Space-time traceable electric power average emission factor generation and presentation method and system

Abstract

The application discloses a kind of space-time traceable electric power average emission factor generation and presentation method and system.The method comprises: obtaining the power generation data of various types of energy in a given area, obtaining the input power data of external transfer into the given area, and binding space-time label;Obtain the time-space disintegration of time-division and subarea of sending end basic data to the time-division factor of sending end and bind corresponding space-time label;Determine the total power generation carbon emission of given area according to the power generation of various types of energy in given area;According to the space-time label of input power data, accurately match input power with time-division emission factor and subarea emission factor, and calculate the total carbon emission of input power in given area;Calculate the electric power average emission factor of given area and bind the fifth space-time label;The visual form of calculation data, source, space-time label is presented through user interface, and bidirectional tracing is supported.The application realizes the precision, traceability and scenario application of electric power average emission factor.

Description

Technical Field

[0001] This invention relates to the field of carbon emission accounting technology for power systems, specifically to a method and system for generating and presenting a spatiotemporally traceable average emission factor for power systems, which is applicable to the refined measurement and management of carbon emissions in power systems. Background Technology

[0002] The average emission factor for electricity refers to the carbon emissions generated per unit of electricity during the production process; it is also known as the electricity carbon emission factor, carbon emission factor, electricity emission factor, or electricity carbon factor. Current methods for calculating the electricity carbon emission factor primarily rely on static regional average data (such as the annual average factor for provincial or regional power grids), which fails to reflect the real-time operating status and spatial distribution differences of the power system. In terms of time, my country's average electricity emission factor is updated annually; spatially, it is calculated at the provincial level at the lowest possible level. Given the current continuous increase in renewable energy penetration, using annually updated emission factors as a regional or corporate emission benchmark can no longer accurately reflect dynamic energy consumption structures. For example, if an industrial park consumes the same amount of electricity at midday (peak photovoltaic power generation) and in the early morning (dominated by thermal power), its actual carbon emissions can differ by more than 50%. However, the annual average factor will "homogenize" the carbon contributions of the two scenarios, leading to deviations in corporate carbon footprint accounting. From a spatial perspective, the emission factor calculated at the provincial level ignores the differences in the regional power supply structure and transmission and distribution network, failing to accurately depict the matching relationship between user load and regional energy consumption patterns.

[0003] Furthermore, in existing technologies, when calculating cross-regional carbon emissions, the emission factor for the sending region (i.e., the source of external electricity input) is often measured using the provincial average emission factor. Currently, the provincial average emission factor is obtained by dividing the sum of fossil fuel carbon emissions from all power plants in the region by the carbon emissions implied by net cross-regional electricity transfers, using the sum of the region's total power generation and the sum of net cross-regional electricity transfers as the denominator. On the one hand, using net electricity transfers—the difference between transferred-in and transferred-out electricity—calculates carbon emissions from the perspective of final consumption in the region, obscuring the carbon emission responsibility chain in intermediate transit links and even deviating from trading contracts, potentially leading to a severe underestimation of cross-regional carbon emissions. On the other hand, the emission factor obtained by this method cannot distinguish the true emission intensity of a specific region at a particular time period, resulting in the carbon emission calculation of transferred-in electricity remaining at a rough estimation level. For example, if 100 MWh of electricity transferred from province A actually comes from the wind power cluster in province A, but is calculated based on the annual average of province A, the carbon emission results will be seriously overestimated, which violates the principle of the authenticity of carbon accounting.

[0004] Therefore, a time- and zone-based average emission factor system for electricity is needed to adapt to the dynamic changes in the power system and the requirements for refined carbon management. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a spatiotemporally traceable method and system for generating and presenting average electricity emission factors. Through a time-division and zone-division calculation framework for average electricity emission factors, time tags are used to accurately track the sources of electricity carbon emissions.

[0006] To achieve the above-mentioned objectives, the present invention adopts the following technical solution:

[0007] Firstly, a spatiotemporally traceable method for generating and presenting the average emission factor of electricity includes the following steps:

[0008] The system acquires power generation data for various energy sources within a given region. This power generation data is bound to a first spatiotemporal label that includes the time unit corresponding to the power generation and the spatial unit of the power cluster within the region. The system also acquires input power data transferred from other regions into the given region. This input power data includes time-sharing and zone-specific details and is bound to a second spatiotemporal label that includes the time unit corresponding to the input power and the spatial unit of the sending-end region of the transfer channel. Finally, the system acquires basic sending-end data, including the inherent emission factor of each power source type, time-sharing load / output data, and the percentage of installed capacity or external power transmitted by the regional power source.

[0009] Based on time-of-use load / output data and the inherent emission factor of power type, the time-of-use emission factor of each time unit is calculated by weighting and bound to a third spatiotemporal label consistent with the time unit of input power; based on the proportion of installed or transmitted power of regional power and the inherent emission factor of the corresponding regional power type, the regional emission factor of each region is calculated and bound to a fourth spatiotemporal label consistent with the spatial unit of the region where the input power is sent.

[0010] The power generation data of various energy sources in a given area are matched with the inherent emission factors of the corresponding energy types to calculate the carbon emissions of power generation in each spatiotemporal unit, and then superimposed to obtain the total carbon emissions of power generation in the given area. Based on the second spatiotemporal label of the input power data, the input power is accurately matched with the time-of-use emission factor and the zone emission factor to calculate the carbon emissions of the transferred power in each spatiotemporal unit, and then superimposed to obtain the total carbon emissions of the transferred power in the given area.

[0011] The average emission factor of electricity in a given region is calculated by using the sum of the total carbon emissions from electricity generation and the total carbon emissions from electricity transferred into the region as the numerator, and the sum of the total electricity generation from all types of energy sources in the given region and the total electricity input from other regions as the denominator. The factor is then bound to a fifth spatiotemporal tag that includes the time unit and spatial range of the given region.

