Pollution reduction and carbon reduction control method and device for energy power industry

Abstract

The invention discloses a pollution reduction and carbon reduction control method and device in the energy power industry. The method comprises the steps that a global renewable energy source development analysis database (GREAN database for short) is obtained, in combination with planning and demand constraints, a pollution reduction and carbon reduction model (EPCR model for short) of the high-proportion renewable energy sources is constructed by utilizing machine learning, and the method comprises the steps of: obtaining a global renewable energy source development analysis database (GREAN database for short), and constructing the pollution reduction and carbon reduction model (EPCR model for short) of the high-proportion renewable energy sources in combination with the planning and demand constraints; planning constraints such as vegetation area, carbon emission, coal consumption, pollutant emission and the like and demand constraints such as energy, electric power, heat supply and the like are incorporated into a target function of the EPCR model of the high-proportion renewable energy; calculating the minimum investment, carbon emission and pollutant emission target values of the energy power industry by using the deep learning model; based on the minimum target value, the total cost and the carbon emission value of the energy power industry are calculated through big data analysis; and in combination with the stepped carbon price, a pollution and carbon reduction control strategy is formulated by applying an intelligent optimization algorithm (such as a genetic algorithm or particle swarm optimization). An apparatus includes a processor and a memory.

Description

Technical Field

[0001] The present invention relates to the field of pollution reduction and carbon emission reduction, and particularly to a pollution reduction and carbon emission reduction control method and device for the energy and power industry. Background Art

[0002] Scientific research shows that the excessive emission of greenhouse gases such as carbon dioxide is one of the main reasons for climate warming.

[0003] With the high - proportion penetration of distributed energy (such as renewable energy sources like wind energy and solar energy) and the continuous deepening of the market - oriented reform of the power system, the traditional energy and power system is facing new challenges and opportunities. On the one hand, the intermittency and instability of distributed energy pose higher requirements for the stable operation of the power system; on the other hand, the operation mode of the energy and power industry requires more refined management and optimization means.

[0004] In recent years, the application of artificial intelligence (AI) technology in the energy and power field has gradually matured, including machine learning (ML), deep learning (DL), reinforcement learning (RL), big data analysis, intelligent optimization algorithms, etc. These technologies provide new solutions for pollution reduction and carbon emission reduction in the energy and power industry. For example, through AI technology, intelligent scheduling of the energy system, accurate prediction of carbon emissions, real - time monitoring of pollutant emissions, and dynamic optimization of emission reduction strategies can be achieved. Therefore, combining AI technology with traditional pollution reduction and carbon emission reduction technologies to develop a new type of pollution reduction and carbon emission reduction control method and device has important practical significance and application value.

[0005] In this context, traditional pollution reduction and carbon emission reduction methods are difficult to meet the current needs of the energy and power industry. Summary of the Invention

[0006] The present invention provides a pollution reduction and carbon emission reduction control method and device for the energy and power industry. The present invention makes full use of the planning constraints and demand constraints encountered in the energy and power industry to optimize and calculate the total cost, carbon emission value, and ladder - type carbon price. By setting carbon prices corresponding to different carbon emission amounts, enterprises are encouraged to reduce carbon emissions; the present invention incorporates the ladder - type carbon price into the optimization model, enabling the planning scheme to effectively reduce carbon emissions while meeting the minimum cost, as described in detail below:

[0007] In a first aspect, an embodiment of the present invention provides a pollution reduction and carbon emission reduction control method for the energy and power industry, and the method includes:

[0008] Obtain the GREAN database, combine the planning constraints and demand constraints, and use machine learning algorithms to construct an EPCR model for a high - proportion renewable energy system;

[0009] Incorporate the planning constraints of vegetation area, total carbon emissions, coal consumption, and total pollutant emissions into the objective function of the EPCR model for high proportion of renewable energy;

[0010] Incorporate the stable demand constraints of energy, electricity, and heating required by the system into the objective function of the EPCR model for high proportion of renewable energy;

[0011] Obtain the results of comprehensive planning constraints and demand constraints according to the objective function, and calculate the minimum target values of planned investment, carbon emissions, and pollutant emissions in the energy and power industry based on the results;

[0012] Based on the minimum target values, calculate the total cost and carbon emission values of the energy and power industry through big data analysis; and combine with the stepped carbon price to obtain the pollution reduction and carbon emission control strategy of the energy and power industry by using intelligent optimization algorithms.

[0013] Among them, the acquisition of the GREAN database is as follows: Based on the initial carbon emission data, energy consumption and cost data of the energy and power industry, using different renewable energy data and natural resource endowment differences as boundary conditions, the GREAN database is obtained.

[0014] Among them, the objective function of the EPCR model for high proportion of renewable energy is: total cost, carbon emission value, and pollutant emission value;

[0015] 1) The minimum target of total cost:

[0016]

[0017] In the formula, t represents time; i represents the main industries of carbon emissions, j represents the power generation methods, k represents the heating methods, E i,t represents the energy consumption of each industry; CE i,t represents the unit energy consumption cost of the industry; Q j,t represents the power generation; CQ j,t represents the power generation cost of each power generation method; H k,t represents the heat supply; CH k,t represents the heating cost, VE t represents the forest area; CV t represents the forest conservation cost; CCS t represents the carbon capture volume; CS t represents the construction and operation cost of unit carbon capture volume; EN i,t represents the production energy consumption of new industries; CEN i,t represents the construction cost of supporting facilities for unit energy consumption of new production in each industry; QIN j,t represents the newly installed capacity of the power system; CQN j,t represents the cost of newly installed capacity of the power system; HN k,tIndicates the newly added heat supply; CHN k,t Indicates the construction cost per unit of newly added heat supply; VEN t Indicates the newly added afforestation area; CVN t Indicates the afforestation cost;

[0018] 2) Minimum target of carbon emission value:

[0019]

[0020] In the formula, Q j,t Indicates the power generation; E i,t Indicates the energy consumption of each industry; CNE i,t Indicates the carbon dioxide emission coefficient per unit of production of each industry; CNQ j,t Indicates the carbon dioxide emission coefficient per unit of power generation; CNH k,t Indicates the carbon dioxide emission coefficient per unit of heat supply; βt indicates the carbon dioxide sequestration of the forest per unit area;

[0021] 3) Minimum target of pollutant emission value is:

[0022]

[0023] In the formula, Q j,t Indicates the power generation; E i,t Indicates the energy consumption of each industry; p indicates the type of pollutant; PE i,t,p Indicates the pollutant discharge coefficient per unit of production of each industry; PQ j,t,p Indicates the pollutant discharge coefficient per unit of power generation; CH k,t,p Indicates the pollutant discharge coefficient per unit of heat supply.

