Transformer air cooling control system dual-power-supply automatic switching loop and control method

Abstract

The invention discloses a transformer air cooling control system dual-power-supply automatic switching loop and a control method, and relates to the technical field of power equipment control. The method comprises the following steps: monitoring voltage and frequency parameters of main and standby power supplies in real time and calculating quality indexes thereof; meanwhile, on the basis of the transformer winding temperature, the environment temperature and the change rate of the transformer winding temperature and the environment temperature, the future trend is predicted through an ARIMA time sequence model, and therefore the cooling load requirement is dynamically evaluated; and finally, judging and executing switching by integrating the power supply quality index, the cooling load demand and the change trend thereof through the integrated decision logic and integrating the power supply quality index and the cooling load demand. A corresponding loop comprises a power supply monitoring module, a power supply quality calculation module, a load demand acquisition module, a switching judgment module and a switching control module. According to the invention, by introducing a self-adaptive threshold adjustment mechanism based on the cooling load, the problem that a traditional fixed threshold switching method cannot adapt to the dynamic working condition of the transformer is solved, and more accurate, reliable and impact-free dual-power automatic switching is realized.

Description

Technical Field

[0001] This invention relates to the field of power equipment control technology, and more specifically, to a dual-power automatic switching circuit and control method for a transformer air-cooled control system. Background Technology

[0002] As a critical piece of equipment in the power system, the stable operation of transformers directly affects the reliability and security of the power grid. The air-cooling control system is an important auxiliary system for ensuring the normal operating temperature of the transformer, while the automatic transfer switch (ATS) is the core guarantee for ensuring continuous power supply from the air-cooling system under any circumstances. During power system operation, main power source failure or quality fluctuations are common risks. Failure to switch to backup power in a timely and reliable manner will lead to the failure of the air-cooling system, resulting in transformer overheating and damage, causing significant economic losses. Therefore, developing an intelligent and reliable automatic transfer switch system has extremely important engineering application value.

[0003] Currently, existing dual-power switching technologies in transformer air-cooling control systems suffer from two main shortcomings: First, there are switching schemes based on fixed thresholds. These schemes only monitor power supply voltage and frequency parameters and use fixed thresholds for judgment. The criteria are singular, ignoring the actual operating conditions of the transformer. When the transformer load is light and the heat dissipation demand is low, normal fluctuations in power supply parameters may trigger unnecessary switching, exacerbating equipment wear. Conversely, when the load is heavy and the temperature rises requiring forced cooling, the fixed switching delay may not meet the extreme requirements for power supply reliability. Second, there are switching control schemes relying on pure hardware logic. These schemes build judgment logic based on analog circuits and relays. While this is low-cost, it cannot integrate complex intelligent algorithms and lacks the ability to perceive power quality trends and dynamic changes in cooling load. It cannot achieve preventative switching and is difficult to effectively suppress the current surge during switching, affecting system lifespan. Existing technologies (CN119049836A, CN116107256A) suffer from these problems, generally treating "power quality monitoring" and "cooling system control" as two independent processes, lacking a mechanism for collaborative analysis and intelligent decision-making between the two. This leads to a lack of diversity in switching strategies: either they become risky due to slow response or they become too sensitive, resulting in frequent switching.

[0004] Therefore, a dual-power automatic switching loop and control method for transformer air-cooling control system is proposed, which can deeply integrate the power supply status and transformer thermal status to achieve a more accurate, more adaptive, faster and shock-free dual-power automatic switching method and loop, thereby improving the operational reliability and intelligence of the transformer air-cooling system. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a dual-power automatic switching circuit and control method for a transformer air-cooled control system to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for automatic switching control of dual power supplies in a transformer air-cooled control system, comprising the following steps: S1. Monitor the power parameters of the main power supply and the backup power supply in real time, wherein the power parameters include at least voltage and frequency; S2. Based on the monitored power parameters, calculate the power quality indicators of the main power supply and the backup power supply. S3. Obtain the current cooling load requirement of the transformer air-cooling system, wherein the cooling load requirement is dynamically evaluated based on the transformer operating status parameters; S4. Based on the power quality indicators and the cooling load requirements, determine whether power switching is required through integrated decision logic, wherein the integrated decision logic simultaneously considers the real-time comparison of power quality indicators and the dynamic changing trend of cooling load requirements. S5. When it is determined that a switch is needed, the control switching device will switch the power supply of the air-cooled system from the current power supply to the target power supply.

