A power distribution room anti-condensation dehumidification method using an optical radiation technology energy-saving dehumidification device

Abstract

The application discloses a power distribution room anti-condensation dehumidification method using an optical radiation technology energy-saving dehumidification device, and relates to the technical field of power distribution room dehumidification. The method comprises the following steps: dividing the power distribution room into a plurality of monitoring areas, installing environment monitoring sensors and intelligent adjusting devices in the monitoring areas, and configuring a communication gateway to build a local communication network; based on the Internet of Things and node communication technology, a dynamic environment control system integrating distributed environment monitoring sensors and intelligent adjusting devices is constructed to monitor and collect environment data and device state data of each monitoring area in the power distribution room in real time, and a digital model containing time and space characteristics is established; based on a preset power distribution room dehumidification task standard, the environment data monitored at the current moment are compared, and the monitoring area with an abnormality is identified. The optical radiation technology energy-saving dehumidification device and the dynamic environment control system are integrated, the cooling and dehumidification effect in the power distribution room is greatly improved, and a more stable and reliable environment guarantee is provided for power distribution equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of dehumidification in power distribution rooms, and in particular to an anti-condensation dehumidification method for power distribution rooms using an energy-saving dehumidification device using light radiation technology. Background Art

[0002] In power distribution rooms, the difference between the heat generated by equipment operation and the ambient temperature can easily cause localized temperature drops. When the humidity saturation reaches 100%, water vapor condenses on cooling surfaces. These condensed droplets can seep into the metal surfaces or insulating components of electrical equipment, causing corrosion, oxidation of metal components, poor contact, degraded insulation, and even short circuits and electrical fires. To ensure the normal operation of equipment in power distribution rooms, extend its service life, and improve its safety and reliability, anti-condensation and dehumidification are crucial.

[0003] Currently, the main technologies for preventing condensation and dehumidifying distribution rooms include air conditioning dehumidification, the use of desiccant agents, dedicated dehumidifiers, and ventilation systems. Air conditioning dehumidification reduces air humidity through refrigeration, preventing condensation from forming from water vapor in the air. Desiccant agents, such as silica gel and molecular sieves, absorb moisture from the air through physical adsorption and are commonly used for humidity control in small areas or specific regions. Dedicated dehumidifiers, on the other hand, use the condensation principle to remove moisture from the air through cooling and drainage, making them a common solution. Furthermore, ventilation systems increase air circulation speed, helping to dissipate and circulate moisture, thereby reducing humidity.

[0004] While existing technologies can effectively control humidity and prevent condensation to a certain extent, some shortcomings remain. First, while air conditioning dehumidification can effectively remove moisture, it consumes a lot of energy, which can result in significant electricity costs, especially in large-scale power distribution rooms. Furthermore, air conditioning dehumidification requires certain temperature control of the equipment, as excessively low temperatures can negatively impact the equipment. Second, while the use of desiccant absorbers is relatively inexpensive, their moisture absorption capacity is limited. When humidity is high, the absorbers easily become saturated, requiring frequent replacement or heating and regeneration. This not only increases maintenance workload but also incurs additional operating costs. Noise issues with dedicated dehumidifiers are also a major drawback, especially in power distribution rooms that operate 24 / 7, where noise can affect the work environment and productivity of workers. Furthermore, while traditional ventilation systems can reduce humidity through air circulation, they cannot completely guarantee stable humidity control. Especially in humid environments, relying on ventilation systems makes effective dehumidification difficult.

[0005] In terms of intelligence and system control, most current dehumidification equipment still uses traditional manual control or simple automated control, lacking precise intelligent management and adjustment mechanisms. For example, many devices are unable to monitor humidity and temperature changes within the distribution room in real time, nor do they have the function to automatically adjust the dehumidification mode based on specific environmental conditions. Furthermore, most existing dehumidification technologies are single-function devices, making it difficult to integrate and synergize multiple technologies. Without information sharing and intelligent control between devices, dehumidification performance is easily affected by changes in the external environment, and operational status cannot be optimized in real time, thus affecting dehumidification effectiveness and energy efficiency. Summary of the Invention

[0006] Based on this, it is necessary to provide a distribution room anti-condensation dehumidification method using a light radiation technology energy-saving dehumidification device to address the above technical problems.

[0007] The present invention provides a method for preventing condensation and dehumidification in a power distribution room using a light radiation technology energy-saving dehumidification device, the method comprising the following steps:

[0008] S1. Divide the power distribution room into several monitoring areas, install environmental monitoring sensors and intelligent adjustment equipment in the monitoring areas, configure communication gateways, and build a local communication network;

[0009] S2. Based on the Internet of Things and node communication technologies, a dynamic environmental control system integrating distributed environmental monitoring sensors and intelligent control equipment is constructed to monitor and collect environmental data and equipment status data from each monitoring area in the power distribution room in real time, and to establish a digital model that includes temporal and spatial characteristics.

[0010] S3: Based on the preset dehumidification task standard for the power distribution room, the system compares the currently monitored environmental data, identifies the monitoring areas with abnormalities, and controls the intelligent adjustment equipment to perform the anti-condensation dehumidification task;

[0011] S4. Real-time monitoring of temperature and humidity changes during the dehumidification process in the power distribution room. Optimization targets are set for optimal equipment energy efficiency and dehumidification performance. Energy-saving control models are created to adjust the control parameters of different intelligent control devices within each monitoring area to optimize the performance of anti-condensation and dehumidification tasks.

[0012] S5. Real-time monitoring of the dehumidification effect and equipment status data of each monitoring area in the power distribution room. When there is equipment failure or abnormal operation, fault warning and maintenance response are triggered;

[0013] The following steps are involved: real-time monitoring of temperature and humidity changes during the dehumidification process in the power distribution room; setting optimal equipment energy efficiency and dehumidification performance as optimization targets; creating an energy-saving control model; adjusting the control parameters of different intelligent control devices in each monitoring area; and optimizing the execution of anti-condensation dehumidification tasks.

[0014] S41. Set a sampling frequency to regularly obtain environmental data and device status data of the intelligent regulating device during the execution of the anti-condensation and dehumidification task, and combine the data with the timestamp information to form a time series.

[0015] S42. Set input variables and output variables, set the optimal equipment energy efficiency by maximizing the humidity reduction rate per unit power consumption, set the optimal dehumidification performance by maximizing the humidity reduction effect in the power distribution room, and establish an energy-saving control model for the intelligent control equipment to perform anti-condensation dehumidification tasks;

[0016] S43. Use the distributed particle swarm optimization algorithm to solve the energy-saving control model, output the optimal control strategy, and adjust and optimize the control parameters of the intelligent control equipment according to the optimal control strategy.

