934 results about "Pollutant emissions" patented technology

The invention relates to the technical field of energy, in particular to a dynamic self-adaptive control method and system for a gas-steam combined cycle unit, and the method comprises the steps: constructing a multi-modal model library comprising a plurality of operation modes; operating parameters and environment parameters of the unit are collected in real time, and multi-source data fusion and system state evaluation are carried out; carrying out multi-time scale prediction on the load demand, fuel characteristics and environmental parameters of the unit based on a deep learning model; dynamically selecting model precision according to a prediction result, and implementing a multi-mode collaborative optimization decision to generate a control instruction; and executing the control instruction and monitoring an execution effect, and carrying out adaptive adjustment on model parameters and strategies according to feedback. According to the method, the unit can maintain efficient and stable operation under the scenes of power grid peak regulation, rapid load fluctuation, complex environment change and the like, meanwhile, pollutant emission is reduced, and the service life of key equipment is prolonged.

The invention relates to the technical field of boiler combustion control, and discloses a boiler closed-loop combustion dynamic optimization control system based on big data, and the system comprises an intelligent sensing module which is used for obtaining and outputting time-synchronized monitoring data in real time; the edge calculation module is used for processing multi-source sensor data in real time, realizing data credible processing and combustion state feature coding, and executing local caching of working condition perception; the digital twin modeling module is used for constructing a combustion process dynamic model and realizing real-time prediction of a combustion state; the optimization control module is used for dynamically adjusting combustion parameters and achieving collaborative optimization of the air-coal ratio, the opening degree of a secondary air door and the over-fire air ratio; and the closed-loop execution module is used for executing and feeding back the control instruction and realizing transmission and closed-loop verification of the control instruction. The combustion efficiency can be improved, pollutant emission can be reduced, and the stability and safety of boiler operation can be enhanced.

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 relates to a method, a device and equipment for identifying abnormal pollution discharge based on multi-source data, and a medium, and belongs to the technical field of environment monitoring. The method comprises the following steps: collecting working condition electricity consumption historical data and pollutant discharge historical data; extracting at least two key variables from the working condition electricity consumption historical data and the pollutant emission historical data, taking the key variables as endogenous variables, constructing a vector autoregression model according to the endogenous variables, and determining a lag order of the vector autoregression model by using an information criterion method; processing the working condition electricity consumption historical data and the pollutant emission historical data to obtain a training set, and training a vector autoregression model by using the training set; obtaining input data according to a to-be-predicted moment and the lag order, inputting the input data into the trained vector autoregression model, outputting a predicted value of a key variable at the to-be-predicted moment, and obtaining a corresponding measured value; and judging whether pollution discharge is abnormal or not according to the predicted value and the measured value of the key variable, and analyzing an abnormal reason.

The invention relates to the technical field of boiler control, and discloses a gas-fired boiler starting control method and system. The method comprises the following steps: acquiring initial operation parameters such as hearth pressure, water inlet temperature, flue gas oxygen content and fuel valve opening of the gas-fired boiler, establishing a thermodynamic state model in a starting stage according to the initial operation parameters, and dividing dynamic response thresholds of different load intervals; and calculating a theoretical fuel supply rate of the combustor based on the model, generating and dynamically updating a fuel supply correction coefficient in combination with a threshold value, synchronously marking key nodes according to abnormal distribution of hearth temperature, and adjusting a spatial air distribution strategy of the combustor. And after the correction coefficient is subjected to multi-stage buffer smoothing, a fuel control instruction is output to an executing mechanism. And switching to steady state control after the boiler reaches the preset load. The method adapts to the characteristics of a power plant unit, so that the starting process is more stable, the damage to a heated surface and pollutant emission are reduced, and rapid grid connection is assisted.

