13 results about "Steam coal" patented technology

The invention discloses an intelligent coal blending method and system for dual-engine staged solution in a power coal scene. The method comprises the following steps: performing structured processing on coal source data and establishing a hundred-ton integer batch variable; the method comprises the following steps of: constructing a hard constraint integer programming (ILP) model, and sequentially executing three stages of solving of cost minimization, heat value deviation minimization under the fixed cost and coal source quantity minimization under the fixed cost and deviation; when any stage is not feasible, automatically switching to a soft constraint target planning (GP) model, performing soft constraint on the coal quality index through a deviation variable, and sequentially performing deviation minimization, cost minimization and coal source quantity minimization; and calculating a combustion stability index (CSI) on the basis of volatile component fluctuation, fixed carbon, ash content change and sulfur content change, and carrying out stability verification on a final coal blending scheme. The system comprises a data management module, a first engine module, a second engine module, an automatic rollback module, a combustion stability index module and a result output module.

The invention discloses a multi-stage separation synergistic power coal washing process, and belongs to the technical field of coal washing processing. The TDS intelligent dry separation system, the dry-wet combined desliming process, the super coal slime classification cyclone, the super coal slime dense medium cyclone and the ultrahigh-pressure elastic squeezing filter press are in multi-stage cooperative linkage to be used for power coal washing, the moisture content and the ash content are reduced to the maximum extent in the separation stage, and the heat productivity of the power coal is increased. Compared with a process before improvement, the power coal washing process with cooperation of multi-stage separation has the advantages that the gangue sorting efficiency and the power coal productivity are improved, the super coal slime dense medium cyclone, the super classification cyclone and the ultrahigh-pressure elastic squeezing filter press are orderly used in the power coal washing process, the water content of a filter cake is greatly reduced, and the water content of the filter cake is greatly reduced. The water content of the filter cake is obviously superior to that of a common quick-opening membrane filter press and is lower than that of the filter cake of dried coal slime, so that the fluctuation range of the heat value of the power coal is lower, the heat value of gangue is reduced, and the heat value of the power coal is improved.

This invention provides a method for preparing graphene quantum dots based on thermal coal and a plasma reaction system, belonging to the field of graphene quantum dot preparation technology. The method includes the following steps: using thermal coal as raw material, it undergoes electrochemical oxidation and KOH ball milling sequentially to obtain pretreated coal; the pretreated coal is introduced into an axial magnetic rotating microwave plasma reactor for segmented temperature-controlled dissociation and recombination reactions; during the reaction, a porous alumina template is used for confined growth, and after the reaction, liquid nitrogen quenching is employed to obtain graphene quantum dots. This invention uses thermal coal to replace high-purity graphite as the carbon source, reducing raw material costs by more than 99%; the pretreatment process, through the synergistic effect of electrochemical oxidation and KOH ball milling, eliminates the need for strong acids and alkalis throughout, completely avoiding the pollution problems of large amounts of acidic and heavy metal-containing wastewater and waste gas generated by the traditional Hummers method, thus aligning with the concepts of green chemistry and sustainable development.

The invention discloses clean processing and upgrading equipment for power coal, belongs to the technical field of advanced green coal dressing, and is used for solving at least one of the problems of poor separation effect, small separation particle size range and low separation precision of fine-grained and viscous and humidified power coal in the prior art. According to the system, an oversize outlet of a first-stage classifying screen is connected with a feeding port of an X-ray sorting unit, discharging ports of the X-ray sorting unit are divided into a first-stage clean coal discharging port and a first-stage gangue discharging port, and the first-stage clean coal discharging port is connected with a feeding port of a second-stage classifying screen through a crushing unit; an undersize outlet of the first-stage classifying screen is connected with a feeding port of the second-stage classifying screen, an oversize outlet of the second-stage classifying screen is connected with a feeding port of the dry-method sorting unit, discharging ports of the dry-method sorting unit are a second-stage clean coal discharging port and a second-stage gangue discharging port respectively, and an undersize outlet of the second-stage classifying screen is connected with the low-temperature steam drying unit. The method can be used for clean processing and upgrading of the power coal.

