Transformer and heat dissipation control method

Abstract

The invention provides a transformer and a heat dissipation control method, belongs to the technical field of transformers, and particularly relates to an iron core and a PLC. The iron core is sleeved with a low-voltage coil, and the low-voltage coil is sleeved with a high-voltage coil. A micro-channel cooling pipeline is arranged between the low-voltage coil and the high-voltage coil, and a micro piezoelectric pump is arranged on the micro-channel cooling pipeline; an oil tank is arranged outside the high-voltage coil; the PLC is electrically connected with the micro piezoelectric pump and controls the micro piezoelectric pump to operate. Heat dissipation requirements of the transformer under different load conditions can be guaranteed, energy use can be optimized, the service life of equipment is prolonged, and the performance of the transformer is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of transformers, and particularly relates to a transformer and a heat dissipation control method. BACKGROUND

[0002] As a core component in the power system, the performance of the transformer directly affects the reliability and efficiency of the entire power network. Therefore, the technical innovation and optimization around the transformer have always been the research focus of the industry. In particular, in terms of cooling technology, an efficient, energy-saving and intelligent cooling scheme can not only meet the increasingly stringent environmental protection requirements, but also significantly improve the operation safety and economy of the power equipment.

[0003] In the related art, the cooling methods of the transformer mainly include natural oil circulation cooling and forced oil circulation cooling. However, the fixed temperature threshold does not consider the influence of load changes on the heat dissipation demand; when the environmental temperature changes, the fixed threshold is easy to cause insufficient heat dissipation. The existing scheme mostly adopts the full-on full-off or random pump selection strategy, so that the full-pump operation at low temperature leads to energy waste; long-term fixed pump operation leads to overwork of part of the pumps, while other pumps are idle, affecting the stability. SUMMARY

[0004] The application provides a transformer and a heat dissipation control method, which can guarantee the heat dissipation demand of the transformer under different load conditions, optimize energy use, prolong equipment life, and improve the performance of the transformer.

[0005] The transformer comprises a core and a PLC controller. The core is externally sleeved with a low-voltage coil, and the low-voltage coil is externally sleeved with a high-voltage coil. A micro-channel cooling pipeline is arranged between the low-voltage coil and the high-voltage coil, and a micro piezoelectric pump is arranged on the micro-channel cooling pipeline. An oil tank is arranged outside the high-voltage coil. The PLC controller is electrically connected with the micro piezoelectric pump and controls the operation of the micro piezoelectric pump.

[0006] It is further explained that temperature sensors are arranged on the low-voltage coil and the high-voltage coil respectively. The PLC controller is electrically connected with the temperature sensors and respectively acquires temperature information of the low-voltage coil and the high-voltage coil, and the PLC controller controls the operation of the micro piezoelectric pump according to the temperature information.

[0007] According to another embodiment of the application, a heat dissipation control method of a transformer is provided, and the method comprises the following steps: The PLC controller executes a control logic according to the received temperature signal; When the temperature in the low-voltage coil and the high-voltage coil is lower than a preset temperature threshold, the PLC controller controls half of the micro piezoelectric pumps to operate; When the temperature inside the low-voltage coil and the high-voltage coil reaches the preset temperature threshold, the PLC controller controls all micro piezoelectric pumps to operate, and the pump flow rate is 80% of the preset maximum flow rate; When the temperature inside the low-voltage coil and the high-voltage coil exceeds the preset temperature threshold, the PLC controller controls all micro piezoelectric pumps to operate, and the pump flow rate is controlled at the maximum flow rate; The PLC controller displays the working status of all micro piezoelectric pumps and the sensed real-time temperature information in real time.

[0008] It should be further explained that the steps of the PLC controller executing the control logic according to the received temperature signal specifically include: The PLC controller integrates a multi-channel input interface to simultaneously collect temperature information of the low-voltage and high-voltage coils, as well as the current and voltage of the transformer. A weighted average algorithm is used to fuse the collected data to generate a more accurate comprehensive temperature assessment value. Calculate the theoretical temperature rise range of the transformer under the current load based on historical operating data and neural network models; Based on the adjusted thresholds, the control levels are divided according to the preset priority rules; A closed-loop control circuit is constructed by real-time monitoring of the vibration frequency of the micro piezoelectric pump, transformer oil flow rate and outlet temperature feedback signals.

[0009] It should be further explained that the weighted average algorithm is:

[0010] in, is the temperature signal of the i-th sensor, for The weight coefficient is assigned based on the reliability of the sensor; The temperature rise trend is predicted based on the neural network model, and the threshold is output. The neural network model is:

[0011] X is the input feature, which can be load or temperature, and W and b are network parameters.

[0012] It should be further explained that the flow rate error correction formula is:

[0013] Among them, Δv is the flow rate deviation, which is used to adjust the vibration frequency of the pump body :

[0014] η is the correction coefficient; f oldRepresent the pump body vibration frequency in the value before the update.

[0015] Further need to explain is, based on fuzzy control logic, control transformer heat dissipation, specifically including: Real-time acquisition of low-voltage coil and high-voltage coil temperature data; The temperature error e=T actual -T thresholde T actual The current actual temperature value, T threshold The preset temperature threshold value; Error rate:

[0016] Dt represents the infinitesimal increment of time, The corresponding change amount of actual temperature; Temperature error e: If , classified as negative big; If , classified as negative small; Error rate Δe: If , classified as negative small; If , classified as positive big; Definition rule one: if e is negative big and Δe is negative small, trigger low-power mode; Definition rule two: if e is positive big and Δe is positive, trigger emergency mode; Low-power mode is that PLC controller activates 50% of micro piezoelectric pump, and the remaining pump body is on standby; The pump flow rate is set to 50% of the rated flow, and the vibration frequency is adjusted by PWM signal; Emergency mode is that PLC controller activates all micro piezoelectric pumps, and the pump body runs at 100% rated flow.

