25 results about "Surface wind speed" patented technology

The invention provides a photovoltaic power generation optimization method for a fishing-light complementary site and a related device. The method comprises the following steps: acquiring a photovoltaic panel sunlight angle, a water surface wind speed, a water surface wave height, a water depth, a photovoltaic panel core parameter, a reflector parameter and double-measuring-point actually-measured light intensity data; determining the initial receiving radiation quantity of the photovoltaic panel according to the sunlight angle of the photovoltaic panel, the core parameters of the photovoltaic panel, the parameters of the reflector and the actually measured light intensity data of the double measuring points; according to the water surface wind speed, the water surface wave height, the water depth, the double-measuring-point actually-measured light intensity data and the reflector parameters, the water surface correction reflection coefficient is determined; correcting the initial received radiation quantity of the photovoltaic panel by adopting the water surface correction reflection coefficient to obtain the actual received radiation quantity of the photovoltaic panel; and according to the actually received radiation quantity of the photovoltaic panel, the inclination angle of the photovoltaic panel is adjusted, and then the photovoltaic power generation process of the fishing-light complementary site is optimized. Excessive concentration of local radiation quantity caused by secondary reflection of sunlight through a water surface-reflector can be avoided, and generation of hot spots on the photovoltaic panel is inhibited.

The invention relates to the technical field of laboratory air ventilation, in particular to a ventilation cabinet airflow dynamic response optimization method based on digital twinning. The specific implementation process comprises the following steps: collecting a state vector sequence to predict a window motion track, identifying an operation intention and generating a virtual boundary condition; constructing a fluid mechanics digital twinborn model to simulate airflow dynamic characteristics, calculating and outputting airflow prediction data including a fluid resistance coefficient and turbulence intensity distribution, and generating an airflow optimization instruction for minimizing surface wind speed fluctuation by using a heuristic search algorithm; and monitoring a virtual-real deviation value, triggering a dynamic correction mechanism when a drift interval is exceeded, and carrying out online transfer learning on model parameters by utilizing the updated state vector sequence. According to the method, the risks of response lag and airflow oscillation are reduced through window trajectory prediction and digital twinborn simulation, meanwhile, errors caused by equipment aging are corrected through an online transfer learning mechanism, and the use precision and safety of long-term operation of the laboratory fume hood are ensured.

The invention discloses a multi-source data fusion-based air volume dynamic adjustment method of a fume hood for a clean environment, particularly relates to the technical field of clean environment control, and aims at solving the problem that air volume adjustment of an existing fume hood cannot give consideration to front air suction safety, pressure difference stability and overall energy conservation. A basic operation data set is formed by collecting and filtering window opening and cabinet air speed, an air volume demand value and an initial priority parameter are calculated according to the data set and a room use state mark to form a demand data set, and a deviation memory parameter and a fluctuation influence parameter are calculated by fusing room pressure difference data and the availability of an exhaust fan. Obtaining a stable control priority adjustment coefficient through a time decay score learning model, correcting the priority, distributing the target exhaust air rate and the exhaust fan output, forming a target distribution result, comparing the target distribution result with the actual air valve opening degree and the exhaust fan output state, calculating the adjustment amount, and issuing a control instruction according to the priority; and the deviation record feedback updating coefficient and the demand value are verified in the control period to realize self-adaptive adjustment.

The application discloses a photovoltaic sand-fixing device and a sand-fixing method, and belongs to the technical field of photovoltaic sand control. The device comprises multiple rows of protection units. The protection unit comprises a photovoltaic panel, a support, a foundation pile and a sand-fixing net. The foundation pile is provided with a pre-embedded part, and the pre-embedded part is connected with a pressing strip plate. The pressing strip plate presses the sand-fixing net on the pre-embedded part. The sand-fixing net is arranged between the foundation piles, so that the ground wind speed can be reduced, the wind sand can be effectively blocked, the construction operation is facilitated, the material cost is reduced, the change of terrain is adapted, the growth of vegetation is not hindered, the sand-fixing net is pressed tightly on a strip surface, the service life of the sand-fixing net at the connecting position is longer, and the connection is more stable. The sand-fixing net is continuously laid on one row of protection units, so that the installation is rapid and simple. When partial damage occurs, a section of the sand-fixing net between two foundation piles can be replaced individually, so that the replacement is simple and fast, the entire sand-fixing net does not need to be replaced, and the maintenance cost is low.