[0024] Among them, the planning constraints of the vegetation area, total carbon emissions, coal consumption, and total pollutant emissions are:

[0025] 1) Vegetation area constraint is:

[0026]

[0027] In the formula, VE t Indicates the forest area; DVE t Indicates the vegetation demand; VEN t Indicates the newly added afforestation; γ t Indicates the carbon sink of the carbon storage per unit area of vegetation; CNV t Indicates the lower limit value of the carbon sink;

[0028] 2) Total pollutant emission constraint is:

[0029]

[0030] In the formula, Q j,t represents the power generation; PM t,p represents the upper limit of the total control of each air pollutant; PEM t,p represents the upper limit of the total control of industrial air pollutants; PQM t,p represents the upper limit of the total control of air pollutants in the power system; PHM t,p represents the upper limit of the total control of air pollutants in the heating system;

[0031] 3) The coal consumption constraint is:

[0032]

[0033] In the formula, Q j,t represents the power generation; E i,t represents the energy consumption of each industry; CAE i,t represents the coal consumption per unit of industrial production in each industry; CAQ j,t represents the coal consumption per unit of power generation; CAH k,t represents the coal consumption per unit of heat supply; CAM t represents the upper limit value of the total annual coal consumption; ψ t represents the proportion of the coal consumption plan of the power system.

[0034] 4) The total carbon emission constraint is:

[0035]

[0036] In the formula, Q j,t represents the power generation; E i,t represents the energy consumption of each industry; HN k,t represents the newly added heat supply; CEM t represents the upper limit of the total control of industrial carbon dioxide; CQM t represents the upper limit of the total control of carbon dioxide in the power system; CHM t represents the upper limit of the total control of carbon dioxide in the heating system.

[0037] Among them, the stable demand constraints for the energy, power, and heating required by the system are:

[0038] 1) Power demand and supply constraint:

[0039]

[0040] In the formula, Q j,t represents the power generation; DQ j,t represents the demand for power generation; QI j,t T represents the actual installed capacity of the power system; QIO j,t represents the installed capacity of the power generation to be phased out naturally; QIDj,t represents the installed capacity of non-natural demolition; T represents the annual operating duration of the power system units; η t represents the proportion of new energy;

[0041] 2) The heating demand balance constraint is:

[0042]

[0043] In the formula, DH t represents the heating demand; HN k,t represents the newly added heat supply; HO k,t represents the heat supply phased out naturally; σ represents the proportion of new energy for heating;

[0044] 3) The industrial energy demand supply constraint is:

[0045]

[0046] In the formula, E i,t represents the energy consumption of each industry; DE i,t represents the production energy demand of each industry; EO i,t represents the energy consumption phased out naturally in the production of each industry; EN i,t represents the production energy consumption of the newly added industry.

[0047] On the second aspect, the embodiment of the present invention provides an energy and power industry pollution reduction and carbon emission reduction control device, and the device includes:

[0048] A module for constructing an EPCR model of a high proportion of renewable energy, which is used to obtain the GREAN database, and construct an EPCR model of a high proportion of renewable energy in combination with planning constraints and demand constraints;

[0049] The first inclusion module is used to incorporate the planning constraints of vegetation area, total carbon emissions, coal consumption, and total pollutant emissions into the objective function of the EPCR model of a high proportion of renewable energy;

[0050] The second inclusion module is used to incorporate the stable demand constraints of energy, power, and heating required by the system into the objective function of the EPCR model of a high proportion of renewable energy;

[0051] The minimum objective value module is used to obtain the results of comprehensive planning constraints and demand constraints according to the objective function, and calculate the minimum objective values of planned investment, carbon emissions, and pollutant emissions in the energy and power industry according to the results;

[0052] The control module is used to calculate the total cost and carbon emission value of the energy and power industry based on the minimum objective value; and obtain the pollution reduction and carbon emission reduction control strategy of the energy and power industry in combination with the stepped carbon price.

[0053] Among them, the acquisition of the GREAN database is as follows: Based on the initial carbon emission data, energy consumption and cost data in the energy and power industries, with different renewable energy data and natural resource endowment differences as boundary conditions, the GREAN database is obtained.

[0054] The objective function of the EPCR model for a high proportion of renewable energy includes: the minimum objective of the total cost, the minimum objective of the carbon emission value, and the minimum objective of the pollutant emission value;

[0055] 1) The minimum objective of the total cost:

[0056]

[0057] In the formula, t represents time; i represents the main industries of carbon emissions, j represents the power generation methods, k represents the heating methods, E i,t represents the energy consumption of each industry; CE i,t represents the unit energy consumption cost of the industry; Q j,t represents the power generation; CQ j,t represents the power generation cost of each power generation method; H k,t represents the heat supply; CH k,t represents the heating cost, VE t represents the forest area; CV t represents the forest conservation cost; CCS t represents the carbon capture volume; CS t represents the construction and operation cost per unit of carbon capture volume; EN i,t represents the production energy consumption of the new industry; CEN i,t represents the construction cost of the unit energy consumption supporting facilities for the new production volume of each industry; QIN j,t represents the newly added installed capacity of the power system; CQN j,t represents the cost of the newly added installed capacity of the power system; HN k,t represents the newly added heat supply; CHN k,t represents the construction cost per unit of newly added heat supply; VEN t represents the newly added afforestation area; CVN t represents the afforestation cost;

[0058] 2) The minimum objective of the carbon emission value:

[0059]

[0060] In the formula, Q j,t represents the power generation; E i,t represents the energy consumption of each industry; CNE i,t represents the carbon dioxide emission coefficient per unit of production volume of each industry; CNQ j,tIndicates the carbon dioxide emission factor per unit of electricity generation; CNH k,t Indicates the carbon dioxide emission factor per unit of heat supply; βt indicates the carbon dioxide sequestration amount per unit area of forest;

[0061] 3) The minimum target for pollutant emission values is:

[0062]

[0063] In the formula, Q j,t Indicates the electricity generation; E i,t Indicates the energy consumption of each industry; p indicates the type of pollutant; PE i,t,p Indicates the pollutant discharge coefficient per unit of production of each industry; PQ j,t,p Indicates the pollutant discharge coefficient per unit of electricity generation; CH k,t,p Indicates the pollutant discharge coefficient per unit of heat supply.

[0064] Among them, the planning constraints for the vegetation area, total carbon emissions, coal consumption, and total pollutant emissions are:

[0065] 1) The vegetation area constraint is:

[0066]

[0067] In the formula, VE t Indicates the forest area; DVE t Indicates the vegetation demand; VEN t Indicates the newly added afforestation; γ t Indicates the carbon sink amount per unit area of vegetation volume; CNV t Indicates the lower limit value of the carbon sink amount;

[0068] 2) The total pollutant emission constraint is:

[0069]

[0070] In the formula, Q j,t Indicates the electricity generation; PM t,p Indicates the upper limit of the total control of each air pollutant; PEM t,p Indicates the upper limit of the total control of industrial air pollutants; PQM t,p Indicates the upper limit of the total control of air pollutants in the power system; PHM t,p Indicates the upper limit of the total control of air pollutants in the heating system;

[0071] 3) The coal consumption constraint is:

[0072]

[0073] In the formula, Q j,t Indicates the electricity generation; E i,tIndicates the energy consumption of each industry; CAE i,t Indicates the coal consumption for the production of each industry in the unit; CAQ j,t Indicates the coal consumption for unit power generation; CAH k,t Indicates the coal consumption for unit heat supply; CAM t Indicates the upper limit value of the total annual coal consumption; ψ t Indicates the proportion of the coal consumption plan in the power system;

[0074] 4) The total carbon emission constraint is:

[0075]

[0076] In the formula, Q j,t Indicates the power generation; E i,t Indicates the energy consumption of each industry; HN k,t Indicates the newly added heat supply; CEM t Indicates the upper limit of the total industrial carbon dioxide control; CQM t Indicates the upper limit of the total carbon dioxide control in the power system; CHM t Indicates the upper limit of the total carbon dioxide control in the heating system.

