Natural lighting and sun-shading integrated system based on intelligent regulation and control

Abstract

The invention provides a natural lighting and sunshade integrated system based on intelligent regulation and control, and belongs to the technical field of intelligent regulation and control, and the system comprises an optical parameter obtaining module which obtains optical parameters based on an optical sensor and marks timestamps; the energy spectrum determination module is used for determining an energy spectrum of an indoor preset space based on the infrared sensor; the prediction module is used for predicting the energy spectrum according to the optical parameters and the curtain wall parameters; and the adjusting module is used for adjusting the curtain wall structure according to the prediction result and a preset energy spectrum range, so that the curtain wall is intelligently adjusted and controlled to achieve good daylighting and sun-shading effects.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control, and in particular to an integrated natural lighting and sunshade system based on intelligent control. Background Art

[0002] With the development of cities, more and more glass curtain walls are being used on the exterior walls of buildings. Most of these glass curtain walls are fixed, with a few being retractable. When sunlight is strong or weak, they must be manually opened and closed to achieve daylighting or sunshade effects. This method is neither controllable nor provides good daylighting or sunshade effects.

[0003] Therefore, the present invention provides an integrated natural lighting and sunshade system based on intelligent regulation. Summary of the Invention The present invention provides an integrated natural lighting and shading system based on intelligent regulation, which is used to obtain optical parameters through optical sensors, determine the energy spectrum of a preset indoor space based on infrared sensors, predict the energy spectrum based on the optical parameters and curtain wall parameters, and adjust the curtain wall structure according to the prediction results and the preset energy spectrum range, thereby realizing intelligent regulation of the curtain wall to achieve good lighting and shading effects.

[0004] The present invention provides an integrated natural lighting and sunshade system based on intelligent regulation, comprising: An optical parameter acquisition module, based on an optical sensor, acquires optical parameters and marks a timestamp; wherein the optical parameters include direct sunlight angle and light intensity; An energy spectrum determination module, which determines the energy spectrum of a preset indoor space based on an infrared sensor; A prediction module, configured to predict the energy spectrum based on the optical parameters and curtain wall parameters; Adjustment module, adjusts the curtain wall structure according to the prediction results and the preset energy spectrum range.

[0005] Preferably, the direct sunlight angle includes the sunlight azimuth angle and the sunlight altitude angle, and the optical parameter acquisition module includes: a first value determining unit, configured to provide a plurality of azimuth optical sensors and obtain first values of the azimuth optical sensors; a normalization processing unit, performing normalization processing on the first value; a sunlight azimuth angle calculation unit, which calculates the sunlight azimuth angle according to the normalized value; a second value determination unit, configured to provide a plurality of vertical optical sensors and obtain second values of the vertical sensors; a sunlight altitude angle calculation unit, configured to calculate the sunlight altitude angle based on the second value; The light intensity calculation unit calculates the light intensity according to the first value and the second value.

[0006] Preferably, the energy spectrum determination module includes: A sensor setting unit, arranged according to a grid layout, for arranging a plurality of the infrared sensors in the indoor preset space; a temperature data acquisition unit, for acquiring temperature data and spatial coordinates of each of the infrared sensors; A data preprocessing unit, which preprocesses the temperature data to generate discrete point cloud data; The energy spectrum generating unit converts discrete temperature points into continuous energy distribution to generate the energy spectrum.

[0007] Preferably, the prediction module includes: A curve acquisition unit, which acquires a historical daily variation curve of light intensity and a historical daily variation curve of sunlight direct angle; A current time determination unit determines the current time based on the direct sunlight angle and a historical daily variation curve of the direct sunlight angle; A historical light intensity determination unit, which determines the historical light intensity according to the current time and the historical light intensity daily variation curve; Weather data acquisition unit, obtains current weather data changes; The weather impact unit determines the current weather impact based on the light intensity, historical light intensity and weather data changes; Light intensity prediction unit, which predicts light intensity based on current weather influence and weather data changes; A radiation intensity calculation unit calculates the radiation intensity received by the curtain wall surface based on the predicted result of light intensity; Radiation intensity distribution unit, which distributes radiation intensity according to curtain wall parameters and energy distribution model;

[0008] in, Indicates the radiation intensity; represents the intensity of transmitted radiation; Indicates the intensity of absorbed radiation; Indicates the intensity of reflected radiation; Indicates the curtain wall transmittance; Indicates the absorption rate of the curtain wall; Indicates the reflectivity of the curtain wall; Surface temperature calculation unit, calculates the curtain wall surface temperature based on the absorbed radiation intensity;