[0017] Further need to explain is, PLC controller according to the received temperature signal to execute control logic also involves the following ways: Step S1021: after PLC controller receives the original temperature signal from temperature sensor, calculate the temperature difference ΔT of current temperature value and preset temperature threshold value, and calculate the temperature change rate of the latest two sampling periods, ΔT / Δt=(Tactual-T_prev) / (Tactual-t_prev); T_prev is the coil temperature value recorded by PLC controller at the last sampling time; t_prev is the time interval between two sampling; Step S1022: The PLC controller calls the health state database of the micro piezoelectric pump, filters out the available pump with a health degree ≥ 90%, denoted as N_available, and excludes the pump with a health degree < 90% or in a maintenance state; at the same time, the number N_running of the currently running pumps is obtained, and the redundancy R = N_available-N_running is calculated; Step S1023: Based on the temperature state of S1021 and the pump group state of S1022, the target flow rate V_target is calculated: If it is a rapid heating state, the target flow rate V_target = 80% × V_max × (ΔT-2℃) / 10℃, V_max is the maximum flow rate of the pump, and ΔT≤15℃ is effective; If it is a slow heating state, the target flow rate V_target = 80% × V_max × (ΔT / 2℃); V_target is linearly increased to 80% × V_max when ΔT≤2℃; If it is a cooling / stable state, the target flow rate V_target = 80% × V_max × (ΔT / 2℃); V_target is linearly decreased to 50% × V_max when ΔT<0; Step S1024: The PLC controller preferentially starts the pump with the highest health degree according to the target flow rate of S1023 and the redundancy of S1022, and reserves one standby pump if the redundancy R>0.

[0018] It should be further pointed out that step S10231 further includes: The PLC controller calculates the real-time heat load Q_heat of the transformer winding through a heat load estimation model based on the current temperature value Tactual calculated in S1021 and the historical temperature curve: Q_heat=k×(Tactual-T_ambient)×A_coil; Wherein, k is the thermal conductivity coefficient of the winding material, A_coil is the winding surface area, and T_ambient is the oil tank ambient temperature; The PLC controller calls the fluid resistance characteristic database of the micro-channel cooling pipeline, combines the current flow rate reference value V_ref = 80% × V_max, and calculates the total resistance ΔP_total that the pipeline needs to overcome f×(L / D)×(ρV_ref²) / 2+ξ×(ρV_ref²) / 2, wherein L is the pipeline length, D is the pipe diameter, and ρ is the density of the transformer oil, to obtain the minimum pump power P_min required to maintain the flow rate P_min=ΔP_total×V_ref / η_pump, and η_pump is the efficiency of the pump; The PLC controller obtains the actual efficiency curve of each pump at the current rotating speed according to the available pump list N_available screened in S1022, that is, η_pump_i=a×V_i²+b×V_i+c, wherein V_i is the real-time flow rate of pump i, a, b, and c are pump characteristic coefficients, selects the pump with the highest efficiency as the main pump, and records the pump as P_main, and the efficiency η_main is the maximum value in the current available pump; The PLC controller corrects the target flow rate in combination with the heat load Q_heat, the minimum pump power P_min, and the main pump efficiency η_main: if Q_heat>P_min / η_main, that is, the current flow rate cannot meet the heat dissipation requirement, the target flow rate is increased to V_target=V_ref×(Q_heat×η_main / P_min).

[0019] It should be further explained that step S1024 specifically includes: The PLC controller generates a pump group priority sorting rule based on the redundancy R of S1022 and the temperature state of S1021: if R>0, the priority is determined by the health degree ×(1+running time weight coefficient); If R≤0, the priority is determined by the health degree ×(1+current temperature change rate weight coefficient); The PLC controller monitors the pipeline pressure P_current in real time through the pressure sensor, and calculates the pressure deviation ΔP=P_current-P_rated in combination with the current flow rate V_current and the pipeline resistance characteristic curve. If |ΔP|>5%×P_rated, the exponential smoothing method is used to adjust the running frequency f_new of the main running pump.

[0020] From the above technical solutions, the present application has the following advantages: The oil circulation heat dissipation mode controlled by the transformer and heat dissipation control method can dissipate the heat generated by the coil more quickly, improves the heat dissipation efficiency, reduces the winding hot spot temperature, effectively solves the problem of low heat dissipation efficiency in the existing structure of the new energy box-type transformer. Due to the improvement of the heat dissipation efficiency, the transformer can better maintain the temperature of the coil within a reasonable range during operation, thereby enhancing the overload capacity of the transformer, allowing it to withstand greater loads in a short period of time, and improving the operation stability and reliability of the transformer.

[0021] The PLC controller can adjust the number and flow rate of the micro piezoelectric pumps according to the temperature change, realizing intelligent control of the transformer heat dissipation process. It can be adjusted in real time according to the actual operation condition, avoiding energy waste caused by excessive heat dissipation, and also ensuring the heat dissipation requirement of the transformer under different load conditions.

