A carbon neutrality simulation method and terminal

Abstract

The present invention discloses a carbon neutrality simulation method and terminal, which measures the carbon emissions of an electric power system to obtain the carbon emission measurement results of the electric power system; performs fitting prediction on the carbon sink total to obtain the carbon sink prediction result; predicts the total carbon emissions of the whole society to obtain the total carbon emissions prediction result of the whole society, and establishes a proportion relationship between the carbon emission measurement results of the electric power system and the total carbon emissions prediction result of the whole society; simulates the carbon neutrality route based on the proportion relationship, the total carbon emissions prediction result of the whole society and the carbon sink prediction result to obtain the carbon neutrality route simulation result, and combines the carbon source and carbon sink analysis to simulate and analyze the carbon neutrality route, which can determine the carbon neutrality route more comprehensively and effectively, and achieve balanced development of economic and social development and power supply security, thereby realizing an effective and reliable carbon neutrality route.

Description

Technical Field

[0001] The present invention relates to the field of carbon neutrality technology, and in particular to a carbon neutrality simulation method and terminal. Background Art

[0002] To combat climate change, controlling global carbon emissions has become a global consensus. This initiative primarily targets climate-damaging carbon emissions generated through fossil fuel use, aiming to achieve carbon peak and carbon neutrality, primarily by reducing these emissions. Power system carbon emissions account for approximately half of total societal carbon emissions and around 80% of energy-related carbon emissions, making them a leading force and a key implementation scenario for achieving the "dual carbon goals." The power system's front-end, directly generating carbon emissions, controls energy consumption, while the back-end connects production across all industries and consumer spending. Changes in the power consumption structure can be directly monitored through adjustments in the carbon emissions structure at the end-point. Changes in power system carbon emissions closely influence fluctuations in overall societal carbon emissions. Achieving carbon peak is primarily achieved through efficiency improvements and structural adjustments to reduce carbon emissions, while achieving carbon neutrality requires technological breakthroughs and implementation of carbon sinks. Maintaining the size of carbon sinks is a long-term and significant undertaking, requiring a balance between economic benefits and environmental protection. While many experiments have been conducted, successful projects are few and far between, necessitating careful planning and strategic planning. my country's low-carbon economy and carbon market have been nascent and developing for over a decade and are currently experiencing rapid development, accelerating the development of carbon emission reduction and carbon sinks. Therefore, it is crucial to carry out flexible carbon neutrality simulations.

[0003] Existing carbon source analysis and carbon sink analysis are basically two separate analyses, with the purpose of emission reduction and carbon sequestration respectively. It is rare to conduct a balanced analysis of the two. Therefore, it is difficult to achieve a better carbon neutrality curve path. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a carbon neutrality simulation method and terminal that can achieve an effective and reliable carbon neutrality route.

[0005] In order to solve the above technical problems, a technical solution adopted by the present invention is:

[0006] A carbon neutrality simulation method, comprising the steps of:

[0007] Calculate the carbon emissions of the power system and obtain the calculation results of the carbon emissions of the power system;

[0008] Fit and predict the total amount of carbon sink to obtain the carbon sink prediction result;

[0009] Predicting the total carbon emissions of the whole society to obtain a prediction result of the total carbon emissions of the whole society, and establishing a ratio relationship between the carbon emissions calculation result of the power system and the prediction result of the total carbon emissions of the whole society;

[0010] Based on the proportion relationship, the total carbon emissions forecast results of the whole society and the carbon sink forecast results, the carbon neutrality route is simulated to obtain the carbon neutrality route simulation results.

[0011] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0012] A carbon neutrality simulation terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0013] Calculate the carbon emissions of the power system and obtain the calculation results of the carbon emissions of the power system;

[0014] Fit and predict the total amount of carbon sink to obtain the carbon sink prediction result;

[0015] Predicting the total carbon emissions of the whole society to obtain a prediction result of the total carbon emissions of the whole society, and establishing a ratio relationship between the carbon emissions calculation result of the power system and the prediction result of the total carbon emissions of the whole society;

[0016] Based on the proportion relationship, the total carbon emissions forecast results of the whole society and the carbon sink forecast results, the carbon neutrality route is simulated to obtain the carbon neutrality route simulation results.

[0017] The beneficial effects of the present invention are: measuring the carbon emissions of the power system to obtain the carbon emissions measurement results of the power system, fitting and predicting the carbon sink total to obtain the carbon sink prediction results, predicting the total carbon emissions of the whole society to obtain the total carbon emissions prediction results of the whole society, and establishing a proportion relationship between the carbon emissions measurement results of the power system and the total carbon emissions prediction results of the whole society, simulating the carbon neutrality route based on the proportion relationship, the total carbon emissions prediction results of the whole society and the carbon sink prediction results to obtain the carbon neutrality route simulation results, and combining the carbon source and carbon sink analysis to simulate and analyze the carbon neutrality route, which can determine the carbon neutrality route more comprehensively and effectively, and achieve balanced development of economic and social development and power supply security, thereby realizing an effective and reliable carbon neutrality route. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a flowchart of the steps of a carbon neutrality simulation method according to an embodiment of the present invention;

[0019] Figure 2 This is a structural diagram of a carbon neutral simulation terminal according to an embodiment of the present invention;

[0020] Figure 3 This is a schematic diagram of the simulation process in a carbon neutrality simulation method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0021] To illustrate the technical content, achieved objectives and effects of the present invention in detail, the following description is given in conjunction with the embodiments and accompanying drawings.