[0009]

[0010]

[0011] Where U represents the thermal conductivity; Indicates the surface temperature of the curtain wall; Indicates the indoor temperature; Indicates outdoor temperature; represents the surface emissivity; represents the Stefan-Boltzmann constant; Indicates the indoor temperature transfer coefficient; Indicates the rate of change of indoor temperature; Indicates the rate of change of outdoor temperature; Indicates the indoor temperature change correction coefficient; Indicates the correction factor for outdoor temperature change; represents the outdoor temperature conductivity coefficient; The prediction unit predicts the energy spectrum according to the transmitted radiation intensity, the absorbed radiation intensity, the curtain wall surface temperature, the indoor temperature conductivity coefficient and the outdoor temperature conductivity coefficient.

[0012] Preferably, the weather influencing unit includes: A light intensity acquisition block, which acquires a plurality of light intensities according to a time schedule; A unification block unifies the timestamps of the light intensity and the historical light intensity; a light intensity change curve block, for constructing a light intensity change curve according to a plurality of light intensities; A curve interception block intercepts the historical light intensity daily variation curve according to the historical light intensity to obtain a portion of the historical light intensity daily variation curve; A first array determination block compares the light intensity variation curve with the partial historical light intensity daily variation curve to determine a first array; a second array determination block, the second array block performing data cleaning on the first array to obtain a second array; The current weather impact determination block determines the current weather impact according to the second data array and the weather change data and based on a preset climate impact model.

[0013] Preferably, the light intensity prediction unit includes: A prediction block, which predicts the light intensity based on the historical light intensity daily variation curve; a current impact factor determination block, which determines a current impact factor according to the weather data change and the current weather impact; A correction block corrects the prediction result based on the current impact factor.

[0014] Preferably, the prediction unit includes:

[0015] in, Indicates indoor air density; represents the specific heat capacity of indoor air; represents the indoor field temperature T (x, y, z, t); k represents the thermal conductivity of air; Indicates the rate of change of curtain wall surface temperature in space; Represents heat dissipation.

[0016] Preferably, the adjustment module includes: a first time determining unit, for determining a first time out of range according to the prediction result and a preset energy spectrum range; a time interval determining unit, configured to determine a time interval according to the first time and a current time; a change range determining unit, configured to determine a change range of the time interval according to the prediction result; an adjustment parameter determination unit, configured to determine an adjustment parameter according to a preset adjustment model and based on the time interval and the change amplitude; An adjustment unit adjusts the curtain wall structure according to the adjustment parameters.

[0017] Compared with the prior art, the present invention has the following advantages: Optical parameters are obtained through optical sensors, the energy spectrum of the preset indoor space is determined based on infrared sensors, the energy spectrum is predicted based on the optical parameters and curtain wall parameters, and the curtain wall structure is adjusted according to the prediction results and the preset energy spectrum range, realizing intelligent control of the curtain wall to achieve good lighting and shading effects.

[0018] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0019] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 This is a structural diagram of an integrated natural lighting and shading system based on intelligent control in an embodiment of the present invention. DETAILED DESCRIPTION

[0021] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0022] Example 1: The embodiment of the present invention provides an integrated natural lighting and sunshade system based on intelligent control, such as Figure 1 Shown, including: An optical parameter acquisition module, based on an optical sensor, acquires optical parameters and timestamps them; the optical parameters include direct sunlight angle and light intensity; An energy spectrum determination module, which determines the energy spectrum of a preset indoor space based on an infrared sensor; Prediction module, which predicts the energy spectrum based on optical parameters and curtain wall parameters; Adjustment module, adjusts the curtain wall structure according to the prediction results and the preset energy spectrum range.

[0023] In this embodiment, an azimuth optical sensor and a vertical optical sensor are provided for measurement. The azimuth optical sensor determines the direction of the sun's projection on the horizontal plane (the azimuth angle of the sun), while the vertical optical sensor determines the angle between the sun's rays and the horizontal plane (the altitude angle of the sun). Combining these two angles, the direct sunlight angle can be obtained.

