A carbon emission evaluation method considering out-of-zone clean energy

Abstract

The present application relates to the technical field of power system operation, and more particularly to a carbon emission evaluation method considering external clean energy, comprising: based on the network structure and operation data of power big data, using the carbon flow tracking algorithm of node power proportion allocation principle, and considering power transmission loss, calculating the carbon emission data of each node in each period of power generation, power transmission and power consumption; considering the regional internal and external new energy and its energy type, establishing a carbon emission index evaluation system in four aspects of comprehensive production capacity, consumption capacity, dump capacity and external access consumption capacity; calculating the carbon emission evaluation index, scoring and strategy making for each city in the region, realizing the fine evaluation of regional carbon emission, perfecting the whole link of power generation, transmission and consumption, effectively quantifying the carbon emission of each city in the region, analyzing and calculating the proportion of each type of power source, clean energy consumption, the rationality of external clean energy access point, the carbon emission and consumption level of each region and other carbon emission problems.

Description

Technical Field

[0001] This invention relates to the field of power system operation technology, and in particular to a carbon emission assessment method that takes into account clean energy from outside the region. Background Technology

[0002] Conducting comprehensive and scientific carbon emission assessments to guide emission reduction decisions is becoming increasingly important. Electricity carbon emissions account for approximately 40% of the energy sector's carbon emissions, primarily from greenhouse gases such as carbon dioxide emitted by power plants burning fossil fuels. Along with electricity transmission, carbon emissions, as a byproduct of electricity generation, also flow through the transmission network. Traditional electricity carbon emission calculations only count emissions from the power source side; however, due to the complex interconnected power grids, electricity generated at the source is not necessarily consumed within its region, leading to a lack of fairness in regional carbon emission assessments. From the perspective of emission reduction responsibility, not only should power generation companies be the main actors in carbon reduction, using their own technological reforms to reduce carbon emissions per unit of electricity production, but electricity users, as the final consumers of electricity, should also bear corresponding emission reduction responsibilities. However, there is currently a lack of practical and feasible methods for scientifically quantifying the carbon emissions generated by electricity consumption by users in different regions and at different times. Where does electricity generated by various power sources such as thermal power, wind power, photovoltaic power, hydropower, and nuclear power go? Are there insufficient capacity in clean energy transmission channels causing transmission congestion? Are there significant differences in the level of clean energy consumption in different regions? Are the layout of photovoltaic and wind power within the province and the access points for external clean energy reasonable? Are there significant differences in carbon emission levels between different regions from the perspectives of power production and power consumption? Do carbon emission production centers and consumption centers overlap? How can the carbon emission ranking of different regions be comprehensively considered from the production and consumption sides? How should regional emission reduction targets be formulated, and how can emission reduction work be carried out in a "targeted" manner? These questions lack corresponding methods and data support.

[0003] There has been much research on carbon emission assessment, such as the Chinese invention patent CN201710406692, "A System and Method for Grid-Source-Load Scheduling Assessment Based on Carbon Emissions," which considers economic and environmental indicators on both the power source and load sides; the Chinese invention patent CN202111310294, "A Method for Electric Carbon Control Based on Real-Time Interaction between Source, Grid, and Load and Its Intelligent Management System," which assesses the cleanliness index of transformer substations; and the Chinese invention patent CN202210546019, "A Method Based on Carbon Footprint Tracking Technology." Methods for tracking invisible carbon emissions include those that comprehensively consider spatiotemporal characteristics to quantify and allocate invisible carbon emissions; for example, Chinese invention patent CN202210266937, "Power Flow Tracing Method and Device for Equivalent Carbon Emissions from Electricity Use," analyzes the carbon tracing matrix and carbon emission source information from users to power plants and from power lines to power plants based on the node averaging principle; and Chinese invention patent CN202210319858, "A Carbon Emission Flow Tracing Method Based on Graph Neural Networks," trains a carbon emission result set based on the proportional equivalence principle using graph neural networks to improve computational efficiency.

[0004] However, the aforementioned research mainly focuses on the power generation and consumption sides, and the data calculation mainly adopts power flow algorithms and their derivatives. The index evaluation mainly involves power source planning and grid planning. This approach has the following drawbacks:

[0005] Carbon emission assessments across the entire chain from power generation to transmission to electricity users are still incomplete. Currently, there is a lack of practical and feasible methods to quantify the carbon emissions from electricity consumption in different regions and at different times. It is also impossible to effectively quantify and answer questions regarding the proportion of various power sources such as thermal, wind, solar, hydro, and nuclear power, the capacity of clean energy transmission channels outside the region and the degree of access and absorption, and the carbon emission and absorption levels in different regions. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a carbon emission assessment method that takes into account clean energy from outside the region, effectively solving the problems in the background art.

[0007] To achieve the above objectives, the technical solution adopted by this invention is: a carbon emission assessment method considering clean energy from outside the region, comprising:

[0008] Step 1: Based on the network structure and operation data of power big data, adopt the carbon flow tracking algorithm with the node power ratio allocation principle, and consider transmission loss to calculate the carbon emission data of each node in each time period of the entire process of power generation, transmission and consumption.

[0009] Step 2: Considering new energy sources and their types both within and outside the region, establish a carbon emission indicator assessment system encompassing four aspects: comprehensive production capacity, absorption capacity, storage capacity, and external access and absorption capacity.

[0010] Step 3: Calculate carbon emission assessment indicators, score cities and prefectures within the region, and formulate strategies.

