Carbon-containing capture integrated energy system thermoelectric optimization method considering stepped carbon transaction mechanism and related device

Abstract

The invention provides a carbon-containing capture integrated energy system thermoelectric optimization method considering a stepped carbon transaction mechanism and a related device. The method comprises the steps of refining a power-to-gas process, and constructing a carbon capture power plant-power-to-gas-gas unit collaborative scheduling framework; wherein an electrolytic bath, a methane reactor and a hydrogen fuel cell are introduced to replace traditional P2G, and CO2 captured by carbon is used as a raw material to be supplied to a gas unit in the process of generating natural gas; considering that the IES participates in a carbon trading market, introducing a stepped carbon trading mechanism to guide the IES to control carbon emission; and based on the obtained parameters, solving a pre-constructed double-layer optimization model according to a set target, and obtaining a thermoelectric optimal operation scheme of the carbon-containing capture integrated energy system. According to the method, a stepped carbon transaction mechanism is considered, and the optimal operation scheme of the IES is obtained by utilizing a double-layer optimization model, so that wind power / photovoltaic power is indirectly schedulable and is flexibly utilized, and the low-carbon property and economical efficiency of the IES are further improved.

Description

Technical Field

[0001] This invention belongs to the field of power system technology, specifically relating to a thermal power optimization method and related apparatus for a carbon capture integrated energy system considering a tiered carbon trading mechanism. Background Technology

[0002] With the continuous development of my country's energy network and the optimization of its energy structure, the social energy supply system must be integrated to some extent to achieve coordinated economic development. However, the relative independence between existing energy systems has resulted in a lack of energy interaction and coordination between different energy types. To address this, American scholar Rifkin J proposed the concept of the Energy Internet. Against this backdrop, the integrated energy system, as the core carrier of the Energy Internet, has received widespread attention. It combines the production, transmission, distribution, conversion, storage, and use of multiple energy subsystems into a unified whole, achieving horizontal "multi-energy coupling" and vertical "source-grid-load-storage" coordination.

[0003] Based on sustainable development, distributed generation has become a new way to integrate renewable energy. However, due to spatial and temporal mismatches between renewable energy and load demand, some regions experience significant wind and solar power curtailment, resulting in severe waste of renewable energy and substantial economic losses. In this context, incorporating a power-to-gas (P2G) process can effectively alleviate these problems. As a key supporting technology for Integrated Renewable Energy Systems (IES), P2G technology functions as follows: when the system load is low or renewable energy generation is at its peak, excess electricity is converted into natural gas or hydrogen and stored in natural gas or hydrogen storage devices; conversely, when the system energy supply is insufficient, the stored natural gas and hydrogen can be converted into electricity or heat to supply users. Therefore, the system's ability to absorb renewable energy during off-peak periods can be improved.

[0004] For CO2 feedstock supply, carbon capture power plants (CCPPs) offer an excellent new approach. These plants, converted from coal-fired power plants using carbon capture technology, significantly reduce carbon emissions. By controlling carbon capture energy consumption, they can serve as time-shifted and adjustable load power, giving them operational flexibility and rapid output adjustment capabilities. Compared to traditional coal-fired power plants, they offer stronger regulation capabilities. While reducing carbon emissions, they can flexibly coordinate with the optimization of various units within an energy ecosystem and adapt to changes in renewable energy output. CCPPs can capture and separate CO2 from flue gas, then transport it to safe locations such as the ocean for long-term storage, thus achieving long-term isolation of CO2 from the atmosphere and significantly reducing the plant's carbon emission intensity.

[0005] However, research on the impact of carbon capture power plants' carbon markets and carbon trading on tiered carbon emission policies, as well as the operational effectiveness of market mechanisms, is often overlooked. Therefore, further exploration of carbon trading mechanisms and carbon emission calculation models is of great significance for reducing wind and solar curtailment rates and improving grid peak-shaving flexibility in the power system. Meanwhile, waste-to-energy plants have developed rapidly in recent years under the guidance of national policies. They possess the characteristics of waste reduction, harmlessness, and resource recovery in power generation, and have enormous potential. However, the flue gas produced by incineration needs to be purified before emission. The energy consumption of the flue gas treatment system accounts for approximately one-quarter of the total power generation. Adding a gas storage device can decouple the power generation and flue gas treatment processes, allowing the flue gas treatment load to be shifted during specific time periods and participate in coordinated dispatch as an active and controllable load, possessing similar dispatch flexibility in terms of time and quantity as controllable loads. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a thermal power optimization method and related apparatus for a carbon capture integrated energy system that considers a tiered carbon trading mechanism. The aim is to rationally schedule the various devices included in the system, provide an economical and reliable operation optimization scheme, fully utilize surplus electricity, reduce the waste of renewable energy, enable the system to improve energy utilization efficiency, optimize equipment operation flexibility, and further reduce carbon emission levels.

[0007] To achieve the above objectives, the technical solution provided by the present invention is as follows:

[0008] In a first aspect, the present invention provides a method and related apparatus for optimizing the thermal power of a carbon capture integrated energy system considering a tiered carbon trading mechanism, applicable to low-carbon operation scenarios of integrated energy systems, characterized by comprising the following steps:

[0009] Construct an IES system coupled operation model, which includes refining the two-stage operation process of P2G, introducing electrolyzers, methane reactors, and hydrogen fuel cells to replace traditional P2G, and using carbon capture CO2 as a raw material to supply gas during the natural gas generation process, and constructing a coordinated scheduling framework for carbon capture power plants, electricity to gas conversion and gas turbine units.

[0010] Considering the participation of IES in the carbon trading market, a tiered carbon trading mechanism should be introduced to guide IES in controlling carbon emissions;

[0011] Based on this, a two-layer optimization model is constructed with the upper layer being the minimum total operating cost of the IES and the lower layer being the minimum load fluctuation. The lower layer model is then transformed into constraints for the upper layer model using KKT conditions, resulting in the optimal thermal power operation scheme for the carbon capture integrated energy system.

[0012] Furthermore, the process of constructing the coupled operation model of the IES system includes constructing models of each aggregation unit:

[0013] The total energy consumption and carbon capture output of the carbon capture system are expressed as follows:

[0014]

[0015]

[0016]

[0017]

[0018] In the formula: P t C-P P represents the total energy consumption of the CCPP-P2G system during time period t; t EL_IN The energy consumption of P2G equipment during time period t (this power is provided by wind and solar curtailment to achieve the absorption of wind and solar curtailment); P t WA P t VA These represent the power curtailed from wind and solar power during time period t; P t CC P t OP P t GN P t G P t GC P t Gα These represent the carbon capture energy consumption during time period t, carbon capture operation energy consumption, net output of the carbon capture power plant, equivalent output of the carbon capture power plant, carbon capture energy consumption provided by the carbon capture power plant, and flue gas treatment energy consumption; P A Energy consumption of the CCPP-P2G system (considered a constant due to its small proportion), in MW;

[0019] The energy consumption model for the flue gas treatment system of a waste incineration power plant is as follows:

[0020]

[0021] In the formula: w α P is the unit energy consumption coefficient of the flue gas treatment system. t α Let α1 be the energy consumption for flue gas treatment at time t; t α3 represents the portion of the flue gas treated at time t provided by the flue gas generated during the operation of the waste-to-energy power plant; t The amount of flue gas supplied by the gas storage device when flue gas treatment is performed at time t;

[0022] The model expressions for gas-fired (CHP) units and gas-fired boilers (GB) are as follows:

[0023]

[0024]

[0025] In the formula: P t PH P t CHP H t CHP These represent the total output power, electrical and thermal power of the CHP unit during time period t; V t CHP V t GB η represents the amount of natural gas consumed by the CHP unit and the gas-fired boiler during time period t; CHP e η CHP h These are the electrical and thermal efficiencies of the CHP unit and the efficiency of the gas-fired boiler, respectively; H t GB The output thermal power of the gas-fired boiler during time period t;

[0026] The expressions for the power of electric and thermal energy storage, taking into account the power losses of the electric and thermal energy storage devices themselves, are as follows:

[0027]

[0028]

[0029] In the formula: S t ES S t TS The electrical and thermal energy storage at the end of time period t, respectively, in MW and P. t ESC P t ESD H represents the charging and discharging power of the energy storage device during time period t; t TSC H t TSD η represents the charging and discharging power of the thermal storage device during time period t; ESC η ESD η TSC η TSD These represent the charging and discharging efficiencies of electrical and thermal energy storage, respectively.