[0022] Please refer to Figure 1 , an embodiment of the present invention provides a carbon neutrality simulation method, comprising the steps of:

[0023] Calculate the carbon emissions of the power system and obtain the calculation results of the carbon emissions of the power system;

[0024] Fit and predict the total amount of carbon sink to obtain the carbon sink prediction result;

[0025] Predicting the total carbon emissions of the whole society to obtain a prediction result of the total carbon emissions of the whole society, and establishing a ratio relationship between the carbon emissions calculation result of the power system and the prediction result of the total carbon emissions of the whole society;

[0026] Based on the proportion relationship, the total carbon emissions forecast results of the whole society and the carbon sink forecast results, the carbon neutrality route is simulated to obtain the carbon neutrality route simulation results.

[0027] From the above description, it can be seen that the beneficial effects of the present invention are: measuring the carbon emissions of the power system to obtain the carbon emissions measurement results of the power system, fitting and predicting the carbon sink total to obtain the carbon sink prediction results, predicting the total carbon emissions of the whole society to obtain the total carbon emissions prediction results of the whole society, and establishing a proportion relationship between the carbon emissions measurement results of the power system and the total carbon emissions prediction results of the whole society, simulating the carbon neutrality route based on the proportion relationship, the total carbon emissions prediction results of the whole society and the carbon sink prediction results to obtain the carbon neutrality route simulation results, and combining the carbon source and carbon sink analysis to simulate and analyze the carbon neutrality route, which can determine the carbon neutrality route more comprehensively and effectively, and achieve balanced development of economic and social development and power supply security, thereby realizing an effective and reliable carbon neutrality route.

[0028] Furthermore, the calculation of the carbon emissions of the power system to obtain the calculation results of the carbon emissions of the power system includes:

[0029] Calculate the carbon emissions of the generator sets in the region and obtain the carbon emissions calculation results of the generator sets in the region;

[0030] Calculate the carbon emissions of inter-regional exchanged electricity and obtain the calculation results of the carbon emissions of inter-regional exchanged electricity;

[0031] Calculate the carbon emissions of electric transportation and obtain the calculation results of carbon emissions of electric transportation;

[0032] The carbon emission calculation results of the power system are obtained based on the carbon emission calculation results of the power generation units in the region, the carbon emission calculation results of the inter-regional exchange electricity and the carbon emission calculation results of the power transportation.

[0033] From the above description, it can be seen that when calculating the carbon emissions of the power system, the carbon emissions of power generation units within the region, the carbon emissions of electricity exchange between regions, and the carbon emissions of power transportation are comprehensively considered, so that the predicted carbon emissions of the power system are more comprehensive and accurate.

[0034] Furthermore, the carbon emissions of the generator sets in the region are calculated to obtain the carbon emissions calculation results of the generator sets in the region, including:

[0035]

[0036] Where, represents the carbon emission calculation results of the power generation units in the region, X1 represents the first row vector of 1*3 dimensions, and Y represents the second row vector of 1*3 dimensions. represents the standard amount of coal consumption of coal-fired units during power generation in year t, It represents the standard fuel consumption of fuel-fired units during the power generation process in year t. represents the standard amount of gas consumption of the gas-fired unit during the power generation process in year t, represents the carbon emission factor of coal consumption, represents the carbon emission factor of oil consumption, represents the carbon emission factor of gas consumption, and t represents the year;

[0037] The carbon emissions of inter-regional exchanged electricity are calculated, and the calculation results of the carbon emissions of inter-regional exchanged electricity include:

[0038]

[0039] Where, represents the carbon emission calculation results of inter-regional electricity exchange, X2 represents the third row vector of 1*3 dimensions, represents the standard amount of coal consumption used by coal-fired units in the regional exchange power in year t, Indicates the standard amount of oil consumption used by fuel-fired units in the regional exchange power in year t, It represents the standard amount of gas consumption used by gas generators in the regional exchange power in year t;

[0040] The calculation of carbon emissions from electric transportation includes:

[0041]

[0042] Where, represents the carbon emission calculation results of electric transportation, X3 represents the fourth row vector of 1*3 dimension, Indicates the standard amount of coal consumption used in electric power transportation, Indicates the standard amount of oil consumption used in electric transportation, Indicates the standard amount of gas consumption used in electric power transportation;

[0043] The power system carbon emission calculation result obtained based on the carbon emission calculation result of the generator set within the region, the carbon emission calculation result of the inter-regional exchange power, and the carbon emission calculation result of the power transportation includes:

[0044]

[0045] Where, Indicates the calculation results of carbon emissions of the power system.

[0046] From the above description, it can be seen that the carbon emissions of generator sets in a region are calculated based on the carbon emission factors of the fuel consumed by the generator sets, and the carbon dioxide emitted by different generator sets is counted as the carbon emissions on the production side. The carbon emissions of inter-regional exchange electricity are predicted based on the consumption of coal, oil and gas used in the regional exchange electricity. The electricity generated by the power plant is transported to the user side through the power grid lines, and electricity is also consumed in the process, that is, line loss electricity. Therefore, the carbon emissions of power transportation are calculated based on the consumption of coal, oil and gas used in power transportation, so that the calculated carbon emissions of the power system are more in line with the actual scenario, thereby improving the accuracy of the power system carbon emissions calculation.

