520results about How to "Improve utilization" patented technology

The invention discloses an automatic driving platform for a long-distance pipe network heat supply system based on a large model and a knowledge graph, and the platform comprises an infrastructure layer which is used for connecting an actual heat source, a long-distance pipe network and a multi-stage pump station heat supply facility of the long-distance pipe network heat supply system into the platform; the data processing layer comprises a data acquisition unit and a multi-source data fusion unit; the digital twinborn layer is used for establishing a digital twinborn model of the long-distance pipe network heat supply system; the large language model-knowledge graph layer comprises a graph construction unit which is used for constructing each business knowledge graph; the system also comprises a large language model construction unit which is used for constructing and training large language models of all businesses and processing automatic driving related businesses of the long-distance pipe network heat supply system. The business application decision-making layer comprises a business application unit which is used for providing a business application module of the long-distance pipe network heat supply system; and the intelligent decision-making unit is used for carrying out simulation analysis according to the digital twin model and calling each business large model to output a corresponding business decision-making result.

The invention provides a method and system for virtual power plant resource allocation optimization and computing equipment, and is applied to the technical field of new energy prediction. The method comprises the following steps: collecting data of a distributed energy production and elimination main body through a centralized control center; establishing prediction data by using the prediction model; forming an internal scheduling plan by using a master-slave game model so as to determine the output and income of each distributed energy production and elimination main body; the operation state of the distributed energy production and elimination main body is monitored in real time through a sensor, intelligent metering equipment and a communication network, and the internal scheduling plan is dynamically adjusted according to the operation state, so that the stability and economy of the system are ensured. By using the method and the system of the invention, flexibility and economy of internal and external resource allocation of the virtual power plant can be improved.

The invention discloses a multi-user sharing-oriented multimedia network video recommendation method, which comprises the following steps: firstly, constructing multi-user characteristics by utilizing collected program information in a multi-user sharing environment, and constructing a leading user label according to the similarity of the program characteristics and the continuity of user watching behaviors, so that separation of multi-user mixed logs is realized; performing periodic multi-user identification prediction of future sessions; secondly, building a user interest mining model based on a time-varying LinUCB algorithm to learn interest changes of a user for each program theme, and enhancing the personalized ability and efficiency of a recommendation system from three aspects of parallel calculation, adaptive control of an exploration coefficient and incremental updating based on LSTM; and finally, establishing an article quality model based on a non-time-varying LinUCB algorithm to further ensure the program quality, and integrating the two algorithms into a final recommendation system model by adopting a cross weighting strategy to form a final program recommendation list. The novelty and accuracy of the recommendation result are ensured.

The invention discloses a Carnot battery system coupled with an uninterrupted low-temperature heat source and an integrated optimization method of the Carnot battery system. The Carnot battery system comprises a high-temperature heat pump system, a heat storage system and a power circulation system, in the charging process, the high-temperature heat pump system operates, and waste heat of the uninterrupted low-temperature heat source module is improved into high-grade heat energy to be stored in the heat storage system through renewable energy source electric power; in the discharging process, the power circulation system operates, gradient utilization is conducted on heat energy stored in the heat storage system and an uninterrupted low-temperature heat source in the discharging stage, and generated mechanical energy is converted into electric energy through a generator and output to a power grid. The system configuration does not depend on the working medium type, and the comprehensive utilization rate of the uninterrupted low-temperature heat source and the back-and-forth efficiency of the Carnot cell are improved; according to the integrated optimization method, the working medium is coded to become a continuous variable capable of being synchronously optimized, and the optimal charge-discharge cycle working medium combination and system operation parameters suitable for different operation conditions can be obtained only through one-time optimization.

