Carbon quota scheduling method, device, equipment, storage medium and program product

Abstract

The present application relates to a carbon quota scheduling method, device, equipment, storage medium and program product. The method includes: obtaining the historical carbon emission data and historical electricity-clearing power data of the target electricity user, and obtaining the historical power generation-clearing power data of the target power generation subject; wherein the target power generation subject includes the renewable energy power generation subject and the non-renewable energy power generation subject; determining the equivalent carbon emissions of the target power user based on the historical power generation-clearing power data and historical electricity-clearing power data of the renewable energy power generation subject, determining the carbon quota transfer data when scheduling the target carbon quota based on the equivalent carbon emissions; scheduling the target carbon quota based on the carbon quota transfer data. The use of this method can improve the reliability of carbon quota scheduling and make energy-saving and emission reduction measures more accurate and effective.

Description

Technical Field

[0001] The present application relates to the technical field of carbon quota scheduling, and in particular to a carbon quota scheduling method, device, equipment, storage medium and program product. Background Art

[0002] With the large-scale grid connection of renewable energy power generation, green electricity (electricity with carbon dioxide emissions approaching zero or zero during the production process) is gradually becoming an important source of electricity supply. Especially for regions with unbalanced distribution of production capacity and energy consumption structure, cross-regional green electricity trading will become an inevitable choice for consuming renewable energy and promoting carbon emission reduction in the future. At present, there is a general consensus on the carbon emission reduction benefits of consuming green electricity, but there is currently no clear accounting and measurement method for how much carbon emissions are equivalent to cross-regional green electricity consumption.

[0003] In the existing technology, it is usually agreed that green electricity does not produce carbon emissions during electricity trading. When calculating electricity carbon emissions, the green electricity consumption is deducted from the total electricity consumption, and then multiplied by the average carbon emission factor of the regional power grid to obtain the electricity carbon emissions. However, the total amount of green electricity in the region has been deducted when calculating the average carbon emission factor of the regional power grid, which will lead to the problem of duplicate calculation. When the carbon emission calculation involves multiple different regions and power generation entities, the calculated carbon emissions are less accurate, which affects the reasonable scheduling of carbon quotas and results in poor energy conservation and emission reduction effects. Summary of the invention

[0004] Based on this, it is necessary to provide a carbon quota scheduling method, device, computer equipment, computer-readable storage medium and computer program product that can improve the accuracy of carbon emission calculation in response to the above technical problems.

[0005] In a first aspect, the present application provides a carbon quota scheduling method, comprising:

[0006] Obtain the historical carbon emission data and historical electricity consumption-clearing data of the target electricity users, and obtain the historical power generation-clearing data of the target power generation entities; the target power generation entities include renewable energy power generation entities and non-renewable energy power generation entities;

[0007] Determine the equivalent carbon emissions of the target electricity user based on the historical power generation-clearing data and historical power consumption-clearing data corresponding to the renewable energy power generation entity, and determine the carbon quota transfer data when scheduling the target carbon quota based on the equivalent carbon emissions;

[0008] The target carbon quota is scheduled according to the carbon quota transfer data.

[0009] In one embodiment, the equivalent carbon emissions of the target electricity user are determined based on the historical power generation-clearing power data and the historical power consumption-clearing power data corresponding to the renewable energy power generation subject, including:

[0010] Determine the total carbon emissions of the target electricity user within a preset historical period;

[0011] The target electricity user's target carbon emissions are determined based on the renewable energy identification information in the historical electricity clearing data. The target carbon emissions of the target electricity user are determined by the difference between the total carbon emissions and the carbon emissions.

[0012] In one embodiment, determining the total carbon emissions of a target electricity user in a preset historical period includes:

[0013] Obtain the total power generation of each non-renewable energy power generation entity in the carbon quota to be dispatched area, and obtain the total carbon emissions in the carbon quota to be dispatched area;

[0014] The average carbon emission factor of the carbon quota area to be scheduled is determined based on the ratio of total carbon emissions to total power generation, and the total carbon emissions of the target electricity user are determined based on the average carbon emission factor and the total electricity consumed by the target electricity user in a preset historical period; among which, the average carbon emission factor is used to characterize the carbon emissions generated when the carbon quota area to be scheduled produces and consumes electricity.

[0015] In one embodiment, the difference in carbon emissions corresponding to the reduction when the target electricity user consumes renewable energy within a preset historical period is determined based on the renewable energy identification information in the historical electricity consumption clearing power data; including:

[0016] The marginal carbon emission factor of the carbon quota to be dispatched area is determined based on the carbon emissions generated by the non-renewable energy power generation entities in the carbon quota to be dispatched area, the total power generation of non-renewable energy power and the total power generation of renewable energy power. The marginal carbon emission factor is used to characterize the corresponding carbon emissions generated by the target electricity users in the carbon quota to be dispatched area when the power resources increase;

[0017] Obtain the renewable energy power output of the target electricity user within the preset historical period, and determine the corresponding carbon emission reduction difference when consuming renewable energy based on the marginal carbon emission factor and renewable energy power output.

