Coal-electricity multi-path transformation and new energy combination decision-making method under low-carbon transformation

Abstract

The invention discloses a coal power multi-path transformation and new energy combination decision-making method under low-carbon transformation. The method comprises the following steps: firstly, constructing a system comprising first-level effect indexes such as environmental influence, economic benefit, energy safety and technical innovation and corresponding second-level indexes; then, alternative schemes of various coal power transformation technology and new energy project type combinations are generated; then quantitatively evaluating the effect index of each scheme, and calculating a comprehensive utility value by using multi-criterion decision analysis; identifying potential risk factors, and performing uncertainty analysis through Monte Carlo simulation; and finally, according to the low-carbon transformation target and policy evaluation scheme conformity, selecting a scheme which most conforms to the policy target, and continuously monitoring and adjusting. The coal-electricity multi-path transformation and new energy combination decision-making method under low-carbon transformation is beneficial to promoting energy low-carbon transformation, optimizing resource allocation, improving economic benefits, promoting technical innovation, enhancing risk management capability and ensuring that a project is consistent with policy orientation.

Description

Technical Field

[0001] The present invention belongs to the technical field of comprehensive utilization planning of low-carbon and new energy, and in particular relates to a method for decision-making on multi-path transformation of coal-fired power and combination of new energy under low-carbon transformation. Background Art

[0002] As global attention to climate change continues to increase, reducing greenhouse gas emissions and achieving low-carbon transformation have become important strategic directions for energy development in various countries. In my country, although the new energy industry has made significant progress, traditional coal-fired power still occupies a dominant position in the current energy structure. As one of the main sources of carbon emissions, the coal-fired power industry faces tremendous pressure to reduce emissions. At the same time, new energy power generation (such as solar energy, wind energy, etc.) has the characteristics of intermittency and volatility, and its large-scale access to the power grid has brought challenges to the stability and reliability of the power system.

[0003] In this context, how to reasonably introduce new energy projects on the basis of making full use of the existing coal-fired power infrastructure, and achieve low-carbon, high-efficiency, safe and stable energy supply through effective technical transformation and combination decision-making, has become a technical problem that needs to be solved urgently. At present, there is a lack of systematic methods to comprehensively evaluate the effectiveness of coal-fired power transformation and new energy combination projects in terms of environment, economy, energy security and technological innovation, as well as to deal with various risks and uncertainties in the implementation of projects, which to a certain extent limits the effective promotion of the low-carbon transformation strategy in the energy field. Summary of the invention

[0004] In view of the above deficiencies in the prior art, the purpose of the present invention is to solve the key problems faced in the process of energy structure adjustment, such as technology selection, resource allocation, and environmental benefit improvement, and to provide comprehensive technical support and decision-making basis for achieving sustainable development in the energy field.

[0005] In order to achieve the above objectives, the present invention adopts the following technical solutions:

[0006] A decision-making method for multi-path transformation of coal-fired power and combination of new energy sources under low-carbon transformation, comprising the following steps:

[0007] S1. Construct an indicator system for the effectiveness of coal-fired power transformation and new energy projects, define the first-level indicators for the effectiveness of coal-fired power transformation and new energy projects, and use the first-level indicators as the basis for evaluating the performance of the scheme. The first-level indicators include environmental impact, economic benefits, energy security, technological innovation, etc.; on the basis of the defined first-level indicators, further subdivide each first-level indicator into second-level indicators;

[0008] S2. Generate alternative plans for coal-fired power transformation and new energy projects. Based on S1, create alternative plans with multiple combinations of plans according to the technical routes of coal-fired power transformation and the types of new energy projects. The alternative plans cover different technical combinations and project configurations to achieve different performance indicator targets;

[0009] S3. Calculate the comprehensive utility value of the alternatives, conduct quantitative evaluation on each performance indicator in the alternatives created in S2, and use the multi-criteria decision analysis (MCDM) method to calculate the comprehensive utility value of each alternative based on the results of the quantitative evaluation to determine the relative advantages and disadvantages of each alternative;

[0010] S4. Risk assessment and uncertainty analysis: Based on S3, identify the potential risk factors that affect the success of the project for each alternative plan, conduct uncertainty analysis on the potential risk factors through Monte Carlo simulation method, evaluate the performance of each plan at different risk levels, and provide a basis for risk management;

[0011] S5. Analysis of the compliance of low-carbon transformation goals with policies. Based on the risk assessment in S4, evaluate the compliance of various alternative plans according to national and local low-carbon transformation goals, ensure that the selected plan is consistent with the policy orientation, and analyze the contribution of each plan to achieving carbon emission peak and carbon neutrality goals, so as to select the plan that is most conducive to achieving policy goals.

[0012] Furthermore, the first-level performance indicators in S1 include:

[0013] Environmental impacts, including consideration of air pollutant emission reductions, greenhouse gas emission reduction effect assessment, and impacts on water resource utilization and pollution emissions;

[0014] Economic benefits are measured from financial indicators such as the project's investment cost, operating cost, revenue, payback period, and internal rate of return;

[0015] Energy security, assessing the stability of energy supply after coal-fired power transformation, the impact of new energy access on grid stability, and the improvement of the diversification of energy supply;

[0016] Technological innovation, which considers the advancement of new technologies adopted in coal-fired power transformation, the maturity and innovation of new energy project technologies, as well as technology R&D investment and talent training;

[0017] Furthermore, the secondary performance indicators in S1 include secondary indicators of environmental impact, secondary indicators of energy security, secondary indicators of economic benefits and secondary indicators of technological innovation;

[0018] Among them, the secondary indicators of environmental impact include:

[0019] Air pollutant emission reduction: calculate the emission concentration and emission changes of sulfur dioxide, nitrogen oxides, particulate matter and other pollutants before and after the coal-fired power transformation, using the formula: emission reduction = emission before transformation - emission after transformation;

[0020] Carbon dioxide emission reduction: the carbon dioxide emission reduction can be calculated based on the change in power generation efficiency before and after the coal-fired power transformation and the amount of electricity replaced by new energy sources. The carbon emission calculation model can be used;

[0021] Water resource utilization efficiency: evaluate the change in water resource consumption per unit of power generation, calculated by comparing water consumption data before and after the transformation;

[0022] Secondary indicators of economic benefits include:

[0023] Investment costs, including detailed information on the purchase and installation costs of coal-fired power transformation equipment, the purchase of new energy project equipment, site construction, etc.

[0024] Operating costs, including analysis of fuel costs, equipment maintenance costs (estimated based on equipment service life and maintenance cycles), etc.