[0012] The user interface presents the average emission factor of electricity in a given area, the data sources involved in the calculation, and the spatiotemporal labels corresponding to each data and factor in a visual form, supporting bidirectional traceability based on spatiotemporal labels.

[0013] Secondly, a spatiotemporally traceable system for generating and presenting average electricity emission factors includes:

[0014] The data acquisition module is used to acquire power generation data of various energy sources within a given area. The power generation data is bound to a first spatiotemporal tag that includes the time unit corresponding to the power generation and the spatial unit of the power cluster within the area. The module is also used to acquire input power data transferred from other areas into the given area. The input power data includes time-sharing and zone-specific details and is bound to a second spatiotemporal tag that includes the time unit corresponding to the input power and the spatial unit of the sending-end area of ​​the transfer channel. The module is also used to acquire basic sending-end data, including the inherent emission factor of each power type, time-sharing load / output data, and the percentage of installed capacity or external power transmitted by the zoned power sources.

[0015] The sending-end factor spatiotemporal decomposition module is used to calculate the time-sharing emission factor of each time unit based on time-sharing load / output data and the inherent emission factor of the power type, and bind it to the third spatiotemporal label consistent with the input power time unit; and to calculate the partition emission factor of each partition based on the partition power installed capacity or external power transmission ratio data and the inherent emission factor of the corresponding partition power type, and bind it to the fourth spatiotemporal label consistent with the input power sending-end area spatial unit.

[0016] The carbon emission calculation module is used to match the power generation data of various energy sources in a given area with the inherent emission factors of the corresponding energy types, calculate the carbon emissions of power generation in each spatiotemporal unit, and sum them up to obtain the total carbon emissions of power generation in the given area; based on the second spatiotemporal label of the input power data, the input power is accurately matched with the time-of-use emission factor and the zone emission factor to calculate the carbon emissions of the transferred power in each spatiotemporal unit, and sum them up to obtain the total carbon emissions of the transferred power in the given area.

[0017] The electricity average emission factor calculation module is used to calculate the electricity average emission factor of a given region by using the sum of the total carbon emissions from power generation and the total carbon emissions from transferred electricity in the given region as the numerator, and the sum of the total power generation of various energy sources in the given region and the total input electricity transferred from other places as the denominator, and binds a fifth spatiotemporal tag containing the time unit and spatial range of the given region.

[0018] The visualization module is used to present the average power emission factor of a given region, the data sources involved in the calculation, and the spatiotemporal labels corresponding to each data and factor in a visual form through the user interface, and supports bidirectional traceability based on spatiotemporal labels.

[0019] Thirdly, the present invention also provides an electronic device comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, wherein when the programs are executed by the processors, they implement the spatiotemporally traceable method for generating and presenting the average emission factor of electricity as described in the first aspect.

[0020] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the spatiotemporally traceable method for generating and presenting the average emission factor of electricity as described in the first aspect.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] (1) By acquiring the power generation in a given area and the power transferred from other areas and binding them with detailed spatiotemporal tags, and combining the basic data of the sending end to decompose the time-sharing and zone-sharing emission factors, the spatiotemporal mismatch problem caused by the traditional reliance on the overall average factor of the sending end is solved, so that the carbon emission calculation is accurately matched with the spatiotemporal characteristics of actual power production and transmission, which greatly reduces the error of factor calculation and improves the accuracy of emission factor calculation.

[0023] (2) Data and factors at each stage are bound to corresponding spatiotemporal tags, which supports the penetration from the final emission factor to the original data source, and can also trace from the original data to the factor calculation process, clearly locating the time unit and spatial source of each part of carbon contribution, realizing full-link spatiotemporal traceability, and meeting the needs of carbon accounting audit and data verification.

[0024] (3) By using the input electricity data transferred from other regions to the given area for calculation, the carbon emissions corresponding to each electricity inflow from the sending end can be clearly tracked based on time-sharing and zone-based transfer volume, providing a basis for the transfer of responsibility in the subsequent transfer-out process. It can realize the correspondence between the carbon emissions of each transaction and the contract, realize process-oriented accounting, and meet the needs of refined management.

[0025] (4) Visualize the factors, data sources and spatiotemporal labels, and intuitively present the characteristics of factor changes in different spatiotemporal dimensions, which can provide accurate data support for power grid dispatch and user electricity planning. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the carbon emission accounting mechanism for the power system provided in this embodiment of the invention;

[0027] Figure 2 This is a schematic diagram illustrating the derivation of the basic equation for the average emission factor of electricity provided in this embodiment of the invention;

[0028] Figure 3This is a flowchart of the method for generating and presenting the average emission factor of electricity provided in this embodiment of the invention;

[0029] Figure 4 This is a block diagram of the power average emission factor generation and presentation system provided in this embodiment of the invention. Detailed Implementation

[0030] The technical solutions in the embodiments of the present invention will now be clearly and completely described in conjunction with the accompanying drawings.

[0031] This invention proposes a spatiotemporally traceable method for generating and presenting the average power emission factor. Before describing this method, to gain a clearer understanding of the derivation principle of the average power emission factor calculation, the basic equation for the average power emission factor is first derived, enabling flexible spatiotemporal granularity calculation of the average power emission factor, i.e., time-sharing and region-based average power emission factor. Then, based on this basic equation, an example of a method for calculating the hourly average power emission factor at the city level is given. Next, based on the time-sharing and region-based approach, and combined with a method for spatiotemporally decomposing the average power emission factor of the sending-end region, the spatiotemporally traceable method for generating and presenting the average power emission factor of this invention will be explained.

[0032] (I) Derivation of the basic equation for the average emission factor of electricity

[0033] Based on the relevant theories in the 2006 IPCC National Greenhouse Gas Inventory Guidelines, and using the mass-balance approach, the carbon emission balance for any region within the same time frame is derived, i.e.:

[0034] Carbon emissions from load consumption in this area = Carbon emissions from power injection into this area + Carbon emissions from electricity imported from outside the area - Carbon emissions from power transmission to other areas

[0035] Emissions (1)

[0036] Figure 1 The input and output principles of the carbon emission accounting mechanism are shown. The carbon emissions injected by the power source in this region include the carbon emissions from traditional thermal power (fossil energy) power generation and new energy power generation.

