Electricity consumption carbon footprint management method, device, computer equipment and storage medium

Abstract

The present application relates to a method, device, computer equipment, storage medium and computer program product for managing carbon footprint of electricity consumption. The method comprises: obtaining satellite images of the target area and calculating the quality of vegetation coverage; the satellite images of the target area are taken by geosynchronous satellites; the carbon benchmark of the target area is determined according to the quality of vegetation coverage; the carbon emissions of the electricity user are obtained based on the carbon benchmark, power plant parameters and the electricity consumption of the electricity user. The present method can determine the carbon benchmark of the target area by the quality of vegetation coverage, get rid of the influence of carbon benchmark calculation indicators, reduce errors and uncertainties, and has strong applicability. Combined with the electricity consumption of the electricity user, it helps to evaluate and monitor the carbon emissions of the electricity users in the target area, and can also provide a basis for energy planning and energy conservation and emission reduction.

Description

Technical Field

[0001] The present application relates to the field of carbon footprint technology, and in particular to a method, device, computer equipment, storage medium and computer program product for managing carbon footprint of electricity consumption. Background Art

[0002] At present, the increasing amount of greenhouse gases is gradually destroying the earth's environment, and the task of carbon peak and carbon neutrality is imminent. Vegetation, as a key tool for eliminating carbon dioxide, is the benchmark for measuring the carbon neutrality capabilities of various regions. However, carbon dioxide is mobile. When the carbon dioxide produced in one region cannot be completely neutralized by local vegetation, it will bring a carbon neutrality burden to vegetation in other regions and endanger the global ecological environment. Therefore, on the premise of accurately calculating the carbon footprint, fairness must also be considered, especially for the field of electricity consumption, which accounts for a large proportion of energy consumption. How to calculate the carbon footprint in an accurate and fair way is the key to solving this problem.

[0003] However, the current electricity consumption carbon footprint management method lacks consideration of factors such as different regions and different electricity sources, which leads to deviations in the carbon footprint calculation results. In addition, due to the lack of encryption and verification of carbon emissions, it is unfair and will also lead to a decline in the confidentiality and credibility of the calculation method. Summary of the invention

[0004] Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium and computer program product for managing the carbon footprint of electricity consumption in consideration of different regions and different electricity sources in order to address the above technical issues.

[0005] In a first aspect, the present application provides a method for managing carbon footprint of electricity consumption. The method comprises:

[0006] Obtain satellite images of the target area and measure the quality of vegetation cover; the satellite images of the target area are taken by geosynchronous satellites;

[0007] Determine carbon baselines for target areas based on vegetation cover quality;

[0008] The carbon emissions of electricity users are obtained based on the carbon benchmark, power plant parameters and electricity consumption of electricity users.

[0009] In one embodiment, a satellite image of a target area is obtained and the quality of vegetation coverage is measured; the satellite image of the target area is taken by a geosynchronous satellite, including:

[0010] Acquire remote sensing images of the target area; the remote sensing images of the target area are taken by geosynchronous satellites;

[0011] Based on the spectral characteristics of vegetation, remote sensing data of vegetation in remote sensing images is extracted, and the remote sensing data is corrected for geographical location;

[0012] The remote sensing data are projected onto the topographic map of the target area, a three-dimensional model of vegetation coverage in the target area is constructed, and the vegetation coverage quality is generated.

[0013] In one embodiment, remote sensing data is projected onto a topographic map of a target area, a vegetation coverage stereo model of the target area is constructed, and the vegetation coverage quality is generated including:

[0014] Extract the plain grids in the target area to obtain the plain area; the plain area is the vertical projection area read from the topographic map of the target area;

[0015] Extract the mountain grids of the target area to obtain the mountain longitude and latitude ratio; extract the basin grids of the target area to obtain the basin longitude and latitude ratio; the mountain longitude and latitude ratio is the ratio between the mountain longitude span and the latitude span; the basin longitude and latitude ratio is the ratio between the basin longitude span and the latitude span;

[0016] Generate a cone based on the longitude and latitude ratio of the mountain and the altitude of the mountain to obtain the lateral area of ​​the mountain; generate an inverted cone based on the longitude and latitude ratio of the basin and the altitude of the basin to obtain the lateral area of ​​the basin;

[0017] The vegetation flat coverage area is obtained according to the plain area, mountain side area and basin side area;

[0018] The vegetation coverage quality is generated based on the vegetation flat coverage area, average vegetation height and vegetation density.

[0019] In one embodiment, the mountain grid of the target area is extracted to obtain the mountain longitude and latitude ratio; the basin grid is extracted to obtain the basin longitude and latitude ratio; the mountain longitude and latitude ratio is the ratio between the mountain longitude span and the latitude span; the basin longitude and latitude ratio is the ratio between the basin longitude span and the latitude span, and further includes:

[0020] Determine whether the mountain longitude and latitude ratio and / or basin longitude and latitude ratio are within a preset range;

[0021] When the longitude-latitude ratio of the mountain and / or the longitude-latitude ratio of the basin are outside the preset range, the mountain and / or the basin are evenly divided until the longitude-latitude ratio of the mountain sub-mountain and / or the longitude-latitude ratio of the basin sub-basin after division are both within the preset range.

[0022] In one embodiment, determining a carbon baseline for a target area based on vegetation cover quality includes:

[0023] Based on the vegetation cover quality and CO2 absorption rate, the CO2 neutralization capacity of the target area is obtained;

[0024] Determine carbon benchmarks for target regions based on CO2 neutrality capabilities.

[0025] In one embodiment, the method further comprises:

[0026] Construct a blockchain, which includes the first blockchain layer, the second blockchain layer and the third blockchain layer; the first blockchain layer is composed of several geosynchronous satellites, which collect satellite images of the target area, measure the quality of vegetation coverage, and determine the carbon benchmark; the second blockchain layer is composed of several power plant servers in the target area to generate several power plant parameters in the target area; the third blockchain layer is composed of several smart meters, which upload the collected power consumption of electricity users and monitor the power plant servers.