[0011] Furthermore, in step 1, the calculation process for carbon emission data at each time point and node in the entire process of power generation, transmission, and consumption is as follows:

[0012] Step 1.1: Calculate the power consumption:

[0013] The observation period is t (a certain hour), and the observation object is node k in the region. The formula for the nodal power relationship is as follows:

[0014]

[0015] In the formula: For the total power flowing in, For end load, For transmission losses, This represents the total outflow power.

[0016] Generating node m generates active power. Considering the end load and transmission losses at node k, and based on the principle of node power proportional allocation, the end load at node k obtains a power proportion from the generating node m. The calculation formula is:

[0017]

[0018] Each element is represented by a matrix obtained through the flow power of the nodes. The calculation formula is:

[0019]

[0020] In the formula: P ji Let P be the power flowing from node j to node i. j Let U be the inflow power at node j. j Let j be the set of downstream tracking nodes starting from node j;

[0021] The power drawn by node k from generating node m by the end load is obtained. for:

[0022]

[0023] In the formula: e m These are unit row vectors whose k-th and m-th elements are 1, and all other elements are 0, respectively.

[0024] To examine the downstream tracking matrix at section t, representing the correlation between nodes;

[0025] Step 1.2: Calculate daily power generation:

[0026] The observation period was changed from hours to days, and the observation objects were N nodes k in various cities within the region, of which M were thermal power nodes. Substituting into equation (4), the power consumption was calculated, and the daily power consumption was obtained:

[0027]

[0028] In the formula: t is the hour number; k is the user node number in various cities within the region, with a total of N nodes; m is the thermal power node number, considering the power source type, taking thermal power as an example, there are M thermal power nodes;

[0029] Based on the carbon emission equivalence factor, the carbon emissions of thermal power generation are converted into carbon emissions and then incorporated into the entire generation-transmission-consumption process to calculate the carbon emissions (CE) per unit of power generated. 发碳 :

[0030] CE 发碳 =P 发火 ×Q (6)

[0031] CE 输碳 =P 输火 ×Q (7)

[0032] CE 用碳 =P 用火 ×Q (8)

[0033] In the formula: Q is the conversion factor, which takes a value of 0.2.

[0034] Furthermore, in step 2, the specific process of establishing the carbon emission indicator assessment system is as follows:

[0035] Step 2.1, Data Preparation;

[0036] Step 2.2: Calculate the proportion of clean energy base and conduct a production capacity assessment;

[0037] Step 2.3: Calculate the local consumption rate of clean energy, assess the nature of clean energy transfer, and evaluate the consumption capacity and storage capacity.

[0038] Step 2.4: Calculate the absorption rate of clean energy outside the area and the capacity margin of the channel, and conduct an assessment of the external reception capacity.

[0039] Further, in step 2.1, the data preparation specifically includes:

[0040] Taking all cities and prefectures within the region as the subjects of study, and statistically analyzing the acquired data, assuming that the total power generation, transmission, and consumption within the region is constant, and that power outside the region has been incorporated into the respective cities and prefectures, then the total power generation of all cities and prefectures within the region equals the sum of the total power consumption and the total transmission losses, i.e.:

[0041] ∑P发 =∑P 用 +∑P 输 (9)

[0042] Similarly, regional carbon emissions are calculated as follows: total carbon emissions from power generation equal the sum of total carbon emissions from power consumption and total carbon emissions from power transmission, i.e.:

[0043] ∑CE 发 =∑CE 用 +∑CE 输 (10)

[0044] Furthermore, the specific steps for production capacity assessment in step 2.2 are as follows:

[0045] Taking a single prefecture-level city as the subject of study, calculate the proportion of clean energy power generation in the region, and calculate the results of different clean energy power generation proportion indicators:

[0046] W 发内清 =P 发内清 / ∑P 发 (11)

[0047] W 发外清 =P 发外清 / ∑P 发 (12)

[0048] Similarly, calculate the proportion of clean energy electricity consumption W. 用内清 W 用外清 The proportion of clean energy transmission W 输内清 W 输外清 ;

[0049] The proportion of clean energy types is calculated based on energy type to obtain the proportion of different clean energy types in the entire process of generation, transmission, and consumption, with wind power as an example:

[0050] W 发内清，风 =P 发,内风 / ∑P 发内清 (13)

[0051] W 发外清，风 =P 发,外风 / ∑P 发内清 (14)

[0052] Similarly, calculate the power generation share of photovoltaic, hydropower, and nuclear power, and calculate the power transmission and consumption share of different clean energy types;

[0053] Taking prefecture-level cities as the perspective, this study analyzes the proportion of various types of clean energy in these cities, as well as basic indicators such as the proportion of clean energy generated within and outside the region. This analysis is then extended to other cities within the region, and the proportion of clean energy generated by each city in the total value of clean energy generated in the entire region is calculated.

[0054] M1=(P 发内清 +P 发外清 ) / ∑(P 发内清 +P 发外清 (15)

[0055] Furthermore, in step 2.3, the local consumption rate of clean energy is calculated, and the nature of clean energy transfer is assessed. The specific steps are as follows:

[0056] Taking a single prefecture-level city as the subject of study, the results of the regional clean energy consumption index for that city are calculated, divided into two levels: energy consumption and transfer, and clean energy consumption and transfer. The formula is as follows:

[0057] ω 能源 =(P 发 -P 用 -P 输 ) / ∑P 用 (16)

[0058] ω 清洁能源 =((P) 发内清 +P 发外清 )-(P 输内清 +P 输外清 )-(P 用内清 +P 用外清 )) / ∑(P 用内清 +P 用外清 (17)

[0059] Where, when ω 能源 =0 Total local energy consumption is entirely local, ω 能源 >0 Local total energy is transferred to other cities, ω 能源 <0 local absorption of total energy power from other cities;

[0060] ω 清洁能源 =0 Local clean energy is completely consumed locally, ω 清洁能源 >0 Local clean energy is being transferred to other cities, ω 清洁能源 <0 Local absorption of clean energy power from other cities.

