Active sharing type lighting method and system

Abstract

The application discloses a kind of active sharing type lighting method and system, its lighting method includes: current heliostat unit obtains the geographic position information of itself, and searches whether there is adjacent heliostat unit online;If there is adjacent machine online, current heliostat unit and adjacent heliostat unit enter multi-machine cooperation mode according to space adaptation agreement, and establish the relative spatial coordinates of itself;By establishing point-to-point connection subgroup, and by background server integration forms more than one simulated optimization sharing path, after two stages of sequencing and light energy test, select the optimization sharing path in numerous possible light paths, and carry out light source guiding action, complete lighting.The technical scheme provided by the application, through automatic mutual recognition between heliostat, automatically establish spatial coordinates, intelligently determine the optimization sharing path of light path, facilitate the unlimited cascade expansion of light transmission.

Description

Technical Field

[0001] This invention relates to the field of building lighting technology, and in particular to an active sharing lighting method and system. Background Technology

[0002] With the increasing urban population, the proliferation of high-rise buildings is impacting the natural lighting in many buildings. Currently, the introduction of natural lighting into buildings has become a rapidly developing industry.

[0003] In natural lighting technology, passive natural lighting methods have been more commonly used in the past. This involves using fixed-location light-receiving openings, such as skylights, bay windows, reflectors, and light-collecting planes, to bring outdoor light into the interior space through light reflection / transmission between these openings. Passive lighting methods are inevitably limited by factors such as the location, orientation, and size of the light-receiving openings, making it difficult to meet the needs of different apartment layouts and thus limiting their effectiveness.

[0004] In recent years, active natural lighting has emerged, introducing sunlight tracking technology on the basis of passive lighting. For example, the active lighting system disclosed in publication number CN108729691B coordinates multiple heliostats and automatically selects the appropriate position of the heliostat based on the window position and real-time solar angle. It can provide lighting to a window for a certain period of time, which is a significant improvement over passive lighting in terms of the efficiency of utilizing natural light.

[0005] However, the implementation scheme of CN108729691B requires the installation of a large number of heliostats around the building to meet the demand for multi-angle sunlight throughout the day. Correspondingly, more installation space and locations are needed to achieve sufficient light coverage. Furthermore, the installation of heliostats requires professional engineers to measure the geographical coordinates in advance and perform repeated adjustments, requiring significant investment of resources and engineering work. Therefore, when the number and density of users increase exponentially, the problem becomes that installation and commissioning costs are directly proportional to the increase in the number and density of users. This means that establishing secondary, tertiary, or more cascaded lighting channels from the main lighting channel becomes complex and difficult, especially when dealing with more intricate, densely packed building clusters.

[0006] Furthermore, patent TWI655390B employs a primary and secondary light guiding method to collect and converge solar light sources; CN1447058A also describes a similar solar light guiding technology, but it does not address the more complex automated control process; CN103605376A describes the use of reflectors between building walls for collaborative beam guiding and the loading of sensors to guide the beam, using wireless and other methods for device information control, but users still need to perform complex professional engineering setups, and it still cannot be widely adopted in the fields of actual architectural and interior design.

[0007] Furthermore, CN106482077A mentions first-level and second-level optical path reflection schemes, along with lateral / vertical rotation axes, to assist in the transmission of light beams between building structures and complete the lighting process.

[0008] While many of the active daylighting designs discussed previously are highly complex, they fail to envision how to purposefully utilize automated control systems and mobile, scalable, modular multi-space, multi-zone, and multi-unit expansion methods to achieve daylighting for communities and small households, while minimizing the costs of building structural modifications. They also lack a clear framework for hardware and software engineering solutions that allow small households to install the systems themselves, and how to maximize the use of light energy in a community or specific area through interconnected sharing. Furthermore, with a large number of daylighting users, the simulation of optical paths becomes extremely complex, and previous passive daylighting solutions have not addressed collaborative approaches for multi-unit equipment. Summary of the Invention

[0009] To overcome the shortcomings of existing technologies, this invention proposes an active sharing light-gathering method and system, which features both automation and intelligence. The heliostat units automatically recognize each other and automatically establish their relative spatial coordinates. The background intelligent system intelligently selects the optimal sharing path (Path of optimal redistribution, POR) for the user and facilitates the infinite cascading expansion of light transmission.

[0010] An active sharing-based daylighting method is applied to a backend server and heliostat units installed on different buildings, and includes:

[0011] S1: When the current heliostat unit is powered on, search for whether there are any adjacent heliostat units online within its preset distance range;

[0012] S2: If an online adjacent heliostat unit is found, the current heliostat unit and the found adjacent heliostat unit enter a multi-machine cooperation mode according to a preset spatial adaptation protocol, and establish their relative spatial coordinates.