[0027] In one embodiment, the method further comprises:

[0028] A supervision node is set in the first blockchain layer, and the operation rules of the first blockchain are set through the supervision node;

[0029] Broadcasting capability characteristic data in any geostationary satellite to the remaining geostationary satellites;

[0030] The capability characteristics of geosynchronous satellites are ranked, and the first geosynchronous satellite is used as the key node of the first blockchain layer, and the second geosynchronous satellite is used as the backup key node of the first blockchain layer;

[0031] When the critical node switching timing is reached, a switching message is sent to the geosynchronous satellite in the first blockchain layer;

[0032] After receiving the switching message, the backup key node is transformed into a new key node, and a switching confirmation message is fed back to the original key node and the supervisory node;

[0033] After receiving the switching confirmation message, the original key node function is turned off, and the next key node and backup key node are selected.

[0034] In a second aspect, the present application also provides a power consumption carbon footprint management device. The device comprises:

[0035] The vegetation processing module is used to obtain satellite images of the target area and measure the quality of vegetation coverage; the satellite images of the target area are taken by geosynchronous satellites;

[0036] The carbon benchmark module is used to determine the carbon benchmark for target areas based on the quality of vegetation cover;

[0037] The processing module is used for obtaining the carbon emission of the electricity user based on the carbon benchmark, the power plant parameters and the electricity consumption of the electricity user.

[0038] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0039] Obtain satellite images of the target area and measure the quality of vegetation cover; the satellite images of the target area are taken by geosynchronous satellites;

[0040] Determine carbon baselines for target areas based on vegetation cover quality;

[0041] The carbon emissions of electricity users are obtained based on the carbon benchmark, power plant parameters and electricity consumption of electricity users.

[0042] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0043] Obtain satellite images of the target area and measure the quality of vegetation cover; the satellite images of the target area are taken by geosynchronous satellites;

[0044] Determine carbon baselines for target areas based on vegetation cover quality;

[0045] The carbon emissions of electricity users are obtained based on the carbon benchmark, power plant parameters and electricity consumption of electricity users.

[0046] The above-mentioned electricity consumption carbon footprint management method, device, computer equipment, storage medium and computer program product can accurately capture the topography and vegetation coverage of the target area from a high-resolution perspective through the satellite images of the target area taken by the geosynchronous satellite, thereby improving the subsequent vegetation coverage quality measurement accuracy. The traditional coefficient method for calculating the carbon benchmark requires the calculation of the coefficient to be measured, and due to the complexity of factors such as regional terrain and vegetation, the carbon benchmark measurement accuracy of the target area is low. Determining the carbon benchmark of the target area through the vegetation coverage quality can get rid of the influence of the accuracy of the carbon benchmark coefficient, reduce errors and uncertainties, and make the carbon benchmark calculation results of the target area more accurate; and it has strong applicability to various regions and vegetation types, and can maintain a high measurement accuracy. Combined with the electricity consumption of the electricity users, it is helpful to evaluate and monitor the carbon emissions of the electricity users in the target area, and it can also provide a basis for energy planning and energy conservation and emission reduction. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A diagram of an application environment of a method for managing carbon footprint of electricity consumption in one embodiment;

[0048] Figure 2 A schematic diagram of a flow chart of a method for managing carbon footprint of electricity consumption in one embodiment;

[0049] Figure 3 This is a schematic diagram of the structure of the blockchain layer in one embodiment;

[0050] Figure 4 A schematic diagram of a flow chart of a method for managing carbon footprint of electricity consumption in another embodiment;

[0051] Figure 5 is a structural block diagram of a power consumption carbon footprint management device in one embodiment;

[0052] Figure 6 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0054] The power consumption carbon footprint management method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. Among them, the terminal 102 can be but is not limited to various personal computers, laptops, smart phones, tablets, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented with an independent server or a server cluster consisting of multiple servers.

[0055] In one embodiment, Figure 2 As shown, a method for managing carbon footprint of electricity consumption is provided, and the method is applied to Figure 1 The server in the example is used to illustrate the following steps:

[0056] Step 202, obtaining a satellite image of the target area and measuring the vegetation coverage quality; the satellite image of the target area is taken by a geosynchronous satellite.

[0057] Step 204, determining the carbon benchmark for the target area based on the vegetation cover quality.

[0058] Step 206, obtaining the carbon emissions of the electricity user based on the carbon benchmark, the power plant parameters and the electricity consumption of the electricity user.

[0059] Specifically, the satellite remote sensing images of the target area are taken by geosynchronous satellites, and the remote sensing data of green vegetation in the satellite remote sensing images of the target area are extracted according to the spectral characteristics of the vegetation. Among them, the spectral characteristics of the vegetation can be used to obtain information such as the coverage area and growth status of the vegetation. According to the vegetation coverage quality and the carbon dioxide absorption rate, the annual carbon dioxide neutralization capacity of the target area is calculated, and the carbon benchmark of the target area is further determined. According to the carbon benchmark of each target area and the carbon benchmark allocation method of the target area, the carbon quota of each power plant is determined. The specific expression is shown in formula (1):

[0060] Mi=B×(Qi / Qt) (1)

[0061] Where Mi is the carbon quota of the i-th power plant in the target area; B is the carbon benchmark of the target area; Qi is the power generation of the i-th power plant in the target area; and Qt is the total power generation of all power plants in the target area.

[0062] According to the carbon quota of each power plant, the carbon emission regional factor of the power plant is determined. The specific expression is shown in formula (2):

[0063] e=Mi / a (2)

[0064] Where e is the carbon emission regional factor of the power plant; a is the number of IoT meters connected to the power plant server; Mi is the carbon quota of the i-th power plant in the target area.

[0065] The power sources of power plants include thermal power, hydropower, wind power, nuclear power and photovoltaic power. Different power sources have different carbon emission technical factors. Therefore, it is necessary to confirm the emission technical factors of each power plant. The specific expression of the carbon emission technical factor is shown in formula (3):

[0066] f=w×y (3)

[0067] In the formula, f is the carbon emission technical factor; w represents the correlation coefficient between power consumption and carbon dioxide emissions; y represents the adjustment coefficient of thermal power, hydropower, wind power, nuclear power and photovoltaic power.

