Calculation center space-time-crossing green lighting system and calculation center space-time-crossing green lighting method

Abstract

The invention discloses a computing power center cross-space-time green lighting system and method, and relates to the technical field of lighting control, and the system can greatly reduce the lighting energy consumption and effectively reduce the operation cost of a computing power center through the maximum capture and efficient utilization of natural light and the combination of the intelligent supplementation and scheduling of green power. By synergistically utilizing natural light and solar energy, the dependence on lighting mains supply is remarkably reduced, so that carbon emission is reduced, the requirements of green and low-carbon development are met, and carbon asset income can be created. On-demand illumination is realized through a space-time cooperation algorithm, electric power can be stored in advance based on load prediction, differential illumination regulation and control can be carried out according to demands of different areas and time periods, and meanwhile, the operation stability is remarkably improved through the redundancy design of the system; and emergency lighting and multiple backup guarantee mechanisms with rapid switching capability are arranged, so that the continuous operation of the lighting system is ensured, and the overall operation safety of the computing power center is improved.

Description

Technical Field

[0001] This invention relates to the field of lighting control technology, and in particular to a cross-temporal and spatial green lighting system and method for computing centers. Background Technology

[0002] With the booming development of the digital economy, computing centers, as key infrastructure supporting various digital applications, have seen continuous expansion in construction scale, leading to a sharp increase in their energy consumption. Energy consumption has become one of the core bottlenecks restricting the sustainable development of computing centers. Computing centers, due to their advantages such as constant temperature environments, have become a construction hotspot in the digital economy era. However, the lighting systems of traditional computing centers rely entirely on mains power, with lighting energy consumption accounting for approximately 3% of the total energy consumption. Given the large-scale construction and long-term operation of computing centers, this energy consumption is considerable and does not meet the low-carbon development requirements under the "dual-carbon" strategy.

[0003] In the field of green lighting technology, fiber optic light guiding technology and photovoltaic conversion technology have been gradually applied to some scenarios. However, in the application of computing centers, existing technologies have obvious limitations. Currently, in green lighting technologies for computing centers, fiber optic light guiding systems and photovoltaic systems mostly operate independently, failing to form an effective energy complementarity mechanism, resulting in low utilization efficiency of natural light and solar energy. At the same time, the lighting needs of different functional areas within the computing center (such as equipment areas and maintenance corridors) vary significantly, and the patterns of personnel activity and computing load are constantly changing. Existing technologies lack a mechanism for precise lighting adjustment based on these dynamic factors, failing to achieve a precise match between lighting supply and actual demand, thus causing energy waste.

[0004] Therefore, there is an urgent need for an integrated lighting system that combines fiber optic light guiding, photovoltaic conversion, and intelligent collaborative control to achieve green lighting for computing centers at all times and in all areas. This has important practical significance and application value for promoting the "low-carbon, efficient, and intelligent" operation of computing centers. Summary of the Invention

[0005] The purpose of this section is to outline some aspects of the embodiments of the present invention and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section, as well as in the abstract and title of the present application, to avoid obscuring the purpose of this section, the abstract and title of the invention. Such simplifications or omissions shall not be used to limit the scope of the present invention.

[0006] In view of the aforementioned existing problems, the present invention is proposed.

[0007] Therefore, the technical problem solved by this invention is to break through the traditional lighting's single dependence on mains power; to establish a multi-regional and multi-time period energy dynamic adaptation mechanism; to optimize system-level energy efficiency through intelligent control and load scenario linkage; and to optimize the adaptability of the lighting system to the operating characteristics of the computing center.

[0008] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a cross-temporal and spatial green lighting system for computing centers, characterized in that it includes: an optical fiber light guide module for introducing natural light into the computing center; a photovoltaic conversion and energy storage module for converting solar energy into electrical energy and storing it, wherein the photovoltaic conversion and energy storage module and the optical fiber light guide module constitute a photovoltaic-electricity complementary green energy supply structure; a human body sensing module for detecting the activity status of personnel in various areas within the computing center; an illuminance detection module for dynamically collecting ambient light intensity data of various areas; and a core control execution unit connected via industrial Ethernet to the optical fiber light guide module, the photovoltaic conversion and energy storage module, and the photovoltaic conversion and energy storage module. The system is connected to the energy module, the human body sensing module, and the illuminance detection module; the core control execution unit includes an intelligent collaborative control module and a zoned lighting execution module; the intelligent collaborative control module integrates a spatiotemporal collaborative algorithm, which is used to predict lighting energy consumption and schedule power across time dimensions and formulate zoned differentiated lighting strategies across spatial dimensions based on the personnel activity status, ambient light intensity data, and historical computing load data, coupled with the power supply status of the photovoltaic conversion and energy storage module, and generates lighting control commands; the zoned lighting execution module is used to execute corresponding lighting operations in the equipment area and maintenance channel according to the lighting control commands.

[0009] In a preferred embodiment of the present invention, the optical fiber light guiding module includes a light-collecting submodule, an optical fiber transmission submodule, and a light-diffusing submodule. The light-collecting submodule integrates a dual-axis gimbal, a Fresnel lens array, and a light-tracking sensor. The light-tracking sensor is used to track the sun's position in real time and dynamically adjust the light-collecting angle of the Fresnel lens array through the dual-axis gimbal. The light-diffusing submodule has a built-in microlens array for uniformly diffusing the optical fiber output light to meet the illumination requirements of the equipment area and the maintenance channel, respectively.

