planned production data, and carbon quota estimates for at least one compliance phase.

[0008] Based on historical carbon allowance data and historical voluntary emission reduction data for at least one compliance phase, determine the carbon allowance price series and voluntary emission reduction price series corresponding to each compliance phase.

[0009] Based on historical carbon emissions, historical energy consumption data, and planned production data, determine the carbon emissions corresponding to each compliance phase.

[0010] Based on carbon emissions, carbon allowance estimates, carbon allowance price series, voluntary emission reduction price series, historical carbon allowance data, and historical voluntary emission reduction data, a carbon compliance plan is determined for each compliance phase. The carbon compliance plan is used to indicate the amount of carbon allowances purchased and the corresponding first purchase time, the amount of voluntary emission reductions purchased and the corresponding second purchase time.

[0011] In one possible implementation, historical carbon allowance data includes: historical carbon allowance prices and corresponding first trading volumes; historical voluntary emission reduction data includes: historical voluntary emission reduction prices and corresponding second trading volumes; based on historical carbon allowance data and historical voluntary emission reduction data for at least one compliance phase, a carbon allowance price sequence and a voluntary emission reduction price sequence corresponding to each compliance phase are determined, including:

[0012] For any one of the at least one performance phases, determine the predicted period of the performance phase;

[0013] Based on historical carbon allowance prices, first trading volume, historical voluntary emission reduction prices, and second trading volume, a carbon allowance price sequence is predicted for the forecast period during the compliance phase. The carbon allowance price sequence is used to indicate the predicted carbon allowance price and the predicted voluntary emission reduction price for each forecast period within the forecast period.

[0014] In one possible implementation, historical energy consumption data includes: historical output and historical carbon emissions per unit for multiple product types; planned output data includes: planned output for multiple product types; and based on historical carbon emissions, historical energy consumption data, and planned output data, the carbon emissions corresponding to each compliance phase are determined, including:

[0015] For any one of the multiple product types, a carbon emission prediction model is constructed based on the product type's historical output and historical unit carbon emissions.

[0016] Input the planned output corresponding to the product type into the carbon emission prediction model to obtain the predicted unit carbon emission of the product type during the prediction period;

[0017] The carbon emission forecast for each product type is determined based on the unit carbon emission forecast and the planned output corresponding to the product type.

[0018] The carbon emissions for each compliance stage are determined based on the predicted and historical carbon emissions for multiple product types corresponding to multiple compliance stages.

[0019] In one possible implementation, the method further includes:

[0020] Determine the predicted electricity consumption and green electricity price series for each stage of compliance within the corresponding forecast period;

[0021] For any one of the multiple forecast periods, the green electricity cost difference is determined based on the first green electricity price in the green electricity price series and the corresponding forecasted electricity consumption. The first green electricity price is less than the other green electricity prices in the green electricity price series.

[0022] If the cost difference of green electricity is greater than the preset difference, the forecast period is determined as the green electricity purchase period;

[0023] Based on the predicted and historical carbon emissions for multiple product types corresponding to multiple compliance phases, the carbon emissions for each compliance phase are determined, including:

[0024] Determine the predicted carbon emissions corresponding to at least one green electricity purchase cycle;

[0025] Based on the carbon emission forecasts for multiple product types, historical carbon emission levels, and carbon emission forecasts for at least one forecast period, the carbon emission level corresponding to each compliance phase is determined.

[0026] In one possible implementation, carbon compliance data also includes: grid-connected electricity emission factors, green electricity emission factors, and historical grid-connected electricity prices. Based on the first green electricity price in the green electricity price series and the corresponding predicted electricity consumption, the green electricity cost difference is determined, including:

[0027] The grid forecast cost is determined based on the grid emission factor, the green electricity emission factor, and the carbon quota forecast price for the forecast period.

[0028] The green electricity forecast cost is determined based on the first green electricity price, historical grid electricity prices, and the forecasted electricity consumption for the forecast period.

[0029] The difference between the grid forecast cost and the green electricity forecast cost is used as the green electricity cost difference.

[0030] In one possible implementation, carbon compliance data further includes: data on at least one carbon reduction program, and the method further includes:

[0031] For any one of the at least one carbon reduction schemes, determine the scheme cost, the energy price corresponding to at least one energy source, and the energy reduction amount;

[0032] The carbon reduction cost difference of the carbon reduction scheme is determined based on the scheme cost, the energy price corresponding to at least one energy source, the energy reduction amount, and the carbon quota forecast price for the forecast period.

[0033] If the cost difference of green electricity exceeds the preset difference, the carbon reduction plan will be implemented within the forecast period.

[0034] Based on carbon emission forecasts for multiple product types, historical carbon emission figures, and carbon emission forecasts for at least one forecast period, the carbon emission figures for each compliance phase are determined, including:

[0035] Determine the predicted carbon reduction amount corresponding to at least one prediction cycle for implementing the carbon reduction plan;

[0036] Based on the carbon emission forecasts for multiple product types, historical carbon emission levels, carbon emission forecasts for at least one forecast period, and predicted carbon reduction, the carbon emission levels corresponding to each compliance phase are determined.

[0037] One possible implementation approach includes:

[0038] If the compliance phase is the verified but not yet implemented phase, the carbon compliance plan is used to indicate the carbon allowance purchase volume and the corresponding first purchase time, the voluntary emission reduction purchase volume and the corresponding second purchase time;

[0039] If the compliance phase is the unverified and unimplemented phase, the carbon compliance plan is used to indicate the carbon allowance purchase volume and the corresponding first purchase time, the voluntary emission reduction purchase volume and the corresponding second purchase time, and the green electricity purchase volume corresponding to at least one green electricity purchase cycle.

[0040] If the compliance phase has not yet commenced, the carbon compliance scheme is used to indicate the amount of carbon allowances purchased and the corresponding first purchase time, the amount of voluntary emission reductions purchased and the corresponding second purchase time, the amount of green electricity purchased for at least one green electricity purchase cycle, and the carbon reduction scheme for at least one forecast cycle.

[0041] Secondly, this application provides an apparatus for determining a carbon compliance scheme, the apparatus comprising:

[0042] The acquisition module is used to acquire carbon compliance data corresponding to the controlled emission enterprises. The carbon compliance data includes: historical carbon emissions, historical carbon quota data, historical voluntary emission reduction data, historical energy consumption data, planned production data, and carbon quota estimates corresponding to at least one compliance stage.

[0043] The determination module is used to determine the carbon allowance price series and voluntary emission reduction price series corresponding to each compliance stage based on historical carbon allowance data and historical voluntary emission reduction data for at least one compliance stage; to determine the carbon emissions corresponding to each compliance stage based on historical carbon emissions, historical energy consumption data, and planned production data; and to determine the carbon compliance scheme corresponding to each compliance stage based on carbon emissions, carbon allowance estimates, carbon allowance price series, voluntary emission reduction price series, historical carbon allowance data, and historical voluntary emission reduction data. The carbon compliance scheme is used to indicate the amount of carbon allowances purchased and the corresponding first purchase time, the amount of voluntary emission reductions purchased and the corresponding second purchase time.

[0044] In one possible implementation, the historical carbon allowance data includes: historical carbon allowance prices and corresponding first trading volumes; the historical voluntary emission reduction data includes: historical voluntary emission reduction prices and corresponding second trading volumes; the device also includes: a processing module.

[0045] The determination module is used to determine the predicted period of the performance phase for any one of the at least one performance phase.

[0046] The processing module is used to predict the carbon allowance price sequence during the forecast period in the compliance phase based on historical carbon allowance prices, first trading volume, historical voluntary emission reduction prices, and second trading volume. The carbon allowance price sequence is used to indicate the predicted carbon allowance price and the predicted voluntary emission reduction price for each forecast period within the forecast period.