[0007] Preferably, in step S2, the power quality indicators include voltage deviation rate and frequency deviation rate, wherein the voltage deviation rate is the percentage difference between the measured voltage value and the rated value, and the frequency deviation rate is the percentage difference between the measured frequency value and the rated value. Furthermore, the calculation of the power quality indicators also involves a comprehensive evaluation of the voltage and frequency fluctuation range, which is within ±5%.

[0008] Preferably, in step S3, the cooling load demand is calculated based on the transformer winding temperature, ambient temperature, and temperature change rate, wherein the temperature change rate is used to deduce the future trend of cooling load demand, and the calculation process also includes reference to historical temperature data to enhance prediction accuracy.

[0009] Preferably, the temperature change rate is calculated based on linear regression analysis using a sliding time window, the window containing 30 consecutive temperature sampling points; and / or, the prediction of future temperatures uses an ARIMA time series model, which is trained using historical temperature data from the past 24 hours, with a prediction step size of 10 minutes.

[0010] Preferably, in step S4, the integrated decision logic includes comparing the power quality indicators of the main power supply and the backup power supply with an adaptive threshold, wherein the adaptive threshold is dynamically adjusted according to the urgency of the cooling load demand, and the higher the cooling load demand, the more stringent the adaptive threshold setting; the dynamic adjustment of the adaptive threshold specifically involves dividing the cooling load demand into three levels: low, medium and high, and corresponding to different voltage deviation rate thresholds.

[0011] Preferably, the low, medium, and high cooling load demand levels correspond to the normalized load demand value ranges [0,40), [40,75), and [75,100], respectively; the voltage deviation rate thresholds corresponding to the low level are ±8%, the medium level is ±5%, and the high level is ±3%.

[0012] Preferably, before step S5, a step of performing a power synchronization check is included, which ensures synchronization by comparing the voltage phase and frequency consistency between the target power supply and the current power supply, and initiates the switching operation only when the synchronization conditions are met, wherein the synchronization conditions include a voltage phase difference within ±5 degrees and a frequency difference within ±0.2Hz.

[0013] An automatic dual-power switching circuit for a transformer air-cooled control system, used to implement the above method, includes: A power monitoring module is used to monitor the power parameters of the main power supply and the backup power supply in real time. The power parameters include at least voltage and frequency. The power quality calculation module is used to calculate the power quality indicators of the main power supply and the backup power supply based on the monitored power parameters. The load demand acquisition module is used to acquire the current cooling load demand of the transformer air-cooled system, wherein the cooling load demand is dynamically evaluated based on the transformer operating status parameters. The switching judgment module is used to determine whether a power switch is needed based on the power quality indicators and the cooling load requirements through integrated decision logic, wherein the integrated decision logic simultaneously considers the real-time comparison of power quality indicators and the dynamic changing trend of cooling load requirements. The switching control module is used to control the switching device to switch the power supply of the air-cooled system from the current power supply to the target power supply when it is determined that a switching is required.

[0014] Preferably, the power monitoring module is configured to continuously sample the voltage and frequency data of the main power supply and the backup power supply, and to use digital filtering to eliminate interference, wherein the digital filtering includes at least one of moving average filtering or low-pass filtering, and the sampling frequency is adjustable in the range of 1kHz to 10kHz; the load demand acquisition module is configured to receive and process the transformer winding temperature and ambient temperature input signals, and to calculate the cooling load demand value through an algorithm, which includes temperature change rate analysis and historical data reference, wherein the historical data reference involves statistical learning of temperature patterns over the past 24 hours.

