A smart building lighting and sunshade linkage adaptive adjustment method and system

Abstract

The application discloses a kind of intelligent building lighting and sunshade linkage adaptive adjustment method and system, it is related to building intelligent control technical field, the method includes: through indoor and outdoor light data acquisition by illumination sensor, calculate and preset comfort range's light deviation value;According to light deviation value and outdoor light data, calculate the light spectrum weight factor that trades off sunshade and lighting adjustment priority;Utilize the factor and parallelly solve out sunshade angle compensation value and lighting brightness compensation value;Synchronous drive sunshade device and lighting lamp execute adjustment, and update its current state;Monitoring adjusted energy consumption and comfort data, calculate comprehensive energy efficiency index, and feedback optimization light spectrum weight factor calculation rule, realize closed-loop adaptive control.The application can effectively improve building light environment comfort, reduce lighting energy consumption, realize the intelligent linkage and optimized operation of lighting and sunshade system.

Description

Technical Field

[0001] The present invention relates to the technical field of building intelligent control, and particularly to a method for coordinated and adaptive adjustment of lighting and shading in smart buildings. Background Art

[0002] With the popularization of the concepts of smart buildings and green buildings, the intelligent control of lighting and shading systems has become an important means to improve building energy efficiency and user comfort. Traditional lighting and shading systems often operate independently and lack coordination, resulting in energy waste and insufficient comfort. For example, on a sunny day, if the shading system is not adjusted in time, it may cause indoor glare. At this time, it is difficult to completely compensate for the light environment quality only by dimming the lighting system; conversely, if the shading is excessive, additional lighting needs to be turned on, increasing energy consumption.

[0003] In the prior art, although some systems have tried coordinated control, most of them adopt control strategies with simple rules and fixed thresholds, and it is difficult to adapt to changing environments and user needs. The lack of a dynamic weight mechanism and feedback optimization ability results in system response lag, low adjustment accuracy, and limited energy efficiency optimization. Therefore, there is an urgent need for a coordinated adjustment method and system that can real-time sense environmental changes, intelligently weigh the priorities of shading and lighting, and have the ability of self-learning and optimization. Summary of the Invention

[0004] A method and system for coordinated and adaptive adjustment of lighting and shading in smart buildings, comprising:

[0005] S1. The smart building system collects indoor and outdoor light data through light sensors and calculates the light deviation value from the preset comfort range;

[0006] S2. Analyze the intensity, duration, and change trend of outdoor light, evaluate the availability of natural light and its potential contribution to indoor lighting, and then comprehensively consider the numerical values and distribution characteristics of the light deviation in each indoor area to calculate the spectral weight factor for weighing the priorities of shading and lighting adjustment;

[0007] S3. According to the adjustment tendency indicated by the spectral weight factor, parallelly calculate the shading angle compensation value and the lighting brightness compensation value, and perform validity verification and range constraint on the preliminary calculation results;

[0008] S4. According to the shading angle compensation value and the lighting brightness compensation value, trigger the feedback mechanism to synchronously drive the shading device and the lighting fixture to perform adjustment and update their current states; [[ID=�0]]

[0009] S5. According to the pre-constructed multi-dimensional comprehensive evaluation system of energy efficiency and comfort, monitor the energy consumption and comfort data after adjustment, calculate the comprehensive energy efficiency index, and accordingly feedback and optimize the calculation rule of the spectral weight factor to complete the adaptive adjustment closed-loop.

[0010] The above-described adaptive adjustment method for lighting and shading linkage in smart buildings includes the following sub-steps: The smart building system collects indoor and outdoor lighting data through light sensors and calculates the lighting deviation value from a preset comfort range.

[0011] Simultaneously, data on light intensity in different functional areas indoors and from multiple directions outside the building were collected;

[0012] The collected real-time illumination data is compared with the preset comfortable illumination range for each area in the system, and the specific deviation between the current illumination level and the median or optimal value of the comfortable range for each area is calculated.

[0013] The deviation of all regions is analyzed, regions with deviations exceeding the preset allowable threshold are selected, and these regions are accurately marked as the regions that need to be adjusted first.

[0014] The above-described adaptive adjustment method for lighting and shading linkage in smart buildings includes the following sub-steps: Calculating a spectral weighting factor that balances the priorities of shading and lighting adjustment based on illumination deviation values ​​and outdoor illumination data.

[0015] Based on the intensity, duration, and trend of outdoor light, a comprehensive assessment is made of the current availability of natural light and its potential contribution to indoor lighting.

[0016] Based on the specific values ​​and spatial distribution of light deviation in various indoor areas, the weight allocation ratio between shading adjustment and electrical lighting adjustment at the current moment is calculated.

[0017] Based on the above analysis, a dynamically adjustable spectral weighting factor is generated, which can be directly used in the subsequent parallel calculation of shading and lighting compensation values.