[0047] In one possible implementation, historical energy consumption data includes historical output and historical carbon emissions per unit for multiple product types, and planned output data includes planned output for multiple product types. The processing module is also used to construct a carbon emission prediction model for any one of the multiple product types based on the historical output and historical carbon emissions per unit for that product type; and to input the planned output corresponding to the product type into the carbon emission prediction model to obtain the predicted carbon emissions per unit for that product type during the prediction period.

[0048] The determination module is used to determine the carbon emission forecast for a product type based on the unit carbon emission forecast and the planned output corresponding to the product type; and to determine the carbon emission corresponding to each compliance stage based on the carbon emission forecasts for multiple product types corresponding to multiple compliance stages and historical carbon emission volumes.

[0049] In one possible implementation, the determining module is further configured to determine the predicted electricity consumption and green electricity price sequence for each performance stage within the corresponding forecast period; for any one of the multiple forecast periods, based on the first green electricity price in the green electricity price sequence and the corresponding predicted electricity consumption, determine the green electricity cost difference, wherein the first green electricity price is less than other green electricity prices in the green electricity price sequence; and if the green electricity cost difference is greater than a preset difference, determine the forecast period as the green electricity purchase period.

[0050] The processing module is used to determine the carbon emission forecast corresponding to at least one green electricity purchase cycle; and to determine the carbon emission corresponding to each compliance stage based on the carbon emission forecasts of multiple product types, historical carbon emissions, and the carbon emission forecasts corresponding to at least one forecast cycle.

[0051] In one possible implementation, the carbon compliance data also includes: grid-connected power emission factors, green electricity emission factors, and historical grid-connected electricity prices. A processing module is used to determine the grid-connected power emission factor, green electricity emission factor, and carbon quota forecast price for the forecast period; determine the green electricity forecast cost based on the first green electricity price, historical grid-connected electricity prices, and forecasted electricity consumption for the forecast period; and use the difference between the grid-connected power emission factor and the green electricity forecast cost as the green electricity cost difference.

[0052] In one possible implementation, the carbon compliance data further includes: at least one carbon reduction scheme data; a determination module is further configured to, for any one of the at least one carbon reduction schemes, determine the scheme cost, the energy price corresponding to at least one energy source, and the energy reduction amount; based on the scheme cost, the energy price corresponding to at least one energy source, the energy reduction amount, and the carbon quota forecast price for the forecast period, determine the carbon reduction cost difference of the carbon reduction scheme; and if the green electricity cost difference is greater than a preset difference, determine to execute the carbon reduction scheme within the forecast period.

[0053] The processing module is used to determine the predicted carbon reduction amount corresponding to at least one prediction period for implementing the carbon reduction plan; and to determine the carbon emission amount corresponding to each compliance stage based on the predicted carbon emission amounts of multiple product types, historical carbon emission amounts, predicted carbon emission amounts corresponding to at least one prediction period, and predicted carbon reduction amounts.

[0054] One possible implementation approach includes:

[0055] If the compliance phase is the verified but not yet implemented phase, the carbon compliance plan is used to indicate the carbon allowance purchase volume and the corresponding first purchase time, the voluntary emission reduction purchase volume and the corresponding second purchase time;

[0056] If the compliance phase is the unverified and unimplemented phase, the carbon compliance plan is used to indicate the carbon allowance purchase volume and the corresponding first purchase time, the voluntary emission reduction purchase volume and the corresponding second purchase time, and the green electricity purchase volume corresponding to at least one green electricity purchase cycle.

[0057] If the compliance phase has not yet commenced, the carbon compliance scheme is used to indicate the amount of carbon allowances purchased and the corresponding first purchase time, the amount of voluntary emission reductions purchased and the corresponding second purchase time, the amount of green electricity purchased for at least one green electricity purchase cycle, and the carbon reduction scheme for at least one forecast cycle.

[0058] Thirdly, this application provides an electronic device, including: a memory and a processor;

[0059] The memory stores the instructions executed by the computer.

[0060] The processor executes computer execution instructions stored in the memory to implement the method shown in the first aspect and / or various possible implementations of the first aspect above.

[0061] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the methods shown in the first aspect and / or various possible implementations of the first aspect.

[0062] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the methods shown in the first aspect and / or various possible implementations of the first aspect.

[0063] The carbon compliance scheme determination method, apparatus, equipment, and storage medium provided in this application acquire historical carbon emissions, historical carbon quota data, historical voluntary emission reduction data, historical energy consumption data, planned production data, and carbon quota estimates for controlled emission enterprises. Furthermore, it determines the carbon quota price series, voluntary emission reduction price series, and carbon emissions corresponding to each compliance stage. By combining carbon emissions, carbon quota estimates, price changes, and historical compliance resource conditions, it can specifically determine the carbon quota purchase amount, the first purchase time, the voluntary emission reduction purchase amount, and the second purchase time for each compliance stage. This method reduces the deviation between static calculations and actual compliance execution, and improves the dynamic adaptability of carbon compliance schemes and the accuracy of compliance cost control at different compliance stages. Attached Figure Description

[0064] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0065] Figure 1 A flowchart illustrating a method for determining a carbon compliance scheme provided in an embodiment of this application;

[0066] Figure 2 A schematic diagram of a device for determining a carbon compliance scheme provided in an embodiment of this application;

[0067] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0068] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0069] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0070] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented, for example, in orders other than those illustrated or described herein.

[0071] In this application, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0072] The carbon compliance scheme determination technology is applied to emission-controlled enterprises such as power generation, steel, cement, chemical, and manufacturing companies that are included in the carbon emission quota management system.

[0073] Related operations typically rely on the coordinated operation of the enterprise's production management system, energy management system, and carbon trading information platform to collect data such as historical emissions, energy consumption, quota holdings, emission reduction holdings, and planned production, and to form procurement and compliance decisions for different compliance stages.

[0074] When conducting carbon compliance management, existing emission-controlled enterprises typically first calculate the quota gap based on historical carbon emission accounting results and the quotas they already hold. Then, they combine the market price of carbon quotas, the price of voluntary emission reductions, and the enterprise's annual production plan to determine the amount of carbon quotas to be purchased, the amount of emission reductions to be purchased, and the corresponding emission reduction measures.

[0075] However, the above-mentioned technical solutions are mostly based on static calculations and use similar processing logic for different performance stages. It is difficult to distinguish the completeness of data and decision-making priorities in states such as verified but not yet cleared, unverified and not yet cleared, and performance cycle not yet started, resulting in a discrepancy between the performance plan and the actual business timeline of the enterprise.

[0076] Meanwhile, there is a lack of linkage analysis between carbon quotas, voluntary emission reductions and changes in corporate emissions. The timing of procurement often relies on experience-based judgments, and emission forecasts and price changes cannot be synchronized into the decision-making process, resulting in a lack of targeted purchasing volume and timing.

[0077] In other words, the relevant technologies lack suitable dynamic optimization decision-making methods for the above-mentioned multi-time-series compliance scenarios, and cannot help emission control enterprises combine their own real-time emission data to plan tiered carbon reduction measures in advance, coordinate emission reduction paths and quota procurement strategies, and achieve the best overall compliance cost.

[0078] To address the aforementioned issues, this application provides a method for determining carbon compliance schemes. This method determines carbon compliance schemes for each compliance stage, incorporating carbon emissions, carbon allowance estimates, price series, historical carbon allowance data, and historical voluntary emission reduction data into the decision-making process. This results in the output of carbon allowance purchase quantities and their corresponding first purchase time, and voluntary emission reduction purchase quantities and their corresponding second purchase time. This method comprehensively considers the historical compliance status of emission-controlled enterprises, emission trends, energy consumption characteristics, planned production, and relevant carbon market factors. It conducts a collaborative analysis of compliance needs and resources at each compliance stage, and based on this, determines carbon compliance schemes suitable for each stage. This reduces the discrepancy between static calculations and actual compliance implementation, improving the dynamic adaptability and cost optimization level of carbon compliance decisions.