[0017] Furthermore, the power distribution room is divided into several monitoring areas, environmental monitoring sensors and intelligent adjustment equipment are installed in the monitoring areas, and communication gateways are configured. Building a local area communication network includes the following steps:

[0018] S11. Based on the spatial layout of the power distribution room, the density of electromechanical equipment, and the dehumidification requirements of the equipment, the power distribution room is divided into different types of monitoring areas. The monitoring areas include the main computer room area, auxiliary area, conditioning equipment area, and monitoring area.

[0019] S12. Install environmental monitoring sensors in a distributed manner in the monitoring area to ensure that the monitoring range covers the entire space of the power distribution room. The environmental monitoring sensors include temperature sensors, humidity sensors, light radiation sensors, air flow rate sensors, and energy consumption sensors.

[0020] S13. Install intelligent regulating equipment at corresponding locations within the monitoring area. The intelligent regulating equipment includes a light radiation technology energy-saving dehumidification device, a fan, an air conditioner, and a condensing dehumidifier;

[0021] S14. Set the environmental monitoring sensor as a communication node, configure a communication gateway in the monitoring area, configure the communication protocol, build a local communication network, use the communication gateway to perform data aggregation and command forwarding, and realize the coordinated work of various intelligent adjustment devices.

[0022] Furthermore, based on the Internet of Things and node communication technology, a dynamic environment control system integrating distributed environmental monitoring sensors and intelligent adjustment equipment is constructed to monitor and collect environmental data and equipment status data of each monitoring area in the power distribution room in real time. The establishment of a digital model with spatiotemporal characteristics includes the following steps:

[0023] S21. Based on the Internet of Things and node communication technology, build a multi-layer integrated Internet of Things architecture to form a dynamic environment control system to manage environmental monitoring sensors and intelligent adjustment equipment;

[0024] S22. Use environmental monitoring sensors to collect real-time environmental data from each monitoring area, including temperature data, humidity data, light radiation data, air flow rate data, and equipment energy consumption data, and monitor equipment status data fed back during the operation of the intelligent control equipment;

[0025] S23, preprocessing the collected environmental data and device status data, and integrating the environmental data into a multidimensional spatiotemporal data set based on timestamp and spatial location information;

[0026] S24. Establish a digital model based on the spatial layout of the distribution room, map the spatiotemporal dataset into the three-dimensional space of the digital model, and generate a visualization model that dynamically displays changes in environmental data.

[0027] Furthermore, the dynamic environment control system includes a perception layer, a network layer, an application layer and a response layer; wherein, the perception layer includes distributed environmental monitoring sensors for real-time collection of environmental data, the network layer includes a local area communication network established by a communication gateway, the application layer includes a dynamic environment control center for data processing, equipment control, three-dimensional modeling and visualization, and the response layer includes a number of intelligent adjustment devices.

[0028] Furthermore, based on the preset dehumidification task standard for the power distribution room, the currently monitored environmental data is compared, abnormal monitoring areas are identified, and the intelligent adjustment device is controlled to perform the anti-condensation dehumidification task, including the following steps:

[0029] S31. Based on the actual operating requirements and equipment performance of the power distribution room, set standard thresholds for various types of environmental data. Combined with the hierarchical response of the intelligent adjustment equipment, establish the dehumidification task standards for the power distribution room.

[0030] S32. Based on the spatiotemporal distribution of the digital model, the environmental data collected in real time is compared with the corresponding standard threshold value to determine whether the intelligent adjustment device meets the execution conditions, and the corresponding intelligent adjustment device is selected to perform the anti-condensation and dehumidification task;

[0031] S33. Obtain the judgment result of the environmental data, mark the monitoring area that exceeds the standard threshold, and mark the abnormal level of the monitoring area according to the amount of environmental data that exceeds the standard threshold.

[0032] Furthermore, based on the spatiotemporal distribution of the digital model, the environmental data collected in real time is compared with the corresponding standard threshold value to determine whether the intelligent adjustment device meets the execution conditions. The selection and calling of the corresponding intelligent adjustment device to perform the anti-condensation dehumidification task includes the following steps:

[0033] S321. Based on the spatial distribution of the digital model, the humidity data in each monitoring area is preferentially compared with the humidity standard threshold. If the humidity data does not exceed the humidity standard threshold, the anti-condensation dehumidification task is not performed. If the humidity data exceeds the humidity standard threshold, the system enters a warning state and selects the corresponding intelligent adjustment device according to the priority, and executes step S322.

[0034] S322. Compare the light radiation data in each monitoring area with the light radiation standard threshold. If the light radiation data is within the light radiation standard threshold, control the light radiation technology energy-saving dehumidification device to perform the anti-condensation dehumidification task, and execute step S323. If the light radiation data does not meet the light radiation standard threshold, control other intelligent adjustment devices to perform the anti-condensation dehumidification task, and execute step S324.

[0035] S323. After the optical radiation technology energy-saving dehumidification device participates in the anti-condensation dehumidification task, if the humidity data in the monitoring area exceeds the upper limit of the humidity standard threshold, the condensing dehumidifier is activated to realize linkage and reduce the indoor humidity of the power distribution room. If the temperature data in the monitoring area exceeds the temperature standard threshold, the air conditioner is activated to realize linkage and adjust the indoor temperature. If the air flow rate data in the monitoring area does not meet the flow rate standard threshold, the fan is activated to realize linkage and adjust the indoor air flow rate.

[0036] S324. Disable the light radiation technology energy-saving dehumidification device, start the condensing dehumidifier, and reduce the indoor humidity in the distribution room. If the temperature data in the monitoring area exceeds the temperature standard threshold, start the air conditioner to achieve linkage and adjust the indoor temperature. If the air flow rate data in the monitoring area does not meet the flow rate standard threshold, start the fan to achieve linkage and adjust the indoor air flow rate.

[0037] Furthermore, input and output variables are set, and the maximization of the humidity reduction rate per unit power consumption is set as the optimal equipment energy efficiency, and the maximization of the humidity reduction effect in the distribution room is set as the optimal dehumidification performance. Establishing an energy-saving control model for intelligent adjustment equipment to perform anti-condensation dehumidification tasks includes the following steps:

[0038] S421. Set the power distribution room humidity data, temperature data, air flow rate data, light radiation data, and real-time power consumption of the intelligent control device as input variables, and set the device energy efficiency, humidity change rate, and total energy consumption as output variables;

[0039] S422. Maximizing the humidity reduction rate per unit power consumption and maximizing the humidity reduction effect in the power distribution room are optimization goals. An objective function for the power distribution room anti-condensation and dehumidification task is established, and sub-objective functions for local equipment energy consumption and humidity reduction effect are independently calculated for each monitoring area.

[0040] S423, based on the historical operation data of each type of intelligent adjusting device, a mathematical model between energy consumption and humidity reduction rate of the intelligent adjusting device is established, constraint conditions of the anti-condensation dehumidification task are set according to the pre-set dehumidification task standard of the power distribution room, and an energy-saving regulation and control model of the power distribution room is constructed.