[0015] Preferably, the switching judgment module includes a logic processing unit programmed to perform multi-condition decision-making, wherein the multi-conditions include a relative comparison of power quality indicators, a priority assessment of cooling load demand, and a calculation of switching delay time. The switching delay time is adjustable within the range of 0 to 5 seconds, and the priority assessment is weighted based on the predicted trend of cooling load demand. The switching control module is configured to implement a soft switching function during the switching process, reduce current surges by controlling the operating timing of the switching device, and includes a status feedback mechanism to verify the completion status of the switching operation.

[0016] The technical effects and advantages of this invention are as follows: Compared to existing technologies, this invention achieves more accurate and intelligent switching judgments by combining power quality indicators with cooling load requirements to form an integrated decision logic. This invention achieves precise and adaptive switching judgment, improving system reliability and economy. By integrating decision logic, it dynamically adjusts the switching threshold based on the real-time thermal state of the transformer. Under relaxed operating conditions of light transformer load and low temperature, appropriately relaxing the switching criteria effectively avoids unnecessary switching caused by normal power fluctuations, reduces electrical and mechanical wear on the switching device, and extends equipment life. Under severe operating conditions of heavy transformer load, high temperature, or rapid temperature rise, the switching criteria are automatically tightened, and a zero-delay switching is performed on the temperature rise trend, ensuring timely power supply before overheating risks occur. This condition-based adaptive mechanism fundamentally solves the problem of both false tripping and failure to tripping in traditional fixed threshold schemes, improving economy while ensuring safety.

[0017] This invention incorporates a forward-looking prediction and trend analysis mechanism to achieve preventative switching. It not only analyzes the current state of the power supply and load, but also identifies potential power supply risks and increasing cooling demand in advance through temperature prediction models and rate of change trend analysis. This allows the system to prepare for switching or adjust strategies in advance when power quality begins to deteriorate but has not yet reached a critical value, providing sufficient time margin for the switching operation and effectively avoiding power outages to the cooling system that may result from switching delays.

[0018] Through fully digital hardware and software co-design and precise process control, the speed and safety of the switching process are ensured. A high-precision software phase-locked loop is used for synchronization checks, combined with a multi-stage timing control process, compressing the core switching process to the millisecond level. Power interruption time is far below the allowable limit for air-cooled motors, ensuring continuous cooling. Simultaneously, the soft switching function and precise timing management effectively suppress current surges during switching. Compared to traditional pure hardware solutions, the entire switching process is faster, more stable, and has less impact on the system, improving equipment lifespan and overall system stability. Attached Figure Description

[0019] Figure 1 This is the overall system control flowchart of the present invention.

[0020] Figure 2 This is a detailed diagram of the power quality calculation for the present invention.

[0021] Figure 3 Detailed diagrams are provided to illustrate the cooling load requirements of this invention.

[0022] Figure 4 This is a detailed diagram of the integrated decision-making and switching control of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Example 1 As attached Figures 1 to 4 This paper presents an automatic dual-power switching loop and control method for a transformer air-cooled control system. This system establishes an intelligent decision-making system that comprehensively considers power quality status and transformer cooling requirements. The system adopts a hierarchical distributed architecture, consisting of five main functional modules. Each module achieves high-speed data communication via industrial Ethernet, and a precise clock synchronization protocol ensures that the time synchronization accuracy of each node reaches the microsecond level.

