Electricity carbon emission trajectory analysis method and device

Abstract

The invention relates to the technical field of electric carbon emission analysis, in particular to an electric carbon emission trajectory analysis method and device. The technical problem is that an electric carbon emission trajectory analysis method in the prior art always focuses on single-aspect analysis of an electric power system or carbon emission, so that mutual influence and internal relation between the electric power system and the carbon emission are possibly ignored in the analysis process; according to the technical scheme, the electric carbon emission trajectory analysis method comprises the steps that an electric carbon coupling model framework comprising an electric power system module and a carbon emission module is constructed, and model variables and parameters are defined; according to the method, the panoramic electricity-carbon coupling model which is cross-regional, cross-professional and cross-information system is constructed, the electricity-carbon coupling model closely links an electric power system and carbon emission together, and the internal relation and rule between the electric power system and the carbon emission are revealed through comprehensive analysis, so that the effects of different emission reduction strategies can be evaluated more accurately, and the economic benefit is improved. The complex relationship between the power system and the carbon emission is comprehensively analyzed, and a more comprehensive analysis result is provided.

Description

Technical Field

[0001] The present invention relates to the technical field of electric carbon emission analysis, and in particular to an electric carbon emission trajectory analysis method and device. Background Art

[0002] Electricity carbon emission trajectory analysis is a process used to evaluate the relationship between the power system and carbon emissions. It involves multiple aspects, including the energy structure of power production, technology selection, policy orientation, and economic and environmental factors. Scientific methods and technical means are needed to conduct electricity carbon emission trajectory analysis. By obtaining power energy emission data and using trajectory tracking algorithms to accurately count and monitor carbon emissions from power production, consumption, and transmission and distribution systems, this method can achieve real-time tracking and analysis of electricity carbon emission trajectories, providing a basis for formulating dynamic emission reduction strategies. However, the electricity carbon emission trajectory analysis methods under existing technologies often focus on the single-aspect analysis of the power system or carbon emissions, and lack a comprehensive analysis that closely combines the two. This may lead to the neglect of the mutual influence and inherent connection between the power system and carbon emissions during the analysis process. Summary of the invention

[0003] In order to overcome the problem that the electricity carbon emission trajectory analysis methods under existing technologies often focus on the single aspect analysis of the power system or carbon emissions, and lack a comprehensive analysis that closely combines the two, which may lead to the neglect of the mutual influence and inherent connection between the power system and carbon emissions during the analysis process.

[0004] The technical solution of the present invention is: a method for analyzing the trajectory of electric carbon emissions, and the specific steps are as follows:

[0005] S1: Determine the geographical scope, time span, carbon emission sources and emission reduction strategies for analyzing electricity carbon emissions;

[0006] S2: Collect power system data, carbon emission data, relevant policies and regulations, and technological progress information data;

[0007] S3: Construct an electricity-carbon coupling model framework that includes two modules: power system and carbon emissions, and define model variables and parameters;

[0008] S4: Input the collected power system data and carbon emission data into the model, and set reasonable values ​​for the parameters in the model based on the actual situation and the latest research results;

[0009] S5: Run the model under the baseline scenario to obtain the baseline results of power system operation and carbon emissions. According to the research objectives, set different emission reduction strategy scenarios, run the model under different scenarios, and obtain the power system operation and carbon emissions results under each scenario;

[0010] S6: Organize and analyze the simulation results, compare indicators such as carbon emissions and carbon emission intensity under different scenarios, evaluate the effects of various emission reduction strategies, analyze the impact of changes in key parameters in the model on the results, determine the key factors affecting carbon emissions, and propose targeted emission reduction policies and suggestions based on the analysis results;

[0011] S7: Organize the research background, methods, results and analysis into a research report and present them visually;

[0012] S8: Continue to collect actual data on the power system and carbon emissions, monitor the effectiveness of the implementation of emission reduction strategies, and revise and optimize the electricity-carbon coupling model based on actual data and feedback.

[0013] As a preferred method, determine the geographical scope, time span, carbon emission sources and emission reduction strategies for analyzing electricity carbon emissions; the specific steps are as follows:

[0014] S101: Determine the geographical scope of electricity carbon emissions analysis based on research needs;

[0015] S102: Set the time span. According to the research purpose and data traceability, determine the time range to capture the long-term trend of the relationship between the power system and carbon emissions;

[0016] S103: Identify the main sources of carbon emissions, analyze the main sources of carbon emissions in the power system within the region, including coal-fired power generation, oil-fired power generation, etc., and determine their proportion and importance;

[0017] S104: Determine the focus of emission reduction strategies. According to the research objectives and regional characteristics, clarify the main focus of emission reduction strategies, including increasing the proportion of new energy, optimizing the energy structure, and implementing carbon trading policies.

[0018] As a preference, collect power system data, carbon emission data, relevant policies and regulations, and technological progress information data; the specific steps are as follows:

[0019] S201: Obtain power generation data, collect historical power generation data within the research area from power companies, energy statistics agencies or government websites, including power generation of different energy types;

[0020] S202: Organize installed capacity data, collect and organize installed capacity data of various power sources in the research area, including coal power, wind power, and solar power;

[0021] S203: Analyze the energy structure. Based on the power generation data and installed capacity data, analyze the characteristics of the energy structure of the research region, including the proportion of new energy and traditional energy;

[0022] S204: Collecting grid structure diagram and load demand curve data according to the grid structure and load demand;

[0023] S205: Obtain historical carbon emission data, and collect historical carbon emission data within the research area from environmental protection departments, statistical agencies and research institutions;

[0024] S206: Calculate the carbon emission intensity of the research area based on the carbon emission and power generation data, that is, the carbon emission generated per unit of power generation;

[0025] S207: Combine power system data and carbon emission data to assess the carbon footprint of the study area, i.e. the total amount of carbon emissions generated by the power system over its entire life cycle;

[0026] S208: Collect energy policies and organize energy policies related to the power system in the research area; collect and understand environmental protection policies in the research area, including carbon emission restrictions and carbon trading policies;

[0027] S209: Collect information on new energy technologies within the research area.

