Method, device, equipment and medium for measuring and calculating carbon emission under carbon reduction path in power industry

Abstract

The invention provides a method, a device, equipment and a medium for measuring and calculating carbon emission under a carbon reduction path in the power industry. The method comprises the following steps: acquiring carbon emission data of a power generation side, a power grid side and an energy storage side of a target area and power data of the power generation side, a load side and the energy storage side; calculating carbon emission influence factors of the power generation side, the power grid side, the load side and the energy storage side according to the carbon emission data of the power generation side, the power grid side and the energy storage side and the power data of the power generation side, the load side and the energy storage side; determining a comprehensive weight coefficient of each carbon emission influence factor based on a subjective and objective comprehensive method; and determining the carbon emission of the target region under the carbon reduction path based on the comprehensive weight coefficient and the carbon emission influence factor. According to the invention, when the carbon emission of the target region is measured and calculated, the optimization target is more comprehensive, and the calculation accuracy can be improved.

Description

Technical Field

[0001] The present invention relates to the field of carbon emission monitoring technology, and in particular to a method, device, equipment and medium for measuring carbon emissions under a carbon reduction pathway in the power industry. Background Art

[0002] At present, there have been a lot of studies on the measurement of carbon emissions. For example, Wang Lijuan et al. used a scenario analysis-based method to predict the trend of carbon emissions in my country's power industry and identify the main driving factors of carbon emission reduction. Liu Hongqin et al. proposed a scope and method for calculating carbon emissions from electricity, but the carbon emissions from electricity in the study only considered the carbon emissions of thermal power generation. Wang Zhonghua et al. used a three-stage data envelopment analysis (DEA) model to measure the carbon emission efficiency of the regional power industry. Kang Chongqing et al. proposed a new carbon emission flow (CEF) analysis model to quantify the carbon emissions generated by electricity from the power generation side to the demand side. Li Baowei et al. proposed a carbon flow tracking method that tracks the power consumption energy of the entire power grid to determine the carbon emissions of electricity consumption. In terms of carbon reduction measures in the power industry, Li Zheng et al. studied the low-carbon transformation path of the power industry under carbon constraints based on the joint optimization model of long-term planning and short-term operation of the power industry based on power balance. Chen Jingdong et al. used a double difference model to quantify the role of carbon trading policies in carbon emission reduction in the power industry. Dai Pan and others analyzed and evaluated the application and development of various emission reduction measures from the power generation side, demand side, and grid side, and proposed a comprehensive optimization model for carbon emission reduction in the power industry. Huang Yuhan and others proposed the existing challenges of the new power system with new energy as the main body, and reviewed the key technologies for carbon emission reduction in the new power system. Kang Chongqing and others proposed a research framework and low-carbon solution for the "carbon perspective" of the new power system. Shu Yinbiao and others proposed suggestions for the low-carbon transformation of electricity from the aspects of policy, technology, and mechanism coordination.

[0003] However, existing research mainly focuses on the industrial, construction, transportation, and agricultural and rural areas, while there are few studies on the measurement of carbon emissions in the comprehensive power industry. In addition, existing research is relatively single in terms of optimization objectives, mainly focusing on the internal factors of carbon emissions, while insufficient consideration is given to the measurement of carbon emissions. Summary of the invention

[0004] The embodiments of the present invention provide a method, device, equipment and medium for calculating carbon emissions under the carbon reduction path of the power industry to solve the problems of lack of research on carbon emissions calculation in the comprehensive power industry and insufficient consideration of carbon emissions calculation at this stage.

[0005] In a first aspect, an embodiment of the present invention provides a method for calculating carbon emissions under a carbon reduction path in the power industry, including:

[0006] Obtain carbon emission data on the power generation side, grid side and energy storage side of the target area, as well as power data on the power generation side, load side and energy storage side;

[0007] Calculate the carbon emission influencing factors of the power generation side, power grid side, load side and energy storage side based on the carbon emission data of the power generation side, power grid side and energy storage side and the power data of the power generation side, load side and energy storage side;

[0008] Determine the comprehensive weight coefficient of each carbon emission influencing factor based on the subjective and objective comprehensive method;

[0009] Based on the comprehensive weight coefficient and various carbon emission influencing factors, the carbon emissions of the target area under the carbon reduction path are determined.

[0010] In some possible implementations, the carbon emission data on the power generation side includes the carbon emissions of coal-fired power units and the carbon emissions of new energy equipment built in the target area;

[0011] The power data on the power generation side includes the power transferred to the target area, the power generation of non-fossil energy, the power generation of various types of power sources, line losses and the power transferred out;

[0012] Based on the carbon emission data and electricity data on the power generation side, the factors affecting the carbon emissions on the power generation side are calculated as follows:

[0013] Based on the carbon emissions of coal-fired power units, calculate the carbon emissions reduction from the withdrawal of coal-fired units or the conversion of coal to gas;

[0014] Based on the amount of electricity transferred to the target area, calculate the carbon emissions after increasing the proportion of green electricity in the net amount of electricity transferred;

[0015] Based on the non-fossil energy power generation, calculate the carbon emissions after increasing the non-fossil energy power generation of local power sources in the target area;

[0016] Based on the power generation of each type of power source, the carbon emissions of local power sources in the target area are calculated; based on the line loss, the carbon emissions caused by line losses when power is transferred in are calculated; based on the power transferred out, the indirect carbon emissions contained in power transfer out of the target area are calculated; based on the carbon emissions of local power sources, the carbon emissions caused by line losses when power is transferred in, the indirect carbon emissions contained in power transfer out and the carbon emissions when new new energy equipment is built in the target area, the carbon reduction on the power generation side is calculated.