[0068] The electricity consumption of the electricity user can be collected through smart meters for the current year, and the carbon emissions of the electricity user can be calculated by combining the carbon emission technical factors. The specific expression is shown in formula (4):

[0069]

[0070] Where q is the electricity consumption of the electricity user in that year; f is the carbon emission technical factor; and e is the carbon emission regional factor.

[0071] In the above-mentioned electricity consumption carbon footprint management method, the satellite images of the target area taken by geosynchronous satellites can provide a high-resolution perspective, accurately capture the topography and vegetation coverage of the target area, and improve the accuracy of vegetation coverage quality measurement. Determining the carbon benchmark of the target area through vegetation coverage quality can get rid of the influence of carbon benchmark measurement indicators, reduce errors and uncertainties, and more accurately calculate the carbon benchmark of the target area; and it is suitable for various regions and vegetation types, with strong applicability. Combining the electricity consumption of the electricity user, carbon emission technical factors and carbon emission regional factors, the electricity consumption of each electricity user is combined with the power generation parameters of the power plant, which helps to evaluate and monitor the carbon emissions of the electricity users in the target area, and can also provide a basis for energy planning and energy conservation and emission reduction.

[0072] In one embodiment, a satellite image of a target area is obtained and the quality of vegetation coverage is calculated; the satellite image of the target area is taken by a geosynchronous satellite, including: obtaining a remote sensing image of the target area; the remote sensing image of the target area is taken by a geosynchronous satellite; based on the spectral characteristics of the vegetation, remote sensing data of the vegetation in the remote sensing image is extracted, and the remote sensing data is corrected for geographical location; the remote sensing data is projected onto a topographic map of the target area, a three-dimensional model of vegetation coverage of the target area is constructed, and the quality of vegetation coverage is generated.

[0073] Specifically, the satellite remote sensing images of the selected target area are taken by geosynchronous satellites, and the remote sensing data of green vegetation in the remote sensing images of the target area are extracted according to the spectral characteristics of green vegetation. Among them, the spectral characteristics of vegetation can be used to obtain information such as the coverage area and growth status of vegetation. Based on satellite global positioning technology, the remote sensing data is corrected for geographical location, and the remote sensing data of green vegetation is projected onto the topographic map of the target area to construct a three-dimensional model of vegetation coverage in the target area. The specific expression is shown in formula (5):

[0074] G=S×h×ρ (5)

[0075] Where S represents the flat coverage area of ​​green vegetation, that is, the plane area of ​​different landforms such as plains, mountains, and basins after being flattened; h represents the average height of green vegetation; ρ represents the density of green vegetation.

[0076] In this embodiment, satellite images of the target area taken by geosynchronous satellites are collected to provide a high-resolution perspective to accurately capture the topography and vegetation coverage of the target area; the geographical location of the remote sensing data is corrected to ensure that the vegetation coverage extracted from the remote sensing data matches the actual vegetation coverage, and then when the remote sensing data is projected onto the topographic map of the target area, an accurate three-dimensional model of vegetation coverage can be constructed, thereby improving the measurement accuracy of vegetation coverage quality and reducing errors and uncertainties.

[0077] In one embodiment, remote sensing data is projected onto a topographic map of a target area, a vegetation coverage stereo model of the target area is constructed, and the vegetation coverage quality is generated, including: extracting plain grids of the target area to obtain the plain area; the plain area is the vertical projection area read from the topographic map of the target area; extracting mountain grids of the target area to obtain the mountain longitude and latitude ratio; extracting basin grids of the target area to obtain the basin longitude and latitude ratio; the mountain longitude and latitude ratio is the ratio between the longitude span of the mountain and the latitude span; the basin longitude and latitude ratio is the ratio between the longitude span of the basin and the latitude span; generating a cone based on the mountain longitude and latitude ratio and the mountain altitude to obtain the mountain side area; generating an inverted cone based on the basin longitude and latitude ratio and the basin altitude to obtain the basin side area; obtaining the vegetation paving coverage area according to the plain area, the mountain side area and the basin side area; generating the vegetation coverage quality according to the vegetation paving coverage area, the average height of the vegetation and the density of the vegetation.

[0078] Specifically, the topographic map is divided into plains, mountains and basins according to the landform type, and the coverage quality of green vegetation is obtained through basic set shape simulation. The plain grid is extracted, and the tiled coverage area St of the green vegetation in the plain grid can be directly read from the topographic map.

[0079] Extract the mountain grid and calculate the ratio between the longitude span and latitude span of the mountain as the longitude and latitude ratio of the mountain. Take the smaller value of the longitude span and latitude span of the mountain as the diameter Ds as the base circle, take the altitude of the mountain as the height Hs as the cone, and calculate the lateral area of ​​the mountain cone. The specific expression is shown in formula (6):

[0080] Ss=π×Rs×Ls (6)

[0081] In the formula, Ss is the lateral area of ​​the mountain cone; Rs is the radius of the base circle of the mountain cone, Rs = Ds / 2; Ls is the generatrix of the mountain cone,

[0082] Extract the basin grid, calculate the ratio between the longitude span and latitude span of the basin, and use it as the latitude and longitude ratio of the basin. Take the smaller value of the longitude span and latitude span of the basin as the diameter Dp to make the bottom circle, take the altitude of the basin as the depth Hp to make the inverted cone of the basin, and calculate the lateral area Sp of the inverted cone of the basin. The specific expression is shown in formula (7):

[0083] Sp=π×Rp×Lp (7)

[0084] Where, Rp is the radius of the bottom circle of the basin inverted cone, Rp = Dp / 2; Lp is the generatrix of the basin inverted cone,

[0085] S is obtained by summing the paved coverage area St, the lateral area of ​​the mountain cone Ss, and the lateral area of ​​the basin inverted cone Sp. The specific expression is shown in formula (8):

[0086] S=St+Ss+Sp (8)

[0087] In this embodiment, by projecting remote sensing data onto a topographic map of the target area, the spatial characteristics of vegetation coverage can be better analyzed. The topographic map provides information on the terrain and landforms of the region, which is helpful for accurate regional division and parameter extraction. The target area is divided into plain grids, mountain grids, and basin grids, and independent calculations are performed based on the characteristic parameters of each grid, which facilitates detailed analysis and evaluation of the quality of vegetation coverage. By simulating mountains and basins through basic set shapes, the calculation method of vegetation coverage area under complex terrain is simplified, and the estimation accuracy of vegetation coverage area is guaranteed.