[0047] Furthermore, the fitting and prediction of the carbon sink total amount to obtain the carbon sink prediction result includes:

[0048] Acquiring historical data on forest carbon sinks, and performing fitting prediction on the historical data on forest carbon sinks to obtain a predicted value of forest carbon sinks;

[0049] Obtaining historical ocean carbon sink data, and performing fitting prediction on the historical ocean carbon sink data to obtain an ocean carbon sink prediction value;

[0050] Obtaining CCUS historical data, and performing fitting prediction on the CCUS historical data to obtain a CCUS prediction value;

[0051] A carbon sink prediction result is obtained based on the forest carbon sink prediction value, the ocean carbon sink prediction value and the CCUS prediction value.

[0052] From the above description, it can be seen that the forest carbon sink, ocean carbon sink and CCUS (carbon capture, utilization and storage) are fitted and predicted respectively to obtain the prediction results of the total carbon sink, so as to combine the carbon sink with carbon emissions to realize carbon neutrality simulation and improve the reliability of carbon neutrality simulation.

[0053] Furthermore, the fitting and prediction of the forest carbon sink historical data to obtain the forest carbon sink prediction value includes:

[0054] Fitting the historical forest carbon sink data using a linear curve to obtain a first forest carbon sink fitting value;

[0055] Fitting the historical data of forest carbon sinks using a quadratic curve to obtain a second forest carbon sink fitting value;

[0056] Fitting the historical data of forest carbon sinks using a logarithmic curve to obtain a third forest carbon sink fitting value;

[0057] Calculating the variances between the first forest tree carbon sink fitting value, the second forest tree carbon sink fitting value, and the third forest tree carbon sink fitting value and the corresponding actual values, respectively, and determining a first fitting weight corresponding to the first forest tree carbon sink fitting value, a second fitting weight corresponding to the second forest tree carbon sink fitting value, and a third fitting weight corresponding to the third forest tree carbon sink fitting value based on the variances;

[0058] Obtaining a predicted forest carbon sink value according to the first forest carbon sink fitting value, the second forest carbon sink fitting value, the third forest carbon sink fitting value, the first fitting weight, the second fitting weight, and the third fitting weight;

[0059] The predicted forest carbon sink value is displayed using a combination of an area chart and a line chart.

[0060] From the above description, it can be seen that different methods are used to fit and predict forest carbon sinks, and the prediction results are displayed, so that the value and growth rate of forest carbon sinks in the entire region can be understood, which facilitates subsequent carbon neutrality.

[0061] Furthermore, the fitting of the historical forest carbon sink data using a linear curve to obtain a first forest carbon sink fitting value includes:

[0062]

[0063] Where, represents the first forest carbon sink fitting value, α represents the first coefficient to be fitted, t represents the year, and c represents the first intercept term;

[0064] The fitting of the forest carbon sink historical data using a quadratic curve to obtain a second forest carbon sink fitting value includes:

[0065]

[0066] Where, represents the second forest carbon sink fitting value, represents the second coefficient to be fitted;

[0067] The fitting of the historical forest carbon sink data using a logarithmic curve to obtain a third forest carbon sink fitting value includes:

[0068]

[0069] Where, represents the fitting value of the third forest carbon sink;

[0070] Obtaining a predicted forest carbon sink value according to the first forest carbon sink fitting value, the second forest carbon sink fitting value, the third forest carbon sink fitting value, the first fitting weight, the second fitting weight, and the third fitting weight includes:

[0071]

[0072] Where, FCS t represents the predicted value of forest carbon sequestration, ξ LF represents the first fitting weight, ξ QLF represents the second fitting weight, ξ LCF represents the third fitting weight.

[0073] From the above description, it can be seen that the fitting weight is determined according to the variance between the fitting value and the actual value of different fitting methods, and finally the future forest carbon sink prediction value is calculated, which can improve the accuracy and reliability of forest carbon sink prediction.

[0074] Furthermore, the prediction of the total carbon emissions of the whole society to obtain the prediction result of the total carbon emissions of the whole society includes:

[0075]

[0076] Where, represents the total carbon emission forecast result of the whole society, c′ represents the second intercept term, α1 represents the third coefficient to be fitted, α2 represents the fourth coefficient to be fitted, α3 represents the fifth coefficient to be fitted, α4 represents the sixth coefficient to be fitted, P t represents the population in year t, represents the GDP per capita in year t, represents the energy consumption intensity in year t, represents the energy consumption and carbon emission intensity in year t, and ε represents the random disturbance term;

[0077] The relationship between the power system carbon emission calculation results and the total carbon emission forecast results of the whole society γ t for:

[0078]

[0079] Where, Indicates the carbon emission calculation results of the power system.

[0080] From the above description, it can be seen that carbon dioxide emissions depend on four determining factors: population, per capita GDP, energy consumption per unit GDP, and emission factor per unit energy consumption. The forecast results of the total carbon emissions of the whole society calculated based on the above four determining factors can meet the total carbon emissions of the whole society for future economic and social development, and facilitate the subsequent determination of the carbon neutrality route based on the total carbon emissions of the whole society.

[0081] Furthermore, the carbon neutrality route is simulated based on the proportion relationship, the total carbon emissions forecast result of the whole society and the carbon sink forecast result, and the carbon neutrality route simulation results obtained include:

[0082] Determine the net carbon emissions based on the total carbon emissions forecast results for the whole society and the carbon sink forecast results;

[0083] If the net amount of carbon emissions is less than or equal to a first preset value, carbon neutrality is achieved;

[0084] If the net carbon emissions are greater than the first preset value, the key indicators affecting carbon emissions are determined, and when the proportion relationship tends to a steady state, the carbon emissions are reduced according to the key indicators until the net carbon emissions tend to the first preset value, thereby obtaining the carbon neutrality route simulation results.