The invention provides an earth surface wind speed prediction method based on multi-source data and spatio-temporal feature fusion, and belongs to the technical field of meteorological prediction and computer cross, and the method comprises the following steps: S1, carrying out the preprocessing of a data set; s2, utilizing a TC-ResNet module to extract spatial and temporal characteristics of the wind speed data; s3, a time sequence dynamic mode of the data is mined through a TE-Liquid Time-Constance Networks module, and a time sequence dynamic mode of the data is mined through a TE-Liquid Time-Constance Networks module; s4, splicing features through a gating fusion mechanism, calculating weights, and inputting the weights into MLP for surface wind speed prediction; s5, Bayesian optimization hyper-parameters are adopted, and in combination with an adaptive moment estimation (AdamW) optimizer with weight attenuation, cosine annealing learning rate scheduling and smooth L1 (SmoonL1Loss) loss function optimization model training are carried out; and S6, performing short-term surface wind speed prediction on the test set by using the trained model. The method has the advantage that the accuracy of surface wind speed prediction under the complex terrain is improved.

The application relates to a building shape optimization method, which comprises the following steps: in a first case, determining an optimized first value of a first parameter of a target building according to the value of a first index of the target building under a first candidate value of the first parameter, the first index comprising the following first index items: a roof average wind pressure coefficient, an average wind pressure coefficient difference between a windward surface and a leeward surface, and building heating energy consumption; and in a second case, determining an optimized second value of a second parameter of the target building according to the value of a second index of the target building under a second candidate value of the second parameter, the second index comprising the following second index items: a proportion of detection points with a surface wind speed less than a non-snow accumulation wind speed, a proportion of detection points with a roof wind speed less than the non-snow accumulation wind speed, and a proportion of detection points with a ground wind speed less than the non-snow accumulation wind speed.

The invention relates to the technical field of agricultural ecological environmental protection, and discloses a desertification farmland soil wind erosion monitoring system which comprises a controller, a wind direction self-adaptive sand collection unit and a multi-dimensional monitoring unit, and the wind direction self-adaptive sand collection unit and the multi-dimensional monitoring unit are electrically connected with the controller. The wind direction self-adaptive sand collecting unit comprises a fixed pile, a rotating base is arranged on the fixed pile, a main rod is arranged on the rotating base, a wind direction sensing assembly is arranged at the top of the main rod, multiple stages of sand collecting channels are uniformly arranged in the circumferential direction of the main rod, the inlet heights of the sand collecting channels are sequentially increased in the vertical direction, and a layered collecting box is arranged at the end, away from the inlet, of each sand collecting channel; the multi-dimensional monitoring unit comprises a near-surface wind speed monitoring assembly, a soil loss amount detection assembly and an environmental parameter acquisition assembly, the near-surface wind speed monitoring assembly comprises at least three wind speed sensors, and the heights of probes of the wind speed sensors are in one-to-one correspondence with the heights of inlets of the sand collection channels. According to the system, accurate, efficient and long-term acquisition of data such as the soil wind erosion amount and the particle structure of the desertification farmland is realized.

The invention discloses a construction method of a desert road composite sand prevention system, which belongs to the technical field of desert road sand prevention, and comprises the following steps of: measuring and paying off sand on two sides of a roadbed, and laying a composite system consisting of grass checkered sand barriers and high standing sand barriers; the reeds soaked with the bio-based sand solidification agent are laid to form grass checkered sand barriers, and the reeds are pressed into a sand layer; a high vertical sand barrier is arranged on the outer side of the grass checkered sand barrier, the high vertical sand barrier is formed by combining reed bundle sand barriers and PE nylon net sand barriers at intervals, and the surface of the PE nylon net is coated with an anti-ultraviolet composite coating; the high-standing sand barrier takes a timber pile as a stand column, and a wind speed sensor and a wind erosion flux sensor are mounted at the top of the timber pile; during construction, a fireproof isolation belt filled with a flame-retardant ecological blanket is arranged in the direction of a route. Through composite arrangement of the grass checkered sand barriers and the high standing sand barriers, a multi-layer and three-dimensional wind prevention and sand fixation structure is formed, the near-surface wind speed is effectively reduced, starting and transportation of sand grains are inhibited, and the overall wind erosion resistance of the system is remarkably improved.