[0018] In one embodiment, the marginal carbon emission factor of the carbon quota to be dispatched area is determined according to the carbon emissions generated by the non-renewable energy power generation entities in the carbon quota to be dispatched area, the total power generation of non-renewable energy power and the total power generation of renewable energy power, including:

[0019] Obtain the total power generation of non-renewable energy power generation entities in the carbon quota to be dispatched area within a preset historical period, the total amount of fuel used for power generation, and the carbon emission factors corresponding to each component of the fuel;

[0020] Determine the actual low calorific value of each non-renewable energy power generation entity based on the total power generation, total fuel volume and carbon emission factor. The actual low calorific value is used to characterize the actual available power generated by the fuel;

[0021] Taking the total power generation as the weight, the weighted average of the carbon emission factors of each non-renewable energy power generation entity in the carbon quota to be dispatched area is calculated to obtain the marginal carbon emission factor of the carbon quota to be dispatched area.

[0022] In one embodiment, the actual low heating value of each non-renewable energy power generation entity is determined based on the total power generation, the total amount of fuel, and the carbon emission factor, including:

[0023] Obtain the fuel data consumed by each non-renewable energy power generation entity to generate non-renewable energy electricity; wherein the fuel data includes the fuel components, total mass, mass proportion of each component and calorific value data of each component;

[0024] Determine the theoretical low-level heating amount corresponding to the non-renewable energy electricity generated by each power generation entity in the carbon quota to be dispatched area based on the fuel data;

[0025] The actual low-level heating value of each non-renewable energy power generation entity is determined according to the theoretical total low-level heating value and the heat loss of each non-renewable energy power generation entity during the energy conversion and transmission process.

[0026] In a second aspect, the present application also provides a carbon quota scheduling device, including:

[0027] The power data acquisition module is used to acquire the historical carbon emission data and historical power consumption-clearing power data of the target power users, and acquire the historical power generation-clearing power data of the target power generation entities; wherein the target power generation entities include renewable energy power generation entities and non-renewable energy power generation entities;

[0028] The power data processing module is used to determine the equivalent carbon emissions of the target power user based on the historical power generation-clearing power data and historical power consumption-clearing power data corresponding to the renewable energy power generation subject, and determine the carbon quota transfer data when scheduling the target carbon quota based on the equivalent carbon emissions;

[0029] The scheduling module is used to schedule the target carbon quota according to the carbon quota transfer data.

[0030] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0031] Obtain the historical carbon emission data and historical electricity consumption-clearing data of the target electricity users, and obtain the historical power generation-clearing data of the target power generation entities; the target power generation entities include renewable energy power generation entities and non-renewable energy power generation entities;

[0032] Determine the equivalent carbon emissions of the target electricity user based on the historical power generation-clearing data and historical power consumption-clearing data corresponding to the renewable energy power generation entity, and determine the carbon quota transfer data when scheduling the target carbon quota based on the equivalent carbon emissions;

[0033] The target carbon quota is scheduled according to the carbon quota transfer data.

[0034] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0035] Obtain the historical carbon emission data and historical electricity consumption-clearing data of the target electricity users, and obtain the historical power generation-clearing data of the target power generation entities; the target power generation entities include renewable energy power generation entities and non-renewable energy power generation entities;

[0036] Determine the equivalent carbon emissions of the target electricity user based on the historical power generation-clearing data and historical power consumption-clearing data corresponding to the renewable energy power generation entity, and determine the carbon quota transfer data when scheduling the target carbon quota based on the equivalent carbon emissions;

[0037] The target carbon quota is scheduled according to the carbon quota transfer data.

[0038] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0039] Obtain the historical carbon emission data and historical electricity consumption-clearing data of the target electricity users, and obtain the historical power generation-clearing data of the target power generation entities; the target power generation entities include renewable energy power generation entities and non-renewable energy power generation entities;

[0040] Determine the equivalent carbon emissions of the target electricity user based on the historical power generation-clearing data and historical power consumption-clearing data corresponding to the renewable energy power generation entity, and determine the carbon quota transfer data when scheduling the target carbon quota based on the equivalent carbon emissions;

[0041] The target carbon quota is scheduled according to the carbon quota transfer data.

[0042] The above-mentioned carbon quota scheduling method, device, computer equipment, storage medium and computer program product obtain the historical carbon emission data and historical electricity-clearing power data of the target electricity user, and obtain the historical power generation-clearing power data of the target power generation subject; wherein the target power generation subject includes renewable energy power generation subject and non-renewable energy power generation subject; it is able to understand the carbon emission situation of the target electricity user and the source of the electricity used, and quantify the carbon footprint; determine the equivalent carbon emissions of the target electricity user based on the historical power generation-clearing power data and historical electricity-clearing power data corresponding to the renewable energy power generation subject, and determine the carbon quota transfer data when scheduling the target carbon quota based on the equivalent carbon emissions; it is able to more accurately reflect the actual carbon emissions of the electricity user, quantify the emission reduction benefits brought by the use of renewable energy by the electricity user, promote the efficient use and precise scheduling of sustainable energy, and schedule the target carbon quota based on the carbon quota transfer data, so as to flexibly realize carbon quota scheduling, improve the reliability of carbon quota scheduling, and make energy-saving and emission reduction measures more precise and effective. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 This is an application environment diagram of a carbon quota scheduling method in an embodiment;