[0025] Revenue, including forecasts of power generation revenue, as well as energy conservation and emission reduction subsidies and other revenues;

[0026] Financial indicators, calculation of payback period and internal rate of return, etc.;

[0027] Secondary indicators of energy security include:

[0028] The peak-shaving capacity of coal-fired power generation, analyzes the changes in parameters such as the minimum stable operating load rate and ramp rate of the units after the coal-fired power generation transformation, in order to evaluate the changes in their role in the peak-shaving of the power grid.

[0029] The impact of new energy access on grid stability. Through the power system stability analysis method, the voltage fluctuation and frequency deviation of the grid after the access of new energy are studied;

[0030] The degree of diversification of energy supply, calculate the change in the proportion of new energy in the total energy supply, and evaluate the degree of optimization of the energy supply structure;

[0031] The secondary indicators of technological innovation include:

[0032] The degree of application of new coal-fired power technologies, assessing the application proportion and effect improvement of supercritical, subcritical technology or other advanced technologies in coal-fired power transformation;

[0033] New energy technology innovation points, analysis of new technologies used in new energy projects (and their impact on project performance, as well as the proportion of technology R&D investment in the total project cost, etc.

[0034] Further, the S2 includes:

[0035] S21. Selection of coal-fired power transformation technology routes, considering different coal-fired power transformation technologies, such as "ultra-low emission" transformation, flexibility transformation, heating transformation (to achieve cogeneration of heat and power), etc.; one technology can be used alone, or a combination of N technologies can be used, N ≥ 2;

[0036] S22. New energy project type combination. New energy project types include: solar photovoltaic power generation, wind power generation, biomass power generation, geothermal power generation, etc. According to the resource conditions of the project location, select the appropriate new energy project type for combination. A single new energy project can be used, such as building a large photovoltaic power station in an area rich in solar energy resources; or a combination of multiple new energy projects, such as wind and solar complementary projects, can be used to improve the stability and reliability of energy supply;

[0037] S23. Combining options to form alternative options, arranging and combining different coal-fired power transformation technology routes with new energy project types to form a variety of alternative options.

[0038] Further, the S3 includes:

[0039] S31. Quantitative evaluation of performance indicators:

[0040] Quantification of environmental impacts: for indicators such as air pollutant emission reduction and carbon dioxide emission reduction, specific values ​​are obtained based on actual monitoring data or using professional emission calculation models;

[0041] Water resource utilization efficiency is calculated through actual measured water consumption and power generation data to obtain specific water consumption indicators;

[0042] Quantify economic benefits, and accurately calculate data such as investment costs, operating costs and revenues based on the project's budget, financial statements and market research data;

[0043] Financial indicators such as payback period and internal rate of return are calculated to obtain accurate values ​​and are used to measure the economic feasibility of the project;

[0044] Energy security is quantified, and the peak-shaving capacity of coal-fired power is evaluated through actual measurements of unit operating parameters and grid dispatch data;

[0045] The impact of new energy access on grid stability is simulated and analyzed through power system simulation software, and quantitative indicators such as voltage fluctuation and frequency deviation are obtained to evaluate the stability margin of the grid;

[0046] The degree of diversification of energy supply is calculated by calculating the proportion of renewable energy in total power generation.

[0047] Quantification of technological innovation: The degree of application of new coal-fired power technologies is quantified by evaluating the proportion of new technologies used in transformation projects and the resulting improvement in power generation efficiency.

[0048] The innovation points of new energy technologies are quantified by comparing the changes in power generation performance indicators before and after the adoption of new technologies, while taking into account factors such as the proportion of technology R&D investment in the total project cost;

[0049] S32. Calculate the comprehensive utility value using the multi-criteria decision analysis (MCDM) method:

[0050] S321. Determine the weight of each performance indicator and use the analytic hierarchy process (AHP) method to determine the relative weight of each primary and secondary indicator;

[0051] S322. Standardize the effectiveness indicators of each alternative plan, and convert the effectiveness indicators of all alternative plans into dimensionless values ​​through standardization, so as to facilitate the subsequent calculation of comprehensive utility values ​​and comparison between plans;

[0052] S323. Calculate the comprehensive utility value. According to the weight of each indicator and the standardized indicator value, use the weighted summation method to calculate the comprehensive utility value of each alternative plan.

[0053] Furthermore, in S4, potential risk factors include:

[0054] Technical risks: including the reliability of coal-fired power transformation technology, the stability of new energy project technology, and technical integration risks;

[0055] Market risks: Consider the impact of coal price fluctuations on coal-fired power costs, the uncertainty of grid-connected electricity prices for renewable energy power generation, and changes in electricity market demand;

[0056] Environmental risks: Assess the impact of climate change on the stability of new energy resources, as well as the risks of environmental policy adjustments that may be faced during coal-fired power transformation and new energy project construction;

[0057] Policy risks: Pay attention to the impact of changes in national and local energy policies on the economics and feasibility of the project.

[0058] Furthermore, in S4, the method of performing uncertainty analysis on potential risk factors by Monte Carlo simulation method includes:

[0059] S41. Determine the probability distribution of uncertainty factors, and determine the probability distribution type and parameters of each risk factor based on historical data, expert experience or market research;

[0060] S42. Construct a simulation model and incorporate various risk factors and their probability distribution into the economic evaluation model or performance evaluation model of the project;

[0061] S43. Conduct Monte Carlo simulation, using computer software to perform a large number of random sampling simulations, and calculate the key indicators of the project based on the randomly selected risk factor values ​​in each simulation;

[0062] S44. Analyze the simulation results to obtain the probability distribution of each key indicator, including calculating the mean, standard deviation, confidence interval and other statistics of the comprehensive utility value, and evaluate the performance of each alternative plan at different risk levels; by drawing the probability distribution curve, the risk characteristics of each plan can be intuitively compared to provide a basis for risk management.