[0028] As a preferred method, an electric-carbon coupling model framework including two modules, power system and carbon emission, is constructed to define model variables and parameters. The specific steps are as follows:

[0029] S301: The model is divided into two core modules: the power system module and the carbon emission module. The power system module focuses on the production, transmission, distribution and consumption of electricity. The carbon emission module focuses on the calculation of carbon emissions in different energy types and the power production process.

[0030] S302: construct the overall framework of the model, connect the two modules through the coupling mechanism, and form a complete electric-carbon coupling model;

[0031] S303: In the power system module, identify and define key variables, including power generation, installed capacity, and load demand; in the carbon emission module, define key variables, including carbon emissions and carbon emission intensity;

[0032] S304: Determine the parameters involved in the model, including energy conversion efficiency and carbon emission factor;

[0033] S305: Establish a power production model to describe the power production process of different energy types;

[0034] S306: construct a power transmission model to describe the transmission process of power from the production site to the consumption site;

[0035] S307: constructing a power distribution model to distribute power to various consumption ends according to load demand and grid structure;

[0036] S308: Establishing a power consumption model to describe the power consumption of different consumption ends;

[0037] S309: Calculate the carbon emissions of each link based on different energy types and carbon emission factors in the electricity production process;

[0038] S310: Summarize the carbon emissions of each link to obtain the total carbon emissions of the entire power system;

[0039] S311: According to the proportion of different energy types in electricity production and the corresponding carbon emission factors, the power system module and the carbon emission module are tightly coupled in the energy structure;

[0040] S312: Incorporate technological progress factors into the coupling mechanism based on the impact of the development of new energy technologies, energy-saving technologies, and carbon capture and storage technologies on electricity production and carbon emissions;

[0041] S313: In accordance with the guiding role of energy policies, environmental policies, and carbon emission trading system policies and regulations on electricity production and carbon emissions, policy-oriented factors are integrated into the coupling mechanism.

[0042] As a preference, the collected power system data and carbon emission data are input into the model, and reasonable values ​​are set for the parameters in the model according to the actual situation and the latest research results; the specific steps are as follows:

[0043] S401: Classify and organize the power system data and carbon emission data collected in the early stage; the power system data includes: power generation, installed capacity, energy structure, grid structure, and load demand; the carbon emission data includes: historical carbon emissions, carbon emission intensity, and carbon footprint;

[0044] S402: According to the requirements of the electric-carbon coupling model, the sorted data is converted into a format recognizable by the model;

[0045] S403: importing the format-converted data into the electric-carbon coupling model, and assigning the data to corresponding modules and variables according to the input requirements of the model;

[0046] S404: According to the definition of the electric-carbon coupling model, all parameters involved in the model are identified, and the meaning, function and position of each parameter in the model are determined;

[0047] S405: Set values ​​for parameters in the model based on actual conditions and the latest research results;

[0048] S406: For parameters with clear numerical basis, including energy conversion efficiency and carbon emission factor, relevant research results and official data are directly adopted;

[0049] S407: For parameters that are difficult to determine directly, including policy impact coefficients and technological progress rates, estimates are made using historical data fitting methods;

[0050] S408: Verify the set parameter values ​​to ensure that they are within a reasonable range and meet the operation requirements of the model;

[0051] S409: According to the model operation results and actual conditions, the parameter values ​​are adjusted and optimized, and through continuous iteration and trial and error, a combination of parameter values ​​that makes the model results more accurate and in line with reality is found.

[0052] As a preference, the model is run under the baseline scenario to obtain the baseline results of power system operation and carbon emissions. According to the research objectives, different emission reduction strategy scenarios are set, and the model is run under different scenarios to obtain the power system operation and carbon emissions results under each scenario. The specific steps are as follows:

[0053] S501: Define the specific contents of the baseline scenario, including the current structure of the power system, energy use ratio, and carbon emission intensity;

[0054] S502: Setting the time range of simulation;

[0055] S503: Input the power system data and carbon emission data collected in the early stage into the model as the initial data of the baseline scenario;

[0056] S504: Run the electricity-carbon coupling model under the baseline scenario to simulate the operation and carbon emission process of the power system, reflecting the entire process of electricity production, transmission, distribution and consumption, as well as the carbon emissions generated in these processes;

[0057] S505: extracting power system operation data and carbon emission data under the baseline scenario from the model, including power generation, carbon emissions, and carbon emission intensity;

[0058] S506: Organize and analyze the data to form the power system operation and carbon emission benchmark results under the baseline scenario;

[0059] S507: Determine the research objectives of emission reduction strategies, including reducing carbon emissions, increasing the proportion of new energy, and optimizing energy structure;

[0060] S508: Set different emission reduction strategy scenarios according to the research objectives; specifically include:

[0061] Scenario for increasing the proportion of renewable energy: Set a target for the proportion of renewable energy in the power system and adjust the energy structure to achieve the target.

[0062] Implementation of carbon trading policy scenario: setting the trading price and volume parameters of carbon emission rights, and simulating the impact of carbon trading policies on power system operation and carbon emissions.

[0063] Energy-saving technology promotion scenario: set the penetration rate of energy-saving technologies and energy-saving effect parameters, and simulate the improvement effect of energy-saving technology promotion on power system operation and carbon emissions;

[0064] S509: For each emission reduction strategy scenario, determine the variables and parameters involved, including the proportion of new energy, the price of carbon emission rights, and the penetration rate of energy-saving technologies; set the specific values ​​and ranges of these parameters;

[0065] S510: Input the set emission reduction strategy scenario data into the model to replace the corresponding data under the baseline scenario;

[0066] S511: Run the electricity-carbon coupling model under different scenarios to simulate the changes in power system operation and carbon emissions;

[0067] S512: Extracting power system operation data and carbon emission data under each scenario from the model, including power generation, carbon emissions, and carbon emission intensity;

[0068] S513: Organize and analyze the data to form the power system operation and carbon emission results under various scenarios;

[0069] S514: Compare the results of each scenario with the baseline scenario, analyze the impact of emission reduction strategies on power system operation and carbon emissions, and evaluate the advantages and disadvantages of different emission reduction strategies.

