3226 results about "Coal fired" patented technology

The invention relates to the technical field of computer programming languages, and particularly discloses a coal-fired power plant safety monitoring system and method. The system comprises a multi-modal data fusion platform, a federal learning agent network and a digital twinborn simulation engine. The edge computing node carries out unified acquisition and feature extraction on multi-source heterogeneous data through multi-protocol conversion, quantum noise suppression and a preprocessing chipset; the multi-modal data fusion platform realizes semantic mapping based on a knowledge graph, and fuses time-space correlation characteristics of data such as an infrared image and gas concentration by adopting a time-space encoder and a cross-modal attention mechanism. According to the method, the problems of early warning delay and high false alarm rate caused by low multi-source data decentralized processing efficiency and insufficient nonlinear correlation analysis in a traditional scheme are solved, efficient data fusion, complex risk accurate prediction and automatic safety response are realized, and the real-time performance and reliability of a coal-fired power plant monitoring system are remarkably improved.

The invention discloses an induced draft fan parameter dynamic early warning method, system and device based on historical data mining and a medium, and relates to the technical field of coal-fired unit intelligent monitoring. The method comprises the steps that characteristic parameters of an induced draft fan are collected, and the characteristic parameters of the induced draft fan are preprocessed; according to the preprocessed data, an induced draft fan characteristic parameter prediction model is established, and an induced draft fan characteristic parameter prediction value is obtained; establishing an early warning threshold value according to the characteristic parameter predicted value of the induced draft fan, and dynamically adjusting the early warning threshold value; establishing an early warning model, and performing early warning on the abnormal characteristic parameters of the induced draft fan according to an early warning threshold value; according to the method, the characteristic parameters of the induced draft fan are collected, data preprocessing is carried out, the early warning threshold value is dynamically adjusted in combination with the predicted value and the environmental factors, the adaptability and accuracy of early warning are improved, the intelligent early warning model is constructed, and targeted fault diagnosis suggestions are provided; the monitoring precision, the early warning accuracy and the fault response efficiency of the operation state of the induced draft fan are effectively improved, and the operation safety and stability of a coal-fired unit are improved.

The invention relates to the technical field of hydrogen energy, and discloses an auxiliary-machine-free solid oxide electrolytic hydrogen production system and an auxiliary coal electricity deep adjustment method, the hydrogen production system comprises an SOE heat box system for electrolytic hydrogen production, a hydrogen circulation subsystem and a hydrogen storage subsystem; the ejector is driven by external heat source steam, part of hydrogen at an outlet of the SOE heat box system is ejected to a low-pressure suction inlet of the ejector through the hydrogen circulation subsystem, and formed reducing mixed gas of steam and hydrogen enters a cathode inlet of the SOE heat box system. The system is driven by an external heat source and operates in an internal stack heating mode, so that the power consumption of the electrolytic hydrogen production system is reduced; by adopting the modes of external material supply, cathode ejector material self-circulation and multi-stream heat exchange, a complex cold and hot auxiliary machine of a traditional solid oxide electrolytic hydrogen production system is omitted, the structure is simple, and the system compactness is greatly improved; electric power-steam-air-condensed water flow coupling is established with a coal-fired power plant, and efficient, flexible and deep peak shaving is adjusted in combination with steam extraction multi-stage adjustment.

The invention relates to a boiler combustion optimization control system of a thermal power plant, relates to the technical field of thermal power generation control, and aims to solve the problems of inaccurate multi-source data perception, slow control response and insufficient multi-target collaborative optimization capability under fire coal quality fluctuation and load change. The system comprises a data perception and fusion module, a working condition self-adaptive identification module, a multi-target dynamic optimization decision module and a distributed execution control module, and through multi-source data acquisition and feature extraction, depth time sequence mode identification, multi-target optimization model solving and distributed coordination control, the multi-target dynamic optimization decision module and the distributed execution control module are subjected to multi-source data fusion. Dynamic balance of boiler heat efficiency improvement and nitrogen oxide emission reduction is achieved, and adaptability and control precision of the system under complex working conditions are enhanced.

