High-voltage switch cabinet anti-condensation device considering meteorological data characteristics

Abstract

The invention discloses a high-voltage switch cabinet anti-condensation device considering meteorological data characteristics, which relates to the technical field of high-voltage switch cabinet protection and comprises a meteorological data acquisition module, a meteorological data prediction module and the like. The meteorological data acquisition module acquires internal and external temperature and humidity and meteorological station forecast data to generate a multi-source data set; the meteorological data prediction module outputs a temperature and humidity time curve by using an ARIMA model; the temperature and humidity sensing modules are distributed in each bin of the switch cabinet to collect and transmit data; the climate compensation curve generation module generates a temperature-water vapor saturation climate compensation curve; the driving control module adjusts the exhaust fan and the heater through a PID algorithm; the air circulation optimization module constructs a forced convection path. In addition, a data storage and fault diagnosis unit is further arranged. The device can accurately control the temperature and humidity, effectively prevents condensation, improves the operation safety and reliability of the high-voltage switch cabinet, and reduces the maintenance cost.

Description

Technical Field

[0001] This application relates to the field of high-voltage switchgear protection technology, specifically a high-voltage switchgear anti-condensation device that takes into account meteorological data characteristics. Background Technology

[0002] In power systems, high-voltage switchgear is a key piece of equipment for power transmission and distribution, and its operational stability and reliability are of paramount importance. However, condensation has always been a major challenge affecting the normal operation of high-voltage switchgear.

[0003] Condensation formation is closely related to ambient temperature and humidity. In areas with high humidity, especially during the rainy season or when there are large temperature differences between day and night, condensation is very likely to occur inside high-voltage switchgear. When the temperature inside the switchgear drops below the dew point, water vapor in the air condenses into water droplets, adhering to the surfaces of electrical components, busbars, insulators, and other equipment inside the switchgear. These water droplets reduce the insulation performance of electrical equipment, causing creepage and flashover faults, seriously threatening the safe operation of the power system. According to incomplete statistics, high-voltage switchgear faults caused by condensation account for a considerable proportion of power equipment faults, not only causing power outages and affecting the continuity of power supply, but also potentially leading to equipment damage and huge economic losses.

[0004] Traditional anti-condensation measures for high-voltage switchgear are relatively simple. A common method is to install heaters inside the switchgear to increase the internal temperature and reduce relative humidity, thereby minimizing condensation. However, this method has significant limitations. First, the heater's power is fixed and cannot be flexibly adjusted according to actual temperature and humidity changes, potentially leading to overheating or underheating. Overheating not only wastes energy but may also accelerate equipment aging; underheating fails to effectively prevent condensation. Second, relying solely on heating cannot solve the air circulation problem; uneven humidity distribution within the switchgear still poses a risk of localized condensation.

[0005] Some switchgear cabinets use ventilation to reduce humidity, that is, by installing exhaust fans to expel humid air outside the cabinet. However, this method also lacks specificity. When the humidity is high and the outside air humidity is also high, ventilation may not achieve the desired effect, and may even introduce more moisture. Moreover, the start and stop control of exhaust fans often does not take into account changes in meteorological data, and cannot intelligently adjust according to changes in environmental conditions.

[0006] With increasingly complex and variable meteorological conditions and ever-increasing reliability requirements of power systems, existing anti-condensation methods are no longer sufficient to meet the operational needs of high-voltage switchgear. Therefore, developing an anti-condensation device for high-voltage switchgear that can take meteorological data characteristics into account, precisely control temperature and humidity, and effectively prevent condensation is of significant practical importance. This can not only improve the safety and stability of the power system and ensure the reliability of power supply, but also reduce equipment maintenance costs, extend equipment lifespan, and provide strong support for the sustainable development of the power industry. Summary of the Invention

[0007] This application provides a high-voltage switchgear anti-condensation device that takes into account meteorological data characteristics to solve the above-mentioned problems.