[0063] Further, the S5 includes:

[0064] S51. Clarify the low-carbon transformation goals and policy requirements, and conduct in-depth research on the overall goals of the country and local governments in low-carbon transformation, such as the time node of carbon emission peak and the deadline for achieving carbon neutrality; and sort out the specific requirements of relevant policies and regulations on coal-fired power transformation and new energy projects, including energy conservation and emission reduction standards, new energy development plans, etc.;

[0065] S52. Evaluate the suitability of each alternative:

[0066] Carbon emission indicator assessment: for each alternative, accurately calculate its expected carbon emission reduction based on its coal-fired power transformation technology and new energy project portfolio;

[0067] Compare the plan with the national and local carbon emission targets to determine whether it can help achieve the carbon emission peak and carbon neutrality targets within the specified time;

[0068] Energy structure optimization analysis: analyze the changes in the proportion of new energy in the total energy supply in the alternative plans to determine whether they are in line with the policy orientation of the energy structure transformation to low-carbon and renewable energy; consider the coordination between the peak-shaving and other auxiliary service capabilities after the coal-fired power transformation and new energy, ensure the stability and reliability of energy supply, and meet the needs of energy structure optimization;

[0069] Consider policy incentives and constraints, study whether each alternative plan can enjoy relevant policy incentives, such as energy conservation and emission reduction subsidies, preferential policies for new energy projects, etc., and evaluate the impact of these incentives on the economic efficiency and feasibility of the plan;

[0070] Check whether the plan meets the constraints in the policy, such as emission limits after coal-fired power transformation and grid connection standards for new energy projects;

[0071] S53. Select the plan that best meets the policy objectives, comprehensively consider the performance of each alternative plan in terms of carbon emission reduction, energy structure optimization, policy incentives and constraint satisfaction, etc.; give priority to plans that have made great contributions to achieving carbon emission peak and carbon neutrality goals, have significant energy structure optimization effects, and fully meet policy requirements. If there are multiple plans with similar performance, other factors can be further combined for weighing and decision-making.

[0072] S54. Continuous monitoring and adjustment, establishing a monitoring mechanism to track the actual carbon emissions, energy supply, etc. during the implementation of the selected plan;

[0073] According to policy changes and actual operating data, the plan will be adjusted and optimized in a timely manner to ensure that it is always consistent with low-carbon transformation goals and policy directions.

[0074] In summary, due to the adoption of the above technical solution, the beneficial technical effects of the invention are:

[0075] Promoting low-carbon transformation and sustainable development of energy, the decision-making method of the present invention helps the energy industry transform from the traditional high-carbon coal-fired power model to a low-carbon, clean energy supply system. By comprehensively evaluating the combination of coal-fired power transformation and new energy solutions, it is possible to screen out solutions that excel in environmental impact, such as achieving a substantial reduction in atmospheric pollutants (sulfur dioxide, nitrogen oxides, particulate matter, etc.) and a significant reduction in carbon dioxide emissions, thereby effectively helping the country and localities achieve carbon emission peaks and carbon neutrality goals, promoting the sustainable development of the energy industry, adapting to the global trend of responding to climate change, reducing the negative impact of energy production on the environment, protecting the ecological balance, and laying a solid foundation for the green development of the economy and society.

[0076] Optimizing energy resource allocation and supply stability, based on a comprehensive analysis of various alternatives, can achieve optimal allocation of coal-fired power and new energy resources. On the one hand, according to the resource conditions of different regions (such as solar radiation intensity, wind resources, etc.), the type of new energy project is reasonably selected and combined with coal-fired power transformation to improve the stability and reliability of energy supply. On the other hand, by evaluating the impact of coal-fired power peak-shaving capacity and new energy access on the stability of the power grid, it is ensured that the power grid can operate safely and stably under various working conditions, effectively deal with the intermittent and volatility of new energy power generation, enhance the anti-interference ability of the entire energy system, ensure the continuity of energy supply, and meet the continuous demand for energy in social production and life.

[0077] Improve the comprehensive economic benefits of energy projects. Detailed quantitative evaluation of economic benefits provides a solid basis for economic decision-making for the projects. In terms of investment costs, accurate calculation of coal-fired power transformation equipment procurement, installation costs, and new energy project equipment purchase, site construction and other cost details will help to reasonably control the initial investment. Operation cost analysis (including fuel costs, equipment maintenance costs, etc.) can help companies optimize operating strategies and reduce daily operating expenses. At the same time, accurate prediction of income from power generation and energy-saving and emission reduction subsidies, combined with the calculation of financial indicators such as payback period and internal rate of return, enables companies to choose the most economically efficient plan, improve project profitability and capital efficiency, enhance the competitiveness of companies in the energy market, promote the commercial success of energy projects, and provide economic support for the healthy development of the energy industry.

[0078] Promoting energy technology innovation and industrial upgrading, technological innovation considerations are an important part of this invention, which helps to promote technological progress and industrial upgrading in the energy field. Encouraging the use of new technologies (such as supercritical and supercritical technologies) in coal-fired power transformation and technological innovation in new energy projects (such as new solar cell technologies, wind power technology improvements, etc.), and evaluating the degree of application of new technologies and the improvement of their effects, can not only improve energy utilization efficiency, reduce energy consumption and carbon emissions, but also drive the development of related industrial chains. For example, new energy technology innovation will promote the technological upgrading and scale expansion of industries such as battery manufacturing and wind turbine manufacturing, cultivate high-quality technical talents, enhance the technological competitiveness of my country's energy industry in the world, lead the energy industry to a higher technological level, and promote the innovative development and structural optimization of the energy industry.

[0079] Enhance the risk management capabilities of energy projects. Risk assessment and uncertainty analysis are a highlight of this technical solution. By identifying potential risk factors such as technical risks (such as reliability of coal-fired power transformation technology, technical stability of new energy projects, and technical integration risks), market risks (coal price fluctuations, uncertainty in the on-grid electricity price of new energy power generation, and changes in electricity market demand), environmental risks (the impact of climate change on the stability of new energy resources, and risks of environmental protection policy adjustments), and policy risks (changes in national and local energy policies), and using the Monte Carlo simulation method for uncertainty analysis, we can fully understand the performance of each alternative plan at different risk levels. This provides a scientific basis for risk management during project implementation, enabling enterprises to formulate response strategies in advance, such as using hedging to deal with coal price fluctuations, optimizing technical integration solutions to reduce technical risks, etc., effectively reducing the possibility and impact of risks, improving the ability of energy projects to cope with complex and changing environments, and ensuring the smooth implementation and long-term stable operation of projects.