The invention relates to a coal-fired unit electrostatic dust collection energy-saving optimization method, system and equipment and a storage medium, and the method comprises the steps: obtaining historically collected system operation data of a coal-fired unit electrostatic dust collection system, and constructing an outlet NOx concentration prediction model and an outlet dust concentration dynamic model according to the system operation data; power optimization control strategies of high-voltage power supplies of all levels of electric fields in the dust removal system are obtained, a model is built based on the outlet NOx concentration prediction model, the outlet dust concentration dynamic model and the optimization control strategies, and an electrostatic dust removal energy-saving optimization model is obtained; acquiring a preset environment-friendly standard concentration, and analyzing the environment-friendly standard concentration through the electrostatic dust collection energy-saving optimization model to obtain an optimal dust collection parameter; and adjusting the current or voltage of each level of electric field in the dust removal system according to the optimal dust removal parameters. Through the constructed energy-saving optimization model, the electrostatic dust collection control system can reduce the dust emission concentration and meet the pollutant emission standard, and meanwhile, the energy consumption of the electric dust collector can be greatly reduced.

The invention discloses a coal-fired power generation steam and heat pump integrated energy storage system and an operation method thereof. The system comprises a coal-fired unit coupling fused salt energy release system and a reheat steam coupling heat pump energy storage system. In the low ebb of electricity utilization, the coal-fired unit outputs electric energy to drive the heat pump charging compressor to compress a heat pump working medium, then the heat pump working medium heats the fused salt, meanwhile, part of reheat steam of the coal-fired unit sequentially heats the fused salt and a working medium at an outlet of the heat pump charging expansion machine, and the load is further reduced; and finally, redundant electric energy and part of heat energy of the reheated steam are converted into fused salt heat energy to be stored. In the peak period of electricity utilization, a part of exhaust steam of the high-pressure cylinder is heated through heat stored in the fused salt storage tank to generate reheated steam, the heat absorption capacity of main steam entering the boiler is increased under the condition that the coal consumption of the boiler is not changed, the flow of the main steam is also increased, and then the output load of the coal-fired unit is increased. According to the method, the peak regulation potential of the coal-fired unit can be exerted, the output load interval of the unit is expanded, and the method is effective for improving the peak regulation capacity of the coal-fired unit and stabilizing power grid fluctuation.

The invention discloses a low-carbon flexible coal-fired unit power control system and method, and relates to the technical field of power systems, and the system comprises a cascade waste heat recovery module, a boiler deep regulation and control module, a thermal coordination module, an environmental protection and emission reduction module, an intelligent operation scheduling module and an energy efficiency monitoring module. The gradient waste heat recovery module carries out gradient recovery on flue gas heat energy according to temperature zone grades; the boiler depth regulation and control module is used for regulating combustion air supply and heat absorption paths to realize low-load stable combustion; the thermal coordination module dynamically distributes thermal loads between the multiple heat sources and the thermal units; the environmental protection and emission reduction module jointly controls desulfurization, denitration and wastewater resourceful treatment; the intelligent operation scheduling module generates a load regulation and control instruction and coordinates multi-module response; the energy efficiency monitoring module collects and analyzes energy consumption and emission indexes and assists strategy optimization. The energy efficiency utilization and emission control capability of the unit under the deep peak regulation condition is improved, and flexible, efficient and low-carbon operation is achieved.

The invention discloses a coal-fired unit SCR denitration system ammonia injection prediction control method based on data driving, which is used for realizing better SCR denitration system ammonia injection control based on a data driving model in combination with an implicit generalized prediction control algorithm. The SCR inlet NOx concentration and the flue gas temperature serve as feedforward of an ammonia spraying amount instruction, the initial control instruction increment of the ammonia spraying amount is calculated through the SCR outlet NOx concentration, the SCR outlet NOx concentration set value and the ammonia spraying amount instruction at the previous moment through an implicit generalized predictive control algorithm, and the final ammonia spraying amount instruction is obtained through summation and amplitude limiting of the last three instructions. Wherein the feedforward instruction of the NOx concentration of the SCR inlet is obtained by a BP neural network prediction model, and the feedforward instruction of the SCR inlet is obtained by a long-short term memory network prediction model fused with an attention mechanism. According to the method, the problem that the concentration of NOx at an SCR outlet fluctuates severely in the frequent load changing process can be effectively solved, meanwhile, transient overshoot of NOx in tail flue gas of a coal-fired unit is restrained, and the SCR denitration control effect is improved.