[0008] On the one hand, this application provides a high-voltage switchgear anti-condensation device that takes into account meteorological data characteristics, the device comprising: The meteorological data acquisition module is used to acquire real-time temperature and humidity data inside and outside the high-voltage switchgear, and generate multi-source meteorological datasets by combining the forecast data from the meteorological station. The meteorological data prediction module preprocesses and predicts the multi-source meteorological dataset based on a time series analysis model, and outputs temperature-time curves and humidity-time curves for future time periods. The temperature and humidity sensing module includes multiple temperature and humidity sensors distributed in the rear, middle and front compartments of the high-voltage switchgear, which are used to collect temperature and humidity data of each zone in real time and transmit them to the intelligent control module. The climate compensation curve generation module dynamically generates a temperature-water vapor saturation climate compensation curve based on the temperature-time curve and humidity-time curve, combined with the dew point temperature-time relationship and the saturation humidity-time relationship. The drive control module receives the set threshold of the climate compensation curve and dynamically adjusts the start-up, shutdown and power output of the exhaust fan and heater through a PID algorithm. The air circulation optimization module constructs a forced convection path through the layout of exhaust fans at the bottom of the high-voltage switchgear rear compartment, top exhaust vents, and distributed heaters, achieving uniform distribution of dry air.

[0009] Preferably, the meteorological data acquisition module includes: Temperature, humidity and barometric pressure sensors collect real-time data in 5-minute intervals. The data preprocessing unit amplifies, filters, and performs analog-to-digital conversion on the acquired analog signals to generate standardized digital signals. The meteorological data fusion unit performs time alignment and spatial interpolation fusion of real-time data and meteorological station forecast data.

[0010] Preferably, the meteorological data prediction module uses the ARIMA model to predict meteorological data, including: The outlier removal unit removes noise points from the data using the 3σ criterion. The standardized processing unit uses the Z-score standardization method to normalize the data; The prediction model training unit builds a time series model based on historical data and updates the model parameters using the sliding window method.

[0011] Preferably, the layout of the temperature and humidity sensing module includes: Two temperature and humidity sensors are installed at the bottom of the rear compartment, and one temperature and humidity sensor is installed at the top of each of the middle and front compartments; Sensor data is transmitted to the intelligent control module via RS-485 bus, and CRC check is used to ensure data integrity.

[0012] Preferably, the PID algorithm of the drive control module includes: The input error calculation unit generates an error signal based on the difference between the real-time temperature and humidity and the threshold of the climate compensation curve; The proportional-integral-derivative control unit adjusts the proportional coefficient. Integral Time and differential time Dynamically optimize control response; The output limiting unit limits the heater power and exhaust fan speed to prevent overload. The PID control output formula is as follows:

[0013] In the formula, This is a real-time error signal. To control the output.

[0014] Preferably, the climate compensation curve generation module generates the curve through the following steps: Establish a mapping relationship between dew point temperature and saturated humidity based on the enthalpy-humidity diagram of moist air; By combining the temperature-time curve and the humidity-time curve, the critical value of water vapor saturation at each moment in the future time period is calculated. Generate piecewise linear compensation curves and discretize the curves into a time-threshold lookup table; The critical value of water vapor saturation is calculated using the following formula:

[0015] In the formula, This is the critical value for water vapor saturation. The saturated vapor pressure at the current temperature. This is the saturated water vapor pressure at the dew point temperature.

[0016] Preferably, the forced convection path design of the air circulation optimization module includes: Two axial flow exhaust fans are installed at the bottom of the rear compartment, and anti-backflow exhaust vents are opened at the top; A centrifugal exhaust fan is installed on the top of both the middle and front compartments, forming a series airflow with the exhaust fan in the rear compartment; The heater uses PTC ceramic heating elements, which are distributed on the side wall of the rear compartment and the top of the front compartment, and improves drying efficiency through a combination of thermal radiation and convection.

[0017] Preferably, the parameter optimization method for the ARIMA model includes: The model order (p, d, q) is determined by the autocorrelation function ACF and the partial autocorrelation function PACF. The optimal combination is found in the preset parameter space using the grid search method, and the model fit is evaluated by the AIC criterion.

[0018] Preferably, the device further includes: The data storage module is used to cache historical meteorological data and control command logs; The fault diagnosis unit identifies abnormalities such as exhaust fan blockage or heater failure by comparing sensor data with equipment operating status.

[0019] Preferably, the speed control strategy of the exhaust fan includes: Based on the pressure sensor data inside the cabinet, a fuzzy logic algorithm is used to dynamically adjust the exhaust fan speed; When the pressure inside the cabinet is higher than the set threshold, the high-speed mode is activated; when the pressure is lower than the threshold, the low-speed energy-saving mode is switched. The output speed adjustment amount of the fuzzy logic is calculated using the following formula:

[0020] In the formula, Exhaust fan speed adjustment amount For the first The activation degree of a fuzzy rule. For the first The control quantity of a fuzzy rule.

