104results about "Sunshine duration recorders" patented technology

The present invention discloses a full-field refined DNI prediction method. At least two total-sky imagers are used to determine the actual position of a cloud, and then a shadow position is determined on the basis of a solar angle; and the thickness of the cloud is determined by means of the imaging brightness of the cloud, and then a DNI value is predicted. The method specifically comprises the following steps: performing cloud identification, cloud image speed calculation, cloud actual-position calculation, cloud / shadow actual-speed calculation, shadow position prediction, cloud thickness extraction, DNI mapping, and DNI prediction. In the method, at least two total-sky imagers or pinhole cameras are used to perform a DNI prediction operation, and a DNI change at each specific position in a heliostat field can be accurately predicted, such that the power generation efficiency is improved.

The invention relates to a method and a device for determining an albedo of the ground and / or an irradiance of radiation reflected by the ground (14), in a solar installation (12), by means of at least one device (30, 31, 54) for capturing ground-based measurement data, comprising at least one camera (32) which captures an image or a plurality of images of the ground (14) and an evaluation unit (42) which evaluates the ground-based measurement data using satellite image data. The invention also relates to a computer program for determining an irradiance of radiation reflected by the ground, to a data processing device, and to trained machine-learning models for extracting features.

Provided is a digital twin model-based method for predicting the power generation amount of a photovoltaic power station. The method includes the steps of: acquiring location information and weather information of a photovoltaic power station; generating a digital twin model for cloud movement simulation based on information of a region in which the photovoltaic power station is located and a weather condition corresponding to the information of the region; modeling cloud movement information by inputting regional weather pattern information to the digital twin model; acquiring future time-based solar irradiance prediction information by inputting the modeled cloud movement information into a pre-trained artificial intelligence model; and predicting the amount of power generation of the photovoltaic power station by calculating thermal information of a photovoltaic panel corresponding to the solar irradiance prediction information.

The present disclosure relates to a computer-implemented method (200) of training a predictive model (10) for short-term forecasting of a Global Horizontal Irradiance, GHI, value at a reference location (21), the method (200) comprising: i) obtaining (201) a satellite image (S1-Sn) of cloud coverage over a ground area comprising said reference location (21); ii) performing (202) image processing of said satellite image (S1-Sn) to obtain a corresponding image of the cloud thickness over said ground area; iii) generating (203) a sun path image (P) by composing said image of the cloud thickness with a solar vector defining a path between said reference location (21) and a sun position at an acquisition time of said satellite image (S1-Sn), wherein said sun path image (P) is representative of a cloud occlusion of the sun along said solar vector; iv) providing (204) said image of the cloud thickness to a first feature extraction pipeline of said predictive model (10) to provide a first set of extracted features; v) providing (205) said sun path image (P) to a second feature extraction pipeline of said predictive model (10) to provide a second set of extracted features; vi) combining (206) said first set of extracted features with the second set of extracted features to generate a concatenated set of extracted features; and vii) inputting (207) said concatenated set of extracted features into a classification layer of the predictive model (10) for training on a relationship between said satellite image (S1-Sn) and said GHI value.

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 present invention provides an information processing method, etc., that can suitably estimate solar radiation. [Solution] The information processing method acquires the amount of sunlight at an observation point and observation time information indicating the time of observation of the sunlight. Based on the acquired sunlight and observation time information, a computer performs a process to estimate the amount of solar radiation at the observation point. Preferably, the amount of solar radiation is estimated based on the acquired sunlight and observation time information using a regression equation that shows the relationship between the amount of solar radiation, the ratio of sunlight, and the observation time.

To provide a generated amount of power estimation device with which it is possible to determine an estimation formula to estimate the generated amount of power that is generated by a solar panel in a prescribed district.SOLUTION: The generated amount of power estimation device is provided with: an input unit 110 to which information about an estimation formula building district that includes an installation range in which a photovoltaic power generation unit is installed is input; an extraction unit 120 that extracts a first explanatory variable relating to an effective space that contributes to photovoltaic power generation, a second explanatory variable relating to a site area in the installation range, and a third explanatory variable relating to the height in the installation range, on the basis of the district information; and an estimation formula creation unit 130 that determines an estimation formula to calculate the estimate value of the generated amount of power that is generated by the photovoltaic power generation unit in the estimation formula building district, which is a polynomial including the first, second and third explanatory variables, the estimation formula creation unit 130 acquiring the generated amount of power that is generated by the photovoltaic power generation unit in the estimation formula building district, and determining an estimation formula on the basis of the degree of fitness of the acquired generated amount of power to the estimation formula.SELECTED DRAWING: Figure 1

