59 results about "Emission intensity" patented technology

The application discloses a fluorescent probe molecule luminous intensity quantification method and system, and belongs to the technical field of fluorescent probes. The fluorescent probe molecule luminous intensity quantification method comprises the following steps: building an initial structure of a fluorescent probe molecule and performing molecular dynamics simulation, uniformly extracting a plurality of molecular conformations from a motion trajectory; performing excitation state property calculation on each molecular conformation, extracting an excitation wavelength and an excitation intensity corresponding to a maximum excitation state oscillator strength; performing excitation state geometry optimization on each molecular conformation, extracting an emission wavelength, an emission intensity and an emission energy; calculating a luminous intensity coefficient based on the wavelength parameter, the intensity parameter and the energy parameter; evaluating the luminous performance of the probe molecule according to the luminous intensity coefficient, and screening a probe molecule with the largest luminous intensity coefficient as a target probe. The application can convert a dynamic effective object which is difficult to directly measure into a numerical form which can be measured and calculated, and realizes the standardization, dynamicization and repeatable quantitative characterization of the luminous intensity of the probe molecule.

The application provides a power carbon emission monitoring method and system based on a power industry chain, wherein the method comprises the following steps: based on a pre-constructed power transmission network, obtaining a total carbon emission amount of a production end and network power loss of adjacent nodes in the power transmission network; and according to the obtained total carbon emission amount of the production end and the network power loss, monitoring carbon emission intensity of a consumption end in a target region. The method overcomes the defect that the actual value of the carbon emission intensity of the consumption end is low due to the fact that the power transmission and distribution process of the smart grid does not consider network loss and in-plant power consumption in the prior art, tracks carbon emission transfer caused by coal and power transactions from the perspective of the power industry chain, determines the flow direction of the power carbon emission, can realize real-time and accurate monitoring of the power carbon emission, and lays a solid foundation for the allocation of emission reduction responsibilities.

This invention provides a method for measuring and assessing carbon emission reduction in pumped storage systems for multi-energy complementary systems. The method establishes a day-ahead optimal scheduling model for a wind-solar-thermal-pumped storage multi-energy complementary system that considers economic benefits and carbon emissions. Based on carbon emission factors and the combined system output ratio, it calculates the carbon emission intensity of pumping and power generation processes in pumped storage on an hourly scale and proposes a method for measuring and assessing carbon emission reduction in pumped storage systems for multi-energy complementary systems. This method can provide support for understanding and assessing the environmental benefits of pumped storage in multi-energy complementary systems.

The application discloses a kind of based on Koopman and CEF model electric carbon collaborative scheduling method, system, medium and equipment, belong to electric power system optimization field, the method is: according to CEF model obtains the original expression of carbon intensity constraint;According to branch outflow power distribution matrix and diagonal matrix, reconstruct the original expression, obtain the nonlinear mapping relationship expression between node carbon emission intensity and node power injection, and according to low rank kernel approximation improved Koopman operator and node power injection dataset are processed, obtain linear mapping relationship expression;According to linear mapping relationship expression, construct electric carbon collaborative scheduling model, and based on electric power system current operation data, solve scheduling model, obtain scheduling optimization strategy;According to the strategy, regulate electric power system operation, complete electric carbon collaborative scheduling.Therefore, by implementing the present application, the problem of insufficient timeliness of electric power system in combination with carbon emission flow for electric carbon collaborative scheduling in the prior art can be solved.

The present application belongs to the technical field of data processing, and particularly relates to a method and system for dynamic monitoring of energy carbon based on multi-source data fusion, which comprises the following steps: collecting high-frequency energy data and low-frequency emission data of a target area, performing frequency-raising processing on the low-frequency emission data by using an interpolation algorithm, and performing standardization processing on the two types of data to obtain energy sequences and emission sequences with unified time resolution; calculating the causal fluctuation confidence of the energy sequences at each time, and constructing a cumulative distance matrix in combination with the causal fluctuation confidence; searching for an optimal alignment path of the energy sequences and the emission sequences by using a dynamic time warping algorithm, and calculating a local slope index at each path point; dynamically adjusting the observation noise covariance of Kalman filtering according to the local slope index, performing smoothing correction on the aligned emission data, and outputting the energy carbon monitoring result. The present application solves the problem of distortion in calculation of carbon emission intensity caused by phase misplacement of multi-source data.