[0077] The stable demand constraints for energy, power, and heating required by the system are:

[0078] 1) Power demand and supply constraint:

[0079]

[0080] In the formula, Q j,t Indicates the power generation; DQ j,t Indicates the demand for power generation; QI j,t T represents the actual installed capacity of the power system; QIO j,t Indicates the installed capacity of power generation phased out naturally; QID j,t Indicates the installed capacity removed unnaturally; T represents the annual operating hours of the power system units; η t Indicates the proportion of new energy;

[0081] 2) Heating demand balance constraint is:

[0082]

[0083] In the formula, DH t Indicates the heating demand; HN k,t Indicates the newly added heat supply; HO k,t Indicates the heat supply phased out naturally; σ represents the proportion of new energy for heating;

[0084] 3) Industrial energy demand and supply constraint is:

[0085]

[0086] In the formula, E i,t represents the energy consumption of each industry; DE i,t represents the energy demand for production in each industry; EO i,t represents the energy consumption of natural elimination in the production of each industry; EN i,t represents the production energy consumption of the new industry.

[0087] In a third aspect, an embodiment of the present invention provides a pollution reduction and carbon emission reduction control device for the energy and power industry. The device includes: a processor and a memory. Program instructions are stored in the memory, and the processor calls the program instructions stored in the memory to enable the device to execute the method described in any item of the first aspect.

[0088] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium. The computer-readable storage medium stores a computer program. The computer program includes program instructions. When the program instructions are executed by a processor, the processor executes the method described in any item of the first aspect.

[0089] The beneficial effects of the technical solution provided by the present invention are as follows:

[0090] 1. By integrating multiple constraints such as ecological protection, energy demand, and pollutant emissions, the present invention constructs a collaborative optimization model, breaks through the limitations of traditional single-objective optimization, and significantly improves the efficiency of environmental governance while ensuring stable energy supply;

[0091] 2. Through machine learning technology, the present invention improves the adaptability and computational efficiency of the EPRC model; integrates the stepped carbon price mechanism and intelligent optimization algorithm to dynamically balance the emission reduction target and system economy, and realizes low-cost and high-precision carbon pollution collaborative control;

[0092] 3. Based on the GREAN database, the present invention constructs a visual analysis system to support closed-loop management from potential assessment to strategy generation; through modular design, it is compatible with multiple energy systems, adapts to multi-energy coupling scenarios such as electricity, heat, and gas, and provides flexible and scalable solutions for different regions. Description of the Drawings

[0093] Figure 1 is a flowchart of a pollution reduction and carbon emission reduction control method for the energy and power industry;

[0094] Figure 2 is a diagram of the EPCR model of the present invention. Detailed Embodiments

[0095] To make the objectives, technical solutions, and advantages of the present invention clearer, the following further describes the embodiments of the present invention in detail.

[0096] To address the challenges posed by the existing technologies, there is an urgent need to propose a new method for optimizing pollution reduction and carbon emission reduction. This method not only needs to comprehensively consider the economic efficiency, stability, and environmental friendliness of the energy and power system, but also needs to utilize advanced AI data analysis and AI optimization algorithms to accurately calculate the pollution reduction and carbon emission reduction data in the energy and power industry, so as to determine the minimized emission reduction targets. In this way, it can provide a scientific basis and technical support for the subsequent implementation of pollution reduction and carbon emission reduction, and promote the energy and power industry to develop towards a more green, low-carbon, and efficient direction.

[0097] To solve the problems in the background technology, the embodiments of the present invention calculate the minimum target of carbon emissions, the minimum target of pollutant emissions, and the planned input cost in combination with the stepped carbon price by using planning constraints and demand constraints, so as to provide standard data for carbon emissions in the energy and power industry.

[0098] Embodiment 1

[0099] A pollution reduction and carbon emission reduction control method for the energy and power industry, see Figure 1 , the method includes the following steps:

[0100] Step 101: Obtain the initial carbon emission data, energy consumption, and cost of the energy and power industry;

[0101] Step 102: Based on the initial carbon emission data, energy consumption, and cost data of the energy and power industry, construct a GREAN database with different renewable energy data and natural resource endowment differences as boundary conditions;

[0102] Step 103: Based on the GREAN database, combine planning constraints and demand constraints, and use machine learning algorithms to construct an EPCR model for a high proportion of renewable energy; Step 104: Incorporate comprehensive planning constraints such as vegetation area, total carbon emissions, coal consumption, and total pollutant emissions into the objective function of the EPCR model for a high proportion of renewable energy;

[0103] Step 105: Incorporate demand constraints such as the energy, electricity, heating, and stability requirements needed by the system into the objective function of the EPCR model for a high proportion of renewable energy;

[0104] Step 106: Obtain the results of comprehensive planning constraints and demand constraints according to the objective function, and calculate the minimum target values of the planned input, carbon emissions, pollutant emissions, etc. of the energy and power industry according to the results;

[0105] Step 107: Calculate information such as the total cost and carbon emission value of the energy and power industry through big data analysis based on the minimum target values of the planned input, carbon emissions, pollutant emissions, etc.;

[0106] Step 108: Based on information such as the total cost and carbon emission value of the energy and power industry, combined with the stepped carbon price, use the intelligent optimization algorithm to generate the pollution reduction and carbon emission reduction control strategy for the energy and power industry.

[0107] In summary, through the above steps 101-108, the embodiments of the present invention can optimize the minimum objective function through planning constraints and demand constraints, and then calculate the total cost, carbon emission value, and combine the stepped carbon price to obtain the pollution reduction and carbon emission reduction control strategy for the energy and power industry.

[0108] Embodiment 2

[0109] The following further introduces the solution in Embodiment 1 in combination with specific calculation formulas and examples. See the following description for details:

[0110] First aspect: Construct the EPCR model with a high proportion of renewable energy

[0111] See Figure 2 The objective function of the GTEP optimization model with a high proportion of renewable energy is the total cost, carbon emission value, and pollutant emission value.

[0112] 1) Minimum objective of the planned total input cost:

[0113]

[0114] In the formula, t represents time; i represents the main industries with carbon emissions, where i = 1, 2, 3, 4; 1, 2, 3, and 4 respectively represent the steel, chemical, building materials, and other coal-using industries; j represents the power generation method, where j = 1, 2, 3, 4; 1, 2, 3, 4, and 5 respectively represent thermal power, nuclear power, hydropower, wind power, and solar energy; k represents the heating method, where k = 1, 2, 1, and 2 respectively represent coal-fired heating and non-coal-fired heating; E i,t represents the energy consumption of each industry; CE i,t represents the unit energy consumption cost of the industry; Q j,t represents the power generation; CQ j,t represents the power generation cost of each power generation method; H k,t represents the heat supply; CH k,t represents the heating cost, VE t represents the forest area; CV t represents the forest conservation cost; CCS t represents the carbon capture volume; CS t represents the construction and operation cost per unit carbon capture volume; EN i,t represents the production energy consumption of the new industry; CEN i,t represents the construction cost of the supporting facilities for the unit energy consumption of the new production volume in each industry; QIN j,t represents the newly installed capacity of the power system; CQN j,tDenote the cost of newly installed capacity in the power system; HN k,t Denote the newly added heat supply; CHN k,t Denote the construction cost per unit of newly added heat supply; VEN t Denote the newly added afforestation area; CVN t Denote the afforestation cost.

