415 results about "Low-carbon emission" patented technology

The invention relates to an electricity-carbon cooperative scheduling optimization method and device for a low-carbon park integrated energy system, and the method comprises the steps: carrying out the cooperative prediction of a multi-state parameter through employing a panoramic situation deduction model, and generating a panoramic dynamic situation scene set; establishing an electricity-carbon cooperative scheduling model considering a carbon transaction mechanism, and deeply embedding the real-time carbon cost into a target function to carry out Pareto optimization of economic cost and carbon emission cost; an electricity-carbon cooperative scheduling model is converted into a standard mixed integer linear programming model, a situation deduction-day-ahead optimization-rolling correction hierarchical calculation framework is adopted to decompose a cooperative scheduling optimization problem to different time scales for decision making, and a global optimization plan is made on the day-ahead layer based on a panoramic dynamic situation. Deviation is corrected on line through rolling optimization in the intraday layer; and the integrated energy system executes the corrected scheduling plan. Compared with the prior art, the method has the advantages that the consumption rate of renewable energy sources can be remarkably increased and carbon emission can be effectively reduced while the operation economy of the system is ensured.

The invention discloses a cementing material for a solid waste-based road of a coal-fired power plant and a preparation method of the cementing material. The cementing material mainly comprises a cementing component, an alkali-activated component and a reinforcing component, the gelling component is a mixture of coal-fired power plant fly ash and furnace slag; the alkali-activated component is a mixture of alkali residues, red mud, blast furnace slag and coal-fired power plant desulfurized gypsum; the reinforcing component is rice hull ash or peanut hull ash. The mass ratio of the gelling component to the alkali-activated component is (4 / 1)-(10 / 1); and the addition amount of the reinforcing component is 1-3% of that of the main body material. The coal-fired power plant solid waste fly ash, the furnace slag and the desulfurized gypsum are used as main bodies, a small amount of other industrial solid waste is added, and the cementing material belongs to a full-solid-waste low-carbon cementing material and can be applied to a road base, a subbase or a base layer. The invention has the characteristics of low carbon emission, high solid waste consumption, simple production process and strong pavement performance, and in addition, the invention has a good stabilization effect on the problem that part of solid waste heavy metals and sulfate ions in a coal-fired power plant exceed the standard.

The invention discloses a high-content steel slag-based functionalized nano-composite cementing material and a preparation method thereof, and belongs to the technical field of solid waste resource comprehensive utilization. The nano composite cementing material is prepared from the following raw materials in parts by mass: 50 to 65 parts of steel slag, 10 to 20 parts of fly ash, 10 to 25 parts of carbide slag, 8 to 15 parts of desulfurized gypsum, 0.3 to 1.0 part of nano silicon dioxide and 0.003 to 0.03 part of silane coupling agent. On the basis of a solid waste synergism theory and an internal alkali excitation effect, quaternary solid wastes such as steel slag and fly ash are optimized and compounded by adopting methods of mechanical-thermal activation, addition of modified nano silicon dioxide, synergistic gelling between solid wastes and the like; the paint is prepared through gradient grinding and a medium-temperature wet curing process. The preparation method is simple, high-temperature calcination is not needed, cement clinker and exogenous excitant do not need to be added, the obtained cementing material can replace part of cement to be applied to the fields of road bases, mine filling, low-carbon building material products and the like, resource utilization and high-value utilization of regional bulk industrial solid waste can be achieved, and carbon emission and production cost are effectively reduced.

The invention belongs to the technical field of novel power system photovoltaic and energy storage system optimization configuration, and discloses an optical storage system optimization method based on carbon emission and line loss rate collaborative modeling, which comprises the following steps: constructing a double-layer planning structure of an upper layer planning model and a lower layer operation model, a carbon emission calculation model and an improved line loss rate calculation model are introduced into the lower layer, joint optimization of configuration and operation is realized through parameter coupling, and the charge and discharge efficiency loss power consumption of the energy storage device is introduced as an independent parameter in line loss rate calculation, so that the line loss calculation precision is improved; and solving by adopting an improved particle swarm optimization algorithm, and objectively sorting candidate schemes in combination with an information entropy method and a TOPSIS comprehensive evaluation method. A simulation result based on an IEEE33 node power distribution system shows that the model can effectively reduce carbon emission and line loss rate, improves node voltage level, and has good convergence and engineering applicability.