[0030] Furthermore, the two-stage operation process of P2G is refined. Specifically, the EL first converts electrical energy into hydrogen energy. Part of the hydrogen energy is input into MR and synthesized with CO2 to form natural gas, which is supplied to the gas load, GB, and CHP units. Part of the hydrogen energy is directly transported to HFC to be converted into electricity and heat energy, and another part is stored in hydrogen storage tanks. The above energy conversion model can be described as follows:

[0031] EL equipment:

[0032]

[0033] In the formula, P t H2 η is the hydrogen energy output by EL during time period t; EL The energy conversion efficiency of EL; P EL_IN,max P EL_IN,min These are the upper and lower limits of the electrical energy input to EL, respectively; △P EL_IN,max , △P EL_IN,min These represent the upper and lower limits of EL's ramp rate, respectively.

[0034] MR equipment:

[0035]

[0036] In the formula, Q t CC w represents the amount of CO2 captured by the CCPP-P2G system during time period t; C Q represents the operating energy consumption per unit of CO2 processed by a carbon capture power plant, expressed in MW·h / t. t P2G,sum α represents the total CO2 consumed by the P2G device during time period t; CO2 The amount of CO2 required to produce a unit power of natural gas, t / (MW·h); η P2G V represents the electro-gas conversion efficiency of the P2G equipment. t P2G H represents the volume of natural gas generated by P2G during time period t; g The calorific value of natural gas is taken as 39 MJ / m³; P P2G,max This represents the upper limit of energy consumption for the MR process.

[0037] HFC equipment:

[0038]

[0039] In the formula, P t H2,HFC P represents the hydrogen energy input into the HFC during time period t; t HFC H t HFC These represent the electrical and thermal energy output of the HFC during time period t; η HFCe η HFC h These represent the efficiencies of HFC in converting energy into electricity and heat, respectively; P H2,HFC,max P H2,HFC,min These represent the upper and lower limits of hydrogen energy input to HFCs; ΔP H2,HFC,max , △P H2,HFC,min These represent the upper and lower limits of HFC ramp rate, respectively.

[0040] Furthermore, a joint operation strategy for carbon capture, waste incineration, wind power, and photovoltaic power is constructed. The specific model is as follows:

[0041] A portion of the power generated by wind and solar power is used as energy consumption for carbon capture systems, another portion is used as energy consumption for flue gas treatment systems, and the remaining power is fed into the power grid. Similarly, a portion of the power generated by carbon capture power plants and waste incineration power generation is used as energy consumption for carbon capture systems, another portion is used as energy consumption for flue gas treatment systems, and the remaining power is fed into the power grid. The specific expressions are as follows:

[0042]

[0043]

[0044]

[0045]

[0046]

[0047]

[0048]

[0049] In the formula: P t WC P t VC P t WIC The carbon capture energy consumption provided by wind power, photovoltaic units, and waste incineration power plants during time period t are respectively; P t Vα P t Wα P t Gα P t WIα The energy consumption for flue gas treatment provided by photovoltaic, wind power, carbon capture power plants, and waste incineration power plants during time period t are respectively; P t WN P t VN Pt WIN These represent the grid-connected power generation capacity of wind power, photovoltaic power, and waste incineration power plants during time period t; P t W P t V P t WI These represent the predicted output of wind power, photovoltaic power, and waste incineration power generation during time period t; Q t N e represents the net CO2 emissions of the carbon capture power plant during time period t, in t / h. g The amount of CO2 produced per unit of equivalent power output of an internal carbon capture power plant, expressed in t / (MW·h).

[0050] Furthermore, the expression for the tiered carbon trading cost is as follows:

[0051]

[0052] In the formula, E IES，t For IES carbon emissions trading, C CO2 λ represents the tiered carbon trading cost; λ represents the base price for carbon trading; l represents the length of the carbon emission bright range; and α represents the price growth rate.

[0053] Furthermore, the actual carbon emission model expression is as follows:

[0054]

[0055]

[0056] In the formula, E IES，a E e,total，a E g,total，a These represent the total carbon emissions from IES (Environmental Engineering Systems), coal-fired power plants, and gas-fired power plants, respectively; Q t e.total e represents the equivalent output energy consumption of a coal-fired power plant during time period t. α For the unit output flue gas emission intensity of waste incineration power plants, t / (MW·h), P t g.total Let t represent the equivalent output power of the gas-fired power plant during time period t; a1, b1, c1 and a2, b2, c2 are the carbon emission parameters of the coal-fired unit and the gas-fired unit, respectively.

[0057] Furthermore, in the calculation of tiered carbon trading costs, the carbon emission allowances for carbon capture power plants, waste incineration power plants, GB, and CHP are calculated as follows:

[0058]

[0059] In the formula, E IES EG E WI E CHP E GB These are carbon emission allowances for IES, carbon capture power plants, waste incineration power plants, CHP, and GB, respectively; x e x g These represent the carbon emission allowances per unit of electricity consumption for coal-fired power units and per unit of natural gas consumption for natural gas-fired power units, respectively; T represents the dispatch cycle.

[0060] Furthermore, a two-layer optimization model is constructed, with the upper layer aiming to minimize the total operating cost of the IES and the lower layer aiming to minimize the load fluctuation. The objective function and constraints corresponding to this objective are as follows:

[0061] Upper-level objective function:

[0062]

[0063]

[0064]

[0065]

[0066]

[0067]

[0068]

[0069]

[0070]

[0071]

[0072] In the formula: the objective function contains 9 parts, which are the fuel cost C of the carbon capture power plant. t F Tiered carbon trading costs C t CO2 CHP unit and gas boiler cost C t H P2G cost C t P2G Carbon sequestration cost C t CS System operation and maintenance costs C t W And the cost of purchasing electricity in the energy market C t M T is the total scheduling duration; a f b fc f d f e f P is the fuel cost coefficient. G，min This represents the lower limit of output for carbon capture power plants; k CH4 The fixed price per unit of natural gas in the natural gas market is $ / m3; V t BUY For natural gas purchase volume, m3; k CO2 The fixed price for purchasing CO2 is $ / t; kP2G is the P2G operating cost coefficient, $ / (MW·h); k CS A fixed price per unit of CO2 for storage, $ / t; k t EM The grid purchase price for electricity during time period t is $ / (MW·h); P t EM Let t be the electricity purchased from the power grid during time period t, in MW·h;

[0073] Upper-level constraints:

[0074]

[0075]

[0076]

[0077]

[0078]

[0079]

[0080]

[0081]

[0082]

[0083]

[0084]

[0085]

[0086]

[0087]

[0088]

[0089]

[0090]

[0091]

[0092]

[0093]

[0094]

[0095]