[0115] 2) Minimum carbon emission target:

[0116]

[0117] In the formula, Q j,t Denote the power generation; E i,t Denote the energy consumption of each industry; CNE i,t Denote the carbon dioxide emission coefficient per unit of production of each industry; CNQ j,t Denote the carbon dioxide emission coefficient per unit of power generation; CNH k,t Denote the carbon dioxide emission coefficient per unit of heat supply; βt denotes the carbon dioxide sequestration of the forest per unit area.

[0118] 3) The minimum pollutant emission target is:

[0119]

[0120] In the formula, Q j,t Denote the power generation; E i,t Denote the energy consumption of each industry; p denotes the type of pollutant, p = 1, 2......, where 1 and 2 denote sulfur dioxide and nitrogen oxides respectively; PE i,t,p Denote the pollutant discharge coefficient per unit of production of each industry; PQ j,t,p Denote the pollutant discharge coefficient per unit of power generation; CH k,t,p Denote the pollutant discharge coefficient per unit of heat supply.

[0121] Second, the power system planning constraints mainly characterize multiple factors including resource and environmental endowments:

[0122] 1) The vegetation area constraint is:

[0123]

[0124] In the formula, VE t Denote the forest area; DVE t Denote the vegetation demand; VEN t Denote the newly added afforestation; γ t Denote the carbon sink of the carbon storage per unit area of vegetation; CNV t Denote the lower limit value of the carbon sink.

[0125] 2) The total pollutant emission limit is:

[0126]

[0127] In the formula, Q j,t represents the generated electricity; PM t,p represents the upper limit of the total control of each air pollutant; PEM t,p represents the upper limit of the total control of industrial air pollutants; PQM t,p represents the upper limit of the total control of air pollutants in the power system; PHM t,p represents the upper limit of the total control of air pollutants in the heating system.

[0128] 3) The total coal consumption control constraint is:

[0129]

[0130] In the formula, Q j,t represents the generated electricity; E i,t represents the energy consumption of each industry; CAE i,t represents the coal consumption per unit of production of each industry; CAQ j,t represents the coal consumption per unit of generated electricity; CAH k,t represents the coal consumption per unit of heat supply; CAM t represents the upper limit value of the annual total coal consumption; ψ t represents the proportion of the coal consumption plan of the power system.

[0131] 4) The total carbon emission control constraint of each industry is:

[0132]

[0133] In the formula, Q j,t represents the generated electricity; E i,t represents the energy consumption of each industry; HN k,t represents the newly added heat supply; CEM t represents the upper limit of the total control of industrial carbon dioxide; CQM t represents the upper limit of the total control of carbon dioxide in the power system; CHM t represents the upper limit of the total control of carbon dioxide in the heating system.

[0134] Thirdly, the operation constraints of the power system mainly characterize the resource requirements of the industry as follows:

[0135] 1) Power demand and supply constraint:

[0136]

[0137] In the formula, Q j,t represents the generated electricity; DQ j,t represents the demanded electricity; QIj,t T represents the installed capacity of the actual power system; QIO j,t represents the installed capacity of power generation phased out naturally; QID j,t represents the installed capacity removed unnaturally; T represents the annual operating hours of power system units; η t represents the proportion of new energy.

[0138] 2) The balance of heating demand is:

[0139]

[0140] In the formula, DH t represents the heating demand; HN k,t represents the newly added heat supply; HO k,t represents the heat supply phased out naturally; σ represents the proportion of new energy for heating.

[0141] 3) The supply constraint of industrial energy demand is:

[0142]

[0143] In the formula, E i,t represents the energy consumption of each industry; DE i,t represents the production energy demand of each industry; EO i,t represents the energy consumption of the natural phased-out amount in the production of each industry; EN i,t represents the production energy consumption of the newly added industry.

[0144] Fourthly, the calculation of the stepped carbon price for pollution reduction and carbon emission reduction in the power system is as follows:

[0145] Based on the planning constraints and demand constraints, and the higher the carbon emissions, the higher the corresponding carbon trading price. A stepped carbon trading calculation model is established. After calculating the total carbon emissions, a stepped carbon trading model is formulated to calculate the stepped carbon price.

[0146]

[0147] In the formula, is the transaction cost of the carbon market, h is the minimum target value of carbon emissions, λ is the basic price of carbon market transactions, ρ is the price increase rate, and l is the length of the carbon emission interval.

[0148] In summary, through the above model, the embodiment of the present invention can optimize the minimum objective function through planning constraints and demand constraints, and then calculate the total cost, carbon emission value, and combine the stepped carbon price to obtain the pollution reduction and carbon emission reduction control strategy for the energy and power industry.

[0149] Embodiment 3

[0150] Next, in combination with specific formulas, the EPCR model is completed, as described in detail below:

[0151] 201: The power system planning constraints mainly represent various factors including the resource and environmental endowment, including:

[0152] 2011: The vegetation area constraint is:

[0153]

[0154] In the formula, VE t represents the forest area; DVE t represents the vegetation demand; VEN t represents the newly added afforestation; γ t represents the carbon sink amount per unit area of vegetation stock; CNV t represents the lower limit value of the carbon sink amount.

[0155] 2012: The total pollutant emission limit is:

[0156]

[0157] In the formula, Q j,t represents the power generation; PM t,p represents the upper limit of the total control of each air pollutant; PEM t,p represents the upper limit of the total control of industrial air pollutants; PQM t,p represents the upper limit of the total control of air pollutants in the power system; PHM t,p represents the upper limit of the total control of air pollutants in the heating system.

[0158] 2013: The total coal consumption control constraint is:

[0159]

[0160] In the formula, Q j,t represents the power generation; E i,t represents the energy consumption of each industry; CAE i,t represents the coal consumption per unit production of each industry; CAQ j,t represents the coal consumption per unit power generation; CAH k,t represents the coal consumption per unit heat supply; CAM t represents the upper limit value of the annual total coal consumption; ψ t represents the proportion of the coal consumption plan in the power system.

[0161] 2014: The total carbon emission control constraint for each industry is:

[0162]

[0163] In the formula, Q j,t represents the power generation; E i,tIndicates the energy consumption of each industry; HN k,t Indicates the newly added heat supply; CEM t Indicates the upper limit of the total carbon dioxide control for the industry; CQM t Indicates the upper limit of the total carbon dioxide control for the power system; CHM t Indicates the upper limit of the total carbon dioxide control for the heating system.