[0085] From the above description, it can be seen that based on the net carbon emissions, it is possible to more accurately judge whether it is in a carbon neutral state, which facilitates the subsequent carbon neutrality route simulation results.

[0086] Furthermore, determining the key indicators that affect carbon emissions, and when the proportion relationship tends to a steady state, reducing carbon emissions according to the key indicators until the net carbon emissions tend to the first preset value, and obtaining the carbon neutrality route simulation results include:

[0087] Determine the main carbon source and the key indicators corresponding to the main carbon source;

[0088] Determining the adjustable range of the key indicator according to the structure and upper limit of the main carbon source, and determining the unit adjustment cost corresponding to each key indicator to obtain the total adjustment cost;

[0089] When the proportion relationship tends to a steady state, the key indicators are adjusted according to the principle of minimizing the total adjustment cost until the net carbon emissions tend to the first preset value, thereby obtaining the carbon neutrality route simulation result.

[0090] From the above description, it can be seen that the carbon neutrality simulation results obtained in this way, while taking into account economic costs, adjust key indicators to reduce carbon emissions until the carbon neutrality state is reached, which can achieve an effective and reliable carbon neutrality route, and then provide a power system construction and development strategy under the constraints of dual carbon goals, and support new power system construction decisions.

[0091] Please refer to Figure 2 Another embodiment of the present invention provides a carbon neutrality simulation terminal, including a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, each step in the above-mentioned carbon neutrality simulation method is implemented.

[0092] The carbon neutrality simulation method and terminal described above in the present invention can be applied to a carbon neutrality sandbox simulation, and are described below through specific implementation methods:

[0093] Example 1

[0094] Please refer to Figure 1 and Figure 3 A carbon neutrality simulation method of this embodiment includes the following steps:

[0095] S1. Calculate the carbon emissions of the power system and obtain the calculation results of the carbon emissions of the power system, including:

[0096] S11. Calculate the carbon emissions of the generator sets in the region and obtain the calculation results of the carbon emissions of the generator sets in the region. Specifically:

[0097]

[0098] Where, represents the carbon emission calculation results of the power generation units in the region, X1 represents the first row vector of 1*3 dimensions, and Y represents the second row vector of 1*3 dimensions. represents the standard amount of coal consumption of coal-fired units during power generation in year t, It represents the standard fuel consumption of fuel-fired units during the power generation process in year t. represents the standard amount of gas consumption of the gas-fired unit during power generation in year t, η C Represents the carbon emission factor of coal consumption, η O Carbon emission factor representing fuel consumption, η G represents the carbon emission factor of gas consumption, and t represents the year;

[0099] Among them, the generator sets include 8 types: coal-fired units, gas-fired units, oil-fired units, wind turbines, photovoltaic units, nuclear power units, hydropower units, and other units. Figure 3 As shown, since wind power generation, photovoltaic power generation, nuclear power generation, hydropower generation and other units do not directly produce carbon emissions, only the carbon emissions of the three major units of coal-fired, gas-fired and oil-fired are calculated here.

[0100] The amount of fuel consumed by coal-fired units, gas-fired units, and oil-fired units is calculated based on their respective installed capacities, average equipment utilization hours, and energy consumption per unit of electricity. The calculation formula is as follows:

[0101]

[0102]

[0103]

[0104]

[0105]

[0106]

[0107] Where, represents the power generation of the coal-fired unit in year t, δ C Indicates the energy consumption per unit of electricity of coal-fired units, I C1，t represents the installed capacity of coal-fired units in year t, H C1，t represents the average utilization hours of coal-fired units in year t, represents the power generation of the fuel-fired unit in year t, δ O Indicates the energy consumption per unit of electricity of the fuel unit, I O1，t represents the installed capacity of fuel-fired units in year t, H O1，t represents the average utilization hours of the fuel-fired units in year t, represents the power generation of the gas turbine unit in year t, δ G Indicates the energy consumption per unit of electricity of the gas generator set, I G1，t represents the installed capacity of the gas-fired unit in year t, H G1，t It represents the average equipment utilization hours of the gas generator set in year t.

[0108] S12. Calculate the carbon emissions of inter-regional exchanged electricity to obtain a calculation result of the carbon emissions of inter-regional exchanged electricity;

[0109] Specifically, the amount of electricity exchanged between regions can be divided into the amount of electricity imported from outside the region and the amount of electricity supplied to outside the region. According to the principle of "whoever uses it, emits it", the carbon emissions of the electricity imported from outside the region are positive, and its carbon emissions are calculated according to the electricity composition of the source unit. The carbon emissions of electricity supplied to outside the region are negative, and its carbon emissions are calculated according to the electricity composition of the supply unit. Among them, if the type of unit for the amount of electricity exchanged between regions can be clearly identified, it will be calculated according to the carbon emission calculation method of the corresponding unit type, and the calculation idea is the same as described in S11. If the type of unit cannot be clearly identified, it will be calculated according to the power structure of this region, and the formula is as follows:

[0110]

[0111] Where, represents the carbon emission calculation results of inter-regional electricity exchange, X2 represents the third row vector of 1*3 dimensions, represents the standard amount of coal consumption used by coal-fired units in the regional exchange power in year t, Indicates the standard amount of oil consumption used by fuel-fired units in the regional exchange power in year t, It represents the standard amount of gas consumption used by gas generators in the regional exchange power in year t;

[0112]

[0113]

[0114]

[0115]

[0116]

[0117]

[0118] Where, represents the inter-regional exchange of electricity between coal-fired units in year t, Q C2，t represents the power generation of coal-fired units in the power supply grid in year t, Q t ′ represents the total power generation of all units in the power supply grid in year t, OQ t represents the total amount of electricity exchanged between regions in year t, represents the inter-regional exchange power of fuel-fired units in year t, Q O2，t represents the power generation of fuel-fired units in the power supply grid in year t, represents the inter-regional exchange power of gas generators in year t, Q G2，t represents the power generation of gas-fired units in the power supply grid in year t.