[0045] Figure 2 A schematic diagram of a process of a carbon quota scheduling method in one embodiment;

[0046] Figure 3 A schematic diagram of a process of a carbon quota scheduling method in one embodiment;

[0047] Figure 4 is a structural block diagram of a carbon quota scheduling device in one embodiment;

[0048] Figure 5 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0050] The carbon quota scheduling method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. Among them, the terminal 102 can be, but is not limited to, sensors and data acquisition devices in various power systems, such as carbon footprint data acquisition devices for measuring or tracking electricity users, carbon trading data recording platforms, power generation data acquisition devices, power consumption data acquisition devices, various types of electric energy meters and power monitoring systems, etc. The server 104 can be implemented with an independent server or a server cluster consisting of multiple servers.

[0051] In an exemplary embodiment, Figure 2 As shown, a carbon quota scheduling method is provided, which is applied to Figure 1 The application environment in is taken as an example to illustrate, including the following steps 202 to 206.

[0052] in:

[0053] Step 202, obtaining the historical carbon emission data and historical electricity consumption-clearing power data of the target electricity users, and obtaining the historical power generation-clearing power data of the target power generation entities; wherein the target power generation entities include renewable energy power generation entities and non-renewable energy power generation entities.

[0054] Among them, the target electricity user refers to the recipient of electricity resources when transferring electricity resources, which can be a power company or an end user. The target power generation entity refers to the power resource provider when transferring electricity resources, that is, the entity used to produce electric energy, which can be a generator set, such as a thermal power unit, a wind power unit, etc. The problem of difficult storage of electricity resources can be solved by timely transferring the generated electricity resources to the electricity user through the power generation entity, so that the production and use of the power system can be completed at the same time, and the utilization rate of electricity resources can be improved. Historical carbon emission data refers to the electricity data transferred when all the electricity resources generated by the power generation entity are transferred to the power user. Renewable energy power generation entity refers to the power generation entity that uses renewable energy to generate electricity, such as wind, hydropower and solar power generation entities. Non-renewable energy power generation entity refers to the power generation entity that uses non-renewable energy to generate electricity, such as the power generation entity that uses coal, natural gas, oil or nuclear energy to generate electricity.

[0055] Exemplarily, the historical carbon emission data, historical electricity consumption-clearing power data and historical power generation-clearing power data of the target electricity user can be obtained through data exchange with the target electricity user, target power generation or carbon emission data provider through data collection tools or data access protocols. For example, the historical electricity consumption data of the target subject can be obtained through the data of electricity meters, smart meters or power providers, the historical carbon emission data can be obtained from energy suppliers or carbon emission data providers, and the historical power generation-clearing power data can be obtained from electricity market data or directly from the target power generation subject.

[0056] Step 204, determine the equivalent carbon emissions of the target electricity user based on the historical power generation-clearing power data and historical power consumption-clearing power data corresponding to the renewable energy power generation entity, and determine the carbon quota transfer data when scheduling the target carbon quota based on the equivalent carbon emissions.

[0057] Among them, equivalent carbon emissions refer to the standardization of all carbon emissions of the subject that emits carbon, so that it can be better compared with other subjects or measure the overall impact of the subject on the greenhouse effect. It is the net carbon emissions of the target electricity user taking into account the emission reduction benefits after the use of renewable energy. Carbon quota represents the carbon emission quota, that is, the total amount of greenhouse gas emissions allowed. Through the setting of carbon quotas, greenhouse gas emissions can be restricted to achieve environmental protection. Target carbon quota refers to the target carbon quota after carbon quota scheduling determined based on equivalent carbon emissions. Carbon quota transfer data refers to data that records and tracks carbon emission rights transactions and transfers, which may include data such as emission subjects and emission quantities.

[0058] For example, the equivalent carbon emissions of the target electricity user can be determined based on the historical power generation and clearing data of renewable energy power generation entities, and information such as power consumption, power generation, and energy sources can be obtained; for different power sources, the corresponding carbon emission factors can be used to calculate the carbon emissions of electricity use. Fossil fuel power generation usually has higher carbon emissions, while renewable energy power generation has very low or approximately zero carbon emissions. Therefore, fossil fuels and renewable energy have different carbon emission factors. Comparing the carbon emission factors of renewable energy with those of traditional energy can obtain the carbon emission reduction benefits of renewable energy. Combining the carbon emissions corresponding to power consumption and the carbon emission reduction benefits corresponding to renewable energy can obtain the equivalent carbon emissions of the target electricity user.

[0059] Step 206: Schedule the target carbon quota according to the carbon quota transfer data.