[0021] Compared with the prior art, the beneficial effects of the present invention are: In terms of data acquisition and forecasting, the meteorological data acquisition module obtains real-time temperature and humidity data from both inside and outside the high-voltage switchgear, and generates a multi-source meteorological dataset by combining it with weather station forecast data. High-frequency acquisition with a 5-minute cycle and refined processing of analog signals by the data preprocessing unit ensure the accuracy and timeliness of the acquired data. The meteorological data fusion unit performs time alignment and spatial interpolation fusion of real-time data and weather station forecast data, making the data more closely reflect the actual operating environment of the switchgear. The meteorological data forecasting module, based on a time series analysis model, uses the ARIMA model and updates model parameters through outlier removal, standardization, and a sliding window method, accurately outputting temperature-time and humidity-time curves for future time periods. This provides a reliable basis for subsequent anti-condensation control. Compared to traditional methods that rely solely on current environmental data for control, this invention can predict temperature and humidity trends in advance, enabling more proactive anti-condensation operations.

[0022] The temperature and humidity sensing module, through a rational layout of two temperature and humidity sensors installed at the bottom of the rear compartment of the high-voltage switchgear, and one temperature and humidity sensor each installed at the top of the middle and front compartments, can comprehensively and accurately collect temperature and humidity data from each zone. RS-485 bus transmission combined with CRC verification ensures the integrity of data transmission. The real-time temperature and humidity information obtained by the intelligent control module is accurate and reliable, avoiding control errors caused by data inaccuracies and thus improving the precision of anti-condensation control.

[0023] The climate compensation curve generation module establishes a mapping relationship between dew point temperature and saturated humidity based on the enthalpy-humidity diagram of moist air. It calculates the critical value of water vapor saturation by combining temperature-time and humidity-time curves, generating piecewise linear compensation curves and discretizing them into a time-threshold lookup table. This process fully considers the dynamic changes in meteorological data, enabling the generated climate compensation curves to more accurately reflect the temperature and humidity conditions required to prevent condensation at different times, providing a scientifically reasonable control threshold for the drive control module.

[0024] The drive control module receives the set threshold from the climate compensation curve and dynamically adjusts the start / stop and power output of the exhaust fan and heater using a PID algorithm. The input error calculation unit generates an error signal based on the difference between the real-time temperature and humidity and the climate compensation curve threshold. The proportional-integral-derivative control unit adjusts the proportional coefficient accordingly. Integral Time and differential time The dynamic optimization control response and output limiting unit set threshold limits for heater power and exhaust fan speed to prevent overload. This precise control method can adjust the equipment's operating status in a timely manner according to actual temperature and humidity deviations. Compared with traditional fixed-power heating or ventilation methods, it can effectively prevent condensation, avoid energy waste, improve energy efficiency, and ensure the safe and stable operation of the equipment.

[0025] The air circulation optimization module constructs a forced convection path by installing axial flow exhaust fans at the bottom of the rear compartment of the high-voltage switchgear, opening anti-backflow exhaust vents at the top, installing centrifugal exhaust fans at the top of the middle and front compartments to form a series airflow, and rationally distributing PTC ceramic heating elements. This design achieves uniform distribution of dry air within the switchgear, accelerates air circulation, and makes the temperature and humidity more uniform, further improving the anti-condensation effect. At the same time, the combination of heat radiation and convection from the PTC ceramic heating elements improves drying efficiency, reduces heating time, and lowers energy consumption.

[0026] In addition, the device includes a data storage module and a fault diagnosis unit. The data storage module caches historical meteorological data and control command logs, which helps in analyzing equipment operating patterns and optimizing control strategies. The fault diagnosis unit, by comparing sensor data with equipment operating status, can promptly identify abnormalities such as exhaust fan blockage or heater failure, facilitating timely maintenance and repair by staff and improving equipment reliability and maintainability. The exhaust fan speed control strategy is based on pressure sensor data inside the cabinet and uses a fuzzy logic algorithm to dynamically adjust the exhaust fan speed, achieving energy-saving operation while ensuring effective air circulation.

[0027] The high-voltage switchgear anti-condensation device provided in this application, which takes into account meteorological data characteristics, has the following beneficial effects: 1. This device uses a meteorological data acquisition and forecasting module, combined with the ARIMA model, to predict temperature and humidity change trends in advance, generate dynamic climate compensation curves, achieve proactive anti-condensation control, and improve the accuracy and timeliness of responding to environmental changes.

[0028] 2. The power of the exhaust fan and heater is dynamically adjusted by adopting the PID algorithm. Combined with the forced convection path design, energy waste and equipment overload are avoided. While effectively preventing condensation, energy efficiency is significantly improved and operating costs are reduced.

