58 results about "Sunshine duration" patented technology

The invention provides a photovoltaic array layout method and system based on mountain topography, and relates to the field of photovoltaic array layout, and the method comprises the steps: obtaining the gradient, the slope direction, the vegetation coverage rate and the current sunshine duration corresponding to each sub-grid region; inputting the gradient, the slope direction, the vegetation coverage rate and the current sunshine duration corresponding to the sub-grid region to a preset photovoltaic installation preset model to obtain a layout expected value; determining the layout areas as expected layout areas, splicing all the expected layout areas with the adjacency relation to obtain all to-be-laid areas, and removing the to-be-laid areas with the area smaller than a preset area to obtain all removed areas; and by taking generation power maximization, shadow shielding loss minimization and photovoltaic module installation total cost minimization as objective functions, outputting a layout optimal solution by using a genetic algorithm, and performing photovoltaic array layout on the region after elimination by using the layout optimal solution. According to the method, the suitability of each sub-grid region is accurately evaluated, so that the accuracy of the photovoltaic array layout is improved.

The invention provides a drought and flood sudden turning event identification method, device and system, and relates to the technical field of water resource management, and the method comprises the steps: determining a research region and time period, collecting rainfall, sunshine duration, wind speed, pressure, humidity and air temperature data, carrying out the linear difference of vacant data, and carrying out the data preprocessing; constructing a rainfall difference comparison index for judging the sudden change degree of the drought and flood sudden change event; calculating a standardized rainfall evapotranspiration index for judging and identifying drought and flood events; establishing a grading standard of drought and flood events, and classifying the severity of the identified drought and flood events; and combining the rainfall difference comparison index with a standardized rainfall evapotranspiration index to construct a drought and flood sudden turning index for analyzing the sudden turning intensity. According to the method, the influence of rainfall intensity change on the flood disaster event is fully considered, and the occurrence process and severity level of the drought and flood sudden change event can be effectively and accurately identified.

The invention relates to an intelligent power transformation micro-station equipment energy consumption prediction method based on a symbolic regression algorithm, and the method comprises the steps: selecting the daily average temperature # imgabs0 #, the daily average humidity # imgabs1 #, the sunshine duration t and the traffic flow VF as four input features which affect the daily total energy consumption of an intelligent power transformation micro-station; three modules of a symbol regression algorithm based on adaptive iteration and control variable genetic programming: an adaptive iteration module, a control variable module and a genetic programming algorithm module are used for training a standard genetic programming algorithm; and inputting the sorted historical energy consumption data set into an intelligent power transformation micro-station equipment energy consumption prediction model based on a symbol regression algorithm to obtain a total energy consumption prediction value of the intelligent power transformation micro-station on the day. The method can effectively mine the potential relation between the characteristics in the data set, obtains the displayed prediction equation, and accurately predicts the energy consumption of the intelligent power transformation micro-station equipment. The search space of the algorithm can be reduced, the training time of the prediction model is shortened, and the model energy consumption prediction precision is improved.

The invention relates to a remote control adjusting system for intelligent garden maintenance, and relates to the field of intelligent garden remote control, and the method comprises the steps: obtaining image information, illumination duration and illumination intensity of each region in an intelligent garden, and environment parameters of a plurality of positions and moments in each region, the environment parameters comprising air temperature and soil humidity, the soil drying speed of each area is determined on the basis of the environment parameters, the sunshine duration, the illumination intensity and the image information, the vegetation density of each area is determined on the basis of the image information, a target area is determined according to the drying speed and the vegetation density, the target area is an area needing irrigation, and sprinkling irrigation equipment in the target area is controlled to be started. The method has the effects of accurately determining the area needing sprinkling irrigation in the smart garden and reducing waste of water resources.

A high-precision solar resource assessment method based on a downscaling method for complex terrain includes steps as follows. Step (1): an average climatic field is calculated based on monitoring data of sunshine durations, climatic field interpolation results are obtained based on the average climatic field, and a climatic field is created. Step (2): a difference between data of the sunshine durations and the climatic field is calculated, anomaly field interpolation results are obtained based on the difference, and an anomaly field is created. Step (3): the climatic field interpolation results and the anomaly field interpolation results are overlayed. Step (4): bias adjustment is performed on the high-precision sunshine duration interpolation results obtained in the step (3) based on the monitoring data of the sunshine durations to obtain final results. Step (5): daily solar radiation is estimated based on the sunshine durations and extraterrestrial solar radiation.