The invention relates to an intelligent photovoltaic power generation control device which integrates a photovoltaic power generation panel, a series connection base, a supporting assembly, a water collection groove, a rainwater collection assembly, a cleaning assembly and a control assembly. A series base and a series interface are arranged below the photovoltaic panel, so that modular installation is facilitated; the supporting assembly comprises two supporting rods, the light following function is achieved, and the photovoltaic panel is automatically adjusted to face the sun. A water collecting groove above the photovoltaic panel and a rainwater collecting assembly at the bottom of the photovoltaic panel can collect and store rainwater; the cleaning assembly comprises a spraying unit and a cleaning brush and is used for automatically cleaning the surface of the photovoltaic panel; the control assembly monitors operation of the system and adjusts the posture of the photovoltaic panel and work of the cleaning assembly. Redundant electricity generated by the photovoltaic power generation panel in sunny days is stored for the system to use, and the light following function is not started in cloudy days, so that electric energy is saved; through the design, the efficiency and sustainability of photovoltaic power generation are improved; the energy conversion efficiency can be improved, the reliability and automation level of the system are enhanced, and the utilization and environmental friendliness of rainwater are improved.

The invention provides a multi-data source plug-in computing resource scheduling method and system supporting algorithm iteration, relates to the technical field of data sources, and comprises the steps of extracting multi-dimensional features by constructing a data source feature analysis engine, generating a feature fingerprint identifier, designing an intelligent matching mechanism based on the feature fingerprint identifier, and optimizing algorithm plug-in selection. The method has the beneficial effects that the utilization efficiency of computing resources is improved, resource allocation is adjusted in real time, stable system performance is ensured, and closed-loop optimization is formed.

The invention relates to the technical field of electricity transaction, in particular to an hour-level green electricity transaction matching method and system considering a green certificate transaction blockchain, and the method comprises the following steps: S1, data collection and preprocessing: collecting the power generation operation data of a green electricity supplier and the power utilization behavior data of a user, preprocessing the collected power generation operation data and power consumption behavior data; s2, constructing a green certificate block chain: constructing a green certificate transaction platform based on a block chain technology, and recording green certificate transaction information; s3, establishing a matching model: constructing a multi-objective optimization model, and integrating multiple factors to carry out transaction matching; s4, transaction execution monitoring: after successful matching, executing the transaction and performing real-time monitoring; s5, transaction settlement evaluation: performing settlement and evaluation after the transaction is completed; according to the invention, the efficiency of green electricity transaction and the satisfaction degree of users and suppliers are effectively improved, and efficient utilization of green electricity resources and vitality improvement of the energy market are realized.

The invention belongs to the field of power system cascade fault prediction, and relates to a graph neural network power grid cascade fault prediction method based on physical information guidance, and the method comprises the steps: obtaining the operation data of a cascade fault, inputting the operation data of the cascade fault into a trained power grid cascade fault prediction model, and obtaining a prediction result; the power grid cascade fault prediction model comprises a common embedded graph neural network and a structure coding module; according to the invention, data enhancement is carried out by using a multi-step random walk matrix considering power grid line attributes and structure coding represented by node degrees, so that the capability of capturing topological information is improved; according to the invention, the interaction between the power grid nodes and the power grid lines is promoted by using the co-embedded graph neural network, and the accuracy of power grid cascade fault prediction is improved; according to the method, the node-edge interaction aggregation function of the co-embedded graph neural network is changed through the power transmission distribution factor of the power grid, the description capability of the actual complex interaction relation of the power grid is improved, and the accuracy of power grid cascade fault prediction is improved.

The invention discloses an efficient intelligent data compression and feature extraction method and system. The method comprises the following steps: S1, data preprocessing: performing data cleaning, denoising and standardization processing on to-be-processed data; s2, data compression and storage: determining a compression algorithm according to the type of the data, and uploading a compressed data file to a database; s3, feature extraction: deploying a machine learning model, and extracting representative features from the compressed data; and S4, data post-processing: further processing and optimizing the extracted features. According to the method, the data compression technology and the feature extraction technology are combined, the most representative information is extracted from the original data, meanwhile, the data storage and transmission cost is reduced, key features in the data are automatically recognized and reserved through an intelligent algorithm, and therefore efficient data compression and feature extraction are achieved.