[0010] In a preferred embodiment of the present invention, the photovoltaic conversion and energy storage module includes a foldable photovoltaic panel, an energy storage submodule, and an energy management submodule; the foldable photovoltaic panel integrates a first adjustment part and a second adjustment part, the first adjustment part being used to achieve 360° circumferential rotation, and the second adjustment part being used to achieve pitch angle adjustment from -15° to 60°; when there is a covering on the surface of the foldable photovoltaic panel, the first adjustment part initiates circumferential rotation, while the second adjustment part is adjusted to remove the covering.

[0011] In a preferred embodiment of the present invention, the energy management submodule is used to execute energy dispatch logic: prioritizing the use of natural light introduced by the optical fiber guide module; automatically activating the power of the energy storage submodule when the natural light intensity is insufficient; and switching to the external power grid backup power supply when the power of the energy storage submodule is depleted.

[0012] As a preferred embodiment of the present invention, the cross-time dimension regulation performed by the intelligent collaborative control module includes: predicting peak computing load periods using a sliding window prediction method based on historical computing load data, and controlling the photovoltaic conversion and energy storage module to store electricity before the peak periods.

[0013] As a preferred embodiment of the present invention, the cross-spatial dimension control performed by the intelligent collaborative control module includes: for the equipment area, a basic lighting and dynamic supplementary lighting mode is adopted, and when the computing power load is ≥n%, the illuminance is automatically supplemented from the basic value to a higher value; where n is a constant; for the maintenance channel, a detection result mode based on the human body sensing module is adopted, and the lighting is delayed and turned off after the personnel leave.

[0014] As a preferred embodiment of the present invention, it further includes an emergency lighting module, which adopts a dual-circuit power supply design; the core control execution unit monitors the main circuit electrical signal in real time, and automatically switches to the backup circuit when the main circuit fails.

[0015] On the other hand, the present invention provides the following technical solution: a method for cross-temporal and spatial green lighting in a computing center, characterized in that it includes: collecting real-time illuminance data of each area through the illuminance detection module, collecting personnel activity status data through the human body sensing module, obtaining computing load data through the DCIM system interface, and collecting operation data through the energy management submodule of the photovoltaic conversion and energy storage module; an intelligent collaborative control module determines whether the natural light meets the current basic lighting requirements based on the real-time illuminance data; if it does, the fiber optic light guide module is activated first; if it does not, the power supply capacity of the photovoltaic conversion and energy storage module is determined to meet the supplementary lighting requirements. If the light demand is met, power is activated; if the demand cannot be met, power is switched to mains backup power. The intelligent collaborative control module, based on a spatiotemporal collaborative algorithm, combines computing load data, personnel activity status data, and real-time illuminance data to generate lighting adjustment strategies for the equipment area and maintenance channel respectively. The strategies include dynamically adjusting the illuminance of the equipment area according to the computing load and controlling the switching and brightness of the maintenance channel lighting according to the personnel activity status. The zoned lighting execution module drives the corresponding lighting equipment according to the lighting adjustment strategy. The core control execution unit monitors the lighting circuit and lamp status in real time, and automatically switches to the backup circuit and backup lamp when a fault is detected.

[0016] The beneficial effects of this invention are as follows: By maximizing the capture and efficient utilization of natural light, and combining it with the intelligent supplementation and scheduling of green electricity, this invention can significantly reduce lighting energy consumption and effectively reduce the operating costs of computing centers; by synergistically utilizing natural light and solar energy, it can significantly reduce dependence on grid electricity for lighting, thereby reducing carbon emissions, meeting the requirements of green and low-carbon development, and creating carbon asset revenue.

[0017] Furthermore, this invention achieves on-demand lighting through a spatiotemporal collaborative algorithm, which can both reserve power in advance based on load forecasting and perform differentiated lighting control according to the needs of different areas and time periods. At the same time, the system's redundancy design significantly improves operational stability. Equipped with emergency lighting with rapid switching capabilities and multiple backup protection mechanisms, it ensures the continuous and uninterrupted operation of the lighting system, thereby improving the overall security of the computing center's operation.

[0018] Furthermore, the special heat dissipation structure of the lighting fixtures and the arrangement that follows the airflow of the equipment effectively avoid interference from the lighting system on the heat dissipation of the computing equipment, thus ensuring the stable operation of the equipment while reducing the additional energy consumption of the cooling system. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a structural diagram of the cross-temporal green lighting system of the computing center in an embodiment of the present invention.

[0020] Figure 2 This is a control logic diagram of the cross-temporal green lighting system of the computing center in an embodiment of the present invention.

[0021] Figure 1 The system comprises: 1. Intelligent collaborative control and zoned lighting execution module; 2. Light-collecting sub-module; 3. Fiber optic transmission sub-module; 4. Foldable photovoltaic panel; 5. Energy storage sub-module; 6. Lighting distribution box; 7. Diffusion sub-module; 8. DC lighting fixtures; 9. AC lighting fixtures; 10. Illuminance detection module; and 11. Human body sensing module. Detailed Implementation

[0022] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0023] Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort should fall within the scope of protection of this invention.