[0017] In some possible implementations, the carbon emission data on the grid side includes the amount of carbon emissions generated per unit of energy during the combustion or use of each energy source;

[0018] According to the carbon emission data on the grid side, the factors affecting the carbon emission on the grid side are calculated as follows:

[0019] The carbon emissions on the grid side are calculated based on the amount of carbon emissions per unit of energy generated during the combustion or use of each energy source.

[0020] In some possible implementations, the load-side power data includes the consumed power on the load side;

[0021] Based on the power data on the load side, the factors affecting the energy saving on the load side are calculated as follows:

[0022] Calculate the energy savings on the load side based on the consumed electrical energy.

[0023] In some possible implementations, the carbon emission data on the energy storage side includes the original carbon emission on the energy storage side;

[0024] The power data on the energy storage side includes the charging and discharging efficiency of the energy storage equipment;

[0025] Based on the electricity data on the energy storage side, the factors affecting the carbon emissions on the energy storage side include:

[0026] Calculate the emission reduction after intelligent peak regulation on the energy storage side based on the original carbon emissions on the energy storage side;

[0027] Based on the charging and discharging efficiency, calculate the reduced power loss on the energy storage side.

[0028] In some possible implementations, the comprehensive weight coefficient of each carbon emission influencing factor is determined based on a subjective and objective comprehensive method, including:

[0029] Adopting objective weighting method, the original data matrix is ​​determined according to each carbon emission influencing factor;

[0030] According to the original data matrix, the objective weight index of each carbon emission influencing factor is obtained; wherein the objective weight index includes the standardized matrix, mean, standard deviation, coefficient of variation and objective weight;

[0031] The importance data and weighted vector of each carbon emission influencing factor are obtained by removing subjective weights, and the importance data are sorted to obtain the sorting results;

[0032] Determine the relative weight of each carbon emission influencing factor based on each importance data and its corresponding weighted vector;

[0033] According to the objective weight index of each carbon emission influencing factor and its corresponding relative weight, the comprehensive weight coefficient of each carbon emission influencing factor is determined.

[0034] In some possible implementations, the carbon emissions of the target area under the carbon reduction path are determined based on the comprehensive weight coefficient and various carbon emission influencing factors, including:

[0035] Multiply each carbon emission influencing factor and its corresponding comprehensive weight coefficient, and add up the multiplication results to obtain the carbon emissions of the target area under the carbon reduction path.

[0036] In a second aspect, an embodiment of the present invention provides a carbon emission calculation device under a carbon reduction path in the power industry, comprising:

[0037] A data acquisition module is used to obtain carbon emission data on the power generation side, grid side and energy storage side of the target area, as well as power data on the power generation side, load side and energy storage side;

[0038] An impact factor determination module is used to calculate the carbon emission impact factors of the power generation side, the power grid side, the load side and the energy storage side according to the carbon emission data of the power generation side, the power grid side and the energy storage side and the power data of the power generation side, the load side and the energy storage side;

[0039] A weight coefficient determination module is used to determine the comprehensive weight coefficient of each carbon emission influencing factor based on a subjective and objective comprehensive method;

[0040] The calculation module is used to determine the carbon emissions of the target area under the carbon reduction path based on the comprehensive weight coefficient and various carbon emission influencing factors.

[0041] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the processor implements the steps of the method described in the first aspect or any possible implementation manner of the first aspect.

[0042] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in the first aspect or any possible implementation method of the first aspect are implemented.

[0043] The embodiments of the present invention provide a method, device, equipment and medium for calculating carbon emissions under the carbon reduction path of the power industry. When calculating the carbon emissions in the target area, the power generation side, grid side, load side and energy storage side of the target area are comprehensively considered to make the optimization target more comprehensive. In addition, various influencing factors affecting the carbon emission calculation are taken into consideration to calculate the influencing factors of each carbon emission. Finally, in order to improve the calculation accuracy, the comprehensive weight coefficient of each carbon emission influencing factor is determined by using the subjective and objective comprehensive method to obtain the carbon emissions of the target area under the carbon reduction path. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0045] Figure 1 It is a flow chart for implementing a method for calculating carbon emissions under a carbon reduction path for the power industry provided by an embodiment of the present invention;

[0046] Figure 2 It is a schematic diagram of energy consumption trend prediction in City F according to the carbon emission calculation method under the carbon reduction path of the power industry provided by an embodiment of the present invention;

[0047] Figure 3 It is a schematic diagram of annual carbon reduction amounts on each side of source-grid-load-storage of a carbon emission calculation method under a carbon reduction path for the power industry provided by an embodiment of the present invention;

[0048] Figure 4 It is a schematic diagram of carbon reduction contributions on the power generation side, the grid side, the load side and the energy storage side of the carbon emission calculation method under the carbon reduction path of the power industry provided by an embodiment of the present invention;

[0049] Figure 5 It is a comparison diagram of the effects of carbon reduction measures of the carbon emission calculation method under the carbon reduction path of the power industry provided by an embodiment of the present invention;

[0050] Figure 6 It is a structural schematic diagram of a carbon emission calculation device under a carbon reduction path in the power industry provided by an embodiment of the present invention;

[0051] Figure 7 is a schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0053] In this embodiment, carbon emissions are calculated by two methods: energy supply side and consumption side. The energy supply side separately counts carbon emissions from coal, oil, natural gas, and net imported electricity. The consumption side separately counts carbon emissions from industry, construction, transportation, and agriculture and rural areas. There are certain deviations in the calculations of the energy supply side and the consumption side. Taking a certain region, City F, as an example, its carbon emission data on the energy supply side and the consumption side in the past ten years are shown in Table 1. It can be seen from the table that there is a deviation of about 10% in the carbon emissions calculated by the energy supply side and the consumption side.