[0029] 3. The rational layout of multiple sensors and RS-485 bus transmission ensure data integrity and reliability. Combined with the fault diagnosis unit, the system can monitor the equipment status in real time, identify anomalies in a timely manner, enhance system reliability and maintainability, and extend equipment life. Attached Figure Description

[0030] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 A diagram of a high-voltage switchgear anti-condensation device considering meteorological data characteristics is provided for an embodiment of this application; Figure 2A schematic diagram of the working principle of a high-voltage switchgear anti-condensation device that takes into account meteorological data characteristics is provided in the embodiments of this application; Figure 3 A flowchart illustrating the operation of the temperature and humidity sensing module provided in this application embodiment; Figure 4 A flowchart illustrating the workflow of the climate compensation curve generation module provided in this application embodiment; Figure 5 A flowchart illustrating the steps for optimizing ARIMA model parameters in the embodiments of this application. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0032] This application provides a high-voltage switchgear anti-condensation device that takes into account meteorological data characteristics. The technical solution proposed in this application will be described in detail below with reference to the accompanying drawings.

[0033] Figure 1 This is a schematic diagram illustrating the working principle of a high-voltage switchgear anti-condensation device that takes into account meteorological data characteristics, provided as an embodiment of this application. Figure 1 As shown, the device includes: Meteorological Data Acquisition Module: This module is responsible for acquiring real-time temperature and humidity data inside and outside the high-voltage switchgear, and generating a multi-source meteorological dataset by combining it with weather station forecast data. Real-time data is collected every 5 minutes using temperature, humidity, and barometric pressure sensors deployed inside and outside the switchgear. The acquired analog signals are amplified, filtered, and converted from analog to digital by the data preprocessing unit to generate standardized digital signals. Then, the meteorological data fusion unit performs time alignment and spatial interpolation fusion with the weather station forecast data, providing a comprehensive and accurate data foundation for subsequent analysis and forecasting.

[0034] Meteorological data prediction module: Based on a time series analysis model, this module preprocesses and predicts multi-source meteorological datasets. First, an outlier removal unit removes noise points from the data according to the 3σ criterion to ensure data reliability. Next, a standardization unit normalizes the data using the Z-score standardization method. Then, a prediction model training unit builds a time series model based on historical data, employing the ARIMA model and updating model parameters using the sliding window method. Finally, it outputs temperature-time and humidity-time curves for future time periods. The ARIMA model parameter optimization process is as follows: Figure 5 As shown.

[0035] Temperature and humidity sensing module: This module includes multiple temperature and humidity sensors distributed in the rear, middle, and front compartments of the high-voltage switchgear. Specifically, two temperature and humidity sensors are installed at the bottom of the rear compartment, and one each at the top of the middle and front compartments. These sensors collect temperature and humidity data from each zone in real time and transmit it to the intelligent control module via an RS-485 bus. CRC checksums are used to ensure data integrity, allowing the intelligent control module to accurately monitor the temperature and humidity conditions in each area of ​​the switchgear. The workflow diagram of the temperature and humidity sensing module is shown below. Figure 3 As shown.

[0036] Climate Compensation Curve Generation Module: Based on the temperature-time and humidity-time curves output by the meteorological data prediction module, and combining the dew point temperature-time and saturation humidity-time relationships, a temperature-water vapor saturation climate compensation curve is dynamically generated. First, a mapping relationship between dew point temperature and saturation humidity is established based on the enthalpy-humidity diagram of moist air. Then, combining the temperature-time and humidity-time curves, the critical value of water vapor saturation at each moment in the future time period is calculated. Finally, a piecewise linear compensation curve is generated, and the curve is discretized into a time-threshold lookup table. The workflow of the climate compensation curve generation module is as follows: Figure 4 As shown.

[0037] Drive control module: Receives the set threshold output from the climate compensation curve generation module and dynamically adjusts the start / stop and power output of the exhaust fan and heater using a PID algorithm. This algorithm includes an input error calculation unit, which generates an error signal based on the difference between the real-time temperature and humidity and the climate compensation curve threshold; and a proportional-integral-derivative adjustment unit, which adjusts the proportional coefficient... Integral Time and differential time Dynamically optimize control response; output limiting unit to limit heater power and exhaust fan speed to prevent overload.