[0070] As a priority, the simulation results are collated and analyzed, and indicators such as carbon emissions and carbon emission intensity under different scenarios are compared. The effects of various emission reduction strategies are evaluated, the impact of changes in key parameters in the model on the results is analyzed, and the key factors affecting carbon emissions are determined. Based on the analysis results, targeted emission reduction policies and suggestions are proposed; the specific steps are as follows:

[0071] S601: Obtain power system operation and carbon emission result data under all scenarios from model simulation and scenario analysis;

[0072] S602: Classify and sort the data by time, scenario, and energy type;

[0073] S603: Extract key indicators from the collated data, including carbon emissions, carbon emission intensity, and new energy proportion;

[0074] S604: Compare indicators such as carbon emissions and carbon emission intensity under different scenarios horizontally, analyze the differences between scenarios, and preliminarily judge the effects of various emission reduction strategies;

[0075] S605: Based on the comparison results, evaluate the degree of reduction of carbon emissions by each emission reduction strategy and analyze the impact of the emission reduction strategy on the operation of the power system;

[0076] S606: Comprehensively evaluate various emission reduction strategies based on factors such as carbon emission reduction and power system operation stability, and determine the optimal combination of emission reduction strategies;

[0077] S607: Identify key parameters from the electricity-carbon coupling model, including energy conversion efficiency and carbon emission factors, and determine the range of variation of these parameters and the degree of impact on the results;

[0078] S608: By adjusting the values ​​of key parameters, observing the changes in model results, and analyzing the impact of parameter changes on carbon emissions and carbon emission intensity indicators;

[0079] S609: Based on the sensitivity test results, identify the key factors affecting carbon emissions, analyze the impact of these factors on the formulation and implementation of emission reduction strategies, and propose corresponding response measures.

[0080] As a preference, the research background, methods, results and analysis are organized into a research report and visualized; the specific steps are as follows:

[0081] S801: Collect and organize all data generated during the analysis process;

[0082] S802: Construct the overall structure of the report, including title, abstract, table of contents, main text, conclusion, and references;

[0083] S803: Arrange the analysis data into a report format according to the report structure;

[0084] S804: Based on the content of the research report, create charts and report summaries, highlight key information and research results, and present the report visually.

[0085] As a preferred method, actual data on power systems and carbon emissions are continuously collected to monitor the implementation effect of emission reduction strategies. Based on actual data and feedback, the power-carbon coupling model is revised and optimized. The specific steps are as follows:

[0086] S901: Determine the power system operation and carbon emission indicators that need to be monitored based on the research objectives and emission reduction strategies;

[0087] S902: Continuously collect actual data on the power system and carbon emissions through power system monitoring equipment and carbon emission monitoring stations;

[0088] S903: Process and analyze the collected data, extract key information and trends, compare with the model simulation results, and analyze the differences and causes;

[0089] S904: Compare the actual data with the model simulation results, analyze the differences and causes, and determine where the model needs to be corrected and optimized;

[0090] S905: Correct and adjust the parameters in the model based on actual data and feedback;

[0091] S906: Verify the effect of the optimized model through simulation and experiments.

[0092] The electric carbon emission trajectory analysis device includes:

[0093] System initialization and parameter setting module, which is used to determine the geographical scope, time span, carbon emission sources and emission reduction strategies for analysis, and collect and organize power system data, carbon emission data, relevant policies and regulations, and technological progress information;

[0094] The electricity-carbon coupling model construction module is used to construct an electricity-carbon coupling model framework that includes two major modules: power system and carbon emissions, define model variables and parameters, and establish each sub-model;

[0095] The data input and parameter setting module is used to input the collected data into the model and set reasonable values ​​for the parameters in the model according to the actual situation and the latest research results;

[0096] The scenario simulation and analysis module is used to run the model under the baseline scenario to obtain the baseline results of power system operation and carbon emissions, set different emission reduction strategy scenarios, simulate and obtain the results under each scenario;

[0097] The result collation and report generation module is used to collate and analyze simulation results, compare indicators under different scenarios, evaluate the effects of emission reduction strategies, generate research reports and perform visual presentations;

[0098] Model correction and optimization module, which is used to continuously collect actual data on power systems and carbon emissions, monitor the implementation effect of emission reduction strategies, and correct and optimize the model;

[0099] The user interaction and interface display module is used to provide a user interface that enables users to easily configure model parameters, view analysis results, and manage data.

[0100] Beneficial effects of the present invention:

[0101] 1. Compared with the existing electric carbon emission trajectory analysis methods, which often focus on the single analysis of the power system or carbon emissions, and lack a comprehensive analysis that closely combines the two, this may lead to the neglect of the mutual influence and internal connection between the power system and carbon emissions during the analysis process; this invention constructs a panoramic electric-carbon coupling model across regions, disciplines, and information systems. The electric-carbon coupling model closely links the power system with carbon emissions, reveals the internal connection and laws between them through comprehensive analysis, and helps to more accurately evaluate the effects of different emission reduction strategies. It conducts a comprehensive analysis of the complex relationship between the power system and carbon emissions, and can consider the impact of multiple factors on carbon emissions, providing more comprehensive analysis results;