[0024] In this embodiment, the energy spectrum is a continuous temperature distribution in a preset space. Multiple infrared sensors are arranged in a preset indoor space according to a grid layout, and the temperature data and spatial coordinates of each infrared sensor are obtained; then the temperature data is preprocessed (temperature calibration and noise filtering) to generate discrete point cloud data; finally, the discrete temperature points are converted into a continuous energy distribution according to the inverse distance weighted method to generate an energy spectrum.

[0025] In this embodiment, the curtain wall parameters include transmittance, reflectance, absorptance, geometric parameters (inclination angle, sunshade angle), etc. The energy spectrum of the preset indoor space is predicted using the initial curtain wall parameters and the predicted light intensity. The transmittance of the curtain wall material to light of different wavelengths is measured using professional optical measurement equipment (such as a spectrophotometer). The reflectance of the curtain wall material to light is measured using a spectrophotometer and other equipment. According to the principle of conservation of energy, absorptance = 1 - transmittance - reflectance. The absorptance can be calculated by measuring the transmittance and reflectance.

[0026] In this embodiment, the curtain wall structure is adjusted to adjust the inclination angle and the sunshade angle to achieve the purpose of shading or lighting, and an electric actuator (such as an electric push rod, a stepper motor, etc.) is used to adjust the inclination angle and the sunshade angle of the curtain wall.

[0027] The beneficial effects of the above technical solution are: obtaining optical parameters through optical sensors, determining the energy spectrum of the preset indoor space based on infrared sensors, predicting the energy spectrum based on optical parameters and curtain wall parameters, and adjusting the curtain wall structure according to the prediction results and the preset energy spectrum range, thereby realizing intelligent control of the curtain wall to achieve good lighting and shading effects.

[0028] Example 2: Based on Example 1, the optical parameter acquisition module includes: a first value determining unit, configured to provide a plurality of azimuth optical sensors and obtain first values of the azimuth optical sensors; a normalization processing unit, performing normalization processing on the first value; A sunlight azimuth angle calculation unit calculates the sunlight azimuth angle according to the normalized value; a second value determination unit, provided with a plurality of vertical optical sensors, and acquiring a second value of the vertical sensor; a sunlight altitude angle calculation unit, which calculates the sunlight altitude angle based on the second value; The light intensity calculation unit calculates the light intensity according to the first value and the second value.

[0029] In this embodiment, one azimuth optical sensor is provided in each of the east, south, west and north directions, and the first value is the light intensity value displayed by the azimuth optical sensor.

[0030] In this embodiment, , represents the first value of the i-th orientation sensor; Indicates the minimum value among the first numerical values; Indicates the maximum value among the first values; express The normalized value of .

[0031] In this embodiment, the inverse tangent function is used to calculate the sunlight azimuth, which refers to the angle between the projection direction of the sun on the horizontal plane and the true north direction (clockwise).

[0032] In this embodiment, the vertical optical sensor is arranged in a vertical direction, and the second value is similar to the first value.

[0033] In this embodiment, the sunlight altitude angle refers to the angle between the sunlight and the horizontal plane.

[0034] In this embodiment, the illumination intensity is calculated by calculating the average value of the first value and the second value as the illumination intensity.

[0035] The beneficial effects of the above technical solution are: determining the light intensity in all directions through the azimuth optical sensor, performing normalization processing, calculating the azimuth angle of sunlight, determining the light intensity in the vertical direction based on the vertical optical sensor, calculating the sunlight altitude angle, and calculating the light intensity based on the numerical value of the optical sensor, laying the foundation for subsequent prediction of light intensity.

[0036] Example 3: Based on Example 1, the energy spectrum determination module includes: A sensor setting unit arranges multiple infrared sensors in a preset indoor space according to a grid layout; Temperature data acquisition unit, which acquires the temperature data and spatial coordinates of each infrared sensor; Data preprocessing unit, preprocesses temperature data to generate discrete point cloud data; The energy spectrum generation unit converts discrete temperature points into continuous energy distribution and generates an energy spectrum.

[0037] In this embodiment, the preset indoor space is divided into 1m×1m grids, and an infrared sensor is set at each grid vertex.

[0038] In this embodiment, the preprocessing includes temperature calibration and noise filtering. Temperature calibration is performed based on the ambient humidity and the distance between sensors. Noise filtering uses a sliding average filter to remove outliers. The temperature and spatial coordinates of each location are recorded to generate discrete point cloud data.