[0079] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0080] Figure 1 This is a flowchart illustrating a method for determining a carbon compliance scheme, provided as an embodiment of this application. Figure 1 As shown in the embodiments of this application, the method for determining a carbon compliance scheme includes:

[0081] S101. Obtain carbon compliance data for enterprises subject to emission control. The carbon compliance data includes: historical carbon emissions, historical carbon quota data, historical voluntary emission reduction data, historical energy consumption data, planned production data, and carbon quota estimates for at least one compliance phase.

[0082] Among them, carbon compliance data serves as the input data set for subsequent calculations, which is used to carry the historical compliance basis, future production arrangements, and resource information available for compliance of emission-controlled enterprises at different compliance stages.

[0083] The compliance phase is used to distinguish different time periods or business processes of emission-controlled enterprises in the carbon compliance cycle. The compliance phase may include, for example, the verified but not implemented phase, the unverified and unimplemented phase, and the initiation phase.

[0084] For example, for emission-controlled enterprises, the carbon compliance stage corresponding to the previous year could be the verified but not implemented stage, the carbon compliance stage corresponding to the current year could be the unverified and unimplemented stage, and the carbon compliance stage corresponding to the next year could be the initiation stage.

[0085] Historical carbon emissions are used to characterize the emissions results calculated by controlled emission enterprises during the period in which they occurred. Historical carbon quota data are used to characterize the carbon quota information that controlled emission enterprises have held, obtained, traded, or locked in during the corresponding compliance phase. Historical voluntary emission reduction data are used to characterize the voluntary emission reduction information that controlled emission enterprises have held, registered, or have the availability for compliance during the corresponding compliance phase.

[0086] Historical energy consumption data is used to characterize the consumption of energy types such as electricity, coal, natural gas, steam, and fuel oil by enterprises in the past production process. Planned output data is used to characterize the production plan and output arrangement in the subsequent period. Carbon quota estimates are used to characterize the amount of quotas that enterprises are expected to obtain or allocate in the subsequent compliance phase.

[0087] The entity that performs this step may be a carbon management server deployed on the enterprise side, a data processing server that interfaces with the enterprise resource planning system, or a compliance decision-making platform that is linked to the carbon trading platform. This application does not impose any restrictions on this.

[0088] When obtaining carbon compliance data for enterprises subject to emission control, a data access list can be established first, defining the historical carbon emissions in the enterprise emission accounting system, the historical carbon quota data in the enterprise quota account ledger, the historical voluntary emission reduction data in the emission reduction holding ledger, the historical energy consumption data in the energy management system, the planned output data in the production planning system, and the carbon quota estimate in the quota allocation calculation module as different data sources.

[0089] Subsequently, raw records from various data sources are received through API calls, direct database connections, batch file imports, or message bus subscriptions. Each record is then appended with an enterprise identifier, a performance year identifier, a performance stage identifier, and a timestamp to form a traceable data entry.

[0090] In one possible embodiment, historical carbon allowance data may include, for example, historical carbon allowance prices and corresponding first trading volumes; historical voluntary emission reduction data may include, for example, historical voluntary emission reduction prices and corresponding second trading volumes; historical energy consumption data may include, for example, historical output and historical unit carbon emissions for multiple product types in multiple historical periods; and planned output data may include, for example, planned output for each future forecast period for multiple product types.

[0091] Carbon compliance data may also include, for example, grid electricity emission factors, green electricity emission factors, and historical grid electricity prices.

[0092] Among them, the historical carbon quota price and the historical voluntary emission reduction price refer to the historical transaction price within the historical period.

[0093] The first trading volume and the second trading volume can respectively represent the remaining carbon allowances from the previous compliance phase or the purchased carbon allowances and voluntary emission reductions corresponding to the current compliance phase that can be used within the corresponding compliance phase.

[0094] The grid-connected electricity emission factor is an abbreviation for the grid-purchased electricity emission factor. It refers to the carbon footprint factor of coal-fired power generation, and the unit can be kgCO2e / kWh.

[0095] Green electricity emission factors refer to the carbon footprint factors of electricity generated by clean energy sources that replace coal-fired power generation, such as wind power carbon footprint factors, photovoltaic power carbon footprint factors, and hydropower carbon footprint factors.

[0096] Historical carbon emissions can be totaled, for example, by month, quarter, or accounting batch; historical carbon quota data and historical voluntary emission reduction data can include information such as time, quantity, source, or status related to compliance resources.

[0097] Historical energy consumption data may include, for example, energy type, unit of measurement, quantity consumed, statistical period, and corresponding production line identifier;

[0098] Planned production data may include, for example, product category, planning period, planned output, and production line load schedule;

[0099] Carbon quota estimates may include, for example, the estimated quantity, the basis for the estimate, and the corresponding compliance stage.

[0100] After data access, fields can be mapped and units can be unified for data from different sources. For example, the volume of standard coal, electricity, and natural gas can be converted into a unified energy accounting standard according to the company's established conversion rules, and the quantity of each contractual resource can be uniformly converted into a carbon dioxide equivalent standard that can be used for contractual deduction.

[0101] For data with missing data, duplication, time misalignment, or inconsistent definitions, it can be cleaned according to preset rules, such as deleting duplicate data entries, filling in missing time labels, resampling cross-day data according to the accounting cycle, and marking outliers that exceed a reasonable range so that the rule engine can correct or remove them.

[0102] For example, after the data acquisition is completed, all carbon compliance data is organized into phase data packages according to the compliance stage. Each phase data package contains at least the historical carbon emissions, historical carbon quota data, historical voluntary emission reduction data, historical energy consumption data, planned production data, and carbon quota estimates corresponding to that stage, and establishes the time sequence relationship and data inheritance relationship between the stages.

[0103] For example, the amount of carbon allowances purchased in the previous stage but not used for collection can be rolled into the historical carbon allowance data of the next stage, and the energy consumption intensity confirmed in the previous stage can also be used as the basis parameter for emission calculation in the next stage.

[0104] S102. Based on historical carbon allowance data and historical voluntary emission reduction data for at least one compliance phase, determine the carbon allowance price sequence and voluntary emission reduction price sequence corresponding to each compliance phase.

[0105] Among them, the carbon allowance price series is used to indicate the change of carbon allowance price over time in the corresponding compliance phase, and the voluntary emission reduction price series is used to indicate the change of voluntary emission reduction price over time in the corresponding compliance phase. Both serve as the direct basis for determining the purchase time in the future.

[0106] Historical carbon allowance data can reflect not only the quantity held and historical trading results, but also the price and time changes of compliance resources in the market; historical voluntary emission reduction data can also carry price information and trading rhythm of voluntary emission reduction resources at different points in time.

[0107] The performance phase serves to stratify the price sample in this step, allowing market behavior characteristics at different stages to be included in the calculation separately, rather than using a single static price as a uniform substitute.

[0108] In practice, historical transaction details related to carbon allowances and voluntary emission reductions can be extracted from the phase data package, sorted by transaction date, and used to form an original price sample table.

[0109] For each type of fulfillment resource, it is first aggregated according to a preset time granularity, which can be set to daily, weekly, or monthly. When daily granularity is selected, multiple transactions within the same trading day are summarized to obtain the representative price for that trading day; when weekly or monthly granularity is selected, the transaction prices within that time window are summarized and the representative price for the window is output, thus obtaining a set of price points arranged in chronological order.

[0110] During the sample construction process, price points can be filled in for periods without transactions by using methods such as previous value continuation, adjacent mean interpolation, or external market index mapping, so that a continuous price sequence can be formed subsequently.

[0111] In one possible implementation, when cleaning the price sample, obviously distorted abnormal transactions can be removed first, and then data from different trading channels and different commodity codes that belong to the same compliance resource caliber can be uniformly classified. After cleaning, normalization processing is used to eliminate price scale differences between different compliance stages, and then carbon quota price series and voluntary emission reduction price series corresponding to each compliance stage are formed according to time sequence.

[0112] This step involves creating price sequences from historical carbon quota data and historical voluntary emission reduction data according to the compliance stage. Price changes can then be incorporated into the subsequent compliance decision-making process, thereby enabling procurement decisions to no longer rely on a single experience-based judgment, but rather to be based on a phased and time-based price trajectory.