An AI-connected-electrified (ACE) heavy truck system equipped with an intelligent multi-mode hybrid (iMMH) powertrain system and a vehicle supervision control strategy based on machine learning (ML) or reinforcement learning (RL) paradigm are presented. This system ensures industry-leading power and braking performance of the ACE heavy truck while automatically optimizes both energy saving and emission reduction based on the vehicle's dynamic driving data and 3D electronic map information of roads for any transport event. In this application, the conventional analog electronic control (AEC) method is replaced by a novel digital pulse control (DPC) method on the instantaneous power function of the engine. The DPC method converts the complex surface working conditions of the AEC engine of the hybrid vehicles into simpler pre-defined working condition lines of the DPC engine. Consequently, the multi-variable nonlinear technical problem of simultaneously optimizing real driving environment (RDE) fuel consumption and pollutant emissions of the ACE heavy truck is simplified into two decoupled quasi-liner optimization problems, and ensures the reduction of on-vehicle computing resources for real-time AI inference computation and the improvement of the optimal performance, the convergent rate, and the robustness of the corresponding fuel-saving algorithm for the trained ML model or the learned RL model. Ultimately, the ACE truck achieves in the engineering sense the global minimum RDE fuel consumption and pollutant emissions meeting the standard consistently at high performance to cost ratio for any transport event and the RDE fuel consumption is decoupled from the vehicle configuration parameters and the human driver.

The invention relates to the technical field of water environment management, in particular to a reservoir ecological scheduling method and system considering water quality dynamic response. The method comprises the following steps: acquiring reservoir water quality monitoring data; performing water eutrophication analysis according to the reservoir water quality monitoring data to obtain water eutrophication data; pollution source tracking is carried out based on the water eutrophication data to obtain pollution source data; the pollutant emission intensity is evaluated based on the pollution source data; a high-pollution area is calibrated according to the pollutant emission intensity; carrying out algae density detection according to the high-pollution area to obtain algae density data; performing water algal toxin analysis according to the algae density data to obtain water algal toxin data; and obtaining reservoir hydrological data, and carrying out maximum rainfall feature extraction to obtain maximum rainfall data. The response rate and the pollution risk identification rate of reservoir water quality dynamic scheduling are improved based on the water environment management technology.

The invention discloses a watershed multi-scale water quality target overall regulation and control method, which is characterized in that a regulation and control unit is delimited based on DEM data, a multi-scale spatial analysis framework is constructed through a hydrological topology and watershed nesting relationship, and the coupling process analysis of pollutant discharge, absorption and transportation is realized; deducing a water quality control target of each catchment area step by step through a process coupling reverse algorithm by taking a watershed outlet section water quality assessment target as a reference; dynamically quantifying a balance relation among pollutant discharge, land area system interception and river network system absorption based on a source-sink profit and loss intensity index, and realizing source-sink state diagnosis of different regulation and control units; and finally, generating a basin overall regulation and control scheme by delimiting a pollution emission hot spot area and a weak absorption capacity area and analyzing a regulation and control scene. The method can be widely applied to water environment refined treatment scenes such as river and lake water quality target management and pollution control zoning, and provides scientific basis and technical support for watershed water environment protection and overall restoration.

The invention discloses a real-time monitoring information system based on a thermal power plant and a control method, and relates to the technical field of thermal power plants, accurate operation control is realized through modular design, an as-fired coal quality data acquisition module synchronously acquires data of elements, minerals, moisture and volatile components by relying on LIBS, terahertz and microwave resonant cavities and other acquisition equipment, and the real-time monitoring information system and control method are applied to the thermal power plant. Calculating a coal quality evaluation value through an algorithm; a boiler combustion feed-forward control module formulates a graded combustion strategy according to the combustion parameters; the biomass blending combustion characteristic acquisition module acquires combustion, chemical and ash form indexes at a specific time point after a combustion strategy is adjusted, and analyzes a slagging risk assessment value in combination with a weight model; the blending combustion regulation and control strategy analysis module dynamically optimizes the biomass blending combustion proportion according to the slagging risk grade, and coordinated regulation such as air distribution and soot blowing is assisted. The system realizes coal quality-combustion-slagging full-chain data driving decision, improves the combustion efficiency and safety of a thermal power plant, and reduces the slagging risk and pollutant emission.