[0096] In the formula: P t EL H t HL The electrical and thermal loads for time period t are in MW and P, respectively. G,max P is the upper limit of equivalent output. t C，max λ represents the upper limit of energy consumption for the carbon capture system during time period t; t CC ΔP represents the flue gas split ratio of the carbon capture system during time period t; G Constraints on the ramp-up rate of carbon capture power plant output; △P C Constraints on the rate of increase of carbon capture energy consumption in carbon capture power plants. CHP,max P CHP,min H CHP,max H CHP,min The upper and lower limits of electrical output and thermal output of the CHP unit are respectively defined; △P PH For the output ramp-up rate constraint of the CHP unit; H GB,max H GB,min These represent the upper and lower limits of the output of the gas-fired boiler; △H GB Constraints on the ramp-up rate of gas-fired boiler output. WI The total daily output of a waste-to-energy power plant is constant because its fuel, supplied by the government in fixed quantities of municipal solid waste based on the installed capacity; W WI,max This represents the maximum daily output of a waste-to-energy power plant; P WI,max P WI,min These represent the maximum and minimum output values ​​at each moment, respectively; ΔP WI For the climbing rate constraint; λ t WI V is the flue gas split ratio, which is the ratio of the amount of flue gas flowing into the reactor of a waste-to-energy power plant to the total amount of flue gas generated on the power generation side; t WIα V represents the gas storage capacity of the flue gas storage tank at time t. t WIα，max The maximum capacity of the gas storage device; αt 2 V represents the amount of flue gas flowing into the gas storage device at time t; L WIα,max P represents the maximum flow rate in the inlet and outlet pipes of the gas storage device. t ES,H2 The power input to the hydrogen storage during time period t;

[0097] Lower-level objective function:

[0098]

[0099]

[0100]

[0101] In the formula: F1 is the equivalent load variance; P t E Let P be the equivalent electrical load at time t; t E.mv Let be the mean of the equivalent electrical load at time t;

[0102] Lower-level constraints:

[0103]

[0104]

[0105]

[0106]

[0107]

[0108]

[0109] In the formula: P ESC,max P ESD,max These represent the maximum charging and discharging power, respectively; Boolean variable μ t ESC μ t ESD These represent whether electrical energy storage is charging / discharging and whether thermal energy storage is storing / releasing heat during time period t, respectively; set to 1 if yes, and 0 otherwise; S ES,max S ES,min These represent the maximum and minimum energy storage capacities, respectively; S0 ES S 24 ES These represent the beginning and end values ​​of the energy storage battery at the start and end of the day, respectively.

[0110] Secondly, this invention provides a carbon capture integrated energy system thermoelectric optimization device considering a tiered carbon trading mechanism, applicable to low-carbon operation scenarios of integrated energy systems, including:

[0111] The model building module is used to obtain a detailed model of the integrated energy system with carbon capture, including refining the two-stage operation process of P2G, introducing electrolyzers, methane reactors, and hydrogen fuel cells to replace the traditional P2G, and using CO2 captured by carbon capture as a raw material to supply gas during the natural gas generation process, and constructing a coordinated scheduling framework for carbon capture power plants, electricity to gas conversion and gas turbine units.

[0112] The parameter acquisition module is used to acquire carbon trading market information and introduce a tiered carbon trading mechanism to guide IES control of carbon emissions.

[0113] The solution module is used to construct a two-layer optimization model with the upper layer being the minimum total operating cost of the IES and the lower layer being the minimum load fluctuation. The lower layer model is transformed into constraints of the upper layer model through KKT conditions to obtain the optimal operating scheme of the carbon capture integrated energy system for thermal power.

[0114] Thirdly, the present invention provides a computer device, the device including a processor and a memory:

[0115] The memory is used to store computer programs and send the instructions of the computer programs to the processor;

[0116] The processor executes, according to the instructions of the computer program, a thermal power optimization method for a carbon capture integrated energy system considering a tiered carbon trading mechanism, as described in the first aspect.

[0117] In summary, this invention provides a method and related apparatus for optimizing the cogeneration (CHP) of an integrated energy system with carbon capture, considering a tiered carbon trading mechanism. Applied to low-carbon operation scenarios of integrated energy systems, it includes refining the P2G process and constructing a collaborative scheduling framework for carbon capture power plants, power-to-gas (HPG) generators, and gas turbine units. Specifically, it introduces electrolyzers, methane reactors, and hydrogen fuel cells to replace traditional P2G, and uses CO2 captured from carbon capture as feedstock to supply the gas turbine units during natural gas generation. Considering the participation of integrated energy systems (IES) in the carbon trading market, a tiered carbon trading mechanism is introduced to guide IES in controlling carbon emissions. Based on the obtained parameters, a pre-constructed two-layer optimization model is solved according to set objectives to obtain the optimal CHP operation scheme for the integrated energy system with carbon capture. This invention considers a tiered carbon trading mechanism and uses a two-layer optimization model to derive the optimal operation scheme for IES, enabling wind / solar power to be indirectly dispatchable and flexibly utilized, further improving the low-carbon nature and economy of IES. Attached Figure Description

[0118] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0119] Figure 1 A flowchart of a thermal power optimization method for a carbon capture integrated energy system considering a tiered carbon trading mechanism is provided for an embodiment of the present invention.

[0120] Figure 2 A technical roadmap for a thermal power optimization method for a carbon capture integrated energy system considering a tiered carbon trading mechanism, provided in an embodiment of the present invention;

[0121] Figure 3 A block diagram of the integrated energy system provided in the embodiments of the present invention;

[0122] Figure 4 A block diagram of a thermal power optimization device for a carbon capture integrated energy system considering a tiered carbon trading mechanism is provided for an embodiment of the present invention.

[0123] Figure 5 This is a block diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0124] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0125] Please see Figure 1 This invention provides a method and related apparatus for optimizing the thermal power of a carbon capture integrated energy system considering a tiered carbon trading mechanism, applicable to low-carbon operation scenarios of integrated energy systems. The method comprises the following steps:

[0126] S11: Construct an IES system coupled operation model, which includes refining the two-stage operation process of P2G, introducing electrolyzers, methane reactors, and hydrogen fuel cells to replace traditional P2G, and using carbon capture CO2 as a raw material to supply gas during the natural gas generation process, and constructing a coordinated scheduling framework for carbon capture power plants, electricity-to-gas conversion, and gas turbine units.

[0127] It should be noted that you should refer to [link / reference]. Figure 2 The IES system constructed in this invention includes flexibly adjustable power generation units (thermal power units and waste incineration power plants), non-adjustable power generation units (wind power and photovoltaic), P2G devices, a carbon capture system, gas storage devices for waste incineration power plants, electrical energy storage, thermal energy storage, and hydrogen energy storage. The gas turbine units consist of combined heat and power (CHP) units and gas-fired boilers, with heat load provided by both in coordination. Except for the CHP units, each generator unit can provide energy to the carbon capture system and flue gas treatment system. By adding gas storage devices, the relationship between flue gas treatment and power generation is decoupled. Utilizing the spatiotemporal complementarity of different energy resources in terms of energy / power, scheduling optimization is more flexible in coordinating with changes in renewable energy output and smoothing net load fluctuations. The coordinated operation scheduling instructions for each unit are formulated based on the energy market electricity price, renewable energy output, and electrical and thermal load predicted after the energy management system collects data.

[0128] S12: Consider IES participation in the carbon trading market and introduce a tiered carbon trading mechanism to guide IES to control carbon emissions.

[0129] It's important to note that the carbon trading mechanism aims to control carbon emissions by establishing legal carbon emission rights and allowing producers to trade these rights in the market. Regulatory authorities first allocate carbon emission allowances to each emission source. Producers then use these allowances to manage their production and emissions appropriately. If actual carbon emissions are lower than the allocated allowance, the remaining allowances can be traded on the carbon trading market; otherwise, they must purchase additional allowances. The tiered carbon trading mechanism model primarily includes a carbon emission allowance model, an actual carbon emission model, and a tiered carbon emission trading model.

[0130] S13: Within each output range, construct a two-layer optimization model with the upper layer minimizing the total operating cost of the IES and the lower layer minimizing the load fluctuation. Then, use KKT conditions to transform the lower-layer model into the constraints of the upper-layer model to obtain the optimal thermal power operation scheme of the carbon capture integrated energy system.

[0131] It should be noted that the KKT conditions are a theoretical tool for solving nonlinear programming problems with equality and inequality constraints. They solve problems by integrating multiple conditions in a coordinated manner. Under complex constraints, it can find the necessary conditions to satisfy optimality, ensuring that the solution reaches the extremum of the objective function within the constraints.