[0080] Ensure the consistency between policy orientation and project implementation. The low-carbon transformation goal and policy compliance analysis ensure that the selected plan is highly consistent with the national and local energy development strategies and low-carbon transformation policy orientation. When evaluating the various alternative plans, fully consider factors such as carbon emission indicators, energy structure optimization requirements, policy incentives and constraints, so that the project can fully enjoy policy support (such as energy conservation and emission reduction subsidies, preferential policies for new energy projects, etc.) during implementation, while meeting the policy requirements for emission limits after coal-fired power transformation and grid connection standards for new energy projects. This will help improve the compliance and feasibility of the project, promote the benign interaction between energy projects and the policy environment, promote the orderly development of the energy industry in accordance with national and local plans, ensure that energy projects achieve sustainable development within the policy framework, and provide technical guarantees for the effective implementation of energy policies. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 It is a logical block diagram of a decision-making method for multi-path transformation of coal-fired power and combination of new energy under low-carbon transformation;

[0082] Figure 2 A logical block diagram for the method of generating alternative solutions for coal-fired power transformation and new energy projects;

[0083] Figure 3 A logical block diagram of the method for calculating the comprehensive utility value of alternative options;

[0084] Figure 4 It is the logic block diagram of risk assessment and uncertainty analysis method;

[0085] Figure 5 This is a logical framework diagram of the analysis method for low-carbon transformation goals and policy compliance. DETAILED DESCRIPTION

[0086] In order to make the purpose, technical solution and advantages of the invention more clear, the invention is further described in detail below in combination with the embodiments. It should be understood that the specific embodiments described here are only used to explain the invention and are not used to limit the invention.

[0087] like Figure 1 As shown, a decision-making method for multi-path transformation of coal-fired power and combination of new energy sources under low-carbon transformation includes the following steps:

[0088] S1. Construct an indicator system for the effectiveness of coal-fired power transformation and new energy projects, define the first-level indicators for the effectiveness of coal-fired power transformation and new energy projects, and use the first-level indicators as the basis for evaluating the performance of the scheme. The first-level indicators include environmental impact, economic benefits, energy security, technological innovation, etc.; on the basis of the defined first-level indicators, further subdivide each first-level indicator into second-level indicators;

[0089] S2. Generate alternative plans for coal-fired power transformation and new energy projects. Based on S1, create alternative plans with multiple combinations of plans according to the technical routes of coal-fired power transformation and the types of new energy projects. The alternative plans cover different technical combinations and project configurations to achieve different performance indicator targets;

[0090] S3. Calculate the comprehensive utility value of the alternatives, conduct quantitative evaluation on each performance indicator in the alternatives created in S2, and use the multi-criteria decision analysis (MCDM) method to calculate the comprehensive utility value of each alternative based on the results of the quantitative evaluation to determine the relative advantages and disadvantages of each alternative;

[0091] S4. Risk assessment and uncertainty analysis: Based on S3, identify the potential risk factors that affect the success of the project for each alternative plan, conduct uncertainty analysis on the potential risk factors through Monte Carlo simulation method, evaluate the performance of each plan at different risk levels, and provide a basis for risk management;

[0092] S5. Analysis of the compliance of low-carbon transformation goals with policies. Based on the risk assessment in S4, evaluate the compliance of various alternative plans according to national and local low-carbon transformation goals, ensure that the selected plan is consistent with the policy orientation, and analyze the contribution of each plan to achieving carbon emission peak and carbon neutrality goals, so as to select the plan that is most conducive to achieving policy goals.

[0093] The first-level performance indicators in S1 include:

[0094] Environmental impact, including consideration of emission reduction of atmospheric pollutants (such as sulfur dioxide, nitrogen oxides, particulate matter, etc.), evaluation of greenhouse gas (mainly carbon dioxide) emission reduction effect, and impact on water resource utilization and pollution emissions;

[0095] Economic benefits are measured from the project's investment cost (including coal-fired power transformation equipment update costs, new energy project construction costs, etc.), operating costs (such as fuel costs, maintenance costs, etc.), benefits (such as power sales revenue, energy conservation and emission reduction subsidy income, etc.), and financial indicators such as investment payback period and internal rate of return;

[0096] Energy security, assessing the stability of energy supply after coal-fired power transformation (such as changes in coal-fired power peak-shaving capacity), the impact of new energy access on grid stability (such as the impact of intermittent and volatile new energy generation on the grid), and the improvement of the degree of diversification of energy supply.

[0097] Technological innovation, considering the advancement of new technologies adopted in coal-fired power transformation (such as the application of supercritical and subcritical technologies), the maturity and innovation of new energy project technologies (such as new solar cell technologies, improvements in wind power generation technologies, etc.), as well as technology research and development investment and talent training;

[0098] The secondary performance indicators in S1 include secondary indicators of environmental impact, secondary indicators of energy security, secondary indicators of economic benefits and secondary indicators of technological innovation;

[0099] Among them, the secondary indicators of environmental impact include:

[0100] Air pollutant emission reduction: calculate the emission concentration and emission changes of sulfur dioxide, nitrogen oxides, particulate matter and other pollutants before and after the coal-fired power transformation, using the formula: emission reduction = emission before transformation - emission after transformation;

[0101] Carbon dioxide emission reduction: Calculate the amount of carbon dioxide emission reduction based on the change in power generation efficiency before and after coal-fired power transformation and the amount of electricity replaced by new energy sources. The carbon emission calculation model (such as the calculation method based on fuel consumption and emission factors) can be used.

[0102] Water resource utilization efficiency: evaluate the change in water resource consumption per unit of power generation, calculated by comparing water consumption data before and after the transformation;

[0103] Secondary indicators of economic benefits include:

[0104] Investment costs include detailed information on coal-fired power transformation equipment procurement and installation costs, new energy project equipment purchases, site construction and other costs.

[0105] Operating costs, analysis of fuel costs (such as the impact of coal price fluctuations on costs), equipment maintenance costs (estimated based on equipment service life and maintenance cycle), etc.

[0106] Income, including forecasted power generation income (calculated based on power generation and on-grid electricity price), and energy conservation and emission reduction subsidies (calculated based on relevant policy subsidy standards and emission reductions).

[0107] Financial indicators include calculation of payback period (the time required to reach the initial investment by accumulating net cash flow) and internal rate of return (the discount rate that makes the net present value zero calculated by trial and error or financial software).

[0108] Secondary indicators of energy security include:

[0109] The peak-shaving capacity of coal-fired power generation, analyzes the changes in parameters such as the minimum stable operating load rate and ramp rate of the units after the coal-fired power generation transformation, in order to evaluate the changes in their role in the peak-shaving of the power grid.

[0110] The impact of renewable energy access on grid stability. Through power system stability analysis methods (such as transient stability analysis, frequency stability analysis, etc.), the voltage fluctuation and frequency deviation of the grid after renewable energy access are studied.

[0111] The degree of diversification of energy supply, calculate the change in the proportion of new energy in the total energy supply, and evaluate the degree of optimization of the energy supply structure;

[0112] The secondary indicators of technological innovation include:

[0113] The degree of application of new coal-fired power technologies, evaluate the application proportion and effect improvement (such as the degree of improvement in power generation efficiency) of supercritical, subcritical technology or other advanced technologies in coal-fired power transformation.