[0039] In this embodiment, discrete temperature points are converted into continuous energy distribution according to the inverse distance weighted method to obtain an energy spectrum, which is a temperature distribution that is continuous in a preset space.

[0040] The beneficial effects of the above technical solution are: by obtaining the temperature data and spatial coordinates of each infrared sensor, preprocessing the temperature data, generating discrete point cloud data, converting the discrete point cloud data into a continuous energy distribution, generating an energy spectrum, and laying the foundation for subsequent calculation and prediction results.

[0041] Example 4: Based on Example 1, the prediction module includes: A curve acquisition unit, which acquires a historical daily variation curve of light intensity and a historical daily variation curve of sunlight direct angle; A current time determination unit determines the current time based on the direct sunlight angle and a historical daily variation curve of the direct sunlight angle; A historical light intensity determination unit, which determines the historical light intensity according to the current time and the historical light intensity daily variation curve; Weather data acquisition unit, obtains current weather data changes; The weather impact unit determines the current weather impact based on the light intensity, historical light intensity and weather data changes; Light intensity prediction unit, which predicts light intensity based on current weather influence and weather data changes; A radiation intensity calculation unit calculates the radiation intensity received by the curtain wall surface based on the predicted result of light intensity; Radiation intensity distribution unit, which distributes radiation intensity according to curtain wall parameters and energy distribution model;

[0042] in, Indicates radiation intensity; represents the intensity of transmitted radiation; Indicates the intensity of absorbed radiation; Indicates the intensity of reflected radiation; Indicates the curtain wall transmittance; Indicates the curtain wall absorption rate; Indicates the reflectivity of the curtain wall; Surface temperature calculation unit, calculates the curtain wall surface temperature based on the absorbed radiation intensity;

[0043]

[0044]

[0045] Where U represents the thermal conductivity; Indicates the surface temperature of the curtain wall; Indicates the indoor temperature; Indicates outdoor temperature; represents the surface emissivity; represents the Stefan-Boltzmann constant; Indicates the indoor temperature transfer coefficient; Indicates the rate of change of indoor temperature; Indicates the rate of change of outdoor temperature; Indicates the indoor temperature change correction coefficient; Indicates the correction factor for outdoor temperature change; represents the outdoor temperature conductivity coefficient; The prediction unit predicts the energy spectrum according to the transmitted radiation intensity, the absorbed radiation intensity, the curtain wall surface temperature, the indoor temperature conductivity coefficient and the outdoor temperature conductivity coefficient.

[0046] In this embodiment, the Stefan-Boltzmann constant is 5.67×10⁻ 8 W / (m²・K 4 ).

[0047] In this embodiment, a historical light intensity daily variation curve and a historical sunlight direct angle daily variation curve of the same historical date are obtained based on the timestamp.

[0048] In this embodiment, the direct sunlight angle is compared with the historical daily variation curve of the direct sunlight angle, and the time corresponding to the same angle is determined to be the current time.

[0049] In this embodiment, the current time is substituted into the historical light intensity daily variation curve to determine the corresponding historical light intensity.

[0050] In this embodiment, weather data changes include temperature changes, cloud cover changes, etc.

[0051] In this embodiment, the current weather impact refers to the impact coefficient of the current weather on the light intensity.

[0052] In this embodiment, the light intensity prediction is obtained by predicting the light intensity based on the historical light intensity daily variation curve and correcting the current influencing factor according to the change of weather data.

[0053] In this embodiment, , G represents the radiation intensity received by the curtain wall surface, E represents the light intensity, represents the solar altitude angle, Indicates the inclination angle of the curtain wall. The inclination angle of the curtain wall refers to the angle between the curtain wall and the vertical plane. The initial inclination angle of the curtain wall is 0°.

[0054] In this embodiment, +

[0055] In this embodiment, the energy spectrum prediction is determined by the heat diffusion equation.

[0056] In this embodiment, when the curtain wall receives radiation, transmission, absorption and reflection will occur. In order to accurately calculate the amount of radiation processed by the curtain wall in different ways, Based on the law of conservation of energy, the total radiation energy must be distributed in these three ways. The above formula can be used to quantitatively analyze the energy of each part.

[0057] In this embodiment, the surface temperature of the curtain wall is affected by multiple factors, including the temperature difference between indoor and outdoor temperatures and the radiation characteristics of the surface.