[0132] First, the primal feasibility conditions, based on the problem's constraint functions, ensure that candidate solutions satisfy all equality and inequality constraints, which is a fundamental prerequisite for the existence of solutions. Equality constraints require that the solution strictly lie on the constraint surface, while inequality constraints confine the solution to a specific region. The dual feasibility conditions impose non-negativity requirements on the Lagrange multipliers corresponding to inequality constraints; this characteristic is key to handling inequality constraints.

[0133] The gradient condition, through the Lagrangian function, linearly combines the gradient of the objective function with the gradient of the constraint function, ensuring that the gradient effects in each direction at the optimal solution are balanced, thus preventing further optimization of the objective function within the feasible region. The complementary relaxation condition establishes a close connection between inequality constraints and Lagrangian multipliers, clarifying that only constraints active on the constraint boundaries (multipliers non-zero) affect the optimal solution, while inactive constraints (multipliers zero) have no effect.

[0134] For general nonlinear programming problems, the KKT conditions are necessary conditions for the existence of local optima, while in convex optimization problems, these conditions are necessary and sufficient conditions for the global optimum. The application of KKT conditions enables rigorous theoretical solutions to optimization problems with complex constraints, providing an important analytical and solution framework for optimization problems in practical engineering, machine learning, economic planning, and other fields.

[0135] The method provided in this embodiment transforms the thermoelectric optimization problem of a carbon capture integrated energy system into a two-level optimization problem. First, a coupled operation model of the IES system is constructed. This step refines the two-stage operation process of P2G, replacing traditional P2G equipment with electrolyzers, methane reactors, and hydrogen fuel cells. During natural gas generation, CO2 from carbon capture is used as fuel gas, constructing a new framework for the coordinated scheduling of carbon capture power plants, power-to-gas (P2G) units, and gas turbine units, achieving deep optimization of the energy conversion process and efficient utilization of carbon resources. Second, the IES is incorporated into the carbon trading market system, introducing a tiered carbon trading mechanism. This mechanism, through economic incentives and constraints, guides the IES to actively control carbon emissions during operation, balancing economic and environmental benefits, and promoting the system's transition to low-carbon development. Based on the above design, a two-level optimization model is constructed: the upper level aims to minimize the total operating cost of the IES, while the lower level focuses on minimizing load fluctuations. Using KKT conditions, the lower-level model is transformed into constraints for the upper-level model, thus converting the two-level optimization problem into a single optimization problem to be solved. This process fully utilizes the theoretical support of KKT conditions for constrained optimization problems, ensuring that the optimality conditions of the lower-level model are coordinated with the upper-level objectives, and ultimately obtains the optimal thermal and power operation scheme of the carbon capture integrated energy system, achieving the dual objectives of economical system operation and load stability.

[0136] Please see Figure 3 , Figure 3 This paper presents a technical approach for optimizing the thermal power of a carbon capture integrated energy system, considering a tiered carbon trading mechanism, based on the above embodiments. The approach includes:

[0137] (1) Consider IES' participation in the carbon trading market and introduce a tiered carbon trading mechanism to guide IES to control carbon emissions;

[0138] (2) Construct the energy consumption model of the CCCP-P2G-gas turbine subsystem, the flue gas treatment model of the waste incineration power plant, the CHP unit and gas boiler model and the energy storage device model;

[0139] (3) Refine the two-stage operation process of power-to-gas (P2G), introduce electrolyzers, methane reactors and hydrogen fuel cells to replace traditional P2G, and use carbon capture CO2 as raw material to supply gas turbine units during the natural gas generation process.

[0140] (4) Establish a joint operation strategy for carbon capture-waste incineration-wind power-photovoltaic power;

[0141] (5) Construct a two-layer optimization model with the upper layer being the minimum total operating cost of IES and the lower layer being the minimum load fluctuation.

[0142] (6) By converting the lower-level model into the upper-level model's constraints through KKT conditions, the optimal thermal power operation scheme of the carbon capture integrated energy system is obtained.

[0143] The above technical approach will be further described below with reference to some other embodiments of the present invention.

[0144] In one embodiment of the present invention, the constructed IES system coupled operation model includes constructing models of each aggregation unit:

[0145] The total energy consumption and carbon capture output of the carbon capture system are expressed as follows:

[0146]

[0147]

[0148]

[0149]

[0150] In the formula: P t C-P P represents the total energy consumption of the CCPP-P2G system during time period t; t EL_IN The energy consumption of P2G equipment during time period t (this power is provided by wind and solar curtailment to achieve the absorption of wind and solar curtailment); P tWA P t VA These represent the power curtailed from wind and solar power during time period t; P t CC P t OP P t GN P t G P t GC P t Gα These represent the carbon capture energy consumption during time period t, carbon capture operation energy consumption, net output of the carbon capture power plant, equivalent output of the carbon capture power plant, carbon capture energy consumption provided by the carbon capture power plant, and flue gas treatment energy consumption; P A Energy consumption of the CCPP-P2G system (considered a constant due to its small proportion), in MW;

[0151] The energy consumption model for the flue gas treatment system of a waste incineration power plant is as follows:

[0152]

[0153] In the formula: w α P is the unit energy consumption coefficient of the flue gas treatment system. t α Let α1 be the energy consumption for flue gas treatment at time t; t α3 represents the portion of the flue gas treated at time t provided by the flue gas generated during the operation of the waste-to-energy power plant; t The amount of flue gas supplied by the gas storage device when flue gas treatment is performed at time t;

[0154] The model expressions for gas-fired (CHP) units and gas-fired boilers (GB) are as follows:

[0155]

[0156]

[0157] In the formula: P t PH P t CHP H t CHP These represent the total output power, electrical and thermal power of the CHP unit during time period t; V t CHP V t GB η represents the amount of natural gas consumed by the CHP unit and the gas-fired boiler during time period t; CHP e η CHP hThese are the electrical and thermal efficiencies of the CHP unit and the efficiency of the gas-fired boiler, respectively; H t GB The output thermal power of the gas-fired boiler during time period t;

[0158] The expressions for the power of electric and thermal energy storage, taking into account the power losses of the electric and thermal energy storage devices themselves, are as follows:

[0159]

[0160]

[0161] In the formula: S t ES S t TS The electrical and thermal energy storage at the end of time period t, respectively, in MW and P. t ESC P t ESD H represents the charging and discharging power of the energy storage device during time period t; t TSC H t TSD η represents the charging and discharging power of the thermal storage device during time period t; ESC η ESD η TSC η TSD These represent the charging and discharging efficiencies of electrical and thermal energy storage, respectively.

[0162] In a further embodiment of the present invention, the two-stage operation process of P2G is refined. Specifically, the EL first converts electrical energy into hydrogen energy. Part of the hydrogen energy is input into MR and synthesized with CO2 to form natural gas, which is supplied to the gas load, GB, and CHP units. Part of the hydrogen energy is directly transported to HFC and converted into electrical and thermal energy. Another part is stored in a hydrogen storage tank. The above energy conversion model can be described as follows:

[0163] EL devices:

[0164]

[0165] In the formula, P t H2 η is the hydrogen energy output by EL during time period t; EL The energy conversion efficiency of EL; P EL_IN,max P EL_IN,min These are the upper and lower limits of the electrical energy input to EL, respectively; △P EL_IN,max , △P EL_IN,min These represent the upper and lower limits of EL's ramp rate, respectively.

[0166] MR equipment:

[0167]

[0168] In the formula, Q t CC w represents the amount of CO2 captured by the CCPP-P2G system during time period t; C Q represents the operating energy consumption per unit of CO2 processed by a carbon capture power plant, expressed in MW·h / t. t P2G,sum α represents the total CO2 consumed by the P2G device during time period t; CO2 The amount of CO2 required to produce a unit power of natural gas, t / (MW·h); η P2G V represents the electro-gas conversion efficiency of the P2G equipment. t P2G H represents the volume of natural gas generated by P2G during time period t; g The calorific value of natural gas is taken as 39 MJ / m³; P P2G,max This represents the upper limit of energy consumption for the MR process.