[0024] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0025] According to an embodiment of the present invention, in combination Figure 1 The structural diagram shown illustrates a spatiotemporal green lighting system for a computing center, comprising: The fiber optic light guiding module includes a light-collecting submodule, a fiber optic transmission submodule, and a light-diffusing submodule.

[0026] The light-collecting submodule is installed in an open outdoor area above the computing center, with each submodule vertically corresponding to the center of 2-3 underground equipment areas / maintenance passages. It consists of a Fresnel lens array and a light-tracking sensor, and integrates a dual-axis gimbal.

[0027] The light-tracking sensor tracks the sun's position in real time with an accuracy of ±0.5°. The dual-axis gimbal dynamically adjusts the light-collecting angle to ensure that the angle of incidence of sunlight is ≤1°. The light-collecting submodule is fixed to a concrete base (dimensions 1.5m × 1.5m × 0.3m, load-bearing capacity ≥5kN), and the levelness error of the dual-axis gimbal is ≤0.1°.

[0028] Fiber optic transmission submodule: It adopts a multi-core quartz fiber bundle with a single core diameter of 500μm and a numerical aperture of 0.22. The outer layer of the fiber bundle is wrapped with an aluminum foil reflective layer and a flame-retardant sheath, and the transmission loss is ≤3% / 100m.

[0029] The fiber optic bundle is fixedly connected to the light-collecting and light-diffusing sub-modules via stainless steel flanges, with a sealing rating of IP65. The fiber optic transmission sub-modules are laid through PE conduits (diameter ≥ 50mm) with a bending radius ≥ 50cm.

[0030] Astigmatism module: Installed in the ceiling of the computing center, it has a built-in microlens array that can evenly diffuse the output light from the optical fiber, with an illumination angle of up to 120° to adapt to the different lighting requirements of the equipment area (300-500 lux) and the maintenance channel (150-200 lux).

[0031] Photovoltaic conversion and energy storage modules, including foldable photovoltaic panels, energy storage sub-modules, and energy management sub-modules.

[0032] The foldable photovoltaic panel, deployed around the ground-based phototransistor module, employs a perovskite-crystalline silicon stacked structure, operates within a temperature range of -40℃ to 85℃, withstands winds of ≥12 on the Beaufort scale, and features an AR coating (reflectivity ≤2%). It is equipped with a first adjustment unit and a second adjustment unit. The first adjustment unit can rotate 360° circumferentially, while the second adjustment unit can adjust the pitch angle from -15° to 60°, ensuring that the angle between the photovoltaic panel's normal and sunlight is ≤1°, thus increasing the light conversion efficiency to over 28%. In extreme weather conditions, when the photovoltaic panel surface is covered with snow / water, the first adjustment unit initiates circumferential rotation (10° / s), while the second adjustment unit adjusts the pitch angle to -15°, using gravity to remove the surface covering.

[0033] Energy storage submodule: Employs lithium iron phosphate battery packs with flexibly configurable capacity based on lighting power (e.g., 500 kWh), cycle life ≥ 3000 cycles, and paired with a bidirectional DC / DC converter. The battery pack features overcharge protection (triggered when charging voltage ≥ 3.65V / cell), over-discharge protection (triggered when discharging voltage ≤ 2.5V / cell), and over-temperature protection (triggered power-off when cell temperature ≥ 60℃), supporting off-grid operation for ≥ 8 hours.

[0034] The energy management submodule collects photovoltaic power generation, the SOC (State of Charge) of the energy storage submodule, and lighting energy consumption data every 0.5 seconds. It interacts with the data via the Modbus TCP protocol and executes the following energy dispatch logic: prioritizing natural light introduced by fiber optic cable; automatically activating photovoltaic energy storage power when natural light is insufficient; and switching to external grid backup power in extreme cases. If the illuminance is ≤50 lux for 24 consecutive hours, the system automatically switches to grid priority mode, and the energy storage submodule enters sleep mode.

[0035] The emergency lighting module, including the lighting distribution box and AC lighting fixtures, adopts a dual-circuit power supply design, with the two circuits connected to the main power supply line and the backup power supply line respectively. The core control execution unit monitors the voltage and current signals of the main circuit in real time, and automatically switches to the backup circuit within 0.3 seconds when the main circuit fails (such as when the voltage is lower than 80% of the rated value).

[0036] The human body sensing module uses infrared sensing technology and is deployed in various functional areas to detect the activity status of people in real time, with a detection response time of ≤0.1 seconds.

[0037] The illuminance detection module employs a high-precision photosensor with a measurement range of 0-1000 lux and an accuracy of ±2%, requiring annual calibration. It is evenly deployed across all zones, uploading ambient light data every 0.5 seconds. If a sensor in a certain area fails to provide data for 3 consecutive seconds, the intelligent collaborative control module automatically retrieves data from adjacent area sensors for interpolation calculations (error ≤10%) and sends a fault alarm.