The invention discloses a low-carbon path real-time planning method and system based on multi-source data fusion and reinforcement learning. According to the invention, through a dynamic weight self-adjustment mechanism, the real-time adaptation capability of low-carbon path planning is significantly improved. Meanwhile, scenes such as traffic flow abrupt change, carbon price abnormity and energy station high load are recognized in real time through high-frequency scanning of multi-source fusion data, weights are dynamically adjusted through a formula, and planning can quickly respond to emergencies. For example, energy weight is reduced during charging pile queuing, emission constraint is enhanced when carbon price rises, planning lag caused by weight fixing in a traditional method is avoided, path selection better fits current environment changes, the problems of congestion and energy supplement shortage can be solved more timely in actual use, emission, time and cost are more accurately balanced under low-carbon constraint, and the method is suitable for popularization and application. In practical application, carbon emission can be effectively reduced, and user time and energy expenditure are saved.

The invention relates to a digital intelligent regulation and control preparation method and system for a high-solid-waste low-carbon high-performance grouting material, and solves the problems that a traditional preparation technology lacks an autonomous and controllable digital intelligent regulation and control system and is weak in adaptability to fluctuation of raw materials, and the method comprises the following steps: obtaining XRF chemical components and XRD mineral composition data of industrial solid waste raw materials; constructing a material gene database; based on the database, screening a proportioning scheme by using a performance prediction model, and predicting workability, strength development and shrinkage performance; inputting a prediction result as a fitness function into a multi-objective optimization algorithm, and outputting an optimal material gene combination; a batching scheme is generated based on the optimal combination, and a stirring process is started after technological parameters are preset; collecting data through a real-time monitoring system, and comparing the data with the digital twin model; and based on a comparison result, automatically adjusting material proportioning parameters. The high-solid-waste, low-carbon and high-performance grouting material has the advantages that accurate design and regulation of the high-solid-waste, low-carbon and high-performance grouting material are achieved, material performance is improved, and carbon emission and cost are reduced.

The invention relates to a building engineering green low-carbon construction evaluation and decision support system, in particular to the field of building engineering, and aims to construct a space-time atlas to comprehensively characterize a construction process by integrating an Internet of Things sensor, a building information model and meteorological data, and accurately estimate a future carbon emission trend by using a dynamic prediction mechanism. And key influence factors and contribution degrees thereof are identified through factor analysis, and finally real-time optimization suggestions are provided by virtue of a visual interface, so that scientific decision support for green low-carbon construction is realized, carbon emission is effectively reduced, the resource utilization efficiency is improved, and the environmental sustainability of constructional engineering is promoted.

The invention belongs to the technical field of ironmaking and steelmaking, and particularly discloses a direct reduction iron production process and system of variable feed gas. The production process comprises the following steps: under a basic working condition, a hydrogen-rich working condition or an all-hydrogen working condition, introducing high-temperature reducing gas into a shaft furnace to produce the direct reduced iron; the production system comprises a shaft furnace, a self-heating modification device, an upgrading device, a heating furnace and a preheating furnace, and is provided with three hydrogen supplementing points and two hydrogenation points. By changing the structure of the raw material gas, supplementing hydrogen at three positions or supplementing or adding hydrogen at at least one of two hydrogenation points, increasing the H2 content of the reducing gas at the inlet of the shaft furnace and the like, the carbon emission, the process energy consumption and the pellet reduction difficulty are reduced.

The invention relates to the technical field of power distribution network dispatching, in particular to a power distribution network dispatching optimization method and device. Constructing a dynamic digital twin of the power distribution network to be dispatched, and reversely correcting a line impedance parameter and an equipment efficiency coefficient in combination with a twin simulation result; multiple scheduling strategies are rehearsed in parallel, and the optimal scheduling strategy is selected through weighted scoring; generating a multi-energy flow collaborative scheduling instruction set according to the optimal scheduling strategy; dynamically distributing a control task by utilizing an edge node; and performing differentiated load response in combination with the power consumption behavior classification of the user. Space-time synchronous acquisition of electricity-heat-gas data is realized by deploying a multi-energy-flow sensor group, a multi-energy-flow collaborative scheduling instruction is generated by combining reverse parameter correction and scene rehearsal optimization of a dynamic digital twin, and dynamic resource allocation is realized based on an edge node dynamic allocation control task and load classification response. The new energy consumption rate capability is obviously improved, and the carbon emission intensity is reduced.