[0088] In one embodiment, the mountain grids of the target area are extracted to obtain the mountain longitude and latitude ratio; the basin grids are extracted to obtain the basin longitude and latitude ratio; the mountain longitude and latitude ratio is the ratio between the mountain longitude span and the latitude span; the basin longitude and latitude ratio is the ratio between the basin longitude span and the latitude span. The method also includes: judging whether the mountain longitude and latitude ratio and / or the basin longitude and latitude ratio are within a preset range; when the mountain longitude and latitude ratio and / or the basin longitude and latitude ratio are outside the preset range, evenly dividing the mountain and / or the basin until the mountain longitude and latitude ratios of the divided sub-mountains and / or the basin longitude and latitude ratios of the sub-basins are within the preset range.

[0089] Specifically, the obtained longitude and latitude ratio of the mountain is judged with the preset range. For example, the preset range of the longitude and latitude ratio of the mountain is 0.6 to 1.3. When the longitude and latitude ratio of the mountain is within the range of 0.6 to 1.3, the lateral area Ss of the mountain cone is directly calculated. When the longitude and latitude ratio of the mountain is outside the range of 0.6 to 1.3, the longitude and latitude ratio of the mountain exceeds the preset range, and the mountain is evenly divided until the longitude and latitude ratio of each divided sub-mountain is within the range of 0.6 to 1.3. The smaller value of the longitude span and latitude span of each sub-mountain is used as the diameter to make the base circle, and the sub-mountain altitude is used as the height to make the cone, and the lateral area of ​​each sub-mountain cone is calculated and summed.

[0090] The obtained basin longitude and latitude ratio is compared with the preset range. For example, the preset range of the basin longitude and latitude ratio is 0.6 to 1.3. When the basin longitude and latitude ratio is within the range of 0.6 to 1.3, the lateral area Ss of the basin inverted cone is directly calculated. When the basin longitude and latitude ratio is outside the range of 0.6 to 1.3, the basin longitude and latitude ratio exceeds the preset range, and the basin is evenly divided until the basin longitude and latitude ratio of each divided sub-basin is within the range of 0.6 to 1.3. The smaller value of the longitude span and latitude span of each sub-basin is used as the diameter to make the bottom circle, and the sub-basin's altitude is used as the height to make the inverted cone. The lateral area of ​​the inverted cone of each sub-basin is calculated and summed.

[0091] In this embodiment, by judging the latitude and longitude ratio of the mountain and basin and the preset range, the situation beyond the range can be discovered in time, and corresponding processing can be performed according to the judgment result. For the mountain and basin beyond the range, an average division operation can be performed to ensure that each sub-mountain and sub-basin meets the preset range of the latitude and longitude ratio. The continuity and accuracy of the calculation are guaranteed, and more accurate vegetation cover quality calculation results can be provided.

[0092] In one embodiment, determining the carbon baseline of the target area based on the vegetation cover quality includes: obtaining the carbon dioxide neutralization capacity of the target area based on the vegetation cover quality and the carbon dioxide absorption rate; and determining the carbon baseline of the target area according to the carbon dioxide neutralization capacity.

[0093] Specifically, based on the vegetation cover quality, the annual carbon dioxide neutralization capacity of the region is calculated, and the specific expression is shown in formula (9):

[0094] N=G×Q (9)

[0095] In the formula, N is the carbon dioxide neutralization capacity; G is the vegetation cover mass; Q is the carbon dioxide absorption rate, that is, the carbon dioxide absorption rate per unit cover mass per year, which can be obtained by experimental measurement and deduction of plant samples. For example, according to the data collected on site, it is measured that every 10,000 square meters of 20-meter-high broad-leaved forest can absorb 1,000 kilograms of carbon dioxide per day, so Q = (1000 × 365) / (10000 × 20) = 1.825.

[0096] Based on the carbon dioxide neutrality capacity, the carbon benchmark of the target area is determined. The specific expression is shown in formula (10):

[0097] B=N / C (10)

[0098] In the formula, B is the carbon benchmark of the target area; C represents the reward and punishment coefficient. The more the target area's carbon dioxide emissions in the previous year exceed its carbon dioxide neutralization capacity, the greater the reward and punishment coefficient, and vice versa; N is the carbon dioxide neutralization capacity.

[0099] In this embodiment, the theoretical carbon dioxide neutralization capacity of the target area can be estimated based on the vegetation coverage quality and the carbon dioxide absorption rate of the target area, which reduces the processing steps of the carbon dioxide neutralization capacity and avoids errors caused by coefficients. The theoretical carbon dioxide neutralization capacity of the target area is calculated as the standard for subsequent calculations, and a reward and punishment mechanism is introduced to impose a base penalty on areas with excessive carbon dioxide emissions and a base reward on areas with carbon dioxide neutralization exceeding expectations, which helps to motivate various regions to take active emission reduction measures.

[0100] In one embodiment, the electricity consumption carbon footprint management method also includes: constructing a blockchain, the blockchain includes a first blockchain layer, a second blockchain layer and a third blockchain layer; the first blockchain layer is composed of a number of geosynchronous satellites, collecting satellite images of the target area, measuring the vegetation coverage quality, and determining the carbon benchmark; the second blockchain layer is composed of a number of power plant servers in the target area to generate a number of power plant parameters in the target area; the third blockchain layer is composed of a number of smart meters, uploading the collected electricity consumption of electricity users, and monitoring the power plant servers.