[0060] Exemplarily, the carbon quota can be scheduled according to the obtained carbon quota transfer data, so that the carbon quota after scheduling is the target carbon quota. Taking the above example as an example, the carbon quota is scheduled between the carbon quota transfer-out party and the carbon quota transfer-in party according to the carbon quota transfer data, so that the carbon quota of the carbon quota transfer-out party or the carbon quota transfer-in party after scheduling is the target carbon quota.

[0061] In the above-mentioned carbon quota scheduling method, the historical carbon emission data and historical electricity-clearing power data of the target electricity user are obtained, and the historical power generation-clearing power data of the target power generation subject is obtained; wherein, the target power generation subject includes renewable energy power generation subject and non-renewable energy power generation subject; the carbon emission situation of the target electricity user and the source of the electricity used can be understood, and the carbon footprint can be quantified; the equivalent carbon emissions of the target electricity user are determined according to the historical power generation-clearing power data and historical electricity-clearing power data corresponding to the renewable energy power generation subject, and the carbon quota transfer data when scheduling the target carbon quota is determined according to the equivalent carbon emissions; the actual carbon emissions of the electricity user can be more accurately reflected, the emission reduction benefits brought by the use of renewable energy by the electricity user can be quantified, and the efficient use and precise scheduling of sustainable energy can be promoted; the target carbon quota can be scheduled according to the carbon quota transfer data, and the carbon quota scheduling can be flexibly realized, the reliability of the carbon quota scheduling can be improved, and the energy-saving and emission reduction measures can be made more precise and effective.

[0062] In an exemplary embodiment, the equivalent carbon emissions of a target electricity user are determined based on historical power generation-clearing power data and historical power consumption-clearing power data corresponding to the renewable energy power generation subject, including: determining the total carbon emissions of the target electricity user within a preset historical period; determining the corresponding difference in carbon emissions reduction when the target electricity user consumes renewable energy within the preset historical period based on the renewable energy identification information in the historical power consumption-clearing power data; and determining the target carbon emissions of the target electricity user based on the difference between the total carbon emissions and the carbon emissions.

[0063] Among them, total carbon emissions refer to the sum of all greenhouse gas emissions generated by the target electricity user, which can be expressed in parameters such as carbon dioxide equivalent. Renewable energy identification information refers to the identification information of energy, electricity or fuel, which is used to indicate that the energy is generated from a renewable energy source. It is usually contained in carriers such as electricity labels or electricity certificates. It can also include information such as the percentage of renewable energy in energy products and the geographical location of renewable energy resources, such as the location of wind farms or solar panels. The corresponding reduction in carbon emissions when consuming renewable energy refers to the carbon emissions reduced by the electricity user due to the use of renewable energy.

[0064] Exemplarily, the target electricity user's electricity source and electricity consumption can be determined, the corresponding carbon emission coefficient can be determined according to the electricity source, and then the carbon emission coefficient can be multiplied by the electricity consumption to obtain the total carbon emissions of the target electricity user in the preset historical period. The corresponding reduction in carbon emissions when the target electricity user consumes renewable energy in the preset historical period can be determined based on the renewable energy identification information in the historical electricity consumption clearing power data, and the carbon emission factor related to the non-renewable energy in the carbon quota to be scheduled area can be used to calculate the carbon emissions of electricity consumption in the carbon quota to be scheduled area without renewable energy; and based on the renewable energy identification information in the electricity consumption clearing power data, the proportion of renewable energy is determined, and the corresponding carbon emission reduction is calculated, and the carbon emissions of non-renewable energy are added to the carbon emission reduction of renewable energy to obtain the carbon emissions reduced by the target electricity user in the preset historical period by consuming renewable energy.

[0065] In an exemplary embodiment, the total carbon emissions of a target electricity user within a preset historical period are determined, including: obtaining the total power generation of each non-renewable energy power generation entity in the carbon quota to be scheduled area, and obtaining the total carbon emissions of the carbon quota to be scheduled area; determining the average carbon emission factor of the carbon quota to be scheduled area according to the ratio of total carbon emissions to total power generation, and determining the total carbon emissions of the target electricity user according to the average carbon emission factor and the total electricity consumed by the target electricity user within the preset historical period; wherein the average carbon emission factor is used to characterize the carbon emissions generated when the carbon quota to be scheduled area produces and consumes electricity.

[0066] Among them, the average carbon emission factor of the carbon quota to be scheduled area refers to the ratio between the total carbon emissions and the total energy consumption generated in the carbon quota to be scheduled area within a specific time period.

[0067] Exemplarily, the average carbon emission factor of the area to be scheduled for carbon quota is determined based on the ratio of total carbon emissions to total power generation, and the total carbon emissions of the target power user are obtained by multiplying the average carbon emission factor by the total electricity consumed by the target power user in a preset historical period. The total carbon emissions of the target power user obtained by multiplying the average carbon emission factor by the total electricity consumed by the target power user in a preset historical period is an estimated value of the actual total carbon emissions, and this value can reflect the carbon emission contribution of the target power user.