[0102] 2. Divide the model into two core modules: power system module and carbon emission module; the power system module focuses on the production, transmission, distribution and consumption of electricity; the carbon emission module focuses on the calculation of carbon emissions in different energy types and power production processes; build the overall framework of the model, connect the two modules through the coupling mechanism, and form a complete electric-carbon coupling model; in the power system module, identify and define key variables, including power generation, installed capacity, and load demand; in the carbon emission module, define key variables, including carbon emissions and carbon emission intensity; determine the parameters involved in the model, including energy conversion efficiency and carbon emission factor; establish a power production model to describe the power production process of different energy types; construct a power transmission model to describe the transmission process of electricity from the production site to the consumption site; construct a power distribution model to distribute electricity to each consumer end according to load demand and grid structure; establish a power consumption model to describe the power consumption of different consumer ends; according to different energy sources The carbon emission factors in the power generation process and the types of energy are used to calculate the carbon emissions of each link; the carbon emissions of each link are summarized to obtain the total carbon emissions of the entire power system; according to the proportion of different energy types in power production and the corresponding carbon emission factors, the power system module and the carbon emission module are tightly coupled in the energy structure; according to the impact of the development of new energy technologies, energy-saving technologies, and carbon capture and storage technologies on power production and carbon emissions, the technological progress factor is incorporated into the coupling mechanism; according to the guiding role of energy policies, environmental protection policies, and carbon emission trading system policies and regulations on power production and carbon emissions, the policy-oriented factors are incorporated into the coupling mechanism; thus, the power-carbon coupling model closely links the power system with carbon emissions, and reveals the inherent connections and laws between them through comprehensive analysis, which helps to more accurately evaluate the effects of different emission reduction strategies, conduct a comprehensive analysis of the complex relationship between the power system and carbon emissions, and can consider the impact of multiple factors on carbon emissions, providing a more comprehensive analysis result;

[0103] 3. By running the model under the baseline scenario, we can obtain the baseline results of power system operation and carbon emissions. According to the research objectives, we set different emission reduction strategy scenarios, run the model under different scenarios, and obtain the power system operation and carbon emission results under each scenario. We organize and analyze the simulation results, compare indicators such as carbon emissions and carbon emission intensity under different scenarios, evaluate the effects of various emission reduction strategies, analyze the impact of changes in key parameters in the model on the results, and determine the key factors affecting carbon emissions. Based on the analysis results, we put forward targeted emission reduction policies and suggestions, which will help to formulate more effective emission reduction strategies and policy measures and promote the low-carbon transformation and sustainable development of the power industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0104] Figure 1 What is shown is a schematic diagram of the working process of the electric carbon emission trajectory analysis device of the present invention;

[0105] Figure 2 Shown is a schematic diagram of the scenario simulation process of the electric carbon emission trajectory analysis method of the present invention. DETAILED DESCRIPTION

[0106] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0107] See also Figure 1-2 The present invention provides an embodiment: a method for analyzing the trajectory of carbon emissions from electricity, the specific steps of which are as follows:

[0108] S1: Determine the geographical scope, time span, carbon emission sources and emission reduction strategies for analyzing electricity carbon emissions;

[0109] S2: Collect power system data, carbon emission data, relevant policies and regulations, and technological progress information data;

[0110] S3: Construct an electricity-carbon coupling model framework that includes two modules: power system and carbon emissions, and define model variables and parameters;

[0111] S4: Input the collected power system data and carbon emission data into the model, and set reasonable values ​​for the parameters in the model based on the actual situation and the latest research results;

[0112] S5: Run the model under the baseline scenario to obtain the baseline results of power system operation and carbon emissions. According to the research objectives, set different emission reduction strategy scenarios, run the model under different scenarios, and obtain the power system operation and carbon emissions results under each scenario;

[0113] S6: Organize and analyze the simulation results, compare indicators such as carbon emissions and carbon emission intensity under different scenarios, evaluate the effects of various emission reduction strategies, analyze the impact of changes in key parameters in the model on the results, determine the key factors affecting carbon emissions, and propose targeted emission reduction policies and suggestions based on the analysis results;

[0114] S7: Organize the research background, methods, results and analysis into a research report and present them visually;

[0115] S8: Continue to collect actual data on the power system and carbon emissions, monitor the effectiveness of the implementation of emission reduction strategies, and revise and optimize the electricity-carbon coupling model based on actual data and feedback.

[0116] As a preferred method, determine the geographical scope, time span, carbon emission sources and emission reduction strategies for analyzing electricity carbon emissions; the specific steps are as follows:

[0117] S101: Determine the geographical scope of electricity carbon emissions analysis based on research needs;

[0118] S102: Set the time span. According to the research purpose and data traceability, determine the time range to capture the long-term trend of the relationship between the power system and carbon emissions;

[0119] S103: Identify the main sources of carbon emissions, analyze the main sources of carbon emissions in the power system within the region, including coal-fired power generation, oil-fired power generation, etc., and determine their proportion and importance;

[0120] S104: Determine the focus of emission reduction strategies. According to the research objectives and regional characteristics, clarify the main focus of emission reduction strategies, including increasing the proportion of new energy, optimizing the energy structure, and implementing carbon trading policies.

[0121] As a preference, collect power system data, carbon emission data, relevant policies and regulations, and technological progress information data; the specific steps are as follows:

[0122] S201: Obtain power generation data, collect historical power generation data within the research area from power companies, energy statistics agencies or government websites, including power generation of different energy types;

[0123] S202: Organize installed capacity data, collect and organize installed capacity data of various power sources in the research area, including coal power, wind power, and solar power;

[0124] S203: Analyze the energy structure. Based on the power generation data and installed capacity data, analyze the characteristics of the energy structure of the research region, including the proportion of new energy and traditional energy;

[0125] S204: Collecting grid structure diagram and load demand curve data according to the grid structure and load demand;

[0126] S205: Obtain historical carbon emission data, and collect historical carbon emission data within the research area from environmental protection departments, statistical agencies and research institutions;

[0127] S206: Calculate the carbon emission intensity of the research area based on the carbon emission and power generation data, that is, the carbon emission generated per unit of power generation;

[0128] S207: Combine power system data and carbon emission data to assess the carbon footprint of the study area, i.e. the total amount of carbon emissions generated by the power system over its entire life cycle;

[0129] S208: Collect energy policies and organize energy policies related to the power system in the research area; collect and understand environmental protection policies in the research area, including carbon emission restrictions and carbon trading policies;

[0130] S209: Collect information on new energy technologies within the research area.