[0022] The PLC controller can display the working state of all pump bodies and the sensed real-time temperature in real time, so as to facilitate the operator to monitor and manage the running state of the transformer in real time, and discover and handle the possible heat dissipation problems in time. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the present application, the drawings required to be used in the description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0024] Figure 1 is a schematic diagram of a transformer; Figure 2 is a flow chart of a heat dissipation control method of a transformer. DETAILED DESCRIPTION

[0025] The transformer and the heat dissipation control method involved in the present application will be described in detail below. For the purpose of illustration but not for the purpose of limitation, specific details such as specific system structures, techniques, etc. are presented in order to thoroughly understand the embodiments of the present application. However, it should be clear to those skilled in the art that the present application can also be implemented in other embodiments without these specific details.

[0026] It should be understood that when used in the specification of the present application, the term includes indicates the existence of the described features, whole, steps, operations, elements and / or components, but does not exclude the existence or addition of one or more other features, whole, steps, operations, elements, components and / or their sets. The terms include, contain, have and their variants mean to include but not limited to, unless otherwise specifically emphasized.

[0027] It should be understood that one or more referred to by the present application refers to one, two or more than two, and the plurality referred to by the present application refers to two or more than two. In the description of the present application, unless otherwise specified, / means or means, such as A / B can represent A or B. And / or in this paper is only a description of the association between the associated objects, which means that there can be three kinds of relationships, such as A and / or B, which can represent three cases of A alone, A and B together, and B alone.

[0028] The terms "one embodiment," "an embodiment," "some embodiments," "one some embodiments," "another embodiment," "some other embodiments," "one various embodiments," "some of the embodiments," "one implementations," "some implementations," "one or more embodiments" used in the specification and in the claims, indicate that the alternative is included in at least one embodiment. In other words, these terms do not necessarily refer to the same embodiment, although they can. Like terms in different places in the specification, or like terms of the same embodiment, do not necessarily have the same meaning because the terms could be used with different embodiments, or in the same or different embodiments, with the same or different meanings. Terms in the examples that are the same or similar are not necessarily used in the same way. For example, a term used in one embodiment, or in a different embodiment, or in the same embodiment, can have a different meaning as compared to another use of the term in a different embodiment, or a same embodiment.

[0029] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the present application.

[0030] Please refer to Figure 1 The schematic diagram of a transformer in a specific embodiment is shown, which comprises: a core 1 and a PLC controller; a low-voltage coil 2 is sleeved outside the core 1, and a high-voltage coil 3 is sleeved outside the low-voltage coil 2; a micro-channel cooling pipeline 4 is arranged between the low-voltage coil 2 and the high-voltage coil 3, and a micro piezoelectric pump 5 is arranged on the micro-channel cooling pipeline 4; an oil tank 6 is arranged outside the high-voltage coil 3; the PLC controller is electrically connected with the micro piezoelectric pump 5 to control the operation of the micro piezoelectric pump 5. Temperature sensors are arranged on the low-voltage coil 2 and the high-voltage coil 3 respectively; the PLC controller acquires the temperature information of the low-voltage coil 2 and the high-voltage coil 3 respectively by being electrically connected with the temperature sensors, and controls the operation of the micro piezoelectric pump 5 according to the temperature information.

[0031] In some embodiments, when an alternating current passes through the low-voltage coil, an alternating magnetic flux is generated in the core 1, which forms a closed loop inside the core and passes through the low-voltage coil and the high-voltage coil to generate an induced electromotive force in the high-voltage coil. If the high-voltage coil is connected with a load, the load can be output with electric energy to realize the transmission and conversion of electric energy.

[0032] During the operation of the transformer, heat is generated in the low-voltage coil 2 and the high-voltage coil 3. The heat is transferred to the transformer oil in the micro-channel cooling pipeline 4, and the micro piezoelectric pump 5 extrudes the transformer oil through the vibrating membrane to make the oil flow at a high speed in the micro-channel cooling pipeline to take away the heat, thereby reducing the temperature of the coils. The PLC controller controls the number and flow rate of the operation of the micro piezoelectric pump according to the coil temperature sensed by the temperature sensor in the micro piezoelectric pump to realize effective control of the heat dissipation of the transformer.

[0033] The embodiment can control the micro piezoelectric pump 5 to make the transformer oil form directional high-speed flow in the micro-channel cooling pipeline 4, so that the oil can continuously absorb the heat generated by the coil in the circulation process and take it away from the coil area, thereby realizing efficient heat dissipation.

[0034] The micro-channel cooling pipeline 4 is distributed between the low-voltage coil 2 and the high-voltage coil 3, increases the contact area of the transformer oil and the coil, and enables the heat to be transmitted to the oil more quickly, and then taken away by the oil. The design of the cooling pipeline can better guide the flow direction of the oil and improve the heat dissipation efficiency.

[0035] The following is an embodiment of the transformer heat dissipation control method provided by the embodiment of the present disclosure. The method belongs to the same inventive concept as the above-mentioned embodiments of the transformer. Details not described in the embodiment of the transformer heat dissipation control method can be referred to the above-mentioned embodiments of the transformer. As shown in the following table, the method comprises: Figure 2 Step S101: The PLC controller executes the control logic according to the received temperature signal.

[0036] The temperature sensor of the embodiment collects the temperature data of the low-voltage coil and the high-voltage coil at a fixed time interval, converts it into an electrical signal, and transmits it to the PLC controller through the secondary line. The PLC controller first performs filtering processing on the temperature signal to remove abnormal fluctuation values generated by electromagnetic interference, component noise, etc. during signal transmission, and then executes the preset control logic program.