[0018] The above-described adaptive adjustment method for lighting and shading linkage in smart buildings, which utilizes a spectral weighting factor to calculate shading angle compensation values ​​and lighting brightness compensation values ​​in parallel, includes the following sub-steps:

[0019] Based on the regulation tendency indicated by the spectral weighting factor, the proportion of the total regulation amount that can be used for shading regulation and lighting regulation should be reasonably allocated;

[0020] Calculate independently the angle offset required for the shading blades to achieve the target shading effect, and the brightness compensation value required for the lighting fixtures to supplement indoor lighting.

[0021] The angle compensation value and brightness compensation value obtained from the preliminary calculation are validated and their range is constrained to prevent overshoot, equipment overload or energy waste.

[0022] The above-described adaptive adjustment method for the linkage between lighting and shading in smart buildings includes the following sub-steps: The method independently calculates the angle offset required for the shading blades to achieve the target shading effect, and the brightness compensation value required for the lighting fixtures to supplement indoor illumination.

[0023] Based on the current blade angle of the shading device, the outdoor sun's azimuth and altitude angle, calculate the blade angle value that needs to be adjusted to block excess glare or introduce an appropriate amount of natural light.

[0024] Based on the illumination deviation in each indoor area and the expected contribution of natural light after passing through the shading system, the brightness values ​​that the electrical lighting system needs to supplement or reduce are calculated.

[0025] Conduct a synergistic check on the adjustment amount of the shading angle and the adjustment amount of the lighting brightness to ensure that the adjustment directions of the two are consistent and do not conflict, and avoid over-adjustment or mutual cancellation.

[0026] The above-described adaptive adjustment method for lighting and shading linkage in smart buildings includes the following sub-steps: Based on shading angle compensation values ​​and lighting brightness compensation values, the shading device and lighting fixtures are synchronously driven to perform adjustments and their current states are updated.

[0027] After the adjustment action is completed, the light data of each area in the room is immediately collected again by the light sensor to verify whether the adjustment effect has brought the light level into the preset comfortable range.

[0028] Accurately record the energy consumption data of the sunshade motor and lighting fixtures during this adjustment process, and calculate the energy efficiency ratio of this adjustment action;

[0029] If the verification finds that the adjustment effect does not meet the expected target, or the energy efficiency ratio is too low, the feedback mechanism will be automatically triggered to recalculate the spectral weighting factor and start a new round of adjustment.

[0030] The adaptive adjustment method for integrated lighting and shading in smart buildings, as described above, involves monitoring energy consumption and comfort data after adjustment, calculating a comprehensive energy efficiency index, and using this as feedback to optimize the calculation rules for the spectral weighting factor, thus completing the adaptive adjustment closed loop. This includes the following sub-steps:

[0031] Based on the multiple adjustment records accumulated during the system's historical operation and their corresponding energy consumption results and comfort compliance status, a multi-dimensional comprehensive evaluation system for energy efficiency and comfort is established.

[0032] Based on the latest comprehensive evaluation results, the key parameters and calculation logic involved in the calculation of the spectral weighting factor are adjusted in reverse.

[0033] Through continuous iterative optimization and experience learning, the system can gradually adapt to the changing light characteristics brought about by different dates, different times of day, and different seasons.

[0034] An adaptive adjustment system for integrated lighting and shading in smart buildings, comprising:

[0035] Data sensing module: The smart building system collects indoor and outdoor lighting data through light sensors and calculates the light deviation value from the preset comfort range;

[0036] Intelligent decision-making module: Based on the light deviation value and outdoor light data, calculate the spectral weighting factor to balance the priority of shading and lighting adjustment; using the spectral weighting factor, calculate the shading angle compensation value and the lighting brightness compensation value in parallel.

[0037] Execution control module: Based on the shading angle compensation value and the lighting brightness compensation value, synchronously drive the shading device and lighting fixtures to perform adjustments and update their current status;

[0038] Feedback optimization module: Monitors the adjusted energy consumption and comfort data, calculates the comprehensive energy efficiency index, and optimizes the calculation rules of the spectral weighting factor based on the feedback to complete the adaptive adjustment closed loop.

[0039] A computer storage medium, characterized in that it comprises: at least one memory and at least one processor;

[0040] Memory, used to store one or more program instructions;

[0041] A processor is used to run one or more program instructions to execute the adaptive adjustment method for intelligent building lighting and shading linkage described in any of the above-mentioned embodiments.

[0042] The beneficial effects achieved by this invention are as follows:

[0043] (1) In terms of environmental perception and data processing, the light deviation is accurately perceived and calculated through multi-source light sensors and dynamic comfort model, providing a reliable data basis for intelligent regulation and significantly improving the accuracy of environmental perception.

[0044] (2) In terms of control strategy, an innovative spectral weighting factor mechanism is introduced to dynamically weigh the adjustment priorities of shading and lighting by comprehensively considering multiple factors, so as to achieve a more refined balance between energy saving and comfort and overcome the problem of unreasonable adjustment in traditional systems.