A system and method for seasonal energy consumption determination using verified energy loads with the aid of a digital computer are provided. A digital computer is operated, including: obtaining energy loads for a building measured over a seasonal time period; obtaining outdoor temperatures for the building as measured over the seasonal time period; verifying stability of the energy loads, including: evaluating the energy loads over time; and identifying at least one of one or more discontinuities and one or more irregularities in the energy loads based on the evaluation. Operating the computer further includes: determining a baseload energy consumption using at least some of those of the energy loads; calculating seasonal fuel consumption rates and balance point temperatures; and disaggregating seasonal fuel consumption based on the baseload energy consumption, seasonal fuel consumption rates, balance point temperatures, and at least some of the outdoor temperatures into component loads of consumption.

The present invention relates to a building sunshine time measuring instrument. It solves the problem of complicated operation and inconvenient use when measuring sunshine hours in the prior art. It includes a stick shadow chart device, a first pointer device and a second pointer device are installed at one end of the stick shadow chart device, a sensor is provided at the lower side of the stick shadow chart device, an arc panel for closing the end of the stick shadow chart device is installed at one end of the stick shadow chart device, a sensing processor module is provided on the arc panel, one end of the first pointer device and the second pointer device are respectively connected to the sensing processor module, and one end of the sensing processor module is connected to a time display component for displaying the time indicated by the first pointer device and the second pointer device, the time display component is connected to a calculation display device, and a switch button for turning on the measuring instrument is also provided at one end of the arc panel. The advantages of the present invention are: data visualization, high result accuracy, more convenient use, and improved work efficiency.

A cloud cover prediction device (10) is provided with: a learning unit (11) that takes a correlation between first time series data of a cloud cover rate derived on the basis of a sky image, which is an image obtained by photographing the sky from an observation location, and second time series data of cloud cover rates at a plurality of locations derived on the basis of a satellite image, and stores, as a time difference map, a correspondence relationship between each of the plurality of locations and a time difference between the time series data with high correlation; and a prediction unit (12) that refers to the time difference map stored in the learning unit by using a cloud movement direction acquired using the satellite image and a preset time difference, to derive a cloud cover rate at a selected location and output a predicted value of the cloud cover rate.

The objective is to provide a light detection device that reduces design man-hours and manufacturing costs, and enables miniaturization of the device. [Solution] The light detection device 1 comprises a circuit board 2 and an optical device 3. The circuit board 2 has a first surface and a second surface opposite to the first surface, and is provided with a window portion 21 that penetrates the first surface and the second surface. The optical device 3 has a plurality of optical sensors 4a, 4b, and is mounted on the second surface of the circuit board 2 with the surface on which the plurality of optical sensors 4a, 4b are provided facing the second surface of the circuit board 2. The plurality of optical sensors 4a, 4b are arranged at different positions within a range in which they can receive light incident from the side of the first surface of the circuit board 2 through the window portion 21. The optical device 3 detects the direction of light based on the output values ​​of each of the plurality of optical sensors 4a, 4b.

In an information processing method according to the present invention, a computer executes processing for acquiring an amount of sunlight at an observation point and observation time point information indicating an observation time point of the amount of sunlight, and estimating the amount of solar radiation at the observation point on the basis of the acquired amount of sunlight and observation time point information. Preferably, the amount of solar radiation is estimated on the basis of the acquired amount of sunlight and observation time point information by using a regression equation indicating the relationship between the observation time point and a ratio of the amount of solar radiation to the amount of sunlight.

The present invention concerns a method for determining the solar distribution in an area, the comprising: - a phase for collecting data to form a training database (B), - a phase for training a model on the basis of the training database (B) to obtain a trained model, the input of the trained model being an image of an area seen from the sky and the output being a global cartography of the irradiance projected on each surface of the area imaged on the input image, - a phase for operating the trained model comprising: o a step of receiving an image of an area seen from the sky, and o a step of determining by the trained model a global cartography of the irradiance projected on each surface of the area imaged on the received image.