[0013] S3: Based on the values ​​obtained by the machine vision module and light energy detection module on each heliostat unit, establish a point-to-point connection subgroup corresponding to the light source requirement point; the point-to-point connection subgroup includes multiple heliostat units;

[0014] S4: Integrate the various point-to-point connection subgroups to construct one or more simulated optimized sharing paths from sunlight to the light source demand point; and establish a simulated test sequence for the one or more simulated optimized sharing paths based on the total optical path distance of the beam propagation between heliostat units in each simulated optimized sharing path, the number of heliostat units through which sunlight passes to the light source demand point, and the light energy value obtained by each heliostat unit.

[0015] S5: In the simulated test sequence, the application order of the simulated optimized sharing path is selected based on the light energy value received by each heliostat unit and the ratio of the light energy value of the final optical path node to the initial optical path node in each simulated optimized sharing path.

[0016] S6: Based on the application sequence of the optimized sharing path, notify the corresponding heliostat unit on the optimized sharing path to perform light source guidance action and complete the light collection.

[0017] An active sharing daylighting system for performing the active sharing daylighting method as described above; and comprising:

[0018] A heliostat unit is mounted on various buildings and includes a fixed support. A dual-axis robotic arm is mounted on the fixed support. A mirror is fixed on the dual-axis robotic arm. Photovoltaic panels are mounted on both sides of the mirror. The heliostat unit also includes a main control board, which integrates a wireless communication module and a power supply module connected to the photovoltaic panels. The heliostat unit is also equipped with an infrared flash signal module and / or a camera, as well as an infrared ranging module.

[0019] The background intelligent system is used to communicate with the heliostat unit wirelessly.

[0020] This invention provides an active sharing-based light-gathering method and system that enables multiple heliostat units at different locations to achieve self-position recognition and establish relative spatial coordinates based on a spatial adaptation protocol. On this basis, a direct peer-to-peer pairing group (DPG) is established as the smallest first-level unit (corresponding to S3). Further integration of multiple DPGs forms multiple optimized sharing paths (PORs) between sunlight and light source demand points based on heliostat unit combinations. To select the optimal path from the PORs, a two-stage sorting process (corresponding to S4 and S5 respectively) is used to obtain the final application order of the optimized sharing path, thereby achieving light source guidance.

[0021] This invention enables automatic mutual recognition and spatial coordinate establishment among heliostat units, and intelligent optimization and sharing of optical paths, facilitating the infinite cascading expansion of light transmission. The backend server intelligently calculates the light energy efficiency of each path and incorporates user weights to determine the path combinations between heliostat units. Furthermore, by adjusting spatial coordinates, measuring energy transfer data, and adaptively performing machine learning, an optimal light guidance control scheme is derived.

[0022] The advantages of this invention are: 1) Low installation cost on the user side; the heliostat unit does not require professional engineers to install, and users can install it themselves, reducing installation costs and facilitating its widespread application; 2) Minimal changes to the environment or buildings; the heliostat unit is simple to set up and can flexibly adapt to complex building clusters; 3) High flexibility in light sharing; each user can flexibly choose whether to include their heliostat unit in the cascaded network for light sharing according to their own needs, thereby overcoming the problem of inconvenience in adjusting the system after deployment.

[0023] Compared with existing technologies, this invention focuses on enabling each heliostat unit to cooperate with each other to form a cascaded network, automatically and autonomously participate in daylight sharing, and guide the daylight to more users, especially to the shadows behind buildings, or the winding shadows of building clusters, or even to continue to distribute and conduct solar beams within complex indoor spatial structures, thereby improving the effective utilization rate of daylight. Attached Figure Description

[0024] Figure 1 This is a schematic diagram illustrating an application scenario of the active sharing lighting system in an embodiment of the present invention;

[0025] Figure 2 This is a flowchart of the main active sharing lighting method in the embodiments of the present invention;

[0026] Figure 3 This is a flowchart illustrating the workflow of the heliostat unit and the back-end intelligent system in an embodiment of the present invention.