[0025] The system hardware platform uses an industrial-grade programmable logic controller (PLC) as the core processing unit, equipped with dedicated signal conditioning and communication interface modules. The controller selection is based on its processing power, reliability, and environmental adaptability; a high-performance model supporting floating-point and trigonometric function operations is chosen to ensure real-time execution of complex algorithms. The power monitoring module uses isolated voltage and current transformers with a transformation ratio accuracy of 0.2% and a phase error of less than 10 points. The input signal undergoes multi-stage anti-aliasing filtering, including a pre-amplifier RC filter and a post-amplifier active filter. The cutoff frequency is carefully designed according to the sampling theorem to ensure distortion-free signal acquisition. The analog-to-digital converter (ADC) adopts a 16-bit ΣΔ architecture with an integral nonlinearity error of less than ±2 LSB and an effective bit depth of 14.5 bits, guaranteeing measurement accuracy.

[0026] The load demand acquisition module connects to a PT100 platinum resistance temperature sensor. The sensor has an accuracy class of A, a resistance of 100.00Ω at 0℃, and a temperature coefficient of 0.00385 / ℃. A four-wire connection completely eliminates the influence of lead resistance. The measurement circuit is powered by a constant current source set to 1mA, ensuring measurement sensitivity while avoiding self-heating. The signal conditioning circuit includes an instrumentation amplifier and a programmable gain amplifier, achieving a common-mode rejection ratio of 120dB, effectively suppressing electromagnetic interference. The switching control module uses a high-power magnetic latching relay with an electrical life of 100,000 cycles and a mechanical life of 10 million cycles. The contact material is silver tin oxide, providing excellent arc resistance. The control circuit is designed with both mechanical and electrical interlocks. The mechanical interlock uses a lever mechanism to ensure that the two contactors cannot close simultaneously, while the electrical interlock uses auxiliary contacts connected in series in the other control circuit for dual protection.

[0027] Furthermore, the power quality assessment system is based on multi-dimensional parameter analysis. The voltage deviation rate is calculated using a real-time effective value detection algorithm. This algorithm, based on discrete Fourier transform theory, obtains the effective voltage value by averaging the squares of 128 sampling points within one power frequency cycle. The specific calculation formula is as follows: in This represents the number of sampling points per wave. For the first The instantaneous voltage value at each sampling point.

[0028] Frequency measurement employs an improved zero-crossing detection method, which enhances detection accuracy through three-point linear interpolation. The specific algorithm is as follows: First, find two adjacent zero-crossing points. and Then, a sampling point is taken near each of these two points, and the precise zero-crossing time is calculated using linear interpolation. The frequency calculation formula is: Volatility assessment introduces the concept of coefficient of variation. ,in Standard deviation To calculate the mean, a sliding time window is used, with a window width set to 10 power frequency cycles, and the calculation results are updated once per cycle. Value exceeds At that time, it was assumed that there were fluctuations in the power supply.

[0029] Furthermore, the cooling load demand assessment employs multi-sensor data fusion technology. The temperature change rate is calculated based on linear regression analysis using a sliding time window, with an observation window of 30 sampling points. The temperature change trend is fitted using the least squares method. The specific algorithm is as follows: Let the time series be... The corresponding temperature value is Then the rate of change The slope is obtained through least squares fitting. The temperature prediction model is established using an ARIMA time series model. ,in , , The optimal model parameters are determined by the autoregressive order, the differencing order, and the moving average order, respectively, using the AIC criterion.

[0030] The model is trained using historical data from the past 24 hours and predicts steps up to the next 10 minutes.

[0031] Historical data matching employs a similarity retrieval algorithm based on weighted Euclidean distance. The distance calculation formula is as follows: The weighting coefficient , , Determined through principal component analysis.

[0032] Cooling load requirements Quantification is performed using a weighted scoring algorithm (normalized to 0100): in , These are the current and predicted temperatures, respectively. and For operating temperature limits, These are weighting coefficients (e.g., 0.5, 0.2, 0.3). This is the scaling factor.

[0033] Furthermore, the core of the integrated decision logic is to establish a dynamic coupling relationship between power quality and cooling demand. The adaptive threshold adjustment mechanism, based on fuzzy control theory, quantifies the cooling load demand into three fuzzy sets and defines specific quantization intervals: Low demand state: Normalized load demand value The corresponding voltage deviation rate adaptive threshold is set to .