[0037] The formula for solving the power average emission factor is derived from Level Assessment, namely:

[0038] Average emission factor for electricity = carbon emissions ÷ electricity consumption (2)

[0039] According to formula (2), the carbon emissions from load consumption in this region can be expressed as:

[0040] Carbon emissions from load consumption in this region = Average emission factor of electricity in this region × Electricity consumption in this region (3)

[0041] To simplify the derivation process, refer to Figure 2 Taking regional power grid X as the research area, we assume that regional power grids A and B are external power-generating terminals that supply electricity to regional power grid X, and that regional power grid X supplies electricity to external regional power grids C and D. The regional power grid is also referred to as a region in this paper. Let CF... x G represents the average emission factor of the regional power grid X. x,th G represents the power generation of thermal power plants in the regional power grid. x,ne E represents the clean energy generation of the regional power grid. in E represents the input power of the regional power grid X. in,a and E in,b E represents the input electricity from regional power grid A and regional power grid B to regional power grid X. out E represents the output power of the regional power grid X. out,c and E out,d These represent the output power from regional power grid X to regional power grid C and regional power grid D, respectively.

[0042] According to formula (3), we have:

[0043] Carbon emissions from load consumption in this region = CF x ×(G x,th +G x,ne +E in,a +E in,b -E out,c -E out,d ) (4)

[0045] Meanwhile, according to formula (1) and assuming that the carbon emission factors of the electricity output from regional power grid X to regional power grid C and regional power grid D are equal, both are values ​​to be determined, CF. x Therefore:

[0046] Carbon emissions from load consumption in this region = CE x,th +CE x,ne +E in,a ×CF a +E in,b ×CF b -E out,c ×CF x -E out,d ×CF x (5)

[0047] Among them, CF a CF represents the carbon emission factor of regional power grid A. b E represents the carbon emission factor of regional power grid B. in,a ×CF a E represents the carbon emissions from the electricity input from regional power grid A to regional power grid X.in,b ×CF b E represents the carbon emissions from the electricity input from regional power grid B to regional power grid X. out,c ×CF x E represents the carbon emissions from the output of electricity from regional grid X to regional grid C. out,d ×CF x This represents the carbon emissions from the electricity output of regional power grid X to regional power grid D.

[0048] Reference Figure 2 Combining formulas (4) and (5), we can obtain

[0049] CF x ×(G x,th +G x,ne +E in,a +E in,b -E out,c -E out,d ) = CE x,th +CE x,ne +E in,a ×CF a +E in,b ×CF b -E out,c ×CF x -E out,d ×CF x (6)

[0050] Simplify formula (6) to get

[0051] CF x ×(G x,th +G x,ne +E in,a +E in,b ) = CE x,th +CE x,ne +E in,a ×CF a +E in,b ×CF b (7)

[0053] Then we have:

[0054]

[0055] From formula (8), the basic equation for the average emission factor of electricity can be derived:

[0056]

[0057] in:

[0058] K represents the total direct carbon emissions of all fossil energy sources in region X, and K is the number of fossil energy types involved in electricity production in region X. For example, k=1 represents coal-fired power generation, k=2 represents gas-fired power generation, k=3 represents oil-fired power generation, etc.

[0059] This represents the total carbon emissions corresponding to the electricity input from outside the region, and J is the number of regions that input electricity into region X.

[0060] N represents the total power generation of region X (including fossil fuels and non-fossil fuels), and N represents the number of energy types involved in power production in region X. For example, n=1 represents coal power, n=2 represents hydropower, n=3 represents wind power, and n=4 represents photovoltaic power, etc.

[0061] This represents the total amount of electricity input from outside the region;

[0062] CF j This represents the average power emission factor corresponding to the sending-end region j.

[0063] According to the formula for calculating the average emission factor of electricity, the average emission factor of electricity in a region during a certain period is calculated by using the sum of the total electricity generation of all energy sources (wind, solar, hydro, thermal, and nuclear) and the electricity input to the region as the denominator, and the sum of the carbon emissions from local fossil fuel power generation and the carbon emissions corresponding to the electricity from the exporting region as the numerator.

[0064] (II) Calculation method of hourly average electricity emission factor at the prefecture-level city level

[0065] Based on the above formula (9), in terms of time-sharing, while the average emission factor of electricity in my country is currently updated annually, this invention further considers different time scales such as month, day, and hour, and fully reflects the corresponding fluctuation characteristics of power source carbon emissions by refining the calculation granularity. In terms of regional dimension, the average emission factor of electricity in my country has been calculated at the national / regional / provincial level, but no calculation has been carried out at the prefecture-level city level. This invention calculates the average emission factor of electricity in each city according to the local power source and the cross-regional transfer of electricity within the administrative region. The core is that the emissions of all power sources in the prefecture-level city are included in the local calculation. This method has a high degree of consistency with international rules, and the factor value is highly correlated with the local power source structure.

[0066] According to the basic equation of the average emission factor of electricity (9), and referring to the calculation methods of the average emission factor of electricity for regions and provinces published by the state, the carbon emissions corresponding to the power supply in the region are calculated according to the administrative division of the prefecture-level city. The carbon emissions corresponding to the cross-regional transfer volume are calculated by multiplying the average emission factor of electricity in the sending region. Based on this, the average emission factor of electricity for each prefecture-level city is calculated. Assuming that city P is the target region and the sending region includes city M in the same province as city P, province K outside the region, and region R outside the region, the average emission factor of electricity for each prefecture-level city is as follows:

[0067]

[0068] In the formula:

[0069] EFp represents the average emission factor of electricity in city P, in kgCO2 / kWh;

[0070] Emp represents the direct carbon dioxide emissions from power generation in City P, expressed in tCO2.