[0054] Table 1 Carbon emissions from energy supply and consumption in a certain region, City F, from 2010 to 2020 (10,000 tons)

[0055]

[0056] By breaking down carbon emissions on the energy supply side into four dimensions: coal, oil, natural gas, and net electricity imports, we can obtain the detailed data on carbon emissions on the energy supply side of City F in the past ten years, as shown in Table 2.

[0057] Table 2: Detailed data of carbon emissions from energy supply side in F City from 2010 to 2020 (10,000 tons)

[0058]

[0059]

[0060] As can be seen from Table 2, coal and net imported electricity generate the highest carbon emissions, followed by oil, and natural gas generates the least carbon emissions.

[0061] Since the current carbon emission calculation method of the power industry calculates the total amount of carbon emissions within a certain period for macro calculation, the carbon emissions of the power industry mainly calculate the carbon emissions of net imported electricity, but there is a lack of calculation for the carbon emissions generated by local power sources. In order to accurately calculate the carbon emissions of the power industry, the embodiment of the present invention calculates the carbon emissions of the power industry for the carbon emissions of local power generation and the carbon emissions of net imported electricity, specifically:

[0062] Considering that carbon emissions in the urban power industry are concentrated in the power generation side, grid side, load side and energy storage side. Carbon emissions on the power generation side are the main source of carbon emissions in the power industry. High energy consumption of equipment inside the grid and line losses will cause carbon emissions inside the grid. Irrational use of the load side will indirectly increase carbon emissions. Energy storage increases the adjustability of the grid, but the energy storage system will lose electricity during the storage and release of electricity, thereby increasing carbon emissions. Therefore, carbon reduction measures in the urban power industry can be analyzed from the power generation side, grid side, load side and energy storage side.

[0063] Based on this, an embodiment of the present invention provides a method for calculating carbon emissions under a carbon reduction path in the power industry. In order to make the objectives, technical solutions and advantages of the present invention clearer, it will be described below through specific embodiments in conjunction with the accompanying drawings.

[0064] Figure 1 is a flow chart of the implementation of the carbon emission calculation method under the carbon reduction path of the power industry provided by the embodiment of the present invention, such as Figure 1 As shown, the method includes:

[0065] Step 110: Obtain the carbon emission data of the target area's power generation side, grid side, and energy storage side, as well as the power data of the power generation side, load side, and energy storage side.

[0066] In this embodiment, the target area may refer to a certain city, and the carbon emission data on the power generation side may include the carbon emissions of coal-fired power units and the carbon emissions of new energy equipment built in the target area; the power data on the power generation side may include the amount of electricity transferred to the target area, non-fossil energy power generation, power generation of various types of power sources, line losses and amount of electricity transferred out.

[0067] Carbon emission data on the grid side may include the amount of carbon emissions generated per unit of energy during the combustion or use of each energy source.

[0068] The carbon emission data on the energy storage side may include the original carbon emissions on the energy storage side; the power data on the energy storage side includes the charging and discharging efficiency of the energy storage equipment.

[0069] The power data on the load side may include the consumed electric energy on the load side.

[0070] Step 120: Calculate the carbon emission influencing factors of the power generation side, the power grid side, the load side and the energy storage side according to the carbon emission data of the power generation side, the power grid side and the energy storage side and the power data of the power generation side, the load side and the energy storage side.

[0071] In this embodiment, the factors affecting carbon emissions on the power generation side may include the carbon emissions reduced by the withdrawal of coal-fired units or the conversion of coal to gas, the carbon emissions after increasing the proportion of green electricity in the net power import, the carbon emissions after increasing the non-fossil energy power generation of local power sources in the target area, and the carbon reduction on the power generation side.

[0072] Accordingly, in order to accelerate the process of "new electrification" and increase the proportion of electricity in terminal energy consumption, the energy consumption per unit of GDP can be reduced by about 4% for every 1% increase in the proportion of electricity in terminal energy consumption. For the urban power industry, mature electricity substitution products can be promoted, such as promoting the transformation of electric energy substitution in mature fields such as electric boilers, electric kilns, and electromagnetic kitchens. The carbon emissions reduced by the withdrawal of coal-fired units or the conversion of coal to gas can be calculated in the following way:

[0073] E 1.1 =ε1E a

[0074] Among them, E 1.1 is the carbon emission reduction due to the withdrawal of coal-fired units or coal-to-gas conversion; ε1 is the withdrawal rate of coal-fired units; E a is the carbon emissions of coal-fired power units.

[0075] For cities with net electricity imports, one of the main sources of carbon emissions is carbon emissions from net electricity imports. Indirect carbon emissions from net electricity imports depend on the amount of electricity imported and the carbon emission factor of net electricity imports. By building a power system dominated by new energy, increasing the proportion of new energy power generation, and increasing the proportion of green electricity in net electricity imports, carbon emissions from net electricity imports can be reduced. Correspondingly, carbon emissions after increasing the proportion of green electricity in net electricity imports can be calculated in the following way:

[0076] E 1.2 =E in Elf ry

[0077] Among them, E 1.2 To increase the carbon emissions after the proportion of green electricity in the net imported electricity; E in To transfer electricity to the target area; ry It is the carbon emission factor of net electricity import.

[0078] To optimize the local power structure, accelerate the establishment of a safe, reliable, economical, efficient, green and low-carbon energy system. Under the premise of overall balance and functional complementarity, the coordinated development of natural gas, hydropower, nuclear power, photovoltaics, wind power, biomass and other power sources should be achieved, and new energy should be gradually promoted to become the main local power source. In order to optimize and adjust the urban energy structure, natural gas, hydropower, photovoltaics, wind power and other power generation should be increased in the short term. In the medium and long term, nuclear power, ocean energy and other power sources can be developed in combination with the city's resource endowment. Correspondingly, the carbon emissions after increasing the non-fossil energy power generation of local power sources in the target area can be calculated in the following way:

[0079] E 1.3 =μ df E df

[0080] Among them, E 1.3 To increase the carbon emissions after the non-fossil energy generation of local power sources; μ df is the non-fossil energy power generation coefficient; E df Non-fossil energy electricity generation.