[0061] Furthermore, in step 2.3, the specific steps for assessing the absorption capacity and storage capacity are as follows:

[0062] Taking a single prefecture-level city as the subject of study, the proportion of that city's clean energy consumption in the total value of clean energy consumption in the entire region:

[0063] M2=(P 用内清 +P 用外清 ) / ∑(P 用内清 +P 用外清 (18)

[0064] Taking a single prefecture-level city as the subject of study, with clean energy generation as the positive direction and clean energy consumption and depletion as the negative directions, the absolute value of the sum of these factors represents the proportion of the total absolute value of the sum across the entire region:

[0065] M3=|(P 发内清 +P 发外清 )-(P 输内清 +P 输外清 )-(P 用内清 +P 用外清 )| / ∑|(P 发内清 +P 发外清 )-(P 输内清 +P 输外清 )-(P 用内清 +P 用外清 (19)

[0066] Furthermore, in step 2.4, the calculation of the external clean energy absorption rate and channel capacity margin, and the assessment of external reception capacity, are carried out through the following steps:

[0067] Taking a single prefecture-level city as the subject of study, the specific degree of acceptance of external clean energy in that prefecture-level city is as follows:

[0068] ω 外，清洁能源 =(P 发外清 -P 输外清 -P 用外清 ) / ∑P 用外清 (20)

[0069] The capacity margin of clean energy corridors outside the urban area of ​​this region is:

[0070] θ A =(S A -P 发外清 ) / S A (twenty one)

[0071] In the formula: S A For the channel capacity of clean energy from outside the region to City A, θ A The remaining margin of clean energy channels outside city A;

[0072] Taking a single prefecture-level city as the subject of study, the degree to which the city receives clean energy from outside the region is defined as the percentage of the total absolute value of clean energy received from outside the region, with the output of clean energy from outside the region as the positive direction and the consumption and loss of clean energy from outside the region as the negative direction.

[0073] M4 = |P 发外清 -P 输外清 -P 用外清 | / ∑|P 发外清 -P 输外清 -P 用外清| (22).

[0074] Furthermore, in step 3, each city is individually scored, the total score is calculated as (M1+M2+M3+M4) / 4, and the quantitative data of the indicator system is combined to evaluate all cities in the region and provide strategy recommendations.

[0075] The assessment specifically involves: performing a qualitative analysis of the data distribution, including concentrated generation on the power generation side, balanced generation on the power generation side, concentrated power consumption on the power consumption side, balanced power consumption on the power transmission side, power transmission side losses exceeding limits, and normal power transmission side losses;

[0076] The strategy is specifically divided into four types based on production capacity, consumption capacity, transfer and storage capacity, and external reception capacity: recommending to increase the output of new energy, recommending to increase the absorption and consumption of new energy, recommending to increase the provision of new energy transfer and storage, and recommending to transform the external channels for new energy.

[0077] Furthermore, in the evaluation process, the qualitative conditions for concentration and balance are as follows: if the proportion of the examined city to the overall region is greater than or equal to 40% within its domain, the qualitative analysis result is "concentrated"; otherwise, it is "balanced". (For example, if the proportion of hydropower generation in city A to the total hydropower generation in the region is greater than or equal to 40%, then the hydropower generation in the region is concentrated in city A.)

[0078] The conditions for normal and excessive losses are as follows: if the transmission loss of the city under investigation is greater than the normal line loss value (3%), the qualitative analysis result is excessive; otherwise, it is normal.

[0079] Data is categorized as either abnormal or normal based on its status. The criteria for determining abnormality is that if the total error during the data preparation phase is greater than 5% (the allowable error is 5%).

[0080] The beneficial effects of this invention are as follows: Based on the network structure and operational data of power big data, and through the active power ratio equal-sharing power flow tracking algorithm, considering external photovoltaic power, the proportion of electricity at each time period and node in the entire process of power generation, transmission, and consumption is calculated. This constructs a comprehensive carbon emission indicator assessment system integrating production, grid connection, and consumption processes, achieving refined assessment of regional carbon emissions. It improves the entire power generation, transmission, and consumption process, effectively quantifies the carbon emissions of electricity consumption in various cities within the region, and analyzes and calculates carbon emission issues such as the proportion of various power sources, clean energy consumption, the rationality of external clean energy grid connection points, and the carbon emission and consumption levels of different regions. Attached Figure Description

[0081] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0082] Figure 1 This is a flowchart of a carbon emission assessment method considering clean energy from outside the region, as described in an embodiment of the present invention.

[0083] Figure 2 This is a block diagram of the carbon emission index system in an embodiment of the present invention; Detailed Implementation

[0084] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0085] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly attached to the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0086] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0087] like Figure 1 The carbon emission assessment methods shown consider clean energy from outside the region, including:

[0088] Step 1: Based on the network structure and operation data of power big data, adopt the carbon flow tracking algorithm with the node power ratio allocation principle, and consider transmission loss to calculate the carbon emission data of each node in each time period of the entire process of power generation, transmission and consumption.

[0089] Step 2: Considering new energy sources and their types both within and outside the region, establish a carbon emission indicator assessment system encompassing four aspects: comprehensive production capacity, absorption capacity, storage capacity, and external access and absorption capacity.