[0058] The beneficial effects of the above technical solution are: determining the current time through the direct sunlight angle and the historical direct sunlight angle daily variation curve, and determining the historical light intensity based on the historical light intensity daily variation curve, determining the current weather impact according to the light intensity, historical light intensity and weather data changes, and predicting the light intensity based on the weather data changes, and then calculating the radiation intensity received by the curtain wall surface, distributing the radiation intensity based on the energy distribution model, and predicting the energy spectrum according to the transmitted radiation intensity, absorbed radiation intensity and curtain wall surface temperature, providing a basis for subsequent intelligent control.

[0059] Example 5: Based on embodiment 4, the weather influencing unit includes: Light intensity acquisition block, which obtains multiple light intensities according to the time schedule; Unified blocks, unified timestamps of light intensity and historical light intensity; Light intensity change curve block, constructs a light intensity change curve based on multiple light intensities; The curve interception block intercepts the historical light intensity daily variation curve according to the historical light intensity to obtain part of the historical light intensity daily variation curve; A first array determination block compares the light intensity variation curve with part of the historical light intensity daily variation curve to determine the first array; a second array determination block, the second array block performs data cleaning on the first array to obtain a second array; The current weather impact determination block determines the current weather impact according to the second data set and the weather change data and based on a preset climate impact model.

[0060] In this embodiment, based on obtaining the light intensity once every 30 seconds, at least 10 light intensities are obtained.

[0061] In this embodiment, a plurality of light intensities are obtained, and a plurality of historical light intensities are correspondingly determined.

[0062] In this embodiment, the light intensity variation curve is a curve showing the current light intensity variation over time.

[0063] In this embodiment, the historical light intensity daily variation curve is intercepted according to the time span of multiple historical light intensities to obtain a partial historical light intensity daily variation curve.

[0064] In this embodiment, the light intensity variation curve and part of the historical light intensity daily variation curve are overlapped and plotted, and a first array is generated based on the amplitude difference.

[0065] In this embodiment, data in the first array whose amplitude difference exceeds a preset change threshold is cleared to obtain a second array.

[0066] In this embodiment, the current weather impact is a preset climate impact model that is trained in advance based on various weather data, initial light intensity and attenuated light intensity, inputs weather change data and amplitude difference changes, and outputs an impact coefficient.

[0067] In this embodiment, the preset climate impact model is pre-trained based on various weather data, initial light intensity, and decaying light intensity. It inputs weather change data and amplitude difference changes and outputs an impact coefficient. Machine learning algorithms (such as neural networks and decision trees) can be used for training to establish a relationship model between weather data and light intensity impact coefficients based on a large amount of historical data.

[0068] The beneficial effects of the above technical solution are: constructing a light intensity change curve through multiple light intensities, and comparing it based on some historical light intensity daily change curves, determining the array, performing data cleaning, and obtaining the cleaned array, and determining the current weather impact based on the preset climate impact model, the cleaned array and weather change data, laying the foundation for subsequent prediction of light intensity.

[0069] Example 6: Based on embodiment 4, the illumination intensity prediction unit includes: The prediction block predicts the light intensity based on the historical light intensity daily variation curve; The current impact factor determination block determines the current impact factor based on the weather data changes and the current weather impact; Correction block, which corrects the predicted light intensity based on the current impact factor.

[0070] In this embodiment, according to the timestamp of the light intensity, the change curve of the historical light intensity daily change curve after the timestamp is used as the predicted light intensity; In this embodiment, if the weather data changes within a preset range, the current weather impact coefficient is the current impact factor. If the weather data changes beyond the preset range, the weather data change is input into the preset climate impact model to obtain the current impact factor, and the current impact factor is less than 1.

[0071] In this embodiment, the product of the current impact factor and the predicted light intensity is used as the corrected prediction result.

[0072] The beneficial effects of the above technical solution are: predicting light intensity through the historical light intensity daily change curve, determining the current influencing factor based on weather data changes and current weather impacts, and correcting the prediction results according to the current influencing factor, thereby improving the accuracy of light intensity prediction.

[0073] Example 7: Based on embodiment 4, the prediction unit includes:

[0074] in, Indicates indoor air density; represents the specific heat capacity of indoor air; represents the indoor field temperature T (x, y, z, t); k represents the thermal conductivity of air; Indicates the rate of change of curtain wall surface temperature in space; Represents heat dissipation.

[0075] The solution to the above formula is as follows: Spatial discretization: Divide the indoor preset space into multiple small grid units and discretely represent the temperature of each grid unit.