The invention relates to the technical field of agricultural information processing, in particular to a sunshine duration forecasting method based on multiple modes. The cloud cover and solar radiation forecasting data of EC and CMA-MESO modes are combined, two different calculation algorithms are adopted for contrastive analysis, the optimal forecasting method is selected, the sunshine duration forecasting precision is effectively improved, the method can accurately forecast the sunshine duration according to the cloud cover and the radiation condition, the method can adapt to different seasonal changes, and the method has the advantages of being high in practicability and wide in application range. And the practicability and the reliability are relatively high.

The invention provides an intelligent early warning method for high-altitude operation falling risks of railway station canopy transformation. Comprising the following steps: inputting canopy component parameters, reference values and weight coefficients, and starting all sensors to carry out data calibration so as to remove abnormal values; the real-time environment temperature, the cumulative sunshine duration of the day, the component surface humidity and the real-time wind speed of an operation point are collected through the multi-dimensional environment sensing module, and the component actual measurement thickness and the component vibration speed are collected through the canopy component state monitoring module. The total load, the actual operation height and the single-time operation duration of the operation platform are collected through the operation platform state monitoring module, and the respiratory frequency variation coefficient of the operation personnel is collected through the personnel physiology monitoring module; inputting the acquired real-time environment temperature, the accumulated sunshine duration on the day, the surface humidity of the component, the actually measured thickness of the component and the vibration speed of the component into an intelligent early warning calculation module; reliable safety guarantee can be provided for railway station canopy transformation aloft work in regions with remarkable temperature differences.

The utility model relates to a novel cross joint coupler which comprises a cross joint, the upper end and the lower end of a vertical shaft are respectively provided with a connecting plate, the front side and the rear side of a transverse shaft are respectively provided with a connecting plate, the two connecting plates on the vertical shaft are oppositely arranged up and down, and a left main beam is clamped by a U-shaped notch between the upper connecting plate and the lower connecting plate; the two connecting plates on the transverse shaft are oppositely arranged front and back, a U-shaped notch between the front connecting plate and the rear connecting plate clamps the right main beam, and gaps exist between the left main beam and the connecting plates and between the right main beam and the connecting plates. The relative position between the two main beams of the novel cross joint coupler can be slightly adjusted, so that certain up-down and left-right deviation can be allowed between the adjacent platforms, a site does not need to be leveled, accurate measurement is not needed, the installed capacity is increased, the installed efficiency is improved, the sunshine duration is prolonged, and the capital construction cost is greatly reduced. In addition, tracking type photovoltaic power generation can be used in areas such as hills, and the application range of the photovoltaic module is widened.

The present invention discloses a method for calculating the glacier meltwater discharge of rivers in arid regions considering dynamic glacier melting, which relates to the field of hydrology. The method includes the following steps: obtaining the glacier areas of all glaciers in the basin; calculating the glacier volumes according to the glacier volume-area ratio relationship; allocating the glacier areas and glacier volumes to each sub-basin of the basin to calculate the total glacier coverage area and glacier volume of each sub-basin; obtaining the solar radiation amount in the basin based on the basin's longitude, latitude and sunshine hours; obtaining the meteorological data within and around the basin, and interpolating the meteorological data to the sub-basins according to the Thiessen polygon method to obtain the meteorological conditions on each sub-basin; calculating the glacier surface temperature on the day of ice melting; calculating the glacier melting amount on each sub-basin based on the ice surface temperature and solar radiation amount, so as to realize the calculation of the glacier meltwater discharge in arid regions.