[0081] The carbon emissions of local power sources in the target area can be calculated as follows:

[0082]

[0083] Among them, E loc is the carbon emissions of local power sources, FLEi Ef is the total power generation of the i-th generator set during the statistical period, in billion kWh; including coal-fired power, gas-fired power, and non-fossil energy power; i is the CO2 emission factor of fossil fuel of the i-th generator set, in units of 10,000 tons of CO2 / 100 million kWh.

[0084] Since the indirect carbon emissions from urban power transfers are calculated using different methods depending on the positive or negative value of power transfers (+) or transfers (-), the following formula can be used to determine whether it is power transfers:

[0085] ELQ=ELC-ELG

[0086]

[0087] Among them, ELQ is the amount of electricity transferred in (+) or out (-), in billion kWh; ELC is the total electricity consumption of cities at or above the prefecture level, in billion kWh; ELG is the power generation of different types of power sources within the city, in billion kWh; ELG i is the electricity production of the ith power source, in billion kWh; power sources include coal-fired power, oil-fired power, gas-fired power, nuclear power, hydropower (excluding pumped storage), wind power, photovoltaic power generation, waste incineration, biomass and other power generation.

[0088] If ELQ is negative, the indirect carbon emissions embodied in electricity transfer from the target region can be calculated using the following formula:

[0089] E ise =ELQ se ×EF e

[0090]

[0091] Among them, E ise The indirect carbon emissions contained in the city’s electricity transfer, in tons of carbon dioxide; ELQ se EF is the electricity output (-), in billion kWh; e is the average CO2 emission factor of the city's power grid, in units of 10,000 tons of CO2 / 100 million kWh; ELG is the power generation of different types of power sources within the city, in units of 100 million kWh; FCE i Ef is the fossil fuel consumption of all power generation of the i-th generator set during the statistical period, in 10,000 tons of standard coal; including coal consumption, oil consumption, natural gas consumption, etc. i is the CO2 emission factor of fossil fuel of the ith generator set, in tons of carbon dioxide / ton of standard coal.

[0092] When transferring electricity from other places, it is necessary to consider the carbon emissions caused by line losses. Accordingly, the carbon emissions caused by line losses when transferring electricity can be calculated using the following formula:

[0093] E incline =αL y

[0094] Among them, E incline is the carbon emission caused by line loss when transferring electricity; α is the line loss coefficient; L y is the current line loss.

[0095] The carbon reduction on the power generation side is determined based on the carbon emissions of local power sources, line loss, indirect carbon emissions, and carbon emissions from local new energy construction and operation and maintenance. Correspondingly, the carbon reduction on the power generation side can be calculated using the following formula:

[0096] E 1.4 =E loc -(E incline +E etc +E ise )

[0097] Among them, E etc The carbon emissions when new energy equipment is built in the target area.

[0098] In order to optimize the power grid structure, promote the application of energy-saving equipment, strengthen energy-saving dispatching, and improve the energy-saving level of the power grid, we should implement green power grid construction and evaluation standards, realize energy saving, water saving, material saving, land saving and environmental protection in the whole process, and promote the integrated development of power grid facilities and the environment. We should deeply tap the potential of the power grid itself, realize lean line loss management, reduce the power transmission loss within the power grid by reducing line loss, and thus reduce carbon emissions.

[0099] The emission factor method provided in the IPCC (Intergovernmental Panel on Climate Change) guidelines is currently the most widely used greenhouse gas emission accounting method.

[0100] The emission factor method provided in the Intergovernmental Panel on Climate Change (IPCC) guidelines is currently the most widely used greenhouse gas emission accounting method. It combines information about the extent of human activities (called "activity data"; Activity Data, AD) with the emission or removal coefficient of the unit activity (i.e., emission factor; Emission Factor, EF). Correspondingly, the carbon emissions on the grid side can be expressed as:

[0101] E 2.1 =AD·EF

[0102] Among them, E 2.1 It is the carbon emissions from the grid after the implementation of carbon reduction measures; AD is the information about the extent of human activities; EF is the emission or removal coefficient for quantifying unit activities. EF carbon emission coefficient / carbon emission factor refers to the amount of carbon emissions generated per unit energy during the combustion or use of each energy. According to the IPCC's assumptions, the carbon emission coefficient of a certain energy is considered to be fixed.

[0103] Accelerate the process of "new electrification" and increase the proportion of electricity in terminal energy consumption. For every 1% increase in the proportion of electricity in terminal energy consumption, the energy consumption per unit of GDP can be reduced by about 4%. For the urban power industry, mature electricity replacement products can be promoted, such as promoting the replacement of electricity in mature fields such as electric boilers, electric kilns, and electromagnetic kitchens. Correspondingly, the carbon emissions on the load side can be calculated in the following way:

[0104] E 3.1 =θE un

[0105] Among them, E 3.1 is the energy saving amount; θ is the electricity substitution coefficient; E un It is the electric energy consumed on the load side.

[0106] Energy storage can improve the flexibility of grid regulation and reduce the peak-to-valley difference of the grid. It is an effective means to increase the scale of renewable energy power generation connected to the grid. Through intelligent peak regulation and optimized energy storage scheduling, the efficiency of power system operation and the absorption of new energy can be improved, and the abandonment of wind and solar power can be reduced. It is one of the measures to achieve carbon emission reduction. Correspondingly, the emission reduction after intelligent peak regulation on the energy storage side can be calculated in the following way:

[0107] E 4.1 =ρE chu

[0108] Among them, E 4.1 is the emission reduction after intelligent peak regulation on the energy storage side; ρ is the peak regulation coefficient; E chu For the original displacement.

