Pure oxygen combustion carbon reduction capacity optimization system and method based on wind and light oxygen generation

Abstract

The invention provides a pure oxygen combustion carbon reduction capacity optimization system and method based on wind and light oxygen generation. Wind energy and solar energy are converted into electric energy through a wind power system and a photovoltaic system; performing direct current-alternating current conversion on the electric energy generated by the wind and light absorption function module, and performing filtering through a filter to complete electric energy preprocessing; the pretreated electric energy passes through a proton exchange membrane electrolytic bath to generate oxygen, and the oxygen is stored through a gas storage tank; oxygen in a gas storage tank is introduced into a pure oxygen kiln, methanated fuel gas is subjected to pure oxygen combustion in the pure oxygen kiln, and carbon dioxide generated after combustion is captured and separated through a carbon dioxide separation device; according to energy resource endowment and load characteristic difference of different regions, with the minimum total cost as a target and the average profit for many years as an auxiliary evaluation index, constraint conditions are constructed, and a differentiated capacity configuration strategy is formulated. The problems that existing new energy consumption is insufficient, the regional adaptability is poor, and the carbon capture cost is high are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of energy carbon reduction technology, and in particular to a pure oxygen combustion carbon reduction capacity optimization system and method based on wind and light oxygen production. BACKGROUND

[0002] Under the background of deepening the "double carbon" goal and accelerating new energy transformation, the power system needs to simultaneously improve the new energy consumption capacity and the industrial carbon reduction effect, but the current technical system faces multiple challenges: on the one hand, wind power, photovoltaic and other new energy sources have intermittent and fluctuating characteristics, and the energy resource endowment and load characteristics of different regions are significantly different, which makes it difficult for traditional new energy systems to adapt to multi-regional scenarios and lack universality; on the other hand, the industrial field is the main source of carbon emissions, and the traditional air combustion technology has low carbon emission concentration, and the carbon capture requires complex chemical absorption process, with high cost, while the oxygen-enriched combustion technology can increase the carbon dioxide concentration to about 80%, but the capture energy consumption is still high, and it is difficult to balance efficiency and economy without forming synergy with new energy consumption.

[0003] In terms of system synergy, existing new energy consumption systems mainly focus on single energy conversion and are not deeply coupled with industrial combustion carbon reduction. The high-purity oxygen produced in the process of electrolytic water hydrogen production is not effectively utilized, which not only wastes resources but also makes the pure oxygen combustion technology difficult to promote due to its dependence on deep freezing and vacuum pressure swing adsorption for oxygen source. At the same time, the modeling of core equipment is not fine enough: the traditional modeling of gas storage system ignores the pre-compressor pressurization and post-compressor pressure stabilization, which cannot accurately simulate the balance between gas supply and demand; the pure oxygen furnace does not fully depict the coupling process of turbulent flow, radiation heat transfer and combustion reaction, resulting in large simulation deviation of operation characteristics and affecting the accuracy of system scheduling. In the field of capacity configuration, traditional optimization models use unified strategies and do not develop differentiated solutions for typical regions such as offshore, inland and plateau: offshore regions have excess wind resources, which can lead to wind curtailment, but lack targeted consumption paths; inland regions rely on upper-level power distribution networks for electricity purchase, indirectly increasing carbon emissions; plateau regions have sparse loads, and the cost of external gas transportation is high, so existing systems are difficult to adapt. In addition, the closed loop of carbon capture and new energy consumption has not been formed, and the pure oxygen combustion can increase the carbon dioxide concentration to more than 95%, and the capture energy consumption is reduced, but how to solve the oxygen source through wind and light redundant electric energy electrolysis, and balance the equipment investment and life cycle benefits through capacity optimization, has become a key problem that needs to be broken through.

[0004] And sharing energy storage although has the application in the energy community, virtual power plant and other scenes, but has not combined with pure oxygen combustion carbon reduction system, cannot play the synergistic effect of "new energy consumption - oxygen supply - carbon capture", the capacity optimization model focuses on single economic target, without considering the multi-year average profit and multi-region adaptability constraints, resulting in the feasibility of the configuration results is insufficient in practical application. In summary, it is urgent to build an integrated system model of "wind and light oxygen generation - pure oxygen combustion - carbon capture", and design a capacity optimization strategy considering regional differences, to fill the technical gap in the cross field of new energy and industrial carbon reduction. SUMMARY

[0005] The application provides a pure oxygen combustion carbon reduction capacity optimization system and method based on wind and light oxygen generation, to solve the problems of insufficient new energy consumption, poor regional adaptability and high carbon capture cost.

[0006] The application provides a pure oxygen combustion carbon reduction capacity optimization system based on wind and light oxygen generation, comprising:

[0007] A wind and light consumption energy supply module is used to convert wind energy and solar energy into electrical energy through a wind power system and a photovoltaic system.