The invention discloses a preparation method of a gas-liquid fluctuation resistant backflow electrolyzed water microchannel, and relates to the technical field of preparation of hydrogen by electrolyzed water, the preparation method comprises the following steps: S1, selecting a polar plate of an unprocessed flow channel, and designing and processing a Tesla valve array structure comprising a Tesla island; s2, selecting a processed polar plate, and processing a micro-column array at a position close to the side wall of the Tesla structure channel; s3, respectively coating the anode side and the cathode side of the proton exchange membrane with iridium oxide and platinum carbon to prepare a catalyst layer of the membrane electrode; s4, preparing a diffusion layer, and hot-pressing the proton exchange membrane loaded with the catalyst layer and the diffusion layer together to form a membrane electrode with catalytic activity; and S5, assembling the polar plate and the membrane electrode to form the proton exchange membrane water electrolysis device with the Tesla structure and the local wettability channel. According to the invention, the phenomenon of gas-liquid backflow of the electrolytic water flow channel under large current can be effectively inhibited, and the loss of active sites caused by blockage of the flow channel by the backflow electrolytic gas is avoided.

The invention discloses a driving permanent magnet synchronous motor with a heat dissipation mechanism, and relates to the technical field of 999. The outer side face of the rear end cover is fixedly connected with the inner side face of a base, a copper bar is embedded in the side, away from a shell, of the rear end cover, the inner side face of the rear end cover is fixedly connected with the surface of the copper bar, the side, away from the rear end cover, of the copper bar makes contact with the base, and the base is grounded; the air cooling assembly is fixedly connected with the end, close to the rear end cover, of the rotating shaft, the natural cooling assembly surrounds the outer portion of the shell, the inner side face of the natural cooling assembly is fixedly connected with the outer side face of the shell, the natural cooling assembly can increase the contact area with the outside, and the heat dissipation effect is enhanced. The rear end cover sucks air in the gap of the natural cooling assembly into the rear end cover to form flowing airflow, so that a better cooling effect is achieved, and the cooling effect of the air cooling assembly is radiated to the outside of the shell.

The invention belongs to the technical field of sewage treatment, and discloses an anaerobic ammonia oxidation enhanced denitrification device and method based on an electron mediator type biological carrier and iron oxide. The anaerobic ammonia oxidation enhanced denitrification device comprises a reactor main body, a heat preservation circulating water device, a stirring device, a water inlet pipeline and a water outlet pipeline, anaerobic ammonium oxidation bacteria are contained in the reactor main body, a certain proportion of electron mediator type biological carriers are filled in the reactor, and a proper amount of iron oxide is added; wherein the added high-valence iron oxide can be used as an extracellular electron acceptor of anaerobic ammonium oxidation bacteria, the electron mediator type carrier can be used as a redox mediator, and nitrogen removal of the anaerobic ammonium oxidation system is promoted by strengthening the extracellular electron transfer process of the anaerobic ammonium oxidation bacteria.

The invention provides a neurosteroid derivative solid dispersion, a preparation method and application thereof, and a medicine containing a hot-melt extrusion solid dispersion, and belongs to the technical field of pharmacy. The preparation method comprises the following steps: carrying out melt extrusion on a raw material mixture at 125-160 DEG C to obtain the neurosteroid derivative solid dispersion, the mixed material comprises an active component, a plasticizer and a carrier material in a mass ratio of 10: (1-15): (10-90); the active component comprises at least one of a neurosteroid derivative (with a structure as shown in a formula 1), an isomer, a solvate and a pharmaceutically acceptable salt thereof; the plasticizer is selected from one or more of polyethylene glycol, poloxamer and Tween, and the average molecular weight of the polyethylene glycol is 1t; 6000, 6000; active components in the neurosteroid derivative solid dispersion exist in an amorphous state. The neurosteroid derivative in the neurosteroid derivative solid dispersion disclosed by the invention has relatively high oral bioavailability. # imgabs0 #