[0071] EFm represents the average emission factor of electricity from city M that supplies electricity to city P, expressed in kgCO2 / kWh.

[0072] Eimp,m,p represents the amount of electricity transmitted from city M to city P, in kWh;

[0073] EFk represents the average emission factor of power generation in Province K that supplies electricity to City P, expressed in kgCO2 / kWh;

[0074] Eimp,k,p represents the amount of electricity transmitted from province K to city P, in kWh;

[0075] EFr represents the regional power grid's average emission factor R, expressed in kgCO2 / kWh;

[0076] Eimp,r,p represents the amount of electricity transmitted from regional power grid R to city P, in kWh;

[0077] Ep represents the total annual power generation of city P, in kWh.

[0078] The average emission factor of electricity at the prefecture-level city level can be used for carbon emission accounting and assessment by governments at all levels, to calculate electricity import (export) emissions when compiling greenhouse gas inventories, and to calculate electricity import (export) emissions in carbon intensity target assessments; it can also be used by enterprises to account for indirect electricity emissions at the compliance boundary.

[0079] Time-of-use and zone-based average emission factors for electricity help achieve precise source tracing of carbon flows in the power system. By dividing the measurement scope into different levels of geographical regions and using finer-grained methods such as daily and hourly time slices, real-time matching of low-carbon power generation and consumption behaviors can be achieved. This refined accounting mechanism can scientifically allocate carbon responsibility in electricity trading flows and avoid the problem of double-counting of environmental rights. This system not only improves the accuracy of emission accounting but also guides social capital to invest in the clean energy sector through market signals, incentivizes green electricity consumption, and thus forms a virtuous cycle of clean energy production and consumption, accelerating the decarbonization process of the power system.

[0080] (III) Spatiotemporally Traceable Methods for Generating and Presenting Average Electricity Emission Factor

[0081] In the derivation of the basic equation for the average electricity emission factor mentioned above, the value of the average electricity emission factor for the sending-end region is based on the annual average electricity emission factor published by the state. Because it is impossible to accurately obtain the specific time-of-use and zone-specific emission factors for other regions within the same region, this can lead to a serious miscalculation of cross-regional carbon emissions. To address this, this invention proposes a spatiotemporally traceable method for generating and presenting the average electricity emission factor. This method decomposes and evaluates the average electricity emission factor for the sending-end region into time-of-use and zone-specific components, and binds spatiotemporal tags to the data and factors during the calculation process. This provides an intuitive, visual, and spatiotemporally traceable access method, promoting refined carbon emission management. (Refer to...) Figure 3 The method includes the following steps:

[0082] S1. Obtain power generation data of various energy sources within a given area and bind it to a first spatiotemporal tag; obtain input power data transferred from other areas to the given area, the input power data including time-sharing and zone-specific details, and bind it to a second spatiotemporal tag; obtain basic data of the sending end, including inherent emission factors of each power source type, time-sharing load / output data, and the proportion of installed capacity or power transmitted from the zoned power source.

[0083] In the context of this invention, a given region refers to a specific geographical or power grid boundary where the average power emission factor needs to be calculated in this scheme. Its scope can be defined according to the application scenario (such as administrative regions, power grid dispatch zones, distribution network areas to which users belong, etc.), and the boundary needs to be clearly defined through the power grid GIS system or regional power planning documents before data collection.

[0084] The term "energy types" encompasses all energy sources used for power generation within a given region, including fossil fuels such as coal-fired power, gas-fired power, and oil-fired power, collectively referred to as thermal power; and non-fossil fuels such as hydropower, wind power, photovoltaic (centralized / distributed), and nuclear power.

[0085] Spatiotemporal tags are structured identifiers that bind power data to “time units + spatial units”. The time units are strongly matched with the granularity of data collection, and the spatial units are strongly associated with the geographical / grid boundaries of power data. The spatial units of local power generation data correspond to power clusters within the region, while the spatial units of power data transferred from other regions correspond to the sending-end region + transmission channel.

[0086] Data on power generation from various energy sources within a given region can be obtained from the online power grid system. Data on incoming power from other regions can be obtained from the synchronous line loss system and / or the power trading platform. Sending-end basic data can be obtained from the power data sharing platform, the online power grid system, and the power trading platform. Specifically, the data platform currently deployed by the power grid company has access to a wealth of data sources through various means. These data sources include: the online power grid, which contains power generation data, equipment ledgers, and topology data for different power source types within the region, from which power generation data for various energy sources within a given region, output data for sending-end power sources, and installed capacity of regional power sources can be obtained; the synchronous line loss system, which enables standardized access and centralized management of metering IoT devices across the entire network, allowing monitoring of power generation and load at key points, and providing data on incoming and outgoing power generation by region, line loss rates by line and distribution area, and load data for sending-end regions; the power trading platform, which provides information on power generation plans, traded power volume, time-of-use pricing, and the flow of power transmission and inter-regional transactions; and the data sharing platform, which provides cross-regional power sharing data, such as the inherent emission factors for each power source type. In this invention, the online power grid and concurrent line losses jointly support the standardization of power generation and loss data for a given region (i.e., the target zone) and the sending end; the trading platform supplements the market-based and external transmission trading structure; and the sharing platform provides authoritative cross-regional data. In the current actual architecture of the power grid data platform, data is usually stored in a table structure and generally supports splitting by time granularity. The tables and system sources corresponding to the data obtained from the data platform are shown in Table 1.

[0087] Table 1. Example of data source for average electricity emission factor in a certain city.

[0088]

[0089]

[0090] In a specific implementation, the data acquisition method for the data platform, which involves creating an API, mainly includes the following steps:

[0091] (1) Application form for data operation platform to post source layer or sharing layer

[0092] Apply for the necessary table query permissions in the source layer, shared layer, and analysis layer on the data operation platform.

[0093] (2) Results of creating a new workspace for the data platform

[0094] Create a new result table in the data platform workspace and analyze and process the requested table data. Then insert the processed data into the newly created result table.