[0038] The core control and execution unit includes an intelligent collaborative control module: configured with an edge computing unit (NVIDIA Jetson Xavier NX processor, 8GB memory, computing power ≥2 TOPS), and running a spatiotemporal collaborative algorithm. It should be noted that in spatiotemporal collaboration, the time dimension refers to "load peak prediction and advance power reserve," and the spatial dimension refers to "differentiated lighting strategies for equipment areas / maintenance channels."

[0039] The core logic of this algorithm includes dual control over both the time and space dimensions, as shown in the pseudocode below: Input: E set (Zone setting illuminance value), E now (Current detected illuminance value), H (Human body detection signal: 1 = someone is present, 0 = no one is present), L (Computing power load ratio), SOC (Remaining energy storage capacity), S solar (Real-time photovoltaic power generation); Among them, the remaining energy storage capacity (SOC) is the ratio of the current energy of the lithium iron phosphate battery pack to its rated capacity, with a value range of 0%-100%; the computing load ratio is the ratio of the actual operating load of the computing center to its rated load, with a value range of 0%-100%. Output: D out (Desired light output), S mode (Energy dispatch mode: 0 = natural light, 1 = photovoltaic energy storage, 2 = grid backup).

[0040] The conversion formula is: supplementary light power P = ΔE × S × K (ΔE is the difference in supplementary light, S is the area of ​​the region, and K is the lighting power coefficient, which is 0.001W / (lux·㎡)).

[0041] 1. Initialization parameters: E equipment area base = 300 lux, E equipment area peak = 500 lux, E channel occupied = 200 lux, E channel unoccupied = 0 lux, delay time = 30 seconds.

[0042] 2. If the current time period is daytime (6:00-18:00): a. S mode Default = 0 (prefers natural light); b. If H=1 (someone): i. If the area is an equipment zone: If L≥80%: E target =E Equipment Area Peak; Otherwise: E target =E Equipment Area Foundation; ii. If the region is an operations and maintenance channel: E target =There are people in the E channel; iii. If E now <E target Calculate the supplementary lighting difference ΔE=E target -E now ; Calculate the supplementary light power P = ΔE × S × K; If S solar If S ≥ P and SOC ≥ 30%, then S mode =1,D out =ΔE; Otherwise S mode =2,D out =ΔE.

[0043] c. If H=0 (no one is present): i. After the delay time, D out =0, S mode =None.

[0044] 3. If the current time period is not daytime: a. If H=1: i. Determine E by region target (Same as step 2.bi-ii); ii. Calculate the required power P=E target ×S×K; iii. If S solar If S ≥ P and SOC ≥ 30%, then S mode =1,D out =E target ; iv. Otherwise S mode =2,D out =E target .

[0045] b. If H=0: After the delay time, D out =0, S mode =None.

[0046] 4. Real-time feedback adjustment: Data is collected every second, and the above logic is repeated.

[0047] Furthermore, time-based control: Based on historical computing load data, illumination data, and personnel activity data (obtained through the DCIM system API interface, sampling frequency 1Hz, data filtered), a sliding window prediction method is adopted (window period 24 hours, weighted average method is used within the window, recent data weight 0.7, long-term data weight 0.3; abnormal data is removed by the 3σ criterion), with a prediction accuracy of ±5%, predicting peak computing load periods (such as 9:00-21:00), and storing electricity in advance through photovoltaic energy storage modules.

[0048] When the computing load suddenly increases from <80% to ≥80% (change rate ≥20% / s), the algorithm activates the fast supplemental lighting mode, and the time for the illuminance to increase from 300 lux to 500 lux is ≤2 seconds.

[0049] Spatial dimension control: The equipment area adopts the "basic lighting + dynamic supplementary lighting" mode. The basic lighting is maintained at 300 lux. When the computing load is ≥ n% (set to 80% in this embodiment), the supplementary lighting is automatically increased to 500 lux. The maintenance channel adopts the "lights on when people come, lights off when people leave" mode. The lighting is turned off 30 seconds after the personnel leave.

[0050] Among them, the basic lighting is the minimum illuminance (300 lux) required for the equipment area to maintain normal operation and maintenance.

[0051] Dynamic supplemental lighting refers to the additional illumination (0-200 lux) provided when the computing load is ≥80% or natural light is insufficient.

[0052] It should be noted that this module communicates with the zoned lighting execution module via industrial Ethernet (communication protocol is Modbus TCP, latency ≤10ms, port 502), adopts standard data frame format, sends control commands and receives status feedback to form a closed-loop control; it is equipped with a remote monitoring platform to display the system energy efficiency indicators in real time.

[0053] The zoned lighting execution module includes the following: Equipment area lighting sub-module: High heat dissipation LED lamps with a color temperature of 5000K and a color rendering index Ra≥90 are used. The lamps are integrated with a heat pipe heat dissipation structure and are arranged along the rack row direction, which is completely in line with the horizontal airflow direction of the cold aisle of the computing center. The power of a single lamp is 50W, the installation height is 3.5m from the ground, and the spacing between lamps is 2.5m.

[0054] Maintenance passage lighting sub-module: adopts low-voltage DC LED light strip (24V), supports stepless dimming (50-200 lux), power 10W / m, installed along the side wall (2.2m from the ground).