[0090] Step 3: Calculate carbon emission assessment indicators, score cities and prefectures within the region, and formulate strategies.

[0091] This invention, based on the network structure and operational data of power big data, uses an active power ratio equal-sharing power flow tracking algorithm, considering external photovoltaic power, to calculate the proportion of electricity at each time period and node in the entire process of power generation, transmission, and consumption. It constructs a comprehensive carbon emission index assessment system for the entire process of production, access, and consumption, achieving refined assessment of regional carbon emissions, improving the entire process of power generation, transmission, and consumption, effectively quantifying the carbon emissions of electricity consumption in various cities within the region, and analyzing and calculating carbon emission issues such as the proportion of various power sources, clean energy consumption, the rationality of external clean energy access points, and the carbon emission and consumption levels of various regions.

[0092] In step 1, the calculation process for carbon emission data at each time point and in each stage of the entire power generation, transmission, and consumption process is as follows:

[0093] Step 1.1: Calculate the power consumption:

[0094] The observation period is t (a certain hour), and the observation object is node k in the region. The formula for the nodal power relationship is as follows:

[0095]

[0096] In the formula: For the total power flowing in, For end load, For transmission losses, This represents the total outflow power.

[0097] Generating node m generates active power. Considering the end load and transmission losses at node k, and based on the principle of node power proportional allocation, the end load at node k obtains a power proportion from the generating node m. The calculation formula is:

[0098]

[0099] Each element is represented by a matrix obtained through the flow power of the nodes. The calculation formula is:

[0100]

[0101] In the formula: P ji Let P be the power flowing from node j to node i. j Let U be the inflow power at node j. j Let j be the set of downstream tracking nodes starting from node j;

[0102] The power drawn by node k from generating node m by the end load is obtained. for:

[0103]

[0104] In the formula: e m These are unit row vectors whose k-th and m-th elements are 1, and all other elements are 0, respectively.

[0105] To examine the downstream tracking matrix at section t, representing the correlation between nodes;

[0106] Step 1.2: Calculate daily power generation:

[0107] The observation period was changed from hours to days, and the observation objects were N nodes k in various cities within the region, of which M were thermal power nodes. Substituting into equation (4), the power consumption was calculated, and the daily power consumption was obtained:

[0108]

[0109] In the formula: t is the hour number; k is the user node number in various cities within the region, with a total of N nodes; m is the thermal power node number, considering the power source type, taking thermal power as an example, there are M thermal power nodes;

[0110] Based on the carbon emission equivalence factor, the carbon emissions of thermal power generation are converted into carbon emissions and then incorporated into the entire generation-transmission-consumption process to calculate the carbon emissions (CE) per unit of power generated. 发碳 :

[0111] CE 发碳 =P 发火 ×Q (6)

[0112] CE 输碳 =P 输火 ×Q (7)

[0113] CE 用碳 =P 用火 ×Q (8)

[0114] In the formula: Q is the conversion factor, which takes a value of 0.2.

[0115] In step 2, the specific process for establishing a carbon emission indicator assessment system is as follows:

[0116] Step 2.1, Data Preparation;

[0117] Taking the cities and prefectures within the region as the subjects of investigation, the power consumption P was obtained. 用 Power generation P 发 and transmission loss P 输 Considering thermal power plants, wind farms, hydropower plants, nuclear power plants, and photovoltaic stations both inside and outside the region, the power consumption P is obtained by superimposing the various types of power sources. 用 :

[0118] P 用 =P 用,火 +P 用,内风 +P用,内水 +P 用,内核 +P 用,内光 +P 用,外风 +P 用,外水 +P 用,外核 +P 用,外光

[0119] Power sources within and outside the region, including wind, hydro, nuclear, and solar power, are categorized into internal and external clean energy sources:

[0120] P 用 =P 用火 +P 用内清 +P 用外清

[0121] Similarly, based on the combined measurement and power flow calculation results, the power generation P 发 and transmission loss P 输 It is also obtained by classifying and superimposing various types of power sources. The statistical data already acquired, assuming a constant total generation-transmission-consumption value within the region, and that data outside the region has been aggregated to various cities, then the total value of each city within the region...

[0122] Electricity generation equals the sum of total electricity consumption and total transmission losses, that is:

[0123] ∑P 发 =∑P 用 +∑P 输 (9)

[0124] Similarly, regional carbon emissions are calculated as follows: total carbon emissions from power generation equal the sum of total carbon emissions from power consumption and total carbon emissions from power transmission, i.e.:

[0125] ∑CE 发 =∑CE 用 +∑CE 输 (10)

[0126] Step 2.2: Calculate the proportion of clean energy base and conduct a production capacity assessment;

[0127] The specific steps for production capacity assessment are as follows: Taking a single prefecture-level city as the subject of study, calculate the proportion of clean energy power generation in the region.

[0128] Results of calculations for the proportion of power generation from different clean energy sources:

[0129] W 发内清 =P 发内清 / ∑P 发 (11)

[0130] W 发外清 =P 发外清 / ∑P 发 (12)

[0131] Similarly, calculate the proportion of clean energy electricity consumption W.用内清 W 用外清 The proportion of clean energy transmission W 输内清 W 输外清 ;

[0132] The proportion of clean energy types is calculated based on energy type to obtain the proportion of different clean energy types in the entire process of generation, transmission, and consumption, with wind power as an example:

[0133] W 发内清，风 =P 发,内风 / ∑P 发内清 (13)

[0134] W 发外清，风 =P 发,外风 / ∑P 发内清 (14)

[0135] Similarly, calculate the power generation share of photovoltaic, hydropower, and nuclear power, and calculate the power transmission and consumption share of different clean energy types;

[0136] Taking prefecture-level cities as the perspective, this study analyzes the proportion of various types of clean energy in these cities, as well as basic indicators such as the proportion of clean energy generated within and outside the region. This analysis is then extended to other cities within the region, and the proportion of clean energy generated by each city in the total value of clean energy generated in the entire region is calculated.