[0119] S13. Calculate the carbon emissions from electricity transportation and obtain the results. Since the electricity generated by the power plant is transported to the user side through the power grid lines, electricity is also consumed in the process, that is, line loss. Therefore, the carbon emissions of this part of the electricity are calculated based on the average installed capacity structure of the regional power grid. Specifically:

[0120]

[0121] Where, represents the carbon emission calculation results of electric transportation, X3 represents the fourth row vector of 1*3 dimension, Indicates the standard amount of coal consumption used in electric power transportation, Indicates the standard amount of oil consumption used in electric transportation, Indicates the standard amount of gas consumption used in electric power transportation;

[0122]

[0123]

[0124]

[0125]

[0126]

[0127]

[0128] Where, It represents the line loss electricity calculated by coal-fired units in year t, Q C3，t represents the power generation of coal-fired units in the regional power grid in year t, Q t Indicates the total power generation of all units in the regional power grid in year t, LQ t represents the total line loss electricity in year t, Indicates the line loss electricity calculated by the fuel-fired unit in year t, Q O3，t represents the power generation of fuel-fired units in the regional power grid in year t, Indicates the line loss electricity calculated by gas generator set in year t, Q G3，t It represents the power generation of gas-fired units in the regional power grid in year t.

[0129] S14, obtaining the carbon emission calculation result of the power system according to the carbon emission calculation result of the generator set in the region, the carbon emission calculation result of the inter-regional exchange power and the carbon emission calculation result of the power transportation, such as Figure 3 As shown, specifically:

[0130]

[0131] Where, Indicates the calculation results of carbon emissions of the power system.

[0132] S2. Fit and predict the total amount of carbon sink to obtain the carbon sink prediction result, such as Figure 3 As shown, specifically including:

[0133] S21. Obtain historical data on forest carbon sinks, and perform fitting and prediction on the historical data to obtain a predicted value of forest carbon sinks, specifically including:

[0134] S211. Fit the historical forest carbon sink data using a linear curve to obtain a first forest carbon sink fitting value. Specifically:

[0135]

[0136] Where, represents the first forest carbon sink fitting value, α represents the first coefficient to be fitted, t represents the year, and c represents the first intercept term;

[0137] S212. Fit the historical forest carbon sink data using a quadratic curve to obtain a second forest carbon sink fitting value. Specifically:

[0138]

[0139] Where, represents the second forest carbon sink fitting value, and β represents the second coefficient to be fitted;

[0140] S213. Fit the historical data of forest carbon sinks using a logarithmic curve to obtain a third forest carbon sink fitting value. Specifically:

[0141]

[0142] Where, represents the fitting value of the third forest carbon sink;

[0143] S214. Calculate the variances between the first tree carbon sink fitting value, the second tree carbon sink fitting value, and the third tree carbon sink fitting value and the corresponding actual values, respectively, and determine a first fitting weight corresponding to the first tree carbon sink fitting value, a second fitting weight corresponding to the second tree carbon sink fitting value, and a third fitting weight corresponding to the third tree carbon sink fitting value based on the variances. Specifically:

[0144]

[0145]

[0146] Where, represents the variance between the fitted value of forest carbon sink under method j and the corresponding actual value, represents the forest carbon sink fitting value under method j, n represents the number of samples, represents the sample mean, ξ j represents the fitting weight under method j, including ξ LF ,ξ QLF ,ξ LCF , j includes linear curve, quadratic curve or logarithmic curve;

[0147] For example, to calculate the first fitting weight, the first forest carbon sink fitting value, the number of samples, and the sample average are substituted into the formula to calculate the variance between the first forest carbon sink fitting value and the corresponding actual value, and then the first fitting weight is calculated based on the variance. The second fitting weight and the third fitting weight are calculated in the same way.

[0148] S215: Obtain a predicted forest carbon sink value based on the first forest carbon sink fitting value, the second forest carbon sink fitting value, the third forest carbon sink fitting value, the first fitting weight, the second fitting weight, and the third fitting weight. Specifically:

[0149]

[0150] Where, FCS t represents the predicted value of forest carbon sequestration, ξ LF represents the first fitting weight, ξ QLF represents the second fitting weight, ξ LCF represents the third fitting weight.

[0151] S216. Display the predicted forest carbon sink value using a combination of an area chart and a line chart.

[0152] In an optional embodiment, a combination of an area chart and a line chart may be used to display the forest carbon sink fitting values ​​obtained by fitting predictions using different methods.