[0037] Step S102: When the temperature in the low-voltage coil and the high-voltage coil is lower than the preset temperature threshold, the PLC controller controls half of the micro piezoelectric pumps to operate.

[0038] When the temperature in the low-voltage coil and the high-voltage coil reaches the preset temperature threshold, the PLC controller controls all the micro piezoelectric pumps to operate, and the pump body flow rate is 80% of the preset maximum flow rate.

[0039] When the temperature in the low-voltage coil and the high-voltage coil exceeds the preset temperature threshold, the PLC controller controls all the micro piezoelectric pumps to operate, and the pump body flow rate is controlled at the maximum flow rate, so that the vibrating membrane extrudes the transformer oil to flow in the micro-channel cooling pipeline at a high speed, and takes away the heat in the transformer winding.

[0040] ​In this embodiment, the preset temperature threshold is stored in the PLC controller program. When the temperature value corresponding to the processed temperature signal continuously falls below the preset temperature threshold, the PLC controller selects the interval-distributed pumps in the micro piezoelectric pump group according to the preset grouping rule, such as grouping by pipeline area, to ensure uniform heat dissipation, selects 50% of the total number of micro piezoelectric pumps, and sends a start instruction to the selected pumps to control the micro piezoelectric pumps to work at a rated voltage and a fixed initial flow rate to drive the transformer oil to flow and dissipate heat in the corresponding micro-channel cooling pipeline.

[0041] Here, only half of the pumps are started, reducing the number of devices in operation and reducing the overall power consumption of the transformer, adapting to the light heat dissipation demand when the temperature is relatively low.

[0042] When the temperature in the low-voltage coil and the high-voltage coil reaches the preset temperature threshold, the PLC controller controls all micro piezoelectric pumps to operate, and the flow rate of the pump body is 80% of the preset maximum flow rate.

[0043] When the temperature value corresponding to the temperature signal continuously falls within the preset threshold interval, the PLC controller sends a start instruction to all micro piezoelectric pumps, and simultaneously adjusts the PWM pulse width of the pumps to accurately control the flow rate of the pump body to be 80% of the preset maximum flow rate. During this process, the PLC monitors the current and pressure signals of the pumps in real time to ensure that the flow rate is stable at the set proportion, so that the transformer oil flows in the micro-channel cooling pipeline at a flow rate suitable for the medium-temperature scenario, and the heat dissipation is strengthened.

[0044] In this way, the full-pump start is triggered by the temperature condition, the power input of the pump is adjusted by PWM, and the oil flow rate is controlled. Combined with feedback monitoring, a closed-loop control is formed, which greatly improves the oil flow and heat dissipation efficiency, effectively meets the heat dissipation demand in the temperature rising stage, and suppresses the further rapid rise of the winding temperature.

[0045] When the temperature in the low-voltage coil and the high-voltage coil exceeds the preset temperature threshold, the PLC controller controls all micro piezoelectric pumps to operate, and the flow rate of the pump body is controlled at the maximum flow rate to make the vibrating membrane extrude the transformer oil in the micro-channel cooling pipeline to flow at a high speed in a certain direction, thereby taking away the heat in the transformer winding.

[0046] In this embodiment, if the temperature value analyzed by the temperature signal continuously exceeds the preset threshold, the PLC controller immediately triggers the full-pump full-load operation logic to output the maximum driving signal to the micro piezoelectric pump, so that the flow rate of the pump body reaches the maximum design flow rate. At this time, the vibrating membrane of the micro piezoelectric pump extrudes the transformer oil at the maximum frequency and amplitude, forcing the oil to flow at a high speed in the micro-channel cooling pipeline in a certain direction, thereby quickly taking away a large amount of heat generated by the winding.

[0047] The full pump maximum flow rate operation makes the transformer oil flow in the microchannel at the fastest speed and the highest heat dissipation efficiency, which can quickly reduce the winding hot spot temperature in a short time, avoid damage to the insulation material due to high temperature, and cause transformer failure, and improve the overload capacity and reliability of the transformer.

[0048] Step S103: The PLC controller displays the working state of all micro piezoelectric pumps and the sensed real-time temperature information in real time.

[0049] It should be noted that the PLC controller integrates the running state data of each micro piezoelectric pump and the real-time temperature data transmitted by the temperature sensor through the internal data processing module, and sends the data to the human-computer interaction interface. The interface presents in a visual form, and the worker can check the working condition of each pump and the real-time temperature of the winding.

[0050] Further, as a refinement and expansion of the above-mentioned embodiment of the transformer heat dissipation control method, in order to fully describe the specific implementation process in this embodiment, the PLC controller in the transformer heat dissipation control method according to the received temperature signal executes the control logic, which specifically includes: S1011: Collect the temperature information of the low-voltage coil and the high-voltage coil, and also collect the current and voltage of the transformer through the multi-channel input interface integrated by the PLC controller; use a weighted average algorithm to fuse the collected data, eliminate sensor noise interference, and generate a more accurate comprehensive temperature evaluation value.

[0051] The weighted average algorithm is:

[0052] Wherein, is the temperature signal of the i-th sensor, is a weight coefficient of, and the weight is distributed according to the reliability of the sensor.

[0053] S1012: Based on historical operation data and a neural network model, calculate the theoretical temperature rise range of the transformer under the current load.

[0054] Compare the theoretical temperature rise range with the actual temperature signal, and adjust the upper and lower limits of the preset temperature threshold to make the control logic more suitable for the actual thermal load demand of the transformer.

[0055] For example, when the load suddenly increases, the upper limit of the threshold can be temporarily increased by 5°C to avoid false triggering of the emergency mode.