The utility model provides a peak-shaving steam supply system for deep waste heat utilization of a thermoelectric unit, which deeply recovers cold end waste heat and flue gas waste heat of a cogeneration unit, is coupled with a two-stage compression heat pump, extracts waste heat to heat demineralized water, and serves as a primary heat source for supplying industrial steam, so that the waste heat participates in external heat supply; the superheater utilizes the generating capacity of the unit to enable industrial steam to reach steam supply parameters, the waste heat of the unit and the generating capacity are combined for external steam supply, the circulating heat efficiency is improved, the steam supply capacity is improved, meanwhile, the on-grid electricity is reduced, thermoelectric decoupling is achieved, the unit adjusting operation interval is expanded, the operation cost and pollutant emission are reduced, and peak regulation or spot transaction earnings are improved. And a clean, low-carbon, flexible, efficient, economical and energy-saving combined heat and power generation system is constructed.

The invention belongs to the technical field of coal-fired boiler control, and particularly relates to a system and a method for dynamically regulating and controlling the structural design of a separated coal bunker and the blending combustion proportion of fire coal. According to the method, the correction coefficient is generated through the small-scale blending combustion experiment data, and the initial proportion calculation model is calibrated, so that the proportion design conforms to the theoretical constraint and adapts to the actual combustion characteristics of the coal type, and the theoretical and actual deviation is reduced; combustion efficiency and pollutant emission trend are predicted on line based on a fire coal combustion prediction model, dynamic adjustment of a fire coal blending combustion proportion is realized in combination with a progressive adjustment rule and an extreme working condition response rule, combustion parameter fluctuation is avoided, a verified alternative scheme is called, environmental protection and combustion stability are met, response time is shortened, and the method is suitable for large-scale popularization and application. The reliability in a fault state is improved; by automatically updating the fire coal combustion prediction model, prediction-adjustment-update closed-loop optimization is realized, the regulation and control error is gradually reduced along with the operation time, and the high regulation and control precision is kept for a long time.

The invention relates to the technical field of pollution treatment of livestock and poultry breeding, in particular to a pollutant emission prediction and management system for a livestock and poultry farm, which comprises a data acquisition and storage unit, a data processing unit, a data processing unit and a data processing unit, and is characterized in that the data acquisition and storage unit is used for acquiring multi-source data of the farm in real time; the influence factor calculation unit obtains key influence factors influencing water quality change and malodorous gas based on production data and facility operation data of the farm; the model prediction analysis unit generates a predicted value of pollutant emission by using a dynamic multi-dimensional pollutant emission prediction model, and key influence factors are introduced in the prediction process for correction; and the management decision-making unit judges the early warning level and generates a control instruction according to the early warning level. According to the system, accurate prediction of emission of malodorous gas and water pollutants is realized by constructing a dynamic multi-dimensional pollutant emission prediction model, and meanwhile, the system not only prevents excessive emission of pollutants in advance, but also is deeply integrated with aquaculture production management to guide actual aquaculture operation.

The invention relates to the technical field of sewage treatment, in particular to a multi-objective-based sewage plant construction parameter calculation method and device, electronic equipment and a storage medium, and the method comprises the steps: defining a plurality of objective functions including economic cost minimization, pollutant discharge minimization, social benefit maximization and ecological environment influence minimization, and constraint conditions are set. According to the method, a multi-target model covering economic cost, pollutant discharge, social benefit and ecological environment is constructed, an improved NSGA-II algorithm is adopted for solving, and multiple groups of Pareto optimal solution sets are generated in combination with rapid non-dominated sorting, crowding degree distance calculation and an elitist retention strategy, so that the optimal solution set is obtained. Therefore, a decision maker is supported to flexibly compare and select according to policy adjustment or budget requirements, scientization and high efficiency of sewage treatment planning are realized, and resource allocation accuracy and long-term sustainability are effectively improved.