The invention discloses a hybrid pumped storage scheduling method for reducing the operation water consumption rate of cascade hydropower stations, which comprises the following steps: establishing a cascade water-light-storage complementary power generation scheduling model, and constructing a target function with the minimum total water consumption of the cascade hydropower stations based on the cascade hydropower scheduling model; determining an objective function constraint condition according to the cascade hydropower dispatching model; establishing a solving model on the basis of an Actor-Critic algorithm; time sequence data in the historical data set is used as environment state parameters to be input into the deep reinforcement learning algorithm model, and an optimal day-ahead scheduling strategy is solved through an iterative training network model; and calculating the water consumption rate by using the obtained optimal scheduling strategy result, and evaluating the result. By introducing an Actor-Critic algorithm in deep reinforcement learning, an optimization decision strategy in a complex environment is realized, the economic operation efficiency and the power generation benefit of the system are effectively improved, and the water consumption rate of cascade hydropower is remarkably reduced.

The invention discloses a photovoltaic-driven IDC electric-cooling linkage method and device, and belongs to the technical field of IDC electric-cooling linkage, and the method comprises the following steps: S1, constructing a gravity energy storage structure; s2, the gravity object is lifted to the highest point of the gravity object channel through the gravity energy storage structure; s3, air at the bottom of the gravity object channel is compressed for the second time, and a thermal cracking reaction is carried out; s4, thermal cracking gas generated by the thermal cracking reaction is drained, and combustion products are discharged into a gas storage chamber; s5, the generated steam waste heat pushes a turbine in a turbine chamber to do work for power generation; and S6, domestic hot water and night heating hot water are prepared, convective heat exchange is conducted, the low-temperature reclaimed water obtained after heat exchange is heated into high-temperature steam in a cooler, the high-temperature steam enters a turbine to become high-temperature reclaimed water, and the high-temperature reclaimed water flows into a control center or a water storage pool. The organic matter compressed garbage is used as a gravity object for gravity energy storage, and heavy oil, solid fuel, adsorbents and other high-value products are produced in the gravity energy storage process.

The utility model discloses a grading type double-roller lint cotton cleaning machine, which relates to the technical field of lint cotton cleaning machines and comprises a cotton inlet, a dust cage and a lint cotton cleaning machine body, and the cotton inlet is arranged on the inner side of the upper end of the lint cotton cleaning machine body. By means of the upper licker-in structure, ginned cotton materials can be hooked and pulled, impurities are discharged through the upper impurity discharging cutter, long ginned cotton materials are discharged through the first discharging port, then short ginned cotton materials are conveyed into the lower licker-in through the lower roller, the lower licker-in hooks and pulls the ginned cotton materials to rotate, and the ginned cotton materials are conveyed into the lower licker-in through the lower roller. Therefore, impurities are removed through the lower impurity removal cutter, the impurities after impurity removal are discharged to the outside through the external impurity removal port, and short lint materials are discharged through the second discharge port, so that two grades of lint can be respectively obtained through the structural design of the double cotton outlets, the economic benefit is improved, resources are utilized to the maximum extent, and the cost is reduced. And greater social value is created.

The invention belongs to the technical field of wireless communication, and discloses a task unloading and wireless energy transmission method and system, and the method comprises the steps: building a communication and calculation model between a UAV (Unmanned Aerial Vehicle) and a ground Internet of Things user, including a time-varying channel model for communication, a WPT (Wireless Power Transfer) channel model for modeling by using a free space loss model, and a WPT channel model for modeling by using a free space loss model; a calculation and transmission model of UAV and ground Internet of Things users; the method comprises the following steps: designing a basic framework for performing task unloading and WPT on a ground Internet of Things user by using UAV under an edge computing scene assisted by the UAV, and performing system modeling according to the framework to obtain a mathematical model of the whole system; designing an optimization problem, and defining a target function as the weighted sum of the total throughput of the system and the energy consumption of the UAV; modeling the whole framework as a Markov process, designing a reasonable state action space, and designing a reasonable reward function by using a target function; and a task unloading decision and wireless energy transmission are optimized while the total throughput of the system and the UAV energy consumption are constrained by using a double-delay depth deterministic strategy gradient algorithm.