To achieve anti-glare by predicting that sunlight is irradiated to eyes in order to prevent passengers from feeling dazzling even for a moment.SOLUTION: An automatic anti-glare device 21 includes shading adjustment means 31 which is capable of adjusting permeation rate of a window glass provided on a vehicle, photograph sun shade means 32 which acquires sight information in front of the vehicle, vehicle travel information acquisition means 33 which acquires vehicle travel information containing vehicle speed and steering angle, vehicle position information acquisition means 34 which acquires vehicle position information containing present position and direction, clock means 38 which acquires present date information, vehicle position prediction means 35 which finds vehicle prediction position after prescribed time from the sight information and the vehicle travel information and sunshine prediction determination means 36 which finds irradiation state of the sunlight from shadow shade information of road surface contained in the sight information in the vehicle prediction position. The shading adjustment means 31 adjusts permeation rate according to the irradiation state.SELECTED DRAWING: Figure 1

Apparatus, methods, and non-transitory computer readable medium for estimating solar radiation energy resources. The method includes receiving a request for estimating solar radiation energy resources for a solar site; obtaining metadata about the solar site; obtaining satellite weather data corresponding to the solar site; obtaining measured solar data on the solar site; generating a training dataset based on the satellite weather data and the measured solar data; training a machine learning model by the training dataset; and synthesizing solar radiation energy resource data corresponding to the solar site using the machine learning model.

The present invention concerns a method for determining the solar distribution in an area, the including, a phase for collecting data to form a training database, a phase for training a model on the basis of the training database to obtain a trained model, the input of the trained model being an image of an area seen from the sky and the output being a global cartography of the irradiance projected on each surface of the area imaged on the input image, and a phase for operating the trained model. The phase for operating the trained models includes, a step of receiving an image of an area seen from the sky, and a step of determining by the trained model a global cartography of the irradiance projected on each surface of the area imaged on the received image.

To provide a solar power generation amount prediction device capable of accurately predicting a solar power generation amount from weather forecast data by performing machine learning, for example, for each building or dwelling unit to which a solar power generation panel is attached.SOLUTION: A solar power generation amount prediction device includes: a machine learning unit that performs, for each of one or a plurality of solar power generation panels, machine learning for each time based on a solar radiation amount actual measurement value and a power generation amount actual measurement value for each time in a past predetermined period with respect to a prediction target day; and a power generation amount prediction unit that predicts a power generation amount on the prediction target day based on results of the machine learning by the machine learning unit.SELECTED DRAWING: Figure 1

A vehicle control device includes a memory that stores program instructions and a processor that executes the program instructions. The processor may obtain at least one of sunlight amount information, temperature information, location information, or time information, and in response, may provide a reward to a user of the vehicle control device in the form of mileage in response to the user transmitting at least one of the obtained sunlight amount information, the obtained temperature information, the obtained location information, or the obtained time information to a server. The mileage may be used as payment for a good, information, or a service, which is identified based on an input of the user of the vehicle control device.

Techniques for predicting solar power generation include a node measuring, using one or more sensors, a first time series of voltage readings for a first power line located at a first location, wherein a portion of power on the first power line is generated from solar irradiance on one or more first solar panels located at the first location; generating a first cross-correlation between the first time series of voltage readings and a second time series of voltage readings for a second power line located at a second location, wherein a portion of power on the second power line is generated from solar irradiance on one or more second solar panels located at the second location; and computing a wind vector based on the first location, the second location, and the first cross-correlation, wherein the wind vector is usable to forecast solar power generation at one or more other locations.

The invention discloses a rail transit station domain spatial form evaluation method and system oriented to sunlight adaptability, and relates to the technical field of rail transit station domain spatial physical environment performance simulation, and the method comprises the steps: selecting sample stations in a specific research city, collecting open source map data, extracting entrances and exits of rail transit stations, and defining a rail transit station domain range; measuring points are selected in a station domain range; calculating the passenger flow intermediate property of a measuring point and sunlight basic indexes in different seasons by using a building volume three-dimensional model in the station domain; taking the sunshine basic indexes of all the measuring points as a data set, and calculating the weight of each basic index by using a CRITIC weight method to obtain a sunshine performance comprehensive index of the measuring points; and drawing a B-S distribution scatter diagram of the measuring points by taking the passenger flow intermediate index as a horizontal axis and the sunlight performance comprehensive index as a longitudinal axis, dividing according to regions to obtain three types of balance, overload and potential, and calculating the proportions of the three types of measuring points to obtain an evaluation result.