[0008] A power control module is used to convert the electrical energy generated by the wind and light consumption function module into alternating current through direct current - alternating current conversion, and complete electrical energy pretreatment through filtering by a filter.

[0009] An energy conversion module is used to generate oxygen by proton exchange membrane electrolytic cell through pretreated electrical energy, and store oxygen by a gas storage tank.

[0010] A pure oxygen combustion carbon capture module is used to connect the oxygen in the gas storage tank to a pure oxygen kiln, and perform pure oxygen combustion on the methaneized fuel gas in the pure oxygen kiln, and capture and separate the carbon dioxide generated after combustion by a carbon dioxide separation device.

[0011] A difference constraint module is used to construct constraint conditions and develop differentiated capacity configuration strategies in the wind and light consumption energy conversion process, according to the differences in energy resource endowment and load characteristics of different regions, with the minimum total cost as the target and the multi-year average profit as the auxiliary evaluation index.

[0012] According to the pure oxygen combustion carbon reduction capacity optimization system based on wind and light oxygen generation provided by the application, the wind power system and the photovoltaic system of the wind and light consumption energy supply module construct a power generation model.

[0013] The wind power system converts wind energy into electrical energy through a wind wheel, a transmission system and a generator system, and the photovoltaic system converts solar energy into electrical energy through a photovoltaic module and a combiner box.

[0014] According to the present invention, a pure oxygen combustion carbon reduction capacity optimization system based on wind and solar oxygen production is provided. The power control module converts the electrical energy generated by the wind and solar energy consumption module into DC power through an AC-DC converter, transmits it in the form of DC power, and before connecting to the grid, the DC power is converted into AC power through a DC-AC inverter. Then, the high-frequency harmonics generated during the conversion process are filtered out by a filter to complete the power preprocessing.

[0015] According to the present invention, a pure oxygen combustion carbon reduction capacity optimization system based on wind and solar oxygen production is provided, wherein the energy conversion module includes: a proton exchange membrane electrolyzer and a gas storage system;

[0016] Oxygen is generated by oxidation and reduction reactions occurring at the anode and cathode of the proton exchange membrane electrolyzer, respectively, thus constructing a power output model for the proton exchange membrane electrolyzer.

[0017] The oxygen produced by the proton exchange membrane electrolyzer is pre-compressed by the pre-compressor of the gas storage system, stored in the gas storage tank, and then output compressed by the post-compressor.

[0018] According to the present invention, a pure oxygen combustion carbon reduction capacity optimization system based on wind and solar oxygen production is provided, wherein the pure oxygen combustion carbon capture module includes: a combustion system and a capture system;

[0019] The combustion system includes a methane reactor and a pure oxygen kiln. The methane reactor is used to methanate the fuel gas, and the pure oxygen kiln is connected to a gas storage tank. After oxygen is introduced, the methanated fuel gas is burned in the pure oxygen kiln.

[0020] The capture system condenses, compresses, and separates the carbon dioxide produced by the combustion of pure oxygen, thus completing the capture of carbon dioxide.

[0021] According to the present invention, a pure oxygen combustion carbon reduction capacity optimization system based on wind and solar oxygen production is provided. The difference constraint module uses the minimum total cost of the wind and solar energy consumption and supply module, power control module, energy conversion module and pure oxygen combustion carbon capture module as the objective function to configure the system capacity; and uses the profit in the future preset period to judge the economics of different schemes and select the scheme accordingly.

[0022] Differentiated capacity configuration strategies are formulated based on constraints using a pre-defined optimization configuration model.

[0023] This invention also provides a method for optimizing carbon reduction capacity through pure oxygen combustion based on wind and solar oxygen production, the method comprising:

[0024] Converting wind and solar energy into electrical energy through wind power systems and photovoltaic systems;

[0025] The electrical energy generated by the wind and solar energy absorption module is converted from DC to AC and filtered by a filter to complete the electrical energy preprocessing.

[0026] The pretreated electrical energy is used to generate oxygen through a proton exchange membrane electrolyzer, and the oxygen is stored in a gas storage tank.

[0027] By introducing oxygen from the gas storage tank into a pure oxygen kiln, the methanated fuel gas is combusted in pure oxygen in the pure oxygen kiln, and the carbon dioxide produced after combustion is captured and separated by a carbon dioxide separation device.

[0028] In the process of wind and solar energy conversion, based on the differences in energy resource endowment and load characteristics in different regions, with the goal of minimizing total cost and using multi-year average profit as an auxiliary evaluation indicator, constraints are constructed and differentiated capacity allocation strategies are formulated.

[0029] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the carbon reduction capacity optimization method for pure oxygen combustion based on wind and solar oxygen production as described above.