[0101] Specifically, combined Figure 3 As shown, Figure 3 The diagram is a schematic diagram of the structure of the blockchain layer. Three blockchain layers are constructed according to different servers. The first blockchain layer consists of several geosynchronous satellites. Satellite images of the target area are collected through geosynchronous satellites. According to the spectral characteristics of vegetation, remote sensing data of vegetation in satellite images are extracted, and the remote sensing data is corrected for geographical location. The remote sensing data is projected onto the topographic map of the target area, and a three-dimensional model of vegetation coverage in the target area is constructed to generate vegetation coverage quality. Satellite images, remote sensing data, topographic maps, vegetation coverage quality and carbon benchmark data are recorded in the first blockchain layer through blockchain technology, and the security and non-tamperability of the data are ensured. The second blockchain layer consists of several power plant servers in the target area. The power plant server equipment is used to generate and record various parameters of the power plant, such as power generation, power generation efficiency, fuel consumption, etc., and the data is recorded in the second blockchain layer through blockchain technology. The third blockchain layer consists of several smart meters. Optionally, the smart meters can be IoT meters. IoT meters are installed in the target area. The power consumption of the power user unit in the year is collected through the IoT meters, and the collected power consumption of the power user unit is uploaded, and the power plant server is monitored, including power grid stability, energy supply capacity, etc.

[0102] In this embodiment, by constructing a three-layer blockchain structure consisting of a geosynchronous satellite, a power plant server, and an IoT meter, the vegetation area can be used as a carbon benchmark to calculate the carbon emission regional factor, the impact of different power generation sources on the carbon emission calculation can be taken into account, and the carbon emission calculation results can be stored in the blockchain for encrypted preservation. Recording data such as satellite images, remote sensing data, and power plant parameters in the blockchain can provide a traceable and auditable process to ensure the authenticity and transparency of the data. This is beneficial for ensuring accurate assessment of vegetation coverage quality, the credibility of power plant parameters, and monitoring of power consumption of power users. By collecting power consumption of power users through IoT meters and monitoring the grid stability and energy supply capacity of power plant servers in real time, better management and optimization of energy can be achieved. This can help power plants understand real-time power demand, optimize power generation plans and operations, improve energy efficiency, and reduce energy waste.

[0103] In one embodiment, the power consumption carbon footprint management method also includes: setting a supervision node in the first blockchain layer, and setting the first blockchain operation rules through the supervision node; broadcasting the capability characteristic data in any geosynchronous satellite to the remaining geosynchronous satellites; sorting the capability characteristics of the geosynchronous satellites, and using the geosynchronous satellite in the first position as the key node of the first blockchain layer, and using the geosynchronous satellite in the second position as the backup key node of the first blockchain layer; when the key node switching timing is reached, sending a switching message to the geosynchronous satellite in the first blockchain layer; after receiving the switching message, converting the backup key node into a new key node, and at the same time feeding back the switching confirmation message to the original key node and the supervision node; after receiving the switching confirmation message, shutting down the original key node function, and screening the next key node and backup key node.

[0104] Specifically, regulatory nodes are set for the first blockchain layer, the second blockchain layer, and the third blockchain layer, which are the first regulatory node, the second regulatory node, and the third regulatory node, respectively. The regulatory nodes in each blockchain layer set operating rules for each blockchain layer.

[0105] The operation rules of the first blockchain layer include maintaining laser communication connectivity between two geosynchronous satellites through heartbeat messages, and each geosynchronous satellite broadcasts its first capability characteristic data to other geosynchronous satellites through capability messages. The first supervisory node ranks the geosynchronous satellites according to their first capability characteristics, and takes the geosynchronous satellite in the first position as the key node of the first blockchain layer. The key node periodically broadcasts announcement messages to other geosynchronous satellites to unify the storage data of each geosynchronous satellite. The first supervisory node takes the geosynchronous satellite in the second position of the first capability characteristic ranking as the backup key node of the first blockchain layer, broadcasts the backup key node information to other geosynchronous satellites, and the backup key node sets its own status to the alternative status. When the switching time of the key node is reached, the first supervisory node sends a switching message to all geosynchronous satellites in the first blockchain layer. After receiving the switching message, the backup key node is transformed into a new key node, and at the same time, the switching confirmation message is fed back to the original key node and the first supervisory node; the original key node closes the key node function after receiving the switching confirmation message; after receiving the switching confirmation message, the first supervisory node selects the next key node and the backup key node from the current first capability characteristic ranking.

[0106] The operating rules of the first blockchain layer also include that when the backup key node cannot receive the declaration message of the key node within a preset time, the backup key node sends an alarm message to the first supervision node; after the first supervision node receives the alarm message, it sends a switching message to all geosynchronous satellites of the first blockchain layer; after receiving the switching message, the backup key node is transformed into a new key node, and at the same time, a switching confirmation message is fed back to the original key node and the first supervision node; after receiving the switching confirmation message, the first supervision node selects the next key node and the backup key node from the current first capability feature ranking.

[0107] The operation rules of the second blockchain layer include several power plant servers in each target area, several geosynchronous satellites covering the area, and the second supervisory node as regional elements to form each target area set. In each regional set, wireless communication is maintained between two regional elements through heartbeat messages. The geosynchronous satellites in each regional set broadcast their second capability feature data to other geosynchronous satellites in the regional set through capability messages. The second supervisory node sorts the geosynchronous satellites according to their second capability features, and takes the geosynchronous satellite in the first place as the key node of the regional set. The key node periodically broadcasts announcement messages to other elements in the regional set to unify the storage data of each element. The second supervisory node takes the geosynchronous satellite in the second position of the second capability feature sorting as the backup key node of the regional set, broadcasts the backup key node information to other elements in the region, and the backup key node sets its own status to the alternative status. When the switching time of the key node is reached, the second supervision node sends a switching message to all elements of the region set. After receiving the switching message, the backup key node is transformed into a new key node, and at the same time, a switching confirmation message is fed back to the original key node and the second supervision node; the original key node turns off the key node function after receiving the switching confirmation message; after receiving the switching confirmation message, the second supervision node selects the next key node and backup key node from the current second capability feature ranking.