A photovoltaic system's configuration specification can be inferred by an evaluative process that searches through a space of candidate values for the variables in the specification. Each variable is selected in a specific ordering that narrows the field of candidate values. A constant horizon is assumed to account for diffuse irradiance insensitive to specific obstruction locations relative to the photovoltaic system's geographic location. Initial values for the azimuth angle, constant horizon obstruction elevation angle, and tilt angle are determined, followed by final values for these variables. The effects of direct obstructions that block direct irradiance in the areas where the actual horizon and the range of sun path values overlap relative to the geographic location are evaluated to find the exact obstruction elevation angle over a range of azimuth bins or directions. The photovoltaic temperature response coefficient and the inverter rating or power curve of the photovoltaic system are determined.

A cloud cover forecasting device (10) comprises: a training unit (11) that obtains a correlation between first time-series data of a cloud shielding rate derived on the basis of a sky image, which is obtained by photographing the sky from an observation location, and second time-series data of cloud shielding rates at a plurality of locations derived on the basis of a satellite image, and that accumulates, as a time difference map and for each of the plurality of locations, a correspondence relationship between the location and a time difference between time-series data for which the correlation is high; and a forecasting unit (12) that uses a preset time difference and a cloud movement direction acquired using the satellite image to derive the cloud shielding rate at a location selected with reference to the time difference map accumulated by the training unit, and outputs a cloud shielding rate forecast value.

To provide a soil condition predicting system and soil condition predicting program for predicting the impact of sunlight on soil condition.SOLUTION: A soil condition predicting system 10 comprises: a storage section 13 that stores date and time information, location information, and sunlight intensity information in association with one another; a communication section 17 that performs communication; a first calculating section 11 that calculates the sunlight intensity information associated with sunlight query information included in predicted information query information input via the communication section; a second calculating section 12 that uses calculated results of the first calculating section to calculate direction-specific sunlight intensity information; and a third calculating section 21 that uses calculated results of the second calculating section to calculate soil condition predicted information predicting the impact of sunlight on soil indicated by soil information included in the predicted information query information input via the communication section.SELECTED DRAWING: Figure 1

The present invention relates to a diagnosis system for measuring string health of a solar power generation system and, more specifically, to a diagnosis system for measuring string health of a solar power generation system, which calculates the string health by measuring a ratio of an actual amount of power generation to an expected amount of power generation for each string constituting the solar power generation system, and quickly detects an abnormal string through the string health, thereby supporting prompt action to be performed.

A method (20) for generating / updating a database of current-voltage characteristic curves is disclosed. This method comprises simulating (25), for at least one combination of a topology of a photovoltaic cell group, an internal cell temperature(s) and a cell irradiation(s), a model of the photovoltaic cell group to provide a current-voltage characteristic curve representative of that combination, and clustering (24) the current-voltage characteristic curves to identify at least one plurality of similar current-voltage characteristic curves. The method also comprises generating (26) a many-to-one mapping in the database to map query requests that correspond to each of the at least one plurality of similar current-voltage characteristic curves onto a single representative current-voltage characteristic curve for that plurality of similar current-voltage characteristic curves, each query request identifying a topology of a photovoltaic cell group, at least one internal temperature for the photovoltaic cells in the photovoltaic cell group and at least one cell irradiation for the photovoltaic cells in the photovoltaic cell group.

A method for determining a weather condition, comprising: measuring horizontal irradiance; measuring first slope irradiance and second slope irradiance, a first slope and a second slope being arranged to face the sun and being symmetrical about the meridian plane; determining an azimuth irradiation deviation rate according to the horizontal irradiance, the first slope irradiance, and the second slope irradiance; and determining a weather condition according to the horizontal irradiance, the first slope irradiance, the second slope irradiance, and the azimuth irradiation deviation rate. Also provided is a device for determining a weather condition.

A method of predicting a photovoltaic power generation amount according to an embodiment may include predicting a sky image of a next time by analyzing sky images captured from a past time to a present time and meteorological data from the past time to the present time, predicting a solar radiation amount of the next time by analyzing the sky image of the next time, a clear-sky solar radiation amount of the next time, and meteorological data of the next time, which are generated as a result of the prediction, and predicting a photovoltaic power generation amount of the next time by analyzing the solar radiation amount of the next time and the meteorological data of the next time, which are generated as a result of the prediction, and power plant specification data.

The invention relates to a solar installation having solar panels (2, 2') which are prefabricated in a Leporello fold (3), which can be unfolded in an unfolding direction (A), said installation having a substructure on which the solar panels are arranged, wherein the substructure is flexible in the unfolding direction (A) and is connected to the solar panels in a positionally fixed manner in such a way that the Leporello fold (3) of the solar panels can be unfolded with the substructure (8, 9, 10, 24) and determines angular positions of the solar panels (2, 2') relative to one another.