[0109] Electric energy is lost during the charging and discharging process. The comprehensive efficiency of the energy storage power stations currently built in China is between 65% and 91%, with a large efficiency gap. The charging and discharging efficiency of energy storage can be improved by optimizing the temperature of the energy storage operating environment, the battery management level, the energy storage converter, the consistency of the battery cells and other technical means, thereby reducing the power loss. Correspondingly, the power loss reduced on the energy storage side can be calculated using the following formula:

[0110] E 4.2 =γV chu

[0111] Among them, E 4.2is the reduced power consumption; γ is the charge and discharge loss coefficient; V chu is the charge and discharge efficiency.

[0112] Step 130: Determine the comprehensive weight coefficient of each carbon emission influencing factor based on the subjective and objective comprehensive method.

[0113] In this embodiment, evaluation indicators are constructed from multiple dimensions including the power generation side, the grid side, the load side, and the energy storage side. Due to the differences among various types of carbon reduction measures, it is impossible to quantify the carbon reduction effects one by one. Therefore, this embodiment determines the comprehensive weight coefficient of each carbon emission influencing factor based on the subjective and objective comprehensive method, so as to quantify the above-mentioned carbon emission influencing factors, assign different weights, and evaluate the carbon reduction effect.

[0114] Exemplarily, the subjective and objective comprehensive method may adopt the CV method and the C-OWA method to remove subjective weights. Accordingly, the comprehensive weight coefficients of various carbon emission influencing factors determined based on the subjective and objective comprehensive method may include:

[0115] First, experts were invited to score the factors affecting carbon emissions to obtain the original data matrix X. Second, the following standardization, mean, standard deviation, coefficient of variation and weight calculation formulas were used to obtain the data in Table 3. Among them, Y, A, S, V, and α represent the standardization matrix, mean, standard deviation, coefficient of variation, and weight, respectively.

[0116] Table 3 Objective weight index of CV method

[0117]

[0118] Among them, each objective weight index can be calculated by the following formula:

[0119]

[0120]

[0121]

[0122] Vj=Sj / Aj

[0123]

[0124] Where x is the scoring result of each expert.

[0125] The OWA operator is a multi-attribute decision-making method that determines the best decision option by considering the ranking and weight of influencing factors. It allows different degrees of preference to be introduced in the ranking to adapt to the needs of different situations. Based on the OWA operator, the data aggregation form is improved to obtain the combined ordered weighted operator C-OWA, which can reduce the situation where extreme values ​​of subjective will appear. Specifically, first, n experts are invited to score the importance of each carbon emission influencing factor, and the initial data a of the scoring results is used as the input. j (j=1,2,…,n) are sorted from large to small and numbered starting from 0, i.e. b0≥b1≥b2≥b j ≥…≥b n-1 That is b j-1 (j=1,2,…,n); secondly determine the weighting vector; then calculate the absolute weight of the factor; finally calculate the relative weight of the factor. The specific formula is as follows:

[0126]

[0127]

[0128]

[0129] Among them, w j+1 is the weighted vector of the j+1th influencing factor, is the number of combinations of taking j data from n-1 data; is the absolute weight of the i-th factor; b j is the result after factor sorting; w i is the relative weight of the ith factor.

[0130] Considering the difference in calculation principle between CV method and C-OWA de-subjective weight method, the embodiment of the present invention adopts the combined weighting method to obtain the final weight result, that is, the comprehensive weight coefficient of each influencing factor, and the calculation formula is as follows:

[0131]

[0132] Among them, P i is the comprehensive weight coefficient of the i-th influencing factor; α i The weight is calculated by CV method; w i is the weight obtained by C-OWA method.

[0133] Based on this formula, the comprehensive weight coefficients of each influencing factor are shown in Table 4:

[0134] Table 4 Comprehensive weight coefficient of each influencing factor

[0135]

[0136] Step 140: Determine the carbon emissions of the target area based on the comprehensive weight coefficient and the carbon emissions influencing factor.

[0137] In this embodiment, the carbon emission reduction calculation of the power industry in the target area mainly calculates the effect of emission reduction measures on the power generation side, the grid side, the load side, and the energy storage side. When the electricity demand is met, the carbon emission reduction is the largest. Accordingly, the carbon emissions of the target area under the carbon reduction path can be calculated by the following formula:

[0138]

[0139] E1=p1E 1.1 +p2E 1.2 +p3E 1.3 +p4E 1.4

[0140] E2=p5E 2.1

[0141] E3=p6E 3.1

[0142] E4=p7E 4.1 +p8E 4.2

[0143] Where y is the year and Y is the total number of years calculated.

[0144] In order to verify the method provided by the embodiment of the present invention, a typical city F in a certain region is selected for measurement. According to the formula, the CO2 emission factors of fossil fuels of different generator sets are different. The emission factors are shown in Table 5:

[0145] Table 5 CO2 emission factors of fossil fuels for different power generation units from 2010 to 2020

[0146] type unit Numeric Coal-fired power Tons of carbon dioxide / ton of standard coal 2.66 Gas and Electricity Tons of carbon dioxide / ton of standard coal 1.73 Non-fossil energy electricity Tons of carbon dioxide / ton of standard coal 1.56

[0147] By calculating the electricity carbon emission data in Table 5, we can obtain the net carbon emission of imported electricity from 2010 to 2020, as shown in Table 6:

[0148] Table 6 Carbon emissions from net electricity imports from 2010 to 2020

[0149]

[0150] Based on the method provided in the embodiment of the present invention, the carbon emissions generated by local power generation are calculated. It is necessary to count the power generation of local power sources. Since different fossil fuels are used in different generator sets, their CO2 emission factors are different. Therefore, it is necessary to count the types of local power sources. According to the literature, the power generation of local power sources in City F is shown in Table 7.