[0113] In one possible implementation, where historical carbon allowance data includes historical carbon allowance prices and corresponding first trading volumes, and historical voluntary emission reduction data includes historical voluntary emission reduction prices and corresponding second trading volumes, the specific implementation of determining the carbon allowance price sequence and voluntary emission reduction price sequence corresponding to each compliance phase may include, for example:

[0114] For any one of the at least one compliance phases, the forecast period for the compliance phase can be determined first; then, based on historical carbon allowance prices, the first trading volume, historical voluntary emission reduction prices, and the second trading volume, the carbon allowance price sequence within the forecast period of the compliance phase can be predicted.

[0115] Among them, the carbon allowance price series is used to indicate the predicted price of carbon allowances and the predicted price of voluntary emission reductions for each prediction period within the prediction period.

[0116] In this embodiment, the prediction period of the performance stage can be determined first based on the performance stage identifier, and the period can be discretized into multiple prediction cycles, such as daily, weekly or monthly.

[0117] For example, if the compliance phase is a verified but not implemented phase (such as the previous year), since the carbon allowance price series and voluntary emission reduction price series corresponding to the verified but not implemented phase are known data, there is no forecast period for this compliance phase; therefore, this step is mainly for the unverified and unimplemented phases and the phases that need to be forecasted.

[0118] If the performance phase is an unverified and unexecuted phase (such as the current year), and the forecast period is divided into months, then the starting period of the forecast period corresponding to this performance phase is the next month when this step is executed, and the ending period can be, for example, December of the current year.

[0119] For example, if the current date is April 15th, the predicted period is from May to December of this year.

[0120] If the performance phase is the initiation phase (e.g., the following year), and the forecast period is divided into months, then the forecast period corresponding to this performance phase can be the entire year from January to December of the following year.

[0121] After obtaining the corresponding forecast period, the historical carbon quota price and the first trading volume, as well as the historical voluntary emission reduction price and the second trading volume, can be input into the price forecast model.

[0122] The price prediction model can be any of the following: a time series regression model, a recurrent neural network model, or a joint prediction model with trading volume characteristics. The price prediction model can output the carbon quota prediction price and the voluntary emission reduction prediction price corresponding to each prediction period, and form the carbon quota price series for the compliance phase.

[0123] In practice, historical carbon allowance prices and the first trading volume constitute the joint features for predicting carbon allowance prices, and historical voluntary emission reduction prices and the second trading volume constitute the joint features for predicting voluntary emission reduction prices. During training, the model uses price fluctuations and trading volume changes within historical periods as samples, and obtains the prediction relationship by minimizing the deviation between the predicted value and the actual value through parameterization.

[0124] For a selected performance phase, the price forecasting model outputs the price series only within the forecast period corresponding to that performance phase, thus ensuring that the forecast results are consistent with the performance timeline.

[0125] This step allows the determination of the price series to simultaneously consider price levels and trading activity. The forecast results can be mapped to the predicted prices of carbon allowances and voluntary emission reductions for each forecast period within the compliance phase, thus providing a continuous price basis for determining the procurement timing of subsequent compliance plans. By limiting the forecast scope to the forecast period of the compliance phase, the resulting series matches the actual compliance status, supporting phased compliance decisions.

[0126] S103. Based on historical carbon emissions, historical energy consumption data, and planned production data, determine the carbon emissions corresponding to each compliance phase.

[0127] Among them, carbon emissions can represent the total emissions that controlled emission enterprises need to include in their compliance accounting at the corresponding compliance stage. It is a core input for subsequent assessment of compliance resource gaps and determination of purchase volume.

[0128] In practice, we can first conduct correlation analysis on historical carbon emissions and historical energy consumption data to establish a mapping relationship between production activities, energy use and carbon emissions.

[0129] For example, the historical period is divided into multiple statistical units, and the output, energy consumption and corresponding carbon emissions are extracted in each statistical unit. The emission level that matches the planned output is calculated by regression fitting, emission factor method or intensity coefficient method, so as to obtain the stage emission measurement relationship that matches the actual production situation.

[0130] In one possible embodiment, carbon emissions can be estimated according to the following relationship: first, historical emission levels are calculated based on historical carbon emissions and production data of the same period; then, the emission levels are corrected based on historical energy consumption data to form the predicted emission levels corresponding to the target stage; finally, the predicted emissions corresponding to each compliance stage are obtained by combining the planned production data.

[0131] If expressed as a formula, it can be expressed as "Stage carbon emissions = Predicted emissions based on planned production data + Actual emissions during the period in which emissions occurred".

[0132] Among them, the predicted emission level reflects the inheritance relationship between historical emissions and energy consumption and future production. The actual emissions during the period that have occurred are used to include the emissions that have actually occurred and been accounted for in the phase into the total, so as to avoid the prediction results from being duplicated or disconnected from the confirmed emissions.

[0133] For situations where the implementation phase has entered the later stages, the total emissions for the phase can be divided into two parts: "actual emissions that have occurred" and "predicted emissions for the remaining period" before summing them up.

[0134] In another possible implementation, corresponding carbon emission calculation relationships can be established for at least one compliance phase. For example, the roles of historical carbon emissions, historical energy consumption data, and planned production data in the calculation can be adjusted based on the differences in the completeness of historical data, energy consumption, and planned production arrangements at different compliance phases, in order to improve the consistency between carbon emissions and actual business timing.

[0135] This step integrates historical carbon emissions, historical energy consumption data, and planned production data into emissions calculations, enabling emissions changes of controlled enterprises at different compliance stages to be quantified and incorporated into the decision-making process along with subsequent price series and available quota resources.

[0136] In one possible implementation, given that historical energy consumption data includes historical output and historical carbon emissions per unit for multiple product types, and planned output data includes planned output for multiple product types, when determining the carbon emissions for each compliance phase, a carbon emission prediction model can be constructed for any one of the multiple product types based on its historical output and historical carbon emissions per unit. Then, the planned output corresponding to the product type is input into the carbon emission prediction model to obtain the predicted carbon emissions per unit for that product type during the prediction period.

[0137] Then, based on the unit carbon emission forecast and the planned output corresponding to the product type, the carbon emission forecast for that product type is determined; finally, based on the carbon emission forecasts for multiple product types corresponding to multiple compliance stages and historical carbon emission volumes, the carbon emission volume corresponding to each compliance stage is determined.

[0138] Among them, enterprises subject to emission control may produce a variety of products, each of which consumes different types and amounts of energy, and the output of each product may also vary at different times. Therefore, carbon emissions of different product types can be predicted separately according to product type, and then the total carbon emissions of enterprises subject to emission control during the compliance phase can be calculated.

[0139] Understandably, the historical production data of enterprises subject to emission control can be approximated as a linear function in the absence of major technological innovations, and therefore a linear regression model can be used for prediction.

[0140] Specifically, for any product type, the historical production sequence and historical unit carbon emission sequence corresponding to that product type can be time-aligned and numerically normalized respectively, and then input into the regression prediction model to construct a carbon emission prediction model.

[0141] Regression prediction models can be linear regression models, support vector regression models, or neural network models. The selected model can learn the emission evolution patterns of product types based on historical changes in output and historical changes in emission intensity.

[0142] Understandably, after constructing a carbon emission prediction model based on the historical production sequence and historical unit carbon emission sequence corresponding to a product type, the planned production corresponding to that product type can be input into the carbon emission prediction model so that the carbon emission prediction model outputs the unit carbon emission prediction amount for that product type within the prediction period. The unit carbon emission prediction amount can be output at the granularity of monthly, quarterly, or compliance cycle, and should be matched with the planned production at the same time granularity.

[0143] After obtaining the predicted unit carbon emissions, multiply it by the planned output of the corresponding product type to obtain the predicted carbon emissions of that product type during the prediction period.