[0045] (3) In terms of execution architecture, a parallel solution and synchronous drive architecture is adopted, which greatly improves the system response speed and control accuracy, effectively avoids the lag and state inconsistency caused by time-sharing adjustment, and improves the overall response performance.

[0046] (4) In terms of system intelligence and continuous optimization, based on energy efficiency indicators and machine learning feedback, the system can continuously optimize the weight factor calculation rules to form an energy-saving and comfortable closed-loop control, and has self-learning and adaptability.

[0047] (5) In terms of system compatibility and scalability, the design has good compatibility and scalability, supports access to multiple types of devices and protocol integration, and is easy to promote and apply in smart buildings. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0049] Figure 1 This is a flowchart of an adaptive adjustment method for the linkage between lighting and shading in smart buildings, provided in an embodiment of this application.

[0050] Figure 2 This is a schematic diagram of an adaptive adjustment system for smart building lighting and shading linkage provided in an embodiment of this application. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] Example 1

[0053] like Figure 1 As shown in the figure, an embodiment of this application provides a method for adaptive adjustment of lighting and shading linkage in smart buildings, comprising:

[0054] Step S1: The smart building system collects indoor and outdoor lighting data through light sensors and calculates the lighting deviation value from the preset comfort range;

[0055] Specifically, by synchronously collecting illumination data from various functional areas indoors and from multiple directions outside the building, and comparing the real-time data with the system's preset comfortable illumination ranges for each area, the deviation from the median or optimal value of the comfortable range is calculated. Then, the deviation of all areas is analyzed, and areas exceeding the set threshold are accurately marked as target areas requiring priority adjustment. This includes the following sub-steps:

[0056] Step S11: Simultaneously collect light intensity data from different functional areas indoors and from multiple directions outside the building;

[0057] The system uses high-precision light sensors deployed in various functional areas, as well as external sensors installed on multiple orientations of the building facade, to synchronously acquire light intensity data at a fixed sampling frequency. All sensor data is transmitted to the central processing unit in real time via wired or wireless communication protocols to ensure that the data is strictly aligned in timestamps and to avoid inconsistencies in spatial lighting conditions caused by acquisition delays.

[0058] Step S12: Compare the collected real-time illumination data with the preset comfortable illumination range for each area in the system, and calculate the specific deviation between the current illumination level of each area and the median or optimal value of the comfortable range.

[0059] Based on the purpose of each functional area and the human body's comfortable lighting requirements, a standard illuminance range is pre-set; the real-time collected illuminance values ​​are compared with the median or optimal reference value of the corresponding area's comfort range, and the absolute and relative deviations are calculated using formulas:

[0060] Absolute deviation: in, Indicates the first Each region at the reference time The absolute deviation at that point; It indicates that it is the first Each region at the reference time The absolute value of a certain original deviation at a certain location; This represents the normalized attenuation coefficient; Indicates the first Historical variance of illumination in each region; Indicates the first The optimal light intensity value for each region.

[0061] Relative deviation: in, Indicates the first Each region at the reference time The relative deviation at the location; Indicates the first Each region at the reference time The absolute deviation at that point; Indicates the first The optimal light intensity value for each region; Indicates the first The upper limit of the comfort range for each area; Indicates the first The lower limit of the comfort range for each region; Indicates the range width index.

[0062] The positive and negative directions and magnitudes of the deviations in each area are recorded to form a list of regional illumination state deviations.

[0063] Step S13: Analyze the deviation of all regions, screen out the regions whose deviation exceeds the preset allowable threshold, and accurately mark them as the regions to be adjusted that need to be adjusted first.

[0064] Set a dynamically adjustable deviation tolerance threshold, sort and prioritize the deviation amounts of all regions; identify regions whose absolute deviation values ​​exceed the threshold as abnormal regions, and determine the urgency of adjustment based on the magnitude and duration of the deviation; finally, generate a list of regions to be adjusted and push it to the linkage control module as the basis for adjustment decisions.

[0065] Step S2: Calculate the spectral weighting factor that balances the priorities of shading and lighting adjustment based on the light deviation value and outdoor light data;

[0066] Specifically, by analyzing the intensity, duration, and trend of outdoor light, the availability of natural light and its potential contribution to indoor lighting are assessed. Then, considering the numerical and distribution characteristics of light deviations in different indoor areas, the weighting ratio of shading adjustment and electrical lighting adjustment at the current moment is calculated. This generates a dynamically adjustable spectral weighting factor for subsequent parallel calculations of shading and lighting compensation values, including the following sub-steps:

[0067] Step S21: Based on the intensity, duration and trend of outdoor light, comprehensively judge the current availability of natural light and its potential contribution to indoor lighting.

[0068] By monitoring the intensity, duration, and trends of outdoor light in real time, the availability of natural light in both time and space is comprehensively assessed to determine its potential contribution to indoor lighting systems.