[0108] The operating rules of the second blockchain layer also include that when the backup key node cannot receive the declaration message of the key node within the preset time, the backup key node sends an alarm message to the second supervision node; the second supervision node sends a switching message to all elements of the region set; after receiving the switching message, the backup key node is transformed into a new key node, and at the same time, a switching confirmation message is fed back to the original key node and the second supervision node; after receiving the switching confirmation message, the second supervision node selects the next key node and the backup key node from the current second capability feature ranking.

[0109] Optionally, the first capability characteristic data and the second capability characteristic data include observed load performance, processor performance, storage space capacity, battery power, etc.

[0110] The operation rules of the third blockchain include each power plant server and its IoT meter and the third supervisory node as elements to form each power plant set. In each power plant set, wireless communication is maintained between two power plant elements through heartbeat messages. As a key node, the power plant server periodically broadcasts announcement messages to other elements in the power plant set to unify the storage data of each element; the third supervisory node periodically backs up the storage data and monitors the operation of the power plant server.

[0111] When the third supervision node cannot receive the declaration message from the power plant within the preset time, it immediately sends a switching message to all elements in the power plant set to enable the power plant backup server. After receiving the switching message, the power plant backup server acts as a new key node and periodically broadcasts declaration messages to other elements in the power plant set.

[0112] In this embodiment, the heartbeat message between nodes is used to ensure the communication connectivity between nodes, prevent communication interruption and data transmission failure, help maintain the stability of the node network, and ensure that carbon footprint data can be communicated and shared in a timely manner. The supervisory node sorts the capability feature data of each node, which can better understand and evaluate the capabilities and characteristics of each node, find and select the most suitable key nodes and backup key nodes, and optimize data management and processing efficiency. The key nodes in the blockchain are rotated to prevent the key nodes from being locked by the outside world and attacked and tampered, thereby effectively improving the data security of the blockchain and improving the security, flexibility and applicability of the nodes in the blockchain. When the key node fails or is attacked, the backup key node does not receive the announcement message of the key node within the preset time, and sends an alarm message to the supervisory node, which can timely discover the failure or unavailable state of the key node and trigger the switching process. The backup key node is quickly transformed into a new key node to ensure the continuity and stability of the system, reduce the impact of the failure or unavailable state of the key node on the entire system, and restore the data management and control functions in time. When abnormal situations such as network attacks and system failures occur at the key node, the backup key node can be immediately enabled to ensure the normal operation of the blockchain.

[0113] In one embodiment, Figure 4 As shown, Figure 4 A flow chart of a method for managing carbon footprint of electricity consumption.

[0114] Step 402, constructing a blockchain, the blockchain includes a first blockchain layer, a second blockchain layer and a third blockchain layer; the first blockchain layer is composed of a number of geosynchronous satellites, which collect satellite images of the target area, measure the vegetation coverage quality, and determine the carbon benchmark; the second blockchain layer is composed of a number of power plant servers in the target area to generate a number of power plant parameters in the target area; the third blockchain layer is composed of a number of smart meters, which upload the collected power consumption of the power users and monitor the power plant servers.

[0115] Step 404: Setting a supervision node in the first blockchain layer, and setting the first blockchain operation rules through the supervision node.

[0116] Step 406, broadcast the capability characteristic data in any geosynchronous satellite to the remaining geosynchronous satellites.

[0117] Step 408, sort the capability characteristics of the geosynchronous satellites, use the geosynchronous satellite ranked first as the key node of the first blockchain layer, and use the geosynchronous satellite ranked second as the backup key node of the first blockchain layer.

[0118] Step 410, when the critical node switching timing is reached, a switching message is sent to the geosynchronous satellite in the first blockchain layer.

[0119] Step 412: after receiving the switching message, the backup key node is converted into a new key node, and a switching confirmation message is fed back to the original key node and the supervisory node.

[0120] Step 414: After receiving the switching confirmation message, the original key node function is disabled, and the next key node and backup key node are selected.

[0121] Step 416, acquiring a remote sensing image of the target area; the remote sensing image of the target area is taken by a geosynchronous satellite.

[0122] Step 418, extracting remote sensing data of vegetation in the remote sensing image based on the spectral characteristics of vegetation, and performing geographic location correction on the remote sensing data.

[0123] Step 420, extract the plain grids of the target area to obtain the plain area; the plain area is the vertical projection area read from the topographic map of the target area.

[0124] Step 422, extract the mountain grid of the target area to obtain the mountain longitude and latitude ratio; extract the basin grid of the target area to obtain the basin longitude and latitude ratio; the mountain longitude and latitude ratio is the ratio between the mountain longitude span and the latitude span; the basin longitude and latitude ratio is the ratio between the basin longitude span and the latitude span.

[0125] Step 424, generate a cone based on the longitude and latitude ratio of the mountain and the altitude of the mountain to obtain the lateral area of ​​the mountain; generate an inverted cone based on the longitude and latitude ratio of the basin and the altitude of the basin to obtain the lateral area of ​​the basin.

[0126] Step 426, obtaining the vegetation flat coverage area according to the plain area, the mountain side area and the basin side area.

[0127] Step 428, generating vegetation coverage quality according to the vegetation tile coverage area, the average height of vegetation and the density of vegetation.

[0128] Step 430, determining whether the mountain longitude and latitude ratio and / or the basin longitude and latitude ratio are within a preset range.

[0129] Step 432, when the longitude-latitude ratio of the mountain and / or the longitude-latitude ratio of the basin are outside the preset range, the mountain and / or the basin are evenly divided until the longitude-latitude ratio of the mountain sub-mountain and / or the longitude-latitude ratio of the basin sub-basin after division are both within the preset range.

[0130] Step 434, based on the vegetation cover quality and the carbon dioxide absorption rate, the carbon dioxide neutralization capacity of the target area is obtained.

[0131] Step 436, determining the carbon benchmark of the target area based on the carbon dioxide neutrality capacity.

[0132] Step 438, obtaining the carbon emissions of the electricity user based on the carbon benchmark, the power plant parameters and the electricity consumption of the electricity user.