[0164] The operation constraints of the power system mainly characterize the demand for industry resources as follows:

[0165] 2015: Power demand - supply constraint:

[0166]

[0167] In the formula, Q j,t Indicates the power generation; DQ j,t Indicates the demand for power generation; QI j,t T represents the actual installed capacity of the power system; QIO j,t Indicates the installed capacity of power generation phased out naturally; QID j,t Indicates the installed capacity removed unnaturally; T represents the annual operating hours of the power system units; η t Indicates the proportion of new energy.

[0168] 2016: The heating demand balance is:

[0169]

[0170] In the formula, DH t Indicates the heating demand; HN k,t Indicates the newly added heat supply; HO k,t Indicates the heat supply phased out naturally; σ represents the proportion of new - energy heating.

[0171] 2017: The industrial energy demand - supply constraint is:

[0172]

[0173] In the formula, E i,t Indicates the energy consumption of each industry; DE i,t Indicates the production energy demand of each industry; EO i,t Indicates the energy consumption of the natural phasing - out of production in each industry; EN i,t Indicates the production energy consumption of the newly added industry.

[0174] Example 4

[0175] The following combines the above - mentioned comprehensive planning constraints and demand constraints to optimize the minimum objective function and combines it with the ladder - type carbon price, details are as follows:

[0176] 301: The planned investment cost, minimum carbon emission target, and minimum pollutant emission target of the power system are as follows:

[0177] 3011: Minimum target for planned input cost:

[0178]

[0179] In the formula, t represents time; i represents the main industries with carbon emissions, where i = 1, 2, 3, 4; 1, 2, 3, and 4 represent the steel, chemical, building materials, and other coal - using industries respectively; j represents the power generation method, where j = 1, 2, 3, 4; 1, 2, 3, 4, and 5 represent thermal power, nuclear power, hydropower, wind power, and solar energy respectively; k represents the heating method, where k = 1, 2, and 1 and 2 represent coal - fired heating and non - coal - fired heating respectively; E i,t represents the energy consumption of each industry; CE i,t represents the unit energy consumption cost of the industry; Q j,t represents the power generation; CQ j,t represents the power generation cost of each power generation method; H k,t represents the heat supply; CH k,t represents the heating cost, VE t represents the forest area; CV t represents the forest conservation cost; CCS t represents the carbon capture volume; CS t represents the construction and operation cost per unit carbon capture volume; EN i,t represents the production energy consumption of the new industry; CEN i,t represents the construction cost of the supporting facilities for unit energy consumption of the new production volume in each industry; QIN j,t represents the newly installed capacity of the power system; CQN j,t represents the cost of the newly installed capacity of the power system; HN k,t represents the newly added heat supply; CHN k,t represents the construction cost per unit newly added heat supply; VEN t represents the newly added afforestation area; CVN t represents the afforestation cost.

[0180] 3012: Minimum carbon emission target:

[0181]

[0182] In the formula, Q j,t represents the power generation; E i,t represents the energy consumption of each industry; CNE i,t represents the carbon dioxide emission coefficient per unit production volume of each industry; CNQ j,t represents the carbon dioxide emission coefficient per unit power generation; CNH k,tIt represents the carbon dioxide emission coefficient per unit of heat supply; βt represents the carbon dioxide accumulation amount per unit area of the forest.

[0183] 3013: The minimum target for pollutant emissions is:

[0184]

[0185] In the formula, Q j,t represents the power generation; E i,t represents the energy consumption of each industry; p represents the type of pollutant, p = 1, 2......, where 1 and 2 represent sulfur dioxide and nitrogen oxides respectively; PE i,t,p represents the pollutant discharge coefficient per unit of production of each industry; PQ j,t,p represents the pollutant discharge coefficient per unit of power generation; CH k,t,p represents the pollutant discharge coefficient per unit of heat supply.

[0186] 302: The calculation of the stepped carbon price for pollution reduction and carbon emission reduction in the power system is as follows:

[0187] Based on the planning constraints, demand constraints, and the higher the carbon emissions, the higher the corresponding carbon trading price. A stepped carbon trading calculation model is established. After calculating the total carbon emissions, a stepped carbon trading model is formulated to calculate the stepped carbon price.

[0188]

[0189] In the formula, C co2 is the carbon market trading cost, h is the minimum target value of carbon emissions; λ is the basic price of carbon market trading, ρ is the price increase rate, and l is the length of the carbon emission interval.

[0190] Example 5

[0191] The following combines specific examples to verify the feasibility of this method. See the following description for details:

[0192] Taking a thermal power plant in Tianjin as the research object, its initial carbon emission data and energy consumption data in the park are collected, and based on its planning constraints and demand constraints, its minimum carbon emission target, planned cost, and stepped carbon price are obtained through optimization calculation.

[0193] Table 1

[0194]

[0195] Example 6

[0196] A pollution reduction and carbon emission reduction control device for the energy and power industry, the device includes:

[0197] A module for constructing an EPCR model with a high proportion of renewable energy, which is used to obtain the GREAN database, combine the planning constraints and demand constraints, and construct an EPCR model with a high proportion of renewable energy;

[0198] The first inclusion module is used to incorporate the planning constraints of vegetation area, total carbon emissions, coal consumption, and total pollutant emissions into the objective function of the EPCR model with a high proportion of renewable energy;

[0199] The second inclusion module is used to incorporate the stable demand constraints of energy, electricity, and heating required by the system into the objective function of the EPCR model with a high proportion of renewable energy;

[0200] The minimum objective value module is used to obtain the results of the comprehensive planning constraints and demand constraints according to the objective function, and calculate the minimum objective values of the planned investment, carbon emissions, and pollutant emissions in the energy and power industries based on the results;

[0201] The control module is used to calculate the total cost and carbon emission value of the energy and power industries based on the minimum objective value; and combine the stepped carbon price to obtain the pollution reduction and carbon emission control strategy for the energy and power industries.

[0202] Among them, obtaining the GREAN database is: based on the initial carbon emission data, energy consumption and cost data of the energy and power industries, using different renewable energy data and natural resource endowment differences as boundary conditions to obtain the GREAN database.

[0203] Among them, the objective function of the EPCR model with a high proportion of renewable energy includes: the minimum objective of the total cost, the minimum objective of the carbon emission value, and the minimum objective of the pollutant emission value;

[0204] 1) The minimum objective of the total cost:

[0205]

[0206] In the formula, t represents time; i represents the main industries of carbon emissions, j represents the power generation methods, k represents the heating methods, E i,t represents the energy consumption of each industry; CE i,t represents the unit energy consumption cost of the industry; Q j,t represents the power generation; CQ j,t represents the power generation cost of each power generation method; H k,t represents the heat supply; CH k,t represents the heating cost, VE t represents the forest area; CV t represents the forest conservation cost; CCS t represents the carbon capture volume; CS t represents the construction and operation cost per unit carbon capture volume; EN i,tRepresents the production energy consumption of the newly added industries; CEN i,t Represents the construction cost of the energy consumption supporting facilities per unit of the newly added production volume in each industry; QIN j,t Represents the newly added installed capacity of the power system; CQN j,t Represents the cost of the newly added installed capacity of the power system; HN k,t Represents the newly added heat supply; CHN k,t Represents the construction cost per unit of the newly added heat supply; VEN t Represents the newly added afforestation area; CVN t Represents the afforestation cost;

[0207] 2) The minimum target of the carbon emission value:

[0208]

[0209] In the formula, Q j,t Represents the power generation; E i,t Represents the industrial energy consumption in each industry; CNE i,t Represents the carbon dioxide emission coefficient per unit of industrial production volume in each industry; CNQ j,t Represents the carbon dioxide emission coefficient per unit of power generation; CNH k,t Represents the carbon dioxide emission coefficient per unit of heat supply; βt represents the carbon dioxide accumulation amount per unit area of the forest;

[0210] 3) The minimum target of the pollutant emission value is:

[0211]

[0212] In the formula, Q j,t Represents the power generation; E i,t Represents the industrial energy consumption in each industry; p represents the type of pollutant; PE i,t,p Represents the pollutant discharge coefficient per unit of industrial production volume in each industry; PQ j,t,p Represents the pollutant discharge coefficient per unit of power generation; CH k,t,p Represents the pollutant discharge coefficient per unit of heat supply.