[0069] Step S22: Based on the specific values ​​and spatial distribution of the light deviation in each area of ​​the room, calculate the weight distribution ratio between the shading adjustment behavior and the electrical lighting adjustment at the current moment.

[0070] Based on the real-time collected illumination deviation values ​​of various indoor areas and their spatial distribution characteristics, we identify areas with insufficient or excessive illumination. Combining the functional attributes of these areas with human comfort requirements, we calculate the respective weighting ratios of shading and electrical lighting adjustments under the current environmental conditions. The following formula represents the respective weighting ratios of shading and electrical lighting adjustments:

[0071] in, Indicates time The weighting percentage of "prioritizing shading control"; Indicates the first A point in time; Indicates the adjustment parameter, used for control. right Sensitivity; Represents variables related to solar radiation; Variables related to the thermal environment; Variables representing the potential for natural lighting; This indicates the lighting adjustment weight.

[0072] Step S23: Based on the above analysis, generate a dynamically adjustable spectral weighting factor, which can be directly used in the subsequent parallel calculation of shading and lighting compensation values;

[0073] Based on the aforementioned analysis results, a spectral weighting factor that can dynamically respond to environmental changes is generated. This factor serves as a comprehensive control coefficient and is used to rationally allocate the proportions of the shading device and the electrical lighting system in the overall adjustment strategy when calculating the compensation values ​​of the shading device and the electrical lighting system in parallel, thereby achieving the optimal balance between energy consumption and comfort between the shading and lighting systems.

[0074] Step S3: Using the spectral weighting factor, calculate the shading angle compensation value and the lighting brightness compensation value in parallel.

[0075] Specifically, based on the spectral weighting factor and The indicated adjustment tendency is used to reasonably allocate the proportion of the total adjustment available for the shading and lighting systems; the angle offset required for the shading blades to achieve the target shading effect and the brightness compensation value required for the lighting fixtures to supplement indoor lighting are calculated independently—the shading angle is calculated based on the current blade status, solar azimuth, and altitude angle to block glare or introduce an appropriate amount of natural light, while the lighting brightness is calculated to compensate for the light deviation and natural light contribution in each area; the adjustment amounts of both are checked for synergy to ensure consistent adjustment directions and avoid conflicts or cancellations; finally, the preliminary calculation results are validated and range-bound to prevent overshoot, equipment overload, or energy waste, including the following sub-steps:

[0076] Step S31: Based on the adjustment tendency indicated by the spectral weighting factor, reasonably allocate the proportion of the total adjustment amount that can be used for shading adjustment and lighting adjustment;

[0077] Based on the weighting factors extracted from the real-time spectral analysis results, the system determines whether the current environment is dominated by shading adjustment or lighting compensation, and then dynamically allocates the proportion of adjustment resources that can be used for shading mechanisms and lighting equipment.

[0078] Step S32: Calculate independently the angle offset required for the shading blades to achieve the target shading effect, and the brightness compensation value required for the lighting fixtures to supplement indoor lighting.

[0079] Step S321: Based on the current blade angle of the shading device, the outdoor sun's azimuth and altitude angle information, calculate the blade angle value that needs to be adjusted to block excess glare or introduce an appropriate amount of natural light.

[0080] The system accesses solar position parameters provided by a real-time astronomical calculation module, and combines these with structural parameters such as building facade orientation and window-to-wall ratio to calculate the ideal shading angle hourly using formulas.

[0081] in, Indicates the ideal shading angle; Represents the arcsine function; Indicates the altitude angle of the sun; Indicates the azimuth of the sun; Indicates the orientation of the building facade; Indicates the building construction correction factor; Indicates the building construction correction factor; Indicates the efficiency coefficient; This indicates the final shading angle compensation value; Indicates the current blade angle; This indicates the weight of the shading adjustment.

[0082] Use shading adjustment weight The angles are weighted to reflect the priority of shading adjustments.

[0083] Step S322: Based on the illumination deviation of each indoor area and the expected contribution of natural light after passing through the shading system, calculate the brightness value that the electrical lighting system needs to supplement or reduce.

[0084] The system acquires the actual light distribution through a network of illuminance sensors deployed in the space, compares it with the set target value to determine the deviation, and then, combined with a natural light penetration model after shading adjustment, estimates the light gap that still needs to be supplemented by artificial lighting. Finally, it uses a formula to calculate the target brightness value of the lighting equipment.

[0085] in, Indicates the target brightness value of the lighting equipment; Indicates the efficiency coefficient of the lighting system; Indicates the natural light utilization coefficient; This indicates the target illuminance that the scene needs to achieve; Indicates solar radiation intensity; This represents the cloud cover correction factor; This indicates the change in the sun's angle; This represents the correction factor for the average illuminance deviation; Indicates the deviation of average illuminance; Represents the system correction constant; This indicates the final lighting brightness compensation value; Indicates the current brightness value; This indicates the lighting adjustment weight.