[0144] When a compliance phase corresponds to multiple product types, the carbon emission forecast for each product type can be calculated separately, and the forecast results for each product type can be summarized or corrected with historical carbon emission amounts to form the carbon emission amount corresponding to that compliance phase.

[0145] This step links historical production volume and historical carbon emissions per unit for different product types with planned production volume, generating emission forecasts by product and by compliance phase, and further aggregating them to obtain the carbon emissions for each compliance phase. This approach ensures that carbon emission calculations at the compliance phase are consistent with the company's planned production arrangements, providing corresponding emission baseline data for subsequent carbon quota and voluntary emission reduction procurement decisions, and making the phased compliance calculation results closer to actual production changes.

[0146] In one possible implementation, an electricity consumption prediction model can be constructed based on historical output and historical unit electricity consumption. Then, based on this electricity consumption prediction model, the predicted electricity consumption corresponding to each performance stage can be predicted. The specific process is similar to the above description and will not be repeated here.

[0147] In one possible implementation, in scenarios where the compliance phase is either an unverified and unimplemented phase (such as the current year) or an initiation phase (such as the following year), when determining carbon emissions, it is also possible to first determine whether there is a green electricity purchase cycle, and then adjust the carbon emissions based on the green electricity purchase cycle.

[0148] Understandably, if the forecast period is monthly, and emission-controlled enterprises pay their electricity bills monthly, they can purchase green electricity in advance when prices are low to reduce total purchase costs. Therefore, the decision on whether to purchase green electricity within each forecast period can be based on the forecast period itself, with the criterion being whether purchasing green electricity can reduce total costs.

[0149] For example, the predicted electricity consumption and green electricity price series for each performance stage in the corresponding forecast period can be determined first.

[0150] For any one of the multiple forecast periods, based on the first green electricity price in the green electricity price series and the corresponding forecasted electricity consumption, the green electricity cost difference is determined. Then, if the green electricity cost difference is greater than the preset difference, the forecast period is determined to be the green electricity purchase period.

[0151] The determination of predicted electricity consumption and green electricity price series can be found in the description of the steps above, and will not be repeated here.

[0152] The first green electricity price can be, for example, the lowest green electricity price in the green electricity price series, which is lower than the other green electricity prices in the green electricity price series.

[0153] After obtaining the predicted electricity consumption and green electricity price for each prediction period within the prediction time period, the lowest green electricity price in the sequence can be selected as the green electricity price for the first prediction period for any prediction period. Then, the green electricity cost difference for the prediction period can be calculated in combination with the corresponding predicted electricity consumption. The difference can be represented by, for example, the difference between the green electricity procurement cost and the grid electricity substitution cost.

[0154] When the difference exceeds the preset difference threshold, it indicates that purchasing green electricity is cheaper than purchasing grid electricity within the prediction period. Therefore, the prediction period can be determined as the green electricity purchase period.

[0155] Understandably, after the current forecast period is completed, the first green electricity price (the lowest green electricity price in the current forecast period) can be compared with the green electricity price corresponding to the next forecast period, and the minimum of the two can be used as the first green electricity price for the next forecast period. Then, the above steps are repeated until all forecast periods are completed, and the judgment result for each forecast period is obtained.

[0156] In one possible implementation, when determining the green electricity cost difference, the grid predicted cost can be determined first based on the grid emission factor, the green electricity emission factor, and the carbon quota predicted price for the forecast period; the green electricity predicted cost can be determined based on the first green electricity price, the historical grid purchase price, and the predicted electricity consumption for the forecast period; and the difference between the grid predicted cost and the green electricity predicted cost can be used as the green electricity cost difference.

[0157] In this step, the predicted price of carbon allowances within the forecast period, along with the grid power emission factor and the green power emission factor, can be input into the cost calculation model to obtain the grid power forecast cost based on the corresponding emission intensity.

[0158] Subsequently, the difference between the first green electricity price and the historical grid electricity price is determined, and the predicted cost of green electricity is calculated based on this difference and the predicted electricity consumption.

[0159] Finally, the difference between the grid forecast cost and the green electricity forecast price is calculated to obtain the green electricity cost difference.

[0160] This cost difference reflects the difference between using green electricity and grid power under the same predicted electricity consumption conditions. It also incorporates emission factors, historical electricity purchase prices, and predicted cycle price parameters to ensure consistency between the cost difference calculation and corporate compliance data. Therefore, in subsequent green electricity purchase cycle determinations, the economic viability of green electricity substitution can be directly quantified and compared based on the green electricity cost difference, providing input for electricity purchase decisions during the compliance phase.

[0161] After obtaining the judgment results of all forecast cycles (whether it is a green electricity purchase cycle), the carbon emission forecast can be calculated by combining the corresponding electricity volume and emission factor of the green electricity purchase cycle. This forecast is then summarized and corrected with the carbon emission forecasts of multiple product types and historical carbon emissions to output the carbon emission corresponding to each compliance stage.

[0162] For example, in a scenario where the compliance phase is an unverified and unimplemented phase (such as the current year), the carbon emissions are the sum of the carbon emissions already generated in that compliance phase and the predicted carbon emissions for the remaining compliance period, minus the sum of the carbon emissions reduced by the period determined to be the period of purchasing green electricity.

[0163] In scenarios where the compliance phase is in the inactive phase (e.g., the following year), the carbon emissions are the predicted carbon emissions for all compliance cycles in that compliance phase, minus the sum of carbon emissions reduced during the green electricity purchase cycle.

[0164] This step links changes in green electricity prices, predicted electricity consumption, and predicted carbon emissions, allowing the identification results of the green electricity purchase cycle to directly contribute to the determination of emissions during the compliance phase. As a result, carbon emissions during the compliance phase are aligned with green electricity procurement decisions, and the timing of green electricity procurement can be screened based on cost difference thresholds. This improves the alignment between emissions calculations and procurement decisions and enhances the feasibility of the compliance plan.

[0165] In one possible implementation, during the unverified and unimplemented phase (such as the current year) and the unstarted phase (such as the following year), emission-controlled enterprises can also adopt at least one carbon reduction plan for energy-saving retrofitting to reduce carbon emissions during the compliance phase.

[0166] Carbon reduction plans can be various energy-saving retrofit schemes that enterprises plan to adopt to reduce carbon emissions during the compliance phase of emission control. Examples include: using clean energy to replace fossil fuels, upgrading equipment, adjusting equipment operation strategies, constructing distributed photovoltaic power plants and energy storage facilities, and utilizing waste energy.

[0167] Carbon reduction schemes may involve reducing or increasing the consumption of one or more types of energy, and the cost of such schemes can be represented, for example, as the average annual cost of construction and operation of the corresponding carbon reduction scheme.

[0168] Understandably, in scenarios where the compliance phase is in the unverified and unimplemented stage (such as the current year) or the initiation stage (such as the following year), when determining carbon emissions, it is also possible to first determine whether carbon reduction measures need to be adopted in the corresponding compliance phase to reduce carbon emissions.

[0169] The following explanation uses any one of the at least one carbon reduction schemes as an example:

[0170] In practical implementation, the cost of the carbon reduction scheme, the energy price corresponding to at least one energy source, and the amount of energy reduction can be determined. Then, based on the cost of the scheme, the energy price corresponding to at least one energy source, the amount of energy reduction, and the carbon quota forecast price for the forecast period, the carbon reduction cost difference of the carbon reduction scheme can be determined.

[0171] If the cost difference of green electricity exceeds the preset difference, the carbon reduction plan will be implemented within the forecast period.

[0172] If the prediction period is monthly, for each carbon reduction scheme, the corresponding carbon reduction cost difference can be calculated, which is the difference between the cost of not using the carbon reduction scheme and the cost of using the carbon reduction scheme.

[0173] For example, the process category, applicable energy type, unit retrofit input, and expected emission reduction boundary corresponding to the carbon reduction plan can be determined first, and then mapped to the plan cost, energy price, and energy reduction amount.