The invention belongs to the technical field of energy management and power system optimization, and particularly discloses a port microgrid optimization scheduling method, device and equipment, a storage medium and a product. According to the application, the microgrid operation optimization model is constructed according to the predicted load demand, the predicted wind power generation power and the predicted solar power generation power; solving a target scheduling strategy according to the power grid operation optimization model and the multi-dimensional microgrid operation constraint conditions; and performing optimal scheduling on the port microgrid according to the target scheduling strategy. Through the above mode, comprehensive optimization of microgrid operation is realized by using the microgrid operation optimization model on the basis of considering the operation cost and the environment cost, the operation stability is ensured according to the multi-dimensional microgrid operation constraint condition, and then optimization scheduling is performed on the port microgrid according to the target scheduling strategy. Therefore, the accuracy of dispatching the port micro-grid can be effectively improved, the operation economy and the energy utilization efficiency of the micro-grid are improved, and carbon emission is reduced.

The invention provides a wind and light storage micro-grid optimization scheduling method and system containing small hydropower storage, and the method comprises the steps: obtaining historical operation data, and carrying out the prediction according to the historical operation data, and obtaining a full-dimension prediction data set; according to the full-dimension prediction data set, constructing a multi-objective optimization model with the goal of minimizing residual load, minimizing power abandoning cost, minimizing cascade water abandoning amount, maximizing green energy collaborative utilization efficiency and minimizing time weighted voltage-power comprehensive error; and solving the multi-objective optimization model by adopting a hybrid optimization algorithm fused by a Hanniac optimization algorithm and an improved sparrow search algorithm to obtain a final output. According to the invention, efficient consumption of green energy can be realized, the electricity abandoning phenomenon is reduced, carbon emission is reduced, and the stability, economical efficiency and environmental protection property of a power system are improved.

The invention discloses a layered, zoned and differentiated CO2 injection system and method for a blast furnace, and belongs to the technical field of ferrous metallurgy low carbon. The system comprises a CO2 supply and distribution system, a tuyere area injection module, a furnace body middle-lower part injection module and a furnace body upper part injection module. And according to the temperature gradient and atmosphere layering characteristics in the blast furnace, a differential CO2 distribution proportion and a collaborative thermal compensation strategy are adopted. An oxygen-CH4 synergistic injection device is arranged in a tuyere area, and rapid conversion of CO2 is promoted by using a high-temperature strong reducing atmosphere; a biomass charcoal synergistic injection device and an angle-adjustable nozzle are arranged at the middle lower part of the furnace body, so that efficient gasification reaction is realized; and low-concentration CO2 mixed injection is adopted at the upper part of the furnace body, so that indirect reduction reaction is promoted. According to the invention, the CO2 conversion rate is 65-80%, the coke ratio is reduced by 15-25%, the consumption of CO2 per ton of iron is 260-90Nm < 3 >, the carbon emission is obviously reduced, and the ironmaking efficiency is improved.

The invention discloses a park-level multi-energy system scheduling method and device considering carbon emission, and belongs to the field of power systems, and the method comprises the steps: building a topology model comprising a carbon capture node, an energy node, a line, a pipe network and a data collection device according to a park-level multi-energy system; acquiring operation data according to a scheduling period and calculating a carbon intensity set in combination with the predicted load; constructing a target function by taking the minimization of the total operation cost as a target, and constructing a safe operation constraint and a carbon flow accounting constraint in combination with the operation data, the carbon intensity set and the topological relation; and establishing a comprehensive optimization model, solving and determining a next round of scheduling scheme by adopting a particle swarm optimization algorithm and a hierarchical collaborative strategy, and controlling operation. Therefore, by implementing the method and the system, the problem that the scheduling cost of the park-level multi-energy system is difficult to reduce while low-carbon emission is guaranteed in the prior art can be solved.

An electricity-carbon-green certificate market transaction method based on chaotic mapping considering carbon capturing, comprising: building a transaction strategy for describing the interaction of the market entities in a multi-element market, the multi-element market comprises an electricity market, a carbon market and a green certificate market; and building an upper-layer electricity-carbon-green certificate multi-market combined transaction model considering carbon emission settlement based on the transaction strategy. With the method proposed in the present invention, the model is built according to the energy transaction flow existing in among the transaction entities, efficient utilization of renewable energies and low carbon emissions can be realized, national requirement on low carbonization of market transaction can be satisfied, and a multi-element market transaction mechanism that complies with the dual-carbon target is provided for the existing energy transaction market.