The invention discloses a method for irrigating a wild jujube ecological economic forest in an extremely arid flowing desert area by using underground brackish water, and relates to the technical field of desertification control and ecological restoration. According to the method, through the steps of land pretreatment, herbaceous plant sowing and management, wild jujube sowing, field management and the like, the ecological economic wild jujube forest is successfully constructed in the extreme drought flowing desert area, especially in the area where fresh water resources are deficient but the salinity (M) is larger than or equal to 5g / L and underground brackish water resources are rich in reserves; the near-surface wind speed can be reduced by more than 50%, and sand burying can be resisted; the survival rate of the wild jujube under the irrigation of brackish water with M greater than or equal to 5g / L can be increased to 85% or above; herbaceous income can be obtained in a short period, a deep processing industry chain is extended based on wild jujube for a long period, and forest cultivation by forest is realized; meanwhile, vegetation coverage is increased, desertification is restrained, and desert land is promoted to be transformed into ecologicalization and economization from wasteful transformation; and a sustainable and developable economic mode is realized.

The invention relates to the technical field of wind speed forecasting in an icing period, and discloses a wind speed forecasting method, system, equipment and medium for a complex terrain icing period based on large eddy simulation, and the method comprises the steps: inhibiting non-physical terrain noise through verifying the reliability of actually measured wind speed data and obtaining high-precision terrain data, and obtaining a wind speed forecasting result; the designed model can reflect the influence of the actual terrain on the wind speed more accurately, and in addition, the optimal scheme can be selected only through simulation and quantitative evaluation when the boundary layer parameterization scheme is selected. And by designing a WRF-LES simulation architecture of a multi-layer nested grid, a wind field environment and an icing sensitive core area of a complex terrain area are reasonably simulated, so that a feedback effect of an icing state on a local wind field can be analyzed. And a WRF-LES model is operated based on the model, so that an icing period surface stratum wind speed forecast field can be generated, and a final forecast effect can be obtained through post-processing output.

The application relates to the technical field of power systems, and provides a power distribution system disaster risk assessment method and device under typhoon disasters and electronic equipment. The method comprises the following steps: inputting geographic information data and typhoon trajectory parameters of a power distribution system; initializing the operation state of each feeder of the power distribution system; calculating the disaster resistance of each feeder; constructing a dynamic typhoon wind field model based on the geographic information data and the typhoon trajectory parameters, and solving the surface wind speed at the position of the feeder; comparing the surface wind speed with the disaster resistance, updating the feeder fault state based on the comparison result; calculating the power outage evaluation index of the power distribution system based on the updated feeder fault state, and returning to the step of initializing the operation state of each feeder of the power distribution system until a preset simulation end condition is reached, and outputting the power outage evaluation index. Through the iteration mechanism of dynamic wind field modeling and disaster resistance comparison, the disaster simulation resolution is self-adaptive, the accuracy is high, more scientific decision support is provided, and the power distribution system flexibility is enhanced.

The present application relates to a kind of urban overhead weather risk assessment method and system, wherein the urban overhead weather risk assessment method includes the following steps: determining the spatial location information corresponding to target evaluation object;Obtain the near-surface wind speed forecast data of target evaluation object in preset prediction period;Based on the wind speed mapping relationship library constructed in advance, the near-surface wind speed forecast data is converted into the high-altitude wind speed data of the spatial location where target evaluation object is located, the height layer where it is located;According to high-altitude wind speed data, in combination with preset risk level threshold, the high-altitude wind risk assessment result of target evaluation object is output;The present application realizes the quick conversion of near-surface wind speed data to high-altitude wind speed data by constructing wind speed mapping relationship library in advance, without re-running complex three-dimensional wind field model at each evaluation time, significantly improve the calculation efficiency of high-altitude wind risk assessment.