[0153] S22. Obtain historical ocean carbon sink data, and perform fitting and prediction on the historical ocean carbon sink data to obtain an ocean carbon sink prediction value. The fitting and prediction of the ocean carbon sink is similar to the fitting and prediction of the forest carbon sink, specifically including:

[0154] S221. Fit the historical ocean carbon sink data using a linear curve to obtain a first ocean carbon sink fitting value. Specifically:

[0155]

[0156] Where, represents the first ocean carbon sink fitting value, α represents the first coefficient to be fitted, t represents the year, and c represents the first intercept term;

[0157] S222. Fit the historical ocean carbon sink data using a quadratic curve to obtain a second ocean carbon sink fitting value. Specifically:

[0158]

[0159] Where, represents the second ocean carbon sink fitting value, and β represents the second coefficient to be fitted;

[0160] S223. Fit the historical ocean carbon sink data using a logarithmic curve to obtain a third ocean carbon sink fitting value. Specifically:

[0161]

[0162] Where, represents the fitted value of the third ocean carbon sink;

[0163] S224. Calculate the variances between the first ocean carbon sink fitting value, the second ocean carbon sink fitting value, and the third ocean carbon sink fitting value and the corresponding actual values, respectively, and determine a first fitting weight corresponding to the first ocean carbon sink fitting value, a second fitting weight corresponding to the second ocean carbon sink fitting value, and a third fitting weight corresponding to the third ocean carbon sink fitting value based on the variances. Specifically:

[0164]

[0165]

[0166] Where, represents the variance between the ocean carbon sink fitting value under method j and the corresponding actual value, represents the ocean carbon sink fitting value under method j, n represents the number of samples, represents the sample mean, ξ j represents the fitting weight under method j, including ξ LF ,ξ QLF ,ξ LCF , j includes linear curves, quadratic curves or logarithmic curves.

[0167] S225: Obtain an ocean carbon sink prediction value based on the first ocean carbon sink fitting value, the second ocean carbon sink fitting value, the third ocean carbon sink fitting value, the first fitting weight, the second fitting weight, and the third fitting weight. Specifically:

[0168]

[0169] Where, OCS t represents the predicted value of ocean carbon sink, ξ LF represents the first fitting weight, ξ QLF represents the second fitting weight, ξ LCF represents the third fitting weight.

[0170] S226. Display the predicted ocean carbon sink value using a combination of an area chart and a line chart.

[0171] S23. Obtaining CCUS (carbon capture, utilization, and storage) historical data and performing fitting prediction on the CCUS historical data to obtain a CCUS prediction value, specifically including:

[0172] S231. Obtain CCUS historical data and determine the preset technology breakthrough year;

[0173] In an optional embodiment, the preset technological breakthrough year is 2030;

[0174] S232: Use a sigmoid curve to fit and predict the CCUS historical data to obtain a CCUS prediction value. Specifically:

[0175]

[0176] Where CCUS t represents the CCUS prediction value, c1 represents the seventh coefficient to be fitted, c2 represents the eighth coefficient to be fitted, c3 represents the ninth coefficient to be fitted, c4 represents the tenth coefficient to be fitted, and d represents the preset technology breakthrough year;

[0177] In an optional embodiment, the curve is fitted using a least squares method.

[0178] S24. Obtain a carbon sink prediction result based on the forest carbon sink prediction value, the ocean carbon sink prediction value, and the CCUS prediction value, specifically:

[0179]

[0180] Where, Represents the carbon sink prediction results.

[0181] S3. Forecast the total carbon emissions of the whole society to obtain the forecast results of the total carbon emissions of the whole society, and establish the relationship between the carbon emissions calculation results of the power system and the forecast results of the total carbon emissions of the whole society, specifically:

[0182] The Kaya identity is used to build a carbon emission prediction model for the whole society, as shown below:

[0183]

[0184] In the formula, C represents carbon dioxide emissions, P represents population, G represents gross national product, and E represents energy consumption;

[0185] From the carbon emission prediction model for the whole society, we know that carbon dioxide emissions depend on four factors: population, per capita GDP, energy consumption per unit GDP, and emission factor per unit energy consumption. Based on this, we construct a multi-factor regression analysis model of carbon emissions to obtain the prediction results of the total carbon emissions for the whole society:

[0186]

[0187] Where, represents the total carbon emission forecast result of the whole society, c′ represents the second intercept term, α1 represents the third coefficient to be fitted, α2 represents the fourth coefficient to be fitted, α3 represents the fifth coefficient to be fitted, α4 represents the sixth coefficient to be fitted, P t represents the population in year t, represents the GDP per capita in year t, represents the energy consumption intensity in year t, represents the energy consumption and carbon emission intensity in year t, and ε represents the random disturbance term;

[0188] In this formula, after obtaining historical data, multiple regression fitting can be used to obtain the estimated values ​​of c′, α1, α2, α3, and α4. The long-term changes of the above four variables can be analyzed in a scenario to obtain the total carbon emissions of the whole society that meet the future economic and social development.

[0189] Among them, the proportion relationship between the power system carbon emission calculation result and the total carbon emission forecast result of the whole society is γ t for:

[0190]

[0191] Where, Indicates the carbon emission calculation results of the power system.

[0192] During the simulation, γ t+1 Extrapolate the proportion of the next year based on the average annual change of the past five years to keep the proportion relationship stable:

[0193] γ t+1 =γ t +Δ t+1 ;

[0194]

[0195] Where, γ t+1 Indicates the proportion relationship in year t+1, Δ t+1 Indicates the change in proportion between year t+1 and year t, Δ i Indicates the change in proportion in year i compared to the previous year.

[0196] S4. Simulating the carbon neutrality route based on the proportion relationship, the total carbon emissions forecast result of the whole society, and the carbon sink forecast result to obtain the carbon neutrality route simulation result, specifically including:

[0197] S41. Determine the net carbon emissions based on the total carbon emissions forecast results for the entire society and the carbon sink forecast results, specifically:

[0198]

[0199] Where, NCt Represents net carbon emissions.