[0034] Medium demand status: Normalized load demand value The corresponding voltage deviation rate adaptive threshold is set to .

[0035] High demand state: Normalized load demand value The corresponding voltage deviation rate adaptive threshold is set to .

[0036] The integrated decision-making process is as follows: 1. Real-time comparison: Continuously compare the quality indicators of the primary and backup power supplies.

[0037] 2. Threshold selection: based on real-time calculations. Select the corresponding adaptive threshold.

[0038] 3. Switchover Trigger: If any indicator of the main power supply exceeds the threshold and the corresponding indicator of the backup power supply is better, a switchover preparation command will be triggered.

[0039] 4. Trend-weighted: If the rate of temperature change Perform the switch immediately; if If so, an adjustable delay of 15 seconds is introduced for re-verification.

[0040] The trend prediction module incorporates an advance correction mechanism. When the temperature change rate is detected to exceed a set value, the switching conditions are tightened in advance, and the correction factor is adjusted accordingly. ,in This is the sensitivity coefficient. This represents the rate of temperature change.

[0041] Furthermore, the power synchronization check employs fully digital phase-locked loop (PLL) technology. A synchronization detection algorithm based on a software PLL is designed, and the digital phase detector uses a multiplier structure to output a phase error signal. .

[0042] The loop filter uses a proportional-integral (PI) structure, and its transfer function is: The proportionality coefficient Integral coefficient The digital voltage-controlled oscillator (VCO) employs an accumulator structure, with its output frequency proportional to the input control voltage. Synchronization condition determination utilizes a multi-cycle verification mechanism, requiring the phase difference to remain constant within three consecutive power frequency cycles. Within the range of degrees, the frequency difference does not exceed Hz, and the voltage amplitude difference is less than .

[0043] Furthermore, the signal acquisition system employs advanced anti-interference processing strategies. The analog signal conditioning circuit is designed with a second-order active low-pass filter, using a SallenKey topology, and its transfer function is... ,in rad / s, quality factor .

[0044] Digital signal processing employs a composite filtering algorithm. The median filter window width is set to 5 sampling points, effectively filtering out impulse interference; the moving average filter window width is set to 10 sampling points, and its transfer function is... The sampling timing management adopts a master-slave synchronization mechanism. The master node generates a synchronization pulse signal, and the slave node starts sampling after receiving the synchronization pulse. The synchronization accuracy reaches 100ns.

[0045] Furthermore, intelligent compensation algorithms are employed for temperature data processing. To address the sensor's nonlinear characteristics, a piecewise linearization correction model is established, dividing the temperature measurement range into multiple intervals, and approximating the sensor using a linear function within each interval. ,in The sensor resistance value. and Let be the correction coefficient for the i-th interval. The temperature gradient calculation introduces inverse distance weighted spatial interpolation. Let the coordinates of the measuring point be... The temperature is Then any point Temperature estimate The weight , The distance to the measuring point. It is an exponential parameter.

[0046] Furthermore, a multi-objective optimization method is adopted for switching decision-making mechanisms. A comprehensive evaluation function is established. ,in For power quality indicators, For load demand indicators, Due to the time factor.

[0047] Power quality rating function Load demand scoring function Time scoring function The weighting coefficients are determined using the analytic hierarchy process (AHP), and a judgment matrix is ​​constructed. ,in The weight vector represents the importance of the i-th factor relative to the j-th factor, and is obtained by solving the eigenvalue problem.

[0048] Furthermore, the switchover process control employs precise timing management technology. A seven-stage switchover sequence is designed, with each stage having a strict time window: The first stage disconnects the main power contactor; operating time... ms; The second stage involves waiting for the arc to extinguish, and the waiting time is... ms; The third phase verifies that the main power supply is completely disconnected; verification time... ms; The fourth stage involves checking the backup power supply synchronization conditions, and the check time is specified. ms; The fifth stage involves closing the backup power contactor, with an operating time of [time missing]. ms; Phase 6: Verify the reliable connection of the backup power supply; verification time... ms; The seventh stage involves entering a stable monitoring state, with a monitoring period of... ms.