[0041] Further, the expression of the objective function is:

[0042]

[0043] In the formula, MaximszeJ indicates the objective function; Δ RH indicates the humidity change rate; Pi indicates the real-time power consumption of the i intelligent adjusting device; N indicates the number of intelligent adjusting devices; w 1, w 2 both indicate weight coefficients.

[0044] Further, the distributed particle swarm optimization algorithm is used to solve the energy-saving regulation and control model, and the optimal regulation and control strategy is output. The control parameters of the optimized intelligent adjusting device are adjusted according to the optimal regulation and control strategy, including the following steps:

[0045] S431, according to the real-time collected environmental data and equipment state data in each monitoring area of the power distribution room, initialize the particle swarm, each particle represents a type of data combination, randomly select n particles in the particle swarm, average division into particle groups and difference groups, and distribute the two groups of particles in different areas;

[0046] S432, set the parameters of the particle swarm optimization algorithm and the differential evolution algorithm, calculate the fitness value of the current particle individual, and find the optimal particle individual in the particle swarm and the difference group, respectively marked as the optimal particle individual and the optimal difference individual;

[0047] S433, select the optimal particle individual from the optimal particle individual and the optimal difference individual, if the iteration number reaches the maximum value, stop the operation, and take the optimal particle individual as the optimal regulation and control strategy, if the iteration does not reach the maximum value, execute step S434;

[0048] S434, replace the optimal particle individual in the particle swarm and the difference group with the optimal particle individual in the optimal particle individual and the optimal difference individual to generate a new generation of particle swarm and difference group;

[0049] S435, update the position and speed of the particle individual in the particle group using the particle swarm optimization algorithm, and update the difference group by hybridization and selection of the individuals in the difference group using the differential evolution algorithm;

[0050] S436. During the iteration process, determine whether there is stagnation in the individuals in the group. If so, use the position update formula to mutate the individuals and obtain the latest positions of the individuals.

[0051] S437. Return to step S432 and continue until the iteration ends.

[0052] Furthermore, the position update formula is:

[0053]

[0054] Where, express t +1 individual in iteration k location; A min represents the best position for individual search; A max - A min Indicates the boundary range within which the search is allowed; rand (0, 1) represents a random number generated in the interval [0, 1].

[0055] The beneficial effects of the present invention are:

[0056] 1. By integrating the energy-saving dehumidification device based on light radiation technology and the dynamic environment control system, a major breakthrough in the environmental control in the distribution room has been achieved; not only can the temperature and humidity changes be accurately grasped through distributed lifting and intelligent adjustment, but the equipment can also be intelligently adjusted according to actual needs to ensure that the environmental data is maintained within the ideal range and achieve precise control; at the same time, the dynamic environment control system can respond to changes in environmental data in real time, quickly trigger the execution equipment, and significantly enhance the environmental response speed; in addition, the comprehensive application of energy-saving dehumidification devices based on light radiation technology, fans, condensing dehumidifiers and other high-efficiency equipment, combined with intelligent closed-loop control, greatly improves the cooling and dehumidification effect in the distribution room, and provides a more stable and reliable environmental protection for the distribution equipment; therefore, the present invention effectively improves the intelligence and efficiency of the distribution room environmental control, and ensures the safe and stable operation of the power system.

[0057] 2. By dividing monitoring areas and deploying environmental monitoring sensors and intelligent control devices, combined with IoT and node communication technologies, this system enables real-time monitoring and precise identification of abnormal areas. It dynamically controls the coordinated operation of multiple intelligent control devices, achieving efficient, anti-condensation dehumidification. Furthermore, it optimizes equipment operating parameters based on energy-saving control models, targeting optimal energy efficiency and dehumidification performance, effectively reducing energy consumption. Furthermore, real-time fault monitoring and maintenance response ensure the safety and reliability of equipment operation. The overall solution is highly intelligent and offers significant energy savings, meeting the anti-condensation dehumidification needs of complex distribution room environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0059] Figure 1 The present invention is a flowchart of a method for preventing condensation and dehumidification in a power distribution room using an energy-saving dehumidification device using light radiation technology according to an embodiment of the present invention. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, 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 only used to explain the present invention and are not intended to limit the present invention.

[0061] See also Figure 1 A method for preventing condensation and dehumidification in a power distribution room using a light radiation technology energy-saving dehumidification device, the method comprising the following steps:

[0062] S1. Divide the power distribution room into several monitoring areas, install environmental monitoring sensors and intelligent adjustment equipment in the monitoring areas, configure communication gateways, and build a local communication network.

[0063] In the description of the present invention, the power distribution room is divided into several monitoring areas, environmental monitoring sensors and intelligent adjustment equipment are installed in the monitoring areas, and communication gateways are configured. Building a local area communication network includes the following steps:

[0064] S11. Based on the spatial layout of the distribution room, the density of electromechanical equipment, and the dehumidification requirements of the equipment, the distribution room is divided into different types of monitoring areas, and the monitoring areas include the main computer room area, auxiliary area, regulation equipment area, and monitoring area.

[0065] Specifically, the main control room area is the area within the power distribution room where major power equipment (such as transformers and circuit breakers) is located. Auxiliary areas include cable mezzanines, passageways, and storage areas for power accessories. The conditioning equipment area is where air conditioning units and ventilation equipment are installed. The monitoring area is the control system equipment area, used for data monitoring and system operation control.

[0066] S12. Install environmental monitoring sensors in a distributed manner in the monitoring area to ensure that the monitoring range covers the entire space of the distribution room. The environmental monitoring sensors include temperature sensors, humidity sensors, light radiation sensors, air flow rate sensors and energy consumption sensors.

[0067] S13. Install intelligent regulating equipment at corresponding locations within the monitoring area. The intelligent regulating equipment includes light radiation technology energy-saving dehumidification devices, fans, air conditioners and condensing dehumidifiers.

[0068] Specifically, a light radiation energy-saving dehumidification device utilizes light radiation (typically solar energy or electricity) to heat the device, thereby accelerating the dehumidification process. This technology utilizes light or radiation sources (such as infrared radiation or sunlight) to provide heat to the dehumidification system, increasing the evaporation rate of moisture in the air, reducing humidity, and preventing condensation. In power distribution room dehumidification, light radiation technology can remove moisture in an energy-efficient manner, preventing equipment damage caused by condensation. It also offers advantages in improving energy efficiency and reducing operating costs.

[0069] Energy-saving dehumidification devices using light radiation technology generally rely on the following principles:

[0070] Photothermal conversion principle: Photothermal technology converts light energy into heat energy through a light source (such as sunlight or infrared light). This process transfers heat to the surrounding air through surface radiation, conduction, or convection. When the air is heated, the water vapor content increases, increasing the evaporation rate and reducing moisture accumulation, thereby lowering the relative humidity.