The invention discloses a coking coal preparation method for improving selectability of extremely-difficult-to-separate coal through mixed washing, and belongs to the technical field of coal washing and processing. The method comprises the following steps: firstly, carrying out a floating and sinking test on target extremely-difficult-to-separate coal and generating a continuous density-yield distribution function; then, by taking a density distribution complementation degree index as a compatibility criterion, quantitatively screening compatible coal types which are complementary with the target coal in density defect in the separation key density interval from the candidate coal types; determining an optimal ratio for maximizing the target ash content yield under the coking performance constraints that the clean coal caking index is not less than 80 and the gelatinous layer thickness is not less than 16.5 mm; and feeding the mixed coal into a dense medium cyclone for separation, and synchronously optimizing the stability of the suspension and a slime water system. According to the method, the overall density distribution curve of the mixed raw coal is remarkably improved, the yield of the clean coal is increased by 12-18%, finally qualified coking clean coal is produced, and conversion of the extremely difficult separation coal from low-value power coal to high-value coking coal is achieved.

The utility model discloses a coal preparation device for a power coal preparation plant, which relates to the technical field of coal screening, and comprises an equipment base, a movable shaft is rotatably mounted on the equipment base, a screening cylinder is fixedly mounted on the movable shaft, a separation outlet is arranged below the screening cylinder, a cleaning mechanism is arranged above the screening cylinder, and the cleaning mechanism is arranged above the screening cylinder. The cleaning mechanism comprises a fixing support fixedly installed on the equipment base, a driving shaft is rotationally installed on the fixing support, one end of the driving shaft is connected with a driving motor, a cleaning brush and a spring are fixedly installed on the driving shaft, a knocking hammer is fixedly installed at the tail end of the spring, and a spraying mechanism is arranged above the fixing support. A movable hole is formed in the fixing support, and a first clamping sleeve is fixedly installed on the driving shaft. According to the coal preparation device for the power coal preparation plant, the cleaning mechanism is used for rapidly cleaning the blocked screening cylinder, and the spraying mechanism can be used for treating dust generated by cleaning.

This invention discloses a method for training and optimizing a large-scale model in the thermal coal industry based on knowledge distillation, belonging to the field of large-scale model training and optimization technology. The method includes the following steps: collecting and preprocessing multimodal industry data to obtain a data matrix; inputting the data into a teacher's visual Transformer network to generate a sparse probability label matrix; constructing an improved TinyViT student network; embedding multiple optimization units in self-attention blocks; completing weight initialization; performing pre-training distillation to generate a composite distillation signal; inputting the signal into the student network for fine-tuning training to obtain a set of fine-tuned student weights; performing dynamic weighted training on hard samples; optimizing the training effect on long-tailed samples; and obtaining a lightweight model through quantized perceptual training and channel pruning. The model is then deployed to edge computing nodes for real-time inference. This invention improves the training efficiency of large-scale models in the thermal coal industry while optimizing the model's inference speed and accuracy, and can be effectively deployed in edge computing environments.

The application provides a coal power adjustable capacity prediction method. The method comprises the following steps: establishing a prediction scene set of typical power coal variety prices to obtain predicted prices of the typical power coal varieties; establishing an objective function of minimizing the coal blending and burning power generation cost, and establishing a coal blending optimization model according to the power coal consumption constraint, the boiler calorific value, the boiler ash content and the boiler sulfur content constraint, solving the coal blending optimization model to obtain an optimal coal blending strategy; establishing a linear regression model of the blocked capacity of the coal power unit during the peak output period and the power coal quality according to the historical data of the adjustable capacity and the power coal quality of the coal power unit in the power system during the peak output period; predicting the corresponding blocked capacity through the linear regression model; calculating the coal power adjustable capacity of each coal power unit in the power system to obtain the adjustable capacity coefficient of the power system, and evaluating the coal power generation capacity according to the adjustable capacity coefficient.

The invention discloses a combined heat and power generation unit load distribution prediction and optimization method, and the method comprises the following steps: S1, obtaining the historical data of a combined heat and power generation unit, carrying out the grouping of two working conditions: medium-pressure air exhaust and low-pressure air exhaust, carrying out the feature extraction through the combination of a Spearman rank correlation coefficient and mutual information, and carrying out the prediction of the load distribution of the combined heat and power generation unit; removing redundant features and low correlation features to obtain a target data set for model training; s2, constructing a TCN-ECA-BiLSTM prediction model, wherein the TCN-ECA-BiLSTM prediction model comprises a time sequence convolutional network layer, an efficient channel attention layer and a bidirectional long and short term memory network layer; according to the method, a TCN-ECA-BiLSTM prediction model and a TD3 reinforcement learning algorithm model are combined to form a prediction and optimization integrated framework, key feature reinforcement of the TCN-ECA-BiLSTM prediction model is matched with bidirectional sequence modeling advantages to reinforce prediction input after feature extraction, and the TD3 reinforcement learning algorithm model carries out distribution by considering a steam coal consumption rate and a power generation steam consumption rate. And real-time and reliable dynamic optimization is realized.