The invention relates to a solar seawater desalination plant, and relates to the technical field of seawater desalination, the solar seawater desalination plant comprises a raw water temporary storage tank, an evaporation tank and a fresh water storage tank, the evaporation tank is arranged at the upper part of the raw water temporary storage tank, an evaporation assembly and a collection assembly are arranged on the evaporation tank, and a flow guide assembly is arranged in the raw water temporary storage tank; the flow guiding assembly is connected with the collecting assembly and used for guiding condensate water to the fresh water storage tank. Seawater to be treated is guided into the raw water temporary storage tank, the water level rises to the evaporation tank, the evaporation assembly is started, condensed water formed after evaporation of the seawater is collected by the collection assembly, and the collected condensed water is guided to the fresh water storage tank through the flow guide assembly, so that condensation desalination of the seawater is realized, and a vacuum pump and a pressurizing device are not needed; the flow guide assembly is arranged in the raw water temporary storage tank, so that heat of condensed fresh water can remain in the raw water temporary storage tank to preheat the seawater to be treated, energy consumption and heat loss are reduced, and subsequent seawater evaporation and condensation efficiency is improved.

The invention discloses a data processing method and system of an intelligent organization construction system. The method comprises the steps that content recognition processing is conducted on a target text input by a user; inputting the content identification processing result into a pre-constructed classification model for processing; performing rewriting optimization processing on the target text; vector conversion processing is carried out, and a data definition language set corresponding to a vector conversion result is determined; generating target cue word data according to the data definition language set, the target text and a preset cue word template; inputting the target cue word data into a large language model to generate a target structured query language text; and executing the target structured query language text to obtain a query result. The method does not depend on a click type query mode any more, the text input by the user is accurately and effectively recognized and processed, the query precision is guaranteed, the processing efficiency of the organization construction data is improved, and the intelligent process of an organization construction system is promoted.

The invention discloses a physical information neural network hyperspectral band selection method for target identification, which uses physical information SDI as prior information to be combined with a channel attention mechanism added in a deep neural network to guide band selection, and evaluates the advantages and disadvantages of band weights through a reconstruction module after the weights are generated. Wave band selection is carried out accordingly; according to the hyperspectral image target recognition waveband selection method based on the physical information neural network, compared with a traditional method, the process is simplified and the precision is improved through end-to-end learning, the utilization of spatial context information can be enhanced by adding an attention mechanism, and the model has interpretability by adding prior SDI information.

The embodiment of the invention provides an image retrieval method and device, equipment, a storage medium and a program product. The method comprises the following steps: on the basis of a local feature vector and a global feature vector corresponding to a to-be-retrieved image, matching a plurality of candidate images from a preset retrieval library; calculating a local feature overlap ratio between the to-be-retrieved image and each candidate image based on the local feature vector corresponding to each candidate image and the local feature vector corresponding to the to-be-retrieved image; for each candidate image, based on the corresponding local feature overlap ratio, fusing the global feature vector corresponding to the candidate image and the global feature vector of the to-be-retrieved image to obtain a fused global feature vector corresponding to the candidate image; and calculating the similarity between the global feature vector corresponding to the to-be-retrieved image and the fused global feature vector corresponding to each candidate image, and determining a retrieval result of the to-be-retrieved image based on the similarity. According to the method, the retrieval accuracy can be improved.