The invention relates to the technical field of boiler equipment fault prediction, in particular to a boiler four-tube wall tube wear prediction method based on a big data algorithm, comprising the following steps: constructing a three-dimensional digital model of boiler four tubes, and spatially binding design parameters, historical operation and maintenance records and real-time monitoring data to form a multi-source associated database; constructing a pipe wall temperature prediction model by using a heat conduction mechanism model and a neural network algorithm, and outputting wall temperature distribution data of a full heating surface; inputting the data into a wear, creep and corrosion model, and calculating the residual life and generating a life map in combination with a historical pipe explosion case; generating a three-dimensional risk thermodynamic distribution diagram by adopting a leakage risk probability algorithm and a coupling risk coefficient model; and superposing the thermodynamic diagram into the three-dimensional digital model, and displaying the risk level based on color gradient mapping, so that the method can be widely applied to online state monitoring and intelligent early warning of the four tubes of the coal-fired power plant boiler.

The invention discloses a coal-fired power plant operation parameter adaptive optimization method and system. The method comprises the steps of operation data fusion acquisition, dynamic load response modeling, fire coal load coordination optimization, emission efficiency adaptive balance and operation parameter adaptive optimization. The invention relates to the technical field of intelligent adjustment of parameters of a coal-fired power plant, and aims at realizing future load minute-level rolling prediction by constructing a standardized multi-source data structure and adopting a long-short-term memory network, and realizing dynamic generation of combustion parameters by introducing adaptive dual-stage collaborative scheduling and an improved multi-objective optimization algorithm. On the basis, the dynamic causal regulation and control diagram is used for carrying out rolling weighted balance on the emission efficiency, the energy efficiency, the responsiveness and the emission compliance are comprehensively considered, the power generation efficiency is improved, the pollutant emission is reduced, and the adaptability and the stability of the system are enhanced.

The invention discloses a method for preventing main steam pressure fluctuation on the basis of controlling the coal combustion amount. The method comprises the following steps: acquiring running state data of the coal-fired boiler in real time; based on the operation state data and a preset boiler dynamic prediction model, predicting a steam pressure sequence of the boiler in a future preset time range, and judging whether to trigger a control action or not in combination with an event triggering strategy obtained by learning of a reinforcement learning agent; if it is judged that the control action is triggered, the reinforcement learning agent outputs an adjustment instruction of the total coal feeding amount according to the current operation state data; and controlling the total coal feeding amount of the boiler according to the adjusting instruction. According to the method, the timing and the force of control intervention can be intelligently determined according to the real-time state and future trend prediction of the boiler, and the accuracy and the foresight of main steam pressure control are improved.

A thermal battery energy storage system coupled with a coal-fired generator set and its operation method, including a coal-fired generator set system and a heat pump energy storage system coupled with molten salt heat storage; the coal-fired generator set system includes a high-pressure cylinder, a medium-pressure cylinder, a low-pressure cylinder, a generator, a condenser, a condensate pump, a low-pressure heater, a deaerator, a feedwater pump, a high-pressure heater, and a boiler; the invention uses the exhaust steam of the low-pressure cylinder as a heat source to preheat the circulating working fluid in the thermal battery heat pump system, so that the total efficiency and COP of the system are increased, and the exhaust steam recovery and utilization capacity is enhanced. At the same time, the output load of the coal-fired unit is reduced, the peak-shaving range of the unit is expanded, and the peak-shaving depth is increased.