Techniques for measuring single synaptic signals under varying experimental conditions include controlling a video recording microscope to capture, at multiple different times, a first imaged area in a sample holder as a video frame when the sample holder is disposed on a stage and holds a sample of neuronal tissue combined with at least one fluorophore that emits a corresponding electromagnetic wavelength in a synapse during synaptic activity. At least one synaptic region of interest is determined based on a group of pixels in the first imaged area that record electromagnetic emissions from the fluorophore at the different times. An ordered time series of emission intensity is recorded in each of the synaptic region of interest. Peak emission intensity values in the time series are corrected for transmitter label transients. The ordered time series with corrected peak emission intensity values are stored in a data structure with a standard format.

The application relates to the technical field of inorganic photoluminescence materials, and discloses a rare earth doped layered stannate-based white light fluorescent powder material and a preparation method thereof, a chemical molecular formula of which is A1-xSn2-xO6:Eu3+, wherein 0 < x <= 0.05, A is one or more divalent alkali earth metal ions in Ca, Sr and Ba, and is doped in different proportions, the A provides a red light emission component, the A provides a blue and yellow light emission component, the emission intensity of the red light and the blue and yellow light can be adjusted by regulating and the doping proportion, the ionic radius of the A is similar to that of the A, and the A substitutes the lattice position. Through the synergic doping of the A and the A and the proportion regulation, the charge compensation and the lattice position optimization of the A and the A are combined, the accurate matching of the red light and the blue and yellow light emission intensity of the fluorescent powder is realized, white light emission effects with excellent color rendering and stable color tone are obtained, and the problems of red light loss or light emission efficiency decay caused by the mixing of multi-color fluorescent powder in traditional white light LED fluorescent powder are effectively overcome.

This invention discloses a method and system for calculating the electricity carbon footprint factor of a regional power system, comprising: determining the initial electricity carbon footprint factor of the target regional power system; calculating the regional average power generation carbon footprint factor and the regional transmission and distribution carbon footprint factor based on the current electricity carbon footprint factor; determining a new electricity carbon footprint factor based on the sum of the current regional average power generation carbon footprint factor and the regional transmission and distribution carbon footprint factor; calculating the relative change between the current electricity carbon footprint factor and the previous electricity carbon footprint factor; and if the current relative change is less than a first preset threshold or the number of iterations is greater than or equal to a second preset threshold, using the current electricity carbon footprint factor as the final value of the regional power system's electricity carbon footprint factor. This invention can improve the accuracy, precision, and effectiveness of electricity carbon footprint calculation, providing effective support for the system assessment of the average carbon emission intensity of a regional power system.

The present invention pertains to a grain-oriented electrical steel sheet and a method for manufacturing same. The grain-oriented electrical steel sheet according to an embodiment of the present invention comprises: by wt %, a base material containing 2.5˜4.0 wt % of Si, 0.005 wt % or less of C, 0.015˜0.040 wt % of Al, 0.04˜0.15 wt % of Mn, 0.005 wt % or less of N, 0.03˜0.10 wt % of Sn, 0.05˜0.2 wt % of Cr, 0.010˜0.050 wt % of P, and 0.01˜0.05 wt % of Sb, with the remainder comprising Fe and inevitable impurities; and a metal oxide layer disposed on the base material, and has an average iron loss (W17 / 50) of 0.80 W / kg or less, wherein the maximum emission intensity ratio of the metal oxide layer may satisfy Expression 1.I⁡(Cr) / I_max⁢(Mg)≤2⁢%<Expression⁢ 1>(In Expression 1, I(Cr) is the intensity of Cr in the metal oxide layer, and I_max(Mg) denotes the maximum emission intensity of Mg in the metal oxide layer)

This invention provides a real-time carbon emission monitoring and early warning device for service enterprise equipment. The device includes two mounting brackets, an ultrasonic flow meter, a temperature sensor, and a control unit. Electrically connected to the ultrasonic flow meter and temperature sensor, it calculates the instantaneous thermal power of the equipment or pipeline in real time based on flow rate and the temperature difference between supply and return water. It also calls upon pre-stored carbon emission factors to calculate carbon emissions in real time. An early warning signal is issued when the carbon emission amount or intensity exceeds a set threshold. A data transmission module uploads real-time carbon emission data to a cloud platform or the enterprise's energy and carbon management center, thus relating to the field of carbon emission monitoring. The device has flow and temperature acquisition components and a control unit installed on the supply and return water pipelines respectively. It can be applied to thermal systems in various service scenarios such as air conditioning, boilers, and heat exchange stations. Installation is convenient and does not require large-scale modifications to the existing pipeline network.