The invention belongs to the field of power grid disaster assessment and prediction, and particularly relates to a risk assessment method, device and equipment for power grid facilities caused by cold waves and strong wind and a medium. The method comprises the following steps: firstly, acquiring numerical weather forecast data, and carrying out aerodynamics processing by adopting a model comprising cold advection, vertical motion, wind shear, turbulent kinetic energy and terrain effect analysis to obtain a cold wave strong wind evolution mechanism analysis result; quantitative prediction is carried out based on the mechanism analysis result, and a strong wind prediction result containing the near-surface wind speed and the system movement trend is obtained; and finally, carrying out risk assessment in combination with power grid facility parameters, and outputting a wind load risk index, a galloping wind vibration assessment conclusion and a space-time evolution path of a risk area. According to the method, the defects that in the prior art, mechanism analysis in a wind field is insufficient, and risk assessment and a physical process are disjointed are overcome, and the crossing from a physical mechanism to accurate risk assessment is achieved.

The invention relates to the technical field of wind power plant simulation, and discloses a wind power plant and power grid bidirectional coupling dynamic simulation system, method and device and a medium, and the wind power plant and power grid bidirectional coupling dynamic simulation system comprises a wind field level controller, a power grid model and a wind power plant station model. The wind power plant station model comprises a wind flow field module and at least one fan module; the at least one fan module is respectively connected with the wind field level controller, the power grid model and the wind flow field module; the air flow field module is configured to obtain the wind wheel face wind speed of the current time step and output the wind wheel face wind speed to the fan module; the fan module is configured to obtain fan power information of the next time step according to the wind wheel surface wind speed of the current time step and an instruction signal of the current time step of the wind field level controller; the power grid model is configured to obtain power supply parameters of the at least one fan module in the next time step according to the fan power information in the next time step; the application scene of dynamic simulation of the wind power plant is expanded, and the dynamic simulation accuracy is improved.

The application discloses a mixed material sintering speed equalization method and relates to the technical field of sintering. When the material surface wind speed difference between the transverse center area and the air extraction area of a sintering machine exceeds a preset wind speed difference threshold value, the mixed material in the center area of the mixed material distribution area is shunted to the periphery of the center area of the mixed material distribution area, which plays a role of loosening the material in the center area of the mixed material distribution area, improves the permeability of the mixed material in the center area of the mixed material distribution area, and further improves the permeability of the mixed material in the transverse center area of the sintering machine, the material surface wind speed in the transverse center area of the sintering machine, and the sintering speed of the mixed material in the transverse center area of the sintering machine, so that the sintering speed is more uniform.

The application discloses an intelligent identification method and device for distinguishing dry sand from wet sand by using multispectral data, and belongs to the technical field of remote sensing monitoring, and comprises the following steps: acquiring a geometric distortion coefficient based on an instantaneous field of view angle of imaging, resolution and ground surface wind speed; acquiring a background heterogeneity coefficient based on the bulk density of sand surface, porosity and salinity; acquiring a surface pollution coefficient based on the coverage rate of algal and microbial film and the coverage degree of coexisting impurities; further combining atmospheric aerosol optical thickness, sand particle size median value and volume percentage of main mineral components to construct an atmosphere-particle-component matching model and acquire matching parameters; and finally, acquiring the target effective spectral channel number by a channel optimization model based on the matching parameters, the current effective spectral channel number and the background heterogeneity coefficient. The application realizes the fusion evaluation of multi-source influencing factors through multi-level system modeling, and significantly improves the precision and environmental adaptability of dry and wet sand identification.