[0213] Among them, the planning constraints of the vegetation area, total carbon emissions, coal consumption, and total pollutant emissions are:

[0214] 1) The vegetation area constraint is:

[0215]

[0216] In the formula, VE t Represents the forest area; DVE t Represents the vegetation demand; VEN t Represents the newly added afforestation; γ tCarbon sink quantity representing the vegetation stock per unit area; CNV t Represents the lower limit value of the carbon sink quantity;

[0217] 2) The total pollutant emissions constraint is:

[0218]

[0219] In the formula, Q j,t Represents the power generation; PM t,p Represents the upper limit of the total control of each air pollutant; PEM t,p Represents the upper limit of the total control of industrial air pollutants; PQM t,p Represents the upper limit of the total control of air pollutants in the power system; PHM t,p Represents the upper limit of the total control of air pollutants in the heating system;

[0220] 3) The coal consumption constraint is:

[0221]

[0222] In the formula, Q j,t Represents the power generation; E i,t Represents the energy consumption of each industry; CAE i,t Represents the coal consumption per unit production of each industry; CAQ j,t Represents the coal consumption per unit power generation; CAH k,t Represents the coal consumption per unit heat supply; CAM t Represents the upper limit value of the annual total coal consumption; ψ t Represents the proportion of the coal consumption plan in the power system;

[0223] 4) The total carbon emissions constraint is:

[0224]

[0225] In the formula, Q j,t Represents the power generation; E i,t Represents the energy consumption of each industry; HN k,t Represents the newly added heat supply; CEM t Represents the upper limit of the total control of industrial carbon dioxide; CQM t Represents the upper limit of the total control of carbon dioxide in the power system; CHM t Represents the upper limit of the total control of carbon dioxide in the heating system.

[0226] Among them, the stable demand constraints for the energy, electricity, and heating required by the system are:

[0227] 1) Power demand and supply constraint:

[0228]

[0229] Wherein, Q j,t represents the generated electricity; DQ j,t represents the demand for electricity generation; QI j,t T represents the installed capacity of the actual power system; QIO j,t represents the installed capacity of power generation phased out naturally; QID j,t represents the installed capacity removed unnaturally; T represents the annual operating hours of the power system units; η t represents the proportion of new energy;

[0230] 2) The heat supply demand balance constraint is:

[0231]

[0232] Wherein, DH t represents the heat supply demand; HN k,t represents the newly added heat supply; HO k,t represents the heat supply phased out naturally; σ represents the proportion of new energy for heat supply;

[0233] 3) The industrial energy demand supply constraint is:

[0234]

[0235] Wherein, E i,t represents the energy consumption of each industry; DE i,t represents the energy demand for industrial production of each industry; EO i,t represents the energy consumption of natural elimination of industrial production of each industry; EN i,t represents the energy consumption of industrial production of newly added industries.

[0236] In summary, through the above modules, the embodiments of the present invention can optimize the minimum objective function through planning constraints and demand constraints, and then calculate the total cost, carbon emission value, and combine the stepped carbon price to obtain the pollution reduction and carbon emission reduction control strategy for the energy and power industry.

[0237] Embodiment 7

[0238] A pollution reduction and carbon emission reduction control device for the energy and power industry, the device includes: a processor and a memory, and program instructions are stored in the memory. The processor calls the program instructions stored in the memory to enable the device to execute the following method steps in Embodiment 1:

[0239] Obtain the GREAN database, and combine planning constraints and demand constraints to construct an EPCR model with a high proportion of renewable energy;

[0240] Incorporate the planning constraints of vegetation area, total carbon emissions, coal consumption, and total pollutant emissions into the objective function of the EPCR model with a high proportion of renewable energy;

[0241] Incorporate the stable demand constraints for energy, electricity, and heating required by the system into the objective function of the EPCR model with a high proportion of renewable energy;

[0242] Obtain the results of the comprehensive planning constraints and demand constraints according to the objective function, and calculate the minimum target values of the planned investment, carbon emissions, and pollutant emissions in the energy and power industries based on the results;

[0243] Calculate the total cost and carbon emission value of the energy and power industries based on the minimum target values; and combine with the stepped carbon price to obtain the pollution reduction and carbon emission control strategy for the energy and power industries.

[0244] Among them, obtaining the GREAN database is as follows: Based on the initial carbon emission data, energy consumption and cost data of the energy and power industries, using different renewable energy data and natural resource endowment differences as boundary conditions, the GREAN database is obtained.

[0245] Among them, the objective function of the EPCR model with a high proportion of renewable energy is: total cost, carbon emission value, and pollutant emission value;

[0246] 1) Minimum target of total cost:

[0247]

[0248] In the formula, t represents time; i represents the main industries of carbon emissions, j represents the power generation methods, k represents the heating methods, E i,t represents the energy consumption of each industry; CE i,t represents the unit energy consumption cost of the industry; Q j,t represents the power generation; CQ j,t represents the power generation cost of each power generation method; H k,t represents the heat supply; CH k,t represents the heating cost, VE t represents the forest area; CV t represents the forest conservation cost; CCS t represents the carbon capture volume; CS t represents the construction and operation cost per unit of carbon capture volume; EN i,t represents the production energy consumption of new industries; CEN i,t represents the construction cost of supporting facilities for unit energy consumption of new production in each industry; QIN j,t represents the newly added installed capacity of the power system; CQN j,t represents the cost of newly added installed capacity of the power system; HN k,t represents the newly added heat supply; CHN k,t represents the construction cost per unit of newly added heat supply; VEN t represents the newly added afforestation area; CVN tIndicates the cost of afforestation;

[0249] 2) Minimum target of carbon emission value:

[0250]

[0251] In the formula, Q j,t Indicates the power generation; E i,t Indicates the energy consumption of each industry; CNE i,t Indicates the carbon dioxide emission coefficient per unit of production of each industry; CNQ j,t Indicates the carbon dioxide emission coefficient per unit of power generation; CNH k,t Indicates the carbon dioxide emission coefficient per unit of heat supply; βt represents the carbon dioxide accumulation amount per unit area of forest;

[0252] 3) Minimum target of pollutant emission value is:

[0253]

[0254] In the formula, Q j,t Indicates the power generation; E i,t Indicates the energy consumption of each industry; p represents the type of pollutant; PE i,t,p Indicates the pollutant discharge coefficient per unit of production of each industry; PQ j,t,p Indicates the pollutant discharge coefficient per unit of power generation; CH k,t,p Indicates the pollutant discharge coefficient per unit of heat supply.