[0114] New energy technology innovations, analysis of new technologies used in new energy projects (such as improved conversion efficiency of new photovoltaic materials, improved efficiency of wind turbines, etc.) and their impact on project performance, as well as the proportion of technology research and development investment in the total project cost.

[0115] like Figure 2 As shown, the S2 includes:

[0116] S21. Selection of technical routes for coal-fired power transformation, considering different coal-fired power transformation technologies, such as "ultra-low emission" transformation (using high-efficiency dust removal, desulfurization, and denitrification equipment), flexibility transformation (improving the peak-shaving capacity of units), heating transformation (realizing cogeneration of heat and power), etc.; one technology can be used alone, or a combination of N technologies can be used, N ≥ 2; for example, a power plant can choose to first carry out "ultra-low emission" transformation, and then carry out flexibility transformation, so as to meet both environmental protection and grid peak-shaving needs;

[0117] S22. Combination of new energy project types. New energy project types include: solar photovoltaic power generation, wind power generation, biomass power generation, geothermal power generation, etc. According to the resource conditions of the project location (such as solar radiation intensity, wind resources, etc.), select appropriate new energy project types for combination. A single new energy project can be used, such as building a large photovoltaic power station in an area rich in solar energy resources; or a combination of multiple new energy projects can be used, such as a wind-solar complementary project (building a wind farm and a photovoltaic power station at the same time) to improve the stability and reliability of energy supply;

[0118] S23. Alternative plans are formed by combining different coal-fired power transformation technology routes with new energy project types to form a variety of alternative plans; for example, Plan 1: A coal-fired power plant undergoes "ultra-low emission + flexibility" transformation and builds a nearby wind farm at the same time; Plan 2: Another coal-fired power plant undergoes heating transformation and builds a supporting biomass power generation project, etc.; Each alternative plan should clearly define the specific technology combination and project configuration, including detailed information such as equipment selection and scale.

[0119] like Figure 3 As shown, the S3 includes:

[0120] S31. Quantitative evaluation of performance indicators:

[0121] Quantification of environmental impacts: for indicators such as air pollutant emission reduction and carbon dioxide emission reduction, specific values ​​are obtained based on actual monitoring data or using professional emission calculation models;

[0122] Water resource utilization efficiency is calculated through actual measured water consumption and power generation data to obtain specific water consumption indicators;

[0123] Quantify economic benefits. Data such as investment costs, operating costs and revenues are accurately calculated based on the project budget, financial statements and market research data. For example, determine equipment procurement costs through bidding procurement data and predict power generation revenue based on energy market prices.

[0124] Financial indicators such as payback period and internal rate of return are calculated to obtain accurate values ​​and are used to measure the economic feasibility of the project;

[0125] Energy security quantification: coal-fired power peak-shaving capacity is evaluated through actual measurements of unit operating parameters (such as minimum stable operating load, ramp rate, etc.) and grid dispatch data; for example, the unit's operating stability data under different loads is recorded to analyze its response capability during grid peak-shaving;

[0126] The impact of new energy access on grid stability is simulated and analyzed through power system simulation software (such as PSASP, PSS / E, etc.), and quantitative indicators such as voltage fluctuation and frequency deviation are obtained to evaluate the stability margin of the grid;

[0127] The degree of diversification of energy supply is calculated by calculating the proportion of renewable energy in total power generation.

[0128] Quantification of technological innovation: The degree of application of new coal-fired power technologies is quantified by evaluating the proportion of new technologies used in renovation projects (such as the proportion of equipment using supercritical technology to total equipment) and the resulting improvement in power generation efficiency.

[0129] The innovation points of new energy technologies are quantified by comparing the changes in power generation performance indicators (such as photovoltaic conversion efficiency, wind turbine power curve, etc.) before and after the adoption of new technologies, while taking into account factors such as the proportion of technology R&D investment in the total project cost;

[0130] S32. Calculate the comprehensive utility value using the multi-criteria decision analysis (MCDM) method:

[0131] S321. Determine the weight of each performance indicator, use the analytic hierarchy process (AHP) to construct a judgment matrix, compare the four primary performance indicators of environmental impact, economic benefits, energy security, and technological innovation, and construct a primary indicator judgment matrix to judge their relative importance; if it is believed that environmental impact is more critical than economic benefits in the context of low-carbon transformation, a higher score (such as 5 points) may be given to environmental impact, while a relatively lower score (such as 1 point) may be given to economic benefits, and vice versa; and so on, compare and score other indicators to construct a complete 4×4 judgment matrix A, A=(a ij ), i, j = 1, 2, 3, 4 correspond to environmental impact, economic benefits, energy security, and technological innovation, respectively, where a ij Indicates the importance of indicator i relative to indicator j, a ij The value is assigned using a 1-9 scale, and the specific rules are as follows:

[0132] When i=j, a ij =1 means the indicator is equally important compared to itself;

[0133] When i≠j, if indicator i is slightly more important than indicator j, then a ij =3, at this time If indicator i is significantly more important than indicator j, then a ij =5, at this time If indicator i is more important than indicator j, then a ij =7, at this time If indicator i is more important than indicator j, then a ij =9, at this time If the importance is between the above adjacent levels, then a ij =2, 4, 6, 8, corresponding

[0134] Calculate the maximum eigenvalue λ of the judgment matrix A max and its corresponding eigenvector ω=(ω1,ω2,ω3,ω4), obtain the eigenvalue by solving the characteristic equation |A-λI|=0 (where I is the unit matrix), and select the largest eigenvalue λ max , and calculate the maximum eigenvalue λ max The corresponding eigenvector ω is calculated using the sum-product method:

[0135] Normalize each column element of the judgment matrix A and get Get the new matrix

[0136] Will Add each row of elements to get the vector in

[0137] right After normalization, we get the weight vector ω = (ω1, ω2, ω3, ω4), where

[0138] Perform consistency check and calculate consistency index Where n is the number of indicators; find the average random consistency index RI, when n = 4, RI = 0.9, RI is obtained by looking up the table to obtain the corresponding values ​​of different values; calculate the consistency ratio If CR < 0.1, the judgment matrix A is considered to have satisfactory consistency, and ω = (ω1, ω2, ω3, ω4) is the weight vector of each primary performance indicator; if CR ≥ 0.1, the judgment matrix A needs to be readjusted until it passes the consistency test;