[0200] S42: If the net carbon emissions are less than or equal to a first preset value, carbon neutrality is achieved;

[0201] In an optional implementation, the first preset value is 0;

[0202] S43. If the net carbon emissions are greater than a first preset value, determine a key indicator that affects carbon emissions, and when the proportion relationship approaches a steady state, reduce carbon emissions according to the key indicator until the net carbon emissions approach the first preset value, thereby obtaining a carbon neutrality route simulation result, which specifically includes:

[0203] S431. If the net carbon emissions are greater than a first preset value, determine a major carbon source and a key indicator corresponding to the major carbon source;

[0204] Specifically, based on S1, a structural analysis of different carbon sources such as different installed capacity, inter-regional exchange, and power transportation within the region is conducted, and the main carbon sources and secondary carbon sources are distinguished according to the conditions of large proportion and rapid growth. A carbon source can be determined as a main carbon source if it meets any of the following conditions: ① The carbon emissions of a certain carbon source account for more than or equal to 10% of the total carbon emissions of the power system, and the annual growth rate is more than 5%; ② It accounts for more than or equal to 30% of the total carbon emissions of the power system;

[0205] The key indicators corresponding to the main carbon sources are analyzed and determined, including installed capacity, average equipment utilization hours, energy consumption per unit of electricity, inter-regional power exchange volume and structure, line loss electricity and other indicators.

[0206] S432. Determine the adjustable range of the key indicator according to the structure and upper limit of the main carbon source, and determine the unit adjustment cost corresponding to each key indicator to obtain the total adjustment cost;

[0207] S433. When the proportion relationship tends to a steady state, the key indicators are adjusted according to the principle of minimizing the total adjustment cost until the net carbon emissions tend to the first preset value, thereby obtaining the carbon neutrality route simulation result.

[0208] Example 2

[0209] Please refer to Figure 2 , a new investment demand forecasting terminal in this embodiment includes a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, each step in the carbon neutrality simulation method in Example 1 is implemented.

[0210] To sum up, the present invention provides a carbon neutrality simulation method and terminal, which measures the carbon emissions of the power system to obtain the carbon emission measurement results of the power system; fits and predicts the carbon sink total to obtain the carbon sink prediction result; predicts the total carbon emissions of the whole society to obtain the total carbon emissions prediction result of the whole society, and establishes a proportion relationship between the carbon emission measurement results of the power system and the total carbon emissions prediction result of the whole society; simulates the carbon neutrality route based on the proportion relationship, the total carbon emissions prediction result of the whole society and the carbon sink prediction result to obtain the carbon neutrality route simulation result, and combines the carbon source and carbon sink analysis to simulate and analyze the carbon neutrality route, which can more comprehensively and effectively determine the carbon neutrality route, achieve balanced development of economic and social development and power supply security, thereby realizing an effective and reliable carbon neutrality route, and then providing a power system construction and development strategy under the constraints of dual carbon goals, and supporting new power system construction decisions.

[0211] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's description and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A carbon neutrality simulation method, characterized in that: Including steps: Calculate the carbon emissions of the power system and obtain the calculation results of the carbon emissions of the power system; Fit and predict the total amount of carbon sink to obtain the carbon sink prediction result; Predicting the total carbon emissions of the whole society to obtain a prediction result of the total carbon emissions of the whole society, and establishing a ratio relationship between the carbon emissions calculation result of the power system and the prediction result of the total carbon emissions of the whole society; Simulating a carbon neutrality route based on the proportion relationship, the total carbon emissions forecast result of the whole society, and the carbon sink forecast result to obtain a carbon neutrality route simulation result; The prediction of the total carbon emissions of the whole society to obtain the prediction results of the total carbon emissions of the whole society includes: ； Where, represents the total carbon emission forecast result of the whole society, c′ represents the second intercept term, represents the third coefficient to be fitted, represents the fourth coefficient to be fitted, represents the fifth coefficient to be fitted, Indicates the sixth coefficient to be fitted, P t represents the population in year t, represents the GDP per capita in year t, represents the energy consumption intensity in year t, represents the energy consumption and carbon emission intensity in year t, represents the random disturbance term; The relationship between the power system carbon emission calculation results and the total carbon emission forecast results of the whole society for: ； Where, Indicates the calculation result of carbon emissions of the power system; The carbon neutrality route is simulated based on the proportion relationship, the total carbon emissions forecast result of the whole society and the carbon sink forecast result, and the carbon neutrality route simulation result is obtained, including: Determine the net carbon emissions based on the total carbon emissions forecast results for the whole society and the carbon sink forecast results; If the net amount of carbon emissions is less than or equal to a first preset value, carbon neutrality is achieved; If the net carbon emissions are greater than a first preset value, a key indicator affecting carbon emissions is determined, and when the proportion relationship tends to a steady state, carbon emissions are reduced according to the key indicator until the net carbon emissions tend to the first preset value, thereby obtaining a carbon neutrality route simulation result; The determining of the key indicators that affect carbon emissions, and when the proportion relationship tends to a steady state, reducing carbon emissions according to the key indicators until the net carbon emissions tend to the first preset value, and obtaining the carbon neutrality route simulation results include: Determine the main carbon source and the key indicators corresponding to the main carbon source; Determining the adjustable range of the key indicator according to the structure and upper limit of the main carbon source, and determining the unit adjustment cost corresponding to each key indicator to obtain the total adjustment cost; When the proportion relationship tends to a steady state, the key indicators are adjusted according to the principle of minimizing the total adjustment cost until the net carbon emissions tend to the first preset value, thereby obtaining the carbon neutrality route simulation result.