[0027] Figure 4 This is a schematic diagram of the spatial adaptation of the heliostat unit in an embodiment of the present invention;

[0028] Figure 5 This is another schematic diagram of the spatial adaptation of the heliostat unit in an embodiment of the present invention;

[0029] Figure 6 This is a schematic diagram of a DPG in an embodiment of the present invention;

[0030] Figure 7 This is another schematic diagram of DPG in an embodiment of the present invention;

[0031] Figure 8 This is a schematic diagram of fully simulated PORs in an embodiment of the present invention;

[0032] Figure 9 This is another schematic diagram of fully simulated PORs in an embodiment of the present invention;

[0033] Figure 10 This is a schematic diagram of the light-sensing recognition of the heliostat unit in an embodiment of the present invention;

[0034] Figure 11 This is a schematic diagram of a heliostat unit correcting its tilt angle based on light sensitivity in an embodiment of the present invention;

[0035] Figure 12 This is a schematic diagram of the heliostat unit in an embodiment of the present invention;

[0036] Figure 13 This is a schematic diagram of the optimized sharing path for multiple optical paths in an embodiment of the present invention;

[0037] Figure 14 This is another schematic diagram of the multi-optical path optimization and sharing path in an embodiment of the present invention;

[0038] Figure 15 This is another schematic diagram of the multi-optical path optimization and sharing path in an embodiment of the present invention;

[0039] Figure 16 This is another schematic diagram of the multi-optical path optimization and sharing path in an embodiment of the present invention;

[0040] The markings in the accompanying drawings are as follows:

[0041] 1. Heliostat unit; 2. Adjacent unit; 21. Infrared flash signal generation module; 3. Main unit; 31. Infrared ranging module; 32. Infrared CCD sensor camera; 33. Image acquisition camera; 34. Light sensor; 101. Fixing bracket; 102. Dual-axis robotic arm; 103. Mirror; 104. Photovoltaic panel. Detailed Implementation

[0042] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0043] This paper provides an active sharing-based lighting method, whose application scenarios include... Figure 1 As shown, the heliostat units form a cascade redirection relationship. Each heliostat unit has three operating modes: Heliostat mode, Relay mode, and Terminal mode. In Heliostat mode, the solar unit (SU) directly receives sunlight, meaning that during a certain period, this unit is responsible for collecting sunlight at the first station in the cascade path, operating like a traditional automatic heliostat. In Relay mode, the solar unit (RU) receives beams from other solar units, typically in dark areas of buildings where sunlight cannot directly reach during a certain period. In Terminal mode, the solar unit (TU) directly guides the light path to the point where the light source is needed, handling the final reflection path and directing the beam into the window. Under specific circumstances, a solar unit can operate in both Heliostat mode and Terminal mode simultaneously.

[0044] Figure 1 In this system, there are 28 heliostat units; P2 has a shorter total path and an N value (the number of heliostat units traversed between sunlight and the light source demand point) of 3; P5 has a longer total path and an N value of 5; the system prioritizes the P2 path.

[0045] The main flowchart of this active sharing lighting method is as follows: Figure 2 , 3 As shown; this method is applied to a backend server and heliostat units located on different buildings, and includes the following steps:

[0046] S1: When the current heliostat unit is powered on, search for whether there are any adjacent heliostat units online within its preset distance range.

[0047] A heliostat unit is a device with a reflective surface that can be mounted on a building. The heliostat unit has wireless communication capabilities, including but not limited to various electromagnetic wave bands, Bluetooth, WiFi, and 4G / 5G modules. The preset distance range can be flexibly determined based on the hardware modules (electromagnetic wave, Bluetooth, WiFi, 4G / 5G, etc.) configured on the heliostat unit.

[0048] Specifically, after powering on, the heliostat unit obtains its geographical location information, such as GPS coordinates, through its wireless communication module or GPS passive signal receiver. It then loads a map or location information of other nearby heliostat units from its local or remote server to determine if adjacent heliostat units exist. Understandably, if other users do not wish to share their heliostat units, they can choose to go offline. In this case, the currently active heliostat unit cannot find the offline heliostat unit.

[0049] S2: If an online neighboring heliostat unit is found, the current heliostat unit and the found neighboring heliostat unit enter a multi-machine collaboration mode according to a preset spatial adaptation protocol and establish their relative spatial coordinates.

[0050] Multi-machine collaboration mode refers to the state in which multiple heliostat units cooperate with each other, including but not limited to automatically identifying each other's geographical location and readiness status.

[0051] Specifically, if adjacent heliostat units are online (which also means that the user is willing to participate in sharing the light), they will calculate their respective relative three-dimensional spatial coordinates, such as (x, y, z), according to the rules of the preset spatial adaptation protocol.

[0052] The preset spatial coordinate adaptation protocol is described in [reference needed]. Figure 4 This includes: the first heliostat unit transmitting an infrared flash signal; and the adjacent heliostat unit, upon detecting the infrared flash signal, calculating its relative spatial coordinates with the first heliostat unit. Specifically, when a neighboring unit is powered on and wishes to share the light, it emits an infrared flash signal via its infrared flash module; upon detecting the infrared flash signal, the unit can calculate the distance between the two units and determine their azimuth angle using its infrared CCD sensor camera and infrared ranging module.