[0049] Each stage sets corresponding verification conditions. For example, in the second stage, the arc is extinguished by voltage detection, and in the third stage, the main power supply is disconnected by the status of the auxiliary contacts.

[0050] Example 2 Consider a specific application scenario. During the summer peak load period, the main transformer of a 220kV substation experiences an ambient temperature of 35℃ and a transformer load rate of 85%. In this scenario, the various modules of the system work collaboratively to execute a complete monitoring, evaluation, and decision-making process.

[0051] After system startup, the power monitoring module synchronously acquires the voltage and current signals of the main and backup power supplies at a sampling frequency of 2kHz. After analog and digital filtering, the effective value of the main power supply voltage is calculated to be 215V (rated 220V), with a voltage deviation rate of 2.27% and a frequency of 49.8Hz, with a frequency deviation rate of 0.4%. Based on a sliding window of 10 power frequency cycles, the voltage fluctuation variation coefficient is calculated. The value is 1.5%, which is within the allowable range but close to the upper limit alarm value of 2%. The power quality calculation module further analyzes the harmonic content and obtains a total harmonic distortion rate of 3.2% through FFT transformation, of which the 5th harmonic content is 1.8% and the 7th harmonic content is 1.1%.

[0052] The load demand acquisition module obtains temperature data through 12 temperature sensors distributed at different locations on the transformer. These sensors are located at key locations including the upper and lower parts of the high-voltage winding, the upper and lower parts of the low-voltage winding, the core, the top of the oil tank, and the bottom of the oil tank. After data fusion processing, the winding hot spot temperature is determined to be 78℃, the top oil temperature to be 72℃, and the ambient temperature to be 35℃. Temperature change rate calculations show a temperature rise rate of 0.8℃ / min over the past 5 minutes. An ARIMA(2,1,1) prediction model trained based on historical data from the past 24 hours and determined using the AIC criterion indicates that the winding hot spot temperature may reach 82℃ within the next 10 minutes. Historical data matching identified three similar operating conditions, two of which subsequently triggered temperature alarms, with similarities of 87% and 92%, respectively. After comprehensive calculation, the current cooling load demand value is... The value is 85, which falls within the "high demand" range [75, 100].

[0053] Switch the judgment module to start multi-dimensional decision analysis.

[0054] 1. Real-time comparison and threshold selection: based on In high-demand situations, the system automatically selects a strict adaptive threshold: voltage deviation rate. Frequency deviation rate Hz. The main power supply voltage deviation rate (2.27%) did not exceed the standard threshold ( However, it has exceeded the current strict threshold. The lower limit of ).

[0055] 2. Switching Trigger: The main power supply quality indicators exceed its adaptive threshold, and the backup power supply voltage deviation rate is monitored to be 0.9% and the frequency deviation rate is +0.2%, which is significantly better than the main power supply, thus meeting the switching trigger conditions.

[0056] 3. Trend-weighted: The system detects the rate of temperature change. (Upward trend) Based on the integrated decision logic, the switch is executed immediately without introducing any delay.

[0057] Before switching execution, a detailed parameter comparison of the synchronous check module startup is performed. This is achieved through configuration. , The software phase-locked loop (SPLL) was used for tracking, and the backup power supply voltage was found to lead the main power supply voltage by 3.2 degrees, with a frequency of 50.1Hz and an effective voltage of 218V. After monitoring and verification for three consecutive power frequency cycles, all parameters met the synchronization conditions (phase difference). Frequency difference Hz, voltage amplitude difference The synchronization conditions have been confirmed to be met.