[0086] Step S323: Perform a coordination check on the shading angle adjustment amount and the lighting brightness adjustment amount to ensure that the two adjustment directions are consistent and do not conflict, and avoid over-adjustment or mutual cancellation.

[0087] Step S33: Verify the validity and constrain the range of the angle compensation value and brightness compensation value obtained from the preliminary calculation to prevent phenomena such as adjustment overshoot, equipment overload or energy waste.

[0088] The system is equipped with physical limit checks and energy boundary judgment mechanisms to limit the amplitude and rate of change of all output commands, avoiding mechanical impacts or frequent large-scale dimming of lighting equipment; at the same time, it incorporates historical regulation efficiency evaluation data to filter and correct abnormal or inefficient commands, ensuring that the output regulation is within the allowable range of the equipment and meets the requirements of green operation.

[0089] Step S4: Based on the shading angle compensation value and the lighting brightness compensation value, synchronously drive the shading device and lighting fixtures to perform adjustments and update their current status;

[0090] Specifically, immediately after adjustment, real-time light data for each area is collected via light sensors to assess whether the actual light level meets the expected comfort range; simultaneously, energy consumption data of the shading motor and lighting fixtures are accurately recorded, and the energy efficiency ratio of this adjustment is calculated; if the adjustment effect is not achieved or the energy efficiency ratio is too low, a feedback mechanism is automatically triggered to recalculate the spectral weighting factor and initiate a new round of adjustment to achieve more precise light environment control and energy consumption optimization, including the following sub-steps:

[0091] Step S41: After the adjustment action is completed, immediately re-collect the light data of each area in the room through the light sensor to verify whether the adjustment effect has brought the light level into the preset comfortable range.

[0092] The measured illuminance values ​​of each area are compared with the preset comfortable illuminance range to determine whether all areas are within the target illuminance range. The degree of deviation and distribution of non-compliant areas are also statistically analyzed as a basis for evaluating the adjustment effect.

[0093] Step S42: Accurately record the energy consumption data of the sunshade motor and lighting fixtures during this adjustment process, and calculate the energy efficiency ratio of this adjustment action;

[0094] Based on the ratio of the improvement in light intensity to the total energy consumption, the energy efficiency ratio for this adjustment is calculated using the following formula:

[0095] in, Indicates the normalized energy efficiency ratio; This represents quantities related to light-related benefits; Indicates total energy consumption; Indicates the base energy offset; Indicates time-related quantities; This represents the time penalty coefficient.

[0096] This is used to comprehensively evaluate the economic efficiency and energy conservation of this coordinated regulation.

[0097] Step S43: If the verification finds that the adjustment effect has not reached the expected target, or the energy efficiency ratio is too low, the feedback mechanism will be automatically triggered to recalculate the spectral weighting factor and start a new round of adjustment.

[0098] Based on the actual degree of light deviation and energy efficiency deviation, the spectral weighting factor is recalculated, and the compensation parameters are corrected in conjunction with historical adjustment records. A new round of shading and lighting linkage adjustment is initiated until the actual light distribution and energy efficiency ratio meet the requirements.

[0099] Step S5: Monitor the adjusted energy consumption and comfort data, calculate the comprehensive energy efficiency index, and optimize the calculation rules of the spectral weighting factor based on the feedback to complete the adaptive adjustment closed loop.

[0100] Specifically, based on multiple adjustment records accumulated during the system's historical operation and their corresponding energy consumption and comfort compliance status, a multi-dimensional comprehensive evaluation system for energy efficiency and comfort is constructed. Based on the latest comprehensive evaluation results, key parameters and calculation logic in the spectral weighting factor calculation process are adjusted in reverse. Through continuous iterative optimization and experience learning, the system gradually acquires the ability to adapt to changes in light intensity on different dates, at different times of day, and in different seasons. This includes the following sub-steps:

[0101] Step S51: Based on the multiple adjustment records accumulated in the historical operation of the system and their corresponding energy consumption results and comfort standards, establish a multi-dimensional comprehensive evaluation system for energy efficiency and comfort.

[0102] Historical adjustment records are extracted from the actual operation database of the lighting and shading linkage system, including lighting power, number of shading mechanism actions, indoor illuminance uniformity, user comfort feedback, and total energy consumption data for each time period. These data are cleaned and normalized to construct a comprehensive evaluation system with energy consumption per unit area, comfort compliance rate, and light stability as core indicators. A weighted aggregation method is used to generate a comprehensive energy efficiency index, where the weights of each indicator are configured according to the dynamic needs of the actual application scenario, ensuring that the evaluation results reflect both energy-saving effects and environmental comfort.

[0103] Step S52: Based on the latest comprehensive evaluation results, adjust the key parameters and calculation logic involved in the calculation of the spectral weighting factor in reverse.