[0174] For energy prices, the price can be obtained from the unit price of fuel, electricity, or steam recorded in the enterprise's energy management system, and combined with market quotations within the forecast period to form the price input; for energy reduction, it can be estimated based on equipment energy-saving parameters, process substitution ratios, or the energy consumption difference of similar historical schemes.

[0175] Subsequently, the scheme cost, energy reduction, energy price and carbon quota forecast price within the forecast period are linked together to obtain the carbon reduction cost difference. This cost difference is then compared with a preset difference. When the green electricity cost difference is greater than the preset difference, it is determined that implementing the carbon reduction scheme within the forecast period can reduce the amount of carbon reduction.

[0176] Once the carbon reduction plan is determined and implemented, the predicted carbon reduction amount can be calculated by combining the production plan, process cycle time and emission reduction coefficient corresponding to the plan within the prediction period. This predicted carbon reduction amount is then added to the original predicted carbon emissions for the product type. At the same time, the baseline for each stage is corrected by referring to historical carbon emissions, thereby determining the carbon emissions corresponding to each compliance stage.

[0177] For scenarios with multiple execution cycles, the system aggregates the predicted carbon reduction for each cycle and then correlates it with the predicted carbon emissions for at least one cycle to obtain the net emissions output for the compliance phase. This approach integrates the timing of carbon reduction implementation, cost, and changes in carbon allowance prices into a single calculation chain, ensuring that the phased carbon emissions reflect the actual emission reduction effect.

[0178] This step can select the execution cycle of the carbon reduction plan based on the comparison between the carbon reduction cost difference and the preset difference, and incorporate the predicted carbon reduction amount formed within the execution cycle into the emission accounting of the compliance phase, so that the carbon reduction measures and the phase emission calculation are updated synchronously, and the output carbon emissions are consistent with the compliance decision.

[0179] Since the cost of the program, energy prices, and predicted carbon allowance prices are all used to determine whether to implement a carbon reduction program, the economics of the compliance program and the phased emission results can be more accurately matched.

[0180] S104. Based on carbon emissions, carbon quota estimates, carbon quota price series, voluntary emission reduction price series, historical carbon quota data, and historical voluntary emission reduction data, determine the carbon compliance plan corresponding to each compliance stage.

[0181] The carbon compliance scheme is a decision output obtained by jointly calculating the aforementioned demand information, resource information and price information. It can indicate the amount of carbon allowances to be purchased and the corresponding first purchase time, the amount of voluntary emission reductions to be purchased and the corresponding second purchase time.

[0182] In this step, the performance gap can be calculated separately for each performance stage.

[0183] For example, the basic compliance gap is obtained by subtracting the carbon allowance estimate from the carbon emissions of this compliance phase, then subtracting the unused allowance stock from historical carbon allowance data that can continue to be included in compliance in this phase, and then subtracting the unused voluntary emission reduction stock from historical voluntary emission reduction data that meets the deduction rules.

[0184] If the basic fulfillment gap is less than or equal to zero, no new procurement is required in this fulfillment phase, and the system can still output zero purchase quantity and empty time or observation time.

[0185] If the basic compliance gap is greater than zero, then the joint allocation calculation begins. During the joint allocation calculation, the maximum amount of voluntary emission reductions that can be purchased can be determined first based on the upper limit of the proportion of voluntary emission reductions that can be deducted in the compliance rules, and then the amount of carbon quotas to be purchased can be determined based on the remaining gap.

[0186] If the deduction rule is limited by a percentage, it can be constrained by the relationship "Voluntary emission reduction purchase cap = Carbon emissions during the compliance phase × Deduction ratio cap - Available voluntary emission reduction stock during the compliance phase", with a value of zero when it is below zero. Subsequently, without exceeding this cap, the cost of carbon quota purchases and voluntary emission reduction purchases is compared and allocated.

[0187] In one possible embodiment, a phase compliance cost function can be constructed with the objective function of "total compliance cost = carbon allowance purchase quantity × corresponding carbon allowance price at the time of purchase + voluntary emission reduction purchase quantity × corresponding voluntary emission reduction price at the time of purchase". Under the constraint that "carbon allowance purchase quantity + historical available allowance + carbon allowance estimate + voluntary emission reduction purchase quantity + historical available voluntary emission reduction is not less than the phase carbon emission quantity", the purchase combination with the lower total cost can be searched.

[0188] The first purchase time is selected from the carbon quota price series, and the second purchase time is selected from the voluntary emission reduction price series. The selection method can be to select the lowest price point in the corresponding series, or to select a local low value period under the condition of meeting the company's funding arrangements and trading window.

[0189] If there are multiple candidate time periods with close low values ​​within a stage, the purchase volume can be split into multiple executions, and the earliest execution time period can be defined as the first or second purchase time of the stage's plan output. At the same time, the batch information can be retained in the plan details.

[0190] In another possible implementation, the purchase amount can be adjusted based on historical carbon quota data and historical voluntary emission reduction data.

[0191] For example, when historical transaction records indicate that market trading volume is limited in a certain period or that a corporate account has a trading limit within a specific time period, the system sets a phased trading capacity constraint on the quantity to be purchased at one time, and the portion exceeding the phased capacity will be postponed to the next candidate time period for execution.

[0192] For example, when historical voluntary emission reduction data indicates that certain voluntary emission reduction resources have restrictions on registration periods, project types, or certification years, the system only includes the quantity of resources that meet the compliance criteria when determining the amount of voluntary emission reductions to purchase. The carbon compliance plan thus formed not only includes quantity and timing but also remains consistent with the market capacity and resource availability at the current compliance stage.

[0193] Furthermore, the system can output phased carbon compliance plans according to each compliance stage. Through this phased output method, emission-controlled enterprises can obtain the corresponding carbon allowance purchase volume, voluntary emission reduction purchase volume, and their respective purchase time at different compliance statuses.

[0194] This step integrates carbon emissions, carbon allowance estimates, price series, and historical holding data into a single decision-making model, simultaneously determining the purchase quantity and timing, rather than statically calculating the gap first and then relying on experience to choose the right time to purchase. The carbon compliance plan generated by this step can directly output the carbon allowance purchase quantity and corresponding first purchase time, and the voluntary emission reduction purchase quantity and corresponding second purchase time at each compliance stage, enabling emission-controlled enterprises to execute compliance resource procurement based on the stage status, future emission changes, and market price changes.

[0195] In one possible implementation, if the compliance phase is the verified but not implemented phase, the carbon compliance scheme can be used to indicate the amount of carbon allowances purchased and the corresponding first purchase time, the amount of voluntary emission reductions purchased and the corresponding second purchase time.

[0196] If the compliance phase is the unverified and unimplemented phase, the carbon compliance scheme can be used to indicate the amount of carbon allowances purchased and the corresponding first purchase time, the amount of voluntary emission reductions purchased and the corresponding second purchase time, and the amount of green electricity purchased for at least one green electricity purchase cycle.

[0197] If the compliance phase has not yet commenced, the carbon compliance scheme can be used to indicate the amount of carbon allowances purchased and the corresponding first purchase time, the amount of voluntary emission reductions purchased and the corresponding second purchase time, the amount of green electricity purchased for at least one green electricity purchase cycle, and the carbon reduction scheme for at least one forecast cycle.

[0198] In practice, the carbon compliance scheme is generated based on the results of the compliance phase identification. After obtaining the enterprise's corresponding carbon emission verification status, quota holdings, voluntary emission reduction holdings, and electricity consumption plan, the system first determines the compliance phase type and then maps the phase type to the corresponding scheme template.

[0199] For the phase that has been verified but not yet implemented, the plan template only retains the carbon quota purchase amount, the first purchase time, the voluntary emission reduction purchase amount, and the second purchase time.

[0200] For the unverified and unimplemented phases, the plan template should be supplemented with at least one additional green electricity purchase volume corresponding to the green electricity purchase cycle, based on the above content.