[0068] In an exemplary embodiment, the difference in carbon emissions corresponding to the reduction when a target electricity user consumes renewable energy within a preset historical period is determined based on renewable energy identification information in historical electricity consumption and clearing power data; including: determining the marginal carbon emission factor of the carbon quota to be scheduled area based on the carbon emissions generated by non-renewable energy power generation entities in the carbon quota to be scheduled area, the total power generation of non-renewable energy power and the total power generation of renewable energy power, the marginal carbon emission factor is used to characterize the carbon emissions corresponding to the increase in power resources of the target electricity user in the carbon quota to be scheduled area; obtaining the renewable energy power clearing amount of the target electricity user within the preset historical period, and determining the difference in carbon emissions corresponding to the reduction when consuming renewable energy based on the marginal carbon emission factor and the renewable energy power clearing amount.

[0069] Among them, the marginal carbon emission factor refers to the carbon emissions corresponding to an additional unit of electricity under specific conditions. It can be used to measure the impact of an increase or decrease in electricity in the power system on carbon emissions. The size of the marginal emission factor is related to factors such as the source of electricity and electricity demand. For example, the increase in renewable energy can reduce the marginal emission factor. Renewable energy power clearing refers to the power supply from renewable energy in the power market.

[0070] For example, the marginal carbon emission factor of the carbon quota to be dispatched area can be obtained by simulating the change of carbon emissions under a specific electricity consumption scenario using an energy model or a power system model based on the energy supply structure of the carbon quota to be dispatched area, or by calculation, for example, using the total power generation as the weight, calculating the weighted average of the carbon emission factors of each non-renewable energy power generation entity in the carbon quota to be dispatched area, and using the average as the marginal carbon emission factor. Multiply the marginal carbon emission factor by the amount of renewable energy power cleared to obtain the amount of carbon emissions reduced by the target power user due to the consumption of renewable energy.

[0071] In an exemplary embodiment, in one of the embodiments, the marginal carbon emission factor of the carbon quota to be scheduled area is determined based on the carbon emissions generated by the non-renewable energy power generation entities in the carbon quota to be scheduled area, the total power generation of non-renewable energy electricity and the total power generation of renewable energy electricity, including: obtaining the total power generation of the non-renewable energy power generation entities in the carbon quota to be scheduled area within a preset historical period, the total amount of fuel used for power generation and the carbon emission factors corresponding to each component of the fuel; determining the actual low heating value of each non-renewable energy power generation entity based on the total power generation, the total amount of fuel and the carbon emission factor, and the actual low heating value is used to characterize the actual available electricity generated by the fuel; using the total power generation as the weight, calculating the weighted average of the carbon emission factors of each non-renewable energy power generation entity in the carbon quota to be scheduled area, and obtaining the marginal carbon emission factor of the carbon quota to be scheduled area.

[0072] Among them, the actual low calorific value refers to the heat released by the fuel during the actual combustion process. When calculating the actual low calorific value, it is necessary to consider the water content in the fuel and the generation and condensation of water vapor during the combustion process. For the same fuel with the same composition, the actual low calorific value is usually lower than the theoretical low calorific value. The actual available electricity refers to the amount of electricity generated by the combustion of fuel, which can be finally put into the power system for use by electricity users after all losses and wastes. The weighted average of the carbon emission factors refers to the average value calculated by considering the weights of different carbon emission factors, which can reflect the total carbon emissions of the power generation entity or the area where the carbon quota is to be dispatched.

[0073] For example, the total power generation of non-renewable energy power generation entities in the carbon quota to be dispatched area within the preset historical period, the total amount of fuel used for power generation, and the carbon emission factor of each fuel can be directly obtained from the database of the power generation entity, or calculated from the fuel used for power generation and related parameters of the fuel. The actual low calorific value can be calculated based on the total amount of fuel, the composition of the fuel, and the chemical reaction of each element during complete combustion, or it can be obtained by calculating the quotient of the total power generation and the total amount of fuel.

[0074] In an exemplary embodiment, the actual low heating value of each non-renewable energy power generation entity is determined based on the total power generation, the total fuel amount and the carbon emission factor, including: obtaining the fuel data consumed by each non-renewable energy power generation entity to generate non-renewable energy power; wherein the fuel data includes the components of the fuel, the total mass, the mass proportion of each component and the calorific value data of each component; determining the theoretical total low heating value corresponding to the non-renewable energy power generated by each power generation entity in the carbon quota to be scheduled area based on the fuel data; determining the actual low heating value of each non-renewable energy power generation entity based on the theoretical total low heating value and the heat loss of each non-renewable energy power generation entity during the energy conversion and transmission process.

[0075] Among them, fuel data refers to data such as fuel type, source, consumption and composition. The fuel consumed to generate non-renewable energy electricity can include coal, natural gas, oil, nuclear fuel and biomass fuel, etc. Calorific value data is called calorific value data, which refers to the energy contained in unit mass or unit volume of fuel. Different fuels usually have different calorific values, which are related to factors such as the chemical composition and energy density of the fuel. The theoretical lower calorific value is the heat released by the fuel when it is completely burned. It characterizes the heat generation of the fuel during the combustion process without considering water vapor condensation and heat recovery, and is usually determined based on the chemical composition of the fuel.