[0137] M1=(P 发内清 +P 发外清 ) / ∑(P 发内清 +P 发外清 (15)

[0138] Finally, the city's production capacity is assessed based on the proportion of its clean energy output to the total value of clean energy generated in the entire region.

[0139] Step 2.3: Calculate the local consumption rate of clean energy, assess the nature of clean energy transfer, and evaluate the consumption capacity and storage capacity.

[0140] Calculating the local consumption rate of clean energy: Taking a single city as the subject of study, the results of the regional clean energy consumption index are calculated, which are divided into two levels: energy consumption and transfer, and clean energy consumption and transfer. The formula is as follows:

[0141] ω 能源 =(P 发 -P 用 -P 输 ) / ∑P 用 (16)

[0142] ω 清洁能源 =((P) 发内清 +P 发外清 )-(P 输内清 +P输外清 )-(P 用内清 +P 用外清 )) / ∑(P 用内清 +P 用外清 (17)

[0143] Where, when ω 能源 =0 Total local energy consumption is entirely local, ω 能源 >0 Local total energy is transferred to other cities, ω 能源 <0 local absorption of total energy power from other cities;

[0144] ω 清洁能源 =0 Local clean energy is completely consumed locally, ω 清洁能源 >0 Local clean energy is being transferred to other cities, ω 清洁能源 <0 Local absorption of clean energy power from other cities.

[0145] The specific steps for assessing the nature of clean energy transfer are as follows: Taking a single prefecture-level city as the subject of study, determine the proportion of clean energy consumed by that city in the total value of clean energy consumed in the entire region.

[0146] M2=(P 用内清 +P 用外清 ) / ∑(P 用内清 +P 用外清 (18)

[0147] Taking a single prefecture-level city as the subject of study, with clean energy generation as the positive direction and clean energy consumption and depletion as the negative directions, the absolute value of the sum of these factors represents the proportion of the total absolute value of the sum across the entire region:

[0148] M3=|(P 发内清 +P 发外清 )-(P 输内清 +P 输外清 )-(P 用内清 +P 用外清 )| / ∑|(P 发内清 +P 发外清 )-(P 输内清 +P 输外清 )-(P 用内清 +P 用外清 (19)

[0149] Step 2.4: Calculate the absorption rate of clean energy outside the area and the capacity margin of the channel, and conduct an assessment of the external reception capacity.

[0150] The specific steps for calculating the external clean energy absorption rate and channel capacity margin are as follows: Taking a single prefecture-level city as the case study, the specific external clean energy absorption rate of that city is as follows:

[0151] ω 外，清洁能源 =(P发外清 -P 输外清 -P 用外清 ) / ∑P 用外清 (20)

[0152] The capacity margin of clean energy corridors outside the urban area of ​​this region is:

[0153] θ A =(S A -P 发外清 ) / S A (twenty one)

[0154] In the formula: S A For the channel capacity of clean energy from outside the region to City A, θ A The remaining margin of clean energy channels outside city A;

[0155] External reception capacity is specifically reflected as follows: taking a single prefecture-level city as the object of study, the degree to which the city receives clean energy from outside the region is defined as the percentage of the total absolute value of the sum of clean energy emitted from outside the region (positive direction) and clean energy absorbed and consumed from outside the region (negative direction) in the total absolute value of clean energy received from outside the region in the entire region.

[0156] M4 = |P 发外清 -P 输外清 -P 用外清 | / ∑|P 发外清 -P 输外清 -P 用外清 | (22)

[0157] In step 3, each city is scored individually, the total score is calculated as (M1+M2+M3+M4) / 4, and the quantitative data of the indicator system is combined to evaluate all cities in the region and provide strategy recommendations.

[0158] The assessment specifically involves: a qualitative analysis of the data distribution, including concentrated generation, balanced generation, concentrated consumption, balanced consumption, transmission losses exceeding limits, and normal transmission losses.

[0159] The specific strategies are as follows: based on production capacity, consumption capacity, transfer and storage capacity, and external reception capacity, they are divided into four categories: recommending to increase the output of new energy, recommending to increase the absorption and consumption of new energy, recommending to increase the provision of new energy transfer and storage, and recommending to transform the external channels for new energy.

[0160] During the evaluation process, the qualitative criteria for concentration and balance are as follows: if the proportion of the examined city to the overall region is greater than or equal to 40% within its domain, the qualitative analysis result is "concentrated"; otherwise, it is "balanced". (For example, if the hydropower generation of city A accounts for greater than or equal to 40% of the total hydropower generation in the region, then the hydropower generation in the region is concentrated in city A).

[0161] The conditions for normal and excessive losses are as follows: if the transmission loss of the city under investigation is greater than the normal line loss value (3%), the qualitative analysis result is excessive; otherwise, it is normal.

[0162] Data is categorized as either abnormal or normal based on its status. The criteria for determining abnormality is that if the total error during the data preparation phase is greater than 5% (the allowable error is 5%).