[0055] Backup protection submodule: Both the lighting power supply and control circuits are equipped with main and backup dual circuits, and both main and backup circuits use ZR-YJV-0.6 / 1kV cables; the lamps are configured with backup at a ratio of 1:1 (hidden installation in the spare ceiling slot).

[0056] When the main lighting circuit or luminaire fails, it will automatically switch to the backup circuit and backup luminaire within 0.5 seconds.

[0057] On the other hand, such as Figure 2 As shown, the present invention also provides a method for cross-temporal and spatiotemporal green lighting in computing centers, comprising: The illuminance detection module collects real-time illuminance data for each area every 0.5 seconds, the human body sensing module detects the activity status data of personnel in real time, the computing load data is obtained every 1 second through the DCIM system API interface, the energy management submodule collects the photovoltaic power generation and the SOC value of the energy storage submodule every 0.5 seconds, and all data are transmitted to the intelligent collaborative control module via industrial Ethernet.

[0058] The intelligent collaborative control module determines whether the current natural light meets the basic lighting needs of the area based on the real-time illuminance data (the judgment condition is E_now ≥ E equipment area basic or E channel occupied × 80%). If it meets the requirements, fiber optic lighting is given priority. If it does not meet the requirements, the module calculates the supplementary lighting power and determines whether the remaining power and real-time power generation of the photovoltaic energy storage module can supplement the lighting gap. If they can, the photovoltaic energy storage power supply is activated. If neither of the above two energy sources can meet the needs, the module switches to the mains backup power supply.

[0059] The intelligent collaborative control module is based on a spatiotemporal collaborative algorithm and combines various collected data to formulate lighting adjustment strategies for the equipment area and the maintenance channel respectively. For the equipment area, the illuminance is dynamically adjusted according to the computing load (supplementary lighting to 500 lux when the load is ≥80%, otherwise maintain 300 lux). For the maintenance channel, the lighting switch and brightness are controlled according to the personnel activity status (200 lux when there are people, and turn off after a 30-second delay when there is no one).

[0060] The zoned lighting execution module drives the corresponding lighting equipment to perform lighting actions based on the decision results; the core control execution unit monitors the voltage and current signals of the lighting circuit and the working status of the lamps in real time. If a fault is detected (such as the voltage being lower than 80% of the rated value or the lamp current being abnormal), the backup circuit and backup lamps are immediately activated, and an alarm message is sent to the remote monitoring platform.

[0061] Example 2 To further verify the beneficial effects of the present invention, the following implementation process is provided: The installation and debugging steps are as follows: First, confirm that the installation area of ​​the light-collecting submodule is unobstructed and that the annual average sunshine duration of the photovoltaic panel deployment area is ≥2000h. The module is installed as follows: (1) The light-collecting submodule is fixed to the concrete base, ensuring that the horizontal error of the dual-axis gimbal is ≤0.1°. (2) The fiber optic transmission submodule is laid in a conduit with a bending radius ≥50cm. (3) LED lights are installed in the equipment area at a distance of 3.5m from the ground and at a spacing of 2.5m; the maintenance channel light strip is installed along the side wall at a distance of 2.2m from the ground.

[0062] The debugging process includes: First, hardware debugging: testing the power supply voltage of each module. Second, algorithm debugging: inputting simulated data to verify whether the lighting output meets expectations. Finally, linkage debugging: simulating a main circuit fault to verify that the backup circuit switching time is ≤0.5 seconds and alarm information is pushed.

[0063] The specific implementation process is as follows: The application scenario is a 5000P computing center (total area of ​​10000㎡, including 10 equipment areas and 5 operation and maintenance channels).

[0064] The module configuration process is as follows: Fiber optic light guide modules: 20 light-collecting sub-modules are set up in the open outdoor area above the computing center. Each light-collecting sub-module is vertically aligned with the center of the two underground equipment areas / maintenance passages. Each light-collecting sub-module covers 500㎡ of underground area (precisely matched with the 120° illumination angle and 50m transmission distance of the diffused light sub-modules). The fiber bundle uses 1000-core quartz fiber (500μm diameter per core) with a transmission distance of 50m, ensuring a transmission loss of ≤1.5%. The diffused light sub-modules are evenly installed on the ceiling according to the distribution of equipment areas and maintenance passages to ensure uniform illumination.

[0065] Photovoltaic conversion and energy storage module: Deploy 200㎡ perovskite-crystalline silicon tandem photovoltaic panels (photovoltaic conversion efficiency 28%, operating temperature range -40℃~85℃), and match with a 1000kW·h lithium iron phosphate battery pack (cycle life ≥3000 cycles). This configuration can meet the lighting needs for 2 cloudy days and ensure a stable supply of green energy. The photovoltaic panels and energy storage sub-modules are connected by wires via a bidirectional DC / DC converter, and 50A fuses are installed on the wires. The mains power supplementation capacity accounts for ≤30%, meeting the annual power saving requirements.