The invention relates to an intelligent power transformation micro-station equipment energy consumption prediction system and method based on a symbol regression algorithm, and the method comprises the steps: selecting daily average temperature, daily average humidity, sunshine duration t and traffic flow VF as four input features which affect the daily total energy consumption of an intelligent power transformation micro-station; three modules of a symbol regression algorithm based on adaptive iteration and control variable genetic programming: an adaptive iteration module, a control variable module and a genetic programming algorithm module are used for training a standard genetic programming algorithm; and inputting the sorted historical energy consumption data set into an intelligent power transformation micro-station equipment energy consumption prediction model based on a symbol regression algorithm to obtain a total energy consumption prediction value of the intelligent power transformation micro-station on the day. The method can effectively mine the potential relation between the characteristics in the data set, obtains the displayed prediction equation, and accurately predicts the energy consumption of the intelligent power transformation micro-station equipment. The search space of the algorithm can be reduced, the training time of the prediction model is shortened, and the model energy consumption prediction precision is improved.

The application discloses a molecular marker for identifying geographical origin of Populus tomentosa and application thereof, and the molecular marker is located at the 42th base of FPA gene in a poplar genome and has C / A polymorphism, wherein a P. tomentosa individual with a genotype AA of the molecular marker has a shorter annual average sunshine duration, and a P. tomentosa individual with a genotype CC of the molecular marker has a longer annual average sunshine duration. The molecular marker provided by the application has a clear function and a significant effect, and can be directly applied to molecular marker assisted breeding of the poplar; and the molecular marker has environmental adaptability and is suitable for directional introduction of the poplar.

The invention relates to the technical field of three-dimensional geographic modeling, in particular to a land utilization planning auxiliary method and system based on a 3D terrain model, and the method comprises the following steps: obtaining point cloud and elevation information, converting the information into a terrain curved surface, discretizing the information into a voxel grid, analyzing a planning index, converting the planning index into a geometric constraint boundary, and traversing to construct a planning voxel field. Calculating earthwork digging and filling requirements and sunshine hours to generate an evaluation matrix, correcting the building voxel distribution and finely adjusting the terrain elevation. According to the method, terrain refined expression is realized by using an octree segmentation algorithm, indexes such as a plot ratio are converted into three-dimensional space geometric constraints, site suitability is evaluated through connectivity analysis, and building layout and earthwork balance are automatically optimized by adopting morphological operation, so that the problems of lack of space intuition and error accumulation in traditional two-dimensional planning are solved; the planning calculation precision and decision scientificity under the complex terrain are remarkably improved, and dynamic adjustment and visual expression of the scheme are achieved.

In an automated power distribution system equipped with a power generation device such as a solar power plant, the discharge time of a substation is estimated. [Solution] The slave station 2 and master station 3 that constitute the power distribution automation system 1 are equipped with a solar power generation unit 220, a power storage unit 230, and a sunshine measurement unit 240 as functions of the slave station 2, and a prediction unit 342 that predicts the amount of power generated by the solar power generation unit 220 based on the sunshine duration and amount of solar radiation as functions of the master station 3, an estimation unit 343 that estimates the dischargeable time of the power storage unit 230 based on the predicted amount of power generated and the amount of power stored in the power storage unit 230, and a display unit 320 that displays the estimated dischargeable time of the power storage unit 230.

The present invention discloses a method and system for calculating sunshine duration for building regeneration based on spherical coordinates, including: taking the moving trajectory of the sun in a day as the bottom surface and the measuring point as the vertex to obtain a sunshine cone surface in the spherical coordinate system, and obtaining sunshine cone surface parameters, including the cone direction vector of the cone vertex, the cone angle, and the sunshine analysis time period interval; triangulating the building model, and converting the vertices of the triangular meshes into spherical coordinates in the same spherical coordinate system as the sunshine cone surface; finding out the triangular meshes that collide with the sunshine cone surface; calculating the longitude of the intersection points of the triangular meshes and the sunshine cone surface to obtain the occlusion intervals of the triangular meshes; merging the occlusion intervals of all the triangular meshes to obtain the occlusion interval of the building model; subtracting the occlusion interval of the building model from the sunshine analysis time period interval to obtain the sunshine interval of the measuring point, and calculating the sunshine duration. The present invention solves the problems that it is difficult to balance the calculation accuracy and calculation speed, and there is a calculation difficulty for complex buildings.