[0163] Taking Jiangsu Province as an example, the specific implementation process is as follows:

[0164] Step 1: Construct a regional carbon emission trend model and use the nodal power ratio tracking algorithm to calculate carbon emission data considering the entire process of generation, consumption, and transmission. The known data are power generation outlet measurements and power consumption outlet measurements. Calculate the electrical and carbon emission data for the three stages of power generation, transmission, and consumption according to power source type.

[0165] Table 1 shows the power generation data for various cities and prefectures within the region (carbon emissions are in tons, and electricity is in megawatt-hours):

[0166] Table 1 Power generation data for each city in the region

[0167]

[0168]

[0169] Based on energy type, it can be divided into energy and clean energy (electricity generation, clean energy electricity generation).

[0170] Table 2 shows the electricity consumption data for various cities and prefectures within the region:

[0171] Table 2 Electricity Consumption Data for Cities in the Region

[0172] Serial Number area thermal power wind power Hydropower nuclear power Photovoltaics outside the region Photovoltaics in the area carbon emissions Electricity consumption Clean energy electricity consumption 1 Nanjing 167167.43 132.72 0.00 46.23 1602.50 248.17 35125.22 169197.05 2029.62 2 Wuxi City 195871.53 56.47 19830.43 3892.52 1122.55 103.75 41156.52 220877.25 25005.72 3 Xuzhou 92243.14 192.55 0.00 3262.12 49.47 626.69 19382.12 96373.97 4130.83 4 Changzhou 116202.99 5.23 16166.73 334.92 1203.13 90.37 24416.57 134003.37 17800.38 5 Suzhou 418589.39 127.34 11633.80 12899.48 1923.11 126.68 87954.00 445299.80 26710.41 6 Nantong City 119630.85 1731.00 0.00 8183.90 1446.02 1078.58 25136.83 132070.35 12439.50 7 Lianyungang City 25792.29 916.48 0.00 47672.43 2612.85 1124.50 5419.47 78118.55 52326.26 8 Huai'an City 42482.94 1960.52 0.00 5568.42 2941.10 390.73 8926.51 53343.71 10860.77 9 Yancheng City 75505.10 3125.67 2.37 17329.44 5464.62 1203.85 15865.13 102631.05 27125.95 10 Yangzhou 65602.89 1444.63 0.00 2607.66 4571.11 632.88 13784.48 74859.17 9256.28 11 Zhenjiang City 78311.17 11.87 0.28 117.92 814.38 377.08 16454.74 79632.70 1321.53 12 Taizhou City 68006.22 299.03 0.00 9756.47 3039.58 161.62 14289.46 81262.92 13256.70 13 Suqian City 52130.21 170.89 0.16 7383.14 5514.27 430.40 10953.60 65629.07 13498.86

[0173] Based on energy type, it can be divided into energy and clean energy (electricity consumption, clean energy electricity consumption).

[0174] Table 3 shows the transmission losses and clean energy transmission losses in various cities and prefectures within the region:

[0175] Table 3 Power Transmission Data for Cities in the Region

[0176] Serial Number Region Name Transmission loss - total Transmission loss - fire Transmission loss - Clean energy Transmission losses - Clean energy outside the region carbon emissions 1 Nanjing 4762.27 4715.33 46.94 11.57 990.79 2 Wuxi City 2322.00 2082.09 239.91 59.11 437.49 3 Xuzhou 1471.85 1435.31 36.54 9.00 301.59 4 Changzhou 1658.97 1437.26 221.71 54.63 302.00 5 Suzhou 3447.04 3259.47 187.57 46.21 684.88 6 Nantong City 1128.16 1061.14 67.02 16.51 222.97 7 Lianyungang City 2569.74 1005.84 1563.89 385.32 211.35 8 Huai'an City 1262.40 1035.71 226.69 55.85 217.62 9 Yancheng City 1733.39 1309.76 423.64 104.38 275.21 10 Yangzhou 1085.60 981.31 104.29 25.70 206.19 11 Zhenjiang City 2354.33 2332.61 21.73 5.35 490.13 12 Taizhou City 1480.29 1289.41 190.88 47.03 270.93 13 Suqian City 876.79 694.24 182.55 44.98 145.87

[0177] Based on energy type, it can be divided into energy and clean energy (transmission loss - total, transmission loss - clean energy).

[0178] Step 2: Construct an evaluation system and calculate the corresponding indicators:

[0179] I. Quantifying the proportion of different clean energy sources in various cities: The results of the proportion indicators of different clean energy sources in various cities of the region are shown in Table 4:

[0180] Table 4. Results of the proportion of different clean energy sources in various cities within the region.

[0181]

[0182] Number (％) 1 Nanjing 5.08 0.00 0.00 39.24 55.68 6.54 0.00 2.28 78.96 12.23 2 Wuxi City 5.78 0.00 0.00 56.62 37.59 0.23 79.30 15.57 4.49 0.41 3 Xuzhou 24.38 0.00 0.00 0.00 75.62 4.66 0.00 78.97 1.20 15.17 4 Changzhou 0.00 96.68 0.00 2.37 0.95 0.03 90.82 1.88 6.76 0.51 5 Suzhou 1.08 0.59 0.00 35.28 63.05 0.48 43.56 48.29 7.20 0.47 6 Nantong City 50.16 0.00 0.00 37.66 12.18 13.92 0.00 65.79 11.62 8.67 7 Lianyungang City 0.73 0.00 96.43 2.29 0.55 1.75 0.00 91.11 4.99 2.15 8 Huai'an City 34.00 0.00 0.00 59.14 6.86 18.05 0.00 51.27 27.08 3.60 9 Yancheng City 36.36 0.03 0.00 59.55 4.06 11.52 0.01 63.89 20.15 4.44 10 Yangzhou 20.06 0.00 0.00 75.66 4.28 15.61 0.00 28.17 49.38 6.84 11 Zhenjiang City 0.00 0.00 0.00 47.85 52.15 0.90 0.02 8.92 61.62 28.53 12 Taizhou City 2.79 0.00 0.00 72.53 24.68 2.26 0.00 73.60 22.93 1.22 13 Suqian City 2.15 0.00 0.00 96.12 1.73 1.27 0.00 54.69 40.85 3.19

[0183] It can be seen that, according to different clean energy ratio indicators, the power generation side is concentrated, the power consumption side is average, and clean energy is used locally in each city.