[0095] (3) Create tables and extract data on the DRDS database in the middle platform.

[0096] Use the data integration task (also known as the DI task) to extract data and create tables on the middle platform DRDS. After the tables are created in DRDS, create another DI task to extract the data from the result table into the middle platform DRDS database.

[0097] (4) Creating APIs

[0098] Generate an API in the data service and retrieve table data through the API.

[0099] For the power generation within a region, power generation data is extracted according to a specified time unit (e.g., hourly), and then associated with the corresponding power cluster to complete the corresponding labeling of "specified time unit + power cluster spatial unit," which serves as the first spatiotemporal label. The first spatiotemporal label includes the time unit (hourly / daily / monthly, etc.) corresponding to the power generation and the spatial unit of the power cluster within the given region. Similarly, the second spatiotemporal label includes the time unit corresponding to the input power and the spatial unit of the sending-end region corresponding to the transfer channel.

[0100] S2, based on time-of-use load / output data and the inherent emission factor of power type, calculates the time-of-use emission factor of each time unit and binds it to the third spatiotemporal label; based on the proportion of installed capacity or external power transmission of regional power sources and the inherent emission factor of the corresponding regional power type, calculates the regional emission factor of each region and binds it to the fourth spatiotemporal label.

[0101] In step S2 of this invention, the emission factor at the sending end is decomposed in a time-division and zone-division manner, mainly in two aspects:

[0102] S21, in the time dimension, based on time-of-use load / output data and the inherent emission factor of power source type, the time-of-use emission factor for each time unit is calculated using a weighted average, specifically including:

[0103] Based on the time-of-use load / output data of the sending-end region, the power output proportion of each time unit in the sending-end region is determined. Using the power output proportion of each time unit in the sending-end region as a weight, and combining it with the inherent emission factor of the corresponding power type, the time-of-use emission factor of each time unit is calculated using a weighted summation method. The formula is expressed as follows:

[0104]

[0105] Among them, E t P is the time-division emission factor for time unit t in the sending region. t,iE represents the output percentage of the i-th type of power source within time unit t. i Let be the inherent emission factor of the i-th type of power source, and n be the total number of power source types in the sending-end region.

[0106] Among them, the power output ratio P of each time unit in the sending-end region t,i It is determined in the following ways:

[0107] If historical power output data of various types of power sources recorded in the sending-end region according to a specified time unit is obtained (from the online power grid system), the ratio of the power output of various types of power sources in each time unit to the total power output of the sending end is directly calculated as the power output ratio of that time unit.

[0108] If historical power output data is not available, the power output ratio for each time unit is allocated based on the load curve of the designated time unit in the sending region (sourced from the power trading platform), combined with the typical output patterns of each power type, such as photovoltaic: output from 10:00 to 17:00 and peak from 13:00 to 15:00; coal power: output throughout the day, with an increased proportion during peak load.

[0109] Calculate the time-of-use emission factor E t Then, the time unit on which it was calculated (consistent with the input electricity time unit T) is extracted as the third spatiotemporal tag, and linked with the time-of-use emission factor E. t Binding storage. Optionally, the third spatiotemporal tag may also include the sending region as a spatial unit tag.

[0110] To ensure the accuracy of the assessment, the time-series emission factor E for each time unit was calculated. t Then, the deviation is verified and adjusted. The verification and adjustment of the deviation includes: calculating the deviation between the sum of the products of the time-of-use emission factor and the corresponding power generation of each time unit and the product of the overall average emission factor of the sending-end region and the total power generation of the sending-end region. If the deviation is greater than a preset threshold (e.g., 5%), the power output ratio is adjusted until the deviation is less than or equal to the preset threshold. The overall average emission factor of the sending-end region adopts the annual average factor of the power grid published by the state.

[0111] S22, in the spatial dimension, based on the proportion of installed or transmitted power from regional power sources and the inherent emission factors of the corresponding regional power source types, the regional emission factors are calculated for each region, specifically including:

[0112] Based on the power generation capacity or power transmission ratio data of each zone in the sending-end region, the power structure weight or power transmission ratio weight of each zone in the sending-end region is determined; if the power generation capacity data of each zone in the sending-end region is obtained (from the online power grid system), the ratio of the installed capacity of the i-th type of power source in each zone to the total installed capacity of the zone is calculated as the power structure weight of the zone; if the power transmission data of each zone in the sending-end region to a given region is obtained (from the settlement report of the sending-end power trading center), the ratio of the power transmission of each zone to the total power transmission of the sending-end region is calculated as the power transmission ratio weight of the zone.

[0113] Based on the weight of power structure or the weight of external transmission ratio, and combined with the inherent emission factor of power type in the corresponding zone, the zone emission factor of each zone in the sending region is calculated.

[0114] When using power structure weights, the calculation method is a weighted sum of the power structure weights and the inherent emission factors of the power type:

[0115]

[0116] When using the weighting of the proportion of electricity transmitted to other regions, the calculation method is the product of the weighting of the proportion of electricity transmitted to other regions and the overall average emission factor of the sending region:

[0117] E k =W k ×E avg (13)

[0118] Among them, E k C represents the emission factor for region k at the sending end. k,i W represents the installed capacity percentage of the i-th type of power supply in partition k. k E represents the weight of the outbound delivery ratio for partition k. avg E represents the overall average emission factor of electricity in the sending-end region. i Let be the inherent emission factor of the i-th type of power source, and n be the total number of power source types in the sending-end region.

[0119] After calculating the zonal emission factor E k Then, the corresponding sending-end region identifier (consistent with the input power sending-end region K) is extracted and used as the fourth spatiotemporal label, along with the zoning emission factor E. k Binding storage. Optionally, the fourth spatiotemporal label may also include the effective / calculation time range of the emission factor for that partition as a time label.