[0169] HFC equipment:

[0170]

[0171] In the formula, P t H2,HFC P represents the hydrogen energy input into the HFC during time period t; t HFC H t HFC These represent the electrical and thermal energy output of the HFC during time period t; η HFC e η HFC h These represent the efficiencies of HFC in converting energy into electricity and heat, respectively; P H2,HFC,max P H2,HFC,min These represent the upper and lower limits of hydrogen energy input to HFCs; ΔP H2,HFC,max , △P H2,HFC,min These represent the upper and lower limits of HFC ramp rate, respectively.

[0172] In a further embodiment of the present invention, a joint operation strategy of carbon capture-waste incineration-wind power-photovoltaic is constructed, and the specific model is as follows:

[0173] A portion of the power generated by wind and solar power is used as energy consumption for carbon capture systems, another portion is used as energy consumption for flue gas treatment systems, and the remaining power is fed into the power grid. Similarly, a portion of the power generated by carbon capture power plants and waste incineration power generation is used as energy consumption for carbon capture systems, another portion is used as energy consumption for flue gas treatment systems, and the remaining power is fed into the power grid. The specific expressions are as follows:

[0174]

[0175]

[0176]

[0177]

[0178]

[0179]

[0180]

[0181] In the formula: P t WC P t VC P t WIC The carbon capture energy consumption provided by wind power, photovoltaic units, and waste incineration power plants during time period t are respectively; P t Vα P t Wα P t Gα P t WIα The energy consumption for flue gas treatment provided by photovoltaic, wind power, carbon capture power plants, and waste incineration power plants during time period t are respectively; P t WN P t VN P t WIN These represent the grid-connected power generation capacity of wind power, photovoltaic power, and waste incineration power plants during time period t; P t W P t V P t WI These represent the predicted output of wind power, photovoltaic power, and waste incineration power generation during time period t; Q t N e represents the net CO2 emissions of the carbon capture power plant during time period t, in t / h. g The amount of CO2 produced per unit of equivalent power output of an internal carbon capture power plant, expressed in t / (MW·h).

[0182] In a further embodiment of the present invention, the expression for the tiered carbon trading cost is as follows:

[0183]

[0184] In the formula, E IES，t For IES carbon emissions trading volume, C CO2λ represents the tiered carbon trading cost; l represents the base price for carbon trading; l represents the length of the carbon emission bright range; and α represents the price growth rate.

[0185] In a further embodiment of the present invention, the actual carbon emission model expression is as follows:

[0186]

[0187]

[0188] In the formula, E IES，a E e,total，a E g,total，a These represent the total carbon emissions from IES (Environmental Engineering Systems), coal-fired power plants, and gas-fired power plants, respectively; Q t e.total e represents the equivalent output energy consumption of a coal-fired power plant during time period t. α For the unit output flue gas emission intensity of waste incineration power plants, t / (MW·h), P t g.total Let t represent the equivalent output power of the gas-fired power plant during time period t; a1, b1, c1 and a2, b2, c2 are the carbon emission parameters of the coal-fired unit and the gas-fired unit, respectively.

[0189] In a further embodiment of the present invention, the carbon emission allowances for carbon capture power plants, waste incineration power plants, GB, and CHP are calculated as follows during the tiered carbon trading cost calculation process:

[0190]

[0191] In the formula, E IES E G E WI E CHP E GB These are carbon emission allowances for IES, carbon capture power plants, waste incineration power plants, CHP, and GB, respectively; x e x g These represent the carbon emission allowances per unit of electricity consumption for coal-fired power units and per unit of natural gas consumption for natural gas-fired power units, respectively; T represents the dispatch cycle.

[0192] In a further embodiment of the present invention, a two-layer optimization model is constructed with the upper layer aiming to minimize the total operating cost of the IES and the lower layer aiming to minimize the load fluctuation. The objective function and constraints corresponding to this objective are as follows:

[0193] Upper-level objective function:

[0194]

[0195]

[0196]

[0197]

[0198]

[0199]

[0200]

[0201]

[0202]

[0203]

[0204] In the formula: the objective function contains 9 parts, which are the fuel cost C of the carbon capture power plant. t F Tiered carbon trading costs C t CO2 CHP unit and gas boiler cost C t H P2G cost C t P2G Carbon sequestration cost C t CS System operation and maintenance costs C t W And the cost of purchasing electricity in the energy market C t M T is the total scheduling duration; a f b f c f d f e f P is the fuel cost coefficient. G，min This represents the lower limit of output for carbon capture power plants; k CH4 The fixed price per unit of natural gas in the natural gas market is $ / m3; V t BUY For natural gas purchase volume, m3; k CO2 The fixed price for purchasing CO2 is $ / t; kP2G is the P2G operating cost coefficient, $ / (MW·h); k CS A fixed price per unit of CO2 for storage, $ / t; k t EM The grid purchase price for electricity during time period t is $ / (MW·h); P t EM Let t be the electricity purchased from the power grid during time period t, in MW·h;

[0205] Upper-level constraints:

[0206]

[0207]

[0208]

[0209]

[0210]

[0211]

[0212]

[0213]

[0214]

[0215]

[0216]

[0217]

[0218]

[0219]

[0220]

[0221]

[0222]

[0223]

[0224]

[0225]

[0226]

[0227]

[0228] In the formula: P t EL H t HL The electrical and thermal loads for time period t are in MW and P, respectively. G,max P is the upper limit of equivalent output. t C，maxλ represents the upper limit of energy consumption for the carbon capture system during time period t; t CC ΔP represents the flue gas split ratio of the carbon capture system during time period t; G Constraints on the ramp-up rate of carbon capture power plant output; △P C Constraints on the rate of increase of carbon capture energy consumption in carbon capture power plants. CHP,max P CHP,min H CHP,max H CHP,min The upper and lower limits of electrical output and thermal output of the CHP unit are respectively defined; △P PH For the output ramp-up rate constraint of the CHP unit; H GB,max H GB,min These represent the upper and lower limits of the output of the gas-fired boiler; △H GB Constraints on the ramp-up rate of gas-fired boiler output. WI The total daily output of a waste-to-energy power plant is constant because its fuel, supplied by the government in fixed quantities of municipal solid waste based on the installed capacity; W WI,max This represents the maximum daily output of a waste-to-energy power plant; P WI,max P WI,min These represent the maximum and minimum output values ​​at each moment, respectively; ΔP WI For the climbing rate constraint; λ t WI V is the flue gas split ratio, which is the ratio of the amount of flue gas flowing into the reactor of a waste-to-energy power plant to the total amount of flue gas generated on the power generation side; t WIα V represents the gas storage capacity of the flue gas storage tank at time t. t WIα，max The maximum capacity of the gas storage device; α t 2 V represents the amount of flue gas flowing into the gas storage device at time t; L WIα,max P represents the maximum flow rate in the inlet and outlet pipes of the gas storage device. t ES,H2 The power input to the hydrogen storage during time period t;

[0229] Lower-level objective function:

[0230]

[0231]

[0232]

[0233] In the formula: F1 is the equivalent load variance; P t E Let P be the equivalent electrical load at time t; t E.mvLet be the mean of the equivalent electrical load at time t;

[0234] Lower-level constraints:

[0235]

[0236]

[0237]

[0238]

[0239]

[0240]

[0241] In the formula: P ESC,max P ESD,max These represent the maximum charging and discharging power, respectively; Boolean variable μ t ESC μ t ESD These represent whether electrical energy storage is charging / discharging and whether thermal energy storage is storing / releasing heat during time period t, respectively; set to 1 if yes, and 0 otherwise; S ES,max S ES,min These represent the maximum and minimum energy storage capacities, respectively; S0 ES S 24 ES These represent the beginning and end values ​​of the energy storage battery at the start and end of the day, respectively.