[0184] II. Calculate the proportion of clean energy, the degree of clean energy consumption, and the degree of clean energy consumption and transmission capacity outside the region.

[0185] The results of clean energy consumption indicators for each city in the region are shown in Table 5:

[0186] Table 5 Results of Clean Energy Consumption Indicators for Cities in the Region

[0187]

[0188] Among them, Lianyungang and Changzhou provided clean energy to the entire grid, while Wuxi, Suzhou, and Yancheng drew clean energy from the entire grid.

[0189] Table 6 shows the capacity margin of external clean energy corridors for each city in the region:

[0190] Table 6. Capacity Margin of External Clean Energy Corridors in Various Cities of the Region

[0191]

[0192]

[0193] Among them, the remaining margin of the channels is relatively high (>50%), with only Yancheng City (22%) and Suqian City (38%) having relatively low remaining margins.

[0194] Step 3: Calculate carbon emission assessment indicators to score regional nodes. The scoring results for each city in the region are shown in Table 7.

[0195] Table 7 Scoring Results for Each City in the Region

[0196] Serial Number area Production capacity Absorption capacity Dumping capacity External capabilities score 1 Nanjing 0.46 0.94 0.52 10.77 3.17 2 Wuxi City 0.55 11.59 11.64 4.41 7.05 3 Xuzhou 0.37 1.91 1.63 0.52 1.11 4 Changzhou 22.57 8.25 15.24 0.75 11.70 5 Suzhou 0.82 12.38 12.15 11.81 9.29 6 Nantong City 1.41 5.77 4.56 2.63 3.59 7 Lianyungang City 57.33 24.25 34.76 1.02 29.34 8 Huai'an City 3.12 5.03 2.06 9.24 4.86 9 Yancheng City 4.24 12.57 8.83 0.25 6.47 10 Yangzhou 3.61 4.29 0.70 12.26 5.21 11 Zhenjiang City 0.49 0.61 0.13 2.71 0.99 12 Taizhou City 0.87 6.14 5.59 15.13 6.93 13 Suqian City 4.17 6.26 2.20 28.51 10.28

[0197] The carbon emission assessment results for this region are as follows: data status is normal; power generation is concentrated in Lianyungang City; power consumption is balanced; and transmission losses are normal. Strategic recommendations are proposed for cities with the lowest capacity in each area: Xuzhou City is advised to increase its renewable energy output; Zhenjiang City is advised to increase its renewable energy absorption and consumption and to provide additional renewable energy storage facilities; and Yancheng City is advised to upgrade its external renewable energy channels.