[0038] Air circulation optimization module: Two axial flow exhaust fans are installed at the bottom of the rear compartment of the high-voltage switchgear, and anti-backflow exhaust vents are opened at the top; a centrifugal exhaust fan is installed at the top of the middle compartment and the front compartment, forming a series airflow with the exhaust fan of the rear compartment; at the same time, in terms of heater layout, PTC ceramic heating elements are used, distributed on the side wall of the rear compartment and the top of the front compartment, which improves drying efficiency by combining heat radiation and convection, constructs a forced convection path, achieves uniform distribution of dry air, and effectively prevents condensation.

[0039] The working principle of the device composed of the above modules is as follows: Figure 2 As shown.

[0040] The present invention will be further described below with reference to Examples 1 to 6: Example 1: This embodiment details the implementation of the meteorological data acquisition module and the meteorological data prediction module. In the meteorological data acquisition module, temperature, humidity, and barometric pressure sensors collect data at fixed intervals of 5 minutes. Taking the temperature sensor as an example, it employs a high-precision thermistor sensor, capable of accurately sensing changes in ambient temperature, with a measurement range of -40℃ to 125℃ and an accuracy of ±0.2℃. The humidity sensor uses a capacitive humidity sensor, with a measurement range of 0%RH to 100%RH and an accuracy of ±3%RH. The analog signals acquired by these sensors are relatively weak and susceptible to external interference. Therefore, the data preprocessing unit first amplifies the analog signals using an operational amplifier to amplify them to a suitable amplitude range. Then, a filtering circuit removes high-frequency noise and low-frequency interference from the signal, such as 50Hz power frequency interference. Finally, analog-to-digital conversion is performed to convert the analog signal into a standardized digital signal that the microcontroller can recognize.

[0041] When fusing real-time data with weather station forecast data, the meteorological data fusion unit first performs time alignment. Since the collection times of weather station forecast data and field-collected data may differ, timestamp comparison is used to adjust the data to the same time reference. Next, spatial interpolation fusion is performed. Using Kriging interpolation, based on forecast data from surrounding weather stations, the meteorological data for the switchgear's location is estimated, ensuring that the fused data more accurately reflects the meteorological conditions of the switchgear's environment.

[0042] The meteorological data prediction module uses the ARIMA model. In the outlier removal unit, the 3σ criterion works by assuming the data follows a normal distribution; data points outside three standard deviations are considered outliers. Let the data sequence be... Its mean is The standard deviation is For data points ,like Then determine Outliers are identified and removed. The standardization process uses the Z-score standardization method, with the formula: ,in For standardized data, This is the original data. The mean of the original data. The standard deviation of the original data is used to normalize the data to an interval with a mean of 0 and a standard deviation of 1, which facilitates subsequent model processing.

[0043] In constructing an ARIMA model, determining the model order (p, d, q) is crucial. The model order is determined using the autocorrelation function (ACF) and partial autocorrelation function (PACF). The ACF measures the correlation between time series data across different time intervals, while the PACF measures the correlation between two variables after removing the influence of other intermediate variables. The values ​​of p and q are determined by observing the graphs of the ACF and PACF, with d representing the difference order, typically determined based on the stationarity of the data. After determining the initial order, a grid search method is used to find the optimal combination within a predefined parameter space. The predefined parameter space is determined based on experience and preliminary experiments; for example, the range of p is [0, 3], and the range of q is [0, 3]. The model fit is evaluated using the AIC criterion, the formula for which is: ,in This represents the maximum likelihood function value of the model. This represents the number of model parameters. A smaller AIC value indicates lower model complexity and better model performance while fitting the data. By continuously adjusting the parameters, the optimal ARIMA model is obtained, which is used to accurately predict future temperature and humidity data.

[0044] Example 2: The proper layout of temperature and humidity sensing modules is crucial for accurately monitoring the temperature and humidity conditions in various areas within the high-voltage switchgear. Two temperature and humidity sensors are installed at the bottom of the rear compartment because this area is typically where cables enter and exit; cables generate heat during operation, and this relatively enclosed area easily accumulates moisture. Installing two sensors allows for more comprehensive monitoring of temperature and humidity changes in this area. The sensors selected are the highly sensitive and stable SHT30 temperature and humidity sensors, with a temperature measurement accuracy of ±0.3℃ and a humidity measurement accuracy of ±2%RH. One temperature and humidity sensor is installed at the top of both the middle and front compartments. The middle compartment typically houses important equipment such as circuit breakers, while the front compartment contains control and protection devices. Installing sensors at the top effectively monitors the temperature and humidity above the equipment, preventing uneven temperature and humidity distribution caused by equipment heat from affecting measurement accuracy.