[0053] Further, see Figure 5The preset spatial adaptation protocol also includes: the second heliostat unit acquires image information from surrounding heliostat units, including other heliostat units, and parses the image information using preset image processing methods, such as azimuth angle measurement, to obtain the relative spatial coordinates between the second heliostat unit and other heliostat units. That is, neither the local unit nor neighboring units need to install infrared flash modules; the local unit acquires images from neighboring units via a camera and calculates distances using its own infrared ranging module.

[0054] For example, the effective distance between heliostat units is between 0.3 meters and 20 meters, which can meet the lighting needs of densely populated communities.

[0055] S3: Based on the values ​​obtained by the machine vision module and light energy detection module on each heliostat unit, establish a point-to-point connection subgroup corresponding to the light source demand point; the point-to-point connection subgroup (DPG) includes multiple heliostat units, which constitute the smallest unit combination for calculating PORs; the background intelligent system further integrates multiple DPGs to form more than one simulation optimization sharing path.

[0056] The machine vision module includes, but is not limited to, high-definition cameras, infrared light detection modules, and supporting graphics and image processing software. The light energy detection module includes, but is not limited to, photosensors and other hardware capable of quantifying light intensity and corresponding processing software. Let the light energy value be expressed as E, then the light energy values ​​acquired by SU, TU, and RU are ESU (Light energy of solar unit), ETU (Light energy of terminal unit), and ERU (Light energy of relay unit), respectively.

[0057] Point-to-point connected subgroups, or DPGs, are groups of adjacent machines that can be directly paired point-to-point. They are the smallest unit combinations that can be used directly as linear optical guides and are the smallest unit combinations for calculating POR.

[0058] For example, such as Figure 6 As shown, the DPG of U6 is (U1, U2, U3, U4, U5, U7, U8, U9, U11); the DPG of U10 is (U1, U2, U3, U4, U5, U7, U8, U9, U11).

[0059] Because of obstacles, the machine vision system cannot scan neighboring units on the GPS or relative coordinates, or the distance value (total D value) is too far, the system determines that U6 and U10 are not directly compatible pairing machines. The characteristics of the DPG group are imported into the simulation calculation module of PORs. Therefore, DPG means that each unit (U) forms its own directly compatible pairing machine group. Figure 7 As shown, the difference in energy transmission (stable / unstable / strong / weak) of red light or sunlight is used to determine whether U10 and U6 can be directly connected and paired.

[0060] S4: Integrate the various point-to-point connection subgroups to construct one or more simulated optimized sharing paths from sunlight to the light source demand point; and establish a simulated test sequence for the one or more simulated optimized sharing paths based on the total optical path distance of the beam propagation between heliostat units in each simulated optimized sharing path, the number of heliostat units through which sunlight passes to the light source demand point, and the light energy value obtained by each heliostat unit.

[0061] The distance between each heliostat unit and its directly adjacent heliostat units is denoted as D. In a certain POR, the total optical path distance is the sum of the D values ​​of each segment between units. The number of heliostat units that sunlight must pass through to reach the light source is denoted as N, that is, N cascades must be passed through during the light transmission process. The solar energy value obtained by each heliostat unit directly facing the sun is denoted as ESU.

[0062] Specifically, a simulated light energy efficiency sequence (PSES) based on PORs is calculated, which is to establish a simulated test sequence: the priority test order of path P is established according to the weighted allocation results of the total D value, N value and ESU value of POR; and the total D value, N value and ESU value are sorted according to the following priority order: for PORs that exist at the same time, the priority order of PORs is sorted according to the total D value > N value > ESU value.

[0063] Among them, the smaller the total D value, the shorter the energy transmission path and the less light energy is lost, and the higher the ranking; conversely, the higher the total D value, the lower the ranking. The smaller the N value, the less light energy is lost during transmission on the mirror, and the higher the ranking; conversely, the higher the N value, the lower the ranking. The larger the ESU value, the better, indicating more sufficient light energy collection at the front end; conversely, the lower the ESU value, the lower the ranking.

[0064] For example, such as Figure 8 As shown, after DPG combination and elimination, the system lists all optical paths, i.e., fully simulated PORs; as... Figure 9 As shown, this is the apparent trajectory path of the sun during the T-time period, loaded with the year, month, day, hour, and minute. It simulates the positional orbits (PORs) of the sun during all T-time periods, with each T-time period having its own fully simulated PORs.

[0065] S5: In the simulated test sequence, based on the light energy value received by each heliostat unit and the ratio of the light energy value of the final optical path node to the initial optical path node in the optimized sharing path, the application sequence of the optimized sharing path is selected, which is called the PORs application sequence (PAS).