[0056] Based on the neural network model to predict the temperature rise trend, output the threshold, and the neural network model is:

[0057] X is an input feature, which can be load or temperature, and W and b are network parameters.

[0058] S1013: According to the adjusted threshold, the control level is divided by the preset priority rule.

[0059] In low-power mode, the PLC controller only activates half of the micro piezoelectric pumps, reducing energy consumption.

[0060] In standard mode, all pump bodies are running but the flow rate is limited, balancing the heat dissipation efficiency and energy consumption.

[0061] In emergency mode, the pump body runs at full power to ensure rapid cooling. Emergency mode takes precedence over standard mode.

[0062] The PID control algorithm of the PLC controller is:

[0063] The temperature error is e, The proportional, integral, and differential coefficients are used to adjust the pump body vibration frequency.

[0064] According to the fuzzy set of temperature deviation e and deviation rate Δe, a fuzzy rule table of pump body operation mode is generated.

[0065] If e is negative and Δe is negative, select low-power mode.

[0066] If e is positive and Δe is positive, select emergency mode.

[0067] In the control system, negative small and positive large are fuzzy language variables used to describe the fuzzy set of error e or error rate Δe. The system makes decisions based on the fuzzification results of the input values.

[0068] It should be noted that negative large (NB) represents a large negative deviation. Negative small (NS) represents a small negative deviation. Zero (ZO) represents no deviation. Positive small (PS) represents a small positive deviation. Positive large (PB) represents a large positive deviation.

[0069] S1014: By monitoring the vibration frequency of the micro piezoelectric pump, the transformer oil flow rate and the outlet temperature feedback signal in real time, a closed-loop control loop is constructed.

[0070] If the actual flow rate deviates from the target value by more than 5%, the PLC controller automatically corrects the vibration frequency parameters of the pump body, and records the corrected control parameters to optimize subsequent decision-making.

[0071] The flow rate error correction formula is

[0072] Wherein, Δv is the flow rate deviation, used to adjust the pump body vibration frequency :

[0073] η is the correction coefficient, taking 0.1-0.5.

[0074] fold represents the value of the pump body vibration frequency before updating.

[0075] In the operation of the micro piezoelectric pump of the embodiment, the vibration frequency, transformer oil flow rate and outlet temperature are monitored in real time by the sensor, and the monitoring signals are used as feedback input to the PLC controller.

[0076] The PLC controller compares the actual flow rate with the preset target flow rate, and when the deviation exceeds 5%, the vibration frequency correction amount to be adjusted is calculated according to the flow rate error correction formula by substituting the flow rate deviation Δv, the correction coefficient η and the pump body vibration frequency fold before updating, the pump body vibration frequency parameter is corrected, the actual flow rate tends to approach the target value, and the corrected control parameter is recorded for subsequent control decision optimization, forming a closed loop control loop, regulating the oil flow rate and ensuring the heat dissipation effect.

[0077] In some specific embodiments, the transformer cooling is controlled based on fuzzy control logic, specifically including: Step S301: Real-time acquisition of temperature data of low-voltage coil and high-voltage coil.

[0078] Calculate the temperature error, e=T actual −T thresholde T actual is the current actual temperature value, T threshold is the preset temperature threshold value. Error change rate:

[0079] dt represents an infinitesimal increment of time, is the corresponding change amount of the actual temperature.

[0080] Temperature error e: If , it is classified as negative large; If , it is classified as negative small.

[0081] Error change rate Δe: If , it is classified as negative small; If , it is classified as positive large.

[0082] Step S302: Definition rule one: if e is negative large and Δe is negative small, trigger low power mode.

[0083] Definition rule two: if e is positive large and Δe is positive, trigger emergency mode.

[0084] Step S303: Low power mode activates 50% of the micro piezoelectric pumps for the PLC controller, and the remaining pumps are on standby.

[0085] The pump flow rate is set to 50% of the rated flow, and the vibration frequency is adjusted by the PWM signal.

[0086] It is suitable for low load and slow temperature rise conditions to reduce energy consumption.

[0087] Emergency mode activates all micro piezoelectric pumps for the PLC controller, and the pump runs at 100% rated flow. The vibration membrane vibrates at high frequency, driving the transformer oil to flow at high speed in the micro-channel cooling pipeline. It is suitable for sudden load increase and rapid temperature rise conditions to quickly cool down.

[0088] Step S304: Real-time monitoring of the running state of the micro piezoelectric pump and the outlet temperature of the transformer oil. If the actual flow rate deviates from the target value by more than 5%, the PLC controller corrects the PWM duty cycle and adjusts the pump vibration frequency. Record the corrected control parameters.

[0089] For example, the transformer load drops suddenly, and the temperature rises from 80°C to 65°C, .

[0090] The fuzzy matching result is that e is negative small and Δe is negative small, triggering low power mode. The control method is: 50% pump operation, flow rate 50%, energy saving 15%.

[0091] The transformer load increases suddenly, and the temperature rises from 70°C to 85°C Fuzzy matching result: e is positive large and Δe is positive large, triggering emergency mode. Control method: 100% pump operation, flow rate 100%, temperature drops to 72°C within 3 minutes.

[0092] On the basis of the above embodiment, in order to further improve the reliability of the heat dissipation control method provided by the above embodiment, the following is a more specific implementation, in the following embodiment, the PLC controller executes the control logic according to the received temperature signal also involves the following way: Step S1021: After the PLC controller receives the original temperature signal from the temperature sensor, it calculates the temperature difference ΔT between the current temperature value and the preset temperature threshold, and simultaneously calculates the temperature change rate of the last two sampling periods, ΔT / Δt=(Tactual-T_prev) / (Tactual-t_prev).