The invention relates to a power plant temperature control system safety protection device and system. The power plant temperature control system safety protection device comprises a redundant temperature acquisition module, a temperature control safety processing module, an actuator control protection module, an intelligent strategy recovery module and a communication and alarm module. Through multi-point temperature data acquisition, abnormal trend intelligent identification and local linkage control, the device realizes quick response and protection control of temperature control abnormity of a key area of a boiler thermodynamic system. The system supports data interconnection with a DCS platform and an alarm analysis platform, has local independent operation and remote centralized management capabilities, and is suitable for temperature control safety protection of high heat load areas such as boilers of coal-fired power plants.

The invention discloses a desert sand-based artificial earthwork lattice sand barrier and a preparation and use method thereof, the artificial earthwork lattice sand barrier comprises the following components in percentage by mass: 93-97% of a coal-sand-ash mixture, 1-10% of an activating agent and 5-15% of externally doped water, and the artificial earthwork lattice sand barrier is prepared by compacting and molding, and the coal-sand-ash mixture accounts for 93-97%, the activating agent accounts for 1-10% and the externally doped water accounts for 5-15%. The desert sand base artificial earthwork grid is horizontally laid in the desert and a water and soil loss area, desert sand stabilization can be achieved, and surface layer floating sand and surface layer sandy soil loss in the water and soil loss area are prevented. Typical coal-fired solid wastes such as the coal ash and the coal slag are used as raw materials for preparing the desert sand-based artificial earthwork grid, collaborative resource utilization of the desert sand, the coal ash and the coal slag is achieved, resource utilization of a large amount of industrial solid wastes is combined with desertification prevention and control engineering, environmental pollution is reduced, and the desertification control cost is reduced.

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 relates to the technical field of fire coal control, and discloses a thermal power plant fly ash floating black online detection control method and system, and the method comprises the steps: 1, employing microwave, infrared and laser sensors for cooperative work, detecting carbon dielectric characteristics through microwave dust interference resistance, identifying thermal radiation difference through infrared, and analyzing particle distribution through laser; 2, on the basis of the detection requirements in the step 1, triple protection of air curtain barrier, ultrasonic cleaning and hydrophobic coating is designed, dust condensation is blocked, and it is ensured that the light transmittance of the sensor is larger than 90%; the invention provides a multi-mode sensing fusion-anti-interference current stabilization-closed loop optimization full-link solution for the industrial problem of signal distortion caused by optical window dew formation and dust deposition, airflow disturbance and environmental interference in fly ash floating black online detection. The light transmittance of the optical window is greater than 93% by combining triple protection of air curtain barrier, ultrasonic cavitation stripping and nano hydrophobic coating.

The invention provides a combustion optimization method and system for a coal-fired boiler, electronic equipment and a storage medium. The combustion optimization method for the coal-fired boiler comprises the steps that historical operation data and operation condition data of the boiler are obtained; determining the combustion efficiency of the boiler according to the historical operation data of the boiler; working condition division is carried out according to the boiler combustion efficiency and the operation working condition data, and information of all working condition intervals is obtained; constructing a combustion efficiency prediction model driven by time series data according to the information of each working condition interval; the combustion efficiency prediction model is embedded into a deep reinforcement learning method framework for training, and an optimization model is generated; and inputting real-time operation data of the boiler into the optimization model to generate optimization decision data.

The invention relates to the technical field of denitration and ammonia spraying, in particular to an intelligent denitration and ammonia spraying automatic control system and method for a thermal power coal-fired unit, and the system comprises a control module which is used for controlling and monitoring the whole denitration process; the data analysis and prediction module is used for analyzing by utilizing historical data and real-time data, predicting NOx concentration change and providing decision support for ammonia injection control; the balancing module is responsible for accurately controlling and optimizing the ammonia spraying amount; the monitoring and feedback module is used for monitoring the concentration of NOx and ammonia escape in real time and providing a feedback signal for the control system; and the communication module is responsible for data transmission between the denitration control system module and the DCS program. The method has the beneficial effects that the time stability and the space uniformity of NOx at an SCR outlet are improved through an intelligent feed-forward algorithm and an override algorithm, excessive ammonia spraying is reduced by utilizing an ammonia escape correction system, the ammonia escape rate is effectively reduced, the operation reliability of a unit is improved, and the resistance increase of a flue gas system caused by blockage of an air pre-heater is reduced.