The application relates to a control method of a tire pressure monitoring device and related products, and belongs to the technical field of tire pressure monitoring, wherein the method comprises the following steps: acquiring environmental noise information of an environment in which a tire pressure monitoring device is located; determining target emission parameters of the tire pressure monitoring device based on the environmental noise information; and controlling the tire pressure monitoring device to perform signal emission according to the target emission parameters. The method can solve the problems of signal reception reliability reduction and / or excessive emission end energy consumption caused by the fact that a fixed emission intensity cannot adapt to a dynamic interference environment.

Disclosed is a surface-treated steel sheet containing Ti and Al, and having improved post-paint corrosion resistance. The surface-treated steel sheet of this disclosure comprises a base steel sheet and a chemical conversion coating disposed on the surface of the base steel sheet. The chemical composition of the base steel sheet is, by mass%, Ti: 0.050 to 1.000% and Al: 0.050 to 2.000%. When elemental analysis of the surface-treated steel sheet of this disclosure is performed from the surface in the thickness direction by glow discharge emission spectrometry, the following relationships are satisfied: 1.1 ≤ I1 / I2 ≤ 20.0 and 1.1 ≤ I3 / I4 ≤ 5.0 (I1: maximum emission intensity for N in the chemical conversion coating, I2: average emission intensity for N in the base steel sheet, I3: maximum emission intensity for Ti in the chemical conversion coating, I4: average emission intensity for Ti in the base steel sheet).

A method of fabricating a superconducting wire includes forming a buffer layer on the substrate, the buffer layer including an Al2O3 layer, the Al2O3 layer being formed by reactive magnetron sputtering in which first oxygen gas as reactant gas and a sputtering target made of aluminium metal are used, the Al2O3 layer being formed while being supplied the first oxygen gas at a first concentration, the first concentration being a concentration of the first oxygen gas at which an emission intensity of Al in plasma near a surface of the sputtering target is not less than 25% and not more than 80% of a first reference value, the first reference value being the emission intensity of Al at which the concentration of the first oxygen gas is zero; and forming a superconducting layer above the buffer layer.

The application discloses a fluorescent probe molecule luminous intensity quantification method and system, and belongs to the technical field of fluorescent probes. The fluorescent probe molecule luminous intensity quantification method comprises the following steps: building an initial structure of a fluorescent probe molecule and performing molecular dynamics simulation, uniformly extracting a plurality of molecular conformations from a motion trajectory; performing excitation state property calculation on each molecular conformation, extracting an excitation wavelength and an excitation intensity corresponding to a maximum excitation state oscillator strength; performing excitation state geometry optimization on each molecular conformation, extracting an emission wavelength, an emission intensity and an emission energy; calculating a luminous intensity coefficient based on the wavelength parameter, the intensity parameter and the energy parameter; evaluating the luminous performance of the probe molecule according to the luminous intensity coefficient, and screening a probe molecule with the largest luminous intensity coefficient as a target probe. The application can convert a dynamic effective object which is difficult to directly measure into a numerical form which can be measured and calculated, and realizes the standardization, dynamicization and repeatable quantitative characterization of the luminous intensity of the probe molecule.

The application provides a high spatial resolution distribution map construction method and device of an electric carbon factor, relates to the field of new energy power generation dynamic monitoring, and comprises the following steps: analyzing the influence of wind and light injection power on the total carbon flow rate of a system according to a system topology structure and system operation parameters, obtaining a branch power flow injection matrix and a unit injection distribution matrix; determining system node carbon potential according to the branch power flow injection matrix, the unit injection distribution matrix and pre-calculated thermal power generation carbon emission intensity; and inserting the system node carbon potential into a layer after substation position fuzzy processing to obtain a high spatial resolution distribution map of the electric carbon factor. The application can calculate the hourly resolution carbon emission intensity of a source side thermal power unit by using the material balance method, obtain the power carbon emission factor of substations at different voltage levels in combination with power flow tracking based on the target regional network structure, further combine the coverage range of substations at different voltage levels, and draw a distribution map of the electric carbon factor by using a spatial allocation technology.