The invention provides an intelligent integrated control system for waste heat recovery of a swimming pool heat pump and domestic hot water. The system comprises a data acquisition module, an energy efficiency evaluation and recovery decision module, an intelligent scheduling execution module and a heating mode optimization module. The waste heat availability is dynamically evaluated by monitoring heat pump operation parameters and the water tank thermal stratification state in real time, the system stability is judged in combination with the heat pump energy efficiency change trend and the water tank top temperature acceleration, and a three-way valve is intelligently controlled to switch a waste heat preheating path. In the waste heat recovery state, the waste heat participation degree is determined based on the temperature difference and flow of the plate heat exchanger, the main heating power is adjusted by combining the up-down temperature difference and the top temperature change trend of the water tank, and efficient, stable and energy-saving domestic hot water supply is achieved. The energy comprehensive utilization efficiency is remarkably improved, carbon emission is reduced, and the system is suitable for green buildings and smart energy scenes.

The invention discloses a method, a device, equipment and a medium for acquiring a carbon emission inversion model. The method comprises the following steps: generating a training sample according to a sample remote sensing image corresponding to a preset sample scene and sample carbon emission intensity corresponding to the sample remote sensing image; training a preset first convolutional neural network model by using the training sample to obtain a remote sensing inversion teacher model; obtaining an intermediate feature tensor corresponding to the remote sensing inversion teacher model; and performing iterative training on a preset initial student model by using the sample remote sensing image, and performing knowledge distillation and parameter pruning by using the intermediate feature tensor in the training process until a carbon emission inversion model is obtained. Therefore, on the basis of the original remote sensing inversion teacher model, knowledge distillation and parameter pruning are performed by using the intermediate feature tensor corresponding to the remote sensing inversion teacher model until the carbon emission inversion model is obtained, so that resource occupation of the carbon emission inversion model is reduced while the performance of the carbon emission inversion model is not reduced.

The invention discloses a civil aviation element configuration optimization method based on mixed integer dynamic programming. The method comprises the following steps: S1, constructing a Chinese civil aviation core element and carbon emission spatial-temporal characteristic database; s2, establishing a mixed integer dynamic programming model with the purpose of minimizing the total cost of the system in the programming period; and S3, establishing decision variables, constraint conditions and a fusion solution algorithm framework required by the mixed integer dynamic programming model. And S4, based on the fusion solution algorithm framework, solving the mixed integer dynamic programming model by using a mathematical programming solver integrated with a robust optimization module so as to obtain a civil aviation core element dynamic configuration scheme which is optimal in total system cost in multiple periods in the future and meets the uncertainty scene. According to the method provided by the invention, a multi-source data fusion algorithm is optimized, a carbon emission measuring and calculating method is deepened, and solver parameters are adjusted, so that the collaborative requirements of improving the operation efficiency and reducing the carbon emission from the perspective of carbon cost are met.

The invention discloses a park dynamic carbon portrait generation method and system, and the method comprises the steps: collecting building, equipment and traffic multi-source energy consumption data in real time through Internet of Things equipment, and calculating the carbon emission intensity in combination with a dynamic carbon emission factor library; constructing a three-dimensional park model, mapping the carbon emission data into a dynamic thermodynamic diagram layer according to a spatial hierarchical structure (park-building-floor-equipment), and synchronously generating a vehicle carbon emission intensity diagram; positioning a key emission source based on the energy flow-carbon flow mulberry-based graph, setting a grading early warning threshold value, and triggering a three-dimensional highlight alarm and carbon reduction strategy suggestion; an optimization algorithm is adopted to generate a multi-energy cooperative regulation and control instruction, and the instruction is pushed to the energy management system for execution; and closed-loop verification and iterative optimization are realized by monitoring emission reduction, economic benefits and carbon potential indexes. The space-time dynamic visualization of carbon emission, key source intelligent positioning and adaptive optimization closed loop are realized, the problems of lack of real-time performance and low traceability precision of park carbon management are solved, and the carbon emission intensity is reduced through actual measurement.

An example operation includes comparing a first set of driving styles for a vehicle to a second set of driving styles for one or more similar vehicles in a geographic area over a period, wherein the first set of driving styles affects a carbon footprint of the vehicle and the second set of driving styles affects another carbon footprint of the one or more similar vehicles; determining a carbon credit when the carbon footprint of the vehicle is lower than the another carbon footprint of the one or more similar vehicles, by a threshold, based on the comparing; and applying the carbon credit to the vehicle.