[0066] The overall idea behind S4 and S5 is as follows: Since a user forms an independent PORs simulation path within a time period T, the computational and memory requirements on the system are considerable. If the number of users and machines is large, the PORs mode paths will become more complex and numerous, requiring the system to conduct energy testing strategically; moreover, it is necessary to coordinate the time of each user to form the final PORs priority sequence.

[0067] Therefore, based on the sorting results of the total D value, N value and ESU value, the priority test order of PORs (i.e. the aforementioned PSES) is established, and then the PORs with the best actual light energy efficiency are screened and sorted according to the light energy value received by each heliostat unit and the ratio of the light energy values ​​at the start and end points in the path.

[0068] Specifically, after PSES in step S4, the conduction efficiency is calculated using the actual tested terminal unit (TU) light energy value ETU and the corresponding ESU at the same time. The ETU / ESU ratio is used as the main evaluation rating weight to establish the user's priority ranking for PORs. That is, the final PORs priority sequence is selected and ranked according to the measured light energy utilization efficiency, which is the PORs application sequence (PAS).

[0069] Furthermore, step S5 can be achieved through the following steps:

[0070] S51: Calculate the average light energy value of each heliostat unit based on the light energy value measured at the same azimuth angle towards the sun during time period T; and select the optimized sharing path that reaches the average light energy value from the simulated test sequence.

[0071] Specifically, if the light received by the heliostat unit is denoted as E, then the average light energy received by all or some units at the same azimuth angle is E. ave =(E1+E2+E3…..+E n ) / n; Confirm whether the energy received by each node of the POR path to be detected reaches E aveThis allows us to filter and obtain POR paths that meet the specified conditions.

[0072] S52: Calculate the ratio of the light energy of the final optical path node (ETU) to the initial optical path node (ESU) in the optimized sharing path.

[0073] In theory, ideally, the POR is ranked based on the energy value of the final optical path node TU0, i.e., the actual measured ETU (light energy value of the final optical path node). The higher the ETU value, the higher the POR's ranking. However, throughout the day, the intensity of sunlight during the test can be affected by various objects or media such as clouds, birds, and animals in the air. Therefore, the system incorporates ESU (light energy value of the initial optical path node) into the determination of the validity of the values.

[0074] Specifically, the actual energy efficiency of the POR is calculated, i.e., the ETU / ESU value is measured. The system first determines whether it is a "many-to-one" or "one-to-one" conduction; if it is many-to-one, each path is tested individually, i.e., the terminal node TU0 is independently measured to correspond to each individual SU, expressed as TU0 / ESU1, TU0 / ESU2, TU0 / ESU3… TU0 / ESU n .

[0075] S53: Reorder the simulated optimized sharing paths according to the ratio of light energy values ​​to obtain the application order (PAS) of the optimized sharing paths.

[0076] Specifically, POR is sorted by ETU / ESU value. The higher the ETU / ESU value, the higher the ranking.

[0077] Furthermore, when selecting the final application sequence (PAS), machine learning methods or a database of solar trajectories and meteorological data can be combined to determine the reasons for the instability of a certain machine's energy.

[0078] Considering the possibility of temporary obstructions from birds, animals, plants, or various temporary activities, this step can correspond to an obstacle self-check module. Within a recurring time period T each day, the system uses machine learning to build a database of PORs (Probability of Occurrence) for each time period over many years. This long-term data establishes a baseline of normal parameters to determine the cause of energy instability at a particular machine. Alternatively, during a specific time period T, solar apparent trajectory data and weather forecast data are downloaded to the network, and energy comparisons across multiple machines are used to determine the cause of energy instability at a particular machine.

[0079] In some cases, during the T-period, numerous users may need to create ETU and PAS profiles. As the number of machines and users increases, a single user may generate thousands of simulated RORs within a single period. If there are thousands of households, the system must handle millions of RORs for testing during the T-period. Moreover, stable sunlight is not available for testing every day, which is impractical. It may take several years to complete the testing, as there are only 365 T-periods per year. Especially since the T-period is in 10-minute increments, the testing time is clearly insufficient.

[0080] Therefore, the Multi-User Test Coordinator (MUTC) module performs streamlined testing on a user's PSES (Personal Skills Evaluation) over a specific time period based on the number of users. Generally, the larger the number of users, the more streamlined the testing should be for any single user. Specifically, if the user base is greater than a certain N... max The system automatically splits the system into two or more regional communities for testing. The following tests will begin with regional communities: Within the launched regional communities, time T... a -T b It contains N s A number of users went online, and each user had N... POR A simulated path in T a -T b Within the specified time period, only the S-field test frequency can actually be conducted. Each user's PSES has N. POR Several simulated paths, ultimately reaching T a -T b The number of PORs tested within the time period is N. POR / Ns, each measurement is performed according to the PSES sorting.