[0030] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the carbon reduction capacity optimization method for pure oxygen combustion based on wind and solar oxygen production as described above.

[0031] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the carbon reduction capacity optimization method for pure oxygen combustion based on wind and solar oxygen production as described above.

[0032] This invention provides a capacity optimization system and method for carbon reduction through pure oxygen combustion based on wind and solar oxygen production. It constructs an integrated carbon reduction system comprising a wind and solar energy consumption module, a power control module, an energy conversion module, and a pure oxygen combustion carbon capture module. Through refined modeling of each subsystem, it achieves synergy between wind and solar redundant electricity electrolysis for oxygen production and efficient carbon reduction through pure oxygen combustion. Simultaneously, it constructs a capacity optimization configuration model considering regional differences, aiming to minimize total cost. Economic viability is assessed based on multi-year average profits, and three configuration strategies—unrestricted, self-sufficient, and minimal wind curtailment—are formulated for three typical regions: nearshore, inland, and plateau. Multi-dimensional constraints, such as typical daily scenario constraints and wind-solar complementarity constraints, ensure system feasibility, ultimately improving the capacity for renewable energy consumption and reducing carbon emissions. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in this 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 some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0034] Figure 1 This is a schematic flowchart of the method for optimizing carbon reduction capacity through pure oxygen combustion in wind and solar oxygen production provided by the present invention.

[0035] Figure 2 This is a schematic diagram of the module connection of the pure oxygen combustion carbon reduction capacity optimization system for wind and solar oxygen production provided by the present invention.

[0036] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention.

[0037] Figure label:

[0038] 110: Wind and solar energy integration module; 120: Power control module; 130: Energy conversion module; 140: Pure oxygen combustion carbon capture module; 150: Differential constraint module;

[0039] 310: Processor; 320: Communication interface; 330: Memory; 340: Communication bus. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0041] The following is combined with Figures 1-2 The present invention describes a pure oxygen combustion carbon reduction capacity optimization system based on wind and solar oxygen production, comprising:

[0042] The wind and solar energy integration module 110 is used to convert wind energy and solar energy into electrical energy through wind power systems and photovoltaic systems.

[0043] The power control module 120 is used to convert the electrical energy generated by the wind and solar energy absorption module into DC-AC and filter it through a filter to complete the electrical energy preprocessing.

[0044] The energy conversion module 130 is used to generate oxygen from pre-treated electrical energy through a proton exchange membrane electrolyzer and store the oxygen in a gas storage tank.

[0045] The pure oxygen combustion carbon capture module 140 is used to connect the oxygen in the gas storage tank to a pure oxygen kiln, perform pure oxygen combustion on the methanated fuel gas in the pure oxygen kiln, and capture and separate the carbon dioxide produced after combustion through a carbon dioxide separation device.

[0046] The differential constraint module 150 is used to construct constraints and formulate differentiated capacity allocation strategies during the energy conversion process of wind and solar power integration, based on the differences in energy resource endowment and load characteristics in different regions, with the goal of minimizing total cost and using multi-year average profit as an auxiliary evaluation indicator.

[0047] In this invention, the wind and solar energy integration module serves as the core energy supply unit, providing electricity in a coordinated manner and using redundant electricity for electrolytic oxygen production to avoid wind and solar curtailment. The power control module ensures power quality through an AC-DC converter and an LCL filter. The energy conversion module uses a PEM electrolyzer (i.e., a proton exchange membrane electrolyzer) to achieve energy form conversion. The gas storage system completes gas storage through a pre-compressor, a gas storage tank, and a post-compressor. The pure oxygen combustion carbon capture module achieves efficient carbon reduction through a methanation device, a pure oxygen kiln, and a carbon dioxide separation device. Furthermore, each subsystem is modeled in detail to improve simulation accuracy. In terms of capacity optimization, the system aims to minimize total cost and uses the average profit over the next 10 years as a secondary evaluation indicator. It comprehensively considers factors such as wind power absorption, economics, and carbon emission reduction. For three different energy resource endowments and load characteristics—offshore, inland, and plateau regions—three differentiated configuration strategies are formulated: unrestricted, self-sufficient, and minimal wind curtailment. The system's feasibility is ensured through eight constraints: typical daily scenarios, wind-solar complementarity, power balance, carbon balance, gas storage systems, upper and lower limits of output, power shortage load rate, and specific scheme limitations. In terms of application results, the system's simulation accuracy is more than 30% higher than traditional models, its universality is 50% higher than traditional unified models, carbon capture cost is reduced to 287.5 yuan / t, and the renewable energy absorption rate is increased to over 95%. Furthermore, all schemes can recoup their costs within 10 years, providing a feasible technical path for achieving dual-carbon goals.