2. A carbon neutrality simulation method according to claim 1, characterized in that: The calculation of the carbon emissions of the power system to obtain the calculation results of the carbon emissions of the power system includes: Calculate the carbon emissions of the generator sets in the region and obtain the carbon emissions calculation results of the generator sets in the region; Calculate the carbon emissions of inter-regional exchanged electricity and obtain the calculation results of the carbon emissions of inter-regional exchanged electricity; Calculate the carbon emissions of electric transportation and obtain the calculation results of carbon emissions of electric transportation; The carbon emission calculation results of the power system are obtained based on the carbon emission calculation results of the power generation units in the region, the carbon emission calculation results of the inter-regional exchange electricity and the carbon emission calculation results of the power transportation.

3. A carbon neutrality simulation method according to claim 2, characterized in that: The carbon emissions of the generator sets in the region are calculated to obtain the carbon emissions calculation results of the generator sets in the region, including: = ； Where, Indicates the carbon emission calculation results of the generator sets in the region, X1 indicates The first row vector of dimension, Y represents The second row vector of dimension represents the standard amount of coal consumption of coal-fired units during power generation in year t, It represents the standard fuel consumption of fuel-fired units during the power generation process in year t. represents the standard amount of gas consumption of the gas-fired unit during the power generation process in year t, The carbon emission factor representing coal consumption, The carbon emission factor that represents fuel consumption, represents the carbon emission factor of gas consumption, and t represents the year; The carbon emissions of inter-regional exchanged electricity are calculated, and the calculation results of the carbon emissions of inter-regional exchanged electricity include: ； Where, represents the carbon emission calculation results of inter-regional electricity exchange, X2 represents The third row vector of dimension, represents the standard amount of coal consumption used by coal-fired units in the regional exchange power in year t, Indicates the standard amount of oil consumption used by fuel-fired units in the regional exchange power in year t, It represents the standard amount of gas consumption used by gas generators in the regional exchange power in year t; The calculation of carbon emissions from electric transportation includes: = ； Where, Indicates the calculation results of carbon emissions from electric transportation, X3 indicates The fourth row vector of dimension, Indicates the standard amount of coal consumption used in electric power transportation, Indicates the standard amount of oil consumption used in electric transportation, Indicates the standard amount of gas consumption used in electric power transportation; The power system carbon emission calculation result obtained based on the carbon emission calculation result of the generator set within the region, the carbon emission calculation result of the inter-regional exchange power, and the carbon emission calculation result of the power transportation includes: ； Where, Indicates the calculation results of carbon emissions of the power system.

4. A carbon neutrality simulation method according to claim 1, characterized in that: The carbon sink prediction result obtained by fitting and predicting the total amount of carbon sink includes: Acquiring historical data on forest carbon sinks, and performing fitting prediction on the historical data on forest carbon sinks to obtain a predicted value of forest carbon sinks; Obtaining historical ocean carbon sink data, and performing fitting prediction on the historical ocean carbon sink data to obtain an ocean carbon sink prediction value; Obtaining CCUS carbon capture, utilization, and storage historical data, and performing fitting and prediction on the CCUS carbon capture, utilization, and storage historical data to obtain CCUS carbon capture, utilization, and storage prediction values; A carbon sink prediction result is obtained based on the forest carbon sink prediction value, the ocean carbon sink prediction value and the CCUS carbon capture, utilization and storage prediction value.

5. A carbon neutrality simulation method according to claim 4, characterized in that: The fitting and prediction of the historical data of forest carbon sinks to obtain the predicted value of forest carbon sinks includes: Fitting the historical forest carbon sink data using a linear curve to obtain a first forest carbon sink fitting value; Fitting the historical data of forest carbon sinks using a quadratic curve to obtain a second forest carbon sink fitting value; Fitting the historical data of forest carbon sinks using a logarithmic curve to obtain a third forest carbon sink fitting value; Calculating the variances between the first forest tree carbon sink fitting value, the second forest tree carbon sink fitting value, and the third forest tree carbon sink fitting value and the corresponding actual values, respectively, and determining a first fitting weight corresponding to the first forest tree carbon sink fitting value, a second fitting weight corresponding to the second forest tree carbon sink fitting value, and a third fitting weight corresponding to the third forest tree carbon sink fitting value based on the variances; Obtaining a predicted forest carbon sink value according to the first forest carbon sink fitting value, the second forest carbon sink fitting value, the third forest carbon sink fitting value, the first fitting weight, the second fitting weight, and the third fitting weight; The predicted forest carbon sink value is displayed using a combination of an area chart and a line chart.

6. A carbon neutrality simulation method according to claim 5, characterized in that: The fitting of the historical forest carbon sink data using a linear curve to obtain a first forest carbon sink fitting value includes: ； Where, represents the first forest carbon sink fitting value, α represents the first coefficient to be fitted, t represents the year, and c represents the first intercept term; The fitting of the forest carbon sink historical data using a quadratic curve to obtain a second forest carbon sink fitting value includes: ； Where, represents the second forest carbon sink fitting value, represents the second coefficient to be fitted; The fitting of the historical forest carbon sink data using a logarithmic curve to obtain a third forest carbon sink fitting value includes: ； Where, represents the fitting value of the third forest carbon sink; Obtaining a predicted forest carbon sink value according to the first forest carbon sink fitting value, the second forest carbon sink fitting value, the third forest carbon sink fitting value, the first fitting weight, the second fitting weight, and the third fitting weight includes: ； Where, represents the predicted value of forest carbon sequestration, represents the first fitting weight, represents the second fitting weight, represents the third fitting weight.

7. A carbon neutrality simulation terminal, 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 processor implements the various steps in a carbon neutrality simulation method according to any one of claims 1 to 6.

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