The invention relates to the technical field of flue gas treatment and waste heat utilization in the non-ferrous metal smelting process, and discloses a multi-kiln flue gas multi-target collaborative intelligent dynamic allocation method and system.The method comprises the steps that original data are collected in real time, and a multi-source flue gas time sequence data set is generated through processing; establishing a multi-furnace flue gas mixing mechanism model, and fusing the data driving model to carry out deviation correction to form a prediction model; and a comprehensive multi-objective optimization function is constructed, safety constraint conditions are defined, the opening degree of each baffle, the rotating speed of an induced draft fan and the optimal set value of a flow dividing valve are calculated in real time through a prediction model prediction control algorithm, and dynamic allocation of stable acid making inlet flue gas parameters and efficient waste heat recovery is achieved. The system comprises a data preprocessing module, a prediction model construction module and a constraint condition construction module. Efficient, stable and low-carbon emission of the smelting flue gas is achieved, and the energy utilization efficiency and production benefits of the whole metallurgical process are improved.

The invention discloses a method for efficiently extracting iron from copper slag through non-molten hydrogen reduction, and belongs to the technical field of green resource utilization of metallurgical solid waste. Hydrogen is introduced to carry out reduction roasting on copper slag pellets, and a reduction auxiliary is added in a matched mode to dissociate fayalite in the copper slag; the purposes of strengthening the hydrogen reduction effect and improving the metal iron reduction rate are achieved, magnetite, fayalite and iron elements in other iron-containing silicate phases in the copper slag are reduced into metal iron, meanwhile, reduction products are treated through ore grinding and magnetic separation, and the iron ore concentrate grade is effectively improved. The method has the characteristics of simple reduction process and low carbon emission, and has high economic benefits.

The invention discloses a data center combined cooling heating and power supply system based on mixed hydrogen energy and a control method thereof, and the system comprises a hydrogen source supply and storage module which is used for inputting hydrogen for power generation, a power generation and energy supply module which is used for converting the hydrogen into electric energy, and a DC micro-grid module which is used for providing the electric energy for a data center. The heat management and application module is used for recycling and applying heat generated during power generation, and the control and protection module is used for controlling the modules. According to the invention, hydrogen energy efficient power generation, waste heat cascade recovery and intelligent scheduling are realized through modular cooperation, the problems of high carbon emission, response delay and energy waste in the prior art are solved, and the system has the advantages of significantly reducing carbon emission, optimizing electric energy use efficiency, improving power supply continuity and energy utilization rate, and simultaneously realizing combined supply of cooling, heating and power.

This invention belongs to the field of peak-shaving technology for thermal power units, specifically a deep peak-shaving method for thermal power units that combines electrolytic hydrogen production with ammonia synthesis and energy storage. It integrates an electrolytic hydrogen production with ammonia synthesis and energy storage system, an energy comprehensive utilization system, and a collaborative control system to form a closed-loop peak-shaving system: during off-peak periods, excess electricity from the thermal power unit is collected; during peak periods, the stored ammonia is used to supplement the unit's energy through coal-ammonia co-firing, while oxygen is utilized for oxygen-enriched combustion to enhance peak-shaving and stable combustion capabilities. The synthesized ammonia can also replace purchased ammonia for flue gas denitrification. Through the collaborative control system, the operation of each link is coordinated, achieving efficient energy conversion and precise control. This invention significantly improves the deep peak-shaving and peak-response capabilities of thermal power units, substantially reduces carbon and pollutant emissions, optimizes energy utilization efficiency, extends equipment lifespan, and provides strong support for the green transformation of coal-fired power and the stable operation of new power systems.

The application discloses a method for producing gapless atomic steel by adopting a full scrap steel+electric arc furnace process, and comprises scrap steel proportioning, electric arc furnace steelmaking, LF refining, RH refining and slab continuous casting. The short process technology realizes industrialized batch production of high-grade, low-carbon emission gapless atomic steel with C≤0.0025%, N≤0.005% and O≤0.004%. The finished product has good strength and forming performance, solves the technical problems of producing ultra-low-carbon steel and ultra-low-nitrogen steel by the electric arc furnace, fills the technical blank in the field, and greatly reduces the carbon emission in the production process of the gapless atomic steel compared with the conventional long-process smelting method of the blast furnace+converter, and has obvious environmental benefits.

The invention discloses a low-carbon path optimization method and device for a sustainable aviation fuel supply chain network, equipment and a storage medium. The method comprises the steps that spatial distribution information and carbon emission factors of related objects of the sustainable aviation fuel supply chain network are acquired; clustering based on biomass raw material yield distribution by adopting a yield weighted clustering method, determining the initial position of the biomass raw material collection station, and determining the final position of the biomass raw material collection station based on the initial position and the railway buffer area; constructing a sustainable aviation fuel supply chain network; and constructing a carbon emission model of the sustainable aviation fuel supply chain network on the basis of the sustainable aviation fuel supply chain network, and performing optimization solution on the carbon emission model to obtain an optimal low-carbon path scheme of the sustainable aviation fuel supply chain network. Therefore, a reasonable low-carbon path scheme can be provided, and carbon emission can be further reduced.