[0071] Moisture evaporation and condensation: The core goal of optical radiation technology is to promote the evaporation of moisture from the air by providing heat. When the humidity in the distribution room is high, the moisture in the air is heated by the light source and converted into water vapor, thereby reducing the possibility of condensation. The water vapor releases heat during the heating process, lowering the humidity and the possibility of condensation, thus preventing moisture from corroding electrical equipment.

[0072] In power distribution rooms, the primary purpose of anti-condensation dehumidification is to maintain a suitable humidity environment to prevent condensation from corroding electrical equipment, causing insulation failure, and short circuits. Traditional dehumidification methods (such as air conditioners, dehumidifiers, and desiccant agents) suffer from high energy consumption, difficult maintenance, and high noise levels. Optical radiation technology offers a more energy-efficient and environmentally friendly solution. This technology utilizes solar energy or other radiation sources to heat the dehumidification system or promote water vapor evaporation, thereby increasing the evaporation rate and reducing relative humidity. Because optical radiation directly provides heat, the dehumidification process requires less external energy, resulting in a high energy efficiency ratio. Furthermore, optical radiation technology does not rely on mechanical compression or chemical desiccant absorption, reducing equipment complexity and maintenance requirements, while also avoiding the noise issues associated with traditional dehumidification technologies.

[0073] S14. Set the environmental monitoring sensor as a communication node, configure a communication gateway in the monitoring area, configure the communication protocol, build a local communication network, use the communication gateway to perform data aggregation and command forwarding, and realize the coordinated work of various intelligent adjustment devices.

[0074] Specifically, local communication networks can choose Ethernet-based wired communication networks to ensure stable data transmission, or wireless communication protocols (such as Wi-Fi, Zigbee, and LoRa) to adapt to the needs of different spatial layouts. In local areas or areas with a high concentration of devices, wired communication is preferred to ensure data reliability and bandwidth. In areas with widespread device distribution or complex spatial structures, wireless communication can be selected, such as using Zigbee (a low-power wireless communication protocol) or LoRa (a protocol suitable for long-distance, low-power devices) to connect sensors.

[0075] S2. Based on the Internet of Things and node communication technology, a dynamic environment control system is constructed that integrates distributed environmental monitoring sensors and intelligent adjustment equipment to monitor and collect environmental data and equipment status data of each monitoring area in the distribution room in real time, and establish a digital model that includes temporal and spatial characteristics.

[0076] In the description of the present invention, based on the Internet of Things and node communication technology, a dynamic environment control system integrating distributed environmental monitoring sensors and intelligent adjustment equipment is constructed to monitor and collect environmental data and equipment status data of each monitoring area in the power distribution room in real time. The establishment of a digital model containing spatiotemporal characteristics includes the following steps:

[0077] S21. Based on the Internet of Things and node communication technology, build a multi-layer integrated Internet of Things architecture to form a dynamic environment control system to manage environmental monitoring sensors and intelligent adjustment equipment.

[0078] In this description, the dynamic environment control system includes a perception layer, a network layer, an application layer, and a response layer. The perception layer includes distributed environmental monitoring sensors for real-time environmental data collection; the network layer includes a local area communication network established by a communication gateway; the application layer includes a dynamic environment control center for data processing, device control, 3D modeling, and visualization; and the response layer includes several intelligent adjustment devices.

[0079] Specifically, a dynamic environmental monitoring and control system (Dynamic Environmental Monitoring and Control System), or DES for short, is an automated control system that monitors environmental conditions (such as temperature, humidity, and air quality) of key equipment in distribution rooms and computer rooms and provides real-time control to ensure optimal equipment operation. The DES's goal is to ensure that environmental conditions (such as temperature and humidity) are suitable for the operation of power equipment, preventing damage to equipment caused by environmental factors (such as excessive humidity or low temperatures), thereby improving equipment safety, reliability, and service life.

[0080] In the anti-condensation and dehumidification of distribution rooms, the key role of the dynamic environment control system is to collect real-time temperature and humidity data through sensors and adjust the operating status of different dehumidification equipment (such as light radiation technology energy-saving dehumidification devices, fans, condensing dehumidifiers and air conditioners) based on this data, thereby achieving optimal humidity control and energy saving effects, and preventing condensation, corrosion, short circuits and other problems caused by excessive moisture in the equipment.

[0081] S22. Use environmental monitoring sensors to collect environmental data of each monitoring area in real time. The environmental data includes temperature data, humidity data, light radiation data, air flow rate data and equipment energy consumption data, and monitor the equipment status data fed back during the operation of the intelligent adjustment equipment.

[0082] S23. Preprocess the collected environmental data and device status data, and integrate the environmental data into a multidimensional spatiotemporal dataset based on timestamp and spatial location information.

[0083] S24. Establish a digital model based on the spatial layout of the distribution room, map the spatiotemporal dataset into the three-dimensional space of the digital model, and generate a visualization model that dynamically displays changes in environmental data.

[0084] Specifically, use a 3D modeling tool (such as Unity, Blender, or a custom engine) to create a basic 3D model based on the actual layout of the power distribution room. Map the spatiotemporal data into 3D space to generate a visualization model that dynamically displays changes in environmental parameters. Color coding can be used to represent different temperature and humidity ranges, for example, red for high temperature and high humidity, and blue for low temperature and low humidity. Furthermore, particle flow can be used to display air flow direction, and dynamic cursors can be used to display the real-time operating area of ​​the dehumidifier.

[0085] S3. Based on the preset dehumidification task standard for the distribution room, compare the currently monitored environmental data, identify the monitoring areas with abnormalities, and control the intelligent adjustment equipment to perform the anti-condensation dehumidification task.

[0086] In the description of the present invention, based on the preset distribution room dehumidification task standard, comparing the currently monitored environmental data, identifying the monitoring area with abnormalities, and controlling the intelligent adjustment device to perform the anti-condensation dehumidification task includes the following steps:

[0087] S31. Based on the actual operating requirements and equipment performance of the distribution room, set standard thresholds for various types of environmental data, and combine the graded responses of the intelligent adjustment equipment to establish the dehumidification task standards for the distribution room.

[0088] S32. Based on the spatiotemporal distribution of the digital model, the environmental data collected in real time is compared with the corresponding standard threshold value to determine whether the intelligent adjustment device meets the execution conditions, and the corresponding intelligent adjustment device is selected to perform the anti-condensation and dehumidification task.