[0081] The above description further elaborates on how intelligent machine learning and periodic testing procedures can be used to avoid excessive testing, which could negatively impact user experience. (Path P) x Testing can be conducted 2-3 times per week, with data collection completed gradually. Through intelligent allocation of testing time, for example, when a user is at work or not at home, a test window is provided on the app or a specific terminal. The system prioritizes using the user's associated machines for solar energy testing to increase the testing efficiency of cascaded networks in a given area. For a specific user, the system simulates all PORs for a specific time period T (in 10-minute increments) within all solar sunshine periods for all years / months / days / hours / minutes.

[0082] S6: According to PAS, notify the corresponding heliostat unit on the optimized sharing path P to perform light source guidance actions to complete the light collection.

[0083] Based on the application sequence of the finally determined optimized sharing path, a cascading guiding relationship is formed between each heliostat unit. That is, the identity or role of each heliostat unit on the daylighting transmission path is determined.

[0084] Based on the cascading guiding relationship, each heliostat unit can flexibly switch the analysis mode according to its own needs and factors such as the time or position of sunlight irradiation, thus forming various possible optical path transmission paths.

[0085] Furthermore, each heliostat unit on the optimized sharing path adjusts its tilt angle according to the received light beam until the light sensitivities of several light sensors on the mirror are closest to being balanced, which can also be used as a means of adjusting the spatial orientation.

[0086] Specifically, see Figure 11 , during the collaborative operation of each heliostat unit, the tilt angle of its respective mirror is related to the accuracy of the optical path transmission. Therefore, the azimuth angle needs to be adjusted based on the numerical values of the light sensitivity test. A four-corner calibration module (i.e., equipped with four light sensors) is set on the mirror surface of each heliostat unit to detect the light brightness (light energy).

[0087] For example, the light beam transmitted from the adjacent machine only shines on 1 light sensor, or the light beams sensed by the 4 light sensors are uneven, such as Sa = Sb = Sc << Sd. At this time, the local system makes a judgment and issues a correction instruction; the tilt angle of the mirror is corrected by calling the robotic arm until the energies of the sensors at the 4 corners are as uniform as possible, that is, Sa = Sb = Sc = Sd. It can be understood that not only can the local machine adjust according to the light beam of the adjacent machine, but the adjacent machine can also adjust according to the light beam of the upper-level adjacent machine, so as to achieve the active adaptive adjustment of each heliostat unit to achieve the optimized transmission effect. In addition, in addition to calculating the energy uniformity on the mirror surface and guiding the beam alignment between two mirrors, the invocation of the 4-corner light sensors, that is, even during the light beam conduction process, the test and calibration means for correcting the azimuth angle of the mechanical axis rotation, not only rely on Figure 4 or Figure 5 the way to establish the relative space coordinates between heliostat units, and more specifically, refer to Figure 11After calculating the azimuth coordinates using infrared light detection and machine vision positioning, under daytime conditions or specific scenarios (such as the introduction of light sources for engineering calibration and testing), the system will further activate the four-corner azimuth adjustment as a subsystem to help reduce the angle error of light transmission and increase light guiding efficiency. This subsystem, which adjusts the virtual space coordinates and the azimuth angle between mirrors, can be used several times a day or once every few days. It is controlled under the permission system architecture of the cascaded network protocol between users. The more heliostat units that participate, the more the accuracy of light guidance can be gradually increased by the adjustment frequency of this subsystem in the cascaded network within the same geographical block of shared light source.

[0088] exist Figure 2 In addition to the main process shown, this active sharing lighting method also includes the following steps:

[0089] S21: If the current heliostat unit does not receive a signal from an adjacent heliostat unit online, it determines whether the current heliostat unit meets the placement conditions. If it does not meet the placement conditions, it prompts the user to reselect the placement position of the current heliostat unit. If it meets the placement conditions, the current heliostat unit enters the stand-alone operation mode.

[0090] The placement conditions include: the heliostat unit's acquired mirror light energy value is lower than a first preset value when searching all day; and the heliostat unit's optimized sharing path score rating is lower than a second preset value.

[0091] Based on S21, the heliostat unit's workflow is more refined, including its environmental sensing module.

[0092] It can not only work in conjunction with other units, but also guide the light source independently, and perform self-checks to ensure that the placement conditions are met and correct the placement position of the unit as much as possible; thus making the function of the heliostat unit more complete.