[0133] In this embodiment, the satellite image of the target area taken by the geosynchronous satellite can provide a high-resolution perspective, accurately capture the topography and vegetation coverage of the target area, and project the remote sensing data onto the topographic map of the target area, so as to better analyze the spatial characteristics of vegetation coverage. The topographic map provides the topographic and geomorphic information of the region, which is helpful for accurate regional division and parameter extraction. By simulating mountains and basins by basic set shapes, the calculation method of vegetation coverage area under complex terrain is simplified, and the estimation accuracy of vegetation coverage area is guaranteed. By determining the carbon benchmark of the target area by the quality of vegetation coverage, the influence of carbon benchmark measurement indicators can be eliminated, errors and uncertainties can be reduced, and the carbon benchmark of the target area can be calculated more accurately; and it is applicable to various regions and vegetation types, and has strong applicability. Combined with the power consumption of the power unit, it is helpful to evaluate and monitor the carbon emissions of the power unit in the target area, and it can also provide a basis for energy planning and energy conservation and emission reduction. By building a multi-layer blockchain, the security and uniformity of carbon emission data are guaranteed, and the carbon emission data can be effectively prevented from being tampered with.

[0134] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are shown in sequence, these steps are not necessarily executed in sequence in the order indicated. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the steps or stages in other steps.

[0135] Based on the same inventive concept, the embodiment of the present application also provides an electricity consumption carbon footprint management device for implementing the electricity consumption carbon footprint management method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more embodiments of the electricity consumption carbon footprint management device provided below can refer to the limitations of the electricity consumption carbon footprint management method above, and will not be repeated here.

[0136] In one embodiment, Figure 5 As shown, a power consumption carbon footprint management device is provided, including: a vegetation processing module 502, a carbon reference module 504 and a processing module 506, wherein:

[0137] The vegetation processing module 502 is used to obtain satellite images of the target area and measure the vegetation coverage quality; the satellite images of the target area are taken by geosynchronous satellites.

[0138] The carbon benchmark module 504 is used to determine the carbon benchmark of the target area based on the vegetation cover quality.

[0139] The processing module 506 is used to obtain the carbon emissions of the electricity user based on the carbon benchmark, the power plant parameters and the electricity consumption of the electricity user.

[0140] In one embodiment, the vegetation processing module 502 further includes:

[0141] The image acquisition module is used to obtain remote sensing images of the target area; the remote sensing images of the target area are taken by geosynchronous satellites.

[0142] The data extraction module is used to extract the remote sensing data of vegetation in the remote sensing image based on the spectral characteristics of the vegetation, and to perform geographic location correction on the remote sensing data.

[0143] The coverage quality processing module is used to project the remote sensing data onto the topographic map of the target area, construct a three-dimensional model of vegetation coverage in the target area, and generate the vegetation coverage quality.

[0144] In one embodiment, the coverage quality processing module further includes:

[0145] The projection module is used to extract the plain grids of the target area and obtain the plain area; the plain area is the vertical projection area read from the topographic map of the target area.

[0146] The longitude and latitude ratio module is used to extract the mountain grids of the target area to obtain the mountain longitude and latitude ratio; extract the basin grids of the target area to obtain the basin longitude and latitude ratio; the mountain longitude and latitude ratio is the ratio between the mountain longitude span and the latitude span; the basin longitude and latitude ratio is the ratio between the basin longitude span and the latitude span.

[0147] The lateral area processing module is used to generate a cone based on the longitude and latitude ratio of the mountain and the altitude of the mountain to obtain the lateral area of ​​the mountain; and to generate an inverted cone based on the longitude and latitude ratio of the basin and the altitude of the basin to obtain the lateral area of ​​the basin.

[0148] The tiled area module is used to obtain the vegetation tiled coverage area based on the plain area, mountain side area and basin side area.

[0149] The quality module is used to generate vegetation cover quality based on vegetation tile coverage area, vegetation average height and vegetation density.

[0150] In one embodiment, the latitude and longitude ratio module further includes:

[0151] The judgment module is used to judge whether the mountain longitude and latitude ratio and / or the basin longitude and latitude ratio are within a preset range.

[0152] The segmentation module is used to evenly segment the mountain and / or basin when the longitude and latitude ratio of the mountain and / or the longitude and latitude ratio of the basin are outside the preset range, until the longitude and latitude ratio of the mountain sub-mountain and / or the longitude and latitude ratio of the basin sub-basin after segmentation are both within the preset range.

[0153] In one embodiment, the carbon benchmark module 504 further includes:

[0154] The carbon neutrality module is used to obtain the carbon dioxide neutrality capacity of the target area based on the vegetation cover quality and carbon dioxide absorption rate.

[0155] Benchmark processing module for determining carbon benchmarks for target regions based on their CO2 neutrality capabilities.

[0156] In one embodiment, the apparatus further comprises:

[0157] A building module is used to build a blockchain, and the blockchain includes a first blockchain layer, a second blockchain layer and a third blockchain layer; the first blockchain layer is composed of several geosynchronous satellites, which collect satellite images of the target area, measure the vegetation coverage quality, and determine the carbon benchmark; the second blockchain layer is composed of several power plant servers in the target area to generate several power plant parameters in the target area; the third blockchain layer is composed of several smart meters, which upload the collected power consumption of electricity users and monitor the power plant servers.

[0158] In one embodiment, the building block further comprises:

[0159] The supervision module is used to set up a supervision node in the first blockchain layer and set the first blockchain operation rules through the supervision node.

[0160] The broadcast module is used to broadcast the capability characteristic data of any geosynchronous satellite to the other geosynchronous satellites.

[0161] The sorting module is used to sort the capability characteristics of geosynchronous satellites, and the geosynchronous satellite in the first position is used as the key node of the first blockchain layer, and the geosynchronous satellite in the second position is used as the backup key node of the first blockchain layer.

[0162] The switching module is used to send a switching message to the geosynchronous satellite in the first blockchain layer when the key node switching timing is reached.

[0163] The feedback module is used to transform the backup key node into a new key node after receiving the switching message, and at the same time feed back the switching confirmation message to the original key node and the supervision node.

[0164] The update module closes the original key node function after receiving the switching confirmation message, and selects the next key node and backup key node.