[0048] Specifically, the power control module converts the electrical energy generated by the wind and solar power integration module into DC power through an AC-DC converter, transmits it in the form of DC power, and then converts the DC power back into AC power through a DC-AC inverter before connecting it to the grid. Finally, a filter is used to remove the high-frequency harmonics generated during the conversion process, thus completing the power preprocessing.

[0049] The power control module of this invention can achieve efficient conversion and stable output of electrical energy, while also possessing a variety of control and protection functions to adapt to different working conditions and load requirements. Its mathematical model is expressed as follows:

[0050] (1)

[0051] in, This is the DC output voltage. The input voltage is AC, and θ is the phase angle. For the efficiency of AC-DC converters, DC output power For AC input power.

[0052] The mathematical model of an LCL filter is expressed as follows:

[0053] (2)

[0054] in, This is the grid voltage. This is the voltage across the filter capacitor. and For filtering inductors, and C is the inductor current, and C is the filter capacitor.

[0055] In this invention, the energy conversion module includes: a proton exchange membrane electrolyzer and a gas storage system;

[0056] Oxygen is generated by oxidation and reduction reactions occurring at the anode and cathode of the proton exchange membrane electrolyzer, respectively, thus constructing a power output model for the proton exchange membrane electrolyzer.

[0057] The oxygen produced by the proton exchange membrane electrolyzer is pre-compressed by the pre-compressor of the gas storage system, stored in the gas storage tank, and then output compressed by the post-compressor.

[0058] The specific representation of the output model of a proton exchange membrane electrolyzer is as follows:

[0059] (3)

[0060] in, and These are the input power and rated power of the electrolytic cell, respectively. For hydrogen production, This refers to the rated capacity of the electrolytic cell; Let be the efficiency function. , , These are three efficiency coefficients.

[0061] Neglecting the thermal energy of the PEM electrolyzer, the formula for the electrolyzer output is as follows:

[0062] (4)

[0063] in, For the hydrogen production rate, V is the voltage of the electrolytic cell, and F is the Faraday constant.

[0064] In oxygen storage, the process generally consists of three parts: pre-injection compression, storage, and output compression, corresponding to the pre-compressor, storage tank, and post-compressor, respectively. The detailed mathematical model of the storage tank is as follows:

[0065] (5)

[0066] in, , These are the power ratings of the front and rear compressors, respectively. , , These represent the gas injection volume, the injection volume at the previous moment, and the output volume, respectively. This refers to the real-time pressure of the hydrogen storage container. This is the flow rate of hydrogen at this time. Let be the ideal gas constant. Where T is the input compression factor, and T is the temperature. This represents the volume of the hydrogen container.

[0067] The pure oxygen combustion carbon capture module includes: a combustion system and a capture system;

[0068] The combustion system includes a methane reactor and a pure oxygen kiln. The methane reactor is used to methanate the fuel gas, and the pure oxygen kiln is connected to a gas storage tank. After oxygen is introduced, the methanated fuel gas is burned in the pure oxygen kiln.

[0069] The capture system condenses, compresses, and separates the carbon dioxide produced by the combustion of pure oxygen, thus completing the capture of carbon dioxide.

[0070] Specifically, this invention does not include additional carbon capture and purification devices. The carbon dioxide absorbed after methanation is burned again with pure oxygen to produce high-purity carbon dioxide that can be directly stored. The model of the methane reactor is shown below:

[0071] (6)

[0072] in, For the power of methane production, This represents the real-time hydrogen flow rate in the methane reactor. The mass of methane per cubic meter of pipeline. For the operating efficiency of the methane reactor, It has the lowest heating value of methane.

[0073] The total output model is then expressed as follows:

[0074] (7)

[0075] in, , , The outlet flow rates are for methane, carbon dioxide, and hydrogen. , Conversion rate; The product of the condenser's conversion efficiency and its compressibility. This refers to the carbon dioxide flow rate at the condenser output. For the volume of the condenser tube, For the energy consumed, For compression efficiency; denoted as carbon dioxide output flow rate, and n as the chemical reaction coefficient.

[0076] Among them, the pure oxygen kiln is a high-efficiency combustion device that uses pure oxygen as a combustion aid. Compared with traditional air combustion, pure oxygen combustion has higher combustion efficiency, lower nitrogen oxide emissions, and better temperature control performance. The mathematical model of the pure oxygen kiln is expressed as follows:

[0077] (8)

[0078] (9)

[0079] (10)

[0080] Where ρ is density, φ is the dependent variable, u is fluid velocity, Γ is the generalized diffusion coefficient, and S is the generalized source term. Let α be the radiation intensity, α be the absorption coefficient, r be the position vector, and s be the direction vector. Let n be the scattering coefficient, n be the refractive index, T be the local temperature, and Ω′ be the solid angle. Contribute to the glass furnace, This is the system efficiency conversion factor. The calorific value of natural gas. is the conversion constant from MW to MJ.