[0120] Similarly, the zoning emission factor E for each zone is calculated. kAfterwards, the deviation is verified and adjusted. This includes: calculating the deviation between the sum of the products of the emission factor of each zone and the corresponding power generation and the product of the average emission factor of the overall power generation in the sending region and the total power generation in the sending region. If the deviation is greater than a preset threshold, the power structure weight or the external transmission ratio weight is adjusted until the deviation is less than or equal to the preset threshold.

[0121] S3 matches the power generation data of various energy sources within a given area with the inherent emission factors of the corresponding energy types, calculates the carbon emissions of power generation in each spatiotemporal unit, and superimposes them to obtain the total carbon emissions of power generation in the given area; based on the second spatiotemporal label of the input power data, the input power is precisely matched with the time-of-use emission factors and the zone emission factors to calculate the total carbon emissions of the transferred power in the given area.

[0122] The carbon emissions generated by power generation within the region are calculated by summing the products of the power generation of each type of thermal power plant unit within the region and the carbon emission baseline value for that type of unit (i.e., the inherent emission factor of the power source type), denoted as C. local .

[0123] For the total carbon emissions from the electricity input in a given region, first determine the emission factor corresponding to the input electricity, and then obtain it by summing the products, denoted as C. import In this invention, based on the second spatiotemporal label of the input electricity data, the input electricity is precisely matched with the time-of-use emission factor and the zone emission factor, specifically including:

[0124] Extract the time unit T and sending region K from the second spatiotemporal label of the input power data, and automatically match the time-of-use emission factor E corresponding to the time unit T in step S21. T In step S22, the emission factor E corresponding to the sending-end region K is... K ;

[0125] As needed, select any of the following methods to obtain the matching factor corresponding to the input power: in E T With E K The mean value is used as the matching factor corresponding to the input power. When the time dimension has higher priority than the spatial dimension, E is directly used. T When spatial dimension has higher priority than time dimension as the matching factor corresponding to the input power, E is directly used. K This serves as the matching factor for the input power level. The priority level can be set as needed.

[0126] S4 uses the sum of total carbon emissions from power generation and total carbon emissions from transferred electricity in a given region as the numerator, and the sum of total power generation from all types of energy sources in the given region and total electricity transferred from other regions as the denominator to calculate the average power emission factor for the given region, and binds it to the fifth spatiotemporal tag.

[0127]

[0128] Among them, Q local Q represents the total electricity generated by all types of energy sources within a given region. import Let C be the total imported electricity from outside the given region. This formula is equivalent to the previously derived formula (9). However, due to the carbon emissions C of the total imported electricity... import It is calculated based on the time-sharing and zone-based emission factors at the sending end, thus providing more accurate calculation results.

[0129] For the calculated average emission factor of a given region, a fifth time tag containing the given region identifier and the calculation period of the average emission factor is attached to clarify the applicable boundaries and traceability basis of the factor.

[0130] S5, through a user interface, presents the average power emission factor of a given region, the data sources involved in the calculation, and the spatiotemporal labels corresponding to each data and factor in a visual form, supporting bidirectional traceability based on spatiotemporal labels.

[0131] The visualization methods will not be elaborated upon in this article.

[0132] This invention calculates that each link in the entire chain of data and factors is bound to a corresponding spatiotemporal tag, supporting bidirectional traceability based on spatiotemporal tags.

[0133] Forward tracing (from factor to data / tag): Starting with the final calculated average electricity emission factor, it reverses the query to retrieve the original data (such as total regional power generation, electricity transferred from other regions) and corresponding spatiotemporal tags that support the calculation of this factor. It presents the calculation link of "data → tag → factor". Specifically, forward tracing starts from the average electricity emission factor, and based on the given regional identifier and calculation period in its bound fifth spatiotemporal tag, it filters the numerator and denominator data used to calculate this factor within the corresponding time period and region, as well as the intermediate calculated factors, and displays the bound first to fourth spatiotemporal tags, presenting a complete association link from factor to data and tags.

[0134] Reverse tracing (from label to data / factor): Starting with a specific spatiotemporal label (e.g., the second spatiotemporal label "2024Q3; City A, transmission area"), the system queries forward for all data associated with that label and the final average emission factor used in the calculation. It displays the relationship between "label → data → factor". Specifically, reverse tracing starts with any of the first to fifth spatiotemporal labels, extracts the time unit and regional identifier from the label, matches the original data or intermediate calculation factors containing the same time and regional information in the database, and then uses the relationships between the data to locate the average electricity emission factor used in the calculation, forming a tracing path from the spatiotemporal label to the associated data and factor.

[0135] Two-way traceability can avoid accounting errors caused by data tampering or mismatch, meet compliance requirements such as carbon audits, and quickly locate the problem when the calculation results are abnormal, greatly improving the efficiency of problem investigation.

[0136] Based on the same technical concept as the method embodiment, another embodiment of the present invention provides a spatiotemporally traceable system for generating and presenting the average emission factor of electricity, referring to... Figure 4 The system includes:

[0137] The data acquisition module is used to acquire power generation data of various energy sources within a given area. The power generation data is bound to a first spatiotemporal tag that includes the time unit corresponding to the power generation and the spatial unit of the power cluster within the area. The module is also used to acquire input power data transferred from other areas into the given area. The input power data includes time-sharing and zone-specific details and is bound to a second spatiotemporal tag that includes the time unit corresponding to the input power and the spatial unit of the sending-end area of ​​the transfer channel. The module is also used to acquire basic sending-end data, including the inherent emission factor of each power type, time-sharing load / output data, and the percentage of installed capacity or external power transmitted by the zoned power sources.

[0138] The sending-end factor spatiotemporal decomposition module is used to calculate the time-sharing emission factor of each time unit based on time-sharing load / output data and the inherent emission factor of the power type, and bind it to the third spatiotemporal label consistent with the input power time unit; and to calculate the partition emission factor of each partition based on the partition power installed capacity or external power transmission ratio data and the inherent emission factor of the corresponding partition power type, and bind it to the fourth spatiotemporal label consistent with the input power sending-end area spatial unit.