The application relates to an electric vehicle low-carbon scheduling method, device, equipment, storage medium and program product. The method comprises the following steps: firstly, constructing a power and traffic double network and initializing relevant parameters, simulating user travel and charging behavior by relying on a travel chain simulation system, and generating a charging load matrix; secondly, combining the network parameters, solving the optimal power flow of the power grid through a second-order cone programming, and obtaining the power flow distribution and active power output state of the generator set in the whole network; then, determining the power transmission proportion of the power supply to the load based on the Kirchhoff current law, combining the unit output and the carbon emission intensity to weightedly calculate the equivalent carbon emission intensity of the power supply node, and further obtaining the carbon emission amount set of each load node; finally, based on the node carbon emission amount and the time-sharing charging power of the charging station, an electric-carbon price strategy is formulated to perform low-carbon scheduling. The method can realize the tracing and responsibility determination of the carbon emission of the charging load; and through a node-level electric-carbon price combination strategy, the charging behavior of the electric vehicle is guided, and the overall carbon emission is effectively reduced.

The application provides a port atmospheric pollution source space fine analysis method, comprising: meteorological normalization analysis is carried out on the mass concentration data of various atmospheric pollutants of multiple monitoring points of the port respectively, and a demeteorized concentration sequence is obtained; the demeteorized concentration sequence is input into a positive definite matrix factor decomposition model, and a pollution source class with spatial uniformity distribution characteristics is extracted; a priori pollution source space distribution matrix is obtained based on prior knowledge composed of the pollution source class, a pollution source space distribution matrix, port pollution source emission information and activity level information; the demeteorized concentration sequence and the a priori pollution source space distribution matrix are input into a Bayesian multivariate receptor model, and a pollution source emission intensity space distribution and a time sequence are obtained; and based on the pollution source emission intensity and the spatial topological relationship of the multiple monitoring points, a high-resolution spatial distribution map of the pollution source emission intensity is generated. The application strips the meteorological influence, and realizes fine space description of the pollution source.

This invention discloses a carbon metering method and system for ultra-high voltage substations, belonging to the field of carbon emission monitoring and metering technology. It acquires equipment operating parameters and historical energy consumption data to construct an equipment energy conversion efficiency model; establishes a carbon emission factor matrix based on energy efficiency coefficients; dynamically estimates equipment carbon emissions using this matrix, generating equipment-level carbon emission estimation curves; integrates equipment topology and energy flow paths to establish a station-wide carbon emission correlation network; calculates the carbon emission intensity of the substation under different operating conditions; and outputs early warning information and executes load optimization or energy efficiency adjustment strategies when the carbon emission intensity exceeds a set threshold. This method achieves dynamic perception, structured expression, and intelligent response to substation carbon emissions, improving the accuracy of carbon emission monitoring and the level of energy efficiency management.

The application discloses a marine fuel full life cycle emission intensity accounting and certification method and related device, relates to the technical field of carbon intensity accounting and certification, and comprises the following steps: in the accounting, based on the accounting data, the first GHG emission intensity of the whole process from the raw material acquisition to the marine fuel on-board filling, the second GHG emission intensity of the marine fuel combustion process and the total GHG emission intensity of the marine fuel full life cycle are calculated. In the certification, the quality of the accounting data is inspected, the score of the accounting data in each dimension is determined, the comprehensive score of the accounting data is calculated, the first GHG emission intensity, the second GHG emission intensity and the total GHG emission intensity are corrected, the carbon intensity evaluation report and the carbon intensity certification certificate are generated, and are uploaded to the block chain. The application provides a method for realizing the full life cycle emission intensity accounting and certification of marine fuel under a unified, transparent and checkable technical framework.