[0242] In a further embodiment of the present invention, the KKT complementary relaxation condition is used to transform the lower-level model into constraints for the upper-level model. Then, the Big-M method is used to linearize the nonlinear quantities in the two-level model, forming a common single-level mixed-integer linear programming model. The specific transformation method of the lower-level model is as follows:

[0243] First, construct the Lagrangian function of the lower-level model:

[0244]

[0245] Next, taking the partial derivative with respect to the independent variable of optimization yields:

[0246]

[0247] Then, the inequality constraints are treated as complementary relaxation constraints, and the complementary conditions are transformed into cutting plane constraints using the Big-M method:

[0248]

[0249]

[0250] The following optimization scheduling is performed on a 24-hour cycle, with a natural gas price of 0.35 yuan / (kW·h) and a carbon emission allowance χ per unit of electricity consumption of coal-fired units. e = 0.798 kg / (kW·h), carbon emission allowance χ per unit of natural gas consumption for natural gas-fired power units g = 0.385 kg / (kW·h), unit wind curtailment penalty cost δ DG = 0.2 yuan / (kW·h), the time-of-use electricity price, the installed capacity and parameters of each energy storage, and the actual carbon emission model parameters are shown in Tables 1-4:

[0251] Table 1 Time-of-use electricity prices

[0252]

[0253] Table 2 Equipment Parameters

[0254] Table 3 Energy Storage Parameters

[0255] Table 4 Actual carbon emission model parameters

[0256]

[0257] To verify the effectiveness of considering the tiered carbon trading mechanism, the interval length is set as l = 2t, the price growth rate as α = 25%, and the carbon trading base price as λ = 250 yuan / t. Three operating scenarios are set up for comparative analysis. Scenario 1 is a traditional economic dispatch scenario under the tiered carbon trading mechanism, where the optimization objective does not consider carbon trading costs but only energy purchase costs and wind curtailment costs. Scenario 2 is a low-carbon economic dispatch scenario under the traditional carbon trading mechanism, where the optimization objective considers energy purchase costs, carbon trading costs, and wind curtailment costs. Scenario 3 is a low-carbon economic dispatch scenario under the tiered carbon trading mechanism, where the optimization objective considers energy purchase costs, carbon trading costs, and wind curtailment costs. Table 3-5 shows the dispatch results under the three operating scenarios. As can be seen from the table, the carbon emissions when the optimization objective considers carbon trading costs are much lower than those when the optimization objective does not consider carbon trading costs. Specifically, carbon emissions in Scenario 2 are reduced by 11.91% compared to Scenario 1; carbon emissions in Scenario 3 are reduced by 18.73% compared to Scenario 1, and Scenario 3 reduces carbon emissions by 1201 kg compared to Scenario 2, which is a reduction of 6.10%. It is evident that considering a tiered carbon trading mechanism can maximize the constraint of carbon emissions and achieve the goal of emission reduction.

[0258] Table 5. Comparison of benefits before and after considering the tiered carbon trading mechanism

[0259]

[0260] Combining time-of-use electricity pricing and gas pricing, we can see that Scenario 1 aims at optimizing traditional economic operations. Since gas prices are cheaper than electricity prices at all times, the system will purchase as much natural gas as possible and supply power to the electrical load through CHP. Therefore, the total energy purchase cost is minimized. However, the large-scale purchase of natural gas results in the actual carbon emissions generated by burning natural gas being far higher than the carbon emission allowance. Based on actual carbon emission models, it is known that when the combustion of natural gas reaches a certain level, continued combustion of natural gas will significantly increase carbon emissions. This is the reason for the high carbon emissions in Scenario 1. At this point, a large number of carbon emission allowances need to be purchased from the carbon trading market, resulting in the highest total cost. Scenario 2 considers carbon trading costs during optimization. Although purchasing gas is cheaper than purchasing electricity, the cost saved by purchasing gas instead of electricity is already lower than the cost of purchasing carbon emission allowances from the carbon trading market due to the high carbon emissions generated by burning natural gas. Therefore, compared to Scenario 1, Scenario 2 reduces gas purchases and increases electricity purchases. Scenario 3, due to the tiered carbon trading mechanism, has a tiered price for carbon emission allowances, which further limits the system's carbon emissions to some extent. Therefore, Scenario 3 again reduces gas purchases and increases electricity purchases, reaching a new equilibrium.

[0261] Comparing the total costs of the three operating scenarios, Scenario 1 has the lowest energy purchase cost, but because it doesn't consider carbon trading costs during optimization, it requires purchasing a large number of carbon emission allowances from the carbon trading market, resulting in the highest total cost. Scenario 2 increases energy purchase costs, but because carbon emission costs are lower and the carbon trading mechanism uses a traditional constant-price mechanism where the purchase price is calculated only based on the base price, the carbon trading cost is lower, resulting in the lowest total cost. Although Scenario 3's total cost is 1024 yuan higher than Scenario 2's, carbon emissions are reduced by 1201 kg, demonstrating that under the tiered carbon trading mechanism, the system can maintain low operating costs while reducing emissions.

[0262] To demonstrate the scheduling advantages of refining the P2G process into a two-stage operation combining EL, MR, and HFC, three operating scenarios were set up: Scenario 4, where the IES (Environmental Engineering System) does not contain electro-pneumatic coupling equipment; Scenario 5, where the IES contains traditional P2G equipment; and Scenario 6, where the P2G is replaced by a two-stage operation combining EL, MR, and HFC. The scheduling results for the three operating scenarios are shown in Table 6. As can be seen from the table, Scenario 6 has the lowest total operating cost, reducing it by 2100 yuan and 1457.3 yuan compared to Scenario 4 and Scenario 5, respectively. In terms of carbon emissions, Scenario 6 reduces emissions by 2917 kg compared to Scenario 4 and by 3112 kg compared to Scenario 5. Therefore, refining the P2G two-stage process can reduce carbon emissions while lowering operating costs.

[0263] Table 6. Detailed Comparison of Benefits Before and After the Two-Stage Operation of P2G

[0264] During the nighttime hours, in Scenario 4 without P2G equipment, due to the anti-peak-shaving characteristics of wind power, wind power output is at its peak at night, while the electricity load is at its lowest. Some of the wind power is directly absorbed by the electricity load, and some is stored in energy storage and released during peak electricity demand, but this still results in severe wind curtailment.

[0265] Scenario 5 adds P2G equipment, which can convert excess electricity into natural gas during periods of wind power surplus, and provide it to gas storage or load. This achieves the goal of low-storage-high-output for energy storage equipment and local load consumption, so there is no wind curtailment. Furthermore, by utilizing the electricity that was originally curtailed from the wind, the cost of purchasing electricity from the upstream is reduced, and the economic cost is further optimized.

[0266] In Scenario 6, IES first feeds surplus wind power into the EL unit to produce hydrogen, absorbing all the wind power. Part of the hydrogen energy is stored in the hydrogen storage system, leveraging its low-storage-high-generation arbitrage potential; part is transported to HFC for cogeneration; and another part is transported to MR for natural gas synthesis. Since hydrogen energy undergoes multiple stages of energy loss before being transported to GB and CHP for power supply via MR synthesis, and because HFC has high efficiency in hydrogen cogeneration while reducing an intermediate energy conversion step, hydrogen energy is preferentially transported to HFC for cogeneration. Therefore, HFC operates at full capacity, and the remaining hydrogen energy is then converted into natural gas via MR.

[0267] Based on the same inventive concept, this application also provides a device for optimizing the thermoelectric power of a carbon-capture integrated energy system considering a tiered carbon trading mechanism, in order to implement the aforementioned method for optimizing the thermoelectric power of a carbon-capture integrated energy system considering a tiered carbon trading mechanism. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations in the embodiments of the device for optimizing the thermoelectric power of a carbon-capture integrated energy system considering a tiered carbon trading mechanism provided below can be found in the limitations of the method for optimizing the thermoelectric power of a carbon-capture integrated energy system considering a tiered carbon trading mechanism described above, and will not be repeated here.