[0131] As a preferred method, an electric-carbon coupling model framework including two modules, power system and carbon emission, is constructed to define model variables and parameters. The specific steps are as follows:

[0132] S301: The model is divided into two core modules: the power system module and the carbon emission module. The power system module focuses on the production, transmission, distribution and consumption of electricity. The carbon emission module focuses on the calculation of carbon emissions in different energy types and the power production process.

[0133] S302: construct the overall framework of the model, connect the two modules through the coupling mechanism, and form a complete electric-carbon coupling model;

[0134] S303: In the power system module, identify and define key variables, including power generation, installed capacity, and load demand; in the carbon emission module, define key variables, including carbon emissions and carbon emission intensity;

[0135] S304: Determine the parameters involved in the model, including energy conversion efficiency and carbon emission factor;

[0136] S305: Establish a power production model to describe the power production process of different energy types;

[0137] S306: construct a power transmission model to describe the transmission process of power from the production site to the consumption site;

[0138] S307: constructing a power distribution model to distribute power to various consumption ends according to load demand and grid structure;

[0139] S308: Establishing a power consumption model to describe the power consumption of different consumption ends;

[0140] S309: Calculate the carbon emissions of each link based on different energy types and carbon emission factors in the electricity production process;

[0141] S310: Summarize the carbon emissions of each link to obtain the total carbon emissions of the entire power system;

[0142] S311: According to the proportion of different energy types in electricity production and the corresponding carbon emission factors, the power system module and the carbon emission module are tightly coupled in the energy structure;

[0143] S312: Incorporate technological progress factors into the coupling mechanism based on the impact of the development of new energy technologies, energy-saving technologies, and carbon capture and storage technologies on electricity production and carbon emissions;

[0144] S313: In accordance with the guiding role of energy policies, environmental policies, and carbon emission trading system policies and regulations on electricity production and carbon emissions, policy-oriented factors are integrated into the coupling mechanism.

[0145] As a preference, the collected power system data and carbon emission data are input into the model, and reasonable values ​​are set for the parameters in the model according to the actual situation and the latest research results; the specific steps are as follows:

[0146] S401: Classify and organize the power system data and carbon emission data collected in the early stage; the power system data includes: power generation, installed capacity, energy structure, grid structure, and load demand; the carbon emission data includes: historical carbon emissions, carbon emission intensity, and carbon footprint;

[0147] S402: According to the requirements of the electric-carbon coupling model, the sorted data is converted into a format recognizable by the model;

[0148] S403: importing the format-converted data into the electric-carbon coupling model, and assigning the data to corresponding modules and variables according to the input requirements of the model;

[0149] S404: According to the definition of the electric-carbon coupling model, all parameters involved in the model are identified, and the meaning, function and position of each parameter in the model are determined;

[0150] S405: Set values ​​for parameters in the model based on actual conditions and the latest research results;

[0151] S406: For parameters with clear numerical basis, including energy conversion efficiency and carbon emission factor, relevant research results and official data are directly adopted;

[0152] S407: For parameters that are difficult to determine directly, including policy impact coefficients and technological progress rates, estimates are made using historical data fitting methods;

[0153] S408: Verify the set parameter values ​​to ensure that they are within a reasonable range and meet the operation requirements of the model;

[0154] S409: According to the model operation results and actual conditions, the parameter values ​​are adjusted and optimized, and through continuous iteration and trial and error, a combination of parameter values ​​that makes the model results more accurate and in line with reality is found.

[0155] As a preference, the model is run under the baseline scenario to obtain the baseline results of power system operation and carbon emissions. According to the research objectives, different emission reduction strategy scenarios are set, and the model is run under different scenarios to obtain the power system operation and carbon emissions results under each scenario. The specific steps are as follows:

[0156] S501: Define the specific contents of the baseline scenario, including the current structure of the power system, energy use ratio, and carbon emission intensity;

[0157] S502: Setting the time range of simulation;

[0158] S503: Input the power system data and carbon emission data collected in the early stage into the model as the initial data of the baseline scenario;

[0159] S504: Run the electricity-carbon coupling model under the baseline scenario to simulate the operation and carbon emission process of the power system, reflecting the entire process of electricity production, transmission, distribution and consumption, as well as the carbon emissions generated in these processes;

[0160] S505: extracting power system operation data and carbon emission data under the baseline scenario from the model, including power generation, carbon emissions, and carbon emission intensity;

[0161] S506: Organize and analyze the data to form the power system operation and carbon emission benchmark results under the baseline scenario;

[0162] S507: Determine the research objectives of emission reduction strategies, including reducing carbon emissions, increasing the proportion of new energy, and optimizing energy structure;

[0163] S508: Set different emission reduction strategy scenarios according to the research objectives; specifically include:

[0164] Scenario for increasing the proportion of renewable energy: Set a target for the proportion of renewable energy in the power system and adjust the energy structure to achieve the target.

[0165] Implementation of carbon trading policy scenario: setting the trading price and volume parameters of carbon emission rights, and simulating the impact of carbon trading policies on power system operation and carbon emissions.

[0166] Energy-saving technology promotion scenario: set the penetration rate of energy-saving technologies and energy-saving effect parameters, and simulate the improvement effect of energy-saving technology promotion on power system operation and carbon emissions;

[0167] S509: For each emission reduction strategy scenario, determine the variables and parameters involved, including the proportion of new energy, the price of carbon emission rights, and the penetration rate of energy-saving technologies; set the specific values ​​and ranges of these parameters;

[0168] S510: Input the set emission reduction strategy scenario data into the model to replace the corresponding data under the baseline scenario;

[0169] S511: Run the electricity-carbon coupling model under different scenarios to simulate the changes in power system operation and carbon emissions;

[0170] S512: Extracting power system operation data and carbon emission data under each scenario from the model, including power generation, carbon emissions, and carbon emission intensity;

[0171] S513: Organize and analyze the data to form the power system operation and carbon emission results under various scenarios;

[0172] S514: Compare the results of each scenario with the baseline scenario, analyze the impact of emission reduction strategies on power system operation and carbon emissions, and evaluate the advantages and disadvantages of different emission reduction strategies.