[0093] T prev is the coil temperature value recorded by the PLC controller at the last sampling time; t prev is the time identifier corresponding to T prev, used to calculate the time interval between two samplings.

[0094] Optionally, the temperature state is marked as fast heating, ΔT / Δt>0 and ΔT≥2℃); slow heating, ΔT / Δt>0 and ΔT<2℃; cooling / stable, ΔT / Δt≤0.

[0095] Step S1022: The PLC controller calls the health state database of the micro piezoelectric pump, filters out the available pump with a health degree ≥90%, and marks it as N available, and excludes the pump with a health degree <90% or in a maintenance state; at the same time, the number N running of the currently running pump is obtained, and the redundancy R=N available-N running is calculated.

[0096] Optionally, the health state database stores the historical vibration frequency, operating current, and fault code of each pump.

[0097] Step S1023: Based on the temperature state of S1021 and the pump group state of S1022, the target flow rate is calculated: If it is in a fast heating state, the target flow rate V target=80%×V max×(ΔT-2℃) / 10℃), V max is the maximum flow rate of the pump, and ΔT≤15℃ is effective; If it is in a slow heating state, the target flow rate V target=80%×V max×(ΔT / 2℃); when ΔT≤2℃, V target linearly increases to 80%×V max; If it is in a cooling / stable state, the target flow rate V target=80%×V max×(ΔT / 2℃); when ΔT<0, V target linearly decreases to 50%×V max.

[0098] Step S1024: The PLC controller preferentially starts the pump with the highest health degree according to the target flow rate of S1023 and the redundancy of S1022, and retains one standby pump if the redundancy R>0; At the same time, the target flow rate instruction is sent to the selected pump, and the pipeline pressure P current is monitored in real time through the pressure sensor of the microchannel cooling pipeline; if P current deviates from the rated pressure (P rated) ±5%, the operating frequency f of the pump is adjusted to f0×(P rated / P current), so as to maintain the pressure stable.

[0099] In an embodiment of the present application, based on step S1023, a possible embodiment will be given below to non-restrictively illustrate the specific implementation scheme. Step S1023 specifically comprises: Step S10231: The PLC controller calculates the real-time heat load Q_heat of the current transformer winding based on the current temperature value Tactual calculated in S1021 and the historical temperature curve through the heat load estimation model: Q_heat = k x (Tactual - T_ambient) x A_coil.

[0100] Wherein, k is the thermal conductivity coefficient of the winding material, A_coil is the winding surface area, and T_ambient is the oil tank ambient temperature.

[0101] Step S10232: The PLC controller calls the fluid resistance characteristic database of the micro-channel cooling pipeline, combines the current flow rate reference value V_ref = 80% x V_max, and calculates the total resistance ΔP_total = f x (L / D) x (pV_ref²) / 2 + ξ x (pV_ref²) / 2 required to be overcome by the pipeline, where L is the pipeline length, D is the pipe diameter, p is the transformer oil density, to obtain the minimum pump power P_min = ΔP_total x V_ref / η_pump required to maintain the flow rate, and η_pump is the efficiency of the pump.

[0102] The fluid resistance characteristic database pre-stores the corresponding resistance coefficient f and local resistance coefficient ξ along the length of the pipeline, the pipe diameter, and the number of bends.

[0103] Step S10233: The PLC controller obtains the actual efficiency curve η_pump_i = a x V_i² + b x V_i + c of each pump at the current speed according to the available pump list N_available screened in S1022, where V_i is the real-time flow rate of pump i, a / b / c is the pump characteristic coefficient, selects the pump with the highest efficiency as the main pump (denoted as P_main), and the efficiency η_main is the maximum value among the current available pumps.

[0104] Step S10234: The PLC controller combines the heat load Q_heat of S10231, the minimum pump power P_min of S10232, and the main pump efficiency η_main of S10233 to correct the target flow rate: if Q_heat > P_min / η_main, i.e., the current flow rate cannot meet the heat dissipation requirement, then the target flow rate is increased to V_target = V_ref x (Q_heat x η_main / P_min).

[0105] Q_heat ≤ P_min / η_main, i.e., the current flow rate is redundant, then the target flow rate is reduced to V_target = V_ref x (0.8 + 0.2 x (R / 2)), R is the redundancy of S1022, R ≤ 2 is effective, and the flow rate is ensured to match the heat dissipation requirement, pump efficiency, and redundancy.

[0106] The embodiment estimates the heat load model, combines real-time temperature and environmental parameters, accurately quantifies the winding heat generation, and then links the pipeline resistance and pump power calculation to correct the flow rate. The oil flow rate is highly matched with the actual heat dissipation demand to ensure stable operation of the transformer. The main pump is selected according to the pump efficiency curve by calling the fluid resistance database, and the high-efficiency pump is preferentially operated. The flow rate is also adjusted in combination with the relationship between the heat load and the power. From pipeline resistance adaptation, pump efficiency utilization to flow rate accurate correction, the energy efficiency potential is fully tapped in all links to reduce the energy consumption of the transformer heat dissipation system.