[0104] The comprehensive energy efficiency index is compared with the preset target range. If the evaluation result does not meet expectations, the parameter adjustment mechanism is activated. Based on the ratio between energy efficiency deviation and comfort deviation, the adjustment direction and magnitude of key parameters such as illuminance compensation coefficient and spectral sensitivity factor used in the calculation of spectral weighting factor are determined. By establishing a parameter-performance response relationship table, the current optimal parameter correction strategy is inferred, and the updated parameter set is applied in the next calculation cycle to gradually approach the optimal energy efficiency-comfort balance point.

[0105] Step S53: Through continuous iterative optimization and experience learning, the system can gradually adapt to the changing characteristics of light intensity brought about by different dates, different times of day, and different seasons.

[0106] After each adjustment and evaluation, the system automatically records the current environmental characteristics, adjustment parameters, and comprehensive energy efficiency indicators to form an experience dataset. Based on this dataset, the calculation rules for the spectral weighting factor are periodically optimized to identify the optimal parameter combinations under different seasons, weather conditions, and time periods. By introducing time series analysis and rule reasoning mechanisms, the system can gradually build a knowledge base for responding to changes in illumination, thereby achieving long-term adaptive adjustment without human intervention.

[0107] Example 2

[0108] like Figure 2 As shown, Embodiment 2 of this application provides an adaptive adjustment system for the linkage between lighting and shading in smart buildings, comprising:

[0109] Data sensing module 21: Collects indoor and outdoor lighting data through a light sensor and calculates the light deviation value from the preset comfort range, including the following sub-modules:

[0110] Data acquisition submodule 211: Simultaneously collects light intensity data from different functional areas indoors and from multiple directions outside the building;

[0111] Data processing and calculation submodule 212: compares the collected real-time illumination data with the preset comfortable illumination range for each area in the system, and calculates the specific deviation between the current illumination level and the median or optimal value of the comfortable range for each area.

[0112] Data Analysis and Decision Submodule 213: Analyzes the deviation of all regions, filters out regions whose deviation exceeds the preset allowable threshold, and accurately marks them as regions to be adjusted with priority.

[0113] Intelligent Decision Module 22: Analyzes the intensity, duration, and trend of outdoor light, assesses the availability of natural light and its potential contribution to indoor lighting, and then comprehensively considers the numerical and distribution characteristics of light deviation in various indoor areas to calculate the spectral weighting factor that balances the priorities of shading and lighting adjustment. Based on the adjustment tendency indicated by the spectral weighting factor, it calculates the shading angle compensation value and lighting brightness compensation value in parallel, and verifies the validity and limits the range of the preliminary calculation results. This module includes the following sub-modules:

[0114] Natural light contribution analysis submodule 221: Based on the intensity, duration and trend of outdoor light, comprehensively judge the current availability of natural light and its potential contribution to indoor lighting.

[0115] Light adjustment strategy trade-off submodule 222: Based on the specific values ​​and spatial distribution of light deviation in various indoor areas, calculate the weight allocation ratio between shading adjustment behavior and electrical lighting adjustment at the current moment.

[0116] Dynamic Spectral Weighting Factor Generation Submodule 223: Based on the above analysis, a dynamically adjustable spectral weighting factor is generated, which is directly used in the subsequent parallel calculation of shading and lighting compensation values;

[0117] Regulation allocation submodule 224: Based on the regulation tendency indicated by the spectral weighting factor, rationally allocate the proportion of the total regulation that can be used for shading regulation and lighting regulation;

[0118] Parallel compensation calculation submodule 225: independently calculates the angle offset required for the shading blades to achieve the target shading effect, and the brightness compensation value required for the lighting fixtures to supplement indoor lighting;

[0119] Compensation value verification and constraint submodule 226: Verifies the validity and constrains the range of the angle compensation value and brightness compensation value obtained in the preliminary calculation to prevent phenomena such as adjustment overshoot, equipment overload or energy waste;

[0120] Execution control module 23: Based on the shading angle compensation value and the lighting brightness compensation value, synchronously drives the shading device and lighting fixtures to perform adjustments and updates their current state, including the following sub-modules:

[0121] Adjustment effect verification submodule 231: After the adjustment action is completed, immediately collect the light data of each area in the room again through the light sensor to verify whether the adjustment effect has brought the light level into the preset comfortable range.

[0122] Energy Efficiency Assessment and Recording Submodule 232: Accurately record the energy consumption data of the shading motor and lighting fixtures during this adjustment process, and calculate the energy efficiency ratio of this adjustment action;

[0123] Feedback optimization control submodule 233: If the verification finds that the adjustment effect does not meet the expected target, or the energy efficiency ratio is too low, the feedback mechanism is automatically triggered to recalculate the spectral weighting factor and start a new round of adjustment;

[0124] Feedback Optimization Module 24: Based on a pre-constructed multi-dimensional energy efficiency and comfort comprehensive evaluation system, it monitors the adjusted energy consumption and comfort data, calculates the comprehensive energy efficiency index, and optimizes the calculation rules of the spectral weighting factor accordingly to complete the adaptive adjustment closed loop. This module includes the following sub-modules:

[0125] Data Analysis and Evaluation Submodule 241: Based on the multiple adjustment records accumulated during the system's historical operation and their corresponding energy consumption results and comfort compliance status, establish a multi-dimensional comprehensive evaluation system for energy efficiency and comfort.