[0173] As a priority, the simulation results are collated and analyzed, and indicators such as carbon emissions and carbon emission intensity under different scenarios are compared. The effects of various emission reduction strategies are evaluated, the impact of changes in key parameters in the model on the results is analyzed, and the key factors affecting carbon emissions are determined. Based on the analysis results, targeted emission reduction policies and suggestions are proposed; the specific steps are as follows:

[0174] S601: Obtain power system operation and carbon emission result data under all scenarios from model simulation and scenario analysis;

[0175] S602: Classify and sort the data by time, scenario, and energy type;

[0176] S603: Extract key indicators from the collated data, including carbon emissions, carbon emission intensity, and new energy proportion;

[0177] S604: Compare indicators such as carbon emissions and carbon emission intensity under different scenarios horizontally, analyze the differences between scenarios, and preliminarily judge the effects of various emission reduction strategies;

[0178] S605: Based on the comparison results, evaluate the degree of reduction of carbon emissions by each emission reduction strategy and analyze the impact of the emission reduction strategy on the operation of the power system;

[0179] S606: Comprehensively evaluate various emission reduction strategies based on factors such as carbon emission reduction and power system operation stability, and determine the optimal combination of emission reduction strategies;

[0180] S607: Identify key parameters from the electricity-carbon coupling model, including energy conversion efficiency and carbon emission factors, and determine the range of variation of these parameters and the degree of impact on the results;

[0181] S608: By adjusting the values ​​of key parameters, observing the changes in model results, and analyzing the impact of parameter changes on carbon emissions and carbon emission intensity indicators;

[0182] S609: Based on the sensitivity test results, identify the key factors affecting carbon emissions, analyze the impact of these factors on the formulation and implementation of emission reduction strategies, and propose corresponding response measures.

[0183] As a preference, the research background, methods, results and analysis are organized into a research report and visualized; the specific steps are as follows:

[0184] S801: Collect and organize all data generated during the analysis process;

[0185] S802: Construct the overall structure of the report, including title, abstract, table of contents, main text, conclusion, and references;

[0186] S803: Arrange the analysis data into a report format according to the report structure;

[0187] S804: Based on the content of the research report, create charts and report summaries, highlight key information and research results, and present the report visually.

[0188] As a preferred method, actual data on power systems and carbon emissions are continuously collected to monitor the implementation effect of emission reduction strategies. Based on actual data and feedback, the power-carbon coupling model is revised and optimized. The specific steps are as follows:

[0189] S901: Determine the power system operation and carbon emission indicators that need to be monitored based on the research objectives and emission reduction strategies;

[0190] S902: Continuously collect actual data on the power system and carbon emissions through power system monitoring equipment and carbon emission monitoring stations;

[0191] S903: Process and analyze the collected data, extract key information and trends, compare with the model simulation results, and analyze the differences and causes;

[0192] S904: Compare the actual data with the model simulation results, analyze the differences and causes, and determine where the model needs to be corrected and optimized;

[0193] S905: Correct and adjust the parameters in the model based on actual data and feedback;

[0194] S906: Verify the effect of the optimized model through simulation and experiments.

[0195] The electric carbon emission trajectory analysis device includes:

[0196] System initialization and parameter setting module, which is used to determine the geographical scope, time span, carbon emission sources and emission reduction strategies for analysis, and collect and organize power system data, carbon emission data, relevant policies and regulations, and technological progress information;

[0197] The electricity-carbon coupling model construction module is used to construct an electricity-carbon coupling model framework that includes two major modules: power system and carbon emissions, define model variables and parameters, and establish each sub-model;

[0198] The data input and parameter setting module is used to input the collected data into the model and set reasonable values ​​for the parameters in the model according to the actual situation and the latest research results;

[0199] The scenario simulation and analysis module is used to run the model under the baseline scenario to obtain the baseline results of power system operation and carbon emissions, set different emission reduction strategy scenarios, simulate and obtain the results under each scenario;

[0200] The result collation and report generation module is used to collate and analyze simulation results, compare indicators under different scenarios, evaluate the effects of emission reduction strategies, generate research reports and perform visual presentations;

[0201] Model correction and optimization module, which is used to continuously collect actual data on power systems and carbon emissions, monitor the implementation effect of emission reduction strategies, and correct and optimize the model;

[0202] The user interaction and interface display module is used to provide a user interface that enables users to easily configure model parameters, view analysis results, and manage data.

[0203] The embodiments of the present invention are described in detail above with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge scope of those skilled in the art without departing from the spirit of the present invention.

Claims

1. Electricity carbon emission trajectory analysis method; characterized by: The specific steps are as follows: S1: Determine the geographical scope, time span, carbon emission sources and emission reduction strategies for analyzing electricity carbon emissions; S2: Collect power system data, carbon emission data, relevant policies and regulations, and technological progress information data; S3: Construct an electricity-carbon coupling model framework that includes two modules: power system and carbon emissions, and define model variables and parameters; S4: Input the collected power system data and carbon emission data into the model, and set reasonable values ​​for the parameters in the model based on the actual situation and the latest research results; S5: Run the model under the baseline scenario to obtain the baseline results of power system operation and carbon emissions. According to the research objectives, set different emission reduction strategy scenarios, run the model under different scenarios, and obtain the power system operation and carbon emissions results under each scenario; S6: Organize and analyze the simulation results, compare indicators such as carbon emissions and carbon emission intensity under different scenarios, evaluate the effects of various emission reduction strategies, analyze the impact of changes in key parameters in the model on the results, determine the key factors affecting carbon emissions, and propose targeted emission reduction policies and suggestions based on the analysis results; S7: Organize the research background, methods, results and analysis into a research report and present them visually; S8: Continue to collect actual data on the power system and carbon emissions, monitor the effectiveness of the implementation of emission reduction strategies, and revise and optimize the electricity-carbon coupling model based on actual data and feedback.