[0045] Data collected by the sensors is transmitted to the intelligent control module via an RS-485 bus. The RS-485 bus is a commonly used industrial communication bus with advantages such as strong anti-interference capability and long transmission distance. During transmission, CRC checksum is used to ensure data integrity. CRC checksum, or Cyclic Redundancy Check, works by generating a checksum at the sending end based on the data to be sent, appending it to the data before transmission. The receiving end recalculates the checksum based on the received data and compares it with the received checksum. If they match, it means the data transmission was error-free; if they do not match, the sending end is required to retransmit the data. The CRC checksum polynomial can be selected according to actual needs; for example, the commonly used CRC-16 polynomial is... This method effectively ensures that temperature and humidity data are accurately transmitted to the intelligent control module, providing a reliable basis for subsequent control decisions.

[0046] Example 3: The drive control module uses a PID algorithm to precisely control the exhaust fan and heater. In the input error calculation unit, real-time temperature and humidity data are transmitted from the temperature and humidity sensing module, and the climate compensation curve threshold is provided by the climate compensation curve generation module. Let the real-time temperature be... The corresponding temperature threshold in the climate compensation curve is Real-time humidity is The humidity threshold is Then the temperature error signal Humidity error signal .

[0047] The proportional-integral-derivative control unit adjusts based on the error signal. The proportional coefficient... This determines the controller's response speed to errors. The larger the value, the faster the response speed, but it may cause system overshoot; integral time Used to eliminate the steady-state error of a system, its function is to integrate the error; as time accumulates, the integral term gradually increases until the steady-state error is eliminated; differential time. The control input is adjusted in advance based on the rate of change of the error, thereby improving the dynamic performance of the system. The PID control output formula is: ,in Real-time error signal (which could be a temperature error signal) or humidity error signal ), To control the output, it is used to control the speed of the exhaust fan or the power of the heater.

[0048] The output limiting unit applies threshold limits to the heater power and exhaust fan speed. Taking the heater as an example, assuming its rated power is... When the PID algorithm calculates the heater power control quantity Exceed When, limit the output to ;when When the value is less than 0, the output is set to 0. For the exhaust fan, let its maximum speed be... The minimum speed is When the calculated exhaust fan speed control value Exceed At that time, set the exhaust fan speed to ;when Less than At that time, set the exhaust fan speed to This method effectively prevents overload of the heater and exhaust fan, ensuring the safe and stable operation of the equipment.

[0049] Example 4: The climate compensation curve generation module plays a crucial role in preventing condensation in high-voltage switchgear. First, a mapping relationship between dew point temperature and saturation humidity is established based on a humid air enthalpy-humidity diagram. The humid air enthalpy-humidity diagram is a line graph representing the relationship between various state parameters of humid air; on this diagram, there is a one-to-one correspondence between dew point temperature and saturation humidity. By consulting the enthalpy-humidity diagram or using relevant mathematical models, the saturation humidity values ​​at different dew point temperatures can be obtained.

[0050] By combining temperature-time and humidity-time curves, the critical values ​​of water vapor saturation at various points in the future time period are calculated. The calculation formula is as follows: ,in This is the critical value for water vapor saturation. The saturated vapor pressure at the current temperature. Let be the saturated vapor pressure at the dew point temperature. The relationship between saturated vapor pressure and temperature can be calculated using the Antoine equation, which is: ,in , , For water, the constants are related to the substance. , , , Temperature (unit: °C). The current temperature is obtained through a temperature-time curve. The dew point temperature is obtained by mapping the dew point temperature to the saturation humidity. Then, the critical value of water vapor saturation at each time point is calculated.

[0051] When generating piecewise linear compensation curves, the time axis is divided into multiple segments based on the calculated critical water vapor saturation value and practical application requirements. Within each segment, a linear compensation curve is generated using linear interpolation, with the critical water vapor saturation value as the ordinate and time as the abscissa. For example, in the time segment... Inside, known The critical value of water vapor saturation at time t is , The critical value of water vapor saturation at time t is Then the equation of the linear compensation curve during this time period is: ,in Finally, the curve is discretized into a time-threshold lookup table and stored in the memory of the intelligent control module for easy reading and use by the subsequent drive control module.