[0089] In the description of the present invention, based on the spatiotemporal distribution of the digital model, the environmental data collected in real time is compared with the corresponding standard threshold value, and whether the intelligent adjustment device meets the execution conditions is determined. Selecting to call the corresponding intelligent adjustment device to perform the anti-condensation dehumidification task includes the following steps:

[0090] S321. According to the spatial distribution of the digital model, the relationship between the humidity data in each monitoring area and the humidity standard threshold is preferentially compared. If the humidity data does not exceed the humidity standard threshold, the anti-condensation dehumidification task is not performed. If the humidity data exceeds the humidity standard threshold, the warning state is entered, and the corresponding intelligent adjustment device is selected according to the priority, and step S322 is executed.

[0091] S322. Compare the relationship between the light radiation data in each monitoring area and the light radiation standard threshold. If the light radiation data is within the light radiation standard threshold, control the light radiation technology energy-saving dehumidification device to perform the anti-condensation dehumidification task and execute step S323. If the light radiation data does not meet the light radiation standard threshold, control other intelligent adjustment devices to perform the anti-condensation dehumidification task and execute step S324.

[0092] S323. After the light radiation technology energy-saving dehumidification device participates in the anti-condensation dehumidification task, if the humidity data in the monitoring area exceeds the upper limit of the humidity standard threshold, the condensing dehumidifier is started to realize linkage and reduce the indoor humidity of the distribution room. If the temperature data in the monitoring area exceeds the temperature standard threshold, the air conditioner is started to realize linkage and adjust the indoor temperature. If the air flow rate data in the monitoring area does not meet the flow rate standard threshold, the fan is started to realize linkage and adjust the indoor air flow rate.

[0093] S324. Disable the light radiation technology energy-saving dehumidification device, start the condensing dehumidifier, and reduce the indoor humidity in the distribution room. If the temperature data in the monitoring area exceeds the temperature standard threshold, start the air conditioner to achieve linkage and adjust the indoor temperature. If the air flow rate data in the monitoring area does not meet the flow rate standard threshold, start the fan to achieve linkage and adjust the indoor air flow rate.

[0094] Specifically, the execution logic and operation steps of the above step S32 can be summarized as follows:

[0095] 1. Humidity warning judgment (S321)

[0096] Logic: Based on the monitoring area divided by the digital model, the current humidity data is compared with the humidity standard threshold to determine whether dehumidification is required.

[0097] Operation: If the humidity data does not exceed the standard threshold (for example, the threshold is 60%, and the current humidity is 55%), the device does not operate. If the humidity data exceeds the standard threshold (for example, the threshold is 60%, and the current humidity is 65%), it enters the warning state and gives priority to efficient intelligent adjustment equipment.

[0098] 2. Light radiation data judgment (S322)

[0099] Logic: Determine whether the light radiation technology energy-saving dehumidification device is suitable for operation under current environmental conditions.

[0100] Operation: If the light radiation data is within the standard threshold range (for example, the threshold is 30-70%, currently 50%), the light radiation dehumidification device is controlled to operate; if the light radiation data exceeds the range (for example, the threshold is 30-70%, currently 80%), turn to other equipment (such as condensing dehumidifier or air conditioner).

[0101] 3. Optical radiation device linkage (S323)

[0102] Logic: If the light radiation device is activated but the humidity, temperature or flow rate is still abnormal, other devices will be linked to assist in operation.

[0103] Operation: If the humidity exceeds the upper limit (such as over 80%), start the condensing dehumidifier to further reduce the humidity; if the temperature exceeds the threshold (such as over 35°C), start the air conditioner to adjust the temperature; if the air flow rate is insufficient (such as less than 1m / s), start the fan to improve air circulation efficiency.

[0104] 4. Other equipment operation (S324)

[0105] Logic: When the light radiation device is not applicable, directly start other equipment (condensing dehumidifier, air conditioner, fan) to adjust the environment.

[0106] Operation: Disable the light radiation device and start the condensing dehumidifier to reduce the humidity; if the temperature exceeds the standard, activate the air conditioner for adjustment; if the flow rate is insufficient, activate the fan to optimize air circulation.

[0107] Examples

[0108] Scenario 1: Humidity exceeds the limit, but light radiation is applicable.

[0109] The current humidity in the area is 70% (higher than the 60% threshold), and the system enters a warning state. The light radiation data is 50% (within the range of 30-70%), and the light radiation energy-saving dehumidification device is activated. As the humidity drops to 58%, the device automatically shuts down.

[0110] Scenario 2: Humidity and temperature exceed the standards and light radiation is not applicable.

[0111] The current humidity is 75% (above the 60% threshold), the temperature is 38°C (above the 35°C threshold), and the light radiation data is 80% (outside the threshold range). The light radiation device is unavailable, so the condensing dehumidifier is activated to reduce the humidity, and the air conditioner is activated to reduce the temperature. After retesting, the humidity drops to 62% and the temperature drops to 34°C. When these standards are met, the equipment shuts down.

[0112] Scenario 3: Insufficient air flow rate after the optical radiation device is in operation.

[0113] The light radiation data was 40% and the humidity was 65%, so the light radiation energy-saving dehumidification device was started; the humidity dropped to 58%, but the flow rate was 0.5m / s (lower than the 1m / s threshold), so the fan was started; after the fan was running, the flow rate increased to 1.2m / s, finally meeting the standard.

[0114] The core of the entire process is to use real-time monitoring data to compare with thresholds, call different devices according to priority, ensure that the equipment with the lowest energy consumption is used to complete the anti-condensation and dehumidification tasks, and at the same time link other equipment to optimize the effects, so as to achieve dynamic control of the environment in the distribution room and energy-saving and efficient operation.

[0115] S33. Obtain the judgment result of the environmental data, mark the monitoring area that exceeds the standard threshold, and mark the abnormal level of the monitoring area according to the amount of environmental data that exceeds the standard threshold.

[0116] Specifically,

[0117] Compare environmental data with standard thresholds and set standard threshold ranges for various types of environmental data, for example:

[0118] Humidity threshold: 30%~60%;

[0119] Temperature threshold: 15°C~35°C;

[0120] Light radiation threshold: 30%~70%;

[0121] Flow rate threshold: 1m / s~3m / s.

[0122] Compare each monitoring area's environmental data with the corresponding thresholds one by one to determine whether the data exceeds the range. Record the type of data and the extent of each exceeding standard, and generate an exceeding standard information table, for example:

[0123] Area A: Humidity = 70% (exceeding the standard by +10%), Temperature = 36°C (exceeding the standard by +1°C);

[0124] Area B: Humidity = 55% (normal), Temperature = 32°C (normal).

[0125] According to the number of exceeding data in each monitoring area, the abnormality level is divided into multiple levels, for example:

[0126] No abnormality (0 level): no any data exceeds the standard;

[0127] Mild abnormality (1 level): the number of exceeding data = 1;

[0128] Moderate abnormality (2 level): the number of exceeding data = 2;

[0129] Severe abnormality (3 level): the number of exceeding data is greater than or equal to 3.