[0139] Similar operations are performed on each secondary indicator under its primary indicator to obtain the weight vector of each secondary indicator. Under the primary indicator of environmental impact, the reduction of atmospheric pollutants is set as E1, the reduction of carbon dioxide emissions is set as E1, and the efficiency of water resource utilization is set as E1 to construct the judgment matrix Calculate its weight vector ω E =(ω E1 ,ω E2 ,ω E3 ,ω E4 ) and conduct consistency test; similarly, under economic benefits, a judgment matrix is ​​constructed for investment cost, operating cost, income, and financial indicators to determine weights; under energy security, a judgment matrix is ​​constructed for coal-fired power peak-shaving capacity, the impact of new energy access on grid stability, and the degree of energy supply diversification to determine weights; under technological innovation, a judgment matrix is ​​constructed for the degree of application of new coal-fired power technologies and new energy technology innovations to determine weights; and finally, the combined weights of each secondary performance indicator relative to the overall goal are obtained;

[0140] S322. Standardize the effectiveness indicators of each alternative plan and clarify the benefit indicators and cost indicators; benefit indicators include the reduction of atmospheric pollutants, the reduction of carbon dioxide emissions, the proportion of new energy in the total energy supply, the improvement of power generation efficiency, the improvement of photovoltaic conversion efficiency, the improvement of wind turbine power curve, etc. The larger the value of these indicators, the better the plan; cost indicators include investment cost, operating cost, etc. The smaller the value of the indicator, the better the plan;

[0141] Standardization of benefit indicators, set x hk is the kth benefit indicator value of the hth alternative, is the maximum value of the kth benefit indicator among all alternatives; for each benefit indicator k, the standardized indicator value y hk , the calculation formula is:

[0142] Cost-based indicators are standardized, and m hk is the kth cost indicator value of the hth alternative, (where t is the number of alternatives), for each cost indicator k, the standardized indicator value m′ hk The calculation formula is:

[0143] Through such standardization, the effectiveness indicators of all alternative plans are converted into dimensionless values ​​between 0 and 1, which facilitates the subsequent calculation of comprehensive utility values ​​and comparison between plans.

[0144] S323. Calculate the comprehensive utility value, assuming U h is the comprehensive utility value of the hth alternative, ω k is the weight of the kth indicator (including primary and secondary indicators, the weights are determined by S321), y hk is the standardized value of the benefit indicator, m y is the index value after standardization of cost-type index, n is the number of indicators; the calculation formula of comprehensive utility value is:

[0145]

[0146] In S4, potential risk factors include:

[0147] Technical risks: including the reliability of coal-fired power transformation technology (such as the risk of equipment failure that may exist in new technologies), the stability of new energy project technology (such as the risk of component attenuation in photovoltaic power generation and the failure rate of wind turbines in wind power generation), and technical integration risks (compatibility issues that may arise when coal-fired power and new energy technologies are combined);

[0148] Market risks: Consider the impact of coal price fluctuations on coal-fired power costs, the uncertainty of the on-grid electricity price of renewable energy power generation (affected by policies and market supply and demand), and changes in electricity market demand (such as a decrease in electricity demand due to economic growth slowdown);

[0149] Environmental risks: Assess the impact of climate change on the stability of new energy resources (such as wind resources and solar resources), as well as the risks of environmental policy adjustments (such as stricter emission standards) that may be faced during coal-fired power transformation and new energy project construction;

[0150] Policy risks: Pay attention to the impact of changes in national and local energy policies (such as subsidy policy adjustments, tightening of carbon emission policies, etc.) on the economics and feasibility of the project.

[0151] like Figure 4 As shown, in S4, the method of performing uncertainty analysis on potential risk factors by Monte Carlo simulation method includes:

[0152] S41. Determine the probability distribution of uncertainty factors. Based on historical data, expert experience or market research, determine the probability distribution type (such as normal distribution, uniform distribution, etc.) and its parameters (such as mean, standard deviation, etc.) of each risk factor (such as coal price, new energy resources, etc.);

[0153] S42. Construct a simulation model and incorporate various risk factors and their probability distribution into the economic evaluation model or performance evaluation model of the project; for example, when calculating the project benefits, the coal price is used as a random variable and randomly selected in each simulation according to its probability distribution, while considering the impact of other risk factors on project cost, power generation and other parameters;

[0154] S43. Conduct Monte Carlo simulations, using computer software (such as Matlab, Crystal Ball, etc.) to perform a large number of random sampling simulations. Each simulation calculates the key indicators of the project (such as comprehensive utility value, investment payback period, etc.) based on the randomly selected risk factor values;

[0155] S44. Analyze the simulation results to obtain the probability distribution of each key indicator, including calculating the mean, standard deviation, confidence interval and other statistics of the comprehensive utility value, and evaluate the performance of each alternative plan under different risk levels; by drawing the probability distribution curve, the risk characteristics of each plan can be intuitively compared to provide a basis for risk management; for example, if the comprehensive utility value of a plan is more dispersed in the simulation results, it means that its risk is greater; while the plan with a more concentrated distribution and a higher mean is relatively better.

[0156] like Figure 5 As shown, the S5 includes:

[0157] S51. Clarify the low-carbon transformation goals and policy requirements, and conduct in-depth research on the overall goals of the country and local governments in low-carbon transformation, such as the time node of carbon emission peak and the deadline for achieving carbon neutrality; and sort out the specific requirements of relevant policies and regulations on coal-fired power transformation and new energy projects, including energy conservation and emission reduction standards, new energy development plans, etc.;

[0158] S52. Evaluate the suitability of each alternative:

[0159] Carbon emission indicator assessment, for each alternative, accurately calculate its expected carbon emission reduction based on its coal power transformation technology (such as "ultra-low emission" transformation, flexibility transformation, etc.) and new energy project portfolio (such as solar energy, wind energy, etc.);

[0160] Compare with the national and local carbon emission targets to determine whether the plan can help achieve the carbon emission peak and carbon neutrality targets within the specified time; for example, if a region requires carbon emissions to peak before 2030, assess whether the carbon emission trends of various plans before that time point meet the requirements;

[0161] Energy structure optimization analysis: analyze the changes in the proportion of new energy in the total energy supply in the alternative plans to determine whether they are in line with the policy orientation of the energy structure transformation to low-carbon and renewable energy; consider the coordination between the peak-shaving and other auxiliary service capabilities after the coal-fired power transformation and new energy, ensure the stability and reliability of energy supply, and meet the needs of energy structure optimization;

[0162] Consider policy incentives and constraints, study whether each alternative plan can enjoy relevant policy incentives, such as energy conservation and emission reduction subsidies, preferential policies for new energy projects, etc., and evaluate the impact of these incentives on the economic efficiency and feasibility of the plan;

[0163] Check whether the plan meets the constraints in the policy, such as emission limits after coal-fired power transformation and grid connection standards for new energy projects;

[0164] S53. Select the plan that best meets the policy objectives, comprehensively consider the performance of each alternative plan in terms of carbon emission reduction, energy structure optimization, policy incentives and constraint satisfaction, etc.; give priority to plans that have made great contributions to achieving carbon emission peak and carbon neutrality goals, have significant energy structure optimization effects, and fully meet policy requirements. If there are multiple plans with similar performance, other factors (such as economic benefits, technical feasibility, etc.) can be further combined to weigh and make decisions.