The invention relates to the technical field of environmental monitoring, and discloses an uncertainty evaluation method based on establishment of a carbon emission monitoring method and an accounting method, and the method comprises the following steps: establishing an uncertainty evaluation model of a coal-fired unit carbon emission monitoring method to quantify the uncertainty of the carbon dioxide emission of the monitoring method; establishing a coal-fired unit carbon emission accounting method uncertainty evaluation model to quantify the uncertainty of the carbon dioxide emission of the accounting method; based on results obtained by the monitoring method uncertainty evaluation model and the accounting method uncertainty evaluation model, carbon emission data quality is analyzed, and improvement measures are put forward. By constructing an uncertainty evaluation model of a monitoring method and an accounting method, various error sources in the whole process of flue gas sampling, analysis, fuel metering, coal quality analysis and the like are comprehensively considered, and a rigorous mathematical method is adopted for synthesis. The quantitative evaluation enables the accuracy of the carbon emission data to have a clear measurement standard.

The invention belongs to the technical field of coal-fired power plant combustion control, and discloses a boiler combustion control method based on blending combustion proportion dynamic optimization and a related device. The boiler combustion control method based on blending combustion proportion dynamic optimization comprises the steps that combustion efficiency parameters, safety parameters and flue gas environmental protection parameters of a boiler are monitored and collected in real time, and the combustion efficiency parameters, the safety parameters and the flue gas environmental protection parameters are preprocessed; inputting the pretreated combustion efficiency parameters, safety parameters and flue gas environmental protection parameters into the trained RF-LSTM double-layer model to obtain an optimal blending combustion ratio, setting an optimal blending combustion ratio threshold according to the optimal blending combustion ratio, and dynamically regulating and controlling the blending combustion ratio according to the optimal blending combustion ratio threshold and a preset wall temperature threshold through a double-screw feeder; the sludge blending combustion proportion can be dynamically adjusted, the reliability and flexibility of the system are guaranteed, and proportional blending combustion is more stable.

The invention relates to the technical field of boiler combustion optimization, in particular to a group combustion optimization method under flexible peak regulation of a coal-fired boiler, which comprises the following steps of: acquiring characteristic historical operation data of the coal-fired boiler, dividing operation conditions, calculating key operation parameters of the coal-fired boiler under different working conditions, and constructing a coal-fired boiler combustion model; coal loading information and load information of a future operation plan of the coal-fired boiler are read, and a planned operation condition group of the coal-fired boiler is constructed in combination with key operation variable action time; key operation parameter analysis is carried out on the planned operation condition group of the coal-fired boiler, group optimization is carried out based on a combustion model, a key operation variable adjustment scheme is given, and operation of the coal-fired boiler is guided. According to the method, the operation condition of the coal-fired boiler under the flexible peak regulation can be analyzed and judged, group combustion optimization of the coal-fired boiler is comprehensively guided in combination with the key operation variable action time, and the high efficiency and the environmental protection property of the coal-fired boiler under the flexible peak regulation can be greatly improved.

The invention belongs to the technical field of industrial flue gas purification, and discloses an ammonia desulfurization optimization control system based on a machine learning algorithm, which comprises a feature extraction module, a working condition clustering module, a dynamic optimization module and a self-adaptive feedback module, the feature extraction module is used for collecting multi-dimensional operation parameters in a coal burning process, performing data dimension reduction through a PCA algorithm, and extracting key working condition features; the working condition clustering module identifies different operation working condition modes; the dynamic optimization module can construct a multi-modal optimization neural network based on different operation condition modes, and generates optimal control parameters in real time. Through PCA dimension reduction processing of the feature extraction module and in combination with a working condition clustering algorithm, automatic mode recognition and strategy switching under complex working conditions are achieved, fluctuation of desulfurization efficiency is reduced, and meanwhile the problems that the ammonia water adding amount depends on experience setting, raw material waste and secondary pollution are likely to be caused, and the operation and maintenance cost is large are solved.