[0268] Please see Figure 4 This invention also provides a carbon capture integrated energy system thermal power optimization device considering a tiered carbon trading mechanism, applicable to low-carbon operation scenarios of integrated energy systems, including:

[0269] The model building module is used to obtain a detailed model of the integrated energy system with carbon capture, including refining the two-stage operation process of P2G, introducing electrolyzers, methane reactors, and hydrogen fuel cells to replace the traditional P2G, and using CO2 captured by carbon capture as a raw material to supply gas during the natural gas generation process, and constructing a coordinated scheduling framework for carbon capture power plants, electricity to gas conversion and gas turbine units.

[0270] The parameter acquisition module is used to acquire carbon trading market information and introduce a tiered carbon trading mechanism to guide IES control of carbon emissions.

[0271] The solution module is used to construct a two-layer optimization model with the upper layer being the minimum total operating cost of the IES and the lower layer being the minimum load fluctuation. The lower layer model is transformed into constraints of the upper layer model through KKT conditions to obtain the optimal operating scheme of the carbon capture integrated energy system for thermal power.

[0272] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0273] Please see Figure 5 This invention provides a computer device, including a memory and a processor, and a computer program stored in the memory. When the computer program is executed on the processor, it implements a method for optimizing the thermal power of a carbon capture integrated energy system considering a tiered carbon trading mechanism, as described in any of the above methods.

[0274] The computer device may be a desktop computer, laptop, handheld computer, or cloud server, etc. This computer device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that... Figure 5 The examples of computer devices are merely examples and do not constitute a limitation on computer devices. They may include more or fewer components than shown in the illustration, or combinations of certain components, or different components. For example, they may also include input / output devices, network access devices, etc.

[0275] The processor referred to can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0276] In some embodiments, the memory may be an internal storage unit of the computer device, such as a hard drive or RAM. In other embodiments, the memory may be an external storage device of the computer device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory may include both internal and external storage units of the computer device. The memory is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory can also be used to temporarily store data that has been output or will be output.

[0277] This invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a method for optimizing the thermal power of a carbon capture integrated energy system considering a tiered carbon trading mechanism, as described in any of the above methods.

[0278] In this embodiment, if the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0279] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0280] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0281] In the embodiments disclosed in this application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0282] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A thermoelectric optimization method and related apparatus for an integrated energy system (IES) with carbon capture and treatment considering a tiered carbon trading mechanism, applied to low-carbon operation scenarios of integrated energy systems, characterized in that, Includes the following steps: An IES system coupled operation model is constructed, which includes refining the two-stage operation process of power to gas (P2G), introducing an electrolyzer (EL), a methane reactor (MR), and a hydrogen fuel cell (HFC) to replace the traditional P2G, and using CO2 from a carbon capture power plant (CCPP) as a feedstock to supply the gas during the natural gas generation process, thus constructing a coordinated scheduling framework for the carbon capture power plant – power to gas – gas turbine unit; Considering the participation of IES in the carbon trading market, a tiered carbon trading mechanism should be introduced to guide IES in controlling carbon emissions; Based on this, a two-layer optimization model is constructed with the upper layer being the minimum total operating cost of the IES and the lower layer being the minimum load fluctuation. The lower layer model is then transformed into the upper layer model's constraint condition through the KKT (Karush-Kuhn-Tucker) condition, thus obtaining the optimal thermal power operation scheme for the carbon capture integrated energy system.

2. The method for optimizing the thermal power of a carbon capture integrated energy system considering a tiered carbon trading mechanism according to claim 1, characterized in that, The process of constructing the coupled operation model of the IES system includes constructing models of each aggregation unit: The total energy consumption and carbon capture output of the carbon capture system are expressed as follows: In the formula: P t C-P P represents the total energy consumption of the CCPP-P2G system during time period t; t EL_IN The energy consumption of P2G equipment during time period t (this power is provided by wind and solar curtailment to achieve the absorption of wind and solar curtailment); P t WA P t VA These represent the power curtailed from wind and solar power during time period t; P t CC P t OP P t GN P t G P t GC P t Gα These represent the carbon capture energy consumption during time period t, carbon capture operation energy consumption, net output of the carbon capture power plant, equivalent output of the carbon capture power plant, carbon capture energy consumption provided by the carbon capture power plant, and flue gas treatment energy consumption; P A Energy consumption of the CCPP-P2G system (considered a constant due to its small proportion), in MW; The energy consumption model for the flue gas treatment system of a waste incineration power plant is as follows: In the formula: w α P is the unit energy consumption coefficient of the flue gas treatment system. t α Let α1 be the energy consumption for flue gas treatment at time t; t α3 represents the portion of the flue gas treated at time t that is supplied by the flue gas generated during the operation of the waste-to-energy power plant; t The amount of flue gas supplied by the gas storage device when flue gas treatment is performed at time t; The model expressions for gas-fired (CHP) units and gas-fired boilers (GB) are as follows: In the formula: P t PH P t CHP H t CHP These represent the total output power, electrical and thermal power of the CHP unit during time period t; V t CHP V t GB η represents the amount of natural gas consumed by the CHP unit and the gas-fired boiler during time period t; CHP e η CHP h These are the electrical and thermal efficiencies of the CHP unit and the efficiency of the gas-fired boiler, respectively; H t GB The output thermal power of the gas-fired boiler during time period t; The expressions for the power of electric and thermal energy storage, taking into account the power losses of the electric and thermal energy storage devices themselves, are as follows: In the formula: S t ES S t TS The electrical and thermal energy storage at the end of time period t, respectively, in MW and P. t ESC P t ESD H represents the charging and discharging power of the energy storage device during time period t; t TSC H t TSD η represents the charging and discharging power of the thermal storage device during time period t; ESC η ESD η TSC η TSD These represent the charging and discharging efficiencies of electrical and thermal energy storage, respectively.

3. The method for optimizing the thermal power of a carbon capture integrated energy system considering a tiered carbon trading mechanism according to claim 1, characterized in that, In the process of constructing the coupled operation model of the IES system, the detailed two-stage operation process of P2G is as follows: EL first converts electrical energy into hydrogen energy. Part of the hydrogen energy is input into MR and synthesized with CO2 to form natural gas, which is supplied to the gas load, GB, and CHP units. Part of the hydrogen energy is directly transported to HFC and converted into electrical and thermal energy. The remaining part is stored in hydrogen storage tanks. The above energy conversion model can be described as follows: EL devices: In the formula, P t H2 η is the hydrogen energy output by EL during time period t; EL The energy conversion efficiency of EL; P EL_IN,max P EL_IN,min These are the upper and lower limits of the electrical energy input to EL, respectively; △P EL_IN,max , △P EL_IN,min These represent the upper and lower limits of EL's ramp rate, respectively. MR equipment: In the formula, Q t CC w represents the amount of CO2 captured by the CCPP-P2G system during time period t; C Q represents the operating energy consumption per unit of CO2 processed by a carbon capture power plant, expressed in MW·h / t. t P2G,sum α represents the total CO2 consumed by the P2G device during time period t; CO2 The amount of CO2 required to produce a unit power of natural gas, t / (MW·h); η P2G V represents the electro-gas conversion efficiency of the P2G equipment. t P2G H represents the volume of natural gas generated by P2G during time period t; g The calorific value of natural gas is taken as 39 MJ / m³; P P2G,max This represents the upper limit of energy consumption for the MR process. HFC equipment: In the formula, P t H2,HFC P represents the hydrogen energy input into the HFC during time period t; t HFC H t HFC These represent the electrical and thermal energy output by the HFC during time period t, respectively. η HFC e η HFC h These represent the efficiencies of HFC in converting energy into electricity and heat, respectively; P H2,HFC,max P H2,HFC,min These represent the upper and lower limits of hydrogen energy input to HFCs; ΔP H2,HFC,max , △P H2,HFC,min These represent the upper and lower limits of HFC ramp rate, respectively.