[0165] S54. Continuous monitoring and adjustment, establishing a monitoring mechanism to track the actual carbon emissions, energy supply, etc. during the implementation of the selected plan;

[0166] Adjust and optimize the plan in a timely manner according to policy changes and actual operation data to ensure that it is always consistent with the low-carbon transformation goals and policy orientation. For example, if the policy has new requirements for the energy storage configuration of new energy projects, promptly evaluate the impact on the existing plan and make improvements.

[0167] The above description is a preferred embodiment of the invention and is not intended to limit the invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the invention should be included in the protection scope of the invention.

Claims

1. A decision-making method for multi-path transformation of coal-fired power and combination of new energy under low-carbon transformation, characterized in that: The following steps are involved: S1. Construct an effectiveness indicator system for coal-fired power transformation and new energy projects, define the first-level effectiveness indicators for coal-fired power transformation and new energy projects, and the first-level effectiveness indicators will serve as the basis for evaluating the performance of the scheme. The first-level effectiveness indicators include environmental impact, economic benefits, energy security, and technological innovation; on the basis of the defined first-level indicators, each first-level indicator will be further subdivided into second-level indicators; S2. Generate alternative plans for coal-fired power transformation and new energy projects. Based on S1, create alternative plans with multiple combinations of plans according to the technical routes of coal-fired power transformation and the types of new energy projects. The alternative plans cover different technical combinations and project configurations to achieve different performance indicator targets; S3. Calculate the comprehensive utility value of the alternatives, conduct quantitative evaluation on each performance indicator in the alternatives created in S2, and use the multi-criteria decision analysis (MCDM) method to calculate the comprehensive utility value of each alternative based on the results of the quantitative evaluation to determine the relative advantages and disadvantages of each alternative; S4. Risk assessment and uncertainty analysis: Based on S3, identify the potential risk factors that affect the success of the project for each alternative plan, conduct uncertainty analysis on the potential risk factors through Monte Carlo simulation method, evaluate the performance of each plan at different risk levels, and provide a basis for risk management; S5. Analysis of the compliance of low-carbon transformation goals with policies. Based on the risk assessment in S4, evaluate the compliance of various alternative plans according to national and local low-carbon transformation goals, ensure that the selected plan is consistent with the policy orientation, and analyze the contribution of each plan to achieving carbon emission peak and carbon neutrality goals, so as to select the plan that is most conducive to achieving policy goals.

2. According to the method for decision-making on multi-path transformation of coal-fired power and combination of new energy under low-carbon transformation in claim 1, it is characterized in that: The first-level performance indicators include: Environmental impacts, including consideration of air pollutant emission reductions, greenhouse gas emission reduction effect assessment, and impacts on water resource utilization and pollution emissions; Economic benefits are measured from the project’s investment cost, operating cost, revenue, payback period, and internal rate of return financial indicators; Energy security, assessing the stability of energy supply after coal-fired power transformation, the impact of new energy access on grid stability, and the improvement of the diversification of energy supply; Technological innovation considers the advancement of new technologies adopted in coal-fired power transformation, the maturity and innovation of new energy project technologies, as well as investment in technological research and development and talent training.

3. The method for decision-making on multi-path transformation of coal-fired power and combination of new energy sources under low-carbon transformation according to claim 1 is characterized in that: The secondary indicators include environmental impact secondary indicators, energy security secondary indicators, economic benefit secondary indicators and technological innovation secondary indicators. Among them, the secondary indicators of environmental impact include: reduction of atmospheric pollutants, which calculates the emission concentration and emission changes of sulfur dioxide, nitrogen oxides, and particulate matter pollutants before and after the coal-fired power transformation, using the formula: emission reduction = emission before transformation - emission after transformation; carbon dioxide emission reduction, which calculates the carbon dioxide emission reduction based on the change in power generation efficiency before and after the coal-fired power transformation and the amount of electricity replaced by new energy; water resource utilization efficiency, which evaluates the change in water resource consumption per unit of power generation, and is calculated by comparing the water consumption data before and after the transformation; Secondary indicators of economic benefits include: investment costs, which detail the purchase and installation costs of coal-fired power transformation equipment, and the purchase and site construction costs of new energy project equipment; Operating costs, analysis of fuel costs and equipment maintenance costs; Revenue, forecast of power generation revenue, and revenue from energy conservation and emission reduction subsidies; Financial indicators, calculation of payback period and internal rate of return; Secondary indicators of energy security include: coal-fired power peak-shaving capacity, analyzing the minimum stable operating load rate and ramp rate parameter changes of coal-fired power units after transformation to evaluate the changes in their role in power grid peak-shaving; the impact of new energy access on power grid stability, using power system stability analysis methods to study the voltage fluctuation and frequency deviation of the power grid after new energy access; the degree of diversification of energy supply, calculating the proportion of new energy in the total energy supply and evaluating the degree of optimization of the energy supply structure; Secondary indicators of technological innovation include: the degree of application of new coal-fired power technologies, which evaluates the proportion of application and effect improvement of supercritical, subcritical technology or other advanced technologies in coal-fired power transformation; new energy technology innovation points, which analyze the new technologies adopted by new energy projects and their impact on project performance, as well as the proportion of technology research and development investment in the total project cost.

4. According to a method for decision-making on multi-path transformation of coal-fired power and combination of new energy sources under low-carbon transformation in claim 1, it is characterized in that: The S2 includes: S21. Selection of coal-fired power transformation technology routes, considering different coal-fired power transformation technologies, such as "ultra-low emission" transformation, flexibility transformation, and heating transformation; one technology can be used alone, or a combination of N technologies can be used, N ≥ 2; S22. New energy project type combination. New energy project types include: solar photovoltaic power generation, wind power generation, biomass power generation, and geothermal power generation. According to the resource conditions of the project location, new energy project types are selected for combination. A single new energy project or a combination of multiple new energy projects, such as wind-solar complementary projects, can be used to improve the stability and reliability of energy supply; S23. Combining options to form alternative options, arranging and combining different coal-fired power transformation technology routes with new energy project types to form a variety of alternative options.