[0139] The carbon emission calculation module is used to match the power generation data of various energy sources in a given area with the inherent emission factors of the corresponding energy types, calculate the carbon emissions of power generation in each spatiotemporal unit, and sum them up to obtain the total carbon emissions of power generation in the given area; based on the second spatiotemporal label of the input power data, the input power is accurately matched with the time-of-use emission factor and the zone emission factor to calculate the carbon emissions of the transferred power in each spatiotemporal unit, and sum them up to obtain the total carbon emissions of the transferred power in the given area.

[0140] The electricity average emission factor calculation module is used to calculate the electricity average emission factor of a given region by using the sum of the total carbon emissions from power generation and the total carbon emissions from transferred electricity in the given region as the numerator, and the sum of the total power generation of various energy sources in the given region and the total input electricity transferred from other places as the denominator, and binds a fifth spatiotemporal tag containing the time unit and spatial range of the given region.

[0141] The visualization module is used to present the average power emission factor of a given region, the data sources involved in the calculation, and the spatiotemporal labels corresponding to each data and factor in a visual form through the user interface, and supports bidirectional traceability based on spatiotemporal labels.

[0142] It should be understood that the spatiotemporally traceable average emission factor generation and presentation system for electricity in this embodiment can realize all the technical solutions in the above method embodiments. The functions of each functional module can be specifically implemented according to the methods in the above method embodiments. The specific implementation process can be referred to the relevant descriptions in the above embodiments, which will not be repeated here.

[0143] Another embodiment of the present invention provides an electronic device, including: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, wherein when the programs are executed by the processors, they implement the spatiotemporally traceable method for generating and presenting the average emission factor of electricity as described above.

[0144] Another embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the spatiotemporally traceable method for generating and presenting the average emission factor of electricity as described above.

[0145] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus (systems), computer devices, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0146] This invention is described with reference to a flowchart of a method according to embodiments of the invention. It should be understood that each step in the flowchart and combinations thereof can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing device, generate instructions for implementing the process. Figure 1 A device for a function specified in one or more processes.

[0147] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 The function specified in one or more processes.

[0148] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 Steps of a specified function in one or more processes.

Claims

1. A method for generating and presenting a spatiotemporally traceable average emission factor for electricity, characterized in that, Includes the following steps: Acquire power generation data of various energy sources within a given area. The power generation data is bound to a first spatiotemporal label containing the time unit corresponding to the power generation and the spatial unit of the power cluster within the area. Acquire input power data transferred from other areas into the given area. The input power data includes time-division and partition details and is bound to a second spatiotemporal label containing the time unit corresponding to the input power and the spatial unit of the sending area of ​​the transfer channel. Acquire basic data from the sending end, including the inherent emission factor of each power type, time-of-use load / output data, and the proportion of installed or transmitted power from regional power sources. Based on time-sharing load / output data and the inherent emission factor of power type, the time-sharing emission factor of each time unit is calculated by weighting and bound to a third spatiotemporal label consistent with the time unit of input power. Based on the data of the proportion of installed or transmitted power in the zoned power supply and the inherent emission factor of the corresponding zoned power supply type, the zoned emission factor of each zone is calculated and bound to the fourth spatiotemporal label consistent with the spatial unit of the input power sending end area. The power generation data of various energy sources in a given area are matched with the inherent emission factors of the corresponding energy types to calculate the carbon emissions of power generation in each spatiotemporal unit, and then superimposed to obtain the total carbon emissions of power generation in the given area. Based on the second spatiotemporal label of the input power data, the input power is accurately matched with the time-of-use emission factor and the zone emission factor to calculate the carbon emissions of the transferred power in each spatiotemporal unit, and then superimposed to obtain the total carbon emissions of the transferred power in the given area. The average emission factor of electricity in a given region is calculated by using the sum of the total carbon emissions from electricity generation and the total carbon emissions from electricity transferred into the region as the numerator, and the sum of the total electricity generation from all types of energy sources in the given region and the total electricity input from other regions as the denominator. The factor is then bound to a fifth spatiotemporal tag that includes the time unit and spatial range of the given region. The user interface presents the average electricity emission factor for a given region, the data sources involved in the calculation, and the spatiotemporal labels corresponding to each data point and factor in a visual format. It supports bidirectional traceability based on spatiotemporal labels, which includes: Forward tracing starts from the average emission factor of electricity. Based on the given regional identifier and calculation period in the fifth spatiotemporal label it is bound to, the database is used to filter out the corresponding time unit, the numerator and denominator data used to calculate the factor within the region, as well as the intermediate calculation factor, and displays the first to fourth spatiotemporal labels it is bound to, presenting a complete link from factor to data and label. The reverse tracing method starts from any of the first to fifth spatiotemporal labels, extracts the time unit and regional identifier in the label, matches the original data or intermediate calculation factors containing the same time and regional information in the database, and then uses the correlation between the data to locate the average electricity emission factor involved in the calculation, forming a tracing path from the spatiotemporal label to the associated data and factors.

2. The method according to claim 1, characterized in that, Based on time-of-use load / output data and the inherent emission factor of power source type, the time-of-use emission factor for each time unit is calculated using a weighted average, including: Based on the time-sharing load / output data of the sending-end region, the power output ratio of each time unit in the sending-end region is determined as follows: If historical power output data of various types of power sources recorded in the sending-end region according to the specified time unit is obtained, the ratio of the power output of each type of power source to the total output of the sending-end region in each time unit is directly calculated as the power output ratio of that time unit; if historical power output data is not obtained, the power output ratio of each time unit is allocated based on the load curve of the specified time unit level in the sending-end region, combined with the typical output patterns of each power source type. The time-of-use emission factor for each time unit is calculated by weighting the power output ratio of each time unit in the sending region and combining it with the inherent emission factor of the corresponding power type.