[0081] The carbon dioxide separation unit of the capture system includes condensation, compression, and separation devices, and its mathematical model is represented as follows:

[0082] (11)

[0083] in, For the power of the condensing unit, For the condenser tube conversion efficiency, For equipment pressure. This refers to the carbon dioxide flow rate at the condenser output. Let be the ideal gas constant. The input compression factor. Where T is the input compression factor, and T is the temperature. For the volume of the condenser tube, For cavity volume, For the energy consumed, R is the output compressibility factor; R is the carbon dioxide heat capacity constant. For the output pressure, For compressor power, For compression efficiency, This represents the output flow rate of carbon dioxide.

[0084] In this invention, the differential constraint module uses the minimum total cost of the wind and solar energy consumption module, power control module, energy conversion module, and pure oxygen combustion carbon capture module as the objective function to configure the system capacity; and uses the profit over the next 10 years to judge the economics of different schemes and select the scheme accordingly.

[0085] Differentiated capacity configuration strategies are formulated based on constraints using a pre-defined optimization configuration model.

[0086] Based on a comprehensive analysis of the technical characteristics and application requirements of pure oxygen combustion carbon reduction systems, a capacity optimization configuration model was constructed. This model comprehensively considers factors such as wind power integration, economics, and carbon emission reduction. By introducing probabilistic analysis, the model can more accurately reflect the system's operating characteristics and uncertainties. Furthermore, optimization strategies for typical scenarios are proposed, taking into account the resource and demand characteristics of different regions.

[0087] The system uses the minimum total cost as the objective function to configure the system capacity; the economics of different schemes are judged based on the profit over the next 10 years to select the scheme. The cost includes glass revenue, carbon dioxide sales revenue, investment cost, operation and maintenance cost, material cost, wind curtailment penalty cost, and carbon capture cost, which can be expressed as equation (12). The formula for the average net profit over the next 10 years is equation (13), specifically expressed as follows:

[0088] (12)

[0089] (13)

[0090] Where C represents the total cost; The average profit over 10 years Let C1 be 10, representing the total operating revenue of the glass furnace, including reducing agent costs, arch costs, furnace wall costs, denitrification costs, maintenance costs, glass loss, and a constant glass revenue. C2 represents equipment investment costs, including the glass furnace, electrolysis unit, hydrogen storage tank, oxygen storage tank, methane storage tank, carbon dioxide storage tank, methanation unit, wind power system, condensation / compression unit, and gas sales lines. C3 represents operation and maintenance costs. C4 represents material costs, including the cost of externally supplied pure oxygen, hydrogen, and natural gas. C5 represents wind curtailment costs. C6 represents carbon dioxide sales revenue. C7 represents carbon capture costs. The glass furnace revenue, equipment investment costs, and maintenance costs are represented as follows:

[0091] (14)

[0092] in, The operating cost is set at 51.6884 million yuan per year, including the cost of the glass furnace roof, furnace walls, denitrification cost, and maintenance cost. This represents the daily glass production, which is 700 t / d; g is the glass raw material breakage rate, taken as 0.05. The cost of glass raw materials is set at 1300 yuan / ton; The profit from glass production is set at 2600 yuan / t; Z represents the number of power generation subsystems, which is set at 11. The total cost of the glass kiln is 22.47 million yuan. This is the gas pipeline strategy coefficient. This refers to the investment cost of gas sales pipelines; , Let represent the capacity and unit capacity cost of the i-th subsystem, r be the discount rate (0.1), Y be the lifespan (10 years), and µ be the maintenance factor (0.05).

[0093] The operating, material, wind curtailment penalty costs, and revenue from selling carbon dioxide are presented below:

[0094] (15)

[0095] (16)

[0096] (17)

[0097] (18)

[0098] Where sl represents the total number of typical daily load scenarios. Let 'sw' be the probability of the i-th typical load day scenario occurring, and 'sw' be the total number of typical wind power day scenarios. Let be the probability of the j-th typical wind power day scenario occurring. The additional gas strategy coefficient is T, where T is the operating cycle for each scenario, taken as 24 hours. The additional methane cost is set as a constant due to its low volatility; M is the difference between the year and 2024. , For the additional unit cost of oxygen and hydrogen, To mitigate the cost of wind curtailment penalties, , , , , These represent the consumption amounts corresponding to each device. , , For the capacity of air separation unit, condenser, and compressor, , , The unit cost corresponds to each of the three.

[0099] The system carbon capture cost formula can be derived from equations (12) to (18) as follows:

[0100] (19)

[0101] in, This refers to the annual carbon replenishment amount.

[0102] In this invention, the constraints of the optimized configuration model include:

[0103] Typical daily scenario constraints are represented as follows:

[0104] (20)

[0105] in, It represents the weight of each component in the DPMM fitting probability expression.