The invention provides a cross-micro-grid power transaction method based on cross-chain of a block chain, and comprises a cross-micro-grid power transaction method based on a cross-chain technology of the block chain. Comprising the steps of transaction demand and quotation submission, cross-chain information synchronization and summarization, expected transaction set generation, transaction matching calculation, transaction result verification, smart contract transaction execution, reputation index adjustment and unmatched transaction processing. The micro-grids share power supply or demand and quotation information through the cross-chain technology, and the relay chain technology broadcasts information to ensure information synchronization. The micro-grids form an expected transaction set, and transaction matching is calculated and synchronized through a cross-chain technology. And after verification succeeds, the smart contract automatically executes a transaction and records a result, the reputation index is updated, and unmatched transactions can be transacted with the public power grid. According to the invention, the transaction efficiency and reliability can be improved, the reputation index is dynamically adjusted, a multi-dimensional evaluation system is adopted, and the fairness and environmental friendliness of the transaction are enhanced.

The invention discloses a 3D medical image registration method and device for contrast learning enhancement of double attention converters. The registration method comprises the steps that a 3D medical image data set is acquired and preprocessed; then down-sampling the fixed image and the floating image to create an image pyramid; then, a registration network based on a converter is established, finally, a loss function value between a fixed image and a registered image is calculated by using a loss function, and a network model is optimized through back propagation, so that a trained neural network model is obtained. According to the invention, by combining a self-attention mechanism and a cross attention mechanism, local and global context information can be comprehensively captured, and the modeling capability of image details and an overall structure is improved. And measuring the distance of the corresponding feature points between the images by using a contrast loss function. Meanwhile, the similarity between the images is further calculated by adopting a normalized total gradient and a modal independent neighborhood descriptor loss function, so that the accuracy and precision of medical image registration are improved.

The invention discloses a hyperspectral and panchromatic image fusion method based on feature enhancement channel shuffling, and the method comprises the steps: obtaining a hyperspectral image and a panchromatic image, carrying out the preprocessing of the hyperspectral image and the panchromatic image, and correspondingly obtaining a preprocessed hyperspectral image and a preprocessed panchromatic image; a hyperspectral image feature enhancement module based on matrix rank constraint performs feature extraction on the preprocessed hyperspectral image to obtain hyperspectral image features; a filtering-based panchromatic image feature extraction module performs feature extraction on the preprocessed panchromatic image to obtain panchromatic image features; splicing the hyperspectral image features and the panchromatic image features to obtain input features of an image feature fusion part; and carrying out feature fusion on the input features based on multi-scale convolution, extracting features of different scales, and carrying out deep fusion on the features of different scales based on a deep and shallow fusion module of channel shuffling to obtain a final fusion result. According to the invention, the image fusion effect is further improved.

The invention discloses an SAR (Synthetic Aperture Radar) interference suppression method based on intelligent image decomposition, which mainly solves the problem of poor SAR imaging interference suppression effect in a complex electromagnetic environment in the existing method. According to the implementation scheme, actually measured data are obtained, and interference signals are generated; respectively imaging measured data, interference signals and mixed data consisting of interference and measured data by using an imaging algorithm, and dividing into a training set and a test set; constructing an image decomposition interference suppression network comprising an image decomposition network and an interference suppression network, and carrying out iterative training on the network by utilizing the training set and adopting back propagation; and inputting the test set into the trained image decomposition interference suppression network to obtain an image after interference suppression. According to the method, interference suppression is carried out on the image level, sufficient interference suppression training can be carried out on a specific scene, the utilization rate of image data and the capability of suppressing interference of the specific scene are improved, and the method can be used for suppressing various interferences caused to radar imaging in a complex electromagnetic environment in target detection.