[0151] Table 7 Local power generation in City F from 2010 to 2020 (100 million kWh)

[0152]

[0153]

[0154] Accordingly, the calculated carbon emissions from local power generation are shown in Table 8:

[0155] Table 8 Carbon emissions from local power generation in City F from 2010 to 2020 (10,000 tons)

[0156]

[0157] By adding the carbon emissions of local power generation and net imported power from City F from 2010 to 2020, that is, combining the contents in Table 6 with those in Table 8, the carbon emissions data of the power industry in City F can be calculated, as shown in Table 9:

[0158] Table 9 Carbon emissions from the power industry in F City from 2010 to 2020 (10,000 tons)

[0159]

[0160] It can be seen from Table 9 that the trend of electricity carbon emission data is consistent with the trend of carbon emission data on the energy supply side of City F from 2010 to 2020 when the method provided in the embodiment of the present invention is used for measurement. The method provided in the embodiment of the present invention can subdivide and measure the carbon emissions of the urban power industry, and has good results.

[0161] The embodiment of the present invention can also predict the energy consumption in the carbon peak scenario. Specifically, the coal, oil, natural gas and net imported electricity in the two key years of 2025 and 2030 in F City are predicted. Assuming that the consumption of each energy type grows linearly during the key years, the energy consumption of F City during the period of "2021 to 2025" and "2026 to 2030" is converted into standard coal (m sc ) prediction results, such as Figure 2 shown.

[0162] Carbon reduction measures in the urban power industry are divided into the power generation side, the grid side, the load side and the energy storage side. Based on the carbon reduction effect evaluation model, the annual carbon emission reduction of City F from 2021 to 2030 can be calculated.

[0163] On the power generation side, some coal-fired power plants in F City have implemented coal-to-gas conversion, which is expected to reduce CO2 emissions by 994,000 tons from 2025. It is estimated that by the end of 2025, the cumulative new natural gas power generation in F City will reach 20.3 billion kWh / year, the cumulative new photovoltaic power generation will reach 500 million kWh / year, and the cumulative new biomass power generation will reach 800 million kWh / year, with a total increase of about 21.6 billion kWh / year. According to literature, by the end of 2025, the new clean energy power generation in F City can reduce CO2 emissions by 7.56 million tons per year. From 2026 to 2030, assuming that there is no major adjustment to the local power structure and 100 million kWh of photovoltaic power generation is added each year, the annual CO2 reduction on the power generation side will increase by 35,000 tons / year from 2021 to 2030.

[0164] On the grid side, the line loss in City F is expected to decrease by about 0.1% each year. A 0.1% decrease in the line loss rate can reduce electricity loss by about 80 million kWh. According to the formula, from 2021 to 2025, about 28,000 tons of CO2 will be reduced each year. From 2026 to 2030, about 24,000 tons of CO2 will be reduced each year.

[0165] On the load side, electricity consumption can be reduced by guiding users to save energy. Energy conservation on the load side can reduce energy consumption by 5%-15%. If the electricity consumption in City F is gradually reduced to 5% by 2030 through energy conservation on the load side, energy conservation on the load side can reduce 1.3 million tons of CO2 by 2030.

[0166] On the energy storage side, according to the grid planning, F City will complete the grid-side configuration of energy storage power stations of no less than 70 MW / 209 MWh from 2021 to 2030. By 2030, it will promote the configuration of 10%-20% of the installed capacity of centralized new energy sites. By 2030, the energy storage configured by the centralized new energy sites in F City will gradually increase to 10%, and the energy storage charging and discharging efficiency will gradually increase from 80% to 85%. According to the formula, the energy storage side can reduce 563,550 tons of CO2 in 2030.

[0167] According to the formula, the annual reduction in carbon emissions (m co2 ),like Figure 3 shown.

[0168] By adding up the carbon emissions reduced each year on the power generation side, the grid side, the load side and the energy storage side, we can calculate the carbon emissions reduced each year from 2021 to 2030 through carbon reduction measures on the power generation side, the grid side, the load side and the energy storage side. As shown in the following table:

[0169] Table 10 Carbon emission reduction in the power industry in City F from 2021 to 2030 (10,000 tons)

[0170]

[0171] The contribution of each side of the power grid to CO2 emission reduction is as follows: Figure 3 As shown, in 2025, 9.2821 million tons of CO2 emissions will be reduced, with the power generation side, grid side, load side and energy storage side accounting for 92.16%, 0.30%, 7.54% and 0% respectively. In 2030, 10.6166 million tons of CO2 emissions will be reduced, with the power generation side, grid side, load side and energy storage side accounting for 82.22%, 0.23%, 12.25% and 5.31% respectively.

[0172] in accordance with Figure 2 , a carbon emission curve generated by the linear growth of electricity consumption in the power industry in 2030, the year when carbon emissions reach the peak, can be drawn. According to the method provided in the embodiment of the present invention, the carbon emission curve of the power industry in 2030, the year when carbon emissions reach the peak, can be calculated after taking carbon reduction measures. Figure 5 It can be seen that the method provided by the embodiment of the present invention can effectively reduce carbon emissions.

[0173] In summary, the embodiment of the present invention comprehensively considers the power generation side, grid side, load side and energy storage side of the target area when calculating the carbon emissions in the target area, so that the optimization target is more comprehensive, and various influencing factors affecting the carbon emission calculation are taken into account to calculate the influencing factors of each carbon emission. Finally, in order to improve the calculation accuracy, the subjective and objective comprehensive method is used to determine the comprehensive weight coefficient of each carbon emission influencing factor to obtain the carbon emissions of the target area under the carbon reduction path.