The invention discloses a gas turbine multi-fuel reference real-time voting scheduling method, and relates to the technical field of gas turbine combustion control, and the method comprises the steps: constructing a plurality of fuel control references, carrying out the collection, integration and comparison of the output of each fuel control reference through a real-time voting control loop, and generating a final fuel control reference; according to the real-time monitoring result, intervention and quit of each fuel control reference are dynamically judged; the proportion of diffusion fuel and premixed fuel and the flow of each branch are controlled through a fuel distribution system, and gas turbine multi-fuel reference real-time voting scheduling is achieved. The fuel distribution proportion can be flexibly adjusted under different working conditions, the combustion process is optimized, fine combustion control of the gas turbine under different working conditions is achieved, the comprehensive performance and economical efficiency of the gas turbine are remarkably improved while the combustion efficiency is improved, pollutant emission is reduced, and the equipment safety is enhanced, and the method is suitable for popularization and application. The method has important application value and wide market prospect.

The invention discloses an analysis method of a pollution reduction and carbon reduction route in the traffic field, and belongs to the technical field of pollution reduction and carbon reduction. According to the method, population, economy, energy and atmospheric environment monitoring data and traffic source information of a target area or a city are collected, a localization analysis system based on an LEAP model is constructed, and precise checking is carried out in combination with an MOVES model. The energy consumption and pollutant emission under different emission reduction scenes are simulated and analyzed, the air quality model is combined to evaluate the carbon emission reduction and air quality improvement effect, and finally the optimal collaborative emission reduction scene is screened out. Based on the air quality target, the optimal scene and scheme are screened by using the cooperative control effect grading index method and the like, and finally the emission reduction path meeting the air quality target is obtained through optimal scene simulation, so that a more scientific, reasonable and comprehensive pollution and carbon reduction analysis method is provided for the traffic field; and the method has important practical guiding significance for realizing comprehensive green transformation.

The invention discloses a composite microecological preparation as well as a preparation method and application thereof. The compound microecological preparation disclosed by the invention comprises lactobacillus casei, lactobacillus plantarum and saccharomyces cerevisiae. The application effect of the composite microecological preparation in cow breeding is remarkable, the optimal addition amount of the composite microecological preparation is 100 mL / cow / day, the production performance of lactating cows can be improved, the milk yield is improved by 3.30 kg / cow / day, the milk yield of 4% standard milk is improved by 3.78 kg / cow / day, the total protein is improved by 15.9%, the albumin is improved by 14.7%, the globulin is improved by 16.5%, and the somatic cell number is reduced by 52.6%; and pollutant emission can be reduced, including 37.2% of ammonia emission reduction and 28.7% of carbon dioxide emission reduction.

The invention discloses a plateau region in-use motor vehicle pollutant emission evaluation method and system, and relates to the technical field of motor vehicle pollutant emission, and the method comprises the steps: carrying out the modeling of a target plateau region, generating a road model of the target plateau region, and obtaining the environment information of the target plateau region, respectively applying environmental factors in the environmental information to the road models to form a plurality of road models with independent environmental factors; respectively acquiring a current motor vehicle degradation coefficient of each road model with the independent environment factor, acquiring an accumulated driving mileage of the current motor vehicle, applying the accumulated driving mileage to the road model, and acquiring a current motor vehicle degradation coefficient based on the accumulated driving mileage; calculating a final degradation coefficient of the current motor vehicle in the target plateau area according to all the current motor vehicle degradation coefficients; and inquiring the emission factor of the current motor vehicle, and calculating the pollutant emission amount of the current motor vehicle in combination with the final degradation coefficient and the mileage.

The invention discloses a fire slash area-based straw open-air incineration pollutant emission amount estimation method, and relates to the technical field of air pollution prevention and control. According to the scheme, the method comprises the steps that a fire slash in satellite image data is extracted through a fire slash recognition model, the incineration area of a target crop is calculated through spatial intersection analysis, the pollutant emission amount of open-air incineration of straw of the target crop is obtained through calculation, and the fire slash is accurately recognized through the fire slash recognition model. And the accuracy of the estimated value of the pollutant emission is improved.