The application discloses a carbon emission optimization method and system based on ESG, relates to the technical field of carbon emission optimization, and comprises the following steps: collecting data based on an ESG framework, calculating characteristic indexes, analyzing carbon emission flow value composition cooperation matrices of different emission points, calculating optimization values by using a geometric optimization function according to difference values and average adaptability values of analyzed areas of emission intensity, and combining the cooperation matrices to construct geometric constraint matrices as dynamic constraints. The method disclosed by the application further strengthens the analysis ability of differentiated cooperation between different emission points by calculating the difference values of emission intensity in the areas and the average adaptability parameters, and finally relates all emission points in the areas to the geometric constraint matrices by standardizing the maximum optimization values and the cooperation value constraints, so that the optimization direction of the emission point cooperation behavior is effectively ensured by taking the optimization values as weights to guide the behavior regulation and control between the points.

The application discloses a carbon emission intensity evaluation method and device based on dynamic area division, a terminal equipment and a storage medium, relates to the technical field of power grid analysis, and comprises the following steps: acquiring real-time operation data of a power grid and a winning amount of a new subject, wherein the real-time operation data comprises a node impedance matrix and a time sequence of net power injection of each node; calculating an electrical distance according to the node impedance matrix; calculating a power fluctuation similarity according to the time sequence of net power injection; constructing a comprehensive similarity matrix according to the electrical distance and the power fluctuation similarity, then constructing a Laplacian matrix and obtaining an eigenvector; dividing a sub-region through clustering; for each sub-region, determining a regional carbon emission factor according to the real-time operation data and the winning amount, and evaluating the carbon emission intensity. Through implementation of the application, the problem that the existing carbon emission factor calculation is limited by administrative regions and ignores the physical correlation of the electrical distance and power flow of the power grid can be solved, and the accuracy of carbon accounting results is improved.

The application discloses a carbon-aware collaborative optimization scheduling method and system for a virtual power plant, and belongs to the technical field of power system optimization operation and low-carbon scheduling. The method comprises the following steps: acquiring a multi-source input signal, wherein the multi-source input signal comprises an electricity market signal, a carbon market signal and real-time state data of distributed resources, wherein the carbon market signal comprises a real-time carbon price and a predicted value of system marginal carbon emission intensity in a future period; based on the real-time state data and the dynamic carbon signal, a resource unified digital image comprising an electricity adjustable capacity sub-model and a carbon emission reduction potential sub-model is constructed; a mixed integer linear programming model is established, taking the maximization of electricity-carbon comprehensive income as an objective and taking a conditional value at risk as a risk constraint, and is solved to generate an optimal scheduling plan; the optimal scheduling plan is executed by a real-time sensing-control module, and a device state is monitored in real time; when an abnormality is detected, a local compensation strategy is started, thereby forming a closed-loop control of "sensing-optimization-control-execution-feedback". The application realizes the collaborative optimization of economic benefits, environmental benefits and operation risks of a virtual power plant by deeply integrating a dynamic carbon signal and load flexibility, and ensures the robust execution of the strategy through a bottom-layer reliable control module, thereby improving the comprehensive benefits and operation reliability of the virtual power plant in an electricity-carbon integrated market.

The application belongs to the technical field of residential environment monitoring, and in particular relates to a residential environment monitoring platform and method based on unmanned aerial vehicle image acquisition, which comprises a water environment evaluation module, a vegetation environment evaluation module and a pollution evaluation determination module, wherein water runoff traces, vegetation coverage data and near-ground suspended particulate matter concentration distribution data are identified from unmanned aerial vehicle multispectral images, pollution bearing factors and basic pollution coefficients are respectively calculated, and finally the final pollution coefficient is obtained by correcting the basic pollution coefficient through the pollution bearing factor; different emission weights are given based on the attributes of each residential area, and the comprehensive environmental pollution degree of the residential area is output after weighted summation. The application highlights the pollution emission intensity of different attribute residential areas through differentiated weights, obtains the comprehensive environmental pollution degree, makes the mitigation evaluation result close to the actual situation, and provides data support for subsequent environmental governance.