[0058] The switching control module then executes the switching operation according to the preset seven-stage timing sequence: exist time( The main power supply trip command is issued within 15.2 ms, and the contactor's operating time is 15.2 ms. ms); exist time( (ms) Enters the arc extinguishing waiting period, and confirms by voltage detection that the arc has extinguished within 4.8ms. ms); exist time( (ms) Confirm that the main power supply is completely disconnected by checking the status of the auxiliary contacts; exist time( (ms) Re-verify the backup power synchronization status, confirming a phase difference of 3.1 degrees and a frequency difference of 0.05Hz, with a check time of 15ms. ms); exist time( The backup power supply closing command is issued within 11.8 ms, and the contactor's operating time is 11.8 ms. ms); exist time( The backup power supply is reliably powered by voltage detection, with a verification time of 30ms. ms); exist time( Finally, it enters a stable monitoring period of 100ms, during which the backup power supply status is checked every 10ms to ensure normal system operation.

[0059] The entire switching process, from the issuance of the trip command to entering the core switching process of stability monitoring, took 76.8 ms. During this period, the power interruption time of the transformer cooling system was controlled within 31.6 ms, which is well within the allowable power outage time range of the air-cooled motor and far superior to traditional switching schemes. Post-switching monitoring showed that the backup power supply quality was good, with the voltage stable at 219V and the frequency maintained at 50.05Hz, and the upward trend of transformer temperature was effectively curbed. The system continued to monitor the transformer temperature changes, and within 30 minutes after the switch, the temperature dropped from 78℃ to 75℃, proving the correctness and timeliness of the integrated decision-making based on dynamically adjusting the threshold according to cooling load demand.

[0060] This system achieves precise management of power switching in transformer air-cooled systems through refined parameter monitoring, intelligent decision-making algorithms, and reliable execution control. Compared to traditional fixed-threshold switching methods, this solution reduces unnecessary switching operations and extends equipment lifespan while ensuring power supply reliability, providing advanced technical support for the safe and stable operation of transformers. Especially under operating conditions with frequent load fluctuations and large ambient temperature variations, the system's adaptive adjustment capabilities demonstrate significant advantages. The system also features comprehensive self-diagnostic functions, enabling real-time monitoring of the operating status of each module, timely detection and reporting of anomalies, ensuring long-term reliable system operation.

[0061] Finally, the following points should be noted: First, in the description of this application, it should be noted that, unless otherwise specified and limited, the terms "installation", "connection", and "linkage" should be interpreted broadly, and can be mechanical or electrical connections, or internal connections between two components, or direct connections. "Up", "down", "left", "right", etc. are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may change. Secondly: The accompanying drawings of the embodiments disclosed in this invention only involve the structures involved in the embodiments disclosed in this invention. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other. In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A dual power automatic switching control method for a transformer air cooling control system, characterized by, The method comprises the following steps: S1, real-time monitoring of power supply parameters of the main power supply and the backup power supply, the power supply parameters at least including voltage and frequency; S2, calculating power supply quality indicators of the main power supply and the backup power supply based on the monitored power supply parameters; S3, obtaining the current cooling load demand of the transformer air cooling system, wherein the cooling load demand is dynamically evaluated based on transformer operating state parameters; S4, judging whether power switching is needed based on the power supply quality indicators and the cooling load demand through integrated decision logic, wherein the integrated decision logic simultaneously considers real-time comparison of the power supply quality indicators and dynamic change trend of the cooling load demand; S5, when it is judged that switching is needed, controlling the switching device to switch the power supply of the air cooling system from the current power supply to the target power supply.

2. The method of claim 1, wherein, In step S2, the power supply quality indicators include voltage deviation rate and frequency deviation rate, wherein the voltage deviation rate is the percentage of the difference between the measured value and the rated value of the voltage, and the frequency deviation rate is the percentage of the difference between the measured value and the rated value of the frequency, and the calculation of the power supply quality indicators also involves comprehensive evaluation of the voltage and frequency fluctuation range, which is within ±5%.