[0076] Time discretization: Divide time into a series of time steps and solve the heat diffusion equation in each time step.

[0077] Iterative solution: Based on the initial conditions (such as the indoor temperature distribution at the initial moment) and boundary conditions, the temperature of each grid cell in each time step is gradually solved in an iterative manner, and finally the temperature distribution of the indoor space at different times is obtained, that is, the energy spectrum.

[0078] The beneficial effect of the above technical solution is: the energy spectrum is predicted through indoor air density, specific heat capacity of indoor air, transmitted radiation intensity, absorbed radiation intensity and curtain wall surface temperature, laying the foundation for subsequent curtain wall structure adjustment.

[0079] Example 8: Based on Example 1, the adjustment module includes: a first time determination unit, which determines a first time when the range is exceeded according to the prediction result and a preset energy spectrum range; a time interval determining unit, which determines a time interval according to the first time and the current time; a change range determining unit, which determines the change range of the time interval according to the prediction result; An adjustment parameter determination unit, which determines the adjustment parameter according to a preset adjustment model and based on the time interval and the change amplitude; Adjustment unit, adjusts the curtain wall structure according to the adjustment parameters.

[0080] In this embodiment, the preset energy spectrum range is set in advance based on the human body's comfortable environment and is maintained between 22-26°C.

[0081] In this embodiment, the time interval is the difference between the first time and the current time.

[0082] In this embodiment, the variation range refers to the variation range of the temperature distribution in the energy spectrum.

[0083] In this embodiment, the preset adjustment model is pre-set and takes as input the time interval, energy change amplitude, and light intensity change, and outputs adjustment parameters. Adjustment parameters include curtain wall inclination angle and sunshade angle. For example, the model is a neural network model trained using a large amount of experimental data under different lighting and temperature change scenarios.

[0084] In this embodiment, when the temperature in the prediction result exceeds the preset range, the earliest time point of the exceedance is the time when the temperature in the room exceeds the preset range. If the prediction is that the temperature in one corner of the room will reach 26.1°C at 1:30 pm, exceeding the preset upper limit for the first time, then 1:30 pm is the first time.

[0085] In this embodiment, the adjustment parameters include, for example, the curtain wall inclination angle, the sun visor angle, etc. For example, according to the model calculation, it is found that the curtain wall inclination angle needs to be adjusted from 0° to 10°, and the sun visor angle needs to be adjusted from horizontal to 30°.

[0086] In this embodiment, the curtain wall structure includes the physical structure of the curtain wall, such as glass panels, support frames, sunshades and other components.

[0087] The beneficial effects of the above technical solution are: determining the time out of range through the prediction results and the preset energy spectrum range, and determining the time interval based on the current time, and then determining the adjustment parameters according to the preset adjustment model, time interval and change amplitude to adjust the curtain wall structure to achieve the purpose of intelligent control.

[0088] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. The integrated natural lighting and sunshade system based on intelligent control is characterized by: include: An optical parameter acquisition module, based on an optical sensor, acquires optical parameters and marks a timestamp; wherein the optical parameters include direct sunlight angle and light intensity; An energy spectrum determination module, which determines the energy spectrum of a preset indoor space based on an infrared sensor; A prediction module, configured to predict the energy spectrum based on the optical parameters and curtain wall parameters; Adjustment module, adjusts the curtain wall structure according to the prediction results and the preset energy spectrum range.

2. The integrated natural lighting and sunshade system based on intelligent control according to claim 1 is characterized in that: The direct sunlight angle includes the sunlight azimuth angle and the sunlight altitude angle, and the optical parameter acquisition module includes: a first value determining unit, configured to provide a plurality of azimuth optical sensors and obtain first values of the azimuth optical sensors; a normalization processing unit, performing normalization processing on the first value; a sunlight azimuth angle calculation unit, which calculates the sunlight azimuth angle according to the normalized value; a second value determination unit, configured to provide a plurality of vertical optical sensors and obtain second values of the vertical sensors; a sunlight altitude angle calculation unit, configured to calculate the sunlight altitude angle based on the second value; The light intensity calculation unit calculates the light intensity according to the first value and the second value.