[0130] By the spatiotemporal distribution of the digital model, the abnormality level of each monitoring area is marked; the state of the area is intuitively displayed by using color or other marking methods:

[0131] No abnormality: green;

[0132] Mild abnormality: yellow;

[0133] Moderate abnormality: orange;

[0134] Severe abnormality: red.

[0135] S4, real-time monitoring of temperature and humidity changes in the dehumidification process of the power distribution room, setting the optimal equipment energy efficiency and dehumidification performance as the optimization target, creating an energy-saving control model, adjusting the control parameters of different intelligent regulation devices in each monitoring area, and optimizing the execution effect of the anti-condensation dehumidification task.

[0136] In the description of the application, real-time monitoring of temperature and humidity changes in the dehumidification process of the power distribution room, setting the optimal equipment energy efficiency and dehumidification performance as the optimization target, creating an energy-saving control model, adjusting the control parameters of different intelligent regulation devices in each monitoring area, and optimizing the execution effect of the anti-condensation dehumidification task include the following steps:

[0137] S41, set the sampling frequency, regularly obtain the environmental data and device state data in the process of the intelligent regulation device executing the anti-condensation dehumidification task, and form a time series combined with the time stamp information.

[0138] S42, set the input variables and output variables, maximize the humidity reduction rate under unit power consumption as the optimal equipment energy efficiency, maximize the humidity reduction effect in the power distribution room as the optimal dehumidification performance, and establish an energy-saving control model for the intelligent regulation device executing the anti-condensation dehumidification task.

[0139] In the description of the application, setting the input variables and output variables, maximizing the humidity reduction rate under unit power consumption as the optimal equipment energy efficiency, maximizing the humidity reduction effect in the power distribution room as the optimal dehumidification performance, and establishing an energy-saving control model for the intelligent regulation device executing the anti-condensation dehumidification task include the following steps:

[0140] S421. Set the humidity data, temperature data, air flow rate data, light radiation data and real-time power consumption of the distribution room as input variables, and set the equipment energy efficiency, humidity change rate and total energy consumption as output variables.

[0141] S422. Taking maximizing the humidity reduction rate per unit power consumption and maximizing the humidity reduction effect in the distribution room as optimization goals, establish the objective function of the anti-condensation and dehumidification task in the distribution room, and independently calculate the sub-objective functions of the local equipment energy consumption and humidity reduction effect according to the monitoring area.

[0142] In the description of the present invention, the expression of the objective function is:

[0143]

[0144] Where, MaximszeJ represents the objective function; Δ RH Indicates the rate of change of humidity; Pi Indicates the i Real-time power consumption of intelligently regulated devices; N Indicates the number of intelligent adjustment devices; w 1. w 2 represents the weight coefficient.

[0145] S423. Based on the historical operating data of various types of intelligent regulating equipment, a mathematical model is established between the energy consumption of the intelligent regulating equipment and the humidity reduction rate. According to the pre-set dehumidification task standards of the distribution room, the constraint conditions of the anti-condensation dehumidification task are set, and the energy-saving control model of the distribution room is constructed in an integrated manner.

[0146] S43. Use the distributed particle swarm optimization algorithm to solve the energy-saving control model, output the optimal control strategy, and adjust and optimize the control parameters of the intelligent control equipment according to the optimal control strategy.

[0147] Specifically, the distributed particle swarm optimization algorithm (PSODE algorithm) is an optimization algorithm that combines the particle swarm optimization algorithm (PSO) with the differential evolution algorithm (DE). It is mainly used to solve the global optimization requirements in complex problems, especially multi-objective optimization problems.

[0148] The Particle Swarm Optimization (PSO) algorithm simulates the foraging behavior of flocks of birds, using multiple "particles" to move through a search space to find the optimal solution. It is simple, easy to implement, and computationally fast, making it suitable for continuous optimization problems. However, it is prone to getting stuck in local optima, especially when optimizing complex, multimodal functions.

[0149] Differential evolution (DE) is a population-based evolutionary strategy that uses differential vectors between individuals in a population to generate new solutions. It has strong global search capabilities and performs well for discrete and complex optimization problems. However, it has a slow convergence rate and can be computationally complex for high-dimensional optimization problems.

[0150] Therefore, the fast convergence characteristics of PSO are combined with the global search ability of DE, and the mutation, crossover and selection mechanisms of DE are introduced into the particle search strategy of PSO to enhance the diversity of the population, avoid falling into local optimality, and improve the convergence speed.

[0151] In complex multi-objective optimization problems, PSO particles tend to concentrate in localized areas of the search space, making it impossible to find the global optimal solution. Introducing DE's mutation operation can break this "stagnation" state and, by generating new individual positions, expand the search range and improve global search capabilities.

[0152] In this paper, energy-saving control models typically involve multiple objectives (such as humidity reduction and energy efficiency). PSODE, through the global search capabilities of DE, can balance the relationships between these multiple objectives. Environmental data in distribution rooms changes dynamically, and the relationship between equipment control parameters and environmental data is complex and nonlinear. PSODE can effectively handle such nonlinear constraints. The optimization objective function in energy-saving control models may have multiple local optimal solutions. PSODE, through the DE's mutation mechanism, broadens the search scope and helps find the global optimal solution.

[0153] In the description of the present invention, using a distributed particle swarm optimization algorithm to solve an energy-saving control model and output an optimal control strategy, adjusting and optimizing the control parameters of the intelligent control device according to the optimal control strategy includes the following steps:

[0154] S431. Initialize a particle swarm based on the real-time environmental data and equipment status data collected from each monitoring area in the power distribution room. Each particle represents a type of data combination. Randomly select n particles from the particle swarm and evenly divide them into a particle group and a difference group. The two groups of particles are distributed in different areas.

[0155] S432. Set the parameters of the particle swarm optimization algorithm and the differential evolution algorithm, calculate the fitness value of the current particle individual, and find the optimal particle individual in the particle group and the differential group, marking them as the optimal particle individual and the optimal differential individual respectively.

[0156] S433. Select the optimal particle individual from the optimal particle individual and the optimal differential individual. If the number of iterations reaches the maximum value, stop the operation and use the optimal particle individual as the optimal control strategy. If the number of iterations does not reach the maximum value, execute step S434.

[0157] S434. Use the best particle individual among the best particle individual and the best differential individual to replace the best particle individual in the particle group and the differential group, to generate a new generation of particle group and differential group.

[0158] S435. Using a particle swarm optimization algorithm to update the positions and velocities of individual particles in the particle group, using a differential evolution algorithm to perform hybridization and selection on the individuals in the differential group, and updating the differential group.

[0159] S436. During the iteration process, determine whether there is stagnation in the individuals in the group. If so, use the position update formula to mutate the individuals and obtain the latest positions of the individuals.

[0160] S437. Return to step S432 and continue until the iteration ends.