The invention discloses a carbon emission evaluation method and system for coal-fired biomass direct-mixing coupling power generation, and relates to the related field of carbon emission evaluation, and the method comprises the steps: determining the type and characteristics of a biomass raw material, and setting blending combustion conditions; establishing a carbon emission parameter calculation model; establishing a coal-fired biomass direct-mixing coupling carbon emission full-life-cycle evaluation model by combining carbon emission in stages of growth, collection, transportation, pretreatment and ash treatment of biomass raw materials; evaluating the influence of the retention duration of the biomass raw material on the combustion carbon emission to obtain a retention duration influence factor, and correcting the coal-fired biomass direct-mixing coupling carbon emission full-life-cycle evaluation model according to the retention duration influence factor; and performing carbon emission evaluation by adopting the corrected coal biomass direct mixing coupling carbon emission full life cycle evaluation model. The technical problem that existing carbon emission evaluation is insufficient in accuracy and comprehensiveness is solved, and the technical effect of improving the accuracy and comprehensiveness of carbon emission evaluation is achieved.

The invention discloses an emission control enterprise fuel end carbon emission factor dynamic checking method and system, and the method comprises the steps: building different coal classification recognition models, building a prediction model of a fire coal combustion carbon emission factor CEF, an element carbon content C and a lower calorific value NCV, and further analyzing the error absolute value of the prediction model according to a prediction result, checking thresholds of the three are respectively determined, and a three-level data checking rule is adopted to automatically check the reasonability of the fuel coal carbon emission factor data of the enterprise, so that abnormal data can be recognized in time, and a third-party checking mechanism is effectively assisted to check the accuracy and reasonability of a fuel end carbon emission factor result of the enterprise; therefore, the quality of carbon emission accounting data is effectively guaranteed. Besides, basic data support and guidance are provided for design and operation of the carbon market, and market managers can master carbon emission factor change trends of different activities and industries, so that reasonable carbon emission limits and prices are set, and emission reduction actions are effectively guided and promoted.

The invention discloses an intelligent optimization operation method for a biomass gas coupling coal-fired boiler, and belongs to the technical field of boiler operation control. Historical operation parameters of a gasification furnace and the coal-fired boiler are collected, a multi-dimensional coordinate system is constructed, historical operation data are mapped into coordinate points, a high-efficiency area boundary, a stable area boundary and a risk area boundary are divided, and a dynamic operation map is formed; meanwhile, the historical operation data are cut into track fragments, and the state evolution process and operation instructions of the coal-fired boiler are recorded; the method comprises the following steps: acquiring gasifier temperature, gas components and boiler temperature data in real time, determining the position of a current state in a dynamic operation map, and predicting a future evolution path of the coal-fired boiler by fitting a motion track and matching a plurality of historical tracks; and when the evolution path reaches the boundary of the risk area, triggering early warning, screening a historical successful track by taking an efficient area as a target, extracting related operation instructions to form a candidate intervention strategy set, selecting the operation instructions according to real-time working conditions, converting the operation instructions into specific adjustment instructions, and sending the specific adjustment instructions to corresponding control equipment.

The invention discloses an omnidirectional tension iterative compensation type array electronic belt scale measuring device and method. The device comprises a signal acquisition module, a signal processing module, a dynamic iterative compensation and fusion module, a redundancy check module and an integral operation module. Multi-source signal synchronous acquisition is realized through an array type weighing unit, a three-axis tension detection unit and a speed detection unit, dynamic gain amplification, anti-aliasing filtering and AD conversion are carried out, then a three-axis tension signal is adopted to carry out dynamic iteration compensation on a weighing signal, belt deformation compensation, transverse deviation correction and frequency domain vibration suppression are executed, and the weighing precision is improved. And environmental interference is eliminated in combination with redundant cross check. And finally, the real-time coal feeding amount is output through integral operation. According to the method, the limitation of traditional static compensation is broken through, errors caused by tension fluctuation, mechanical vibration and transverse deviation are effectively restrained through the multi-dimensional dynamic fusion compensation technology, the anti-interference capacity is high, and high-reliability metering support is provided for energy efficiency management of the coal-fired unit.