[0076] For example, the fuel data consumed by each power generation entity to generate non-renewable energy power can be obtained by monitoring the energy usage of the power generation entity or directly exchanging data with the power generation entity; the sum of the theoretical low calorific value of each power generation entity that generates non-renewable energy power in the carbon quota to be dispatched area can be calculated based on the total mass of the fuel, the mass proportion of each fuel and the calorific value data, and the theoretical low calorific value of each fuel can be obtained by multiplying the total mass of each fuel by the calorific value of the fuel, and then calculating the sum of the theoretical low calorific value of each fuel of each power generation entity to obtain the total theoretical low calorific value of non-renewable energy power generated in the carbon quota to be dispatched area. According to the energy flow path of each power generation entity in the energy conversion and transmission process, and the energy loss points and energy loss types that may exist on the path, such as resistance, heat loss or mechanical loss generated by fuel combustion, generator efficiency, transmission lines, transformers, converters and other links, the energy loss is quantified according to the energy loss point and loss type, and then the theoretical low calorific value is subtracted from the energy loss to obtain the actual low calorific value of each power generation entity.

[0077] In an exemplary embodiment, a carbon quota scheduling method is provided, where the emission reduction contribution of one green certificate (i.e., 1000KW·h green electricity) generated by renewable energy power generation can be equivalent to the carbon emissions generated by renewable energy power generation, such as Figure 3 As shown, the method comprises the following steps:

[0078] Step 302: Obtain the historical carbon emission data and historical electricity consumption-clearing power data of the target electricity user, and obtain the historical power generation-clearing power data of the target power generation entity.

[0079] The historical electricity consumption clearing data may include the number of green certificates purchased by the target electricity user. The green certificates may be purchased by the target from power generation entities within or outside the carbon quota to be dispatched area.

[0080] Step 304: Calculate the marginal carbon emission factor per unit electricity volume in the region based on the carbon emissions generated by power generation entities in the carbon quota to be dispatched region, non-renewable energy electricity, and renewable energy electricity.

[0081] Purchasing one green certificate is equivalent to purchasing 1000kWh of green electricity. Its essence is a kind of electricity substitution. The emission reduction it produces is not a linear emission reduction effect, but a nonlinear emission reduction effect, and there is a marginal decreasing effect. Therefore, it is necessary to determine the actual emission reduction of green electricity in different regions. The specific calculation method is as follows:

[0082] Assume that the carbon emissions generated by the regional power industry are Q CO2 , the regional thermal power supply is E f , the regional green electricity supply is E g, then the emission factor per unit of electricity in the region is:

[0083]

[0084] Let θ represent the proportion of renewable energy generation, then

[0085]

[0086] It can be seen that for every one percentage point increase in the proportion of green electricity, the change in the regional electricity carbon emission factor is the derivative of the above formula with respect to θ:

[0087]

[0088] Solving the above ordinary differential equation, we can get:

[0089]

[0090] When θ = 0, it means that 100% of the electricity supply in the carbon quota dispatch area is thermal power, so the constant e can be determined c for:

[0091]

[0092] This constant can be expressed as the carbon emission per unit of electricity of the most advanced thermal power units, or as the average carbon emission per unit of regional thermal power. In addition, it can be seen that when the proportion of renewable energy increases, the carbon efficiency of thermal power supply will decrease accordingly. Then the carbon emission reduction increased by green electricity should actually be equal to the emission reduction corresponding to green electricity minus the increase caused by the reduction in thermal power efficiency.

[0093] Assume that the original green electricity ratio in region A is Increase the proportion of green electricity to Keeping the thermal power generation unchanged, the change in the unit carbon emission factor of regional thermal power is:

[0094]

[0095] Therefore, the change in carbon emissions from thermal power caused by the change in green electricity is:

[0096]

[0097] The direct carbon emission change caused by the change of green electricity is:

[0098]

[0099] The change in regional carbon emissions caused by changes in green electricity is:

[0100] C=C1+C2

[0101] The carbon emission reduction for every additional 1MWh of green electricity in the region is:

[0102]

[0103] This indicates the carbon emission reduction brought about by each additional green certificate generated in region A.

[0104] From the above calculation process, it can be seen that the main factor affecting the marginal carbon emission factor is the proportion of green electricity. In order to demonstrate the above method more clearly, the marginal carbon emission reduction of two carbon quota dispatching areas with different electricity consumption structures is calculated separately: assuming that the total electricity consumption of regions A and B is 1000MWh, region A has 500MWh of thermal power and 500MWh of green power, then green electricity accounts for 50%; region A has 900MWh of thermal power and 100MWh of green power, then green electricity accounts for 10%. If both regions increase the green electricity by 200MW, it can be seen that the green electricity in region A actually increased by 8.3% percentage points, while that in region B increased by 15%, and the marginal carbon emission reduction brought about is different, and the marginal carbon emission reduction in region B is much greater than that in region A.