The invention discloses a mechanism and deep learning model-based dynamic working condition self-adaptive boiler closed-loop combustion optimization control method, system and device and a storage medium, and the method comprises the steps: designing a closed-loop control architecture through a mechanism constraint-data correction fusion modeling strategy and a self-adaptive MPC closed-loop architecture in combination with self-adaptive model prediction control; according to the method, collaborative optimization of combustion efficiency improvement and pollutant emission reduction is achieved, collaborative optimization of boiler combustion efficiency improvement and pollutant emission reduction is achieved, and physical interpretability and dynamic adaptability optimization control are achieved; the problems that a traditional method is poor in physical interpretability, insufficient in dynamic adaptability and low in control precision and the problems that due to strong nonlinearity, multi-parameter coupling and dynamic working condition fluctuation of an industrial boiler combustion system, the control precision is low, the physical interpretability is poor and the dynamic adaptability is insufficient are solved.

The invention discloses a vehicle emission conformity online evaluation method and device, a storage medium, equipment and an evaluation method, and the method comprises the following steps: obtaining a remote monitoring data flow of a to-be-evaluated vehicle in a preset time period, carrying out the preprocessing of the remote monitoring data flow, and generating a valid data set; identifying and segmenting a plurality of independent driving cycles from the effective data set, and screening out the independent driving cycles with cold start characteristics and engine accumulated work not smaller than a preset cycle work threshold value as effective driving cycles; dividing the data of each effective driving cycle into a plurality of preset working condition partitions according to the operating characteristics; aiming at each preset working condition subarea, adopting a corresponding calculation model, and calculating a pollutant emission result of the target pollutant; and comparing the pollutant discharge result of the target pollutant in each subarea with a corresponding preset discharge limit value for judgment. By using the scheme of the invention, low-cost, large-scale and high-frequency emission supervision is realized.

The application discloses a device for reducing fluorine-containing gas pollutant emission in electroslag remelting and a use method, which comprises a flue gas recovery cover (1), a flue gas discharge pipeline (7) and a purification tank (10). The flue gas recovery cover (1) is respectively provided with a remelted slag discharging hole (2), a self-consuming mother electrode (6) passing hole and a flue gas discharge pipeline (7) mounting hole. The flue gas discharge pipeline (7) is arranged through the flue gas discharge pipeline (7) mounting hole, one end of the flue gas discharge pipeline (7) is located in a closed space formed by the flue gas recovery cover (1) and a crystallizer (5), and the other end is inserted into the purification tank (10). A fan (8) is arranged on the flue gas discharge pipeline (7). Through the device, the fluorine-containing flue gas is recovered, and the fluorine-containing flue gas is converted into calcium fluoride by using an alkali solution. The device can realize the cyclic and repeated use of part of the calcium fluoride, greatly reduces the concentration of fluorine-containing harmful gas in the air environment of an electroslag remelting operation site, and makes the concentration of the fluorine-containing harmful gas reduce from the original 5.6 mg / m 3 to 0.02 mg / m 3 .

The invention relates to the technical field of lime manufacturing, and provides a process and a system for manufacturing high-purity lime. The process comprises the steps of raw material pretreatment, plasma surface pretreatment, segmented atmosphere calcination, sound wave reinforced mass transfer, heat energy comprehensive utilization and intelligent control, rapid cooling, flue gas treatment and finished product packaging. The system comprises a raw material pretreatment unit, a plasma surface pretreatment unit, a multi-section gradient atmosphere calcining kiln, a sound wave reinforced mass transfer system, a heat energy comprehensive utilization and intelligent control system, a carbon dioxide capturing and recycling unit and a finished product cooling and packaging unit. Through raw material deep purification, surface activation treatment, gradient calcination and atmosphere accurate control, sound wave mass transfer reinforcement, intelligent optimization regulation and control, rapid cooling and flue gas purification and resource recovery, the purity and the reaction activity of a calcium oxide product are synergistically improved, and the production energy consumption and pollutant emission are remarkably reduced; and high-efficiency, clean and resource production of the high-purity lime is realized.