[0201] For the unstarted phase, the scheme template is further superimposed with at least one carbon reduction scheme corresponding to the prediction cycle. The carbon reduction scheme can consist of a periodic implementation arrangement of energy-saving renovation, energy substitution or process optimization.

[0202] In one implementation process, the system can unify the compliance phase, historical emission data, predicted emission data, green electricity procurement decisions, and carbon reduction decisions onto the same compliance cycle index, thereby outputting compliance content of different granularities at different stages.

[0203] The verified but not yet implemented phase focuses on determining the supplementary arrangements for quotas and voluntary emission reductions. The unverified and unimplemented phase adds green electricity procurement on this basis. The uninitiated phase further incorporates carbon reduction plans to create a linkage between subsequent emission reductions, green electricity substitution, and compliance procurement.

[0204] In this step, the carbon compliance plan can adjust its output content as the compliance stage changes. The verified but not implemented stage, the unverified and unimplemented stage, and the initiation stage correspond to different compliance decision information, thus enabling the procurement arrangements to be consistent with the actual compliance timeline of the enterprise, and allowing green electricity purchases and carbon reduction plans to be included in the unified output at the appropriate stage, thereby improving the completeness and stage adaptability of the compliance plan.

[0205] This application provides a method for determining carbon compliance schemes. By acquiring historical carbon emissions, historical carbon quota data, historical voluntary emission reduction data, historical energy consumption data, planned production data, and carbon quota estimates for controlled emission enterprises, and further determining the carbon quota price series, voluntary emission reduction price series, and carbon emissions corresponding to each compliance stage, this method can combine carbon emissions, carbon quota estimates, price changes, and historical compliance resource conditions to specifically determine the carbon quota purchase amount, first purchase time, voluntary emission reduction purchase amount, and second purchase time for each compliance stage. This method reduces the deviation between static calculations and actual compliance execution, and improves the dynamic adaptability of carbon compliance schemes and the accuracy of compliance cost control at different compliance stages.

[0206] Figure 2 This is a schematic diagram of a device for determining a carbon compliance scheme, provided as an embodiment of this application. Figure 2 As shown, the carbon compliance scheme determination device 200 includes:

[0207] The acquisition module 201 is used to acquire carbon compliance data corresponding to the emission-controlled enterprises. The carbon compliance data includes: historical carbon emissions, historical carbon quota data, historical voluntary emission reduction data, historical energy consumption data, planned production data, and carbon quota estimates corresponding to at least one compliance stage.

[0208] The determination module 202 is used to determine the carbon allowance price series and voluntary emission reduction price series corresponding to each compliance stage based on historical carbon allowance data and historical voluntary emission reduction data for at least one compliance stage; to determine the carbon emissions corresponding to each compliance stage based on historical carbon emissions, historical energy consumption data, and planned production data; and to determine the carbon compliance scheme corresponding to each compliance stage based on carbon emissions, carbon allowance estimates, carbon allowance price series, voluntary emission reduction price series, historical carbon allowance data, and historical voluntary emission reduction data. The carbon compliance scheme is used to indicate the amount of carbon allowance purchased and the corresponding first purchase time, the amount of voluntary emission reduction purchased and the corresponding second purchase time.

[0209] In one possible implementation, the historical carbon allowance data includes: historical carbon allowance prices and corresponding first trading volumes, and the historical voluntary emission reduction data includes: historical voluntary emission reduction prices and corresponding second trading volumes. The device also includes: a processing module 203.

[0210] The determination module 202 is used to determine the predicted period of the performance stage for any one of the at least one performance stage.

[0211] The processing module 203 is used to predict the carbon allowance price sequence during the forecast period in the compliance phase based on historical carbon allowance prices, first trading volume, historical voluntary emission reduction prices, and second trading volume. The carbon allowance price sequence is used to indicate the predicted carbon allowance price and the predicted voluntary emission reduction price for each forecast period within the forecast period.

[0212] In one possible implementation, historical energy consumption data includes: historical output and historical carbon emissions per unit for multiple product types; planned output data includes: planned output for multiple product types; and processing module 203 is further used to construct a carbon emission prediction model for any one of the multiple product types based on the historical output and historical carbon emissions per unit for that product type; and to input the planned output corresponding to the product type into the carbon emission prediction model to obtain the predicted carbon emissions per unit for that product type during the prediction period.

[0213] The determination module 202 is used to determine the carbon emission forecast of a product type based on the unit carbon emission forecast and the planned output corresponding to the product type; and to determine the carbon emission corresponding to each compliance stage based on the carbon emission forecast of multiple product types corresponding to multiple compliance stages and historical carbon emission.

[0214] In one possible implementation, the determining module 202 is further configured to determine the predicted electricity consumption and green electricity price sequence for each performance stage within the corresponding prediction period; for any prediction period among multiple prediction periods, based on the first green electricity price in the green electricity price sequence and the corresponding predicted electricity consumption, determine the green electricity cost difference, wherein the first green electricity price is less than other green electricity prices in the green electricity price sequence; and if the green electricity cost difference is greater than a preset difference, determine the prediction period as a green electricity purchase period;

[0215] Processing module 203 is used to determine the carbon emission forecast corresponding to at least one green electricity purchase cycle; and to determine the carbon emission corresponding to each compliance stage based on the carbon emission forecasts of multiple product types, historical carbon emissions, and the carbon emission forecasts corresponding to at least one forecast cycle.

[0216] In one possible implementation, the carbon compliance data also includes: grid power emission factor, green electricity emission factor, and historical grid electricity purchase price. Processing module 203 is used to determine the grid forecast cost based on the grid power emission factor, green electricity emission factor, and carbon quota forecast price for the forecast period; determine the green electricity forecast cost based on the first green electricity price, historical grid electricity purchase price, and forecasted electricity consumption for the forecast period; and use the difference between the grid forecast cost and the green electricity forecast cost as the green electricity cost difference.

[0217] In one possible implementation, the carbon compliance data further includes: at least one carbon reduction scheme data; the determination module 202 is further configured to, for any one of the at least one carbon reduction schemes, determine the scheme cost, the energy price corresponding to at least one energy source, and the energy reduction amount; based on the scheme cost, the energy price corresponding to at least one energy source, the energy reduction amount, and the carbon quota forecast price for the forecast period, determine the carbon reduction cost difference of the carbon reduction scheme; and if the green electricity cost difference is greater than a preset difference, determine to execute the carbon reduction scheme within the forecast period.

[0218] The processing module 203 is used to determine the predicted carbon reduction amount corresponding to at least one prediction period for implementing the carbon reduction plan; and to determine the carbon emission amount corresponding to each compliance stage based on the predicted carbon emission amounts of multiple product types, historical carbon emission amounts, predicted carbon emission amounts corresponding to at least one prediction period, and predicted carbon reduction amounts.

[0219] One possible implementation approach includes:

[0220] If the compliance phase is the verified but not yet implemented phase, the carbon compliance plan is used to indicate the carbon allowance purchase volume and the corresponding first purchase time, the voluntary emission reduction purchase volume and the corresponding second purchase time;

[0221] If the compliance phase is the unverified and unimplemented phase, the carbon compliance plan is used to indicate the carbon allowance purchase volume and the corresponding first purchase time, the voluntary emission reduction purchase volume and the corresponding second purchase time, and the green electricity purchase volume corresponding to at least one green electricity purchase cycle.

[0222] If the compliance phase has not yet commenced, the carbon compliance scheme is used to indicate the amount of carbon allowances purchased and the corresponding first purchase time, the amount of voluntary emission reductions purchased and the corresponding second purchase time, the amount of green electricity purchased for at least one green electricity purchase cycle, and the carbon reduction scheme for at least one forecast cycle.

[0223] The carbon compliance scheme determination device provided in this embodiment can execute the carbon compliance scheme determination method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0224] Figure 3This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 3 As shown, the electronic device 300 provided in this embodiment includes at least one processor 301 and a memory 302. Optionally, the electronic device 300 further includes a communication interface 303. The processor 301, memory 302, and communication interface 303 are connected via a bus 304.