[0126] Rule optimization calculation submodule 242: Based on the latest comprehensive evaluation results, adjust the key parameters and calculation logic involved in the calculation of spectral weighting factors in reverse.

[0127] Self-learning evolution submodule 243: Through continuous iterative optimization and experience learning, the system can gradually adapt to the changing characteristics of light intensity brought about by different dates, different times of day, and different seasons.

[0128] Corresponding to the above embodiments, the present invention provides a computer storage medium, including: at least one memory and at least one processor;

[0129] The memory is used to store one or more program instructions;

[0130] A processor is used to run one or more program instructions to execute a method for adaptive adjustment of lighting and shading linkage in smart buildings;

[0131] Corresponding to the above embodiments, this embodiment of the invention provides a computer-readable storage medium containing one or more program instructions, which are executed by a processor to provide a method for adaptive adjustment of lighting and shading linkage in smart buildings.

[0132] The embodiments disclosed in this invention provide a computer-readable storage medium storing computer program instructions. When the computer program instructions are executed on a computer, the computer executes the aforementioned adaptive adjustment method for intelligent building lighting and shading linkage.

[0133] In this embodiment of the invention, the processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0134] The various methods, steps, and logic diagrams disclosed in the embodiments of this invention can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The processor reads information from the storage medium and, in conjunction with its hardware, completes the steps of the above methods.

[0135] The storage medium can be memory, such as volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.

[0136] Among them, non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory.

[0137] Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (Synchlink DRAM, SLDRAM), and direct memory bus RAM (DRRAM).

[0138] The storage media described in the embodiments of the present invention are intended to include, but are not limited to, these and any other suitable types of memory.

[0139] Those skilled in the art will recognize that, in one or more of the examples above, the functions described in this invention can be implemented using a combination of hardware and software. When applied as software, the corresponding functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of computer programs from one place to another. Storage media can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0140] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, or improvements made on the basis of the technical solution of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for adaptive adjustment of intelligent building lighting and shading linkage, characterized in that, Comprise: S1, the intelligent building system collects indoor and outdoor light data through light sensors, and calculates the light deviation value from the preset comfortable range; S2, analyze the intensity, duration and trend of outdoor light, evaluate the availability of natural light and the potential contribution to indoor lighting, and then consider the numerical value and distribution characteristics of indoor light deviation, calculate the spectral weight factor that balances the priority of shading and lighting adjustment; The following formula represents the respective weighting of shading adjustment and electrical lighting adjustment: ,in, and For spectral weighting factors, Indicates time The weighting of priority given to shading control; Indicates the first A point in time; Indicates the adjustment parameter, used for control. right Sensitivity; Represents variables related to solar radiation; Variables related to the thermal environment; Variables representing the potential for natural lighting; Indicates the lighting adjustment weight; S3, according to the adjustment tendency indicated by the spectral weight factor, the shading angle compensation value and the lighting brightness compensation value are calculated in parallel, and the validity check and range constraint of the preliminary calculation result are carried out; S4, according to the shading angle compensation value and the lighting brightness compensation value, trigger the feedback mechanism to drive the shading device and lighting lamps to execute adjustment synchronously, and update its current state; S5, according to the pre-constructed multi-dimensional energy efficiency and comfort comprehensive evaluation system, monitor the energy consumption and comfort data after adjustment, calculate the comprehensive energy efficiency index, and feed back the calculation rule of the spectral weight factor to complete the adaptive adjustment closed loop.

2. The method of claim 1, wherein, The intelligent building system collects indoor and outdoor light data through light sensors, and calculates the light deviation value from the preset comfortable range, including the following sub-steps: At the same time, collect the light intensity data of different functional areas in the room and multiple directions outside the building; Compare the collected real-time light data with the preset comfortable light range in the system, and calculate the specific deviation of each region from the current light level and the comfortable range value or optimal value; Analyze the deviation of all regions, select the regions whose deviation exceeds the preset allowed threshold, and accurately mark them as the regions to be adjusted which need to be adjusted first.

3. The method of claim 1, wherein the method further comprises: According to the light deviation value and outdoor light data, calculate the spectral weight factor that balances the priority of shading and lighting adjustment, including the following sub-steps: According to the intensity, duration and trend of outdoor light, comprehensively judge the availability of current natural light and its potential contribution to indoor lighting; Combined with the specific numerical value and spatial distribution of indoor light deviation, calculate the weight distribution proportion between shading adjustment and electrical lighting adjustment at the current time; Generate a dynamically adjustable spectral weight factor according to the weight distribution proportion, which is directly used in the subsequent parallel calculation process of shading and lighting compensation value.