The application relates to the technical field of energy control, in particular to a boiler combustion carbon reduction and pollution reduction control method, device, equipment, medium and program, wherein the method comprises the following steps: acquiring coal quality data, fly ash images and boiler operation parameters of a boiler; inputting the fly ash images into a carbon content prediction model, and outputting corresponding fly ash carbon contents by the carbon content prediction model; determining boiler efficiency and carbon emission intensity according to the coal quality data, the fly ash carbon contents and the boiler operation parameters; taking maximization of the boiler efficiency, minimization of the carbon emission intensity, minimization of operation coal consumption and minimization of nitrogen oxide emission concentration as targets, and calculating corresponding target control parameters under different working conditions; and controlling the boiler to perform corresponding carbon reduction and pollution reduction control operations according to the target control parameters. Therefore, the problems, such as low combustion efficiency, increased pollutants and carbon emissions, caused by the fact that the artificial experience and PID control strategy in the related art lead to combustion regulation lag and insufficient precision and are difficult to adapt to coal quality fluctuation and load change, are solved.

This invention discloses a method for evaluating the carbon emission index of a power grid supply chain based on multi-stage accounting, comprising the following steps: S1, dividing supply chain activities into four stages and calculating the annual supply chain carbon emissions for each stage; S2, summing the annual supply chain carbon emissions of the four stages to obtain the total carbon emissions of the power grid enterprise's supply chain; S3, constructing calculation models for the total supply chain carbon emission index, the supply chain carbon emission intensity index, and the overall supply chain data quality index; S4, constructing a calculation model for the annual supply chain carbon emission comprehensive index and calculating the annual supply chain carbon emission comprehensive index. This method addresses the problem that existing power grid supply chain carbon emission index evaluation methods lack a comprehensive evaluation system that integrates total emissions, emission intensity, and data quality.

The application provides a terahertz emitter film structure based on a Ni / Cr / Ti metal heterostructure and an ion irradiation enhancement method thereof, a substrate material is glass, and a ferromagnetic layer of a Ni film, an intermediate functional layer of a Cr film and a protective layer of a Ti film are sequentially deposited on the surface of the substrate material. The ion irradiation enhancement method comprises the following steps: a ferromagnetic layer of a Ni film, an intermediate functional layer of a Cr film and a protective layer of a Ti film are sequentially deposited on the surface of the substrate material by adopting a magnetron sputtering deposition method, and an intermediate product on which the three metal film layers are deposited is subjected to ion irradiation. The beneficial effects are as follows: the Cr film layer is used to realize ultrafast current transients under femtosecond laser excitation and generate terahertz radiation. The metal film is subjected to ion irradiation treatment, and the terahertz emission intensity is significantly improved.

The application relates to the technical field of intelligent operation and maintenance and green manufacturing of semiconductor manufacturing equipment, and discloses a predictive maintenance and carbon emission reduction collaborative control method and device for a semiconductor test process, which comprises the following steps: controlling a collaborative robot to collect multi-source operation data of equipment; performing wavelet denoising and fast Fourier transform to extract a frequency spectrum feature set, and judging abnormal features based on a dynamic threshold; inputting the frequency spectrum feature set into an LSTM or a Transformer model to predict the remaining service life and generate a fault warning; obtaining production plans and energy consumption data, constructing a multi-objective optimization function with the minimum maintenance cost and carbon emission intensity as the target, and adopting a Pareto optimization solution to generate a collaborative control strategy; adjusting equipment parameters and executing maintenance instructions according to the strategy, and recording data for model updating. The device comprises corresponding modules. The application realizes the collaborative control of predictive maintenance and carbon emission reduction in the semiconductor test process, improves the reliability of the equipment, and reduces carbon emissions.

The application provides a data intelligent analysis method and system applied to carbon emission monitoring, and comprises the following method: a dynamic non-negative row vector is obtained by executing an NMF load decoupling algorithm, the dynamic non-negative row vector comprises a resident coefficient and an industrial coefficient, carbon emission intensities of residents and industries corresponding to a current period are calculated according to the non-negative row vector and a space-time database, and are updated to the space-time database; future carbon emission prediction values corresponding to future different periods are calculated and generated according to the space-time database; and abnormality detection calculation is performed according to the carbon emission intensity and the future carbon emission prediction values corresponding to the current period. By using the above method, the carbon emission intensity situation of the whole region can be indirectly reflected intuitively, in real time and in a non-falsifiable manner.