[0093] An active sharing lighting system is provided for executing the active sharing lighting method. The lighting system includes:

[0094] Heliostat unit, see Figure 12The heliostat unit is mounted on various buildings and includes a fixed support frame with a dual-axis robotic arm mounted on it. A mirror is fixed to the robotic arm. Photovoltaic panels are installed on both sides of the mirror. The mirror can rotate within a near-spherical range of motion. The vertical axis robotic arm can rotate freely in 5˚~355˚ in the horizontal plane, while the horizontal axis robotic arm can rotate 360˚, allowing the heliostat unit to adapt to beam reflection at various azimuth angles. The fixed support frame also houses a main control board, which integrates a wireless communication module and a power supply module connected to the photovoltaic panels. The heliostat unit is also equipped with an infrared flash signal module and / or a camera.

[0095] Furthermore, multiple light sensors are evenly arranged within the mirror surface; preferably, the wireless communication module includes a Bluetooth or WiFi module, and the number of light sensors is four.

[0096] In addition, the heliostat unit integrates or is a cloud-based central server with modules such as DPG, PSES, PAS, PORs scoring and detection, obstacle self-checking, and user test coordination.

[0097] The DPG, PSES, and PAS modules correspond to steps S3, S4, and S5, respectively; the PORs scoring and detection module is a sub-module of the PSES and PAS modules; in the PORs scoring and detection module, the system performs actual energy detection and determines the PORs priority order. For example, in a certain T n Over a specific time period, energy is measured directly using sunlight, and the light energy value is expressed as E, where a certain T represents the energy measured directly over that period. n P n For example, the final TU is labeled as TU0. The measured ETU is higher; the larger the ETU value, the better. n The higher the priority of the test database, the more complete the test database will be.

[0098] The fault self-check module is used to determine the cause of whether the energy of a certain machine is stable or not.

[0099] The user test coordination module is used to resolve conflicts in user test responses (PORs).

[0100] The back-end intelligent system refers to the back-end server system that communicates with each heliostat unit wirelessly, including but not limited to various cloud computing centers, servers, and server clusters. After determining multiple possible optical path transmission paths in step S3, the back-end intelligent system calculates the optimized sharing path (i.e., the previously described PORs) between sunlight and the light source demand point through the heliostat units.

[0101] Based on this active sharing lighting method and system, its application is illustrated as follows: Figure 10 ,14 As shown in Figure 16.

[0102] exist Figure 13 In the diagram, the heliostat units labeled U1, U2, U3…U are connected online. 11 Higher-privilege user A can obtain longer hours of sunshine, or more multiple Proof-of-Origin (POO) sets (more than one set). Further, refer to... Figure 15 In a certain building complex area, for a certain date and time period T, the system performs multiple optical path simulations, with the time period T in 10-minute increments, to calculate the POR of P1, P2, and P3. TU is the unique terminal node of the optical path.

[0103] exist Figure 14 In the middle, users with lower priority permissions are intelligently assigned to a single optical path.

[0104] exist Figure 15 In the process, the nodes after the calculation are loaded: there exist heliostat elements U1, U2, U3…U 11 The sun's position changes during a certain time period T' on a certain date: the system loads the simulated multiple optical paths for time T'. For example, the Probability of Orientation (POO) for user A is calculated for T'P1, T'P2, T'P3, and T'P4. At this time, the TU, RU, and SU identities of the various units in the original time period T will undergo a new task identity switch.

[0105] exist Figure 16 In the second case of TU: it can act as both RU and TU (e.g., TU1 and TU2, or only TU0 can act as TU). For example: when user A goes on vacation, they share the PORs group with user B. The system then establishes a new allocation model, generating a new PORs group PORs', in which light is introduced to user B through TU0 and TU1.

[0106] The above is a description of the active sharing lighting method and system of the present invention, which is used to help understand the present invention; however, the implementation of the present invention is not limited to the above embodiments. Any changes, modifications, substitutions, combinations, or simplifications made without departing from the principle of the present invention shall be considered equivalent substitutions and are included within the protection scope of the present invention.