[0165] Each module in the above-mentioned power consumption carbon footprint management device can be implemented in whole or in part by software, hardware and their combination. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0166] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 6As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for managing the carbon footprint of power consumption is implemented.

[0167] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0168] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0169] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0170] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0171] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0172] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0173] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0174] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the present application. It should be noted that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for managing carbon footprint of electricity consumption, characterized in that: The method comprises: Obtaining satellite images of a target area and measuring the quality of vegetation coverage; the satellite images of the target area are taken by a geosynchronous satellite; including: Acquiring a remote sensing image of the target area; the remote sensing image of the target area is taken by a geosynchronous satellite; Extracting remote sensing data of vegetation in the remote sensing image based on spectral characteristics of vegetation, and performing geographic location correction on the remote sensing data; The remote sensing data is projected onto a topographic map of a target area, a vegetation coverage stereo model of the target area is constructed, and a vegetation coverage quality is generated; including: extracting the plain grid of the target area to obtain the plain area; the plain area is the vertical projection area read from the topographic map of the target area; extracting the mountain grid of the target area to obtain the mountain longitude and latitude ratio; extracting the basin grid of the target area to obtain the basin longitude and latitude ratio; the mountain longitude and latitude ratio is the ratio between the longitude span of the mountain and the latitude span; the basin longitude and latitude ratio is the ratio between the longitude span of the basin and the latitude span; generating a cone based on the mountain longitude and latitude ratio and the mountain altitude to obtain the mountain side area; generating an inverted cone based on the basin longitude and latitude ratio and the basin altitude to obtain the basin side area; obtaining the vegetation paving coverage area according to the plain area, the mountain side area and the basin side area; generating the vegetation coverage quality according to the vegetation paving coverage area, the average height of vegetation and the density of vegetation; Determining a carbon baseline for the target area based on the quality of the vegetation cover; The carbon emissions of the electricity user are obtained based on the carbon benchmark, the power plant parameters and the electricity consumption of the electricity user.

2. The method according to claim 1, characterized in that The mountain grid of the target area is extracted to obtain the mountain longitude and latitude ratio; the basin grid is extracted to obtain the basin longitude and latitude ratio; the mountain longitude and latitude ratio is the ratio between the longitude span and the latitude span of the mountain; The basin longitude and latitude ratio is the ratio between the longitude span and the latitude span of the basin and also includes: Determine whether the mountain longitude and latitude ratio and / or basin longitude and latitude ratio are within a preset range; When the longitude-latitude ratio of the mountain and / or the longitude-latitude ratio of the basin are outside the preset range, the mountain and / or the basin are evenly divided until the longitude-latitude ratio of the mountain sub-mountain and / or the longitude-latitude ratio of the basin sub-basin after division are both within the preset range.

3. The method according to claim 1, characterized in that Determining the carbon benchmark of the target area based on the vegetation cover quality includes: Based on the vegetation cover quality and the carbon dioxide absorption rate, the carbon dioxide neutralization capacity of the target area is obtained; A carbon baseline for the target region is determined based on the stated CO2 neutrality capacity.

4. The method according to claim 1, characterized in that: The method further comprises: Construct a blockchain, the blockchain comprising a first blockchain layer, a second blockchain layer and a third blockchain layer; the first blockchain layer is composed of a number of geosynchronous satellites, which collect satellite images of the target area, measure the vegetation coverage quality, and determine the carbon benchmark; the second blockchain layer is composed of a number of power plant servers in the target area to generate a number of power plant parameters in the target area; the third blockchain layer is composed of a number of smart meters, which upload the collected power consumption of power users and monitor the power plant servers.

5. The method according to claim 4, characterized in that The method further comprises: Setting a supervision node in the first blockchain layer, and setting the first blockchain operation rules through the supervision node; Broadcasting capability characteristic data in any geostationary satellite to the remaining geostationary satellites; The capability characteristics of the geosynchronous satellites are ranked, and the geosynchronous satellite ranked first is used as the key node of the first blockchain layer, and the geosynchronous satellite ranked second is used as the backup key node of the first blockchain layer; When the key node switching timing is reached, sending a switching message to the geosynchronous satellite in the first blockchain layer; After receiving the switching message, the backup key node is transformed into a new key node, and a switching confirmation message is fed back to the original key node and the supervisory node; After receiving the switching confirmation message, the original key node function is turned off, and the next key node and backup key node are selected.

6. A power consumption carbon footprint management device, characterized in that: The device comprises: The vegetation processing module is used to obtain satellite images of the target area and measure the vegetation coverage quality; the satellite images of the target area are taken by geosynchronous satellites; including: obtaining remote sensing images of the target area; the remote sensing images of the target area are taken by geosynchronous satellites; based on the spectral characteristics of vegetation, extracting remote sensing data of vegetation in the remote sensing images, and performing geographic location correction on the remote sensing data; projecting the remote sensing data onto a topographic map of the target area, constructing a three-dimensional model of vegetation coverage in the target area, and generating the vegetation coverage quality; including: extracting plain squares of the target area to obtain the plain area; the plain area is the vertical projection read from the topographic map of the target area. The shadow area is obtained by extracting the mountain grid of the target area to obtain the mountain longitude and latitude ratio; extracting the basin grid of the target area to obtain the basin longitude and latitude ratio; the mountain longitude and latitude ratio is the ratio between the longitude span of the mountain and the latitude span; the basin longitude and latitude ratio is the ratio between the longitude span of the basin and the latitude span; a cone is generated based on the mountain longitude and latitude ratio and the mountain altitude to obtain the mountain side area; an inverted cone is generated based on the basin longitude and latitude ratio and the basin altitude to obtain the basin side area; a vegetation paving coverage area is obtained according to the plain area, the mountain side area and the basin side area; a vegetation coverage quality is generated according to the vegetation paving coverage area, the average height of vegetation and the density of vegetation; A carbon benchmark module, for determining a carbon benchmark for a target area based on the vegetation cover quality; The processing module is used to obtain the carbon emissions of the electricity user based on the carbon benchmark, power plant parameters and electricity consumption of the electricity user.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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