[0105] Step 306: Calculate the carbon emissions reduction of electricity users in the carbon quota to be dispatched area due to consumption of renewable energy electricity based on the marginal carbon emission factor, and determine the carbon quota transfer data when dispatching the target carbon quota based on the reduced carbon emissions.

[0106] If the power user j in the power system area i obtains the green certificate quantity G generated by the power system area A through cross-regional green certificate transactions k , then the carbon emissions that can be offset by purchasing this part of the green certificate is:

[0107] GEC j =G k GF(A)

[0108] In the above formula, GEC j represents the carbon offset amount of green certificate transaction of power user j, and GF(A) is the carbon offset factor of green certificate of regional power grid A. The carbon emissions that can be offset by the above green certificate can be used as the carbon quota transfer data of the target power user or the calculation basis of carbon quota transfer data to obtain carbon quota transfer data.

[0109] Step 308: Scheduling the target carbon quota according to the carbon quota transfer data.

[0110] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0111] Based on the same inventive concept, the embodiment of the present application also provides a carbon quota scheduling device for implementing the carbon quota scheduling method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more carbon quota scheduling device embodiments provided below can refer to the limitations of the carbon quota scheduling method above, and will not be repeated here.

[0112] In an exemplary embodiment, Figure 4 As shown, a carbon quota scheduling device 400 is provided, comprising: a power data acquisition module 402, a power data processing module 404 and a scheduling module 406, wherein:

[0113] The power data acquisition module 402 is used to acquire the historical carbon emission data and historical power consumption-clearing power data of the target power user, and acquire the historical power generation-clearing power data of the target power generation entity; wherein the target power generation entity includes the renewable energy power generation entity and the non-renewable energy power generation entity;

[0114] The power data processing module 404 is used to determine the equivalent carbon emissions of the target power user based on the historical power generation-clearing power data and historical power consumption-clearing power data corresponding to the renewable energy power generation subject, and determine the carbon quota transfer data when scheduling the target carbon quota based on the equivalent carbon emissions;

[0115] The scheduling module 406 is used to schedule the target carbon quota according to the carbon quota transfer data.

[0116] In an exemplary embodiment, the power data processing module 404 is used to: determine the total carbon emissions of a target electricity user within a preset historical period; determine the difference in carbon emissions corresponding to the reduction when the target electricity user consumes renewable energy within a preset historical period based on the renewable energy identification information in the historical electricity clearing data; and determine the target carbon emissions of the target electricity user based on the difference between the total carbon emissions and the carbon emissions.

[0117] In an exemplary embodiment, the power data processing module 404 is used to: obtain the total power generation of each non-renewable energy power generation entity in the carbon quota to be scheduled area, and obtain the total carbon emissions of the carbon quota to be scheduled area; determine the average carbon emission factor of the carbon quota to be scheduled area according to the ratio of total carbon emissions to total power generation, and determine the total carbon emissions of the target electricity user according to the average carbon emission factor and the total electricity consumed by the target electricity user in a preset historical period; wherein the average carbon emission factor is used to characterize the carbon emissions generated when the carbon quota to be scheduled area produces and consumes electricity.

[0118] In an exemplary embodiment, the power data processing module 404 is used to: determine the marginal carbon emission factor of the carbon quota to be scheduled area based on the carbon emissions generated by non-renewable energy power generation entities in the carbon quota to be scheduled area, the total power generation of non-renewable energy power and the total power generation of renewable energy power, the marginal carbon emission factor is used to characterize the corresponding carbon emissions generated by the target electricity users in the carbon quota to be scheduled area when the power resources increase; obtain the renewable energy power clearance of the target electricity users within a preset historical period, and determine the corresponding carbon emission reduction difference when consuming renewable energy based on the marginal carbon emission factor and the renewable energy power clearance.

[0119] In an exemplary embodiment, the power data processing module 404 is used to: obtain the total power generation of non-renewable energy power generation entities in the carbon quota to be scheduled area within a preset historical period, the total amount of fuel used for power generation and the carbon emission factors corresponding to each component of the fuel; determine the actual low heating value of each non-renewable energy power generation entity based on the total power generation, the total amount of fuel and the carbon emission factor, and the actual low heating value is used to characterize the actual available electricity generated by the fuel; use the total power generation as the weight to calculate the weighted average of the carbon emission factors of each non-renewable energy power generation entity in the carbon quota to be scheduled area, and obtain the marginal carbon emission factor of the carbon quota to be scheduled area.

[0120] In one of the embodiments, in an exemplary embodiment, the power data processing module 404 is used to: obtain the fuel data consumed by each non-renewable energy power generation entity to generate non-renewable energy power; wherein the fuel data includes the components of the fuel, the total mass, the mass proportion of each component and the calorific value data of each component; determine the theoretical total low-level heating value corresponding to the non-renewable energy power generated by each power generation entity in the carbon quota to be scheduled area according to the fuel data; determine the actual low-level heating value of each non-renewable energy power generation entity according to the theoretical total low-level heating value and the heat loss of each non-renewable energy power generation entity during the energy conversion and transmission process.