[0161] In the description of the present invention, the location update formula is:

[0162]

[0163] Where, express t +1 individual in iteration k location; A min represents the best position for individual search; A max - A min Indicates the boundary range within which the search is allowed; rand (0, 1) represents a random number generated in the interval [0, 1].

[0164] S5. Real-time monitoring of the dehumidification effect and equipment status data of each monitoring area in the distribution room. When there is equipment failure or abnormal operation, fault warning and maintenance response are triggered.

[0165] Specifically, each device is equipped with a status detection module, and data is aggregated to a central control platform via a communication gateway. This allows real-time monitoring of the operating status of intelligent regulation devices (power, start / stop status, and operating hours). Fault detection parameters (such as current overload, voltage anomaly, and overtemperature) are also monitored.

[0166] Compare environmental data (humidity, temperature, etc.) to preset standard thresholds in real time. If the humidity value does not fall within the target range, the dehumidification effect in the current area is determined to be abnormal. Determine whether device parameters exceed the operating range (such as power overload or excessive current). Detect whether the device operating status deviates from normal operating conditions (such as insufficient output power or frequent device startup and shutdown).

[0167] In summary, by virtue of the technical scheme of the present application, the integration of the light radiation energy-saving dehumidification device and the dynamic environment control system realizes a major breakthrough in the environmental control of the power distribution room; not only the temperature and humidity changes are accurately controlled through distributed hoisting and intelligent adjustment, but also the equipment is intelligently adjusted according to actual needs to ensure that the environmental data is maintained in an ideal range, realizing accurate control; at the same time, the dynamic environment control system can respond to changes in environmental data in real time, quickly trigger the execution equipment, and significantly enhance the environmental response speed; in addition, the comprehensive application of the light radiation energy-saving dehumidification device, the fan and the condensing dehumidifier and other efficient equipment, combined with intelligent closed-loop control, greatly improves the cooling and dehumidification effect in the power distribution room, providing more stable and reliable environmental protection for power distribution equipment; therefore, the present application effectively improves the intelligence and efficiency of the environmental control of the power distribution room, ensuring the safe and stable operation of the power system. By dividing the monitoring area and deploying environmental monitoring sensors and intelligent adjustment equipment, combined with the Internet of Things and node communication technology, abnormal areas can be monitored and accurately identified in real time, and the coordinated operation of various intelligent adjustment equipment is dynamically controlled, realizing efficient and anti-condensation dehumidification; at the same time, based on the energy-saving regulation and control model, the equipment operation parameters are optimized, with the optimal energy efficiency and dehumidification performance as the target, to effectively reduce energy consumption; in addition, through real-time fault monitoring and maintenance response, the safety and reliability of equipment operation are ensured. The overall scheme has high intelligence and significant energy-saving effect, and can meet the anti-condensation dehumidification needs of the power distribution room in complex environments.

[0168] It should be understood that although each step in the flowchart of the accompanying drawings is shown in sequence according to the direction of the arrow, these steps are not necessarily executed in sequence according to the direction of the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and they can be executed in other orders. Moreover, at least part of the steps in the flowchart of the accompanying drawings can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence is not necessarily sequential, but can be alternately or alternately executed with at least part of other steps or sub-steps or stages of other steps.

Claims

1. A method for preventing condensation and dehumidification in a power distribution room using a light radiation technology energy-saving dehumidification device, characterized in that: The method comprises the following steps: S1. Divide the power distribution room into several monitoring areas, install environmental monitoring sensors and intelligent adjustment equipment in the monitoring areas, configure communication gateways, and build a local communication network; S2. Based on the Internet of Things and node communication technologies, a dynamic environmental control system integrating distributed environmental monitoring sensors and intelligent control equipment is constructed to monitor and collect environmental data and equipment status data from each monitoring area in the power distribution room in real time, and to establish a digital model that includes temporal and spatial characteristics. S3: Based on the preset dehumidification task standard for the power distribution room, the system compares the currently monitored environmental data, identifies the monitoring areas with abnormalities, and controls the intelligent adjustment equipment to perform the anti-condensation dehumidification task; S4. Real-time monitoring of temperature and humidity changes during the dehumidification process in the power distribution room. Optimization targets are set for optimal equipment energy efficiency and dehumidification performance. Energy-saving control models are created to adjust the control parameters of different intelligent control devices within each monitoring area to optimize the performance of anti-condensation and dehumidification tasks. S5. Real-time monitoring of the dehumidification effect and equipment status data of each monitoring area in the power distribution room. When there is equipment failure or abnormal operation, fault warning and maintenance response are triggered; Wherein, step S4 comprises the following steps: S41. Set a sampling frequency to regularly obtain environmental data and device status data of the intelligent regulating device during the execution of the anti-condensation and dehumidification task, and combine the data with the timestamp information to form a time series. S42. Set input variables and output variables, set the optimal equipment energy efficiency by maximizing the humidity reduction rate per unit power consumption, set the optimal dehumidification performance by maximizing the humidity reduction effect in the power distribution room, and establish an energy-saving control model for the intelligent control equipment to perform anti-condensation dehumidification tasks; S43, using a distributed particle swarm optimization algorithm to solve the energy-saving control model, output an optimal control strategy, and adjust and optimize the control parameters of the intelligent control device according to the optimal control strategy; Step S3 includes the following steps: S31. Based on the actual operating requirements and equipment performance of the power distribution room, set standard thresholds for various types of environmental data. Combined with the hierarchical response of the intelligent adjustment equipment, establish the dehumidification task standards for the power distribution room. S32. Based on the spatiotemporal distribution of the digital model, the environmental data collected in real time is compared with the corresponding standard threshold value to determine whether the intelligent adjustment device meets the execution conditions, and the corresponding intelligent adjustment device is selected to perform the anti-condensation and dehumidification task; S33, obtaining the judgment result of the environmental data, marking the monitoring area that exceeds the standard threshold, and marking the abnormal level of the monitoring area according to the amount of environmental data that exceeds the standard threshold; Step S32 includes the following steps: S321. Based on the spatial distribution of the digital model, the humidity data in each monitoring area is preferentially compared with the humidity standard threshold. If the humidity data does not exceed the humidity standard threshold, the anti-condensation dehumidification task is not performed. If the humidity data exceeds the humidity standard threshold, the system enters a warning state and selects the corresponding intelligent adjustment device according to the priority, and executes step S322. S322. Compare the light radiation data in each monitoring area with the light radiation standard threshold. If the light radiation data is within the light radiation standard threshold, control the light radiation technology energy-saving dehumidification device to perform the anti-condensation dehumidification task, and execute step S323. If the light radiation data does not meet the light radiation standard threshold, control other intelligent adjustment devices to perform the anti-condensation dehumidification task, and execute step S324. S323. After the optical radiation technology energy-saving dehumidification device participates in the anti-condensation dehumidification task, if the humidity data in the monitoring area exceeds the upper limit of the humidity standard threshold, the condensing dehumidifier is activated to realize linkage and reduce the indoor humidity of the power distribution room. If the temperature data in the monitoring area exceeds the temperature standard threshold, the air conditioner is activated to realize linkage and adjust the indoor temperature. If the air flow rate data in the monitoring area does not meet the flow rate standard threshold, the fan is activated to realize linkage and adjust the indoor air flow rate. S324. Disable the light radiation technology energy-saving dehumidification device, start the condensing dehumidifier, and reduce the indoor humidity in the distribution room. If the temperature data in the monitoring area exceeds the temperature standard threshold, start the air conditioner to achieve linkage and adjust the indoor temperature. If the air flow rate data in the monitoring area does not meet the flow rate standard threshold, start the fan to achieve linkage and adjust the indoor air flow rate.