2. The method for analyzing the trajectory of electric carbon emissions according to claim 1, characterized in that: Determine the geographical scope, time span, carbon emission sources and emission reduction strategies for analyzing electricity carbon emissions; the specific steps are as follows: S101: Determine the geographical scope of electricity carbon emissions analysis based on research needs; S102: Set the time span. According to the research purpose and data traceability, determine the time range to capture the long-term trend of the relationship between the power system and carbon emissions; S103: Identify the main sources of carbon emissions, analyze the main sources of carbon emissions in the power system within the region, including coal-fired power generation, oil-fired power generation, etc., and determine their proportion and importance; S104: Determine the focus of emission reduction strategies. According to the research objectives and regional characteristics, clarify the main focus of emission reduction strategies, including increasing the proportion of new energy, optimizing the energy structure, and implementing carbon trading policies.

3. The electric carbon emission trajectory analysis method according to claim 2 is characterized in that: Collect power system data, carbon emission data, relevant policies and regulations, and technological progress information data; the specific steps are as follows: S201: Obtain power generation data, collect historical power generation data within the research area from power companies, energy statistics agencies or government websites, including power generation of different energy types; S202: Organize installed capacity data, collect and organize installed capacity data of various power sources in the research area, including coal power, wind power, and solar power; S203: Analyze the energy structure. Based on the power generation data and installed capacity data, analyze the characteristics of the energy structure of the research region, including the proportion of new energy and traditional energy; S204: Collecting grid structure diagram and load demand curve data according to the grid structure and load demand; S205: Obtain historical carbon emission data, and collect historical carbon emission data within the research area from environmental protection departments, statistical agencies and research institutions; S206: Calculate the carbon emission intensity of the research area based on the carbon emission and power generation data, that is, the carbon emission generated per unit of power generation; S207: Combine power system data and carbon emission data to assess the carbon footprint of the study area, i.e. the total amount of carbon emissions generated by the power system over its entire life cycle; S208: Collect energy policies and organize energy policies related to the power system in the research area; collect and understand environmental protection policies in the research area, including carbon emission restrictions and carbon trading policies; S209: Collect information on new energy technologies within the research area.

4. The method for analyzing the trajectory of electric carbon emissions according to claim 3, characterized in that: Construct an electric-carbon coupling model framework that includes two modules: power system and carbon emissions, and define model variables and parameters; the specific steps are as follows: S301: The model is divided into two core modules: the power system module and the carbon emission module. The power system module focuses on the production, transmission, distribution and consumption of electricity. The carbon emission module focuses on the calculation of carbon emissions in different energy types and the power production process. S302: construct the overall framework of the model, connect the two modules through the coupling mechanism, and form a complete electric-carbon coupling model; S303: In the power system module, identify and define key variables, including power generation, installed capacity, and load demand; in the carbon emission module, define key variables, including carbon emissions and carbon emission intensity; S304: Determine the parameters involved in the model, including energy conversion efficiency and carbon emission factor; S305: Establish a power production model to describe the power production process of different energy types; S306: construct a power transmission model to describe the transmission process of power from the production site to the consumption site; S307: constructing a power distribution model to distribute power to various consumption ends according to load demand and grid structure; S308: Establishing a power consumption model to describe the power consumption of different consumption ends; S309: Calculate the carbon emissions of each link based on different energy types and carbon emission factors in the electricity production process; S310: Summarize the carbon emissions of each link to obtain the total carbon emissions of the entire power system; S311: According to the proportion of different energy types in electricity production and the corresponding carbon emission factors, the power system module and the carbon emission module are tightly coupled in the energy structure; S312: Incorporate technological progress factors into the coupling mechanism based on the impact of the development of new energy technologies, energy-saving technologies, and carbon capture and storage technologies on electricity production and carbon emissions; S313: In accordance with the guiding role of energy policies, environmental policies, and carbon emission trading system policies and regulations on electricity production and carbon emissions, policy-oriented factors are integrated into the coupling mechanism.

5. The method for analyzing the trajectory of electric carbon emissions according to claim 4, characterized in that: Input the collected power system data and carbon emission data into the model, and set reasonable values ​​for the parameters in the model based on the actual situation and the latest research results; the specific steps are as follows: S401: Classify and organize the power system data and carbon emission data collected in the early stage; Power system data include: power generation, installed capacity, energy structure, grid structure, and load demand; carbon emission data include: historical carbon emissions, carbon emission intensity, and carbon footprint; S402: According to the requirements of the electric-carbon coupling model, the sorted data is converted into a format recognizable by the model; S403: importing the format-converted data into the electric-carbon coupling model, and assigning the data to corresponding modules and variables according to the input requirements of the model; S404: According to the definition of the electric-carbon coupling model, all parameters involved in the model are identified, and the meaning, function and position of each parameter in the model are determined; S405: Set values ​​for parameters in the model based on actual conditions and the latest research results; S406: For parameters with clear numerical basis, including energy conversion efficiency and carbon emission factor, relevant research results and official data are directly adopted; S407: For parameters that are difficult to determine directly, including policy impact coefficients and technological progress rates, estimates are made using historical data fitting methods; S408: Verify the set parameter values ​​to ensure that they are within a reasonable range and meet the operation requirements of the model; S409: According to the model operation results and actual conditions, the parameter values ​​are adjusted and optimized, and through continuous iteration and trial and error, a combination of parameter values ​​that makes the model results more accurate and in line with reality is found.