The invention discloses a DEM (Digital Elevation Model) sunshine duration method and system based on GPU (Graphics Processing Unit) and terrain entropy optimization, and belongs to the technical field of geographic information science and space calculation. The method comprises the following steps: firstly, calculating topographic information entropy by using digital elevation model data to quantify topographic complexity of different regions; and the terrain information entropy is used as a self-adaptive driving factor to dynamically adjust the search radius and the search step length of the sun visible range, so that the condition that no shielding exists in a terrain gentle region is quickly judged, and the terrain shielding relationship is finely simulated in a mountain region or a complex terrain region. Besides, the method is realized by adopting a CUDA (Compute Unified Device Architecture) parallel architecture, and is combined with a GPU (Graphics Processing Unit) parallel strategy of partitioning and partitioning, so that the calculation load of high-resolution data is effectively reduced, and the overall operation efficiency and the memory utilization rate are improved.

The invention discloses a distributed photovoltaic output model construction method and system, and an output prediction method and system. The method comprises the following steps: dividing historical distributed photovoltaic output data into photovoltaic output data of each season according to seasons; based on the photovoltaic output data of each season, a distribution interval of a proportionality coefficient, a telescopic coefficient, a translation coefficient and a beta distribution shape parameter in each season is determined by using a least square method, and a basic component model is constructed in combination with a beta distribution model; determining a distribution interval of an autocorrelation coefficient and a random variance correlation coefficient in each time period of each season by using a least square method based on the photovoltaic output data of each season, and constructing a random component model in combination with a colored noise model; constructing a distributed photovoltaic output model considering seasonal characteristics based on the basic component model and the random component model; according to the invention, the proportionality coefficient, the expansion coefficient and the translation coefficient are introduced to describe the output amplitude, the sunshine duration and the peak phase of each season, and the photovoltaic output rules in different seasons are accurately described.

The application discloses a kind of based on earthworm soil immunity strawberry facility environment synergic regulation method and system, belong to strawberry facility planting technical field.This method aims at solving the problem that earthworm activity is difficult to maintain continuously in prior art, environment regulation and biological demand are split.The technical scheme points are as follows: through sensor network, soil temperature, moisture content, oxygen concentration and by image recognition are obtained earthworm manure accumulation rate;These data are input into pre-trained earthworm strawberry symbiosis dynamic model, the model can be switched according to environmental temperature and sunshine duration Winter Energy Saving and conventional symbiosis two modes, and generate corresponding temperature, humidity and oxygen control threshold;Finally, by comparing real-time data and threshold to trigger actuator to carry out synergic environment regulation.This method is mainly used for precise management of environment in strawberry facility cultivation, to synergistically improve earthworm population survival rate and strawberry production efficiency.

Predicts the occurrence of plant diseases and pests with high accuracy. [Solution] The prediction device (1) includes a calculation unit (12) that calculates the current rate of proliferation of plant diseases and pests by referring to at least one of the information indicating the temperature, humidity, and sunshine hours around the plant at the present time, and a prediction unit (13) that predicts the current amount of disease and pest occurrence using Bayesian modeling based on the cumulative value of the proliferation rate and the amount of disease and pest occurrence at a time prior to the present time.

The application discloses a DEM sunshine duration method and system based on GPU and terrain entropy optimization, and belongs to the field of geographic information science and spatial computing technology. The method firstly calculates terrain information entropy by using digital elevation model data to quantize the terrain complexity of different regions; and then dynamically adjusts the solar visibility range search radius and search step length by taking the terrain information entropy as an adaptive driving factor, so that the terrain shielding relationship is finely simulated in the mountainous or complex terrain area while the unobstruction is quickly determined in the flat terrain area. In addition, the application is realized by using a CUDA parallel architecture, and the GPU parallel strategy of block partitioning is combined, so that the calculation load of high-resolution data is effectively reduced, and the overall operation efficiency and memory utilization are improved.