[0174] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0175] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0176] Figure 6 The structural schematic diagram of the carbon emission measurement device under the carbon reduction path of the power industry provided by an embodiment of the present invention is shown. For the convenience of explanation, only the part related to the embodiment of the present invention is shown, which is described in detail as follows:

[0177] like Figure 6 As shown, the carbon emission calculation device 6 under the carbon reduction path of the power industry includes:

[0178] A data acquisition module 61 is used to acquire carbon emission data on the power generation side, the grid side and the energy storage side of the target area, as well as power data on the power generation side, the load side and the energy storage side;

[0179] An impact factor determination module 62 is used to calculate the carbon emission impact factors of the power generation side, the power grid side, the load side and the energy storage side according to the carbon emission data of the power generation side, the power grid side and the energy storage side and the power data of the power generation side, the load side and the energy storage side;

[0180] The weight coefficient determination module 63 is used to determine the comprehensive weight coefficient of each carbon emission influencing factor based on a subjective and objective comprehensive method;

[0181] The calculation module 64 is used to determine the carbon emissions of the target area under the carbon reduction path based on the comprehensive weight coefficient and various carbon emission influencing factors.

[0182] In some possible implementations, the carbon emission data on the power generation side includes the carbon emissions of coal-fired power units and the carbon emissions of new energy equipment built in the target area;

[0183] The power data on the power generation side includes the power transferred to the target area, the power generation of non-fossil energy, the power generation of various types of power sources, line losses and the power transferred out;

[0184] The impact factor determination module 62 is specifically used for:

[0185] Based on the carbon emissions of coal-fired power units, calculate the carbon emissions reduction from the withdrawal of coal-fired units or the conversion of coal to gas;

[0186] Based on the amount of electricity transferred to the target area, calculate the carbon emissions after increasing the proportion of green electricity in the net amount of electricity transferred;

[0187] Based on the non-fossil energy power generation, calculate the carbon emissions after increasing the non-fossil energy power generation of local power sources in the target area;

[0188] Based on the power generation of each type of power source, the carbon emissions of local power sources in the target area are calculated; based on the line loss, the carbon emissions caused by line losses when power is transferred in are calculated; based on the power transferred out, the indirect carbon emissions contained in power transfer out of the target area are calculated; based on the carbon emissions of local power sources, the carbon emissions caused by line losses when power is transferred in, the indirect carbon emissions contained in power transfer out and the carbon emissions when new new energy equipment is built in the target area, the carbon reduction on the power generation side is calculated.

[0189] In some possible implementations, the carbon emission data on the grid side includes the amount of carbon emissions generated per unit of energy during the combustion or use of each energy source;

[0190] The impact factor determination module 62 is specifically used for:

[0191] The carbon emissions on the grid side are calculated based on the amount of carbon emissions per unit of energy generated during the combustion or use of each energy source.

[0192] In some possible implementations, the load-side power data includes the consumed power on the load side;

[0193] The impact factor determination module 62 is specifically used for:

[0194] Calculate the energy savings on the load side based on the consumed electrical energy.

[0195] In some possible implementations, the carbon emission data on the energy storage side includes the original carbon emission on the energy storage side;

[0196] The power data on the energy storage side includes the charging and discharging efficiency of the energy storage equipment;

[0197] The impact factor determination module 62 is specifically used for:

[0198] Calculate the emission reduction after intelligent peak regulation on the energy storage side based on the original carbon emissions on the energy storage side;

[0199] Based on the charging and discharging efficiency, calculate the reduced power loss on the energy storage side.

[0200] In some possible implementations, the weight coefficient determination module 63 is specifically configured to:

[0201] Adopting objective weighting method, the original data matrix is ​​determined according to each carbon emission influencing factor;

[0202] According to the original data matrix, the objective weight index of each carbon emission influencing factor is obtained; wherein the objective weight index includes the standardized matrix, mean, standard deviation, coefficient of variation and objective weight;

[0203] The importance data and weighted vector of each carbon emission influencing factor are obtained by removing subjective weights, and the importance data are sorted to obtain the sorting results;

[0204] Determine the relative weight of each carbon emission influencing factor based on each importance data and its corresponding weighted vector;

[0205] According to the objective weight index of each carbon emission influencing factor and its corresponding relative weight, the comprehensive weight coefficient of each carbon emission influencing factor is determined.

[0206] In some possible implementations, the computing module 64 is specifically configured to:

[0207] Multiply each carbon emission influencing factor and its corresponding comprehensive weight coefficient, and add up the multiplication results to obtain the carbon emissions of the target area under the carbon reduction path.

[0208] Figure 7 Schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 7As shown, the electronic device 7 of this embodiment includes: a processor 70, a memory 71, and a computer program 72 stored in the memory 71 and executable on the processor 70. When the processor 70 executes the computer program 72, the steps in the above-mentioned embodiments of the carbon emission calculation method under the carbon reduction path of the power industry are implemented, for example Figure 2 Alternatively, when the processor 70 executes the computer program 72, the functions of each module / unit in the above-mentioned device embodiments are realized, for example Figure 6 The functions of each module are shown.

[0209] Exemplarily, the computer program 72 may be divided into one or more modules / units, which are stored in the memory 71 and executed by the processor 70 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program 72 in the electronic device 7. For example, the computer program 72 may be divided into Figure 6 The modules shown.

[0210] The electronic device 7 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device 7 may include, but is not limited to, a processor 70 and a memory 71. Those skilled in the art will appreciate that Figure 7 It is only an example of the electronic device 7 and does not constitute a limitation of the electronic device 7. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0211] The processor 70 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0212] The memory 71 may be an internal storage unit of the electronic device 7, such as a hard disk or memory of the electronic device 7. The memory 71 may also be an external storage device of the electronic device 7, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 7. Further, the memory 71 may also include both an internal storage unit and an external storage device of the electronic device 7. The memory 71 is used to store the computer program and other programs and data required by the electronic device. The memory 71 may also be used to temporarily store data that has been output or is to be output.