[0052] Example 5: The air circulation optimization module constructs a forced convection path through a rational layout of exhaust fans and heaters. Two axial-flow exhaust fans are installed at the bottom of the rear compartment. Axial-flow exhaust fans are characterized by large air volume and low air pressure, which can quickly expel humid air from the bottom of the rear compartment. The air volume of the exhaust fans can be selected according to the volume of the switch cabinet and actual needs. For example, for a volume of... For a switch cabinet with a capacity of cubic meters, based on the required air exchange rate (e.g., 6 air exchanges per hour), the total air volume of the exhaust fan is... Should meet cubic meters per minute. A backflow prevention vent is provided at the top to prevent outside air from flowing back into the switch cabinet when the exhaust fan is not operating. The vent uses a one-way valve structure; when the exhaust fan is operating, the internal pressure increases, the one-way valve opens, and air is discharged; when the exhaust fan stops operating, the one-way valve closes, preventing outside air from entering.

[0053] Centrifugal exhaust fans are installed on the top of both the middle and front compartments. These fans have high air pressure, effectively overcoming duct resistance and forming a series airflow with the exhaust fan in the rear compartment. The air exhausted by the rear compartment exhaust fan enters the middle and front compartments through the duct, where the centrifugal fans accelerate airflow, achieving air circulation throughout the entire switch cabinet.

[0054] The heaters utilize PTC ceramic heating elements, which offer advantages such as rapid heating and excellent temperature stability. These elements are distributed along the rear side walls and the front top. The heating elements on the rear side walls directly heat the air inside the rear compartment through thermal radiation, increasing the air temperature and reducing relative humidity. The heating elements on the front top of the front compartment distribute hot air to all corners of the front compartment through convection, improving drying efficiency. The heater placement is rationally planned based on the temperature distribution and power requirements within the switchgear to ensure a uniform temperature rise throughout the switchgear and effectively prevent condensation.

[0055] Example 6: This embodiment describes the device's data storage module, fault diagnosis unit, and exhaust fan speed control strategy. The data storage module uses a large-capacity Flash memory to cache historical meteorological data and control command logs. Historical meteorological data includes collected temperature, humidity, and air pressure data; the storage time can be set according to actual needs, such as storing data from the past year. This data is crucial for analyzing the long-term changing trends of the switchgear's environment and evaluating the operational effectiveness of the anti-condensation device. The control command log records the commands issued by the drive control module to control the exhaust fan and heater, including the command sending time and command content (such as start / stop of the exhaust fan, speed adjustment, heater power adjustment, etc.), facilitating traceability and troubleshooting in case of problems.

[0056] The fault diagnosis unit identifies anomalies by comparing sensor data with the equipment's operating status. For example, if the humidity data collected by the temperature and humidity sensor is consistently high, while the exhaust fan and heater are running, there may be a problem with the exhaust fan being blocked or the heater malfunctioning. Let the current during normal operation of the exhaust fan be... When the exhaust fan current is detected Less than If a certain percentage (e.g., 80%) of the surface temperature exceeds a set duration (e.g., 5 minutes), the exhaust fan is considered potentially blocked; for the heater, if its surface temperature... If the heater fails to reach the set temperature range after a period of normal operation (e.g., below 80% of the lower limit of the set temperature), it is determined that the heater may be malfunctioning.

[0057] The exhaust fan speed control strategy employs a fuzzy logic algorithm. Based on pressure sensor data inside the cabinet, when the pressure inside the cabinet exceeds a set threshold... When the pressure is below the threshold, the high-speed mode is activated; when the pressure is below the threshold, it switches to low-speed energy-saving mode. The output speed adjustment of the fuzzy logic is determined by the formula. Calculation, where This is the amount of adjustment for the exhaust fan speed. For the first The activation degree of a fuzzy rule. For the first The control quantity of a fuzzy rule. The fuzzy rule is determined based on practical experience and experimental data, such as when the pressure inside the cabinet... Slightly higher When, set , (This indicates an increase in rotational speed of 10 revolutions per minute); when pressure Much higher When, set , (This indicates an increase in rotation speed of 30 revolutions per minute), etc. Through this fuzzy logic algorithm, the exhaust fan speed can be dynamically adjusted in real time based on the pressure inside the cabinet, achieving energy-saving operation while ensuring effective air circulation.

[0058] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0059] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0060] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A high-voltage switchgear anti-condensation device taking into account meteorological data characteristics, characterized in that, Includes the following modules: The meteorological data acquisition module is used to acquire real-time temperature and humidity data inside and outside the high-voltage switchgear, and generate multi-source meteorological datasets by combining the forecast data from the meteorological station. The meteorological data prediction module preprocesses and predicts the multi-source meteorological dataset based on a time series analysis model, and outputs temperature-time curves and humidity-time curves for future time periods. The temperature and humidity sensing module includes multiple temperature and humidity sensors distributed in the rear, middle and front compartments of the high-voltage switchgear, which are used to collect temperature and humidity data of each zone in real time and transmit them to the intelligent control module. The climate compensation curve generation module dynamically generates a temperature-water vapor saturation climate compensation curve based on the temperature-time curve and humidity-time curve, combined with the dew point temperature-time relationship and the saturation humidity-time relationship. The drive control module receives the set threshold of the climate compensation curve and dynamically adjusts the start-up, shutdown and power output of the exhaust fan and heater through a PID algorithm. The air circulation optimization module constructs a forced convection path through the layout of exhaust fans at the bottom of the high-voltage switchgear rear compartment, top exhaust vents, and distributed heaters, achieving uniform distribution of dry air.