The present application relates to renewable energy assessment and weather forecasting technical field, especially to a kind of wind and light resource fine estimation method based on numerical simulation and observation constraint. Global climate model driving field set is constructed, and the optimal GCM combination is screened out;Regional climate model framework is constructed;High spatio-temporal resolution simulated wind speed and solar radiation data are obtained;Generate kilometer level, hourly wind and light resource data set of history and future. The present application provides a kind of wind and light resource fine estimation method based on numerical simulation and observation constraint, by introducing high resolution, multi-source fusion ground surface wind speed and solar radiation long sequence historical observation data, using quantile mapping method to carry out systematic deviation correction to simulation result, realize statistical downscaling processing under the observation data constraint, finally obtain the wind resource data with 5 kilometers horizontal resolution, so as to significantly improve the high spatio-temporal resolution information capture ability to future wind resource change.

The invention relates to the technical field of renewable energy evaluation and weather forecast, in particular to a wind and light resource refined estimation method based on numerical simulation and observation constraint. Constructing a global climate mode driving field set, and screening out an optimal GCM combination; constructing a regional climate mode framework; acquiring simulated wind speed and solar radiation data with high temporal-spatial resolution; and generating kilometer-level hour-by-hour historical and future wind and light resource data sets. According to the wind and light resource fine estimation method based on numerical simulation and observation constraint provided by the invention, systematic deviation correction is carried out on a simulation result by introducing high-resolution and multi-source fusion earth surface wind speed and solar radiation long sequence historical observation data and adopting a quantile mapping method; statistical downscaling processing under the constraint of observation data is achieved, wind resource data with the horizontal resolution reaching 5 kilometers are finally obtained, and therefore the capacity of capturing high-temporal-spatial-resolution information of future wind resource changes is remarkably improved.

The application discloses a kind of based on Fengyun polar orbit meteorological satellite South China Sea summer monsoon double-index monitoring method, this method obtains 850hPa atmospheric temperature and specific humidity by polar orbit meteorological satellite FY-3D vertical detection instrument group VASS, 850hPa false equivalent potential temperature index is calculated;Ocean surface wind speed and wind direction are obtained by ocean surface wind field data of the wind field measurement radar WindRAD inversion of polar orbit meteorological satellite FY-3E, average zonal wind index is calculated;By evaluating the accuracy of FY-3D / VASS temperature and specific humidity relative to ERA5, and the accuracy of ocean surface wind of FY-3E / WindRAD relative to MetOp-C / ASCAT is evaluated index, the accuracy of the double-index monitoring South China Sea summer monsoon outbreak process is verified from the evaluation result.The application uses FY-3D to calculate false equivalent potential temperature and FY-3E ocean surface wind double-index monitoring South China Sea summer monsoon, double-index is well monitored 2022 South China Sea summer monsoon outbreak process temperature and humidity field and wind field conversion, so as to verify the application ability of two kinds of satellite data in South China Sea summer monsoon climate monitoring.

The present application relates to the technical field of airflow optimization, in particular to an airflow optimization method for a shell drying system. The method comprises the following steps: obtaining environmental parameters in a shell drying cabin through experimental testing, and performing data analysis on the environmental parameters using standard deviation and coefficient of variation; establishing a CFD simulation model based on Navier-Stokes equation, setting initial CFD simulation model to identify steady-state distribution data of shell surface wind speed, temperature and humidity; determining local airflow insufficient area based on the CFD simulation model, optimizing fan quantity and air supply angle; introducing a brand-new drying environment wind field vector airflow organization and adjustment device, a centralized rotary dehumidification system and an automatic air volume control strategy; and performing experimental verification on the optimized shell drying system again. The airflow optimization method for the shell drying system realizes accurate control of airflow and humidity by combining the wind field vector airflow organization and adjustment device and the centralized rotary dehumidification system with the automatic air volume control strategy.