The invention discloses a deep learning runoff prediction model based on a three-dimensional network structure and a prediction method thereof. A two-dimensional convolutional neural network is used for extracting nonlinear correlation among multi-dimensional meteorological elements such as air pressure, air temperature, relative humidity, rainfall, evaporation, wind direction and wind speed, sunshine duration and ground temperature; and discrete site data is mapped into a spatial continuous grid by adopting an inverse distance weighted interpolation (IDW) method, so that the omnibearing description of the driving runoff change is realized. Long and short term dependence is captured in combination with BiLSTM, and an Attention mechanism dynamically focuses on key meteorological events, so that the model has higher robustness when processing time sequence characteristics, and the defects that a traditional method is strong in dependence on a single factor and is easily influenced by local anomaly are effectively overcome.

1. The name of the design product: light radiation sensor. 2. The use of the design product: for monitoring light intensity, total radiation, sunshine hours, ultraviolet intensity and other light source data. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

A step-shaped three-dimensional cultivation frame comprises supporting plates, a cross beam is arranged between the two supporting plates, the two ends of the cross beam are fixedly connected with the inner sides of the two supporting plates respectively, a folding sunshade is arranged behind the two supporting plates and comprises a storage box and supporting plates, the front portion of the storage box is fixedly connected with the rear portions of the two supporting plates, and the supporting plates are fixedly connected with the storage box. The support is located in front of the supporting plate, cultivation grooves are formed in the upper portion of the support and the upper portion of the supporting plate, plants with saturated sunlight can be shaded through the folding plate and the sliding plate, damage to the plants due to too sufficient sunlight is prevented, and when sunlight is insufficient in cloudy days, the planting lamps can prolong the illumination time of the plants to promote growth of the plants; by means of the device, the sunshine duration of the plants can be adjusted, and stable growth of the plants is promoted.

The invention provides a northwest region sunshine duration prediction method and system, and belongs to the technical field of data processing, and the method comprises the steps: obtaining the altitude of a target city and historical data of multiple days, obtaining the update assignment of the relative sunshine duration under each weather type in the first update seven-score method of the target city and the specific relative sunshine duration of the target city in each day; and obtaining a prediction model of the relative sunshine duration of the target city according to the specific relative sunshine duration, the actual daily maximum temperature, the actual daily minimum temperature, the actual wind speed, the daily ordinal number and the actual weather type of the target city in each day and the update assignment of the relative sunshine duration under each weather type. The invention aims to solve the problem that the difference between the sunshine duration of a target city and the actual sunshine duration forecasted by the current seven-division method is too large because the current seven-division method has high universality and cannot reflect the unique characteristics of each city and each day.

The present invention relates to the technical field of battery energy storage management, and particularly relates to a distributed optical storage energy management method based on a string-type energy storage system, including the following steps: Step 1: Construct a regional terrain model, and calculate the theoretical conversion power based on the total power generation area of the photovoltaic panel array, the component conversion power, and the power generation loss coefficient; Step 2: Conduct a simulation calculation of sunlight irradiation to obtain the occlusion parameter value; Step 3: Analyze and calculate the coverage influence value based on the total suspended particulate matter index at the installation location; Step 4: Obtain the annual average irradiance G at the area corresponding to the installation location, and analyze and calculate the power measurement value in combination with the occlusion parameter value, the coverage influence value, and the theoretical conversion power; Step 5: Calculate the daily average power generation prediction value and the peak power generation prediction value based on the average sunshine duration and the peak sunshine duration; calculate the demand peak power of the load circuit; divide the energy storage unit into a storage unit and a circulation unit, and calculate the set quantities of the storage unit and the circulation unit.

The invention discloses a TCN-GLU-Attention-based load energy consumption prediction method and device, equipment, a medium and a product, and relates to the field of load energy consumption prediction, and the method comprises the steps: obtaining a current load energy consumption sequence; the current load energy consumption sequence is input into a load energy consumption prediction model to predict future load energy consumption, a future load energy consumption sequence is obtained, and the load energy consumption prediction model takes a historical sample load energy consumption sequence as input and takes external auxiliary features as labels to train a TCN-GLU-Attention network; the external auxiliary features comprise air temperature, humidity, wind speed, sunshine duration, holidays and festivals and workdays; the TCN-GLU-Attention network comprises a TCN network, a GLU network, a multi-head attention mechanism network and a position feedforward network; according to the invention, the prediction precision of load energy consumption prediction is improved.