[0106] The constraints on wind-solar hybridization are specifically expressed as follows:

[0107] (twenty one)

[0108] in, For wind and solar penetration rate, To achieve maximum wind and solar penetration, To achieve maximum wind and solar penetration, This refers to the total power generation or total load demand of the system. To support the power grid's capabilities, and The energy supply ratio coefficient between wind power and solar power.

[0109] The power balance constraint is specifically represented as follows:

[0110] (twenty two)

[0111] in, For total wind power, , , , , , , , , These include the fan system, waste air, pure oxygen kiln, electrolytic cell, three front gas storage compressors, three rear gas storage compressors, methanation unit, condensation unit, and carbon dioxide compressor power.

[0112] The carbon balance constraint is specifically represented as follows:

[0113] (twenty three)

[0114] in, and denoted as methane and carbon dioxide flow rates at time t, respectively.

[0115] The constraints of the gas storage system are specifically represented as follows:

[0116] (twenty four)

[0117] in, , , , , These represent the total hydrogen production, hydrogen storage, methane storage, carbon dioxide storage, and total oxygen production at time t, respectively. , , , These represent the total storage amounts of hydrogen, oxygen, methane, and carbon dioxide at time t, respectively. , , , This refers to the volume of hydrogen storage tanks, oxygen storage tanks, methane tanks, and carbon dioxide tanks.

[0118] The upper and lower limits of output constraints are specifically represented as follows:

[0119] (25)

[0120] in, , , , , These are the rated power of the electric field, electrolytic cell, front compressor, rear compressor, methanation carbon capture unit, and air separation unit, respectively.

[0121] The power shortage load factor constraint is specifically represented as follows:

[0122] (26) (27)

[0123] in, The power shortage during time period t. Let be the load demand during time period t. Let be the total power generation of the microgrid during time period t. This represents the total load demand for the entire year. The maximum allowable load loss rate of the system.

[0124] The constraints require additional restrictions on the self-sufficiency and minimum wind curtailment schemes, as detailed below:

[0125] (28)

[0126] (29)

[0127] Analyze the characteristics of typical regions, formulate differentiated configuration strategies, and simulate and verify the economy and feasibility of system operation under different scenarios.

[0128] This invention also discloses a method for optimizing carbon reduction capacity through pure oxygen combustion based on wind and solar oxygen production, the method comprising:

[0129] Converting wind and solar energy into electrical energy through wind power systems and photovoltaic systems;

[0130] The electrical energy generated by the wind and solar energy absorption module is converted from DC to AC and filtered by a filter to complete the electrical energy preprocessing.

[0131] The pretreated electrical energy is used to generate oxygen through a proton exchange membrane electrolyzer, and the oxygen is stored in a gas storage tank.

[0132] By introducing oxygen from the gas storage tank into a pure oxygen kiln, the methanated fuel gas is combusted in pure oxygen in the pure oxygen kiln, and the carbon dioxide produced after combustion is captured and separated by a carbon dioxide separation device.

[0133] In the process of wind and solar energy conversion, based on the differences in energy resource endowment and load characteristics in different regions, with the goal of minimizing total cost and using multi-year average profit as an auxiliary evaluation indicator, constraints are constructed and differentiated capacity allocation strategies are formulated.

[0134] A power generation model is constructed for the wind power system and photovoltaic system of the wind-solar energy integration module;

[0135] The wind power system converts wind energy into electrical energy through a wind turbine, transmission system, and generator system, while the photovoltaic system converts solar energy into electrical energy through photovoltaic modules and combiner boxes.

[0136] The power control module converts the electrical energy generated by the wind and solar power integration module into DC power through an AC-DC converter. The DC power is then transmitted in the form of DC power. Before being connected to the grid, the DC power is converted back into AC power by a DC-AC inverter. Finally, a filter is used to remove high-frequency harmonics generated during the conversion process, thus completing the power preprocessing.

[0137] The energy conversion module includes: a proton exchange membrane electrolyzer and a gas storage system;

[0138] Oxygen is generated by oxidation and reduction reactions occurring at the anode and cathode of the proton exchange membrane electrolyzer, respectively, thus constructing a power output model for the proton exchange membrane electrolyzer.

[0139] The oxygen produced by the proton exchange membrane electrolyzer is pre-compressed by the pre-compressor of the gas storage system, stored in the gas storage tank, and then output compressed by the post-compressor.

[0140] The pure oxygen combustion carbon capture module includes: a combustion system and a capture system;

[0141] The combustion system includes a methane reactor and a pure oxygen kiln. The methane reactor is used to methanate the fuel gas, and the pure oxygen kiln is connected to a gas storage tank. After oxygen is introduced, the methanated fuel gas is burned in the pure oxygen kiln.