The invention provides a device for monitoring a combustion process in real time, and belongs to the technical field of combustion process monitoring and control. The device comprises a multispectral light source module, an optical detection module, a data processing module and a control module. The multispectral light source module can emit multispectral signals covering ultraviolet, visible and infrared bands, and multiple paths of light beams are generated through light beam shaping, frequency doubling, optical parametric oscillation and the like and are incident to a combustion area. The data processing module performs feature extraction, mode recognition and trend prediction on the signals, and recognizes parameters such as flame state, temperature, gas concentration, combustion efficiency and pollutant emission. The control module dynamically adjusts operation parameters of the combustor according to the analysis result, and closed-loop control is achieved. Through multi-band spectrum joint detection and intelligent algorithm analysis, the defect that single-band detection is prone to interference is overcome, and high-sensitivity, multi-dimensional and real-time monitoring and intelligent control over the combustion process are achieved.

The invention discloses a 700MW CFB pollutant prediction method and system based on machine learning and K-means + + optimization. The pollutant prediction method comprises the steps of obtaining boiler operation data and pollutant emission concentration data; processing the boiler operation data and the pollutant emission concentration data to obtain key characteristic factors; the key feature factors are used for training a machine learning model, a K-means + + method is used for optimizing the machine learning model, a prediction model is obtained, and the prediction model is used for predicting the pollutant concentration in real time according to the boiler operation data. The invention aims to improve the prediction precision and efficiency, and provides a reliable basis for boiler operation optimization and pollutant control. According to the method, modeling is carried out on pollutant emission data through a machine learning model, and the model is optimized by using a K-means + + algorithm, so that the prediction performance is improved.

The invention provides a methanol-diesel dual-fuel engine knock control method, relates to the technical field of engine control, and aims to implement multi-cylinder independent control, realize differentiated control of each cylinder, independently collect and filter knock sensor signals of each cylinder, and improve the reliability of the engine knock control. Extracting the detonation characteristic intensity of each cylinder by using a fast Fourier transform and time domain integral analysis method; judging which level of response strategy threshold range the knock characteristic intensity is located in, and executing a response strategy of a matching level; and establishing an adaptive learning mechanism, and optimizing the threshold value of each level of response strategy. The method has the advantages that the knocking detection accuracy is remarkably improved, the optimal control boundary under different methanol mixing proportions is achieved through a self-adaptive learning mechanism, the problem of inconsistency of cylinders under the dual-fuel working condition is solved by adopting a differentiated cylinder control strategy, the engine safety is guaranteed, and the reliability of the engine is improved. Torque output under the full-load working condition is improved, the failure rate of knock-related parts is reduced, the service life of an engine is prolonged, and pollutant emission is reduced.

The mobile charging equipment comprises a semi-trailer type vehicle body, an energy storage compartment, a photovoltaic power generation and heat collection device, a solar photovoltaic panel, a storage battery pack, a heat collection device, a water electrolysis hydrogen production pool, a hydrogen storage tank, a boiler device, a steam turbine generator unit and a fuel cell power generation system. By integrating the technologies of solar power generation and heat collection, solid oxide water electrolysis hydrogen production, steam turbine unit power generation, fuel cell power generation and the like, convenient energy supplementation of the electric agricultural machine is achieved. The equipment is an efficient and environment-friendly energy supply platform, automatic control and remote management can be achieved, and operation convenience and efficiency are improved. Meanwhile, the steam turbine power generation and fuel cell technology is adopted to replace a traditional diesel generator, pollutant emission is reduced, and the requirements of green energy and sustainable development are met. In addition, the equipment can serve as energy storage equipment when being idle, peak load shifting of energy is achieved, and agricultural modernization and sustainable development are promoted.