The utility model relates to a kind of field use small direct-current blowing formula sand wind tunnel, its structure includes air inlet round pipe, fan, square round deformation pipe, honeycomb rectifier, square mouth contraction pipe and several experimental wind channel, square round deformation pipe, honeycomb rectifier and square mouth contraction pipe are sequentially connected;The air inlet round pipe includes straight pipe section and elbow section, elbow section forms the air inlet of bending and upwarping, the air inlet round pipe is provided with the flange baffle of height higher than the upper edge of air inlet outside air inlet, soft connecting pipe is provided between air inlet round pipe and square round deformation pipe.The utility model is easy to install, tough and durable, data stable, wind speed measurement accuracy is high, frequency is big, and experimental data can be automatically stored by data acquisition box, overcome the existing wind tunnel generally existing cannot conveniently, quickly, accurately, high-frequency measurement near-surface wind speed profile difficult problem, suitable for soil wind erosion and dust release characteristics and the identification research work of main dust source.

The invention discloses a field near-surface high-frequency wind-sand-dust collaborative observation system and monitoring method, and relates to the technical field of environmental monitoring, and the method comprises the steps: obtaining a complete vertical structure of near-surface wind speed, sand-dust concentration and sand transport flux through a data collection module, aligning the observation of multiple sources and different heights into a unified spatial-temporal scale through a preprocessing module, and carrying out the observation of multiple sources; a continuous vertical profile is constructed, a mode analysis module identifies typical sand and dust release modes from various profiles and extracts quantifiable mode characteristic parameters, and a coupling modeling module establishes quantitative mapping between wind field dynamic characteristics and sand and dust release modes by capturing the influence of wind speed pulsation and turbulence intensity on sand and dust response. Through systematic observation and analysis, the internal corresponding relation between the wind field power and the sand and dust release mode and the vertical structure of the sand and dust release mode can be quantitatively reflected, and a basis can be provided for sand and dust release analysis and prediction.

The present application relates to a kind of automatic block mine car thermal management system matching method and thermal management system.The present application constructs heat dissipation demand calculation model to calculate the heat dissipation demand under different working conditions under heavy load working condition, heavy load working condition, start-up variable torque condition;A one-dimensional cooling simulation model is established for the automatic block mine car thermal management system;Three-dimensional simulation model is established by applying the three-dimensional numerical model of vehicle and fan performance data, the surface wind speed distribution of radiator under different working conditions, vehicle speed and fan speed is calculated, and the surface wind speed distribution of radiator is imported into one-dimensional cooling simulation model;The radiator heat dissipation, oil cooler heat dissipation, radiator outlet water temperature and oil cooler outlet oil temperature under heavy load working condition, heavy load working condition and start-up variable torque condition calculated by applying the one-dimensional cooling simulation model are matched with heat dissipation demand, engine water temperature demand and gearbox oil temperature demand, and the matching result of the automatic block mine car thermal management system meeting the requirements is obtained by continuous iteration calculation.

The invention discloses a terrace side wall lateral evaporation blocking control and yield increasing binary covering method and structure, and belongs to the technical field of dry farming water and soil conservation. In order to solve the problems of lateral migration of soil moisture and low edge yield caused by strong evaporation of terraced field ridges (side walls), the method adopts a'straw and sunscreen net 'binary coupling covering mode. The structure comprises a flat soil substrate layer, a diffusion resistance layer formed by crop straws, and a radiation decoupling and fixing layer formed by a black HDPE (High-Density Polyethylene) sunscreen net from inside to outside. According to the method, lateral evaporation is effectively inhibited and the transverse water potential gradient in the terrace is eliminated through multiple synergistic mechanisms such as radiation interception and cooling by the sunscreen net, water vapor diffusion resistance increase by the straw layer and near-surface wind speed weakening by the composite structure of the sunscreen net and the straw layer, so that soil moisture homogenization is realized, and the yield of crops at the edge of the terrace and the rainfall utilization efficiency of the system are remarkably improved. The method is low in cost, easy to construct, eco-friendly and suitable for dry farming terraced fields such as loess plateau.

The invention provides a near-surface wind speed prediction method based on a self-supervised neural network. The method comprises the steps of constructing a near-surface wind speed prediction model, training the near-surface wind speed prediction model based on a preset data set, and performing near-surface wind speed prediction based on the trained model. According to the method, a self-supervised neural network structure is adopted, and an existing gridding ground data set is combined, so that global climate mode simulation deviation is corrected, the prediction precision of the near-surface wind speed is improved, and the method is convenient to use.