[0066] Intelligent collaborative control module: Configured with 10 edge computing units (NVIDIA Jetson Xavier NX, 8GB memory), one unit for every two device zones. The edge computing units run a space-time collaborative algorithm with a sampling frequency of 1Hz to ensure real-time acquisition and rapid response of various types of data. The remote monitoring platform is deployed in the operation and maintenance management room of the computing power center, supporting web (browser access) and mobile (APP access) terminals, and displays key indicators such as PUE, energy consumption, and SOC value in real time.

[0067] Zoned lighting execution module: 100 sets of LED lights (50W power per set, 5000K color temperature, Ra≥90) are installed in the equipment area to ensure that the illuminance requirements of the equipment area are met under different load conditions; 200m LED light strip (10W / m power, 24V low voltage DC) is installed in the maintenance channel to adapt to stepless dimming requirements; both main and backup circuits use ZR-YJV-0.6 / 1kV cables to ensure safe and stable power supply.

[0068] Human body sensing module and illuminance detection module: 3-4 human body sensing sensors (response time ≤ 0.1 seconds) and illuminance sensors (measurement range 0-1000 lux, accuracy ±2%) are evenly deployed in each equipment area. The maintenance channel is configured with a density of 1 human body sensing sensor and illuminance sensor every 10m to ensure the accuracy and comprehensiveness of data collection.

[0069] The workflow is as follows: During the daytime (6:00-18:00), the light-collecting submodule tracks the sun's position in real time through a light-tracking sensor, and the dual-axis gimbal dynamically adjusts the light-collecting angle (to ensure the incident angle is ≤1°). After focusing the natural light, it transmits it to the underground computing center through an optical fiber bundle. The light-diffusing submodule evenly diffuses the optical fiber output light to the equipment area and maintenance passage. The illuminance sensor collects illuminance data for each area every 0.5 seconds and feeds it back to the intelligent collaborative control module via industrial Ethernet (Modbus TCP protocol).

[0070] Photovoltaic panels generate electricity under sunlight conditions, and the generated electricity is prioritized for use by the lighting system. When the power demand of the lighting system is less than the photovoltaic power generation, the excess power is stored in the lithium iron phosphate battery pack through a bidirectional DC / DC converter. When the illuminance of the fiber optic light is insufficient (such as on cloudy days or at dusk), the intelligent collaborative control module calculates the supplementary lighting power based on the feedback data from the illuminance sensor and automatically switches to the photovoltaic energy storage power supply mode.

[0071] The edge computing unit utilizes human status data detected by human body sensors, illuminance data detected by light sensors, and computing load data acquired by the DCIM system, and employs a runtime-space collaborative algorithm. (1) When the computing load of a certain device area is detected to increase from 60% to 90% (≥80%), the LED lights in that area are instructed to increase the illumination from 300 lux to 500 lux (fast illumination mode, time ≤2 seconds). (2) When the human body sensor detects that maintenance personnel enter a certain section of the maintenance channel, the corresponding LED light strip gradually brightens from 0 lux to 200 lux, and turns off after a 30-second delay after the personnel leave; (3) During peak computing load periods (9:00-21:00), the intelligent collaborative control module predicts demand in advance using the sliding window prediction method and schedules the energy storage sub-module to release power to ensure that lighting demand is stably met.

[0072] The core control execution unit monitors the voltage and current signals of the lighting circuit and the working status of the lamps in real time. If a fault occurs in the main lighting circuit of a certain equipment area (such as the voltage being lower than 80% of the rated value), the intelligent collaborative control module will start the backup circuit and backup lamps within 0.5 seconds after receiving the fault signal to maintain normal lighting in the area. It will also send alarm information (including the fault area and fault type) to the operation and maintenance personnel through the remote monitoring platform to remind them to repair in time.

[0073] It should be noted that this system and method are not only applicable to newly built computing centers, but also to the lighting renovation of existing computing centers. No large-scale alterations to the original building structure are required, making the renovation easy and cost-effective. Furthermore, it can be extended to large underground spaces such as large underground transportation hubs and large warehousing and logistics centers that require green lighting and intelligent control. (For large underground transportation hubs, the "computing load ratio" can be replaced with "personnel density," and the adjustment logic can be adjusted to "when the person flow is ≥50 people / 100㎡, the illuminance is increased to 300 lux," and other module parameters can be scaled proportionally according to the area). With a wide range of applications, it has enormous market potential.

[0074] Taking a 10,000㎡ computing center as an example, the initial investment includes 20 light-collecting sub-modules (approximately 800,000 yuan), 200㎡ of photovoltaic panels and a 1000kW·h energy storage system (approximately 1.5 million yuan), 100 sets of LED lights and 200m of LED light strips (approximately 300,000 yuan), 10 edge computing units and a monitoring platform (approximately 400,000 yuan), and other auxiliary equipment (sensors, cables, flanges, etc.) and installation costs of approximately 500,000 yuan, for a total initial investment of approximately 3.5 million yuan. Based on an annual electricity saving of 1.8 million kWh (180,000 kWh per 1,000 square meters, 1.8 million kWh for 10,000㎡), and an industrial electricity price of 0.8 yuan / kWh, the annual electricity cost savings are 1.44 million yuan. At the same time, the annual carbon emission reduction is approximately 800 tons. Based on a carbon trading price of 50 yuan / ton, the annual carbon asset income is approximately 40,000 yuan, for a total annual income of 1.48 million yuan. The static investment payback period is approximately 2.4 years, demonstrating significant economic and environmental benefits.