2. The apparatus according to claim 1, characterized in that, The meteorological data acquisition module includes: Temperature, humidity and barometric pressure sensors collect real-time data in 5-minute intervals. The data preprocessing unit amplifies, filters, and performs analog-to-digital conversion on the acquired analog signals to generate standardized digital signals. The meteorological data fusion unit performs time alignment and spatial interpolation fusion of real-time data and meteorological station forecast data.

3. The apparatus according to claim 1, characterized in that, The meteorological data prediction module uses the ARIMA model to predict meteorological data, including: The outlier removal unit removes noise points from the data using the 3σ criterion. The standardized processing unit uses the Z-score standardization method to normalize the data; The prediction model training unit builds a time series model based on historical data and updates the model parameters using the sliding window method.

4. The apparatus according to claim 1, characterized in that, The layout of the temperature and humidity sensing module includes: Two temperature and humidity sensors are installed at the bottom of the rear compartment, and one temperature and humidity sensor is installed at the top of each of the middle and front compartments; Sensor data is transmitted to the intelligent control module via RS-485 bus, and CRC check is used to ensure data integrity.

5. The apparatus according to claim 1, characterized in that, The PID algorithm of the drive control module includes: The input error calculation unit generates an error signal based on the difference between the real-time temperature and humidity and the threshold of the climate compensation curve; The proportional-integral-derivative control unit adjusts the proportional coefficient. Integral Time and differential time Dynamically optimize control response; The output limiting unit limits the heater power and exhaust fan speed to prevent overload. The PID control output formula is as follows: In the formula, This is a real-time error signal. To control the output.

6. The apparatus according to claim 1, characterized in that, The climate compensation curve generation module generates the curve through the following steps: Establish a mapping relationship between dew point temperature and saturated humidity based on the enthalpy-humidity diagram of moist air; By combining the temperature-time curve and the humidity-time curve, the critical value of water vapor saturation at each moment in the future time period is calculated. Generate piecewise linear compensation curves and discretize the curves into a time-threshold lookup table; The critical value of water vapor saturation is calculated using the following formula: In the formula, This is the critical value for water vapor saturation. The saturated vapor pressure at the current temperature. This is the saturated water vapor pressure at the dew point temperature.

7. The apparatus according to claim 1, characterized in that, The forced convection path design of the air circulation optimization module includes: Two axial flow exhaust fans are installed at the bottom of the rear compartment, and anti-backflow exhaust vents are opened at the top; A centrifugal exhaust fan is installed on the top of both the middle and front compartments, forming a series airflow with the exhaust fan in the rear compartment; The heater uses PTC ceramic heating elements, which are distributed on the side wall of the rear compartment and the top of the front compartment, and improves drying efficiency through a combination of thermal radiation and convection.

8. The apparatus according to claim 3, characterized in that, The parameter optimization methods for the ARIMA model include: The model order (p, d, q) is determined by the autocorrelation function ACF and the partial autocorrelation function PACF. The optimal combination is found in the preset parameter space using the grid search method, and the model fit is evaluated by the AIC criterion.

9. The apparatus according to claim 1, characterized in that, The device further includes: The data storage module is used to cache historical meteorological data and control command logs; The fault diagnosis unit identifies abnormalities such as exhaust fan blockage or heater failure by comparing sensor data with equipment operating status.

10. The apparatus according to claim 7, characterized in that, The speed control strategy for the exhaust fan includes: Based on the pressure sensor data inside the cabinet, a fuzzy logic algorithm is used to dynamically adjust the exhaust fan speed; When the pressure inside the cabinet is higher than the set threshold, the high-speed mode is activated; when the pressure is lower than the threshold, the low-speed energy-saving mode is switched. The output speed adjustment amount of the fuzzy logic is calculated using the following formula: In the formula, This is the amount of adjustment for the exhaust fan speed. For the first The activation degree of a fuzzy rule. For the first The control quantity of a fuzzy rule.

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