Claims

1. An active sharing-type light-gathering method, characterized in that, It is applied to backend servers and heliostat units installed on different buildings, and includes: S1: When the current heliostat unit is powered on, search for whether there are any adjacent heliostat units online within its preset distance range; S2: If an online adjacent heliostat unit is found, the current heliostat unit and the found adjacent heliostat unit enter a multi-machine cooperation mode according to a preset spatial adaptation protocol and establish their relative spatial coordinates. S3: Based on the values ​​obtained by the machine vision module and light energy detection module on each heliostat unit, establish a point-to-point connection subgroup corresponding to the light source requirement point; the point-to-point connection subgroup includes multiple heliostat units; S4: Integrate the various point-to-point connection subgroups to construct one or more simulated optimized sharing paths from sunlight to the light source demand point; and establish a simulated test sequence for the one or more simulated optimized sharing paths based on the total optical path distance of the beam propagation between heliostat units in each simulated optimized sharing path, the number of heliostat units through which sunlight passes to the light source demand point, and the light energy value obtained by each heliostat unit. S5: In the simulated test sequence, the application order of the simulated optimized sharing path is selected based on the light energy value received by each heliostat unit and the ratio of the light energy value of the final optical path node to the initial optical path node in each simulated optimized sharing path. S6: Based on the application sequence of the optimized sharing path, notify the corresponding heliostat unit on the optimized sharing path to perform light source guidance action and complete the light collection.

2. The active sharing lighting method as described in claim 1, characterized in that, The preset space adaptation protocol includes: The first heliostat unit sends out an infrared flash signal; After detecting the infrared flash signal, the heliostat unit adjacent to the first heliostat unit obtains the distance and spatial azimuth angle between itself and the first heliostat unit through infrared ranging, and calculates the relative spatial coordinates between the two.

3. The active sharing lighting method as described in claim 1, characterized in that, The preset space adaptation protocol also includes: The second heliostat unit acquires image information of the surrounding area, including other heliostat units. After parsing the image information through a preset image processing method, it calculates the relative spatial coordinates between itself and other heliostat units by combining the distance and spatial azimuth angle between itself and other heliostat units obtained by infrared ranging.

4. The active sharing lighting method as described in claim 1, characterized in that, The S5 also includes: An optimized sharing path database based on the simulated test sequence is established within a preset time using machine learning; wherein, the optimized sharing path database serves as a parameter baseline to determine the reasons for whether the light energy value of any heliostat unit is stable. Alternatively, solar trajectory data and meteorological data can be acquired within a preset time period. The solar trajectory data and meteorological data are used in conjunction with the light energy value of the heliostat unit to determine whether the light energy value of the current heliostat unit is stable.

5. The active sharing lighting method as described in claim 1, characterized in that, In step S4, when establishing the simulation test sequence of the optimized sharing path of the heliostat unit traversed by sunlight to the light source demand point, the paths are sorted according to the following priority order: The total distance between each heliostat unit and its directly adjacent heliostat units, the number of heliostat units that sunlight must pass through to reach the light source demand point, and the light energy value acquired by each heliostat unit.

6. The active sharing lighting method as described in claim 1, characterized in that, The S5 includes: S51: The backend server determines the average light energy value based on the light energy value received by each heliostat unit; and selects the simulated optimized sharing path that reaches the average light energy value from the simulated test sequence; S52: The background server calculates the ratio of the light energy value of the final optical path node to the initial optical path node in the simulated and optimized sharing path; S53: The backend server reorders the simulated optimized sharing paths according to the magnitude of the light energy value ratio to obtain the application order of the simulated optimized sharing paths.

7. The active sharing lighting method as described in claim 6, characterized in that, The active sharing lighting method further includes: S21: If no adjacent heliostat unit is found online, the current heliostat unit determines whether it meets the placement conditions. If it does not meet the placement conditions, the user is prompted to reselect the placement position of the current heliostat unit. If it meets the placement conditions, the current heliostat unit enters the stand-alone operation mode. The placement conditions include: the light energy value acquired by the heliostat unit within a preset time period is lower than a first preset value; or, the light energy value of the heliostat unit is lower than the average light energy value.

8. The active sharing lighting method as described in claim 1, characterized in that, In step S6, after notifying the corresponding heliostat unit on the optimized sharing path to perform a light source guidance action, the method further includes: Each heliostat unit on the optimized sharing path adjusts its tilt angle according to the received light beam until the light sensitivity is equalized.

9. An active sharing lighting system, characterized in that, Used to perform the active sharing light-gathering method as described in any one of claims 1 to 8; And includes: A heliostat unit is mounted on various buildings and includes a fixed support. A dual-axis robotic arm is mounted on the fixed support. A mirror is fixed on the dual-axis robotic arm. Photovoltaic panels are mounted on both sides of the mirror. The heliostat unit also includes a main control board, which integrates a wireless communication module and a power supply module connected to the photovoltaic panels. The heliostat unit is also equipped with an infrared flash signal module and / or a camera, as well as an infrared ranging module. The background intelligent system is used to communicate with the heliostat unit wirelessly.

10. The active sharing lighting system as described in claim 9, characterized in that, At least one photosensor is uniformly arranged within the mirror surface. The photosensor is used to calibrate the angular error of the reflected light beam and the error of the relative spatial coordinates.

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