[0075] As can be seen, this invention maximizes the capture of natural light through the precise light tracking (incident angle ≤1°) and efficient transmission (loss ≤3% / 100m) of the fiber optic light guide module. Combined with the green power supplementation and intelligent scheduling of the photovoltaic energy storage module, it is expected to increase the utilization rate of natural light to 75% and reduce lighting energy consumption by 60%. Calculated based on a 1,000-square-meter computing center, the original traditional lighting system consumes about 300,000 kWh of energy per year, while this system consumes about 120,000 kWh per year, resulting in annual power savings of up to 180,000 kWh, significantly reducing the operating cost of the computing center.

[0076] This invention relies on the efficient and synergistic use of renewable energy sources such as natural light and solar energy to reduce dependence on grid electricity, thereby reducing carbon emissions. Taking a 1,000㎡ computing center as an example, it can reduce carbon emissions by about 80 tons per year (calculation basis: annual electricity saving of 180,000 kWh × 0.67 tons CO2 / 1,000 kWh ≈ 80 tons, which is in line with the "dual carbon" development goal and can also bring additional carbon asset benefits).

[0077] Furthermore, this invention utilizes a spatiotemporal collaborative algorithm to achieve pre-emptive power reserves based on load forecasting in the time dimension (prediction accuracy ±5%) and zoned differentiated lighting in the spatial dimension. This accurately matches the lighting needs of different areas and time periods within the computing center, achieving "on-demand lighting." Simultaneously, through the redundant design of the backup and protection submodule, the equipment failure rate is reduced by 40% (based on accelerated aging tests of 100 sets of lamps, the traditional lamps had 8 failures, while the redundant design of this invention resulted in 4.8 lamp failures, reducing the failure rate from 8% to 4.8%), thus improving system operational stability.

[0078] It is equipped with a complete emergency lighting module (dual power supply circuit, 0.3-second fast switching) and backup protection sub-module (redundant control circuit, 1:1 lamp backup). The main and backup dual circuits and backup lamp design ensure uninterrupted lighting. The combination of emergency power supply protection and the overall system operation characteristics effectively improves the security of the computing center operation.

[0079] The lighting fixtures in the equipment area adopt a specific heat pipe heat dissipation structure and an arrangement that conforms to the airflow of the cold aisle, so as to avoid the interference of lighting heat dissipation with equipment heat dissipation, reduce the additional energy consumption of the cooling system (reduced by 5%-8%), ensure the stable operation of the computing center equipment, and realize the coordinated optimization of the lighting system and the overall operation of the computing center.

[0080] The system also includes one or more processors and memory.

[0081] The memory is used to store operable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations, including the flow of a computing center spatiotemporal green lighting system according to the foregoing embodiments, particularly... Figure 1 The flowchart of the method is shown.

[0082] Other aspects disclosed in the embodiments of the present invention also propose a computer-readable medium for storing software including instructions executable by one or more computers, which, upon execution, cause the one or more computers to perform operations, including the flow of a computing center-based spatiotemporal green lighting system of the foregoing embodiments, particularly... Figure 1 The flowchart of the method is shown.

[0083] It should be recognized that embodiments of the present invention may be implemented or carried out by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable storage medium.

[0084] The method can be implemented using standard programming techniques, including a non-transitory computer-readable storage medium in which a computer program is integrated, wherein the storage medium is configured such that the computer operates in a specific and predefined manner.

[0085] Each program can be implemented in a high-level procedural or object-oriented programming language to communicate with the computer system; however, if required, the program can be implemented in assembly or machine language.

[0086] In any case, the language can be either compiled or interpreted.

[0087] Furthermore, for this purpose, the program can run on programmed application-specific integrated circuits.

[0088] The processes (or variations and / or combinations thereof) described herein can be executed under the control of one or more computer systems with integrated executable instructions, and can be implemented by hardware or a combination thereof as code (e.g., executable instructions, one or more computer programs, or one or more applications) that commonly executes on one or more processors. The computer program includes a plurality of instructions executable by one or more processors.

[0089] Furthermore, the method can be implemented in any suitable computing platform, including but not limited to personal computers, minicomputers, mainframes, workstations, networked or distributed computing environments, standalone or integrated computer platforms, or in communication with charged particle tools or other imaging devices.

[0090] Various aspects of the present invention can be implemented in machine-readable code stored on a non-transitory storage medium or device, whether portable or integrated into a computing platform, such as a hard disk, optical read and / or write storage medium, RAM, ROM, etc., such that it can be read by a programmable computer, and when the storage medium or device is read by the computer, it can be used to configure and operate the computer to perform the processes described herein.

[0091] Furthermore, machine-readable code, or parts thereof, can be transmitted via wired or wireless networks.

[0092] When such media includes instructions or programs that combine with a microprocessor or other data processor to implement the steps described above, the invention described herein includes these and other different types of non-transitory computer-readable storage media.