6. The method for analyzing the trajectory of electric carbon emissions according to claim 5, characterized in that: Run the model under the baseline scenario to obtain the baseline results of power system operation and carbon emissions. According to the research objectives, set different emission reduction strategy scenarios, run the model under different scenarios, and obtain the power system operation and carbon emissions results under each scenario. The specific steps are as follows: S501: Define the specific contents of the baseline scenario, including the current structure of the power system, energy use ratio, and carbon emission intensity; S502: Setting the time range of simulation; S503: Input the power system data and carbon emission data collected in the early stage into the model as the initial data of the baseline scenario; S504: Run the electricity-carbon coupling model under the baseline scenario to simulate the operation and carbon emission process of the power system, reflecting the entire process of electricity production, transmission, distribution and consumption, as well as the carbon emissions generated in these processes; S505: extracting power system operation data and carbon emission data under the baseline scenario from the model, including power generation, carbon emissions, and carbon emission intensity; S506: Organize and analyze the data to form the power system operation and carbon emission benchmark results under the baseline scenario; S507: Determine the research objectives of emission reduction strategies, including reducing carbon emissions, increasing the proportion of new energy, and optimizing energy structure; S508: Set different emission reduction strategy scenarios according to the research objectives; specifically include: Scenario for increasing the proportion of renewable energy: Set a target for the proportion of renewable energy in the power system and adjust the energy structure to achieve the target. Implementation of carbon trading policy scenario: setting the trading price and volume parameters of carbon emission rights, and simulating the impact of carbon trading policies on power system operation and carbon emissions. Energy-saving technology promotion scenario: set the penetration rate of energy-saving technologies and energy-saving effect parameters, and simulate the improvement effect of energy-saving technology promotion on power system operation and carbon emissions; S509: For each emission reduction strategy scenario, determine the variables and parameters involved, including the proportion of new energy, the price of carbon emission rights, and the penetration rate of energy-saving technologies; set the specific values ​​and ranges of these parameters; S510: Input the set emission reduction strategy scenario data into the model to replace the corresponding data under the baseline scenario; S511: Run the electricity-carbon coupling model under different scenarios to simulate the changes in power system operation and carbon emissions; S512: Extracting power system operation data and carbon emission data under each scenario from the model, including power generation, carbon emissions, and carbon emission intensity; S513: Organize and analyze the data to form the power system operation and carbon emission results under various scenarios; S514: Compare the results of each scenario with the baseline scenario, analyze the impact of emission reduction strategies on power system operation and carbon emissions, and evaluate the advantages and disadvantages of different emission reduction strategies.

7. The method for analyzing the trajectory of electric carbon emissions according to claim 6, characterized in that: Organize and analyze the simulation results, compare indicators such as carbon emissions and carbon emission intensity under different scenarios, evaluate the effects of various emission reduction strategies, analyze the impact of changes in key parameters in the model on the results, determine the key factors affecting carbon emissions, and propose targeted emission reduction policies and suggestions based on the analysis results; the specific steps are as follows: S601: Obtain power system operation and carbon emission result data under all scenarios from model simulation and scenario analysis; S602: Classify and sort the data by time, scenario, and energy type; S603: Extract key indicators from the collated data, including carbon emissions, carbon emission intensity, and new energy proportion; S604: Compare indicators such as carbon emissions and carbon emission intensity under different scenarios horizontally, analyze the differences between scenarios, and preliminarily judge the effects of various emission reduction strategies; S605: Based on the comparison results, evaluate the degree of reduction of carbon emissions by each emission reduction strategy and analyze the impact of the emission reduction strategy on the operation of the power system; S606: Comprehensively evaluate various emission reduction strategies based on factors such as carbon emission reduction and power system operation stability, and determine the optimal combination of emission reduction strategies; S607: Identify key parameters from the electricity-carbon coupling model, including energy conversion efficiency and carbon emission factors, and determine the range of variation of these parameters and the degree of impact on the results; S608: By adjusting the values ​​of key parameters, observing the changes in model results, and analyzing the impact of parameter changes on carbon emissions and carbon emission intensity indicators; S609: Based on the sensitivity test results, identify the key factors affecting carbon emissions, analyze the impact of these factors on the formulation and implementation of emission reduction strategies, and propose corresponding response measures.

8. The method for analyzing the trajectory of electric carbon emissions according to claim 7, characterized in that: Organize the research background, methods, results and analysis into a research report and present it visually; the specific steps are as follows: S801: Collect and organize all data generated during the analysis process; S802: Construct the overall structure of the report, including title, abstract, table of contents, main text, conclusion, and references; S803: Arrange the analysis data into a report format according to the report structure; S804: Based on the content of the research report, create charts and report summaries, highlight key information and research results, and present the report visually.

9. The method for analyzing the electric carbon emission trajectory according to claim 8, characterized in that: Continuously collect actual data on power systems and carbon emissions, monitor the implementation effect of emission reduction strategies, and revise and optimize the power-carbon coupling model based on actual data and feedback; the specific steps are as follows: S901: Determine the power system operation and carbon emission indicators that need to be monitored based on the research objectives and emission reduction strategies; S902: Continuously collect actual data on the power system and carbon emissions through power system monitoring equipment and carbon emission monitoring stations; S903: Process and analyze the collected data, extract key information and trends, compare with the model simulation results, and analyze the differences and causes; S904: Compare the actual data with the model simulation results, analyze the differences and causes, and determine where the model needs to be corrected and optimized; S905: Correct and adjust the parameters in the model based on actual data and feedback; S906: Verify the effect of the optimized model through simulation and experiments.

10. Electric carbon emission trajectory analysis device, characterized by: Included are: System initialization and parameter setting module, which is used to determine the geographical scope, time span, carbon emission sources and emission reduction strategies for analysis, and collect and organize power system data, carbon emission data, relevant policies and regulations, and technological progress information; The electricity-carbon coupling model construction module is used to construct an electricity-carbon coupling model framework that includes two major modules: power system and carbon emissions, define model variables and parameters, and establish each sub-model; The data input and parameter setting module is used to input the collected data into the model and set reasonable values ​​for the parameters in the model according to the actual situation and the latest research results; The scenario simulation and analysis module is used to run the model under the baseline scenario to obtain the baseline results of power system operation and carbon emissions, set different emission reduction strategy scenarios, simulate and obtain the results under each scenario; The result collation and report generation module is used to collate and analyze simulation results, compare indicators under different scenarios, evaluate the effects of emission reduction strategies, generate research reports and perform visual presentations; Model correction and optimization module, which is used to continuously collect actual data on power systems and carbon emissions, monitor the implementation effect of emission reduction strategies, and correct and optimize the model; The user interaction and interface display module is used to provide a user interface that enables users to easily configure model parameters, view analysis results, and manage data.

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