[0121] Each module in the above carbon quota scheduling device can be implemented in whole or in part by software, hardware and their combination. Each module can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0122] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 5 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store historical carbon emission data, historical electricity consumption clearing power data, historical power generation clearing power data of the target power generation entity, calculation model data, carbon quota data and other data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a carbon quota scheduling method is implemented.

[0123] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0124] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0125] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0126] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0127] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0128] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0129] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0130] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A carbon quota scheduling method, characterized in that: The method comprises: Obtaining historical carbon emission data and historical electricity consumption-clearing power data of target electricity users, and obtaining historical power generation-clearing power data of target power generation entities; wherein the target power generation entities include renewable energy power generation entities and non-renewable energy power generation entities; Determine the equivalent carbon emissions of the target electricity user based on the historical power generation-clearing power data corresponding to the renewable energy power generation subject and the historical power consumption-clearing power data, and determine the carbon quota transfer data for scheduling the target carbon quota based on the equivalent carbon emissions; and schedule the target carbon quota based on the carbon quota transfer data; The equivalent carbon emissions are the emission reduction contribution of 1000KW·h green electricity generated by the target power generation entity using renewable energy. The equivalent carbon emissions of the target power user are determined based on the historical power generation-clearing power data and the historical power consumption-clearing power data corresponding to the renewable energy power generation entity, including: Assume that the carbon emissions generated by the regional power industry are Q CO2 , the regional thermal power supply is E f , the regional green electricity supply is E g , then the emission factor per unit of electricity in the region is: Let θ represent the proportion of renewable energy generation, It can be seen that for every one percentage point increase in the proportion of green electricity, the change in the regional electricity carbon emission factor is the derivative of the above formula with respect to θ: Solving the above ordinary differential equation, we can get: When θ = 0, the power supply in the carbon quota dispatching area is 100% thermal power, and the constant e is determined c for: The constant e c The carbon emission per unit of electricity of the most advanced thermal power unit or the average carbon emission per unit of regional thermal power; Assume that the original green electricity ratio of the target electricity user is Increase the proportion of green electricity to Keeping the thermal power generation unchanged, the change in the unit carbon emission factor of regional thermal power is: The changes in carbon emissions from thermal power caused by changes in green electricity are as follows: The direct carbon emission change caused by the change of green electricity is: The change in regional carbon emissions caused by changes in green electricity is: C=C1+C2 The carbon emission reduction corresponding to each additional 1MWh of green electricity in the region is: Wherein, A represents the area where the target power generation entity is located.

2. A carbon quota scheduling device, characterized in that: The device comprises: A power data acquisition module is used to acquire the historical carbon emission data and historical power consumption-clearing power data of the target power user, and to acquire the historical power generation-clearing power data of the target power generation entity; wherein the target power generation entity includes a renewable energy power generation entity and a non-renewable energy power generation entity; A power data processing module, used to determine the equivalent carbon emissions of the target power user according to the historical power generation-clearing power data and the historical power consumption-clearing power data corresponding to the renewable energy power generation subject, and determine the carbon quota transfer data when scheduling the target carbon quota according to the equivalent carbon emissions; A scheduling module, used for scheduling the target carbon quota according to the carbon quota transfer data; The equivalent carbon emissions are the emission reduction contribution of 1000KW·h green electricity generated by the target power generation entity using renewable energy. The equivalent carbon emissions of the target power user are determined based on the historical power generation-clearing power data and the historical power consumption-clearing power data corresponding to the renewable energy power generation entity, including: Assume that the carbon emissions generated by the power industry in region A is Q CO2 , the regional thermal power supply is E f , the regional green electricity supply is E g , then the emission factor per unit of electricity in the region is: Let θ represent the proportion of renewable energy generation, It can be seen that for every one percentage point increase in the proportion of green electricity, the change in the regional electricity carbon emission factor is the derivative of the above formula with respect to θ: Solving the above ordinary differential equation, we can get: When θ = 0, the power supply in the carbon quota dispatching area is 100% thermal power, and the constant e is determined c for: The constant e c The carbon emission per unit of electricity of the most advanced thermal power unit or the average carbon emission per unit of regional thermal power; Assume that the original green electricity ratio of the target electricity user is Increase the proportion of green electricity to Keeping the thermal power generation unchanged, the change in the unit carbon emission factor of regional thermal power is: The changes in carbon emissions from thermal power caused by changes in green electricity are as follows: The direct carbon emission change caused by the change of green electricity is: The change in regional carbon emissions caused by changes in green electricity is: C=C1+C2 The carbon emission reduction corresponding to each additional 1MWh of green electricity in the region is: Wherein, A represents the area where the target power generation entity is located.

3. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to claim 1 are implemented.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to claim 1 are implemented.

5. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to claim 1 are implemented.

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