5. The method for decision-making on multi-path transformation of coal-fired power and combination of new energy sources under low-carbon transformation according to claim 1 is characterized in that: The S3 includes: S31. Quantitative evaluation of performance indicators: Quantification of environmental impacts: for indicators of air pollutant emission reduction and carbon dioxide emission reduction, specific values ​​are obtained based on actual monitoring data or by using professional emission calculation models; Water resource utilization efficiency is calculated through actual measured water consumption and power generation data to obtain specific water consumption indicators; Quantify economic benefits, and accurately calculate investment costs, operating costs and revenue data based on the project's budget, financial statements and market research data; Financial indicators such as payback period and internal rate of return are calculated to obtain accurate values ​​and are used to measure the economic feasibility of the project; Energy security is quantified, and the peak-shaving capacity of coal-fired power is evaluated through actual measurements of unit operating parameters and grid dispatch data; The impact of new energy access on grid stability is simulated and analyzed through power system simulation software to obtain quantitative indicators of voltage fluctuation and frequency deviation, and evaluate the stability margin of the grid; The degree of diversification of energy supply is calculated by calculating the proportion of renewable energy in total power generation. Quantification of technological innovation: The degree of application of new coal-fired power technologies is quantified by evaluating the proportion of new technologies used in transformation projects and the resulting improvement in power generation efficiency; The innovation points of new energy technologies are quantified by comparing the changes in power generation performance indicators before and after the adoption of new technologies, while taking into account the proportion of technology R&D investment in the total project cost; S32. The comprehensive utility value is calculated using the multi-criteria decision analysis (MCDM) method.

6. The method for decision-making on multi-path transformation of coal-fired power and combination of new energy sources under low-carbon transformation according to claim 1 is characterized in that: The S32 includes: S321. Determine the weight of each performance indicator and use the analytic hierarchy process (AHP) method to determine the relative weight of each primary and secondary indicator; S322. Standardize the effectiveness indicators of each alternative plan, and convert the effectiveness indicators of all alternative plans into dimensionless values ​​through standardization, so as to facilitate the subsequent calculation of comprehensive utility values ​​and comparison between plans; S323. Calculate the comprehensive utility value. According to the weight of each indicator and the standardized indicator value, use the weighted summation method to calculate the comprehensive utility value of each alternative plan.

7. The method for decision-making on multi-path transformation of coal-fired power and combination of new energy sources under low-carbon transformation according to claim 1 is characterized in that: In S4, potential risk factors include: Technical risks: including the reliability of coal-fired power transformation technology, the stability of new energy project technology, and technical integration risks; Market risks: Consider the impact of coal price fluctuations on coal-fired power costs, the uncertainty of grid-connected electricity prices for renewable energy power generation, and changes in electricity market demand; Environmental risks: Assess the impact of climate change on the stability of new energy resources, as well as the risks of environmental policy adjustments that may be faced during coal-fired power transformation and new energy project construction; Policy risks: Pay attention to the impact of changes in national and local energy policies on the economics and feasibility of the project.

8. The method for decision-making on multi-path transformation of coal-fired power and combination of new energy sources under low-carbon transformation according to claim 1 is characterized in that: In S4, the method of performing uncertainty analysis on potential risk factors by Monte Carlo simulation method includes: S41. Determine the probability distribution of uncertainty factors, and determine the probability distribution type and parameters of each risk factor based on historical data, expert experience or market research methods; S42. Construct a simulation model and incorporate various risk factors and their probability distribution into the economic evaluation model or performance evaluation model of the project; S43. Conduct Monte Carlo simulation, using computer software to perform a large number of random sampling simulations, and calculate the key indicators of the project based on the randomly selected risk factor values ​​in each simulation; S44. Analyze the simulation results to obtain the probability distribution of each key indicator, including calculating the mean, standard deviation, and confidence interval statistics of the comprehensive utility value, and evaluate the performance of each alternative plan at different risk levels; by drawing the probability distribution curve, intuitively compare the risk characteristics of each plan to provide a basis for risk management.

9. According to a method for decision-making on multi-path transformation of coal-fired power and combination of new energy sources under low-carbon transformation in claim 1, it is characterized in that: The S5 includes: S51. Clarify the low-carbon transformation goals and policy requirements, and conduct in-depth research on the overall goals of the country and local governments in low-carbon transformation, such as the time node of carbon emission peak and the deadline for achieving carbon neutrality; and sort out the specific requirements of relevant policies and regulations on coal-fired power transformation and new energy projects, including energy conservation and emission reduction standards and new energy development plans; S52. Evaluate the suitability of each alternative, including: Carbon emission indicator assessment: for each alternative, calculate its expected carbon emission reduction based on its coal-fired power transformation technology and new energy project portfolio; Compare the plan with the national and local carbon emission targets to determine whether it can help achieve the carbon emission peak and carbon neutrality targets within the specified time; Energy structure optimization analysis: analyze the changes in the proportion of new energy in the total energy supply in the alternative options to determine whether they are in line with the policy orientation of the energy structure transformation to low-carbon and renewable energy; consider the coordination between the peak load auxiliary service capacity and new energy after the coal-fired power transformation to ensure the stability and reliability of energy supply while meeting the needs of energy structure optimization; Consider policy incentives and constraints, study whether each alternative plan can enjoy relevant policy incentives, such as energy conservation and emission reduction subsidies, preferential policies for new energy projects, and evaluate the impact of these incentives on the economic efficiency and feasibility of the plan; Check whether the plan meets the constraints in the policy, including emission limits after coal-fired power transformation and grid connection standards for new energy projects; S53. Select the plan that best meets the policy objectives, comprehensively considering the performance of each alternative plan in terms of carbon emission reduction, energy structure optimization, policy incentives and constraint satisfaction; give priority to plans that have a great contribution to achieving carbon emission peak and carbon neutrality goals, have significant energy structure optimization effects and fully meet policy requirements; S54. Continuously monitor and adjust, establish a monitoring mechanism, and track the actual carbon emissions and energy supply of the selected plan during implementation; adjust and optimize the plan in a timely manner according to policy changes and actual operating data to ensure that it is always consistent with the low-carbon transformation goals and policy orientations.

Images