The invention discloses a combined type air conditioning unit and a control method, and relates to the technical field of machine room air conditioners, the combined type air conditioning unit comprises an outdoor heat exchange system and an indoor heat exchange system, the outdoor heat exchange system comprises a main loop, a first condenser and a pressure pump, and the main loop is provided with a plurality of branches corresponding to the indoor heat exchange system; the indoor heat exchange system comprises a compressor, a second condenser, a throttling element and a second evaporator, one set of indoor heat exchange system at least corresponds to two branches, one branch is connected with a first electric control valve and a first evaporator in series, and the other branch is provided with a second electric control valve and exchanges heat with the second condenser. Therefore, refrigerant heat in the indoor heat exchange system is taken away. Wherein the first evaporator and the second evaporator are both arranged indoors, at least one of the first evaporator and the second evaporator provides cooling capacity for the indoor space, and the first evaporator and the second evaporator are arranged in series in the airflow direction. Different refrigeration modes can be operated according to different outdoor working conditions, and outdoor natural cold sources are utilized to the maximum extent.

The utility model provides a full-automatic powder spraying room capable of rapidly switching colors and types, which comprises a powder spraying room and a conveying assembly arranged in the powder spraying room and used for conveying workpieces, and the powder spraying room is divided into a color powder spraying area, an operation area and a metal powder spraying area along the conveying direction of the conveying assembly. Two powder spraying mechanisms arranged in a mirror symmetry mode are arranged in the color powder spraying area, a starting controller is arranged in the operation area, and the starting controller is connected with the conveying assembly and the powder spraying mechanisms. The powder spraying room is small in occupied area, workpieces sequentially enter the color powder spraying area and the metal powder spraying area through the conveying assembly to be colored and decorated, the time for changing lines and colors is saved, color crossing is not likely to happen, the workpiece spraying efficiency is improved, and the equipment utilization rate is increased. And a powder spraying area and an employee operation area are isolated, so that dust pollution can be reduced, and color powder and metal powder can be conveniently distinguished and recycled while the health of employees is protected.

According to the regional load aggregator-oriented transformer area user flexible load scheduling method provided by the invention, the temperature control load, the electric vehicle, the energy storage equipment and the like are optimally scheduled, so that the balance of a power grid and the maximization of economic benefits are realized. The method comprises the following steps: predicting the load demand of a transformer area user through modeling analysis, and formulating an optimal scheduling strategy in combination with external signals such as real-time electricity price and environment temperature; a home energy efficiency management system (HEMS), a vehicle-to-power grid (V2G) control platform and an intelligent energy management system (EMS) are utilized to dynamically dispatch and control various flexible loads. The implementation result shows that the method effectively reduces the electric charge of the user, improves the revenue of the aggregator, improves the stability of the power grid, and has remarkable practicability and popularization value.

The invention provides a gasification furnace, an oxygen flow control method of a first-section coal burner of the gasification furnace and the gasification furnace. The gasification furnace comprises a furnace body, a first-section coal burner and a second-section coal burner, the first-section coal burner is communicated with the side wall of the furnace body; the second-section coal burner is communicated with the side wall of the furnace body and is positioned above the first-section coal burner; the gas outlet is communicated with the top of the furnace body; and the coal cinder outlet is communicated with the bottom of the furnace body. According to the technical scheme provided by the invention, the problem of energy waste of the gasification furnace caused by relatively low conversion rate of the dry pulverized coal synthetic gas in related technologies is effectively solved.

The invention discloses a scalp care solution containing a probiotic fermentation product and a preparation method thereof, which comprises the following raw materials by weight: 87-91 parts of water, 3-5 parts of glycerol, 4-9.3 parts of probiotic fermentation products, 1.3-2.6 parts of plant extracts, 0.4-0.8 parts of 1,2-hexanediol, 0.4-0.8 parts of p-hydroxyacetophenone, 0.1-0.3 parts of carbomer, 0.1-0.2 parts of arginine, 0.1-0.15 parts of trace components, and 7-11 parts of composite nano-carrier liquid. The scalp care solution provides nutrition for scalp probiotics by adding prebiotic fermentation products, such as lactobacillus fermentation products, bifid yeast fermentation product filtrate, altermonas fermentation product extract, and bifid yeast fermentation product lysate, which is beneficial to promoting the growth of scalp probiotics and enhancing the scalp barrier, thereby achieving scalp health.