3. The method according to claim 2, characterized in that, After calculating the time-sharing emission factors for each time unit, the process also includes: verifying the time-sharing emission factors for each time unit and adjusting for deviations. The verification and adjustment of deviations includes: calculating the deviation between the sum of the products of the time-of-use emission factors and the corresponding power generation for each time unit and the product of the overall average emission factor of the sending-end region and the total power generation of the sending-end region. If the deviation is greater than a preset threshold, the power output ratio is adjusted until the deviation is less than or equal to the preset threshold. The overall average emission factor of the sending-end region adopts the annual average factor of the power grid published by the state.

4. The method according to claim 1, characterized in that, Based on the percentage of installed or transmitted power from different zones and the inherent emission factors of the corresponding zone power types, the zone emission factors for each zone are calculated, including: Based on the power installed capacity or power transmission ratio of each region in the sending-end area, determine the power structure weight or power transmission ratio weight of each region in the sending-end area. Based on the power structure weight or the external transmission ratio weight, and combined with the inherent emission factor of the power type of the corresponding zone, the zone emission factor of each zone in the sending-end region is calculated. When using the power structure weight, the calculation method is the weighted sum of the power structure weight and the inherent emission factor of the power type; when using the external transmission ratio weight, the calculation method is the product of the external transmission ratio weight and the overall average emission factor of the sending region, wherein the overall average emission factor of the sending region adopts the annual average factor of the power grid published by the state.

5. The method according to claim 4, characterized in that, After calculating the emission factors for each zone, the process also includes verifying and adjusting the deviations of the emission factors for each zone. The verification and adjustment of deviations includes: calculating the deviation between the sum of the products of the emission factors of each zone and the corresponding power generation and the product of the overall average emission factor of the sending region and the total power generation of the sending region; if the deviation is greater than a preset threshold, adjusting the power structure weight or the external transmission ratio weight until the deviation is less than or equal to the preset threshold.

6. The method according to claim 1, characterized in that, Based on the second spatiotemporal label of the input electricity data, the input electricity is precisely matched with the time-of-use emission factor and the zone emission factor, including: Extract the time unit T and sending region K from the second spatiotemporal label of the input power data, and automatically match the time-of-use emission factor E corresponding to the time unit T. T The emission factor E corresponding to the sending-end region K. K ; As needed, select any of the following methods to obtain the matching factor corresponding to the input power: in E T With E K The mean value is used as the matching factor corresponding to the input power. When the time dimension has higher priority than the spatial dimension, E is directly used. T When spatial dimension has higher priority than time dimension as the matching factor corresponding to the input power, E is directly used. K This serves as the matching factor corresponding to the input power level.

7. A spatiotemporally traceable system for generating and presenting the average emission factor of electricity, characterized in that, include: The data acquisition module is used to acquire power generation data of various energy sources within a given area. The power generation data is bound to a first spatiotemporal tag that includes the time unit corresponding to the power generation and the spatial unit of the power cluster within the area. The module is also used to acquire input power data transferred from other areas into the given area. The input power data includes time-division and partition details and is bound to a second spatiotemporal tag that includes the time unit corresponding to the input power and the spatial unit of the sending area of ​​the transfer channel. Acquire basic data from the sending end, including the inherent emission factor of each power type, time-of-use load / output data, and the proportion of installed or transmitted power from regional power sources. The sending-end factor spatiotemporal decomposition module is used to calculate the time-sharing emission factor of each time unit based on the time-sharing load / output data and the inherent emission factor of the power supply type, and bind it to a third spatiotemporal tag consistent with the input power time unit. Based on the data of the proportion of installed or transmitted power in the zoned power supply and the inherent emission factor of the corresponding zoned power supply type, the zoned emission factor of each zone is calculated and bound to the fourth spatiotemporal label consistent with the spatial unit of the input power sending end area. The carbon emission calculation module is used to match the power generation data of various energy sources in a given area with the inherent emission factors of the corresponding energy types, calculate the carbon emissions of power generation in each spatiotemporal unit, and sum them up to obtain the total carbon emissions of power generation in the given area; based on the second spatiotemporal label of the input power data, the input power is accurately matched with the time-of-use emission factor and the zone emission factor to calculate the carbon emissions of the transferred power in each spatiotemporal unit, and sum them up to obtain the total carbon emissions of the transferred power in the given area. The electricity average emission factor calculation module is used to calculate the electricity average emission factor of a given region by using the sum of the total carbon emissions from power generation and the total carbon emissions from transferred electricity in the given region as the numerator, and the sum of the total power generation of various energy sources in the given region and the total input electricity transferred from other places as the denominator, and binds a fifth spatiotemporal tag containing the time unit and spatial range of the given region. The visualization module is used to present the average electricity emission factor for a given region, the data sources involved in the calculation, and the spatiotemporal labels corresponding to each data point and factor in a visual form through a user interface. It supports bidirectional traceability based on spatiotemporal labels, which includes: Forward tracing starts from the average emission factor of electricity. Based on the given regional identifier and calculation period in the fifth spatiotemporal label it is bound to, the database is used to filter out the corresponding time unit, the numerator and denominator data used to calculate the factor within the region, as well as the intermediate calculation factor, and displays the first to fourth spatiotemporal labels it is bound to, presenting a complete link from factor to data and label. The reverse tracing method starts from any of the first to fifth spatiotemporal labels, extracts the time unit and regional identifier in the label, matches the original data or intermediate calculation factors containing the same time and regional information in the database, and then uses the correlation between the data to locate the average electricity emission factor involved in the calculation, forming a tracing path from the spatiotemporal label to the associated data and factors.

8. An electronic device, comprising: One or more processors; Memory; And one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, wherein when the programs are executed by the processors, they implement the spatiotemporally traceable method for generating and presenting the average emission factor of electricity as claimed in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the spatiotemporally traceable method for generating and presenting the average emission factor of electricity as described in any one of claims 1-6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the spatiotemporally traceable method for generating and presenting the average emission factor of electricity as described in any one of claims 1-6.

Images