The system according to this embodiment aims to collect and analyze environmental data in agriculture, provide optimal cultivation advice, and automatically control the environment. [Solution] The system according to the embodiment comprises a collection unit, an analysis unit, and a control unit. The collection unit collects data such as sunshine duration, temperature, humidity, and moisture content. The analysis unit analyzes the data collected by the collection unit and provides optimal cultivation advice. The control unit automatically controls the environment based on the analysis results obtained by the analysis unit.

The application provides a northwest region sunshine duration prediction method and system, and belongs to the technical field of data processing. The method comprises the following steps: obtaining the altitude of a target city and historical data of multiple days to obtain the updated assignment of the relative sunshine duration of each weather type in the first updated seven-point method of the target city and the specific relative sunshine duration of the target city on each day; and obtaining a prediction model of the relative sunshine duration of the target city according to the specific relative sunshine duration of the target city on each day, the actual daily maximum temperature, the actual daily minimum temperature, the actual wind speed, the day serial number, the actual weather type, and the updated assignment of the relative sunshine duration of each weather type. The application aims to solve the problem that the current seven-point method has too strong universality and fails to reflect the unique characteristics of each city and each day, so that the difference between the sunshine duration of the target city predicted by the current seven-point method and the actual sunshine duration is too large.

An agricultural light complementation method relates to the technical field of agricultural light complementation and comprises the following steps: acquiring parameters of a photovoltaic laying target area and constructing a simulation model, and performing simulation calculation to obtain track data of a sunlight shielding shadow in a photovoltaic sunshine duration; a light supplementing mechanism is arranged in the simulation model according to the track data of the photovoltaic shielding shadow, and the light supplementing mechanism dynamically guides light to a photovoltaic shielding shadow area; the positions of the photovoltaics and the light supplementing mechanism are adjusted until the shading shadow area between the photovoltaics and the shading shadow area of the light supplementing mechanism on the photovoltaics and the crops are lower than a threshold value; the position parameters of the photovoltaic and light supplementing mechanism and the parameters of the light supplementing mechanism are output, the parameters of the light supplementing mechanism comprise the size parameters and the dynamic control parameters, the light supplementing mechanism is additionally arranged, the positions of the photovoltaic and light supplementing mechanism are optimized, and light supplementing is conducted on crops below the photovoltaic device while shielding is reduced as much as possible; the crop photosynthesis and growth rhythm effects are effectively improved.

This invention discloses an AI-based climate-adaptive elderly care and health building design optimization system, relating to the fields of building design optimization and smart health management technology. It includes a state assessment module, a counterfactual diagnosis module, and an evolution path module. The system acquires building operational characteristics and dynamic meteorological parameters for sample augmentation and nonlinear mapping training. It locates failure points in the set of design variables for health and health buildings, and uses counterfactual path optimization to pinpoint the minimum intervention sequence. It then performs causal contribution measurement and semantic encapsulation to generate a decision evolution path. This invention can accurately locate environmental failure risks. Using the architectural design standards for elderly care facilities as constraints, it coordinates the control of winter solstice sunshine duration, summer shading needs, and indoor thermal environment in elderly activity spaces. This achieves a balance between sunshine compliance, age-friendly thermal safety, and environmental load in health and health buildings, improving the living comfort and climate adaptability of elderly care buildings.

The invention discloses a building global sunshine analysis method based on a live-action three-dimensional model, and the method comprises the steps: calculating a sunshine vector according to a time window, the number of analysis days, a moment list and the latitude and longitude of a location, and carrying out the loading, normal vector correction, roof recognition and adaptive subdivision of a building model. And for the subdivided building model, constructing a ray parallel to the sunlight direction by taking the center point of the surface as a starting point, judging whether the surface is shielded or not through ray-grid intersection detection, and calculating the sunshine duration of the triangular surface. And further calculating direct radiation, scattered radiation and ground reflection radiation of the surface, and estimating the total irradiance of the triangular surface. And calculating a mean value of all results on the time sequence to obtain a comprehensive sunlight analysis result. And matching an analysis result with a model surface index, exporting a data table, and embedding a surface patch color into a model for storage.