The invention discloses a power plant fire coal cost management and control and dispatching system which comprises a data acquisition module, a management and control dispatching module and a data display window. The data acquisition module is used for acquiring power plant real-time load data, power plant fire coal consumption speed, historical fire coal price, inventory period, international energy price index and policy document; and the management and control dispatching module is used for inputting related data integration through a mathematical model, analyzing the market trend and price fluctuation, and predicting and controlling the fire coal cost. Limitations of a traditional fire coal management system can be broken through, complex decision-making elements are quantified through mathematical modeling, dynamic balance of cost and risks is achieved, the response speed and accuracy of a fire coal cost prediction model to market changes can be effectively improved through the method of combining a dynamic threshold value and online learning, and the market development prospect is wide. The enterprise can realize dynamic optimization and risk controllability of cost prediction in uncertainty of coal price fluctuation, transportation delay and the like.

The invention discloses a flue gas compensation type pulverized coal wide-load stable combustion system based on staged combustion and intelligent regulation and control and a control method, and belongs to the technical field of coal-fired power generation. The system is composed of a combustor, an intelligent control module and a flue gas backflow module, the combustor adopts a double-ring fuel channel design, an inner ring injects high-concentration pulverized coal and is provided with an adjustable swirler, and pulverized coal-flue gas mixed airflow is introduced into an outer ring; the intelligent control module predicts a load through an LSTM neural network, and realizes accurate matching of air and coal in combination with PID adjustment; and the flue gas backflow module adopts an oxygen concentration adjustable technology to maintain the combustion intensity. Under the working condition of 30%-40% low load, the system achieves the stable combustion effect that the flame center temperature is stabilized at 920 + / -20 DEG C by means of optimizing the proportion of inner ring pulverized coal to 75%-85%, increasing the primary air temperature to 145-170 DEG C, compressing the proportion of secondary air to 20%-30%, strengthening a swirling flow field to 45 degrees and the like in cooperation with flue gas backflow with the oxygen concentration of 23%-25%, and has the advantages of efficient combustion and low emission.

The invention discloses an auxiliary decision-making method and system for regional coal market purchase, and belongs to the technical field of coal market purchase decision-making, and the method comprises the steps: building model input parameters through collecting the data of a fire coal demand plan of a power plant, the maximum supply of a supplier, a coal quality index, a purchase price and a transportation cost; constructing a mixed integer linear programming model taking the minimization of the total purchase cost as a target function, and setting a demand satisfaction constraint, a supply capability constraint and a coal quality standard reaching constraint; solving the mixed integer linear programming model by adopting a two-stage approximation algorithm; and converting the obtained approximate optimal solution into a visual purchasing scheme chart and report, and supporting a user to dynamically adjust the purchasing scheme through an interactive interface to generate a final purchasing decision. According to the invention, on the basis of comprehensively considering the coal quality, the purchase cost, the transportation mode and the supplier capability, the coal purchase plan is optimized, the cost minimization is realized, and the overall quality of coal purchase is improved.

The invention relates to an operation optimization method and device for coal blending combustion of a coal-fired unit, and the method comprises the steps: obtaining at least one of parameters related to the operation state of the coal-fired unit, flue gas component parameters related to combustion, parameters related to a coal pulverizing system, historical coal quality parameter data and coal price; performing data cleaning on at least one item of data; establishing at least one of a safety index, an environmental protection index, an economic index and a combustibility index of the coal-fired unit, and establishing a case library of the coal-fired unit according to the target working condition; retrieving operation parameters of the load interval of the corresponding coal-fired unit in the case library; and optimizing the stock coal type blending scheme by using the at least one piece of historical coal blending quality information to generate a predicted blending scheme meeting a preset optimal condition. According to the embodiment, the requirement for the temporary peak in the operation process can be met with the highest load historical coal blending quality as the target, and the situation that a unit cannot respond to the high load requirement is avoided.