4. The method for optimizing the thermal power of a carbon capture integrated energy system considering a tiered carbon trading mechanism according to claim 1, characterized in that, The process of constructing the coupled operation model of the IES system includes building a joint operation strategy for carbon capture-waste incineration-wind power-photovoltaics, specifically: A portion of the power generated by wind and solar power is used as energy consumption for carbon capture systems, another portion is used as energy consumption for flue gas treatment systems, and the remaining power is fed into the power grid. Similarly, a portion of the power generated by carbon capture power plants and waste incineration power generation is used as energy consumption for carbon capture systems, another portion is used as energy consumption for flue gas treatment systems, and the remaining power is fed into the power grid. The specific expressions are as follows: In the formula: P t WC P t VC P t WIC The carbon capture energy consumption provided by wind power, photovoltaic units, and waste incineration power plants during time period t are respectively; P t Vα P t Wα P t Gα P t WIα The energy consumption for flue gas treatment provided by photovoltaic, wind power, carbon capture power plants, and waste incineration power plants during time period t are respectively; P t WN P t VN P t WIN These represent the grid-connected power generation capacity of wind power, photovoltaic power, and waste incineration power plants during time period t; P t W P t V P t WI These represent the predicted output of wind power, photovoltaic power, and waste incineration power generation during time period t; Q t N e represents the net CO2 emissions of the carbon capture power plant during time period t, in t / h. g The amount of CO2 produced per unit of equivalent power output of an internal carbon capture power plant, expressed in t / (MW·h).

5. The method for optimizing the thermal power of a carbon capture integrated energy system considering a tiered carbon trading mechanism according to claim 1, characterized in that, The tiered carbon trading cost is: In the formula, E IES，t For IES carbon emissions trading volume, C CO2 λ represents the tiered carbon trading cost; λ represents the base price for carbon trading; l represents the length of the carbon emission bright range; and α represents the price growth rate.

6. The method for optimizing the thermal power of a carbon capture integrated energy system considering a tiered carbon trading mechanism according to claim 5, characterized in that, In the calculation of the tiered carbon trading cost, the actual carbon emission model is as follows: In the formula, E IES，a E e,total，a E g,total，a These represent the total carbon emissions from IES (Environmental Engineering Systems), coal-fired power plants, and gas-fired power plants, respectively; Q t e.total e represents the equivalent output energy consumption of a coal-fired power plant during time period t. α For the unit output flue gas emission intensity of waste incineration power plants, t / (MW·h), P t g.total Let t represent the equivalent output power of the gas-fired power plant during time period t; a1, b1, c1 and a2, b2, c2 are the carbon emission parameters of the coal-fired unit and the gas-fired unit, respectively.

7. The method for optimizing the thermal power of a carbon capture integrated energy system considering a tiered carbon trading mechanism according to claim 5, characterized in that, In the calculation of the tiered carbon trading cost, the carbon emission allowances for carbon capture power plants, waste incineration power plants, GB, and CHP are calculated as follows: In the formula, E IES E G E WI E CHP E GB These are carbon emission allowances for IES, carbon capture power plants, waste incineration power plants, CHP, and GB, respectively; x e x g These represent the carbon emission allowances per unit of electricity consumption for coal-fired power units and per unit of natural gas consumption for natural gas-fired power units, respectively; T represents the dispatch cycle.

8. The method for optimizing the thermal power of a carbon capture integrated energy system considering a tiered carbon trading mechanism according to claim 1, characterized in that, The proposed two-layer optimization model aims to minimize the total operating cost of the IES (Environment, Environment, and Systems) at the upper layer and minimize load fluctuations at the lower layer. The objective functions and constraints corresponding to this objective are as follows: Upper-level objective function: In the formula: the objective function contains 9 parts, which are the fuel cost C of the carbon capture power plant. t F Tiered carbon trading costs C t CO2 CHP unit and gas boiler cost C t H P2G cost C t P2G Carbon sequestration cost C t CS System operation and maintenance costs C t W And the cost of purchasing electricity in the energy market C t M T is the total scheduling duration; a f b f c f d f e f P is the fuel cost coefficient. G，min This represents the lower limit of output for carbon capture power plants; k CH4 The fixed price per unit of natural gas in the natural gas market is $ / m3; V t BUY For natural gas purchase volume, m3; k CO2 The fixed price for purchasing CO2 is $ / t; kP2G is the P2G operating cost coefficient, $ / (MW·h); k CS A fixed price per unit of CO2 for storage, $ / t; k t EM The grid purchase price for electricity during time period t is $ / (MW·h); P t EM Let t be the electricity purchased from the power grid during time period t, in MW·h; Upper-level constraints: In the formula: P t EL H t HL The electrical and thermal loads for time period t are in MW and P, respectively. G,max P is the upper limit of equivalent output. t C，max This represents the upper limit of energy consumption for the carbon capture system during time period t. λ t CC ΔP represents the flue gas split ratio of the carbon capture system during time period t; G Constraints on the ramp-up rate of carbon capture power plant output; △P C Constraints on the rate of increase of carbon capture energy consumption in carbon capture power plants. CHP,max P CHP,min H CHP,max H CHP,min The upper and lower limits of electrical output and thermal output of the CHP unit are respectively defined; △P PH For the output ramp-up rate constraint of the CHP unit; H GB,max H GB,min These represent the upper and lower limits of the output of the gas-fired boiler; △H GB Constraints on the ramp-up rate of gas-fired boiler output. WI The total daily output of a waste-to-energy power plant is constant because its fuel is supplied by the government in fixed quantities of municipal solid waste based on the installed capacity; W WI,max This represents the maximum daily output of a waste-to-energy power plant; P WI,max P WI,min These represent the maximum and minimum output values ​​at each moment, respectively. △P WI For the climbing rate constraint; λ t WI V is the flue gas split ratio, which is the ratio of the amount of flue gas flowing into the reactor of a waste-to-energy power plant to the total amount of flue gas generated on the power generation side; t WIα V represents the gas storage capacity of the flue gas storage tank at time t. t WIα，max The maximum capacity of the gas storage device; α t 2 V represents the amount of flue gas flowing into the gas storage device at time t; L WIα,max P represents the maximum flow rate in the inlet and outlet pipes of the gas storage device. t ES,H2 The power input to the hydrogen storage during time period t; Lower-level objective function: In the formula: F1 is the equivalent load variance; P t E Let P be the equivalent electrical load at time t; t E.mv Let be the mean of the equivalent electrical load at time t; Lower-level constraints: In the formula: P ESC,max P ESD,max These represent the maximum charging and discharging power, respectively; Boolean variable μ t ESC μ t ESD These represent whether electrical energy storage is charging / discharging and whether thermal energy storage is storing / releasing heat during time period t, respectively; set to 1 if yes, and 0 otherwise; S ES,max S ES,min These represent the maximum and minimum energy storage capacities, respectively; S0 ES S 24 ES These represent the beginning and end values ​​of the energy storage battery at the start and end of the day, respectively.

9. A thermoelectric optimization device for an integrated energy system (IES) with carbon capture, considering a tiered carbon trading mechanism, applied to low-carbon operation scenarios of integrated energy systems, characterized in that, include: The model building module is used to obtain a detailed model of the integrated energy system with carbon capture, including a detailed two-stage operation process of power-to-gas (P2G), the introduction of electrolyzers (EL), methane reactors (MR), and hydrogen fuel cells (HFC) to replace the traditional P2G, and the use of CO2 captured by carbon capture as a raw material to supply gas during the natural gas generation process, and the construction of a coordinated scheduling framework of carbon capture power plant-power-to-gas-gas unit. The parameter acquisition module is used to acquire carbon trading market information and introduce a tiered carbon trading mechanism to guide IES to control carbon emissions; The solution-solving module is used to construct a two-layer optimization model with the upper layer being the minimum total operating cost of the IES and the lower layer being the minimum load fluctuation. The lower-layer model is transformed into constraints for the upper-layer model through KKT conditions to obtain the optimal thermal power operation scheme of the carbon capture integrated energy system.

10. A computer device, characterized in that, The device includes a processor and a memory: The memory is used to store computer programs and send the instructions of the computer programs to the processor; The processor executes, according to the instructions of the computer program, a thermal power optimization method for a carbon capture integrated energy system considering a tiered carbon trading mechanism as described in any one of claims 1-8.

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