The invention discloses a recovery mechanism for N-methyl pyrrolidone, and relates to the field of waste gas recovery, the recovery mechanism comprises a recovery tower body, the lower part of the recovery tower body is provided with a gas inlet main pipe, the outer wall of the gas inlet main pipe is provided with gas inlet branch pipes which are distributed at equal intervals, and the outer surfaces of the gas inlet main pipe and the gas inlet branch pipes are uniformly provided with gas inlet nozzles; a uniform spraying structure is arranged at the upper part of the recovery tower body and comprises a rotating disc rotationally mounted on the inner wall of the recovery tower body, spraying pipes distributed at equal angles are arranged on the outer wall of the rotating disc, spraying heads distributed uniformly are arranged at the bottoms of the spraying pipes, and a knocking structure is arranged at the bottom of the filler layer. And uniform contact between the recovered waste gas and the spraying liquid is realized. According to the recycling mechanism for the N-methyl pyrrolidone, through cooperation of the gas inlet structure, the uniform spraying structure and the knocking structure, waste gas containing the N-methyl pyrrolidone is efficiently recycled, meanwhile, resource waste is reduced, and emission of environmental pollutants is reduced.

The invention provides a thermal power plant coal fuel intelligent co-combustion optimization system, and relates to the field of coal fuel co-combustion, and the system comprises a coal fuel detection module which is used for detecting coal quality characteristic parameters of coal fuel; the coal fuel storage bin group module comprises a plurality of independent coal fuel storage bins, and each coal fuel storage bin is provided with a weighing sensor and a discharging flow adjusting valve; the intelligent coal blending module is used for generating an optimal coal blending scheme through a multi-objective optimization algorithm on the basis of detection data of the coal fuel detection module and in combination with a boiler combustion characteristic database; the coal blending control module is used for adjusting discharging flow adjusting valves of all the coal fuel storage bins according to the optimal coal blending scheme, and accurate coal blending is achieved; and the correction module is used for collecting coal fuel combustion state data and feeding back the data to the intelligent coal blending module for scheme dynamic correction. A multi-objective optimization algorithm is adopted to replace artificial experience decision, combustion efficiency, pollutant discharge and equipment operation and maintenance cost are optimized synchronously, and a coal blending scheme is optimized dynamically and iteratively.

The invention discloses a regional atmospheric pollution and carbon emission reduction cooperative benefit evaluation method, system and device, and relates to the technical field of atmospheric pollution and carbon emission reduction, and the method comprises the steps: carrying out the evaluation of the regional policy scene parameters of a target region based on a greenhouse gas-atmospheric pollution cooperative effect model according to the regional policy scene parameters of the target region; determining a pollutant emission list and PM2.5 space distribution concentration prediction data; based on a machine learning algorithm, determining O3 spatial distribution concentration prediction data according to the pollutant emission list and the PM2.5 spatial distribution concentration prediction data; calculating health benefits by adopting an environmental benefit evaluation model according to the PM2.5 spatial distribution concentration prediction data and the O3 spatial distribution concentration prediction data; and based on a life value method, calculating economic benefits according to health benefits. The method is high in evaluation efficiency, more comprehensive in evaluation, high in precision and good in practicability.

The invention provides a sludge-based composite fuel as well as a preparation method and application thereof. The sludge-based composite fuel is prepared from the following raw materials in percentage: 40-60% of dewatered sludge, 20-40% of biomass powder, 3-8% of a nano catalyst and 2-5% of a composite adhesive. According to the sludge-based composite fuel, sludge, biomass and other fuels are mixed according to a certain proportion, the nano-catalyst is added to improve the combustion performance of the sludge fuel, the composite adhesive enhances the forming strength and waterproofness of the fuel, the component proportion and process conditions are optimized, and the sludge-based composite fuel is prepared. The problems that traditional sludge fuel is low in heat value, poor in combustion stability, high in pollutant emission and insufficient in forming storage performance are solved.