[0225] In a specific implementation, at least one processor 301 executes computer execution instructions stored in memory 302, causing at least one processor 301 to perform the above-described method.

[0226] The specific implementation process of processor 301 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0227] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0228] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0229] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0230] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0231] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0232] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0233] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0234] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0235] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0236] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0237] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0238] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0239] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0240] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0241] It should be understood that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, or integrated into another system, or some features may be ignored or not executed.

[0242] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this application can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or in the form of software program modules.

[0243] When integrated units / modules are implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor can be any suitable hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the storage unit can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0244] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0245] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0246] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0247] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for determining a carbon compliance scheme, characterized in that, The method includes: Obtain carbon compliance data for enterprises subject to emission control, including: historical carbon emissions, historical carbon quota data, historical voluntary emission reduction data, historical energy consumption data, planned production data, and carbon quota estimates for at least one compliance phase. Based on historical carbon allowance data and historical voluntary emission reduction data for at least one of the aforementioned compliance phases, determine the carbon allowance price sequence and the voluntary emission reduction price sequence corresponding to each compliance phase. Based on the historical carbon emissions, the historical energy consumption data, and the planned production data, determine the carbon emissions corresponding to each compliance phase; Based on the carbon emissions, carbon quota estimates, carbon quota price series, voluntary emission reduction price series, historical carbon quota data, and historical voluntary emission reduction data, a carbon compliance plan is determined for each compliance phase. The carbon compliance plan is used to indicate the amount of carbon quota purchased and the corresponding first purchase time, the amount of voluntary emission reduction purchased and the corresponding second purchase time.

2. The method according to claim 1, characterized in that, The historical carbon allowance data includes: historical carbon allowance prices and corresponding first trading volumes; the historical voluntary emission reduction data includes: historical voluntary emission reduction prices and corresponding second trading volumes; the step of determining the carbon allowance price sequence and voluntary emission reduction price sequence corresponding to each compliance stage based on historical carbon allowance data and historical voluntary emission reduction data at least one of the compliance stages includes: For any one of the at least one of the performance phases, determine the predicted time period of the performance phase; Based on the historical carbon allowance price, the first trading volume, the historical voluntary emission reduction price, and the second trading volume, a carbon allowance price sequence is predicted for the forecast period during the compliance phase. The carbon allowance price sequence is used to indicate the predicted carbon allowance price and the predicted voluntary emission reduction price for each forecast period within the forecast period.

3. The method according to claim 2, characterized in that, The historical energy consumption data includes: historical output and historical carbon emissions per unit for multiple product types; the planned output data includes: planned output for multiple product types; and determining the carbon emissions for each compliance phase based on the historical carbon emissions, the historical energy consumption data, and the planned output data includes: For any one of the multiple product types, a carbon emission prediction model is constructed based on the historical output and historical unit carbon emissions of that product type. The planned output corresponding to the product type is input into the carbon emission prediction model to obtain the predicted unit carbon emission of the product type during the prediction period. The carbon emission forecast for the product type is determined based on the predicted unit carbon emission and the planned output corresponding to the product type. The carbon emissions for each compliance stage are determined based on the predicted carbon emissions for multiple product types corresponding to multiple compliance stages and the historical carbon emissions.

4. The method according to claim 3, characterized in that, The method further includes: Determine the predicted electricity consumption and green electricity price series for each stage of compliance within the corresponding forecast period; For any one of the multiple forecast periods, a green electricity cost difference is determined based on the first green electricity price in the green electricity price sequence and the corresponding forecasted electricity consumption, wherein the first green electricity price is less than the other green electricity prices in the green electricity price sequence; If the cost difference of green electricity is greater than a preset difference, the prediction period is determined to be the green electricity purchase period; The step of determining the carbon emissions corresponding to each compliance stage based on the predicted carbon emissions of multiple product types corresponding to multiple compliance stages and the historical carbon emissions includes: Determine the predicted carbon emissions corresponding to at least one green electricity purchase cycle; Based on the carbon emission forecasts for the multiple product types, the historical carbon emission amounts, and the carbon emission forecasts for at least one forecast period, the carbon emission amount corresponding to each compliance phase is determined.

5. The method according to claim 4, characterized in that, The carbon compliance data also includes: grid electricity emission factors, green electricity emission factors, and historical grid electricity prices. The determination of the green electricity cost difference based on the first green electricity price in the green electricity price series and the corresponding predicted electricity consumption includes: Based on the grid emission factor, the green electricity emission factor, and the carbon quota forecast price for the forecast period, the grid forecast cost is determined. The green electricity forecast cost is determined based on the first green electricity price, the historical grid electricity price, and the forecasted electricity consumption for the forecast period. The difference between the predicted grid cost and the predicted green electricity cost is taken as the green electricity cost difference.

6. The method according to claim 4, characterized in that, The carbon compliance data also includes: data on at least one carbon reduction program, and the method further includes: For any one of the at least one carbon reduction schemes, determine the scheme cost, the energy price corresponding to at least one energy source, and the energy reduction amount of the carbon reduction scheme; Based on the cost of the proposed scheme, the energy price corresponding to at least one energy source, the amount of energy reduction, and the predicted price of carbon allowances for the forecast period, the carbon reduction cost difference of the proposed carbon reduction scheme is determined. If the difference in green electricity costs is greater than a preset difference, the carbon reduction plan will be implemented within the forecast period. The determination of carbon emissions for each compliance phase based on the carbon emission forecasts for the multiple product types, the historical carbon emissions, and the carbon emission forecasts for at least one forecast period includes: Determine the predicted carbon reduction amount corresponding to at least one prediction cycle for implementing the carbon reduction scheme; Based on the carbon emission forecasts for the multiple product types, the historical carbon emission amounts, the carbon emission forecasts for at least one forecast period, and the predicted carbon reduction, the carbon emission amount corresponding to each compliance stage is determined.

7. The method according to claim 6, characterized in that, The carbon compliance scheme includes: If the compliance phase is a verified but not yet implemented phase, the carbon compliance scheme is used to indicate the carbon quota purchase amount and the corresponding first purchase time, the voluntary emission reduction purchase amount and the corresponding second purchase time; If the compliance phase is an unverified and unexecuted phase, the carbon compliance scheme is used to indicate the carbon quota purchase amount and the corresponding first purchase time, the voluntary emission reduction purchase amount and the corresponding second purchase time, and the green electricity purchase amount corresponding to at least one green electricity purchase cycle. If the compliance phase has not been initiated, the carbon compliance scheme is used to indicate the amount of carbon allowances purchased and the corresponding first purchase time, the amount of voluntary emission reductions purchased and the corresponding second purchase time, the amount of green electricity purchased for at least one green electricity purchase cycle, and the carbon reduction scheme for at least one prediction cycle.

8. A device for determining a carbon compliance scheme, characterized in that, The device includes: The acquisition module is used to acquire carbon compliance data corresponding to the controlled emission enterprises. The carbon compliance data includes: historical carbon emissions, historical carbon quota data, historical voluntary emission reduction data, historical energy consumption data, planned production data, and carbon quota estimates corresponding to at least one compliance stage. The determination module is configured to determine, based on historical carbon allowance data and historical voluntary emission reduction data for at least one of the compliance phases, a carbon allowance price sequence and a voluntary emission reduction price sequence corresponding to each compliance phase; determine the carbon emissions corresponding to each compliance phase based on the historical carbon emissions, the historical energy consumption data, and the planned production data; and determine the carbon compliance scheme corresponding to each compliance phase based on the carbon emissions, carbon allowance estimates, carbon allowance price sequences, voluntary emission reduction price sequences, historical carbon allowance data, and historical voluntary emission reduction data, wherein the carbon compliance scheme indicates the amount of carbon allowances purchased and the corresponding first purchase time, the amount of voluntary emission reductions purchased and the corresponding second purchase time.

9. An electronic device, characterized in that, include: Memory and processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 7.

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