3. The method according to claim 1 or 2, characterized in that, In step S3, the cooling load demand is calculated based on the transformer winding temperature, the ambient temperature and the temperature change rate, wherein the temperature change rate is used to derive the future change trend of the cooling load demand, and the calculation process also includes reference to historical temperature data to enhance prediction accuracy.

4. The method of claim 3, wherein, The temperature change rate is calculated based on linear regression analysis of a sliding time window, and the window contains 30 consecutive temperature sampling points; and / or, the prediction of future temperature adopts an ARIMA time series model, which is trained using historical temperature data of the past 24 hours, and the prediction step is 10 minutes.

5. The method of claim 1, wherein, In step S4, the integrated decision logic includes comparing the power supply quality indicators of the main power supply and the backup power supply with an adaptive threshold value, wherein the adaptive threshold value is dynamically adjusted according to the urgency of the cooling load demand, and the higher the cooling load demand, the stricter the adaptive threshold value is set; the dynamic adjustment of the adaptive threshold value is specifically: dividing the cooling load demand into low, medium and high levels, and respectively corresponding to different voltage deviation rate thresholds.

6. The method of claim 5, wherein, The low, medium and high cooling load demand levels respectively correspond to the normalized load demand value intervals [0, 40), [40, 75), [75, 100]; the voltage deviation rate threshold corresponding to the low level is ±8%, the medium level is ±5%, and the high level is ±3%.

7. The method of claim 1, wherein, Before step S5, there is also a step of performing power synchronization check to ensure synchronization by comparing the voltage phase and frequency consistency of the target power supply and the current power supply, and only when the synchronization condition is met, the switching operation is started, wherein the synchronization condition includes that the voltage phase difference is within ±5 degrees and the frequency difference is within ±0.2 Hz.

8. A dual power automatic switching circuit for a transformer air cooling control system for implementing the method of any one of claims 1-7, characterized in that, It comprises: a power monitoring module for real-time monitoring of power supply parameters of the main power supply and the backup power supply, the power supply parameters at least including voltage and frequency; a power quality calculation module for calculating power supply quality indicators of the main power supply and the backup power supply based on the monitored power supply parameters; The load demand acquisition module is configured to acquire the current cooling load demand of the transformer air-cooling system, wherein the cooling load demand is dynamically evaluated based on the transformer operating state parameters; The switching judgment module is configured to judge whether power switching is needed based on the power quality index and the cooling load demand through integrated decision logic, wherein the integrated decision logic considers both real-time comparison of the power quality index and dynamic change trend of the cooling load demand; The switching control module is configured to control the switching device to switch the power supply of the air-cooling system from the current power supply to the target power supply when it is judged that switching is needed.

9. The dual automatic transfer switching circuit of claim 8, wherein, The power monitoring module is configured to continuously sample the voltage and frequency data of the main power supply and the backup power supply, and adopt digital filtering processing to eliminate interference, wherein the digital filtering processing includes at least one of sliding average filtering or low-pass filtering, and the sampling frequency is adjustable within the range of 1 kHz to 10 kHz; the load demand acquisition module is configured to receive and process the transformer winding temperature and ambient temperature input signals, and calculate the cooling load demand value through an algorithm, wherein the algorithm includes temperature change rate analysis and historical data reference, and the historical data reference involves statistical learning of the temperature pattern within the past 24 hours.

10. The dual automatic transfer switching circuit of claim 8, wherein, The switching judgment module includes a logic processing unit programmed to perform multi-condition decision, wherein the multi-conditions include relative comparison of the power quality index, priority evaluation of the cooling load demand, and calculation of switching delay time, the switching delay time is adjustable within the range of 0 to 5 seconds, and the priority evaluation is weighted based on the predicted trend of the cooling load demand; the switching control module is configured to realize soft switching function during the switching process, reduce current impact by controlling the operation timing of the switching device, and include a state feedback mechanism to verify the completion state of the switching operation.

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