The invention discloses a high-temperature steam in-situ coal leaching hydrogen production and waste residue in-situ metal mining method, and belongs to the technical field of coal underground in-situ hydrogen production and resource comprehensive utilization. The method comprises the following steps: firstly, injecting high-temperature and high-pressure steam into a target coal seam through a ground or underground drill hole, enabling the steam to seep in a coal seam fracture network subjected to fracturing transformation by utilizing pumping and injecting pressure difference, and carrying out pyrolysis and gasification reaction with coal to generate a combustible gas-liquid mixture taking hydrogen as a main component; after the product is extracted and separated, hydrogen and other resources are recycled, and coke is retained in underground supporting overburden strata. And then, according to the porous waste residue ore deposit rich in metal formed after gasification, adaptive in-situ leaching liquid is injected through original or newly-arranged drill holes, and valuable metal in the porous waste residue ore deposit is dissolved and recycled. According to the invention, direct ignition and oxygen injection combustion of traditional underground gasification are avoided, the problems of easy flameout, unstable gas production, low heat value and the like are solved, and meanwhile, clean hydrogen production of coal and green collaborative mining of associated metal resources are realized.

The invention relates to an efficient power generation method for a heat recovery coke oven adopting power coal, which comprises the following steps: 1) taking the power coal as a coal charge, tamping and forming the coal charge into a coal cake, and forming grooves in the surface of the coal cake and / or forming holes in the coal cake; (2) increasing the air supply amount of the carbonization chamber, so that the coal gas generated after dry distillation is completely combusted, and meanwhile, the raw material coal and dry distillation coke in the carbonization chamber are combusted; finally, only residual ash and part of residual carbon in the coke oven are subjected to heat recovery; and 4) controlling the temperature of the discharged high-temperature flue gas to be between 1250 DEG C and 1350 DEG C, and introducing the high-temperature flue gas into the waste heat boiler to generate high-pressure steam for driving a steam turbine generator unit to generate electricity. According to the invention, sufficient combustion of the dry distillation product of the coal as fired and the fixed fuel is realized, and the purposes that the heat recovery coke oven adopts the power coal to generate electricity and the generating capacity is greatly increased are achieved.

This invention discloses an optimized scheduling method for a power system incorporating biomass indirect co-firing units, belonging to the field of power system optimization. The method includes: establishing a power system scheduling model with the objective function of minimizing the sum of power generation cost, coal-fired unit start-up cost, carbon trading cost, and curtailment penalty; and using the following optimization variables: the quality of thermal coal input to the boiler of each coal-fired unit at each time, the quality of biomass input to the pyrolysis furnace of each coal-fired unit at each time, the start-up status of each coal-fired unit, the net carbon dioxide emissions of each coal-fired unit at each time, and the renewable energy curtailment of each renewable energy unit at each time. The optimized scheduling plan is obtained by solving the power system scheduling model under preset constraints. These preset constraints include the operational constraints of the pyrolysis furnace, boiler, and turbine within the coal-fired units. This invention can simultaneously improve the renewable energy absorption capacity and reduce carbon emissions while satisfying the operational constraints of the pyrolysis furnace, boiler, and turbine within the coal-fired units.

This invention discloses a coal resource allocation calculation model and method in the field of coal resource planning and allocation, aiming to solve the technical problems of inaccurate coal resource allocation calculation, poor coordination, low matching efficiency, and lagging revenue accounting in existing coal resource allocation calculations. The model achieves accurate calculation of the raw coal allocation and washing decision-making module for the Dingwugeng coal group, the allocation module for coal from the four major coal preparation plants, and the production-sales coordination and dynamic optimization module. Combined with data acquisition and preprocessing, dynamic ratio adjustment, vector matching, and profit calculation algorithms, it realizes accurate calculation of the raw coal washing volume and thermal coal allocation volume for the Dingwugeng coal group, the coal allocation volume for the four major coal preparation plants, and the coal supply matching volume between the mine and the coal preparation plant. This invention reduces the calculation error by more than 30%, increases resource utilization by 15%-20%, and improves economic benefits by 10%-15%, making it suitable for refined and dynamic resource allocation and production decision-making in coal enterprises.