[0255] Among them, the planning constraints of vegetation area, total carbon emission, coal consumption, and total pollutant emission are:

[0256] 1) Vegetation area constraint is:

[0257]

[0258] In the formula, VE t Indicates the forest area; DVE t Indicates the vegetation demand; VEN t Indicates the newly added afforestation; γ t Indicates the carbon sink amount of carbon storage per unit area of vegetation; CNV t Indicates the lower limit value of carbon sink amount;

[0259] 2) Total pollutant emission constraint is:

[0260]

[0261] In the formula, Q j,t Indicates the power generation; PM t,p Indicates the upper limit of total control of each air pollutant; PEM t,pRepresents the upper limit of the total control of industrial air pollutants; PQM t,p Represents the upper limit of the total control of air pollutants in the power system; PHM t,p Represents the upper limit of the total control of air pollutants in the heating system;

[0262] 3) The constraint on coal consumption is:

[0263]

[0264] In the formula, Q j,t Represents the power generation; E i,t Represents the industrial energy consumption of each industry; CAE i,t Represents the coal consumption per unit of industrial production of each industry; CAQ j,t Represents the coal consumption per unit of power generation; CAH k,t Represents the coal consumption per unit of heat supply; CAM t Represents the upper limit value of the total annual coal consumption; ψ t Represents the proportion of coal consumption planning in the power system.

[0265] 4) The constraint on the total carbon emissions is:

[0266]

[0267] In the formula, Q j,t Represents the power generation; E i,t Represents the industrial energy consumption of each industry; HN k,t Represents the newly added heat supply; CEM t Represents the upper limit of the total industrial carbon dioxide control; CQM t Represents the upper limit of the total carbon dioxide control in the power system; CHM t Represents the upper limit of the total carbon dioxide control in the heating system.

[0268] Among them, the stable demand constraints for energy, electricity, and heating required by the system are:

[0269] 1) Power demand supply constraint:

[0270]

[0271] In the formula, Q j,t Represents the power generation; DQ j,t Represents the demand for power generation; QI j,t T represents the actual installed capacity of the power system; QIO j,t Represents the installed capacity of power generation phased out naturally; QID j,t Represents the installed capacity removed unnaturally; T represents the annual operating hours of the power system unit; η t Represents the proportion of new energy;

[0272] 2) The heat supply demand balance constraint is as follows:

[0273]

[0274] In the formula, DH t represents the heat supply demand; HN k,t represents the newly added heat supply; HO k,t represents the heat supply phased out naturally; σ represents the proportion of new energy heat supply;

[0275] 3) The industrial energy demand supply constraint is as follows:

[0276]

[0277] In the formula, E i,t represents the industrial energy consumption of each industry; DE i,t represents the industrial production energy demand of each industry; EO i,t represents the energy consumption of the natural phased out amount of industrial production of each industry; EN i,t represents the production energy consumption of the newly added industry.

[0278] It should be noted here that the device description in the above embodiments corresponds to the method description in the embodiments, and the embodiments of the present invention will not be elaborated herein.

[0279] The execution subjects of the above-mentioned processor and memory can be devices with computing functions such as a computer, a single-chip microcomputer, and a microcontroller. Specifically, in implementation, the embodiments of the present invention do not limit the execution subject, and it is selected according to the needs in actual applications.

[0280] Data signals are transmitted between the memory and the processor through a bus, and the embodiments of the present invention will not be elaborated herein.

[0281] Based on the same inventive concept, the embodiments of the present invention also provide a computer-readable storage medium. The storage medium includes a stored program, and when the program runs, it controls the device where the storage medium is located to execute the method steps in the above embodiments.

[0282] The computer-readable storage medium includes, but is not limited to, flash memory, hard disk, solid-state drive, etc.

[0283] It should be noted here that the description of the readable storage medium in the above embodiments corresponds to the method description in the embodiments, and the embodiments of the present invention will not be elaborated herein.

[0284] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions according to the embodiments of the present invention are generated in whole or in part.

[0285] The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted through a computer-readable storage medium. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that integrates one or more available media. The available medium can be a magnetic medium or a semiconductor medium, etc.

[0286] In the embodiments of the present invention, except for those with special specifications for the models of each device, the models of other devices are not limited, as long as the devices can perform the above functions.

[0287] Those skilled in the art can understand that the drawings are only schematic diagrams of a preferred embodiment, and the serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0288] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for reducing pollution and carbon emissions in the energy and power industry, characterized in that: The method comprises: Obtain the GREAN database, combine planning constraints and demand constraints, and use machine learning algorithms to build an EPCR model with a high proportion of renewable energy; Incorporate planning constraints of vegetation area, total carbon emissions, coal consumption, and total pollutant emissions into the objective function of the EPCR model with a high proportion of renewable energy; Incorporate the stable demand constraints of energy, electricity, and heat required by the system into the objective function of the EPCR model with a high proportion of renewable energy; The results of comprehensive planning constraints and demand constraints are obtained according to the objective function, and the minimum target values ​​of planned investment, carbon emissions, and pollutant emissions of the energy and power industry are calculated using deep learning algorithms based on the results; Based on the minimum target value, big data analysis technology is used to calculate the total cost and carbon emission value of the energy and power industry; and combined with the step-by-step carbon price, the pollution reduction and carbon reduction control strategy of the energy and power industry is obtained through an intelligent optimization algorithm.

2. A method for reducing pollution and carbon emissions in the energy and power industry according to claim 1, characterized in that: The GREAN database is obtained by: based on the initial carbon emission data, energy consumption and cost data of the energy and power industry, taking different renewable energy data and natural resource endowment differences as boundary conditions, obtaining the GREAN database.

3. A method for reducing pollution and carbon emissions in the energy and power industry according to claim 1, characterized in that: The objective function of the EPCR model for high proportion of renewable energy includes: a minimum target for total cost, a minimum target for carbon emission value, and a minimum target for pollutant emission value; 1) Minimum total cost goal: In the formula, t represents time; i represents the main carbon emission industry, j represents the power generation method, k represents the heating method, and E i,t Indicates the energy consumption of various industries; CE i,t represents the unit energy consumption cost of the industry; Q j,t Indicates power generation; CQ j,t represents the power generation cost of each power generation method; H k,t Indicates heating supply; CH k,t represents the heating cost, VE t represents forest area; CV t represents the cost of forest maintenance; CCS t represents carbon capture; CS t Indicates the construction and operation cost per unit of carbon capture; EN i,t Indicates the production energy consumption of new industries; CEN i,t It represents the construction cost of supporting facilities for energy consumption per unit of new production in each industry; QIN j,t Indicates the newly installed capacity of the power system; CQN j,t HN represents the cost of newly installed capacity in the power system; k,t Indicates the additional heating supply; CHN k,t VEN represents the construction cost of unit additional heating supply; t Indicates newly planted afforestation area; CVN t represents the cost of afforestation; 2) Minimum carbon emission target: In the formula, Q j,t Indicates the amount of electricity generated; E i,t Indicates the energy consumption of various industries; CNE i,t Indicates the carbon dioxide emission coefficient per unit of industrial production in each industry; CNQ j,t Indicates the carbon dioxide emission coefficient per unit of electricity generation; CNH k,t represents the carbon dioxide emission coefficient per unit heat supply; βt represents the carbon dioxide sequestration per unit area of ​​forest; 3) The minimum target for pollutant emissions is: In the formula, Q j,t Indicates the amount of electricity generated; E i,t represents the energy consumption of each industry; p represents the type of pollutant; PE i,t,p Indicates the pollution emission coefficient of each industry's production volume; PQ j,t,p Indicates the emission coefficient per unit of power generation; CH k,t,p Indicates the sewage discharge coefficient per unit heat supply.