[0142] The capture system condenses, compresses, and separates the carbon dioxide produced by the combustion of pure oxygen, thus completing the capture of carbon dioxide.

[0143] The differential constraint module uses the minimum total cost of the wind and solar energy integration module, power control module, energy conversion module, and pure oxygen combustion carbon capture module as the objective function to configure the system capacity; and uses the profit over the next 10 years to judge the economics of different schemes and select the scheme accordingly.

[0144] Differentiated capacity configuration strategies are formulated based on constraints using a pre-defined optimization configuration model.

[0145] Based on the present invention, a carbon reduction capacity optimization method for pure oxygen combustion based on wind and solar oxygen production is provided. This method constructs an integrated carbon reduction system comprising a wind and solar energy consumption and supply module, a power control module, an energy conversion module, and a pure oxygen combustion carbon capture module. Through refined modeling of each subsystem, the method achieves synergy between wind and solar redundant power electrolysis for oxygen production and efficient carbon reduction through pure oxygen combustion. Simultaneously, a capacity optimization configuration model considering regional differences is constructed. With the goal of minimizing total cost, economic viability is assessed based on multi-year average profits. Three configuration strategies are formulated for three typical regions: nearshore, mid-inland, and plateau, namely, unlimited, self-sufficient, and minimal wind curtailment. Multi-dimensional constraints, such as typical daily scenario constraints and wind-solar complementarity constraints, ensure system feasibility, ultimately improving the renewable energy consumption capacity and reducing carbon emissions.

[0146] Figure 3 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 3 As shown, the electronic device may include: a processor 310, a communications interface 320, a memory 330, and a communications bus 340, wherein the processor 310, the communications interface 320, and the memory 330 communicate with each other through the communications bus 340. The processor 310 can call logic instructions in the memory 330 to execute a pure oxygen combustion carbon reduction capacity optimization method based on wind and solar oxygen production. This method includes: converting wind and solar energy into electrical energy through wind power and photovoltaic systems; converting the electrical energy generated by the wind and solar energy absorption module from DC to AC, filtering it through a filter to complete electrical energy preprocessing; generating oxygen from the preprocessed electrical energy through a proton exchange membrane electrolyzer, and storing the oxygen in a storage tank; connecting the oxygen in the storage tank to a pure oxygen kiln, performing pure oxygen combustion on the methanated fuel gas in the kiln, and capturing and separating the carbon dioxide produced after combustion through a carbon dioxide separation device; and, during the wind and solar energy conversion process, constructing constraints and formulating differentiated capacity configuration strategies based on the differences in energy resource endowment and load characteristics in different regions, with the goal of minimizing total cost and using multi-year average profit as an auxiliary evaluation indicator.

[0147] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0148] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the pure oxygen combustion carbon reduction capacity optimization method based on wind and solar oxygen production provided by the above methods. The method includes: converting wind energy and solar energy into electrical energy through wind power systems and photovoltaic systems; converting the electrical energy generated by the wind and solar energy absorption module into DC-AC conversion, filtering it through a filter, and completing the electrical energy preprocessing; generating oxygen from the preprocessed electrical energy through a proton exchange membrane electrolyzer, and storing the oxygen in a gas storage tank; connecting the oxygen in the gas storage tank to a pure oxygen kiln, performing pure oxygen combustion on the methanated fuel gas in the pure oxygen kiln, and capturing and separating the carbon dioxide generated after combustion through a carbon dioxide separation device; and, in the process of wind and solar energy conversion, constructing constraints and formulating differentiated capacity configuration strategies based on the differences in energy resource endowment and load characteristics in different regions, with the goal of minimizing total cost and using the average profit over many years as an auxiliary evaluation indicator.

[0149] On another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the above-described method for optimizing carbon reduction capacity through pure oxygen combustion based on wind and solar energy generation. This method includes: converting wind and solar energy into electrical energy through wind power and photovoltaic systems; performing DC-AC conversion on the electrical energy generated by the wind and solar energy absorption module, filtering it through a filter, and completing electrical energy preprocessing; generating oxygen from the preprocessed electrical energy through a proton exchange membrane electrolyzer, and storing the oxygen in a gas storage tank; connecting the oxygen in the gas storage tank to a pure oxygen kiln, performing pure oxygen combustion on the methanated fuel gas in the pure oxygen kiln, and capturing and separating the carbon dioxide generated after combustion through a carbon dioxide separation device; and, in the process of wind and solar energy conversion, constructing constraints and formulating differentiated capacity configuration strategies based on the differences in energy resource endowment and load characteristics in different regions, with the goal of minimizing total cost and using multi-year average profit as an auxiliary evaluation indicator.