[0107] In an embodiment of the present application, based on step S1024, a possible embodiment will be given below to specifically and non-limitingly illustrate the specific implementation thereof. Step S1024 specifically comprises: The PLC controller generates a pump group priority sorting rule based on the redundancy R of S1022 and the temperature state of S1021: if R>0, the priority is determined by the health degree x (1+running time weight coefficient); The running time weight coefficient = 1- running time / total design life, to avoid overwork of long-running pumps; If R≤0, indicating insufficient redundancy, the priority is determined by the health degree x (1+current temperature change rate weight coefficient); The temperature change rate weight coefficient = ΔT / Δt x 0.5, to preferentially start the high-health-degree pump when the temperature rises rapidly.

[0108] The PLC controller monitors the pipeline pressure P_current in real time through the pressure sensor, combines the current flow rate V_current and the pipeline resistance characteristic curve, and calculates the pressure deviation ΔP = P_current-P_rated.

[0109] If |ΔP|>5% x P_rated, the exponential smoothing method is used to adjust the running frequency f_new of the main running pump.

[0110] f_new = f_old + α x (P_rated-P_current) / Δt, α = 0.1 is the smoothing coefficient, and the pre-starting frequency f_standby_new of the standby pump is updated synchronously; f_standby_new = f_standby + β x (P_rated-P_current) / Δt, β = 0.05, to ensure that the pressure is stable within the range of P_rated±3%.

[0111] The embodiment prioritizes according to redundancy and temperature state rules, prevents excessive use of pumps when redundant, and quickly responds to temperature rise when redundant. Let the pump group start and run in line with the heat dissipation working condition, avoid invalid loss or response lag, and improve the timeliness of heat dissipation. Real-time monitoring of pipeline pressure, accurate suppression of pressure fluctuations, stable flow of oil in microchannels, continuous and reliable heat dissipation effect, and avoiding the impact of abnormal pressure on heat removal. Through the running time weight coefficient, health degree and other factors, the healthy and low-loss pump is preferentially selected to reduce the overuse of equipment. Whether it is regular heat dissipation, load mutation, or pressure fluctuation, the pump group strategy can be automatically adjusted to improve the intelligence and robustness of transformer heat dissipation control.

[0112] It should be understood that the size of the serial number of each step in the above embodiment does not mean the order of execution, and the execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the application.

[0113] Those skilled in the art can appreciate that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been described in the above description. Whether the functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0114] The flowcharts and block diagrams in the drawings illustrate the possible implementation architecture, function and operation of the devices, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram can represent a module, program segment or part of code containing one or more executable instructions for implementing a specified logic function. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in different order from that noted in the drawings. For example, two blocks indicated in succession can actually be executed substantially in parallel, and they can also be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0115] In several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method can be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and in actual implementation, another division manner can be used, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, and can also be electrical, mechanical or other forms of connection.

[0116] The above description of disclosed embodiments enables a person skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A transformer, characterized in that: include: Iron core (1) and PLC controller; The iron core (1) is provided with a low-voltage coil (2) on the outside, and the low-voltage coil (2) is provided with a high-voltage coil (3) on the outside; A microchannel cooling pipeline (4) is provided between the low-voltage coil (2) and the high-voltage coil (3), and a micro piezoelectric pump (5) is provided on the microchannel cooling pipeline (4); An oil tank (6) is provided outside the high-voltage coil (3); The PLC controller is electrically connected to the micro piezoelectric pump (5) to control the operation of the micro piezoelectric pump (5).

2. The transformer according to claim 1, characterized in that Temperature sensors are respectively provided on the low-voltage coil (2) and the high-voltage coil (3); The PLC controller is electrically connected to the temperature sensor to obtain temperature information of the low-voltage coil (2) and the high-voltage coil (3), respectively. The PLC controller controls the operation of the micro piezoelectric pump (5) based on the temperature information.

3. A heat dissipation control method for a transformer, characterized in that: The method performs heat dissipation control on the transformer according to any one of claims 1 to 2; the method comprises: The PLC controller executes control logic based on the received temperature signal; When the temperature inside the low-voltage coil and the high-voltage coil is lower than the preset temperature threshold, the PLC controller controls half of the micro piezoelectric pumps to operate; When the temperature inside the low-voltage coil and the high-voltage coil reaches the preset temperature threshold, the PLC controller controls all micro piezoelectric pumps to operate, and the pump flow rate is 80% of the preset maximum flow rate; When the temperature inside the low-voltage coil and the high-voltage coil exceeds the preset temperature threshold, the PLC controller controls all micro piezoelectric pumps to operate, and the pump flow rate is controlled at the maximum flow rate; The PLC controller displays the working status of all micro piezoelectric pumps and the sensed real-time temperature information in real time.

4. The heat dissipation control method of a transformer according to claim 3, characterized in that: The steps of the PLC controller executing the control logic according to the received temperature signal specifically include: The PLC controller integrates a multi-channel input interface to simultaneously collect temperature information of the low-voltage and high-voltage coils, as well as the current and voltage of the transformer. A weighted average algorithm is used to fuse the collected data to generate a more accurate comprehensive temperature assessment value. Calculate the theoretical temperature rise range of the transformer under the current load based on historical operating data and neural network models; Based on the adjusted thresholds, the control levels are divided according to the preset priority rules; A closed-loop control circuit is constructed by real-time monitoring of the vibration frequency of the micro piezoelectric pump, transformer oil flow rate and outlet temperature feedback signals.

5. The heat dissipation control method of a transformer according to claim 4, characterized in that: The weighted average algorithm is: in, is the temperature signal of the i-th sensor, for The weight coefficient is assigned based on the reliability of the sensor; The temperature rise trend is predicted based on the neural network model, and the threshold is output. The neural network model is: X is the input feature, W and b are the network parameters.