4. The method of claim 1, wherein, Use the spectral weight factor to calculate the shading angle compensation value and the lighting brightness compensation value in parallel, including the following sub-steps: According to the adjustment tendency indicated by the spectral weight factor, reasonably allocate the total adjustment amount ratio that can be used for shading adjustment and lighting adjustment; Independently calculate the angle offset amount of the shading blade needed to achieve the target shading effect, and the brightness compensation value of the lighting lamps needed to supplement the indoor light; Carry out validity check and range constraint on the angle compensation value and brightness compensation value obtained by preliminary calculation, to prevent adjustment overshoot, equipment overload or energy waste.

5. The method of claim 4, wherein, Independently calculate the angle offset amount of the shading blade needed to achieve the target shading effect, and the brightness compensation value of the lighting lamps needed to supplement the indoor light, including the following sub-steps: According to the current blade angle of the sunshade device, the outdoor sun azimuth and elevation angle information, the blade angle value required to be adjusted for blocking excessive glare or introducing appropriate natural light is calculated; According to the light deviation of each area in the room and the expected contribution of natural light after passing through the sunshade system, the brightness value that needs to be supplemented or reduced by the electrical lighting system is calculated; The sunshade angle adjustment amount and the lighting brightness adjustment amount are checked for coordination to ensure that the adjustment directions are consistent and will not conflict, avoiding excessive adjustment or mutual cancellation.

6. The method of claim 1, wherein, According to the sunshade angle compensation value and the lighting brightness compensation value, the sunshade device and the lighting lamp are synchronously driven to execute adjustment, and the current state is updated, including the following sub-steps: After the adjustment action is completed, the indoor light data of each area is immediately re-collected by the light sensor to verify whether the adjustment effect makes the light level enter the preset comfortable range; Accurately record the energy consumption data of the sunshade motor and the lighting lamp during this adjustment process, and calculate the energy efficiency ratio of this adjustment action; If it is found that the adjustment effect does not reach the expected target or the energy efficiency ratio is too low, the feedback mechanism is automatically triggered, the light spectrum weight factor is recalculated, and a new round of adjustment is started.

7. The method of claim 1, wherein, Monitor the energy consumption and comfort data after adjustment, calculate the comprehensive energy efficiency index, and feed back the calculation rules of the light spectrum weight factor according to the comprehensive energy efficiency index, complete the adaptive adjustment closed loop, including the following sub-steps: Based on the multiple adjustment records accumulated in the system historical operation and their corresponding energy consumption results and comfort degree reaching conditions, a multi-dimensional energy efficiency-comfort comprehensive evaluation system is established; According to the latest comprehensive evaluation results, the key parameters involved in the calculation process of the light spectrum weight factor and their calculation logic are adjusted reversely; Through continuous iteration optimization and experience learning, the system can gradually adapt to the light change characteristics brought by different dates, different time periods of each day and different seasons.

8. A smart building lighting and shading linkage adaptive adjustment system, characterized in that, It includes: Data perception module: collect indoor and outdoor light data through light sensors and calculate light deviation value from the preset comfortable range; Intelligent decision-making module: analyze the intensity, duration and trend of outdoor light, evaluate the availability and contribution potential of natural light to indoor lighting, and then consider the numerical value and distribution characteristics of indoor light deviation, calculate the light spectrum weight factor to balance the adjustment priority of sunshade and lighting; According to the adjustment tendency indicated by the light spectrum weight factor, the sunshade angle compensation value and the lighting brightness compensation value are calculated in parallel, and the preliminary calculation results are verified for effectiveness and range constraints; The following formula is used to express the weight proportion that each of the shading adjustment and the electrical lighting adjustment behavior should occupy: wherein, and is a spectral weight factor, represents a time instant for which the weight proportion of the shading control is prioritized; represents the time point; represents an adjustment parameter for controlling the sensitivity to ; represents a variable related to solar radiation; represents a variable related to thermal environment; represents a variable related to natural lighting potential; represents the lighting adjustment weight; Execution control module: according to the sunshade angle compensation value and the lighting brightness compensation value, the sunshade device and the lighting lamp are synchronously driven to execute adjustment, and the current state is updated; Feedback optimization module: according to the pre-established multi-dimensional energy efficiency and comfort comprehensive evaluation system, monitor the energy consumption and comfort data after adjustment, calculate the comprehensive energy efficiency index, and feed back the calculation rules of the light spectrum weight factor to complete the adaptive adjustment closed loop.

9. A computer storage medium, characterized in that It includes: At least one memory and at least one processor; Memory for storing one or more program instructions; A processor for running one or more program instructions to perform the method of adaptive adjustment of intelligent building lighting and shading linkage according to any one of claims 1-7.

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