[0093] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A spatiotemporal green lighting system for a computing center, characterized in that: include: Fiber optic light guide module, used to introduce natural light into the computing center; A photovoltaic conversion and energy storage module is used to convert solar energy into electrical energy and store it. The photovoltaic conversion and energy storage module and the optical fiber light guide module constitute a green energy supply structure that is complementary to light and electricity. Human body sensing module is used to detect the activity status of personnel in various areas within the computing center; The illuminance detection module is used to dynamically collect ambient light intensity data for each area; The core control and execution unit is connected to the optical fiber light guide module, the photovoltaic conversion and energy storage module, the human body sensing module and the illuminance detection module via an industrial Ethernet; The core control execution unit includes an intelligent collaborative control module and a zoned lighting execution module; The intelligent collaborative control module integrates a spatiotemporal collaborative algorithm, which is used to predict lighting energy consumption and schedule power across time dimensions and formulate differentiated lighting strategies across spatial dimensions based on the personnel activity status, ambient light intensity data and historical computing load data, and coupled with the power supply status of the photovoltaic conversion and energy storage module, and generate lighting control commands. The zoned lighting execution module is used to perform corresponding lighting operations in the equipment area and maintenance channel according to the lighting control instructions.

2. The computing center cross-temporal green lighting system as described in claim 1, characterized in that: The optical fiber light guide module includes a light collection submodule, an optical fiber transmission submodule, and a light diffusion submodule; The light-collecting submodule integrates a dual-axis gimbal, a Fresnel lens array, and a light-tracking sensor. The light-tracking sensor is used to track the sun's position in real time and dynamically adjust the light-collecting angle of the Fresnel lens array through the dual-axis gimbal. The astigmatism submodule has a built-in microlens array to uniformly diffuse the output light from the optical fiber, adapting to the illumination requirements of the equipment area and the maintenance channel respectively.

3. The computing center cross-temporal green lighting system as described in claim 2, characterized in that: The photovoltaic conversion and energy storage module includes a foldable photovoltaic panel, an energy storage submodule, and an energy management submodule; The foldable photovoltaic panel integrates a first adjustment part and a second adjustment part. The first adjustment part is used to achieve 360° circumferential rotation, and the second adjustment part is used to achieve pitch angle adjustment from -15° to 60°. When there is a covering on the surface of the foldable photovoltaic panel, the first adjustment part starts to rotate circumferentially, while the second adjustment part is adjusted to remove the covering.

4. The cross-temporal green lighting system for computing centers as described in claim 3, characterized in that: The energy management submodule is used to execute energy dispatch logic: prioritize the use of natural light introduced by the optical fiber light guide module; when the natural light intensity is insufficient, automatically activate the power of the energy storage submodule; when the power of the energy storage submodule is exhausted, switch to the external power grid backup power supply.

5. The computing center cross-temporal green lighting system as described in claim 4, characterized in that: The cross-time dimension regulation performed by the intelligent collaborative control module includes: Based on historical computing load data, a sliding window prediction method is used to predict peak computing load periods, and the photovoltaic conversion and energy storage module is controlled to store electricity before the peak period.

6. The cross-temporal green lighting system for computing centers as described in claim 5, characterized in that: The cross-spatial dimension regulation performed by the intelligent collaborative control module includes: For the equipment area, a basic lighting and dynamic supplemental lighting mode is adopted. When the computing load is ≥ n%, the illuminance is automatically supplemented from the basic value to a higher value; where n is a constant. For maintenance channels, a detection result mode based on the human body sensing module is adopted, and the lighting is turned off after a delay after personnel leave.

7. The cross-temporal green lighting system for computing centers as described in claim 1, characterized in that: It also includes an emergency lighting module, which adopts a dual-circuit power supply design; The core control execution unit monitors the main circuit electrical signals in real time, and automatically switches to the backup circuit when the main circuit fails.

8. A method for cross-temporal and spatial green lighting for computing centers, based on the cross-temporal and spatial green lighting system for computing centers according to any one of claims 1 to 7, characterized in that: Also includes: The system collects real-time illuminance data for each area through the illuminance detection module, collects personnel activity status data through the human body sensing module, obtains computing load data through the DCIM system interface, and collects operation data through the energy management submodule of the photovoltaic conversion and energy storage module. The intelligent collaborative control module determines whether the natural light meets the current basic lighting requirements based on real-time illuminance data. If it does, the fiber optic light guide module is activated first. If it does not, the module determines whether the power supply capacity of the photovoltaic conversion and energy storage module meets the supplementary lighting requirements. If it does, the power supply is activated. If the requirements cannot be met, the module switches to the mains backup power supply. The intelligent collaborative control module is based on a spatiotemporal collaborative algorithm, which combines computing load data, personnel activity status data and real-time illuminance data to generate lighting adjustment strategies for the equipment area and the maintenance channel respectively. The strategies include dynamically adjusting the illuminance of the equipment area according to the computing load, and controlling the on / off and brightness of the maintenance channel lighting according to the personnel activity status. The zoned lighting execution module drives the corresponding lighting devices according to the lighting adjustment strategy; The core control execution unit monitors the status of the lighting circuit and lamps in real time, and automatically switches to the backup circuit and backup lamps when a fault is detected.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the computing center intertemporal green lighting system according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the computing center intertemporal green lighting system as described in any one of claims 1 to 7.

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