[0213] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0214] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0215] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0216] In the embodiments provided by the present invention, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0217] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0218] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0219] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned carbon emission measurement method embodiments under the carbon reduction path of the power industry can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium.

[0220] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for calculating carbon emissions under the carbon reduction path of the power industry, characterized in that: include: Obtaining carbon emission data on the power generation side, grid side and energy storage side of the target area and the power data on the power generation side, load side and energy storage side; Calculate the carbon emission influencing factors of the power generation side, the power grid side, the load side and the energy storage side according to the carbon emission data of the power generation side, the power grid side and the energy storage side and the power data of the power generation side, the load side and the energy storage side respectively; Determine the comprehensive weight coefficient of each carbon emission influencing factor based on the subjective and objective comprehensive method; Based on the comprehensive weight coefficient and the carbon emission influencing factor, the carbon emissions of the target area under the carbon reduction path are determined.

2. The carbon emission calculation method under the carbon reduction path of the power industry according to claim 1 is characterized in that: The carbon emission data on the power generation side includes the carbon emission of coal-fired power units and the carbon emission of new energy equipment newly built in the target area; The power data on the power generation side includes the power transferred into the target area, the power generation of non-fossil energy, the power generation of various types of power sources, the line loss and the power transferred out; Calculating the carbon emission influencing factor of the power generation side according to the carbon emission data and power data of the power generation side includes: Based on the carbon emissions of the coal-fired power units, calculate the carbon emissions that would be reduced if the coal-fired units were phased out or switched to gas; Based on the amount of electricity transferred into the target area, calculate the carbon emissions after increasing the proportion of green electricity in the net amount of electricity transferred into the target area; Based on the non-fossil energy power generation, calculate the carbon emissions after increasing the non-fossil energy power generation of the local power source in the target area; The carbon emissions of local power sources in the target area are calculated based on the power generation of each type of power source. The carbon emissions caused by line losses when power is transferred in are calculated based on the line losses. The indirect carbon emissions contained in power transfer out of the target area are calculated based on the power transfer out. The carbon reduction on the power generation side is calculated based on the carbon emissions of local power sources, the carbon emissions caused by line losses when power is transferred in, the indirect carbon emissions contained in power transfer out, and the carbon emissions when new new energy equipment is built in the target area.

3. The carbon emission calculation method under the carbon reduction path of the power industry according to claim 1 is characterized in that: The carbon emission data on the grid side includes the amount of carbon emissions generated per unit of energy during the combustion or use of each energy source; Calculating the carbon emission influencing factor on the grid side according to the carbon emission data on the grid side includes: The carbon emissions on the grid side are calculated based on the amount of carbon emissions per unit of energy generated during the combustion or use of each energy source.

4. The carbon emission calculation method under the carbon reduction path of the power industry according to claim 1 is characterized in that: The power data on the load side includes the power consumption on the load side; Calculating the energy saving factor on the load side according to the power data on the load side includes: The energy saving amount on the load side is calculated based on the consumed electric energy.

5. The carbon emission calculation method under the carbon reduction path of the power industry according to claim 1 is characterized in that: The carbon emission data of the energy storage side includes the original carbon emission of the energy storage side; The power data on the energy storage side includes the charging and discharging efficiency of the energy storage device; Calculating the carbon emission impact factor of the energy storage side according to the power data of the energy storage side includes: Calculate the emission reduction after intelligent peak regulation of the energy storage side according to the original carbon emission of the energy storage side; The reduced power consumption on the energy storage side is calculated according to the charge and discharge efficiency.

6. The carbon emission calculation method under the carbon reduction path of the power industry according to claim 1 is characterized in that: The comprehensive weight coefficient of each carbon emission influencing factor determined based on the subjective and objective comprehensive method includes: Adopting objective weighting method, the original data matrix is ​​determined according to each carbon emission influencing factor; Obtaining objective weight indicators of various carbon emission influencing factors according to the original data matrix; wherein the objective weight indicators include a standardized matrix, a mean, a standard deviation, a coefficient of variation and an objective weight; Obtaining importance data and weighted vectors of various carbon emission influencing factors by removing subjective weights, and sorting the importance data to obtain sorting results; Determine the relative weight of each carbon emission influencing factor based on each importance data and its corresponding weighted vector; According to the objective weight index of each carbon emission influencing factor and its corresponding relative weight, the comprehensive weight coefficient of each carbon emission influencing factor is determined.

7. The carbon emission calculation method under the carbon reduction path of the power industry according to claim 1 is characterized in that: Determining the carbon emissions of the target area under the carbon reduction path based on the comprehensive weight coefficient and each carbon emissions influencing factor includes: Multiply each carbon emission influencing factor and its corresponding comprehensive weight coefficient, and add the multiplication results to obtain the carbon emissions of the target area under the carbon reduction path.

8. A carbon emission calculation device under the carbon reduction path of the power industry, characterized in that: include: A data acquisition module, used to acquire the carbon emission data of the power generation side, the grid side and the energy storage side of the target area and the power data of the power generation side, the load side and the energy storage side; An impact factor determination module, used to calculate the carbon emission impact factors of the power generation side, the power grid side, the load side and the energy storage side according to the carbon emission data of the power generation side, the power grid side and the energy storage side and the power data of the power generation side, the load side and the energy storage side; A weight coefficient determination module is used to determine the comprehensive weight coefficient of each carbon emission influencing factor based on a subjective and objective comprehensive method; A calculation module is used to determine the carbon emissions of the target area under the carbon reduction path based on the comprehensive weight coefficient and the carbon emissions influencing factor.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method as claimed in any one of claims 1 to 7 are implemented.

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