4. A method for reducing pollution and carbon emissions in the energy and power industry according to claim 1, characterized in that: The planning constraints for vegetation area, total carbon emissions, coal consumption, and total pollutant emissions are: 1) Vegetation area constraints are: Where, VE t Indicates forest area; DVE t Indicates vegetation demand; VEN t Indicates new afforestation; γ t Indicates the carbon sink of vegetation accumulation per unit area; CNV t Indicates the lower limit of carbon sink; 2) The total amount of pollutant emissions is constrained as follows: In the formula, Q j,t Indicates power generation; PM t,p Indicates the upper limit of total amount control of each air pollutant; PEM t,p It indicates the upper limit of the total amount of industrial air pollutants; PQM t,p It represents the upper limit of the total amount of air pollutants in the power system; PHM t,p It indicates the upper limit of the total amount of air pollutants in the heating system; 3) The coal consumption constraints are: In the formula, Q j,t Indicates the amount of electricity generated; E i,t Indicates the energy consumption of various industries; CAE i,t Indicates coal consumption per unit of industrial production in each industry; CAQ j,t Indicates coal consumption per unit of electricity generation; CAH k,t Indicates coal consumption per unit of heat supply; CAM t Indicates the upper limit of annual coal consumption; ψ t Indicates the planned proportion of coal consumption in the power system; 4) The total carbon emission limit is: In the formula, Q j,t Indicates the amount of electricity generated; E i,t Indicates the energy consumption of various industries; HN k,t Indicates the additional heating supply; CEM t It represents the upper limit of total carbon dioxide volume control in the industry; CQM t Represents the upper limit of total carbon dioxide in the power system; CHM t Indicates the upper limit of total carbon dioxide control in the heating system.

5. A method for reducing pollution and carbon emissions in the energy and power industry according to claim 1, characterized in that: The stable demand constraints for energy, electricity and heating required by the system are: 1) Power demand and supply constraints: In the formula, Q j,t Indicates power generation; DQ j,t Indicates demand for power generation; QI j,t T represents the actual installed capacity of the power system; QIO j,t Indicates the installed capacity of power generation that is naturally phased out; QID j,t represents the installed capacity that is not removed naturally; T represents the operating time of the power system units per year; η t Indicates the proportion of new energy; 2) The heat demand balance constraint is: In the formula, DH t Indicates heating demand; HN k,t Indicates the additional heating supply; HO k,t represents the natural elimination of heating; σ represents the proportion of heating from new energy sources; 3) Industrial energy demand and supply constraints are: In the formula, E i,t Indicates the energy consumption of various industries; DE i,t Indicates the energy demand of various industries; EO i,t Indicates the energy consumption of natural elimination in production of various industries; EN i,t Represents the production energy consumption of new industries.

6. A pollution reduction and carbon reduction control device for the energy and power industry, characterized in that: The device comprises: The module for constructing the EPCR model with a high proportion of renewable energy is used to obtain the GREAN database and construct the EPCR model with a high proportion of renewable energy by combining planning constraints and demand constraints; The first incorporation module is used to incorporate the planning constraints of vegetation area, total carbon emissions, coal consumption, and total pollutant emissions into the objective function of the EPCR model with a high proportion of renewable energy; The second incorporation module is used to incorporate the stable demand constraints of energy, electricity, and heat required by the system into the objective function of the EPCR model with a high proportion of renewable energy; The minimum target value module is used to obtain the results of comprehensive planning constraints and demand constraints based on the objective function, and calculate the minimum target values ​​of planned investment, carbon emissions, and pollutant emissions in the energy and power industry based on the results; The control module is used to calculate the total cost and carbon emission value of the energy and power industry based on the minimum target value; and to obtain the pollution reduction and carbon reduction control strategy of the energy and power industry in combination with the tiered carbon price.

7. A pollution reduction and carbon reduction control device for the energy and power industry according to claim 6, characterized in that: The GREAN database is obtained by: based on the initial carbon emission data, energy consumption and cost data of the energy and power industry, taking different renewable energy data and natural resource endowment differences as boundary conditions, obtaining the GREAN database.

8. The pollution reduction and carbon reduction control device for the energy and power industry according to claim 6 is characterized in that: The objective function of the EPCR model for high proportion of renewable energy includes: a minimum target for total cost, a minimum target for carbon emission value, and a minimum target for pollutant emission value; 1) Minimum total cost goal: In the formula, t represents time; i represents the main carbon emission industry, j represents the power generation method, k represents the heating method, and E i,t Indicates the energy consumption of various industries; CE i,t represents the unit energy consumption cost of the industry; Q j,t Indicates power generation; CQ j,t represents the power generation cost of each power generation method; H k,t Indicates heating supply; CH k,t represents the heating cost, VE t represents forest area; CV t represents the cost of forest maintenance; CCS t represents carbon capture; CS t Indicates the construction and operation cost per unit of carbon capture; EN i,t Indicates the production energy consumption of new industries; CEN i,t It represents the construction cost of supporting facilities for energy consumption per unit of new production in each industry; QIN j,t Indicates the newly installed capacity of the power system; CQN j,t HN represents the cost of newly installed capacity in the power system; k,t Indicates the additional heating supply; CHN k,t VEN represents the construction cost of unit additional heating supply; t Indicates newly planted afforestation area; CVN t represents the cost of afforestation; 2) Minimum carbon emission target: In the formula, Q j,t Indicates the amount of electricity generated; E i,t Indicates the energy consumption of various industries; CNE i,t Indicates the carbon dioxide emission coefficient per unit of industrial production in each industry; CNQ j,t Indicates the carbon dioxide emission coefficient per unit of electricity generation; CNH k,t represents the carbon dioxide emission coefficient per unit heat supply; βt represents the carbon dioxide sequestration per unit area of ​​forest; 3) The minimum target for pollutant emissions is: In the formula, Q j,t Indicates the amount of electricity generated; E i,t represents the energy consumption of each industry; p represents the type of pollutant; PE i,t,p Indicates the pollution emission coefficient of each industry's production volume; PQ j,t,p Indicates the emission coefficient per unit of power generation; CH k,t,p Indicates the sewage discharge coefficient per unit heat supply.

9. A pollution reduction and carbon reduction control device for the energy and power industry, characterized in that: The device comprises: a processor and a memory, wherein program instructions are stored in the memory, and the processor calls the program instructions stored in the memory to enable the device to execute the method according to any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor is enabled to perform the method according to any one of claims 1 to 5.

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