[0198] Those skilled in the art should understand that this invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to this invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A carbon emission assessment method considering clean energy from outside the region, characterized in that, include: Step 1: Based on the network structure and operation data of power big data, adopt the carbon flow tracking algorithm with the node power ratio allocation principle, and consider transmission loss to calculate the carbon emission data of each node in each time period of the entire process of power generation, transmission and consumption. Step 2: Considering new energy sources and their types both within and outside the region, establish a carbon emission indicator assessment system encompassing four aspects: comprehensive production capacity, absorption capacity, storage capacity, and external access and absorption capacity. Step 3: Calculate carbon emission assessment indicators, score cities and prefectures within the region, and formulate strategies. In step 1, the calculation process for carbon emission data at each time point and stage of the entire process of power generation, transmission, and consumption is as follows: Step 1.1: Calculate the power consumption: Inspection time The objects of study are the nodes within the region. The formula for the node power relationship is obtained as follows: （1） In the formula: For the total power flowing in, For end load, For transmission losses, This represents the total outflow power. Power generation node Issuing meritorious service Consider nodes Using end load and transmission loss, based on the principle of node power proportional allocation, nodes... Use end load from generation node Obtain power ratio The calculation formula is: （2） Each element is represented by a matrix obtained through the flow power of the nodes. The calculation formula is: （3） In the formula: For nodes Flow to Node power, For nodes The inflow power, Starting from node The set of downstream tracking nodes; The nodes are obtained. Use end load from generation node Power absorbed for: （4） In the formula: , The first The, the A unit row vector with 1 element and 0 elements elsewhere; To examine the cross-section The downstream tracking matrix represents the relationships between nodes; Step 1.2: Calculate daily power generation: The observation period was changed from hours to days, and the observation targets were N nodes within various cities in the region. There are M thermal power nodes. Substitute them into equation (4) to calculate the power drawn by the electricity and obtain the daily electricity consumption: （5） In the formula: Numbered by hour; Number the user nodes in each city within the region, with a total of N nodes; Number the thermal power nodes, taking power source type into account. For example, there are M thermal power nodes. The carbon emissions from thermal power generation are converted into carbon emissions based on carbon emission equivalence factors and then aggregated across the entire generation-transmission-consumption process to calculate the carbon emissions per unit of power generated. : （6） （7） （8） In the formula: Q is the conversion factor, which takes a value of 0.2; In step 2, the specific process for establishing the carbon emission indicator assessment system is as follows: Step 2.1, Data Preparation; Step 2.2: Calculate the proportion of clean energy base and conduct a production capacity assessment; Step 2.3: Calculate the local consumption rate of clean energy, assess the nature of clean energy transfer, and evaluate the consumption capacity and storage capacity. Step 2.4: Calculate the absorption rate of clean energy outside the area and the capacity margin of the channel, and conduct an assessment of the external reception capacity; In step 2.3, the specific steps for assessing the absorption capacity and storage capacity are as follows: Taking a single prefecture-level city as the subject of study, the proportion of that city's clean energy consumption in the total value of clean energy consumption in the entire region: （18） Taking a single prefecture-level city as the subject of study, with clean energy generation as the positive direction and clean energy consumption and depletion as the negative directions, the absolute value of the sum of these factors represents the proportion of the total absolute value of the sum across the entire region: （19）。 2. The carbon emission assessment method considering clean energy from outside the region according to claim 1, characterized in that, In step 2.1, the data preparation specifically includes: Taking all cities and prefectures within the region as the subjects of study, and statistically analyzing the acquired data, assuming that the total power generation, transmission, and consumption within the region is constant, and that power outside the region has been incorporated into the respective cities and prefectures, then the total power generation of all cities and prefectures within the region equals the sum of the total power consumption and the total transmission losses, i.e.: （9） Similarly, regional carbon emissions are calculated as follows: total carbon emissions from power generation equal the sum of total carbon emissions from power consumption and total carbon emissions from power transmission, i.e.: （10）。 3. The carbon emission assessment method considering clean energy from outside the region according to claim 1, characterized in that, In step 2.2, the specific steps for production capacity assessment are as follows: Taking a single prefecture-level city as the subject of study, calculate the proportion of clean energy power generation in the region, and calculate the results of different clean energy power generation proportion indicators: （11） （12） Similarly, calculate the proportion of electricity consumption from clean energy sources. , The proportion of clean energy transmission , ; The proportion of clean energy types is calculated based on energy type to obtain the proportion of different clean energy types in the entire process of generation, transmission, and consumption, with wind power as an example: （13） （14） Similarly, calculate the power generation share of photovoltaic, hydropower, and nuclear power, and calculate the power transmission and consumption share of different clean energy types; Taking prefecture-level cities as the perspective, this study analyzes the proportion of various types of clean energy in each city, the proportion of clean energy generated within and outside the region, and so on, extending to all cities within the region. It also calculates the proportion of clean energy generated by each city in the total value of clean energy generated in the entire region. （15）。 4. The carbon emission assessment method considering clean energy from outside the region according to claim 1, characterized in that, In step 2.3, the local consumption rate of clean energy is calculated, and the nature of clean energy transfer is assessed. The specific steps are as follows: Taking a single prefecture-level city as the subject of study, the results of the regional clean energy consumption index for that city are calculated, divided into two levels: energy consumption and transfer, and clean energy consumption and transfer. The formula is as follows: （16） （17） Among them, when All local energy consumption is local. Local energy is shifting to other cities. Locally absorbs the total energy output of other cities; Local clean energy is completely consumed locally. Local clean energy is being transferred to other cities. The local area absorbs clean energy power from other cities.

5. The carbon emission assessment method considering clean energy from outside the region according to claim 3, characterized in that, Step 2.4 involves calculating the external clean energy absorption capacity and channel capacity margin, and conducting an external reception capacity assessment. The specific steps are as follows: Taking a single prefecture-level city as the subject of study, the specific degree of acceptance of external clean energy in that prefecture-level city is as follows: （20） The capacity margin of clean energy corridors outside the urban area of ​​this region is: （21） In the formula: For the capacity of the channel for clean energy from outside the district to City A, The remaining margin of clean energy channels outside city A; Taking a single prefecture-level city as the subject of study, the degree to which the city receives clean energy from outside the region is defined as the percentage of the total absolute value of clean energy received from outside the region, with the output of clean energy from outside the region as the positive direction and the consumption and loss of clean energy from outside the region as the negative direction. （22）。 6. The carbon emission assessment method considering clean energy from outside the region according to claim 5, characterized in that, In step 3, individual scores are given to each city, and the total score is calculated. And by combining quantitative data from the indicator system, an assessment and strategy recommendations are made for all cities in the region; The assessment specifically involves: performing a qualitative analysis of the data distribution, including concentrated generation on the power generation side, balanced generation on the power generation side, concentrated power consumption on the power consumption side, balanced power consumption on the power transmission side, power transmission side losses exceeding limits, and normal power transmission side losses; The strategy is specifically divided into four types based on production capacity, consumption capacity, transfer and storage capacity, and external reception capacity: recommending to increase the output of new energy, recommending to increase the absorption and consumption of new energy, recommending to increase the provision of new energy transfer and storage, and recommending to transform the external channels for new energy.

7. The carbon emission assessment method considering clean energy from outside the region according to claim 6, characterized in that, During the evaluation process, the qualitative conditions for concentration and balance are as follows: if the proportion of the examined cities in the overall region is greater than or equal to 40% in the region, the qualitative analysis result is considered concentrated; otherwise, it is considered balanced. The conditions for normal and excessive losses are as follows: if the transmission loss of the city under investigation is greater than the normal value of line loss, the qualitative analysis result is excessive; otherwise, it is normal. The data is categorized as either abnormal or normal based on its status. The criterion for abnormality is that the total error during the data preparation phase is greater than 5%.

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