3. The integrated natural lighting and sunshade system based on intelligent control according to claim 1 is characterized in that: The energy spectrum determination module includes: A sensor setting unit, arranged according to a grid layout, for arranging a plurality of the infrared sensors in the indoor preset space; a temperature data acquisition unit, for acquiring temperature data and spatial coordinates of each of the infrared sensors; A data preprocessing unit, which preprocesses the temperature data to generate discrete point cloud data; The energy spectrum generating unit converts discrete temperature points into continuous energy distribution to generate the energy spectrum.

4. The integrated natural lighting and sunshade system based on intelligent control according to claim 1 is characterized in that: The prediction module includes: A curve acquisition unit, which acquires a historical daily variation curve of light intensity and a historical daily variation curve of sunlight direct angle; A current time determination unit determines the current time based on the direct sunlight angle and a historical daily variation curve of the direct sunlight angle; A historical light intensity determination unit, which determines the historical light intensity according to the current time and the historical light intensity daily variation curve; Weather data acquisition unit, obtains current weather data changes; The weather impact unit determines the current weather impact based on the light intensity, historical light intensity and weather data changes; Light intensity prediction unit, which predicts light intensity based on current weather influence and weather data changes; A radiation intensity calculation unit calculates the radiation intensity received by the curtain wall surface based on the predicted result of light intensity; Radiation intensity distribution unit, which distributes radiation intensity according to curtain wall parameters and energy distribution model; in, Indicates the radiation intensity; represents the intensity of transmitted radiation; Indicates the intensity of absorbed radiation; Indicates the intensity of reflected radiation; Indicates the curtain wall transmittance; Indicates the absorption rate of the curtain wall; Indicates the reflectivity of the curtain wall; Surface temperature calculation unit, calculates the curtain wall surface temperature based on the absorbed radiation intensity; Where U represents the thermal conductivity; Indicates the surface temperature of the curtain wall; Indicates the indoor temperature; Indicates outdoor temperature; represents the surface emissivity; represents the Stefan-Boltzmann constant; Indicates the indoor temperature transfer coefficient; Indicates the rate of change of indoor temperature; Indicates the rate of change of outdoor temperature; Indicates the indoor temperature change correction coefficient; Indicates the correction factor for outdoor temperature change; represents the outdoor temperature conductivity coefficient; The prediction unit predicts the energy spectrum according to the transmitted radiation intensity, the absorbed radiation intensity, the curtain wall surface temperature, the indoor temperature conductivity coefficient and the outdoor temperature conductivity coefficient.

5. The integrated natural lighting and sunshade system based on intelligent control according to claim 4 is characterized in that: The weather influencing unit includes: A light intensity acquisition block, which acquires a plurality of light intensities according to a time schedule; A unification block unifies the timestamps of the light intensity and the historical light intensity; a light intensity change curve block, for constructing a light intensity change curve according to a plurality of light intensities; A curve interception block intercepts the historical light intensity daily variation curve according to the historical light intensity to obtain a portion of the historical light intensity daily variation curve; A first array determination block compares the light intensity variation curve with the partial historical light intensity daily variation curve to determine a first array; a second array determination block, the second array block performing data cleaning on the first array to obtain a second array; The current weather impact determination block determines the current weather impact according to the second data array and the weather change data and based on a preset climate impact model.

6. The integrated natural lighting and sunshade system based on intelligent control according to claim 4 is characterized in that: The illumination intensity prediction unit includes: A prediction block, which predicts the light intensity based on the historical light intensity daily variation curve; a current impact factor determination block, which determines a current impact factor according to the weather data change and the current weather impact; A correction block corrects the prediction result based on the current impact factor.

7. The integrated natural lighting and sunshade system based on intelligent control according to claim 4 is characterized in that: The prediction unit includes: in, Indicates indoor air density; represents the specific heat capacity of indoor air; represents the indoor field temperature T (x, y, z, t); k represents the thermal conductivity of air; Indicates the rate of change of curtain wall surface temperature in space; Represents heat dissipation.

8. The integrated natural lighting and sunshade system based on intelligent control according to claim 1 is characterized in that: The adjustment module includes: a first time determining unit, for determining a first time out of range according to the prediction result and a preset energy spectrum range; a time interval determining unit, configured to determine a time interval according to the first time and a current time; a change range determining unit, configured to determine a change range of the time interval according to the prediction result; an adjustment parameter determination unit, configured to determine an adjustment parameter according to a preset adjustment model and based on the time interval and the change amplitude; An adjustment unit adjusts the curtain wall structure according to the adjustment parameters.

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