The application discloses a kind of fluorite tailing material fatigue-resistant water-stable base and preparation method thereof.Belongs to the technical field of solid waste utilization.Preparation of the fluorite tailing material fatigue-resistant water-stable base aggregate ratio is as follows: gravel, river sand, fluorite tailing material and tap water quality ratio is as follows: 55-65 wt%, 30-35 wt%, 5-10 wt% and 40-45 wt% tap water.In the application, fluorite tailings are used as raw materials for building materials, which is a reasonable way of resource utilization, and is also an inevitable demand for promoting ecological protection and high-quality development in the Yellow River Basin.Compared with traditional natural materials, it can also reduce carbon emissions and production energy consumption.When applied to water-stable base, it improves its fatigue resistance, prolongs the service life of water-stable base and improves economic efficiency.

The application provides a low-carbon multimodal transport network design method considering consignor path selection, comprising: obtaining freight demand data, multimodal transport network topology, parameters of each transport mode, network node transfer time and cost; obtaining consignor preference data covering all origin-destination points in the planning period, brand effect, utility coefficient of transport time and transport cost, low-carbon subsidy data; based on the obtained data, constructing freight flow batch transport constraints, low-carbon subsidy constraints, consignor path selection constraints and multimodal transport network constraints respectively; establishing an objective function for the purpose of pursuing lower carbon emission cost on the premise of not paying a large amount of low-carbon subsidies; under the constraints, using a particle swarm optimization algorithm embedded with CPLEX to solve the objective function to obtain a low-carbon multimodal transport network design scheme. The method can accurately depict the consignor path selection behavior and realize the dual improvement of transport efficiency and environmental benefit.

The invention discloses a method for deeply recovering phosphorus and vanadium from molten iron containing phosphorus and vanadium, which comprises the following steps: treating the molten iron containing phosphorus and vanadium by adopting an oxygen blowing method, in the oxygen blowing method, directly blowing mixed gas into the molten iron by utilizing a spray gun, the volume concentration of the oxidizing gas is 18%-50%. The method has the advantages of improving the recovery rate of phosphorus and vanadium, reducing the smoke amount and the like, and also has the characteristics of low cost, short process, environmental friendliness, less carbon emission, high heat utilization rate, full utilization of resources and the like.

This invention discloses a short-process bar rolling method and system. The method includes the following steps: S1, heating the billet in a heating furnace; S2, descaling with high-pressure water; S3, completing eight rolling passes in rolling zone one; S4, performing multiple-length segmentation with a first flying shear; S5, performing four rolling passes in rolling zone two; S6, performing multiple-length segmentation with a second flying shear; S7, performing diameter reduction rolling on the bar using a KOCKS mill; S8, a third flying shear; S9, water cooling; S10, cooling; S11, shearing the bar to length; S12, finishing and annealing; S13, magnetic flux leakage testing. This invention can meet the requirements for bar shape and size as well as the requirements for flaw detection, achieving integrated bar heating, controlled rolling and cooling, and flaw detection while saving space. This invention can reduce the number of traditional bar rolling passes, realizing short-process bar production with small space requirements, low power consumption, customization, greenness, and low carbon emissions.

The invention relates to a biomass natural gas coupled SOEC hydrogen production and methanol production system, which is characterized in that a biomass natural gas device is arranged, agricultural straws and livestock and poultry manure are used as core raw materials, urban and rural garbage and industrial organic waste liquid are synergistically absorbed, and the gas production efficiency is improved through a mixed fermentation and pretreatment technology; the separation device is communicated with a methane storage device to realize treatment of biomass natural gas and methane storage; the electrolysis device is communicated with the methane storage device, and the compression device and the methanol synthesis device are sequentially communicated to construct a process that methane participates in electrolysis and subsequent methanol synthesis. According to the structure, organic waste is treated through anaerobic fermentation of biomass natural gas, direct emission of greenhouse gas such as methane is reduced, fossil energy is replaced, carbon emission is reduced, waste such as straw is digested, and environmental pollution is avoided; the problems of high carbon emission, hydrogen-carbon ratio defect and low utilization rate of hydrogen production equipment are solved.