2. The anti-condensation dehumidification method for a power distribution room using a light radiation technology energy-saving dehumidification device according to claim 1, characterized in that: Step S1 includes the following steps: S11. Divide the power distribution room into different types of monitoring areas based on the spatial layout of the power distribution room, the density of electromechanical equipment, and the dehumidification requirements of the equipment. The monitoring areas include a main machine room area, an auxiliary area, a conditioning equipment area, and a monitoring area. S12. Distributedly install environmental monitoring sensors in the monitoring area to ensure that the monitoring range covers the entire space of the power distribution room, and the environmental monitoring sensors include temperature sensors, humidity sensors, light radiation sensors, air flow rate sensors and energy consumption sensors; S13, installing intelligent regulating equipment at corresponding locations within the monitoring area, wherein the intelligent regulating equipment includes a light radiation technology energy-saving dehumidification device, a fan, an air conditioner, and a condensing dehumidifier; S14. Set the environmental monitoring sensor as a communication node, configure a communication gateway in the monitoring area, configure the communication protocol, build a local communication network, use the communication gateway to perform data aggregation and command forwarding, and realize the coordinated work of each of the intelligent adjustment devices.

3. The anti-condensation dehumidification method for a power distribution room using a light radiation technology energy-saving dehumidification device according to claim 1, characterized in that: Step S2 includes the following steps: S21. Based on the Internet of Things and node communication technology, build a multi-layer integrated Internet of Things architecture to form a dynamic environment control system to manage environmental monitoring sensors and intelligent adjustment equipment; S22. Using environmental monitoring sensors to collect real-time environmental data from each monitoring area, including temperature data, humidity data, light radiation data, air flow rate data, and equipment energy consumption data, and monitoring equipment status data fed back during the operation of the intelligent regulating equipment; S23, performing data preprocessing on the collected environmental data and device status data, and integrating the environmental data into a multidimensional spatiotemporal data set based on timestamp and spatial location information; S24. Establish a digital model based on the spatial layout of the power distribution room, map the spatiotemporal dataset into the three-dimensional space of the digital model, and generate a visualization model that dynamically displays changes in environmental data.

4. The anti-condensation dehumidification method for a power distribution room using a light radiation technology energy-saving dehumidification device according to claim 3, characterized in that: The dynamic environment control system includes a perception layer, a network layer, an application layer and a response layer; wherein, the perception layer includes distributed environmental monitoring sensors for real-time collection of environmental data, the network layer includes a local area communication network established by a communication gateway, the application layer includes a dynamic environment control center for data processing, equipment control, three-dimensional modeling and visualization, and the response layer includes a number of intelligent adjustment devices.

5. The anti-condensation dehumidification method for a power distribution room using a light radiation technology energy-saving dehumidification device according to claim 1, characterized in that: Step S42 includes the following steps: S421. Set the power distribution room humidity data, temperature data, air flow rate data, light radiation data, and real-time power consumption of the intelligent control device as input variables, and set the device energy efficiency, humidity change rate, and total energy consumption as output variables; S422. Maximizing the humidity reduction rate per unit power consumption and maximizing the humidity reduction effect in the power distribution room are optimization goals. An objective function for the power distribution room anti-condensation and dehumidification task is established, and sub-objective functions for local equipment energy consumption and humidity reduction effect are independently calculated for each monitoring area. S423. Based on the historical operating data of various types of intelligent regulating equipment, a mathematical model is established between the energy consumption of the intelligent regulating equipment and the humidity reduction rate. According to the pre-set dehumidification task standards of the distribution room, the constraint conditions of the anti-condensation dehumidification task are set, and the energy-saving control model of the distribution room is constructed in an integrated manner.

6. The anti-condensation dehumidification method for a power distribution room using a light radiation technology energy-saving dehumidification device according to claim 5, characterized in that: The expression of the objective function is: Where, Maximsze J represents the objective function; Δ RH Indicates the rate of change of humidity; Pi Indicates the i Real-time power consumption of intelligently regulated devices; N Indicates the number of intelligent adjustment devices; w 1. w 2 represents the weight coefficient.

7. The anti-condensation dehumidification method for a power distribution room using a light radiation technology energy-saving dehumidification device according to claim 5, characterized in that: Step S43 includes the following steps: S431. Initialize a particle swarm based on the real-time environmental data and equipment status data collected from each monitoring area in the power distribution room. Each particle represents a data combination. Randomly select n particles from the particle swarm and evenly divide them into a particle group and a difference group. The two groups of particles are distributed in different areas. S432. Setting the parameters of the particle swarm optimization algorithm and the differential evolution algorithm, calculating the fitness value of the current individual particle, and searching for the optimal individual particle in the particle swarm and the differential swarm, marking them as the optimal individual particle and the optimal differential individual, respectively; S433, selecting the optimal particle individual from the optimal particle individual and the optimal differential individual. If the number of iterations reaches the maximum value, the operation is stopped, and the optimal particle individual is used as the optimal control strategy. If the number of iterations does not reach the maximum value, step S434 is executed; S434, using the best particle individual among the best particle individual and the best difference individual to replace the best particle individual in the particle group and the difference group, to generate a new generation of particle group and difference group; S435, using a particle swarm optimization algorithm to update the positions and velocities of individual particles in the particle group, using a differential evolution algorithm to perform hybridization and selection on the individuals in the differential group, and updating the differential group; S436. During the iteration process, determine whether there is stagnation in the individuals in the group. If so, use the position update formula to mutate the individuals and obtain the latest positions of the individuals. S437. Return to step S432 and continue until the iteration ends.

8. The anti-condensation dehumidification method for a power distribution room using a light radiation technology energy-saving dehumidification device according to claim 7, characterized in that: The position update formula is: Where, express t +1 individual in iteration k location; A min represents the best position for individual search; A max - A min Indicates the boundary range within which the search is allowed; rand (0, 1) represents a random number generated in the interval [0, 1].

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