[0150] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0151] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; 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; and these 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 pure oxygen combustion carbon reduction capacity optimization system based on wind and solar oxygen production, characterized in that, include: Wind and solar energy integration modules are used to convert wind and solar energy into electrical energy through wind power systems and photovoltaic systems. The power control module is used to convert the electrical energy generated by the wind and solar energy absorption module from DC to AC, and then filter it through a filter to complete the electrical energy preprocessing. The energy conversion module is used to generate oxygen from pre-treated electrical energy through a proton exchange membrane electrolyzer, and then store the oxygen in a gas storage tank. The pure oxygen combustion carbon capture module is used to connect the oxygen in the gas storage tank to a pure oxygen kiln, and to perform pure oxygen combustion on the methanated fuel gas in the pure oxygen kiln. The carbon dioxide produced after combustion is captured and separated by a carbon dioxide separation device. The differential constraint module is used to construct constraints and formulate differentiated capacity allocation strategies during the energy conversion process of wind and solar power, based on the differences in energy resource endowment and load characteristics in different regions, with the goal of minimizing total cost and using multi-year average profit as an auxiliary evaluation indicator.

2. The pure oxygen combustion carbon reduction capacity optimization system based on wind and solar oxygen production according to claim 1, characterized in that, The wind power system and photovoltaic system of the wind-solar energy integration module are used to construct a power generation model; The wind power system converts wind energy into electrical energy through a wind turbine, transmission system, and generator system, while the photovoltaic system converts solar energy into electrical energy through photovoltaic modules and combiner boxes.

3. The pure oxygen combustion carbon reduction capacity optimization system based on wind and solar oxygen production according to claim 1, characterized in that, The power control module converts the electrical energy generated by the wind and solar power integration module into DC power through an AC-DC converter, transmits it in the form of DC power, and then converts the DC power back into AC power through a DC-AC inverter before connecting it to the grid. Finally, a filter is used to remove the high-frequency harmonics generated during the conversion process, thus completing the power preprocessing.

4. The pure oxygen combustion carbon reduction capacity optimization system based on wind and solar oxygen production according to claim 1, characterized in that, The energy conversion module includes: a proton exchange membrane electrolyzer and a gas storage system; Oxygen is generated by oxidation and reduction reactions occurring at the anode and cathode of the proton exchange membrane electrolyzer, respectively, thus constructing a power output model for the proton exchange membrane electrolyzer. The oxygen produced by the proton exchange membrane electrolyzer is pre-compressed by the pre-compressor of the gas storage system, stored in the gas storage tank, and then output compressed by the post-compressor.

5. The pure oxygen combustion carbon reduction capacity optimization system based on wind and solar oxygen production according to claim 1, characterized in that, The pure oxygen combustion carbon capture module includes: a combustion system and a capture system; The combustion system includes a methane reactor and a pure oxygen kiln. The methane reactor is used to methanate the fuel gas, and the pure oxygen kiln is connected to a gas storage tank. After oxygen is introduced, the methanated fuel gas is burned in the pure oxygen kiln. The capture system condenses, compresses, and separates the carbon dioxide produced by the combustion of pure oxygen, thus completing the capture of carbon dioxide.

6. The pure oxygen combustion carbon reduction capacity optimization system based on wind and solar oxygen production according to claim 1, characterized in that, The differential constraint module uses the minimum total cost of the wind and solar energy consumption module, power control module, energy conversion module, and pure oxygen combustion carbon capture module as the objective function to configure the system capacity; and uses the profit within a preset future period to judge the economics of different schemes and select the scheme accordingly. Differentiated capacity configuration strategies are formulated based on constraints using a pre-defined optimization configuration model.

7. A method for optimizing carbon reduction capacity through pure oxygen combustion based on wind and solar oxygen production, characterized in that, The method includes: Converting wind and solar energy into electrical energy through wind power systems and photovoltaic systems; The electrical energy generated by the wind and solar energy absorption module is converted from DC to AC and filtered by a filter to complete the electrical energy preprocessing. The pretreated electrical energy is used to generate oxygen through a proton exchange membrane electrolyzer, and the oxygen is stored in a gas storage tank. By introducing oxygen from the gas storage tank into a pure oxygen kiln, the methanated fuel gas is combusted in pure oxygen in the pure oxygen kiln, and the carbon dioxide produced after combustion is captured and separated by a carbon dioxide separation device. In the process of wind and solar energy conversion, based on the differences in energy resource endowment and load characteristics in different regions, with the goal of minimizing total cost and using multi-year average profit as an auxiliary evaluation indicator, constraints are constructed and differentiated capacity allocation strategies are formulated.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the carbon reduction capacity optimization method for pure oxygen combustion based on wind and solar oxygen generation as described in claim 7.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the carbon reduction capacity optimization method for pure oxygen combustion based on wind and solar oxygen production as described in claim 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the carbon reduction capacity optimization method for pure oxygen combustion based on wind and solar oxygen production as described in claim 7.

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