6. The heat dissipation control method of a transformer according to claim 4, characterized in that: The flow rate error correction formula is: Among them, Δv is the flow rate deviation, which is used to adjust the vibration frequency of the pump body : η is the correction coefficient; f old Represents the value of the pump vibration frequency before updating.

7. The heat dissipation control method of a transformer according to claim 4, characterized in that: Based on fuzzy control logic, the heat dissipation of the transformer is controlled, including: Real-time collection of temperature data of low-voltage coils and high-voltage coils; Calculate the temperature error, e=T actual −T thresholde T actual is the current actual temperature value, T threshold is the preset temperature threshold; Error change rate: dt represents an infinitesimal increment of time, is the corresponding change in actual temperature; Temperature error e: like , classified as negative large; like , classified as negative small; Error change rate Δe: like , classified as negative small; like , classified as positive; Definition rule 1: If e is negative and large, and Δe is negative and small, low power mode is triggered; Definition Rule 2: If e is positive and Δe is positive, trigger the emergency mode; In low power mode, the PLC controller activates 50% of the micro piezoelectric pumps, and the remaining pumps are on standby; The pump flow rate is set to 50% of the rated flow rate, and the vibration frequency is adjusted by the PWM signal; In emergency mode, the PLC controller activates all micro piezoelectric pumps, and the pump bodies run at 100% rated flow.

8. The heat dissipation control method of a transformer according to claim 3, characterized in that: The PLC controller also executes control logic according to the received temperature signal in the following ways: Step S1021: After receiving the original temperature signal from the temperature sensor, the PLC controller calculates the temperature difference ΔT between the current temperature value and the preset temperature threshold, and simultaneously calculates the temperature change rate of the most recent two sampling periods: ΔT / Δt = (Tactual - T_prev) / (Tactual - t_prev); T_prev is the coil temperature value recorded by the PLC controller at the last sampling time; t_prev is the time interval between two samplings; Step S1022: The PLC controller calls the health status database of the micro piezoelectric pumps, selects available pumps with a health level of ≥90%, and records them as N_available. It excludes pumps with a health level of <90% or those under maintenance. It also obtains the number of currently running pumps N_running and calculates the redundancy R = N_available - N_running. Step S1023: Calculate the target flow rate based on the temperature status in S1021 and the pump group status in S1022: If the temperature is rising rapidly, the target flow rate V_target = 80% × V_max × (1 + (ΔT - 2°C) / 10°C), where V_max is the maximum flow rate of the pump and is valid when ΔT ≤ 15°C. If the temperature is rising slowly, the target flow rate V_target = 80% × V_max × (ΔT / 2°C); when ΔT ≤ 2°C, V_target increases linearly to 80% × V_max; If the temperature is falling / stable, the target flow rate V_target = 80% × V_max × (ΔT / 2°C); when ΔT < 0, V_target decreases linearly to 50% × V_max; Step S1024: The PLC controller prioritizes the operation of the pump with the highest health based on the target flow rate in S1023 and the redundancy in S1022. If the redundancy R>0, one spare pump is retained.

9. The heat dissipation control method of a transformer according to claim 8, characterized in that: Step S10231 also includes: The PLC controller calculates the real-time heat load Q_heat of the current transformer winding using the heat load estimation model based on the current temperature value Tactual calculated in S1021 and the historical temperature curve: Q_heat=k×(Tactual-T_ambient)×A_coil; Where k is the thermal conductivity of the winding material, A_coil is the surface area of ​​the winding, and T_ambient is the ambient temperature of the fuel tank; The PLC controller calls the fluid resistance characteristic database of the microchannel cooling pipeline and, combined with the current flow rate reference value V_ref = 80% × V_max, calculates the total resistance that the pipeline needs to overcome ΔP_total = f × (L / D) × (ρV_ref²) / 2 + ξ × (ρV_ref²) / 2, where L is the pipeline length, D is the pipe diameter, and ρ is the transformer oil density. The minimum pump power required to maintain this flow rate is P_min = ΔP_total × V_ref / η_pump, where η_pump is the pump efficiency. The PLC controller obtains the actual efficiency curve η_pump_i = a × V_i² + b × V_i + c for each pump at the current speed based on the available pump list N_available selected in S1022, where V_i is the real-time flow rate of pump i, and a, b, and c are the pump characteristic coefficients. The pump with the highest efficiency is selected as the main pump, denoted as P_main, and the efficiency η_main is the maximum value among the currently available pumps. The PLC controller combines the heat load Q_heat, the minimum pump power P_min and the main pump efficiency η_main to correct the target flow rate: if Q_heat>P_min / η_main, that is, the current flow rate cannot meet the heat dissipation requirements, then the target flow rate is increased to V_target=V_ref×(Q_heat×η_main / P_min).

10. The heat dissipation control method of a transformer according to claim 8, characterized in that: Step S1024 specifically includes: The PLC controller generates a pump group priority ranking rule based on the redundancy R of S1022 and the temperature status of S1021: if R>0, the priority is determined by health × (1 + running time weight coefficient); If R≤0, the priority is determined by health × (1 + current temperature change rate weight coefficient); The PLC controller monitors the pipeline pressure P_current in real time through the pressure sensor, and calculates the pressure deviation ΔP=P_current-P_rated based on the current flow rate V_current and the pipeline resistance characteristic curve; If |ΔP|>5%×P_rated, the exponential smoothing method is used to adjust the operating frequency f_new of the main operating pump.

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